paperID stringlengths 36 36 | pwc_id stringlengths 8 47 | arxiv_id stringlengths 6 16 ⌀ | nips_id float64 | url_abs stringlengths 18 329 | url_pdf stringlengths 18 742 | title stringlengths 8 325 | abstract stringlengths 1 7.27k ⌀ | authors stringlengths 2 7.06k | published stringlengths 10 10 ⌀ | conference stringlengths 12 47 ⌀ | conference_url_abs stringlengths 16 198 ⌀ | conference_url_pdf stringlengths 27 199 ⌀ | proceeding stringlengths 6 47 ⌀ | taskID stringlengths 7 1.44k | areaID stringclasses 688 values | embedding stringlengths 9.26k 12.5k | umap_embedding stringlengths 29 44 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
10cf09ee-b8a7-41ca-82e4-d0466e7c0536 | extracting-events-with-informal-temporal | null | null | https://aclanthology.org/P13-2145 | https://aclanthology.org/P13-2145.pdf | Extracting Events with Informal Temporal References in Personal Histories in Online Communities | null | ["Carolyn Penstein Ros{\\'e}", 'Hyeju Jang', 'Guang Xiang', 'Zeyu Zheng', 'Miaomiao Wen'] | 2013-08-01 | null | null | null | acl-2013-8 | ['temporal-information-extraction'] | ['natural-language-processing'] | [-8.63703638e-02 1.71006292e-01 -6.22772932e-01 -4.08054382e-01
-8.41685571e-03 -9.08429027e-01 6.55310392e-01 -6.53472245e-01
-2.85945535e-01 1.06888819e+00 -4.63127941e-02 -1.01159286e+00
-3.91567826e-01 -9.63214397e-01 -4.95059669e-01 -6.31337762e-01
-9.79754329e-01 7.25764990e-01 3.30370307e-01 -6.93831444e-01
7.03166842e-01 7.88774848e-01 -1.68942046e+00 7.18545914e-01
7.04417467e-01 8.52217197e-01 2.49141872e-01 1.14950800e+00
-1.95044339e-01 1.55633950e+00 -7.48382092e-01 -5.46825826e-01
3.13719302e-01 -1.23176083e-01 -7.22945035e-01 -1.01074085e-01
9.28529128e-02 -8.59008506e-02 -2.09758401e-01 9.22211111e-01
5.37373662e-01 4.49454933e-02 1.08379531e+00 -1.42548037e+00
-5.91619551e-01 6.10313773e-01 -4.01565880e-02 1.21627934e-01
1.03678203e+00 -5.39447069e-01 1.19919395e+00 -1.13026452e+00
7.20913768e-01 1.26888943e+00 8.66221786e-01 5.44149756e-01
-1.22286928e+00 -1.94712028e-01 -3.26822817e-01 -9.51717794e-02
-1.46558487e+00 -3.25250506e-01 4.25783843e-02 -2.08119690e-01
1.66093647e+00 1.26596653e+00 1.20609856e+00 1.01401424e+00
1.26658809e+00 8.34431887e-01 1.04267764e+00 -5.13792276e-01
3.35295945e-01 3.66983831e-01 1.54683650e-01 6.33519173e-01
8.40953708e-01 5.26628852e-01 -7.06372619e-01 -9.13127720e-01
9.33553874e-01 -2.94925272e-01 1.71355158e-01 -5.05680561e-01
-9.05919552e-01 6.91228509e-01 1.78732842e-01 3.83959889e-01
-1.39880210e-01 9.89067405e-02 1.26390755e-01 5.30987144e-01
-2.58292928e-02 6.47037446e-01 -9.11868811e-01 -1.33165747e-01
-8.71728659e-01 5.10332465e-01 1.25398111e+00 1.52653182e+00
1.24482810e-01 2.94908643e-01 -9.34252143e-02 3.17179203e-01
8.92314315e-01 1.01808000e+00 4.28362608e-01 -1.36146402e+00
-6.87414408e-02 1.72361732e-01 5.01781464e-01 -8.52631688e-01
-6.33224547e-01 -9.64177120e-03 -8.93263519e-01 4.49267089e-01
3.49161088e-01 4.57367361e-01 -8.02827001e-01 5.07305264e-01
4.33481112e-02 -2.34125629e-01 4.53833073e-01 5.55570945e-02
4.99930978e-01 3.76208365e-01 -1.34477139e-01 -5.73289394e-01
1.06082785e+00 -1.36716676e+00 -1.35299087e+00 2.33215362e-01
9.05734658e-01 -1.07320261e+00 4.35900748e-01 5.33875942e-01
-1.55548143e+00 -1.37560293e-01 -1.08699942e+00 1.78573877e-01
-7.27255583e-01 -3.14239264e-01 8.57801437e-01 1.43120694e+00
-1.60129595e+00 9.73287821e-01 -4.91727620e-01 6.59165755e-02
1.20568443e-02 8.24621081e-01 -2.64718989e-03 4.62812334e-01
-1.33193445e+00 1.08501506e+00 2.22979754e-01 -1.21242590e-01
-1.65216476e-01 -2.13068098e-01 -8.23704481e-01 -5.63443303e-01
-4.78693932e-01 -5.29636025e-01 1.44139910e+00 -2.59346128e-01
-1.65295815e+00 9.71794367e-01 -1.42069459e-01 -1.97814897e-01
6.14786744e-01 -1.28011424e-02 -8.31891418e-01 2.42498964e-01
-1.89849049e-01 5.76383233e-01 9.28263724e-01 -1.35132408e+00
-7.59897232e-01 -1.67359829e-01 -1.23336017e-01 2.66287565e-01
-1.25510961e-01 1.89734384e-01 2.11616129e-01 -1.12999000e-01
3.27147305e-01 -7.20919967e-01 -2.53068686e-01 -5.32041907e-01
-1.46512717e-01 -7.10518599e-01 7.70373225e-01 -4.51523662e-01
1.83705616e+00 -1.67618537e+00 -2.06720144e-01 3.98590982e-01
3.57815564e-01 -1.24705513e-03 2.40583986e-01 1.08380008e+00
-2.76906848e-01 7.32199550e-01 4.11965609e-01 -1.10722095e-01
2.24991128e-01 4.85861301e-01 -4.16602850e-01 3.05609167e-01
-1.29282743e-01 1.15307164e+00 -1.16605783e+00 -5.23096442e-01
4.11106765e-01 9.42391157e-02 -4.58732933e-01 4.79237735e-01
2.99364805e-01 1.47170946e-01 -3.56553018e-01 1.39399457e+00
1.15709066e+00 -1.31984919e-01 1.45911396e-01 5.30878425e-01
-3.79135728e-01 3.55090618e-01 -6.96863770e-01 1.05554795e+00
7.08333924e-02 5.00173986e-01 1.02364108e-01 -7.94621468e-01
3.33247900e-01 8.61540735e-01 4.37155962e-01 -9.67555881e-01
-2.26398129e-02 6.92409754e-01 1.12803578e-01 -6.07703328e-01
7.58228302e-01 3.94563079e-02 -3.64872098e-01 6.40070081e-01
-2.37588286e-01 -6.59476995e-01 9.64643434e-02 3.08100313e-01
6.22585893e-01 -5.18246442e-02 5.62923312e-01 -1.05613089e+00
7.86340594e-01 -1.82965681e-01 -1.81299388e-01 1.03415680e+00
-3.09923887e-01 3.19085121e-01 2.99841821e-01 -6.65102363e-01
-6.45341039e-01 -1.12307119e+00 -4.89381433e-01 1.30636716e+00
3.24267983e-01 -4.39044595e-01 -9.54439282e-01 -2.49762803e-01
1.77620783e-01 6.89606130e-01 -5.90509653e-01 3.84124845e-01
-5.03739953e-01 -8.32535863e-01 7.39044368e-01 3.45434904e-01
-5.07752821e-02 -1.33414865e+00 -6.58416986e-01 1.25490099e-01
-2.20292807e-01 -6.63697243e-01 -6.23428151e-02 4.48765576e-01
-1.35989368e+00 -5.18594682e-01 -6.66252747e-02 -8.20914626e-01
5.87345481e-01 2.46782884e-01 1.27047324e+00 5.39230824e-01
-2.31483161e-01 4.26904231e-01 -1.21292919e-01 -4.95818377e-01
-4.59671497e-01 -8.00336525e-02 5.28869390e-01 -5.87835789e-01
5.19427478e-01 -2.50617653e-01 -7.29350567e-01 5.37953973e-01
-6.88540697e-01 1.62748516e-01 1.79803044e-01 1.04410267e+00
1.35816500e-01 -9.34035778e-02 1.22507080e-01 -6.38007045e-01
8.72274399e-01 -1.69219792e-01 -3.78732830e-01 5.77745810e-02
-6.77108407e-01 -3.74140263e-01 3.21430594e-01 -3.25342178e-01
-1.01981449e+00 -4.87835288e-01 -9.82677937e-02 2.45538145e-01
1.11353043e-02 -1.46784872e-01 6.47139177e-02 -5.24923325e-01
8.02199244e-01 9.25758183e-02 1.99174434e-02 -6.80815242e-03
3.01039815e-01 7.09525108e-01 -6.82967342e-03 -6.68678164e-01
8.44880998e-01 4.91470337e-01 7.98524171e-02 -9.57177758e-01
-1.52186140e-01 -2.60129690e-01 -9.51962709e-01 -6.54426932e-01
6.56643391e-01 -6.78531289e-01 -9.10833478e-01 3.91110867e-01
-9.38691139e-01 -3.38627815e-01 -3.91645581e-01 4.25431967e-01
-1.01278400e+00 2.75717527e-02 -3.90154392e-01 -1.27895141e+00
-5.10977268e-01 -1.02017939e+00 9.43384409e-01 5.30070923e-02
-5.10597289e-01 -1.26927447e+00 5.87685481e-02 2.71537274e-01
1.81734428e-01 -1.73075795e-01 6.90226793e-01 -2.38256708e-01
-4.24233019e-01 -1.53791070e-01 2.34436691e-02 -1.39755070e-01
1.70832314e-02 4.95917559e-01 -9.81751978e-01 -5.31145096e-01
6.65065646e-02 -1.92070693e-01 -1.08835101e-01 6.52520418e-01
5.91872573e-01 -2.29931593e-01 -8.56000841e-01 5.40386558e-01
1.38545322e+00 3.85070026e-01 5.32770038e-01 7.28214979e-01
1.41836226e-01 5.53460240e-01 9.17806149e-01 4.63203549e-01
1.30579369e-02 3.28798652e-01 2.40537539e-01 1.49327129e-01
1.11720070e-01 -1.54819340e-01 3.77893507e-01 1.16112018e+00
-8.18235934e-01 -2.69281328e-01 -5.07867396e-01 4.42987174e-01
-1.72482407e+00 -1.40330648e+00 -4.32368398e-01 6.90478683e-01
6.25676990e-01 1.56016424e-01 -1.48347050e-01 3.35214496e-01
4.99015123e-01 -2.03574806e-01 -1.19133167e-01 -1.06291151e+00
-1.43546045e-01 3.15233678e-01 7.37729073e-01 1.00061214e+00
-7.20721722e-01 1.03317809e+00 1.29781246e+01 1.02230716e+00
2.21112028e-01 1.03134915e-01 5.16071796e-01 3.48020852e-01
-4.36954498e-01 -4.56139445e-02 -1.04416132e+00 2.72933897e-02
1.38140702e+00 -4.30666685e-01 6.85999811e-01 5.44219851e-01
3.44648361e-01 -4.23268199e-01 -1.26188684e+00 5.26221812e-01
9.73738134e-02 -1.40886843e+00 -2.83300440e-04 6.85225725e-01
7.73699820e-01 -5.08050561e-01 6.22419357e-01 3.24184299e-01
6.09259963e-01 -1.14389277e+00 8.60300779e-01 2.53660440e-01
1.03040910e+00 -6.05088234e-01 5.67372203e-01 1.68872893e-01
-1.14389896e+00 -2.20873043e-01 -8.77727985e-01 -1.00755692e+00
3.93533185e-02 -1.81779593e-01 -4.29956943e-01 3.48861217e-01
9.58353162e-01 2.99398601e-01 -3.93658698e-01 9.95779395e-01
-4.78694476e-02 1.04875881e-02 -2.71853864e-01 -4.48467314e-01
4.83122796e-01 -3.54241252e-01 4.66730654e-01 1.00164843e+00
2.48499006e-01 3.51035744e-01 -9.84472036e-02 4.01770771e-01
5.45058846e-01 3.29446048e-02 -1.19659424e+00 -1.78908288e-01
2.83276141e-01 9.16795909e-01 -4.83487815e-01 -4.22520459e-01
-2.00212970e-01 8.62069130e-01 -3.55488248e-02 5.01107454e-01
-6.11489356e-01 -4.35615242e-01 9.72222984e-01 -1.27327025e-01
-1.14700586e-01 -3.48497719e-01 -6.23769283e-01 -7.30352640e-01
-5.89872956e-01 -4.54965204e-01 5.93606755e-02 -5.53365827e-01
-1.39813089e+00 5.79277515e-01 -2.27688253e-02 -1.40553558e+00
-6.99901402e-01 -1.27676582e+00 -4.76714373e-01 4.92853165e-01
-1.11898029e+00 -1.10984349e+00 2.50124663e-01 4.52870727e-01
1.64141744e-01 -5.34416080e-01 1.39563632e+00 3.57715860e-02
1.00637585e-01 9.24474537e-01 6.69434488e-01 -7.37814724e-01
5.56605101e-01 -1.27867436e+00 5.68737745e-01 -1.37897313e-01
-4.31265175e-01 9.05828118e-01 6.28349900e-01 -5.39804697e-01
-1.41196322e+00 -3.66917729e-01 1.08350635e+00 -9.83769417e-01
6.55218959e-01 -3.86345625e-01 4.23767231e-02 7.88592756e-01
7.15902448e-01 -6.18741751e-01 8.21781039e-01 -1.83753878e-01
1.80774391e-01 5.75296998e-01 -1.39248300e+00 6.12354755e-01
1.66275799e+00 -4.63594139e-01 -6.25784039e-01 7.60327101e-01
8.13696027e-01 -6.94087505e-01 -1.30082703e+00 3.34633321e-01
8.65424156e-01 -8.75409484e-01 1.61978090e+00 -1.32660246e+00
-4.43697497e-02 2.81152606e-01 -2.61993498e-01 -9.32519078e-01
-5.96193194e-01 -1.23518765e+00 -5.33532679e-01 -5.83747849e-02
5.96577883e-01 -1.13057327e+00 3.42365682e-01 8.74560475e-01
-2.82833427e-01 -6.42737269e-01 -1.06996536e+00 -1.32016802e+00
-3.35779637e-02 -1.45572275e-01 4.90409225e-01 7.63798356e-01
6.83744550e-01 1.09839931e-01 -6.36873543e-02 -1.00294888e-01
5.33176839e-01 9.55312885e-03 4.41501856e-01 -1.34294486e+00
3.86843324e-01 -5.75816095e-01 -3.07655483e-01 -9.45992947e-01
-8.85957032e-02 -8.12076271e-01 -6.53862000e-01 -1.28511906e+00
-8.32044985e-03 -1.91056758e-01 -1.11109078e-01 -1.65725678e-01
3.67937148e-01 2.13746816e-01 1.20859891e-02 1.03788137e-01
-3.71160030e-01 6.18435517e-02 1.29639816e+00 6.91750320e-05
-1.62315920e-01 4.85058486e-01 -4.81304944e-01 7.84440815e-01
8.58408585e-02 -2.99253196e-01 -6.78878546e-01 6.11881316e-02
6.69384480e-01 4.61409837e-02 3.24159935e-02 -7.42885649e-01
5.37211418e-01 -3.75702560e-01 4.78586555e-01 -1.32223868e+00
1.30741090e-01 -9.61415648e-01 6.95283338e-02 9.40189242e-01
2.74610907e-01 1.20424610e-02 8.66204947e-02 5.39500564e-02
-1.44871444e-01 -5.70943117e-01 9.21121240e-01 -4.07591403e-01
-4.92852688e-01 -5.20386267e-03 -1.03226590e+00 8.97834301e-02
9.92593169e-01 -7.84614205e-01 -3.59281451e-01 -4.20183957e-01
-8.29068601e-01 -1.95836127e-02 6.50830388e-01 3.03609259e-02
7.30431557e-01 -1.51530886e+00 -2.30721906e-01 7.18729138e-01
-3.22939813e-01 -3.74400020e-01 -1.70157343e-01 6.58265352e-01
-1.32361674e+00 1.02442718e+00 -5.41665435e-01 -4.55340147e-01
-1.14228773e+00 4.78126436e-01 4.28307921e-01 -2.41845414e-01
-2.15481281e-01 1.11954463e+00 2.71224789e-02 -8.23025763e-01
1.85185194e-01 -9.21545625e-02 -7.54407048e-01 3.55081353e-03
6.88606799e-01 1.05194807e+00 -2.91290224e-01 -6.04341030e-01
-4.56784427e-01 6.65885091e-01 2.32151806e-01 -2.87484169e-01
9.17833567e-01 -2.19243199e-01 -9.89108324e-01 4.28274393e-01
8.38715494e-01 -1.36269778e-01 -3.69319022e-02 4.16855574e-01
1.25943512e-01 -8.02164078e-01 -4.32406247e-01 -3.55811834e-01
-1.85641110e-01 5.54822803e-01 5.34874737e-01 8.99602413e-01
8.57008278e-01 -3.02566767e-01 8.18335712e-01 9.66778398e-01
5.72402716e-01 -1.68019545e+00 -2.13140488e-01 6.89524531e-01
9.12339568e-01 -9.28350806e-01 5.44190466e-01 -7.27165341e-01
-4.14997995e-01 1.32979155e+00 4.68304873e-01 -1.55325383e-01
1.27306652e+00 5.74917436e-01 1.14069022e-02 -3.70670199e-01
-9.44949508e-01 1.12705544e-01 3.75366658e-01 1.11147714e+00
5.06513238e-01 5.07374525e-01 -9.66500878e-01 3.21953118e-01
-7.28706717e-01 -2.34555230e-01 4.90474731e-01 1.41972518e+00
-6.43810987e-01 -1.20391917e+00 -7.23931909e-01 4.61561680e-01
-5.49773455e-01 -1.16372630e-01 -5.28106689e-01 8.46754074e-01
-5.76629937e-02 1.49448860e+00 -1.97535474e-03 -5.03491640e-01
4.11356747e-01 1.41089618e-01 7.21762300e-01 -1.23501487e-01
-9.04846430e-01 4.15413082e-01 3.84890139e-01 -1.23056793e+00
-8.58632207e-01 -1.05834293e+00 -1.40667629e+00 -1.19437599e+00
-5.12782812e-01 1.89310342e-01 3.83317530e-01 3.90289724e-01
-2.06836104e-01 2.85260603e-02 9.80917513e-01 -1.07949340e+00
-3.90341938e-01 -9.39418614e-01 -1.00026262e+00 -7.84516707e-02
2.89751232e-01 -8.00943017e-01 -7.83523321e-01 2.83909619e-01] | [-7.374553203582764, 3.7077677249908447] |
8192f97d-b2ab-4c9f-80a6-505901d03670 | patient-specific-3d-volumetric-reconstruction | 1810.03270 | null | http://arxiv.org/abs/1810.03270v1 | http://arxiv.org/pdf/1810.03270v1.pdf | Patient-Specific 3D Volumetric Reconstruction of Bioresorbable Stents: A Method to Generate 3D Geometries for Computational Analysis of Coronaries Treated with Bioresorbable Stents | As experts continue to debate the optimal surgery practice for coronary
disease - percutaneous coronary intervention (PCI) or coronary aortic bypass
graft (CABG) - computational tools may provide a quantitative assessment of
each option. Computational fluid dynamics (CFD) has been used to assess the
interplay between hemodynamics and stent struts; it is of particular interest
in Bioresorbable Vascular Stents (BVS), since their thicker struts may result
in impacted flow patterns and possible pathological consequences. Many proofs
of concept are presented in the literature; however, a practical method for
extracting patient-specific stented coronary artery geometries from images over
a large number of patients remains an open problem.
This work provides a possible pipeline for the reconstruction of the BVS.
Using Optical Coherence Tomographies (OCT) and Invasive Coronary Angiographies
(ICA), we can reconstruct the 3D geometry of deployed BVS in vivo. We
illustrate the stent reconstruction process: (i) automatic strut detection,
(ii) identification of stent components, (iii) 3D registration of stent
curvature, and (iv) final stent volume reconstruction. The methodology is
designed for use on clinical OCT images, as opposed to approaches that relied
on a small number of virtually deployed stents.
The proposed reconstruction process is validated with a virtual phantom
stent, providing quantitative assessment of the methodology, and with selected
clinical cases, confirming feasibility. Using multimodality image analysis, we
obtain reliable reconstructions within a reasonable timeframe. This work is the
first step toward a fully automated reconstruction and simulation procedure
aiming at an extensive quantitative analysis of the impact of BVS struts on
hemodynamics via CFD in clinical trials, going beyond the proof-of-concept
stage. | ['Alessandro Veneziani', 'Yasir Bouchi', 'Boyi Yang', 'Habib Samady', 'Bill Gogas', 'Don Giddens', 'Tianli Han', 'Marina Piccinelli', 'Gaetano Esposito'] | 2018-10-08 | null | null | null | null | ['3d-volumetric-reconstruction'] | ['computer-vision'] | [ 2.59831455e-03 2.45574815e-03 1.55108973e-01 3.18458796e-01
-4.47877407e-01 -7.51971722e-01 1.55643195e-01 4.51658249e-01
-1.50270015e-01 5.68126738e-01 -3.73533554e-02 -1.14686966e+00
-1.58649385e-01 -5.72855115e-01 -2.29346484e-01 -4.90270317e-01
-5.02442300e-01 8.95730078e-01 5.01843214e-01 -6.53738007e-02
1.19739600e-01 9.70504880e-01 -8.91217291e-01 5.92140630e-02
5.65948844e-01 8.79394352e-01 3.42624307e-01 5.96304178e-01
-6.30634204e-02 3.96481663e-01 1.21520422e-01 -1.91457331e-01
4.19892251e-01 -3.82352471e-01 -5.27743161e-01 7.87428543e-02
-6.37642145e-02 -4.97176170e-01 9.83987078e-02 5.79999924e-01
7.29648113e-01 -6.27388299e-01 5.89652717e-01 -1.50943279e-01
1.99609652e-01 3.03299993e-01 -6.99702278e-02 3.72332484e-01
1.53466035e-02 6.54231966e-01 4.15892959e-01 -8.17158878e-01
7.94113278e-01 7.45198548e-01 7.52356172e-01 4.21951860e-02
-1.46563649e+00 2.98000220e-02 -4.64640677e-01 -2.45612696e-01
-9.74107385e-01 -2.49983296e-01 8.09618592e-01 -1.03333759e+00
4.18221027e-01 4.90171343e-01 1.19550192e+00 5.03857255e-01
2.66534567e-01 5.61265200e-02 1.40791416e+00 -4.80417699e-01
3.15790445e-01 5.54125786e-01 1.95643187e-01 3.20827067e-01
8.02299738e-01 7.72419214e-01 4.64781076e-01 -3.61514509e-01
1.35039055e+00 -1.83521420e-01 -3.48500192e-01 -7.42973149e-01
-1.04228735e+00 5.64173698e-01 1.41854048e-01 5.70672691e-01
-8.07779193e-01 -5.89396842e-02 7.29932785e-01 1.10823140e-01
2.42541522e-01 3.01852077e-01 -3.44452411e-01 -1.74111977e-01
-8.68342280e-01 1.72193184e-01 8.32839072e-01 2.62134880e-01
2.01488748e-01 -1.27624646e-01 1.28082618e-01 5.52754641e-01
6.90722167e-01 4.54503715e-01 4.74651188e-01 -7.88357794e-01
8.86255782e-03 4.75823075e-01 2.24367291e-01 -8.57263625e-01
-2.84223735e-01 -7.70336449e-01 -8.66990507e-01 8.14458728e-01
6.48084104e-01 -2.17161119e-01 -4.86934602e-01 8.74899507e-01
5.62496662e-01 3.32154393e-01 -3.02386135e-01 1.15483499e+00
5.18824100e-01 -3.01924497e-01 2.55829930e-01 -5.38985670e-01
1.67593253e+00 -2.15101793e-01 -1.81225225e-01 -1.08447872e-01
8.50813806e-01 -9.17197764e-01 7.48067379e-01 7.16459304e-02
-1.31099844e+00 -3.77242446e-01 -7.44612634e-01 6.51265740e-01
2.22082153e-01 9.14753824e-02 4.51334924e-01 1.18499959e+00
-9.23051715e-01 9.78707552e-01 -9.38915730e-01 -3.63847762e-01
6.38967276e-01 1.04619943e-01 -2.55335331e-01 2.67719865e-01
-7.52742946e-01 1.18658471e+00 -9.39153507e-02 2.40799814e-01
-5.32578528e-01 -9.96631861e-01 -4.74459499e-01 -1.20388925e-01
-2.46256948e-01 -1.20258069e+00 8.73937309e-01 -4.05587643e-01
-1.73938489e+00 1.15066409e+00 -3.61234806e-02 -6.20181859e-01
1.01718485e+00 7.16023967e-02 -3.59202921e-02 5.18797040e-01
-2.23949458e-02 -1.09233566e-01 3.24228674e-01 -1.36738122e+00
3.50914374e-02 -4.20848548e-01 -4.19064671e-01 -3.49090129e-01
2.53902376e-01 -3.11351214e-02 1.59444824e-01 -5.26964724e-01
4.46084708e-01 -1.08881354e+00 -8.26497972e-01 3.19696516e-01
-4.09532458e-01 7.12234735e-01 2.94229716e-01 -6.37520730e-01
1.15416276e+00 -1.92864144e+00 -2.45711103e-01 3.79158169e-01
4.19752389e-01 7.96195149e-01 3.36326241e-01 3.03578317e-01
-3.87737483e-01 3.75879109e-01 -3.54423761e-01 1.25934482e-01
-5.70152879e-01 -3.01211387e-01 -1.24795452e-01 5.69608986e-01
-1.54373005e-01 1.10675859e+00 -6.34833157e-01 -4.99305874e-01
7.77437091e-01 4.01505321e-01 -3.75478655e-01 -2.27548137e-01
2.31951430e-01 9.66814220e-01 -7.92509019e-01 3.49331141e-01
8.46132696e-01 -2.40733087e-01 6.73264921e-01 -2.89691031e-01
-5.27261138e-01 6.39252886e-02 -1.10967600e+00 1.15110874e+00
-5.80115020e-01 3.01409125e-01 1.09598987e-01 -9.31693256e-01
1.03605568e+00 7.01674223e-01 9.83281255e-01 -6.06063962e-01
6.24164462e-01 8.00936460e-01 4.66653585e-01 -6.25742614e-01
-3.36623162e-01 -6.57059848e-01 5.97108126e-01 3.01838160e-01
-5.63319981e-01 -9.97767448e-02 -3.22539769e-02 -2.16559738e-01
8.95880699e-01 8.98671597e-02 3.64959985e-01 -6.60049081e-01
7.97808588e-01 4.48236138e-01 -1.96624231e-02 4.77899283e-01
-5.08571267e-01 7.85327792e-01 5.27020037e-01 -8.87324750e-01
-1.30705106e+00 -1.01587331e+00 -7.50913560e-01 -6.53765142e-01
3.08323324e-01 -1.45973727e-01 -5.31832099e-01 1.03406578e-01
1.69877455e-01 2.09931791e-01 -3.30033511e-01 2.37110183e-01
-9.29815710e-01 -6.90172255e-01 1.16518244e-01 8.50704908e-02
6.95570884e-03 -7.91804552e-01 -1.26399434e+00 8.36355448e-01
1.77855819e-01 -1.25204217e+00 3.82223189e-01 -4.31178063e-01
-1.64250350e+00 -1.53527021e+00 -8.72458577e-01 -5.45300305e-01
3.56369197e-01 6.91816136e-02 1.19698501e+00 4.22560871e-01
-7.82257438e-01 1.93362266e-01 -8.03163052e-02 -1.84389398e-01
-1.00904679e+00 -4.11473215e-01 -3.27520281e-01 -1.85890809e-01
-3.09263408e-01 -1.03894830e+00 -1.26965547e+00 5.49447179e-01
-3.28357965e-01 8.82954597e-02 6.15846872e-01 3.77576262e-01
7.17387438e-01 -5.55029273e-01 5.78319848e-01 -1.06059575e+00
5.07148862e-01 -3.66110533e-01 -6.62959337e-01 -1.15567498e-01
-6.32543802e-01 -4.21303064e-01 4.94684696e-01 -1.66359246e-01
-7.89489210e-01 -2.66219601e-02 -2.93407083e-01 -4.07596022e-01
-5.03816605e-01 7.17804074e-01 5.22790194e-01 -6.97683245e-02
1.07838953e+00 -2.97151767e-02 6.11854017e-01 -5.57061374e-01
1.33220747e-01 3.90080661e-01 1.34079888e-01 -6.10158324e-01
6.10791802e-01 8.45253468e-01 5.43334544e-01 -8.32959771e-01
2.44038120e-01 -5.45210004e-01 -7.57402241e-01 -3.88105482e-01
4.50954646e-01 -4.75474715e-01 -8.88915479e-01 9.86721367e-03
-1.09026921e+00 -2.94618875e-01 -7.23283231e-01 7.45537281e-01
-5.96142232e-01 6.24919176e-01 -6.23742998e-01 -8.44562232e-01
-5.86883426e-01 -1.54985178e+00 7.14660168e-01 -2.97145277e-01
-3.21934998e-01 -1.11267579e+00 2.54280001e-01 3.12371738e-02
7.79928148e-01 8.29821229e-01 1.02874553e+00 -1.21500932e-01
-7.49005854e-01 -5.07317662e-01 2.17909385e-02 5.97250229e-03
-2.62572672e-02 1.04966499e-01 -5.81919193e-01 -4.07605916e-02
1.51870668e-01 4.60935056e-01 3.54871750e-01 1.16890752e+00
4.52162355e-01 3.04614782e-01 -7.51739204e-01 3.07275057e-01
1.71756220e+00 7.76033774e-02 9.79014277e-01 3.88702720e-01
2.81527400e-01 5.28369069e-01 2.72565454e-01 4.47967172e-01
-1.88029066e-01 8.04946601e-01 5.26548862e-01 -2.43694827e-01
-6.77474499e-01 1.48553014e-01 -1.72432899e-01 3.46984237e-01
-3.12867343e-01 5.04848421e-01 -9.20995235e-01 3.97554040e-01
-1.45789826e+00 -6.03744626e-01 -9.28069532e-01 2.54857087e+00
3.02062809e-01 3.50888938e-01 4.43119556e-01 -7.23912790e-02
6.71728313e-01 -4.70199674e-01 -3.16530496e-01 -2.78923631e-01
6.35637194e-02 4.31614220e-01 4.23291981e-01 6.69648170e-01
-6.98086083e-01 3.47536474e-01 6.52203751e+00 3.16825882e-02
-1.62344921e+00 1.12849668e-01 7.84568846e-01 4.82972443e-01
-3.45532030e-01 6.33778155e-01 -2.57890254e-01 4.85044956e-01
8.94698977e-01 -8.60146582e-02 -6.03929684e-02 5.05813897e-01
9.06420529e-01 -2.73482800e-01 -6.16884649e-01 6.55334592e-01
-7.92486489e-01 -1.97472095e+00 -2.84093320e-01 3.28029782e-01
8.24191421e-02 1.90175727e-01 -3.57967049e-01 -2.52371013e-01
-2.98506528e-01 -5.77137172e-01 6.63623691e-01 5.52869797e-01
1.03597951e+00 1.93624750e-01 7.04068899e-01 2.71858454e-01
-1.09529626e+00 1.70173526e-01 8.36686268e-02 -5.25257401e-02
8.29720020e-01 1.17964053e+00 -1.03199852e+00 6.75886273e-01
2.56569505e-01 5.25635481e-01 -3.68700892e-01 1.49038482e+00
3.88095647e-01 6.61955893e-01 -2.52203584e-01 3.07675123e-01
-2.92100787e-01 -6.23230875e-01 1.05603492e+00 7.17705607e-01
3.30311507e-01 -9.21956170e-03 -2.69530136e-02 1.25896192e+00
7.72591949e-01 5.12999475e-01 -4.29126322e-01 2.93004513e-01
3.56535614e-01 1.24767923e+00 -1.15743279e+00 -2.55652934e-01
-2.69375056e-01 1.63581669e-01 -2.00480312e-01 2.98064023e-01
-3.57441425e-01 5.07540286e-01 5.84955513e-01 1.27949774e+00
5.30757904e-02 -2.72764087e-01 -9.88483787e-01 -9.15186584e-01
8.20399374e-02 -2.86237717e-01 5.69356270e-02 -5.15064418e-01
-9.70600188e-01 6.92282617e-01 -7.00546205e-02 -1.49377787e+00
-1.60516694e-01 -9.17379498e-01 -7.68851936e-01 1.45544922e+00
-1.52051449e+00 -9.15684819e-01 -1.04284480e-01 -1.02468908e-01
1.43298566e-01 -2.04821527e-02 1.09167075e+00 5.39180100e-01
-2.42338285e-01 -3.13847005e-01 -2.72282064e-01 -2.71273404e-01
1.44712970e-01 -8.61972272e-01 2.47237593e-01 5.23253560e-01
-6.73517823e-01 6.30496323e-01 9.12895977e-01 -8.67153108e-01
-9.98357892e-01 -6.07816279e-01 4.89114612e-01 -3.67956012e-01
5.08450925e-01 4.22447622e-01 -5.62967181e-01 2.81762749e-01
-1.06342293e-01 4.58397776e-01 6.12352788e-01 -2.86884278e-01
4.16417629e-01 1.71017289e-01 -1.12991691e+00 6.00075662e-01
6.81235731e-01 5.93328774e-02 -1.15493640e-01 2.45858327e-01
-1.27387002e-01 -5.70131004e-01 -1.09572303e+00 5.76722264e-01
9.03584301e-01 -1.33800805e+00 1.21676469e+00 -5.18318653e-01
3.48490745e-01 -3.18908274e-01 3.78106505e-01 -7.75228441e-01
-3.33565921e-01 -5.45103371e-01 2.51378179e-01 5.91318965e-01
2.67094851e-01 -9.85340714e-01 7.67760575e-01 6.67168856e-01
-4.18305933e-01 -1.16520035e+00 -9.34276938e-01 -4.16660011e-01
5.09716868e-01 -3.26302290e-01 -5.23010083e-03 5.51365674e-01
-3.50950323e-02 -3.08717459e-01 3.93260807e-01 -2.37500537e-02
5.09956121e-01 2.01761797e-01 5.37871838e-01 -1.66097319e+00
-2.79262125e-01 -7.19144285e-01 -5.89953125e-01 -3.49726111e-01
-2.04691380e-01 -9.71456289e-01 -5.98743081e-01 -1.47042716e+00
-1.69701308e-01 -1.02626359e+00 1.47824287e-01 -4.14059252e-01
3.83117311e-02 7.81734437e-02 4.20060055e-03 6.59980297e-01
5.49974442e-01 -1.16569348e-01 1.85302138e+00 4.86611813e-01
-3.18671554e-01 1.99566901e-01 -4.85955358e-01 5.29555976e-01
6.94508970e-01 -4.05000895e-01 -3.12132269e-01 2.71877617e-01
-1.10818379e-01 5.81118226e-01 9.35362339e-01 -9.33944583e-01
1.81090869e-02 2.66928464e-01 4.10073251e-02 -2.42782980e-01
-1.32932112e-01 -1.06625986e+00 7.23450422e-01 1.13252413e+00
7.98124373e-02 -2.66364962e-01 3.67300391e-01 2.37974003e-01
-7.96700120e-02 -4.03224736e-01 1.03746462e+00 -6.05997741e-01
1.14587825e-02 1.71621516e-01 -6.56867146e-01 -6.85760230e-02
1.10753810e+00 -6.33063674e-01 2.10915636e-02 1.08462565e-01
-1.35006475e+00 -5.24120152e-01 4.40593481e-01 -4.82672334e-01
4.79991764e-01 -9.61152732e-01 -9.76592481e-01 2.30278283e-01
-2.52523035e-01 -1.53687671e-01 6.67015553e-01 1.46434820e+00
-1.37661684e+00 3.93029600e-01 -8.99355710e-02 -1.04338229e+00
-9.24057662e-01 5.27119756e-01 1.13458252e+00 -5.04801273e-01
-1.18241990e+00 2.15062901e-01 9.92774293e-02 -2.86901351e-02
-6.61725223e-01 -1.57880634e-01 -1.45421401e-01 -2.79418707e-01
1.08464576e-01 2.82476395e-01 3.46673995e-01 -6.64636493e-01
-2.82587677e-01 8.96262825e-01 2.55402505e-01 -2.14153081e-02
1.08021915e+00 -3.82748246e-01 -6.07349537e-03 -2.27440447e-02
6.68676913e-01 -8.19240585e-02 -1.01998663e+00 7.25055998e-03
-1.17416114e-01 -5.40271282e-01 2.61656284e-01 -7.88856566e-01
-1.09981108e+00 8.87108982e-01 9.41785097e-01 3.61634970e-01
7.67301500e-01 -1.09344371e-01 7.99332380e-01 -6.80700421e-01
3.50266486e-01 -2.33492985e-01 -3.55043679e-01 -2.84099191e-01
8.38291705e-01 -8.86232376e-01 1.29174680e-01 -1.28006792e+00
-2.18693927e-01 1.46485698e+00 -2.48415768e-01 -3.83355349e-01
1.26015687e+00 3.88977140e-01 3.90154988e-01 -4.19890910e-01
-2.54856348e-01 -2.20365360e-01 -3.45963612e-02 3.07134032e-01
6.91434503e-01 3.40511501e-01 -7.91439354e-01 4.76229340e-01
1.58050790e-01 4.22915936e-01 4.59384769e-01 8.07445884e-01
-2.64578998e-01 -1.41479599e+00 -3.26665878e-01 3.96723002e-01
-4.62647736e-01 -1.15178958e-01 1.43283755e-01 7.50304043e-01
-5.59070557e-02 6.84856534e-01 -3.67154717e-01 2.44957373e-01
8.12325120e-01 -2.91940812e-02 5.39290667e-01 -4.26494747e-01
-8.22571516e-01 4.90591377e-01 1.88707203e-01 -1.65452272e-01
-3.28805268e-01 -1.00427639e+00 -1.05901480e+00 -5.96985556e-02
-2.26764008e-01 -1.36878654e-01 9.05693650e-01 8.90234768e-01
5.78883350e-01 7.58784354e-01 5.72874367e-01 -9.39260602e-01
-2.17092574e-01 -7.04183996e-01 -8.48724842e-01 6.29220665e-01
4.51697558e-02 -7.74680257e-01 -2.99537420e-01 2.59955108e-01] | [14.044008255004883, -2.5936434268951416] |
3d472a89-b5c3-48c0-8ad8-ec8878121c34 | a-gis-aided-approach-for-geolocalizing-an | 2208.12251 | null | https://arxiv.org/abs/2208.12251v1 | https://arxiv.org/pdf/2208.12251v1.pdf | A Gis Aided Approach for Geolocalizing an Unmanned Aerial System Using Deep Learning | The Global Positioning System (GPS) has become a part of our daily life with the primary goal of providing geopositioning service. For an unmanned aerial system (UAS), geolocalization ability is an extremely important necessity which is achieved using Inertial Navigation System (INS) with the GPS at its heart. Without geopositioning service, UAS is unable to fly to its destination or come back home. Unfortunately, GPS signals can be jammed and suffer from a multipath problem in urban canyons. Our goal is to propose an alternative approach to geolocalize a UAS when GPS signal is degraded or denied. Considering UAS has a downward-looking camera on its platform that can acquire real-time images as the platform flies, we apply modern deep learning techniques to achieve geolocalization. In particular, we perform image matching to establish latent feature conjugates between UAS acquired imagery and satellite orthophotos. A typical application of feature matching suffers from high-rise buildings and new constructions in the field that introduce uncertainties into homography estimation, hence results in poor geolocalization performance. Instead, we extract GIS information from OpenStreetMap (OSM) to semantically segment matched features into building and terrain classes. The GIS mask works as a filter in selecting semantically matched features that enhance coplanarity conditions and the UAS geolocalization accuracy. Once the paper is published our code will be publicly available at https://github.com/OSUPCVLab/UbihereDrone2021. | ['Alper Yilmaz', 'Deniz Karakay', 'Jianli Wei'] | 2022-08-25 | null | null | null | null | ['homography-estimation'] | ['computer-vision'] | [ 4.07249741e-02 -3.20409358e-01 2.88489699e-01 -2.56460130e-01
-7.34300375e-01 -7.38269091e-01 4.21766281e-01 -1.62064731e-01
-3.16689402e-01 7.22591579e-01 -8.40434432e-02 -2.41218269e-01
-1.08782955e-01 -1.10959148e+00 -8.32273364e-01 -7.74554551e-01
-1.94528684e-01 2.30218440e-01 1.16548486e-01 -4.95635927e-01
2.43963785e-02 6.95392787e-01 -1.52663803e+00 -4.02678281e-01
1.03235126e+00 8.52061033e-01 2.05045775e-01 5.35088599e-01
2.70539075e-01 -1.32988676e-01 -3.33390743e-01 1.02849513e-01
8.30272496e-01 -1.13522276e-01 -5.76866865e-01 4.44062911e-02
4.32154000e-01 -4.11255270e-01 -4.08827543e-01 1.22513616e+00
4.52641100e-01 1.59555808e-01 2.01159343e-01 -1.27488828e+00
-6.04809225e-02 2.48845547e-01 -5.53626597e-01 1.05346693e-02
4.68337059e-01 5.79420254e-02 5.11604011e-01 -6.16700470e-01
2.78995961e-01 6.83641136e-01 9.94735718e-01 -2.99585581e-01
-9.76865649e-01 -4.80864584e-01 -3.11011858e-02 -2.31593549e-02
-1.77387917e+00 -3.66814524e-01 5.37232935e-01 -4.10740137e-01
5.20232737e-01 2.98410177e-01 7.74072170e-01 6.83437645e-01
2.96672016e-01 2.60635585e-01 5.36146760e-01 -2.70787477e-01
1.29111007e-01 -3.48702788e-01 -4.18221146e-01 5.90113163e-01
4.47454840e-01 2.58497685e-01 -3.65984529e-01 -9.14968401e-02
7.46954679e-01 2.48090446e-01 -6.90339029e-01 -3.73575002e-01
-1.42355633e+00 5.57416320e-01 1.02234066e+00 2.74098694e-01
-5.33934355e-01 1.10760227e-01 -1.42821714e-01 3.23420823e-01
9.65348929e-02 4.22032148e-01 -2.65072733e-01 -5.43885231e-02
-1.06427276e+00 1.07935451e-01 4.63069707e-01 1.07414067e+00
1.08468151e+00 3.77412885e-01 8.08742344e-01 3.72750849e-01
2.63781339e-01 8.58314931e-01 5.88064134e-01 -6.61597490e-01
3.61381739e-01 6.02534175e-01 2.99742639e-01 -1.54021573e+00
-5.79406679e-01 -6.71023369e-01 -8.03181589e-01 -1.18476905e-01
1.33220151e-01 -3.65161538e-01 -7.83230841e-01 1.15093648e+00
4.50778008e-01 4.87409204e-01 4.27687503e-02 1.08356416e+00
4.67581034e-01 6.68033302e-01 -2.43017495e-01 2.40595490e-01
9.73832369e-01 -3.84538352e-01 -3.46563250e-01 -6.74306452e-01
9.07998919e-01 -8.95788312e-01 6.11693740e-01 3.18891108e-02
-1.55872717e-01 -4.22154874e-01 -1.44823468e+00 2.70785451e-01
-5.97028494e-01 3.05348933e-01 6.49300933e-01 3.44650507e-01
-1.26733923e+00 4.98814672e-01 -1.00212801e+00 -7.47206926e-01
-1.59477100e-01 4.86704767e-01 -7.19694734e-01 8.33973065e-02
-1.34898543e+00 7.35528350e-01 4.13896054e-01 5.21401644e-01
-5.12169838e-01 -3.91998589e-01 -1.16512680e+00 -2.68371344e-01
8.68049413e-02 -6.57151997e-01 5.74715555e-01 -9.66559649e-01
-1.16807926e+00 6.90174580e-01 2.12753266e-01 -5.86699545e-01
3.00018281e-01 -2.79087067e-01 -5.63135684e-01 -1.08245574e-01
4.41443533e-01 4.28457499e-01 8.40974331e-01 -1.05340183e+00
-1.09962261e+00 -5.60909688e-01 -3.03225014e-02 4.82831150e-01
1.24652661e-01 -4.59543526e-01 -2.02140406e-01 -5.61557889e-01
1.15016270e+00 -1.31724226e+00 -1.73996270e-01 -4.03549850e-01
-2.88241625e-01 6.56230748e-01 8.31018031e-01 -7.33849883e-01
9.88664210e-01 -2.20284891e+00 8.00056662e-03 2.36350894e-01
-2.55948424e-01 -7.40288123e-02 2.03529105e-01 5.38044453e-01
-1.34686366e-01 5.63267767e-02 -4.54950243e-01 -2.17893589e-02
-2.36558616e-01 1.87456861e-01 -5.14490128e-01 8.98399770e-01
-2.31596842e-01 4.72271472e-01 -7.06538022e-01 2.90592853e-02
4.58453417e-01 3.40158314e-01 -2.61171430e-01 -5.65821007e-02
3.73508155e-01 7.59032369e-01 -5.01803935e-01 9.17755306e-01
1.09441042e+00 2.12280020e-01 -5.04185595e-02 -3.43550980e-01
-6.16654575e-01 -3.02814022e-02 -1.29421699e+00 1.75520682e+00
-4.86407727e-01 6.13020301e-01 1.85178086e-01 -8.04717422e-01
9.86381233e-01 2.78008934e-02 5.96639931e-01 -4.31024343e-01
1.84076741e-01 3.59844923e-01 -4.89172578e-01 -2.89893240e-01
8.09790075e-01 1.76460788e-01 -3.97295743e-01 -2.49228999e-01
-2.13368535e-01 -4.73708808e-01 -4.24907178e-01 -8.24500099e-02
9.54989195e-01 2.60850251e-01 4.34182107e-01 -2.65720278e-01
4.52782631e-01 4.28170651e-01 6.42922163e-01 4.22215372e-01
-1.23411743e-02 8.42208445e-01 -2.10246183e-02 -5.99751830e-01
-7.74908662e-01 -9.04545009e-01 -2.76557326e-01 3.62357885e-01
4.34922308e-01 -2.18377430e-02 -4.53441322e-01 -2.00385138e-01
1.59389541e-01 3.78635645e-01 -2.04070330e-01 -2.21080601e-01
-3.10992032e-01 -8.52758527e-01 5.67954838e-01 1.17719598e-01
1.01172960e+00 -1.55292615e-01 -7.34685004e-01 3.44632685e-01
-4.63412642e-01 -8.97813499e-01 1.17914379e-01 8.50064456e-02
-8.46248209e-01 -1.14883482e+00 -5.06333828e-01 -4.77246284e-01
6.56029046e-01 7.67246246e-01 5.42250812e-01 -9.54559967e-02
9.70431119e-02 3.65457207e-01 -5.13250172e-01 -2.48485766e-02
2.86041975e-01 1.13883995e-01 4.04854536e-01 9.68576223e-02
2.82054812e-01 -6.77798033e-01 -6.25444949e-01 6.42701983e-01
-6.99372530e-01 -9.36172605e-02 1.91647545e-01 6.60714328e-01
4.85730678e-01 4.26365614e-01 5.80821782e-02 -1.97459236e-01
-1.09643161e-01 -7.44952381e-01 -1.18092787e+00 -1.28706172e-01
-9.82889757e-02 -4.31555450e-01 4.03177351e-01 2.93651819e-01
-6.13211870e-01 7.23491430e-01 -2.15099007e-02 -8.95320550e-02
-3.30655128e-01 9.37456250e-01 -3.70133907e-01 -6.62619829e-01
6.68433011e-01 2.84893334e-01 -1.69766918e-01 -2.14384481e-01
5.82619347e-02 7.93576241e-01 6.59210503e-01 -6.80795312e-02
1.18160307e+00 7.79227316e-01 1.21338464e-01 -1.28296566e+00
-2.44679004e-01 -5.81595838e-01 -7.82899499e-01 -2.63779044e-01
6.24742210e-01 -1.40053678e+00 -3.49642187e-01 5.04064739e-01
-8.16272080e-01 -1.74425058e-02 2.14896008e-01 7.93007374e-01
-3.45780015e-01 4.39259380e-01 1.85009181e-01 -5.27094066e-01
5.06210700e-02 -1.09510279e+00 9.66617584e-01 5.23613751e-01
-3.36785018e-02 -8.92194450e-01 5.17793521e-02 2.39622921e-01
3.20734680e-01 6.29231215e-01 2.25083642e-02 -2.74568111e-01
-9.38984036e-01 -7.27883995e-01 4.68854681e-02 2.44472455e-03
4.33818221e-01 -6.24599829e-02 -9.26851451e-01 -4.92259324e-01
6.64598644e-02 2.70177454e-01 7.10626066e-01 5.76121271e-01
3.57511908e-01 -1.32002622e-01 -4.25306976e-01 1.33999157e+00
1.72231269e+00 3.16436291e-01 5.92648149e-01 9.18812573e-01
7.49489963e-01 4.34714258e-01 1.02134502e+00 6.22022748e-01
2.96321511e-01 6.68739021e-01 9.42404270e-01 -1.79711685e-01
4.65729266e-01 -3.61199766e-01 3.42476457e-01 3.71873051e-01
-1.13392465e-01 -1.95328355e-01 -1.14757359e+00 6.84886456e-01
-1.90873480e+00 -4.75944728e-01 -3.23418021e-01 2.55866909e+00
6.24120422e-02 -2.66262889e-01 -5.26543081e-01 -1.26634091e-01
8.30843151e-01 2.10413754e-01 -2.98138320e-01 3.87293398e-01
-2.48799279e-01 -4.86656845e-01 1.45591092e+00 6.56072438e-01
-1.48743558e+00 1.11406302e+00 4.49855375e+00 3.63200277e-01
-1.47145021e+00 -2.38319367e-01 3.33632017e-03 3.54883999e-01
-4.48249802e-02 4.32695240e-01 -7.86138535e-01 4.73005384e-01
6.22754395e-01 5.10907285e-02 2.79461712e-01 1.06231654e+00
3.32007974e-01 -5.71519136e-01 -4.93885756e-01 1.16319895e+00
-1.37195691e-01 -1.21663320e+00 -1.98753789e-01 2.32796565e-01
6.34386241e-01 3.75558764e-01 2.59012897e-02 -1.86781958e-01
1.85904652e-01 -4.19446856e-01 5.49835086e-01 4.51550633e-01
6.77279472e-01 -7.06712902e-01 1.07194543e+00 1.37418449e-01
-1.47563756e+00 -3.86914387e-02 -6.53488874e-01 -2.13633835e-01
3.20747614e-01 6.04369402e-01 -1.05225277e+00 1.07095540e+00
8.06008160e-01 8.69715333e-01 -4.42612648e-01 1.45300317e+00
-3.73087525e-01 2.10175410e-01 -8.27548504e-01 5.90028524e-01
4.77424979e-01 -5.92555285e-01 8.11767936e-01 3.58732283e-01
1.24312389e+00 1.26528010e-01 3.28168392e-01 4.44163531e-01
2.85701752e-01 -1.32623300e-01 -1.26909518e+00 2.10454270e-01
5.77280343e-01 1.09968913e+00 -7.03371525e-01 5.18137589e-02
-1.67242765e-01 8.70621741e-01 -5.19758940e-01 3.63886744e-01
-8.38807285e-01 -5.11484563e-01 8.31102073e-01 2.17938423e-01
-7.87816197e-02 -7.31689572e-01 -6.90390468e-02 -1.25241423e+00
-1.21993117e-01 -5.12878835e-01 1.21346749e-01 -8.08667123e-01
-5.97147048e-01 5.71242213e-01 -2.81067848e-01 -2.01197195e+00
-1.79729551e-01 -2.09667891e-01 -4.49916184e-01 8.63763928e-01
-1.29041135e+00 -1.42886186e+00 -7.70885944e-01 4.26629126e-01
1.97663039e-01 -1.41804665e-01 7.52836108e-01 4.04399008e-01
-2.72610277e-01 -9.85609069e-02 3.79010051e-01 -2.56547872e-02
7.80889332e-01 -8.84352624e-01 6.17951512e-01 1.35038614e+00
1.02509007e-01 6.60713673e-01 1.01205301e+00 -1.07211125e+00
-1.47894955e+00 -1.13087153e+00 7.23233998e-01 -1.84438989e-01
7.64991999e-01 4.46987478e-03 -6.74618363e-01 1.08996964e+00
-2.46102706e-01 -1.85609534e-01 3.46554160e-01 -2.06919834e-01
4.17663485e-01 -4.26188707e-01 -9.66318607e-01 6.03026748e-01
7.46833205e-01 -3.87279898e-01 -3.69763941e-01 4.47343111e-01
4.71238196e-01 -6.10615194e-01 -6.49716973e-01 5.81223428e-01
4.41089332e-01 -1.00372887e+00 8.58408093e-01 1.37010396e-01
-2.73468226e-01 -8.79852116e-01 -4.74734545e-01 -1.50994039e+00
-3.24321002e-01 -4.92885977e-01 8.22782457e-01 1.08636427e+00
2.01246828e-01 -1.04569888e+00 7.74837494e-01 5.04369617e-01
-4.00783181e-01 1.36371434e-01 -1.06938291e+00 -7.06664622e-01
-6.01374865e-01 -3.31547171e-01 7.91005671e-01 1.04680550e+00
-2.34152392e-01 -2.84489900e-01 -5.10448456e-01 1.22371936e+00
5.57220638e-01 1.01224437e-01 1.03054094e+00 -1.23494637e+00
3.72097492e-01 1.37929484e-01 -8.29818368e-01 -9.07881260e-01
-3.96884456e-02 -6.26296997e-01 5.91521151e-02 -1.34166074e+00
-1.03509915e+00 -6.35773301e-01 9.13592055e-02 4.69960362e-01
4.27902609e-01 3.03324848e-01 -2.76409805e-01 4.13685083e-01
-5.18679768e-02 7.36095905e-01 5.69551706e-01 -7.82261565e-02
-4.62830156e-01 4.86197919e-01 -1.28858611e-01 9.03298855e-01
8.65593970e-01 -3.88372511e-01 -2.35412017e-01 -7.56252170e-01
6.06951654e-01 1.87362552e-01 5.60261846e-01 -1.77547431e+00
5.85660160e-01 7.46209845e-02 3.97586912e-01 -7.53723621e-01
4.15896326e-01 -1.30981255e+00 7.87783563e-01 4.36384559e-01
5.26220798e-01 1.52204186e-01 2.88796186e-01 4.55812663e-01
-6.16762161e-01 -1.94017559e-01 5.80393910e-01 -3.62849422e-02
-1.16438532e+00 4.46537822e-01 -5.75993419e-01 -6.67452514e-01
9.12270784e-01 -5.21946251e-01 -1.59172893e-01 -4.51162845e-01
-6.22055352e-01 3.75013769e-01 1.16396224e+00 2.73079365e-01
7.10962832e-01 -1.16953611e+00 -2.22048908e-01 7.38958001e-01
2.92632759e-01 9.99625325e-02 5.69986224e-01 9.59970057e-01
-1.27621841e+00 4.65826124e-01 -3.55862260e-01 -6.18526399e-01
-1.03042746e+00 1.48278043e-01 4.22359914e-01 6.24674439e-01
-4.73455340e-01 7.69962490e-01 -1.21605411e-01 -5.38515270e-01
-2.46087834e-01 -4.42053586e-01 -1.38780311e-01 2.59090275e-01
3.28428656e-01 1.75633863e-01 2.08331257e-01 -1.18629944e+00
-5.61593831e-01 9.14054871e-01 5.40344238e-01 -1.86011437e-02
1.15179300e+00 -6.84808910e-01 -1.73114121e-01 8.79845172e-02
9.92026508e-01 9.22070444e-02 -1.20225620e+00 4.14666384e-02
6.17166385e-02 -8.60881031e-01 4.15732265e-01 -5.96126132e-02
-9.44130540e-01 5.59227467e-01 9.11401749e-01 1.48915097e-01
1.00387418e+00 -4.75055337e-01 7.24062562e-01 5.41564107e-01
8.88515055e-01 -1.00485313e+00 -7.24508882e-01 6.50547028e-01
6.91627800e-01 -1.45511937e+00 1.40086532e-01 -2.75347918e-01
-5.27114391e-01 1.15171397e+00 2.53960162e-01 -2.56577402e-01
6.53579235e-01 -1.29321903e-01 1.68353036e-01 -5.90511449e-02
2.48567984e-01 -4.19217885e-01 -6.12686574e-02 7.31630325e-01
-9.86981615e-02 1.04724318e-01 1.94281653e-01 2.13137373e-01
-5.43886960e-01 -1.72889113e-01 6.30752981e-01 1.19729578e+00
-6.76562130e-01 -7.00449824e-01 -7.70803154e-01 8.58432949e-02
-1.53225930e-02 -7.59011284e-02 -5.20046651e-02 7.22264469e-01
1.28442079e-01 7.36090124e-01 1.08550034e-01 -7.32143223e-01
3.05785835e-01 -1.98648080e-01 -8.09848309e-02 -3.53229672e-01
-1.52774408e-01 1.19811006e-01 5.64536564e-02 -7.66930401e-01
-3.01794410e-01 -4.98325706e-01 -1.17268932e+00 -3.93303394e-01
-3.29628825e-01 2.76514143e-01 1.12802660e+00 7.77265668e-01
4.75453585e-01 1.92974150e-01 7.45969176e-01 -1.07776606e+00
-3.30566056e-02 -4.95202214e-01 -9.31947231e-01 -3.40828508e-01
5.21987319e-01 -8.22967112e-01 -5.47960281e-01 1.50531968e-02] | [7.411804676055908, -1.9582751989364624] |
f8ac7da6-cc34-4201-a9f0-0dec62acee95 | emotion-twenty-questions-dialog-system-for | 2210.02400 | null | https://arxiv.org/abs/2210.02400v1 | https://arxiv.org/pdf/2210.02400v1.pdf | Emotion Twenty Questions Dialog System for Lexical Emotional Intelligence | This paper presents a web-based demonstration of Emotion Twenty Questions (EMO20Q), a dialog game whose purpose is to study how people describe emotions. EMO20Q can also be used to develop artificially intelligent dialog agents that can play the game. In previous work, an EMO20Q agent used a sequential Bayesian machine learning model and could play the question-asking role. Newer transformer-based neural machine learning models have made it possible to develop an agent for the question-answering role. This demo paper describes the recent developments in the question-answering role of the EMO20Q game, which requires the agent to respond to more open-ended inputs. Furthermore, we also describe the design of the system, including the web-based front-end, agent architecture and programming, and updates to earlier software used. The demo system will be available to collect pilot data during the ACII conference and this data will be used to inform future experiments and system design. | ['Nie', 'Huihui', 'Adedamola Sanusi', 'Abe Kazemzadeh'] | 2022-10-05 | null | null | null | null | ['emotional-intelligence'] | ['natural-language-processing'] | [-6.68556988e-01 5.40942967e-01 7.51663685e-01 -8.36828113e-01
-1.44983172e-01 -5.08734941e-01 4.01607275e-01 -1.19684413e-01
-3.88237983e-01 8.26364338e-01 1.31411478e-01 -3.52751046e-01
1.44010529e-01 -9.20632362e-01 3.28082263e-01 2.66683102e-03
8.77786204e-02 6.98242784e-01 4.13705230e-01 -8.92718196e-01
1.22553475e-01 1.26767963e-01 -1.51707828e+00 5.48461854e-01
4.11974549e-01 7.64365315e-01 2.95187593e-01 1.26278293e+00
-4.11992908e-01 1.48026264e+00 -1.03793073e+00 -2.11576030e-01
-2.81732470e-01 -5.08427620e-01 -1.09781229e+00 -4.16189909e-01
-2.85206944e-01 -5.55698574e-01 -1.26547709e-01 5.95604479e-01
7.06414223e-01 5.82868993e-01 3.01429480e-01 -1.65260935e+00
-6.99568391e-02 6.82506636e-02 6.32512867e-01 5.34969382e-02
1.10694849e+00 2.30402760e-02 6.65055096e-01 -3.97037655e-01
4.00569052e-01 1.39458418e+00 4.97067273e-01 1.20828748e+00
-6.95381224e-01 -6.48844063e-01 -2.80707061e-01 2.94028610e-01
-9.05894220e-01 -3.52441639e-01 8.86304736e-01 -1.66153267e-01
1.39169228e+00 6.01242065e-01 8.38180065e-01 9.52744007e-01
2.08252475e-01 6.87456727e-01 1.40509343e+00 -6.76504195e-01
7.34686732e-01 9.42536175e-01 5.23651600e-01 9.50309575e-01
-7.67443001e-01 -2.97444481e-02 -5.03224254e-01 -5.62870204e-01
6.71344340e-01 -6.92069829e-01 4.31612283e-02 1.00235075e-01
-1.99318454e-01 1.10345376e+00 -7.50171244e-02 6.05026662e-01
-4.36199576e-01 1.32942051e-01 3.46873760e-01 5.55470109e-01
4.59337741e-01 8.19729149e-01 -8.11162055e-01 -8.35455418e-01
1.59748256e-01 5.52419603e-01 1.81466174e+00 5.65907538e-01
4.71434385e-01 7.07545877e-02 -6.86400458e-02 9.71658230e-01
8.00692976e-01 9.00928229e-02 3.17064285e-01 -1.49235165e+00
-1.49794102e-01 5.15425444e-01 7.45926380e-01 -7.55982697e-01
-9.17204082e-01 5.81472576e-01 3.23714972e-01 7.00036108e-01
5.72864652e-01 -1.14994407e+00 -7.69777074e-02 1.50293279e+00
4.74592090e-01 -4.32019144e-01 2.07375675e-01 7.98315167e-01
1.57541144e+00 7.49177277e-01 3.76043826e-01 1.98218048e-01
1.79310513e+00 -5.57762742e-01 -1.18109930e+00 5.41511327e-02
6.87998414e-01 -4.42451954e-01 1.16926277e+00 2.89967060e-01
-1.14422464e+00 -3.29167813e-01 -8.39366198e-01 1.54374480e-01
-9.19573128e-01 -2.53869414e-01 1.03098381e+00 1.31568241e+00
-1.33067036e+00 6.65311888e-02 -4.93743926e-01 -1.02868652e+00
-3.82325143e-01 4.65688586e-01 2.35697255e-01 5.68818390e-01
-1.83354223e+00 1.50582063e+00 1.84975296e-01 -1.97930321e-01
-3.29114020e-01 -2.08056509e-01 -8.91097486e-01 1.50983810e-01
1.53509915e-01 -6.27275527e-01 1.84457600e+00 -8.90052617e-01
-2.72559404e+00 7.86294281e-01 7.99519420e-02 5.08907959e-02
8.21936876e-02 7.85711706e-02 -4.65000510e-01 4.41604078e-01
-2.90836483e-01 8.61854553e-01 2.97217458e-01 -9.95169640e-01
-7.37032652e-01 -2.16895819e-01 9.15246904e-01 4.04816449e-01
-5.01704253e-02 6.45526886e-01 -1.03442535e-01 7.48301893e-02
-8.17154109e-01 -7.21601546e-01 -9.33047906e-02 -3.55114281e-01
3.26379418e-01 -9.36530352e-01 6.82421625e-01 -6.64996684e-01
8.11274946e-01 -1.62211108e+00 -4.99990970e-01 3.49954069e-02
-1.03723042e-01 2.56807804e-01 -1.80604048e-02 8.99208069e-01
-4.71335687e-02 -1.25898048e-01 4.64927465e-01 5.48375631e-03
5.02881944e-01 2.43862107e-01 2.26241015e-02 -2.60462314e-01
3.50111425e-02 7.94220746e-01 -8.43017578e-01 -4.02712077e-01
5.99285424e-01 -8.51546414e-04 -3.96445453e-01 8.11102271e-01
-4.93665665e-01 1.54228993e-02 -6.28057063e-01 5.93073219e-02
7.01009184e-02 3.01173955e-01 2.03142315e-02 9.89428312e-02
1.22567927e-02 2.00842798e-01 -9.77418303e-01 1.37458861e+00
-7.18991935e-01 6.76452458e-01 7.21132398e-01 -6.85156345e-01
1.18982387e+00 8.27252626e-01 2.93376148e-01 -4.84721035e-01
6.06598735e-01 -2.60006905e-01 -1.75422207e-01 -1.28377092e+00
5.85834265e-01 -3.87163043e-01 -2.62224883e-01 4.96536344e-01
1.53202385e-01 -8.08219612e-01 1.23399556e-01 3.04320902e-01
1.05521965e+00 3.31715494e-01 3.33149657e-02 -2.79917836e-01
5.09485304e-01 3.56253713e-01 3.80662158e-02 7.97187984e-01
-3.60889435e-01 6.78683743e-02 5.49740314e-01 -4.03236598e-01
-6.18350506e-01 -6.81992173e-01 3.10448885e-01 1.50787926e+00
2.60741860e-02 -3.85536194e-01 -1.18462062e+00 -4.34025943e-01
-5.70018291e-01 1.52376401e+00 -4.17319745e-01 5.67681575e-03
2.92482693e-02 -5.71355224e-01 5.10493696e-01 2.51312912e-01
6.06884718e-01 -1.74457943e+00 -1.17703724e+00 4.09318954e-01
-2.74933279e-01 -7.86171138e-01 2.27615163e-01 3.36227566e-01
-4.73417759e-01 -1.00490558e+00 -4.16315496e-01 -8.59172285e-01
3.12848128e-02 -3.02110821e-01 1.25352538e+00 2.64387667e-01
-1.36172533e-01 1.38020539e+00 -6.96900487e-01 -7.87316442e-01
-5.92162848e-01 5.50928153e-02 -3.29668283e-01 -5.80788374e-01
9.91215765e-01 -4.81544793e-01 -2.22579107e-01 2.73630172e-01
-6.83512032e-01 1.80450324e-02 -4.48241085e-01 4.60975647e-01
-8.94942462e-01 -1.20355412e-01 1.10823345e+00 -6.65460467e-01
1.73878086e+00 -3.59397590e-01 -3.40526372e-01 1.92703754e-01
-1.08155325e-01 -1.78746626e-01 4.55743283e-01 -1.30773559e-01
-1.54246891e+00 -3.46354693e-02 -8.40479970e-01 3.97334516e-01
-6.37978554e-01 3.90498072e-01 -2.46589139e-01 -5.09818830e-02
8.19033146e-01 -2.68900663e-01 3.38851392e-01 -1.51095495e-01
2.42860407e-01 1.26394284e+00 1.82250723e-01 -6.12121999e-01
1.42529666e-01 -1.04096040e-01 -6.58953905e-01 -1.05456960e+00
-1.20382056e-01 -2.25675538e-01 1.30857378e-01 -8.16713631e-01
1.06764364e+00 -5.76143026e-01 -1.81627059e+00 3.44440848e-01
-1.16663826e+00 -1.02655935e+00 -1.39975280e-01 1.64447471e-01
-7.33830273e-01 -4.79471050e-02 -9.41866219e-01 -1.38776803e+00
-4.67101634e-01 -4.92996365e-01 4.73125368e-01 8.57899308e-01
-8.71212602e-01 -1.23667872e+00 2.46103033e-01 5.70939422e-01
6.45581782e-01 -3.06686103e-01 9.31384265e-01 -9.97051656e-01
3.21539223e-01 -3.54975015e-01 2.62725860e-01 6.15958013e-02
-9.60710272e-02 -2.50334471e-01 -1.03776443e+00 1.92774013e-01
2.70227015e-01 -1.01442063e+00 -2.06018582e-01 1.40700750e-02
4.48500186e-01 2.51605123e-01 1.70376692e-02 -4.49711502e-01
7.44205058e-01 8.65911186e-01 7.12645531e-01 2.60715723e-01
-2.87288427e-01 1.29354548e+00 5.44958949e-01 4.53687638e-01
9.37449932e-01 6.07314825e-01 1.21951804e-01 1.23754948e-01
4.37904149e-01 6.15535378e-02 3.90983224e-01 4.68227595e-01
1.24151014e-01 -1.59814626e-01 -6.89989686e-01 7.51783475e-02
-1.92800128e+00 -9.01798546e-01 -1.62130207e-01 1.33497620e+00
6.24127507e-01 -1.46597251e-01 3.54896933e-01 -2.86277473e-01
5.69340765e-01 -2.54687443e-02 -3.17785114e-01 -1.12859380e+00
4.40344125e-01 5.02329588e-01 -4.50496435e-01 1.12993705e+00
-8.59778106e-01 1.01005995e+00 7.01606989e+00 4.00945961e-01
-6.02176189e-01 2.54159719e-01 6.00396693e-01 3.05518389e-01
-1.05941907e-01 -3.14643413e-01 -2.75855750e-01 1.72918677e-01
1.19171512e+00 -2.04608679e-01 6.72384441e-01 9.05169606e-01
5.33435166e-01 -8.61312389e-01 -8.14690411e-01 8.57687056e-01
1.40363574e-01 -9.06314611e-01 -8.37365448e-01 -4.97386128e-01
-1.09595589e-01 -2.88226187e-01 -5.99436939e-01 9.55938697e-01
7.42826939e-01 -7.50047982e-01 2.69187331e-01 6.78731978e-01
2.77679533e-01 -6.91870570e-01 8.88368487e-01 4.29327130e-01
-7.10502088e-01 -6.26346618e-02 -2.44392097e-01 -7.02095330e-01
1.71149850e-01 -3.82498384e-01 -1.08670306e+00 8.31761733e-02
8.80725145e-01 -3.59778494e-01 -3.41058582e-01 6.04225218e-01
-3.00589025e-01 5.95845222e-01 -4.93423671e-01 -1.32955945e+00
-1.21963955e-01 -3.75800610e-01 2.90956259e-01 1.00296354e+00
-1.17155135e-01 9.06568706e-01 7.50098526e-02 7.45585978e-01
5.68480968e-01 1.82820648e-01 -3.00048351e-01 2.25305438e-01
8.01249892e-02 1.56817412e+00 -6.87036812e-01 -3.82752180e-01
-2.58617759e-01 1.03328109e+00 -8.35040510e-02 4.60028291e-01
-7.72518098e-01 -9.30405974e-01 4.59389120e-01 -2.13532627e-01
-2.19091296e-01 -3.85555327e-02 -9.63942334e-03 -9.53827202e-01
-5.89154601e-01 -9.40226912e-01 9.94645059e-02 -1.73168838e+00
-1.18707323e+00 7.42121875e-01 2.19259843e-01 -8.82869437e-02
-8.02245021e-01 -7.25561798e-01 -8.69360089e-01 1.06454575e+00
-3.86626720e-01 -8.23767066e-01 -5.77444196e-01 4.10830528e-01
6.11757100e-01 -1.86050028e-01 1.63665366e+00 -1.01286210e-01
-7.82984495e-02 6.42510429e-02 -3.25181752e-01 1.87683150e-01
4.64428425e-01 -1.52295697e+00 -8.70804489e-02 -3.17401022e-01
-1.97856441e-01 1.80147409e-01 1.00709498e+00 -5.52809238e-01
-1.18427062e+00 -2.54301429e-01 6.47423625e-01 -6.97725594e-01
5.05458355e-01 -5.69322526e-01 -5.78694761e-01 4.00838494e-01
8.43563855e-01 -7.94263363e-01 9.75831330e-01 2.10272670e-01
4.09897149e-01 -2.59022266e-02 -1.57902777e+00 7.90021837e-01
2.54819363e-01 -6.61875367e-01 -1.05008447e+00 2.61348814e-01
3.63010675e-01 -2.05176607e-01 -5.69408476e-01 -1.61617830e-01
6.60615087e-01 -1.02294171e+00 3.60617548e-01 -7.66695678e-01
9.59672704e-02 -5.82178384e-02 6.40588105e-02 -1.51023579e+00
2.45939028e-02 -8.50170732e-01 2.12761104e-01 1.31197298e+00
4.54299510e-01 -8.74245167e-01 1.03131831e+00 1.63987017e+00
3.14485610e-01 -4.22060788e-01 -8.27895284e-01 1.09746419e-02
5.95454015e-02 -6.31055415e-01 1.55196086e-01 4.96383667e-01
1.12909782e+00 9.25885856e-01 -3.09585035e-01 -1.65539294e-01
-2.19056726e-01 -4.74925458e-01 7.46142805e-01 -1.09872448e+00
-3.36066961e-01 -9.41057205e-02 -9.06453431e-02 -9.21135545e-01
1.05816685e-01 -3.19866776e-01 4.12000895e-01 -1.63214076e+00
-4.09884125e-01 -4.87639084e-02 3.70068461e-01 3.16190839e-01
-2.95294702e-01 -1.08221233e-01 4.53641087e-01 -5.73714137e-01
-5.13016343e-01 6.14853680e-01 5.30053675e-01 1.68654546e-01
-4.93422806e-01 8.29122886e-02 -4.80277002e-01 9.19061601e-01
1.22570181e+00 -2.87159830e-01 -4.84510958e-01 2.42479429e-01
5.63109696e-01 3.77881497e-01 1.06659859e-01 -9.64845479e-01
4.35571909e-01 9.71186981e-02 3.21470469e-01 -2.20160112e-01
1.00902975e+00 -1.08227444e+00 -3.70260738e-02 5.06546676e-01
-5.05042195e-01 -2.20861975e-02 3.92788231e-01 6.28352761e-02
9.05359164e-02 -1.03305960e+00 3.26769680e-01 -4.92434978e-01
-5.15727043e-01 -5.15918314e-01 -1.83290720e+00 -1.77513480e-01
1.16166425e+00 6.18457654e-03 2.37850398e-02 -1.41730976e+00
-9.82561529e-01 6.13763571e-01 5.21630868e-02 4.67133224e-01
4.56636459e-01 -7.41438866e-01 -2.17714489e-01 -2.74035275e-01
-2.42301628e-01 -7.36924767e-01 3.46127711e-02 1.51953669e-02
-8.11139584e-01 3.08278739e-01 -3.39473069e-01 1.85102243e-02
-1.46277905e+00 2.61378825e-01 8.43019962e-01 -9.81000587e-02
-1.30917236e-01 7.91357994e-01 -3.44975442e-01 -9.55458045e-01
3.53014618e-01 1.76261634e-01 -8.25115919e-01 1.06900163e-01
7.73004711e-01 2.72383273e-01 -2.94872761e-01 2.59218756e-02
-2.51299441e-01 -1.65713444e-01 3.29128623e-01 -9.29557323e-01
1.15930974e+00 -1.53630450e-01 -3.77350971e-02 8.42249215e-01
6.49255693e-01 -2.10551709e-01 -6.48664176e-01 3.53740185e-01
3.45696062e-02 9.20289680e-02 -1.84495181e-01 -1.24316442e+00
-3.14525843e-01 6.90156341e-01 8.56382728e-01 8.84467781e-01
8.07089925e-01 3.85173666e-03 4.01320368e-01 9.49824095e-01
4.98330176e-01 -1.57895744e+00 2.32420787e-01 7.97436357e-01
9.67526436e-01 -9.71044123e-01 -3.85371000e-01 -4.33708400e-01
-7.78458655e-01 1.45753622e+00 1.11055720e+00 -6.16064444e-02
7.28631020e-01 3.58348757e-01 6.20704830e-01 -4.77697790e-01
-1.05552495e+00 -1.19817361e-01 -6.63441122e-01 9.53079760e-01
3.29566419e-01 -3.80188599e-02 -4.36248869e-01 9.08110797e-01
-2.87242085e-01 5.82277417e-01 6.36887789e-01 1.05034220e+00
-5.39475739e-01 -9.87295806e-01 -6.18842125e-01 3.37926596e-01
-4.01909977e-01 9.63518396e-02 -9.40529585e-01 6.18383467e-01
-2.78852358e-02 1.91623771e+00 3.60268541e-02 -5.56471646e-01
4.34095800e-01 6.72383308e-01 3.68956596e-01 -5.23163259e-01
-1.35583961e+00 -5.39086699e-01 1.06401825e+00 -4.04089093e-01
-3.70662034e-01 -9.85841230e-02 -1.25656009e+00 -8.53587165e-02
-4.13145781e-01 9.12644207e-01 7.22839057e-01 8.67950857e-01
2.19356030e-01 3.88823360e-01 5.46458244e-01 -7.44862318e-01
-2.17621908e-01 -1.58551383e+00 -5.92671275e-01 1.47121370e-01
-4.75949049e-01 -3.46498609e-01 -2.93437749e-01 -1.68689802e-01] | [13.081067085266113, 7.780576705932617] |
35b75a76-398f-4553-b400-9e7ea05f7c19 | on-the-multidimensional-augmentation-of | 2211.10642 | null | https://arxiv.org/abs/2211.10642v1 | https://arxiv.org/pdf/2211.10642v1.pdf | On the Multidimensional Augmentation of Fingerprint Data for Indoor Localization in A Large-Scale Building Complex Based on Multi-Output Gaussian Process | Wi-Fi fingerprinting becomes a dominant solution for large-scale indoor localization due to its major advantage of not requiring new infrastructure and dedicated devices. The number and the distribution of Reference Points (RPs) for the measurement of localization fingerprints like RSSI during the offline phase, however, greatly affects the localization accuracy; for instance, the UJIIndoorLoc is known to have the issue of uneven spatial distribution of RPs over buildings and floors. Data augmentation has been proposed as a feasible solution to not only improve the smaller number and the uneven distribution of RPs in the existing fingerprint databases but also reduce the labor and time costs of constructing new fingerprint databases. In this paper, we propose the multidimensional augmentation of fingerprint data for indoor localization in a large-scale building complex based on Multi-Output Gaussian Process (MOGP) and systematically investigate the impact of augmentation ratio as well as MOGP kernel functions and models with their hyperparameters on the performance of indoor localization using the UJIIndoorLoc database and the state-of-the-art neural network indoor localization model based on a hierarchical RNN. The investigation based on experimental results suggests that we can generate synthetic RSSI fingerprint data up to ten times the original data -- i.e., the augmentation ratio of 10 -- through the proposed multidimensional MOGP-based data augmentation without significantly affecting the indoor localization performance compared to that of the original data alone, which extends the spatial coverage of the combined RPs and thereby could improve the localization performance at the locations that are not part of the test dataset. | ['Jeremy Smith', 'Kyeong Soo Kim', 'Sihao Li', 'Zhe Tang'] | 2022-11-19 | null | null | null | null | ['indoor-localization'] | ['computer-vision'] | [ 1.77923683e-02 -3.24485987e-01 3.21643412e-01 -2.05740958e-01
-6.74458861e-01 -4.52630639e-01 5.44987880e-02 1.64852012e-02
-3.98662776e-01 8.57519448e-01 -1.05772361e-01 -3.59521359e-01
-6.89565063e-01 -1.14559913e+00 -9.39792216e-01 -9.02439475e-01
-4.27319445e-02 3.28852713e-01 3.86766605e-02 1.24502622e-01
6.31827936e-02 7.24662721e-01 -1.59317589e+00 -4.17387545e-01
1.09959579e+00 1.13371742e+00 4.43424404e-01 3.15647423e-01
4.72449400e-02 1.47060364e-01 -8.71385932e-01 -4.34958786e-02
2.29015037e-01 2.78025150e-01 -3.70462309e-03 -5.83613396e-01
2.22032383e-01 -2.19995677e-01 -4.71497267e-01 6.65711343e-01
9.48803961e-01 3.33346605e-01 3.68492275e-01 -1.14666522e+00
-4.69340920e-01 4.21139717e-01 -4.70725417e-01 -1.84683904e-01
2.60834157e-01 -5.04097402e-01 1.88652754e-01 -5.69354355e-01
5.46173900e-02 7.58257449e-01 1.28344166e+00 -1.46657392e-01
-1.19666612e+00 -8.43561828e-01 -2.27821246e-01 -8.62262025e-02
-2.03032756e+00 -1.38059095e-01 7.91988373e-01 -1.14477850e-01
2.57701576e-01 2.97204584e-01 2.42393598e-01 1.34829319e+00
1.54540353e-02 4.42323610e-02 9.28027689e-01 -3.64083588e-01
2.43630216e-01 5.20119444e-02 -8.14779401e-02 4.56171513e-01
6.50979280e-01 5.02954423e-02 -2.43610844e-01 -4.39334840e-01
1.00084054e+00 2.33674049e-01 -2.01011702e-01 -3.02427053e-01
-1.24983299e+00 2.80875027e-01 5.19587696e-01 4.87481087e-01
-5.00074327e-01 4.14736211e-01 -1.32007644e-01 -3.65074098e-01
1.07511543e-02 5.74633598e-01 -4.65044409e-01 -2.37116501e-01
-1.03989053e+00 8.12503323e-02 6.57831490e-01 1.18217814e+00
8.35407495e-01 -4.67061587e-02 -3.31505686e-01 1.02547038e+00
3.45661461e-01 1.20172298e+00 2.75417686e-01 -8.55416834e-01
8.75046432e-01 4.27511424e-01 5.32796383e-01 -1.54238367e+00
-6.82424545e-01 -9.53383327e-01 -1.06338370e+00 -5.83333313e-01
4.68172193e-01 -4.77596492e-01 -6.34677112e-01 1.81733930e+00
2.12973237e-01 3.79539818e-01 -2.01822311e-01 3.38895321e-01
4.69178408e-01 6.15945220e-01 -1.74183056e-01 2.31703743e-01
9.16982949e-01 -5.43073416e-01 -4.75429118e-01 1.73134748e-02
2.85615474e-01 -6.48860753e-01 9.46572959e-01 9.01837051e-02
-3.45457196e-01 -1.01369250e+00 -1.13172340e+00 5.38831651e-01
-3.92959416e-01 5.75907171e-01 4.54675287e-01 1.26354277e+00
-8.50564361e-01 4.40398097e-01 -7.10464954e-01 -1.58762455e-01
1.31041870e-01 5.52574873e-01 -2.60828406e-01 -3.89311045e-01
-1.17434871e+00 3.82030606e-01 1.09873973e-01 5.16220212e-01
-1.90848336e-01 -6.63833737e-01 -5.75539172e-01 2.29044825e-01
8.50087684e-03 -3.42494518e-01 5.73928654e-01 2.17733346e-02
-1.20628130e+00 -3.79156917e-01 -2.04769626e-01 -6.57658428e-02
3.37412208e-01 1.83866471e-02 -7.04318106e-01 -3.15040320e-01
3.72534245e-01 2.32025385e-01 3.59460294e-01 -1.30132174e+00
-5.33131897e-01 -4.15877432e-01 -2.71066427e-01 -1.55288130e-01
-2.49795079e-01 -5.75625658e-01 -5.54676831e-01 -5.98104835e-01
6.03048801e-01 -1.32576895e+00 -3.35555822e-01 -5.61810315e-01
-5.42622685e-01 3.85540545e-01 6.06602252e-01 -7.28916585e-01
1.16301095e+00 -2.24448156e+00 -7.08905935e-01 9.57570076e-01
-3.49957317e-01 -9.62427184e-02 -5.03868610e-02 4.10884112e-01
3.07296991e-01 1.14118502e-01 1.04565278e-01 -3.19798827e-01
-1.29610719e-02 1.25171810e-01 4.48922217e-02 4.42453861e-01
-6.03800952e-01 4.32943165e-01 -8.47827673e-01 -1.50276288e-01
2.90202290e-01 7.76679933e-01 -2.77097911e-01 -7.04604089e-02
4.56651390e-01 6.86346114e-01 -6.35014892e-01 6.45897150e-01
1.06347477e+00 -1.14106707e-01 5.95400762e-03 -4.19175357e-01
-3.12481910e-01 -2.07287576e-02 -1.63082790e+00 1.49942935e+00
-7.44648516e-01 4.33857232e-01 -2.97224373e-01 -5.32190144e-01
1.26860142e+00 2.70463109e-01 7.29293287e-01 -8.57649505e-01
-1.27853200e-01 3.62049669e-01 -2.82233596e-01 -1.83672249e-01
5.45997202e-01 4.55177784e-01 -2.32597247e-01 1.57686055e-01
-3.51048708e-01 3.83155584e-01 -8.90269503e-02 -5.03413677e-01
1.16482520e+00 5.03500253e-02 -3.21805060e-01 -1.06250256e-01
6.26916945e-01 -5.37324548e-01 5.02813756e-01 1.28512967e+00
2.86448985e-01 5.92733026e-01 -4.71291319e-02 1.10868879e-01
-7.85141647e-01 -1.06737697e+00 -4.83673304e-01 7.40935624e-01
3.08329880e-01 8.33661258e-02 -4.65955704e-01 -2.90012240e-01
3.40686619e-01 6.52409554e-01 -4.01037782e-01 2.80684382e-01
-5.05673289e-01 -8.70872736e-01 1.21172774e+00 5.20960867e-01
9.45889056e-01 -5.61322093e-01 -1.56668857e-01 2.55511254e-01
-4.38141197e-01 -1.18203211e+00 -1.42033741e-01 2.73445010e-01
-5.37792087e-01 -7.35802531e-01 -7.76496649e-01 -4.83414620e-01
9.39806044e-01 4.54155684e-01 2.91765094e-01 -2.59062856e-01
3.18195969e-01 4.22628015e-01 -1.95103452e-01 -2.59640366e-01
-1.37672317e-03 3.71108025e-01 1.87805519e-01 1.20197706e-01
-2.15674698e-01 -8.60429883e-01 -6.38620436e-01 9.16284263e-01
-4.54342782e-01 -2.93537349e-01 7.26788819e-01 5.12452304e-01
6.54510617e-01 5.45674324e-01 5.60154974e-01 -4.75240916e-01
5.60599387e-01 -6.19483054e-01 -8.08494508e-01 3.31922740e-01
-6.40046895e-01 7.46353343e-02 7.39300013e-01 -3.34249616e-01
-1.00091064e+00 -4.89921346e-02 -2.20087618e-01 2.00341418e-02
-1.47382572e-01 4.48817462e-01 -5.57042420e-01 -6.91335499e-01
5.65271199e-01 2.82115757e-01 -4.12089735e-01 -5.67591667e-01
9.60901678e-02 7.51336336e-01 4.72948998e-01 -8.37569714e-01
9.40670907e-01 3.36328208e-01 4.15679157e-01 -9.59792435e-01
-2.48517469e-01 -5.26125431e-01 -4.06528801e-01 6.04414009e-02
3.24716747e-01 -7.62799919e-01 -9.75468159e-01 4.42507416e-01
-1.02366543e+00 4.10423726e-02 1.21689282e-01 7.07916379e-01
-2.01001003e-01 3.40221524e-01 -2.06227437e-01 -7.40522623e-01
-1.00611866e-01 -1.15653634e+00 6.86866820e-01 4.00080770e-01
1.30904064e-01 -5.64292192e-01 8.86892453e-02 4.17217523e-01
9.12783980e-01 3.48685741e-01 7.21410930e-01 -4.68533009e-01
-6.81526780e-01 -7.01475620e-01 -2.10193872e-01 2.78202623e-01
2.28995398e-01 -3.44183385e-01 -1.00299096e+00 -1.56149343e-01
-1.45987913e-01 5.14232576e-01 -4.36887480e-02 5.77712059e-01
1.34898078e+00 -1.25196368e-01 -5.53454638e-01 7.71576822e-01
1.53318989e+00 3.85104865e-01 7.21534967e-01 5.03825843e-01
6.60849810e-01 2.21001834e-01 7.05099046e-01 3.98954928e-01
3.04105550e-01 8.06933761e-01 3.25164080e-01 -8.42623487e-02
2.12945968e-01 -5.58680594e-01 -2.64269322e-01 4.84930426e-01
-3.32371324e-01 -3.74948055e-01 -8.79233778e-01 2.97293901e-01
-1.72990191e+00 -7.55800307e-01 -2.04004467e-01 2.71441483e+00
2.41901353e-01 -1.80026665e-01 -3.51497710e-01 3.19949329e-01
8.88053000e-01 1.01793406e-03 -1.39762461e-01 1.26509726e-01
1.21313788e-01 1.75259128e-01 1.24550939e+00 2.49154493e-01
-9.92167115e-01 1.92391098e-01 5.12021399e+00 7.80359089e-01
-1.07931328e+00 1.00719355e-01 2.58612633e-01 1.76845983e-01
-1.13319345e-01 -3.58445197e-01 -1.00607145e+00 1.00009024e+00
1.05560076e+00 5.92472076e-01 5.16961336e-01 1.09715796e+00
3.63283843e-01 -2.09538847e-01 -5.95026433e-01 1.10859966e+00
-2.97649413e-01 -1.16542590e+00 -4.43954378e-01 4.64348704e-01
7.78327048e-01 1.22339696e-01 1.95551738e-01 3.39055002e-01
-3.32734287e-01 -6.90730810e-01 5.53612113e-01 6.57479048e-01
7.40700424e-01 -9.37877893e-01 1.15866303e+00 3.55448782e-01
-1.26024103e+00 -3.09318751e-01 -3.68657678e-01 4.29180264e-01
9.09317434e-02 6.16326392e-01 -9.14111793e-01 6.90938175e-01
5.95658302e-01 -1.99438691e-01 -7.59996474e-01 1.52668405e+00
-1.50618434e-01 5.08503914e-01 -8.60692501e-01 -1.64277807e-01
-7.51974154e-03 -1.83656484e-01 2.21551880e-01 9.27678466e-01
1.08038795e+00 -3.86954546e-01 -1.01106852e-01 6.35303676e-01
-1.52028473e-02 -6.33141249e-02 -3.74859810e-01 4.40622747e-01
1.24461639e+00 9.58565116e-01 -4.72863257e-01 2.77546376e-01
-2.24972531e-01 5.38852155e-01 -2.78730363e-01 8.13271821e-01
-1.05205190e+00 -6.24737382e-01 2.98273355e-01 4.29829091e-01
4.40816492e-01 -4.69377697e-01 -2.17572212e-01 -4.11575764e-01
1.89484879e-01 -4.45869684e-01 -3.99423331e-01 -4.88170356e-01
-7.96359479e-01 3.99031609e-01 -2.13911697e-01 -1.08068454e+00
-6.46310970e-02 -1.76075086e-01 -2.43338659e-01 1.05512035e+00
-1.12754893e+00 -1.27532876e+00 -7.36476362e-01 5.34198225e-01
-2.73290515e-01 1.03418142e-01 9.31492984e-01 1.06067598e+00
-5.87077439e-01 8.74682069e-01 9.92074966e-01 4.20803763e-02
4.64309841e-01 -7.87384570e-01 3.72774631e-01 8.15584898e-01
7.58126825e-02 9.50078487e-01 6.03529692e-01 -6.76585674e-01
-1.23617816e+00 -1.09644365e+00 5.73877454e-01 -2.75289774e-01
1.48993269e-01 -4.22002941e-01 -4.28598404e-01 3.53778660e-01
-7.79432654e-01 -1.77526623e-02 7.32598245e-01 3.05932820e-01
1.74278617e-01 -6.78118110e-01 -1.43663085e+00 4.48351711e-01
8.50074232e-01 -4.86516088e-01 1.52149320e-01 -7.46152597e-03
3.98105145e-01 -3.06270808e-01 -1.01500547e+00 5.96589029e-01
9.22178328e-01 -7.66973138e-01 1.49885023e+00 5.54351389e-01
-2.71188468e-01 -6.46383047e-01 -5.77963650e-01 -9.24587846e-01
-4.23163772e-01 -2.03370079e-01 6.29770057e-03 1.63882577e+00
3.99538428e-01 -9.97089624e-01 9.29969251e-01 6.95316613e-01
8.14062133e-02 -6.12849295e-01 -1.12103617e+00 -9.01893377e-01
-8.06884944e-01 -6.31636024e-01 1.05324173e+00 4.77500379e-01
-7.37534702e-01 -2.05211148e-01 -2.76296437e-01 8.57996285e-01
7.08675325e-01 -3.09742361e-01 1.04861367e+00 -1.26035249e+00
-3.05558473e-01 1.61397219e-01 -3.91015500e-01 -1.14025795e+00
-3.95785153e-01 -3.50707293e-01 1.99568376e-01 -1.59889090e+00
-3.99254233e-01 -1.42016602e+00 -5.24714351e-01 1.87335536e-01
2.45845258e-01 1.30303845e-01 -8.99733007e-02 1.95269763e-01
-3.05433214e-01 3.83307427e-01 8.39380860e-01 -1.06183812e-02
-5.17246783e-01 8.01675856e-01 -4.45679307e-01 5.17061174e-01
6.15552187e-01 -6.89046144e-01 -5.13302922e-01 -2.93492615e-01
2.36679271e-01 1.32351115e-01 3.46573085e-01 -1.77483976e+00
3.53665888e-01 1.25005811e-01 7.93651938e-01 -8.33211720e-01
4.91663933e-01 -1.21180284e+00 8.13699901e-01 1.41434282e-01
1.51473030e-01 -4.94629424e-03 2.11328208e-01 8.12210262e-01
7.95410424e-02 -2.69340336e-01 2.95165628e-01 2.74412841e-01
-2.68437952e-01 1.04541764e-01 -2.00621545e-01 -6.12160563e-01
6.22626841e-01 -4.17983949e-01 -3.07269633e-01 -3.00560206e-01
-2.64260471e-01 -2.00512424e-01 4.68358904e-01 2.76724458e-01
2.76144028e-01 -1.32727766e+00 -1.26468418e-02 3.03635687e-01
-8.37020278e-02 -7.89852962e-02 3.95119280e-01 8.03433120e-01
-6.09728158e-01 7.15786338e-01 -3.75350192e-02 -4.25448507e-01
-9.39378083e-01 1.50250435e-01 3.44858199e-01 -2.57135779e-01
-1.71507373e-01 6.08833432e-01 -1.94639966e-01 -8.47855270e-01
5.61197460e-01 -5.72660148e-01 -7.87776262e-02 -2.30097264e-01
8.18551704e-02 8.87813687e-01 7.03998953e-02 -4.17674273e-01
-4.17975903e-01 7.17128098e-01 5.59443653e-01 4.25467305e-02
1.04563892e+00 -3.41642380e-01 3.08365487e-02 7.97064304e-02
9.94319677e-01 5.85015655e-01 -8.68142486e-01 1.39723539e-01
-1.09202169e-01 -5.94568133e-01 -1.65707782e-01 -7.96144009e-01
-6.58460796e-01 3.72163504e-01 1.09860504e+00 9.31931958e-02
6.87603533e-01 -4.40200806e-01 7.51561642e-01 6.09232008e-01
1.02800226e+00 -9.90088105e-01 -4.07360852e-01 2.43254349e-01
4.69256759e-01 -8.35678220e-01 -1.17719933e-01 -2.40600735e-01
7.12176934e-02 8.98072660e-01 1.69920892e-01 1.75339952e-01
7.41156876e-01 8.99668857e-02 -2.19543502e-01 1.74307674e-01
6.35237098e-01 1.85433432e-01 4.40157279e-02 8.03151011e-01
9.66324210e-02 2.02711210e-01 9.41961724e-03 9.43618357e-01
-2.66208291e-01 -2.70896479e-02 5.37684262e-02 7.73421168e-01
-2.26880208e-01 -1.18399084e+00 -9.29873109e-01 4.65574414e-01
-2.90677994e-01 3.79877314e-02 5.50815463e-01 6.40211642e-01
6.53196752e-01 1.10344398e+00 -3.28114957e-01 -5.52291870e-01
5.21377087e-01 -3.04670095e-01 2.92454213e-01 3.11096082e-03
-2.08579555e-01 -2.07440183e-01 9.26269069e-02 -2.95586228e-01
-4.46421467e-02 -4.17155266e-01 -1.12791264e+00 -4.01370704e-01
-5.63847244e-01 3.12073916e-01 1.32604420e+00 7.69435883e-01
6.48780048e-01 5.67873895e-01 7.98418283e-01 -8.97327602e-01
-3.90321642e-01 -9.28069293e-01 -7.30984926e-01 -2.50211447e-01
-2.31673755e-03 -8.66738498e-01 -2.66341865e-01 -7.08530068e-01] | [6.402682781219482, 0.9253554940223694] |
737e0159-d4fa-458c-b59f-618d2a651ec6 | data-mining-in-clinical-trial-text | 2001.11268 | null | https://arxiv.org/abs/2001.11268v1 | https://arxiv.org/pdf/2001.11268v1.pdf | Data Mining in Clinical Trial Text: Transformers for Classification and Question Answering Tasks | This research on data extraction methods applies recent advances in natural language processing to evidence synthesis based on medical texts. Texts of interest include abstracts of clinical trials in English and in multilingual contexts. The main focus is on information characterized via the Population, Intervention, Comparator, and Outcome (PICO) framework, but data extraction is not limited to these fields. Recent neural network architectures based on transformers show capacities for transfer learning and increased performance on downstream natural language processing tasks such as universal reading comprehension, brought forward by this architecture's use of contextualized word embeddings and self-attention mechanisms. This paper contributes to solving problems related to ambiguity in PICO sentence prediction tasks, as well as highlighting how annotations for training named entity recognition systems are used to train a high-performing, but nevertheless flexible architecture for question answering in systematic review automation. Additionally, it demonstrates how the problem of insufficient amounts of training annotations for PICO entity extraction is tackled by augmentation. All models in this paper were created with the aim to support systematic review (semi)automation. They achieve high F1 scores, and demonstrate the feasibility of applying transformer-based classification methods to support data mining in the biomedical literature. | ['Julian P. T. Higgins', 'Julie Weeds', 'Lena Schmidt'] | 2020-01-30 | null | null | null | null | ['pico', 'entity-extraction'] | ['natural-language-processing', 'natural-language-processing'] | [ 6.69791460e-01 8.32745373e-01 -6.67115569e-01 -3.10745299e-01
-1.15236485e+00 -2.33353525e-01 5.28357506e-01 1.06088686e+00
-9.77927804e-01 8.15660298e-01 6.64107203e-01 -8.66119385e-01
-4.73040104e-01 -4.95891064e-01 -5.58350503e-01 -3.51490706e-01
-1.15330480e-01 4.10306782e-01 -2.76704341e-01 -2.13834018e-01
2.36522108e-01 2.54727393e-01 -1.04765642e+00 5.54391801e-01
8.10634971e-01 6.84671998e-01 2.62427032e-01 6.57866538e-01
-3.25546741e-01 7.86016583e-01 -6.11237705e-01 -5.15074968e-01
-4.61552411e-01 -2.65170246e-01 -1.00196898e+00 -6.12756670e-01
1.63485274e-01 -1.20838746e-01 4.79259565e-02 6.77290440e-01
8.55716169e-01 -2.55527705e-01 7.65741646e-01 -7.12933183e-01
-7.86798835e-01 1.02493966e+00 1.75008059e-01 3.27997178e-01
4.83283013e-01 5.86191155e-02 1.19164836e+00 -1.00817287e+00
1.06346512e+00 9.03176606e-01 7.95369923e-01 7.77662814e-01
-8.92345846e-01 -5.68128347e-01 -2.31350027e-02 1.78036705e-01
-7.37496376e-01 -5.12985826e-01 2.40142033e-01 -5.56018949e-01
1.73968160e+00 7.77878687e-02 5.54175735e-01 1.45649254e+00
8.19429815e-01 6.51397049e-01 6.72568202e-01 -6.96747661e-01
3.17177474e-01 2.71550000e-01 3.86762619e-01 5.98814249e-01
4.89823490e-01 -1.00744493e-01 -5.00864863e-01 -2.33369112e-01
8.02231729e-02 -1.96176365e-01 -2.50956744e-01 2.54048128e-03
-1.42969120e+00 1.00371599e+00 3.55060518e-01 4.73263472e-01
-5.45113742e-01 -1.76842928e-01 9.09169793e-01 1.92235678e-01
3.89654487e-01 1.00011945e+00 -9.76561069e-01 5.33156144e-03
-9.05036092e-01 1.96070187e-02 9.90715146e-01 9.07433867e-01
-6.07122034e-02 -1.99865565e-01 -3.46329629e-01 8.26781154e-01
1.91568241e-01 3.12226117e-01 9.17201817e-01 -4.04794693e-01
9.53885853e-01 7.74433434e-01 -3.57937008e-01 -6.97597086e-01
-1.17233098e+00 -3.05346787e-01 -9.25716102e-01 -2.53573686e-01
-3.42679881e-02 -4.74207312e-01 -8.89136672e-01 1.71112502e+00
1.84273645e-01 -5.79015017e-01 5.65052032e-01 4.85342979e-01
1.42068815e+00 4.51670974e-01 7.38490999e-01 -1.09453447e-01
2.00406313e+00 -7.18593299e-01 -1.24467266e+00 -2.75943875e-01
1.34191191e+00 -4.58243072e-01 4.60146815e-01 1.33234546e-01
-1.09145796e+00 -2.11590156e-01 -1.19669676e+00 -5.66712260e-01
-1.02468967e+00 2.29751259e-01 4.22922790e-01 5.66308379e-01
-8.18496406e-01 5.68937898e-01 -5.98414421e-01 -4.47641313e-01
9.86879528e-01 4.98996884e-01 -7.58567333e-01 1.51789159e-01
-1.61605716e+00 1.52174366e+00 5.68963051e-01 1.86793461e-01
-4.10047829e-01 -1.14046955e+00 -1.18849874e+00 3.41585428e-01
2.74114281e-01 -1.14366484e+00 1.15580702e+00 -5.10621250e-01
-1.19095457e+00 9.87923384e-01 6.81726635e-02 -8.48621488e-01
-3.73849496e-02 -1.23747669e-01 -4.70312536e-01 3.18099290e-01
2.72525012e-01 7.19463229e-01 2.75549203e-01 -2.87261397e-01
-5.47057390e-01 -4.71253663e-01 -4.03136134e-01 1.82230830e-01
-5.74091136e-01 3.59300613e-01 1.93270952e-01 -6.51113570e-01
-7.21482217e-01 -4.25573111e-01 -5.65230191e-01 -2.01713115e-01
-3.11015874e-01 -5.78888476e-01 1.00976072e-01 -9.99494255e-01
1.53514886e+00 -1.72462428e+00 8.94402713e-02 -7.52076060e-02
4.85239267e-01 4.14557040e-01 -2.06263274e-01 5.88596523e-01
-3.67582113e-01 6.23525083e-01 -4.14151013e-01 -1.10498287e-01
-6.41673356e-02 -1.06988112e-02 -9.21634287e-02 1.53884813e-01
1.01711810e+00 1.23419976e+00 -1.03994930e+00 -5.83483815e-01
-2.87686288e-02 3.05859983e-01 -5.11497736e-01 1.36622742e-01
3.10535952e-02 -1.16785213e-01 -4.58646238e-01 3.69792044e-01
1.56998485e-01 -2.26686344e-01 4.14643884e-01 -1.23112500e-01
-1.41367108e-01 1.07207954e+00 -5.98132432e-01 1.79125202e+00
-7.44250178e-01 6.38886094e-01 -9.52053070e-03 -1.15183043e+00
5.98369837e-01 7.77664721e-01 4.71975505e-01 -6.56613886e-01
2.63197988e-01 4.39587086e-01 2.88159341e-01 -9.64791238e-01
2.97913253e-01 -2.77882338e-01 -1.38508633e-01 3.13517600e-01
5.75383902e-01 -4.74609993e-02 1.75290555e-01 1.21487580e-01
1.33081484e+00 -2.10969001e-02 8.91614735e-01 -4.14690197e-01
4.76869017e-01 1.89233959e-01 3.87652308e-01 7.11181641e-01
8.10314044e-02 4.56004828e-01 7.25951910e-01 -2.95443445e-01
-1.09018230e+00 -5.99278450e-01 -7.30746627e-01 6.63809359e-01
-8.90963435e-01 -6.58718348e-01 -7.06210852e-01 -6.73317313e-01
-2.07261652e-01 7.68984616e-01 -9.81291234e-01 -3.65789413e-01
-5.14179945e-01 -1.04540765e+00 6.65267110e-01 6.49813473e-01
-9.23905745e-02 -1.54868484e+00 -1.18949461e+00 6.69438183e-01
8.52308944e-02 -1.31124818e+00 -1.62194654e-01 7.41971016e-01
-9.50819671e-01 -1.41476190e+00 -8.90215099e-01 -1.09603715e+00
2.31505275e-01 -7.44002700e-01 1.14638591e+00 -2.46725425e-01
-5.66854715e-01 4.08379465e-01 -2.81498194e-01 -1.04101396e+00
-6.96050704e-01 5.68889499e-01 -1.56183258e-01 -7.56986737e-01
8.92096043e-01 -3.77487838e-02 -5.56027353e-01 -3.69934469e-01
-1.03857243e+00 4.03890423e-02 8.01088274e-01 1.41964996e+00
2.85980791e-01 -6.89901471e-01 1.24915457e+00 -1.07944107e+00
1.23434770e+00 -7.37661481e-01 -1.30684704e-01 4.04778063e-01
-8.78079593e-01 2.16189981e-01 5.90515375e-01 -2.90045232e-01
-7.86011517e-01 -3.71735901e-01 -5.30843437e-01 3.30300570e-01
-3.03754598e-01 9.61908281e-01 -2.93428022e-02 4.66746271e-01
8.99922311e-01 -1.78515404e-01 2.72425205e-01 -2.59388149e-01
3.05547446e-01 9.65183616e-01 -1.30645847e-02 -1.59063503e-01
-3.50466408e-02 -1.29309222e-01 5.79782575e-02 -9.01725233e-01
-6.78463221e-01 -3.47827762e-01 -5.78728855e-01 5.61486244e-01
1.33069527e+00 -7.97596216e-01 -6.56305254e-01 -2.00726300e-01
-1.29755139e+00 -8.04339573e-02 -5.16110122e-01 6.55179203e-01
-3.93218815e-01 8.37352574e-02 -5.07723510e-01 -5.06253958e-01
-1.00057614e+00 -1.18948913e+00 1.01389182e+00 2.13556569e-02
-6.05672657e-01 -1.17443275e+00 1.30340025e-01 9.53170285e-02
3.01515341e-01 8.02471116e-02 1.48513007e+00 -1.33711040e+00
2.67116815e-01 -2.84608692e-01 -8.59906748e-02 2.42265359e-01
2.36385331e-01 -3.69307667e-01 -7.42665291e-01 2.45363384e-01
-6.41268715e-02 -2.08627239e-01 6.55826211e-01 4.94249046e-01
1.06234348e+00 -4.70100880e-01 -5.16930044e-01 2.90319860e-01
1.05313981e+00 3.03708881e-01 3.79407912e-01 4.87263739e-01
5.67559123e-01 1.05560744e+00 1.83257014e-01 -2.31456254e-02
4.48933631e-01 4.44175571e-01 -6.44258037e-02 -2.01683223e-01
-1.39752552e-01 -2.91036256e-02 8.57373625e-02 7.53800809e-01
4.67710406e-01 -1.15505151e-01 -1.30143690e+00 8.98321569e-01
-1.54079294e+00 -5.72070360e-01 -6.25560880e-02 1.86691380e+00
1.22079945e+00 2.16029376e-01 -2.42517337e-01 -8.81674662e-02
1.57953247e-01 -3.36668223e-01 -2.79353499e-01 -1.23502803e+00
-1.71878681e-01 8.80779803e-01 5.28858900e-01 1.27394691e-01
-1.09809005e+00 5.62015653e-01 5.92935991e+00 5.74297428e-01
-7.43088126e-01 1.52822569e-01 6.38764679e-01 1.31667331e-01
-1.46987230e-01 -3.68293077e-01 -8.00345659e-01 2.52828896e-01
1.75118411e+00 -8.87085497e-02 -4.49877650e-01 3.50300193e-01
3.12245399e-01 1.02619104e-01 -1.40181911e+00 5.25779247e-01
8.38321075e-02 -1.82389963e+00 1.70484513e-01 -1.84139177e-01
3.76893044e-01 1.03965983e-01 -9.11318585e-02 3.35182726e-01
-6.15103394e-02 -1.36869776e+00 1.10542826e-01 3.41800094e-01
8.93457353e-01 -3.73068124e-01 1.26337576e+00 1.91085860e-02
-6.00344658e-01 -2.76063740e-01 -1.27681896e-01 3.21083099e-01
1.07106350e-01 4.56863910e-01 -1.41159320e+00 8.69539022e-01
6.15430236e-01 8.00481498e-01 -6.44012451e-01 9.35375273e-01
-2.92264730e-01 7.04696834e-01 -1.41222566e-01 -5.51245391e-01
4.29936409e-01 2.99550861e-01 2.54646540e-01 1.75604892e+00
1.32176504e-01 3.36308181e-02 -3.31730098e-01 6.02759063e-01
-3.92418444e-01 6.18341804e-01 -8.97510767e-01 -3.53436381e-01
7.24365637e-02 9.80836272e-01 -2.93939292e-01 -4.06631112e-01
-4.34383869e-01 3.10746491e-01 1.80704236e-01 2.59240400e-02
-2.92395025e-01 -6.82537913e-01 2.13211209e-01 6.49364144e-02
1.22024521e-01 3.51020813e-01 -5.07281601e-01 -9.33446169e-01
-4.94953580e-02 -1.17433286e+00 6.85877800e-01 -6.81511462e-01
-1.14155936e+00 6.55273974e-01 3.26504335e-02 -9.80469644e-01
-4.33368772e-01 -1.09817612e+00 -1.34771153e-01 1.07112253e+00
-1.45491123e+00 -1.05705595e+00 5.55102527e-01 3.25252265e-02
6.85812056e-01 -3.81498545e-01 1.41903543e+00 3.41517568e-01
-5.68392336e-01 6.36017919e-01 9.13948640e-02 3.16826552e-01
8.28395903e-01 -1.34976470e+00 2.16010362e-01 2.86727905e-01
-1.08079970e-01 8.38957965e-01 2.37638265e-01 -4.97714520e-01
-1.12923646e+00 -8.30105484e-01 1.65505719e+00 -7.15120733e-01
9.27478731e-01 -3.07900608e-01 -8.73349488e-01 3.60943764e-01
5.48106253e-01 -3.53297949e-01 1.26044977e+00 3.27518970e-01
-1.79407686e-01 2.61956036e-01 -1.09571135e+00 7.10203588e-01
6.93648458e-01 -5.44269860e-01 -1.28019786e+00 5.28637528e-01
7.47701049e-01 -4.05935884e-01 -1.25230467e+00 4.55275387e-01
3.46287847e-01 9.90713909e-02 8.77993286e-01 -1.48589730e+00
1.11789787e+00 3.70484054e-01 4.15071279e-01 -1.21462727e+00
9.13535769e-04 -4.50970292e-01 -1.94554050e-02 8.74010921e-01
1.06714404e+00 -5.19375563e-01 3.55172575e-01 4.53293115e-01
-2.86799252e-01 -1.17514956e+00 -1.17201900e+00 -8.61731172e-02
6.86443865e-01 -2.23689914e-01 3.49085033e-01 9.16893423e-01
5.60273767e-01 9.25187528e-01 2.21811607e-01 -1.82171792e-01
1.70436084e-01 -2.68590689e-01 7.99363106e-02 -1.15530121e+00
3.05029124e-01 -6.99929297e-01 -3.64478141e-01 -2.54109561e-01
2.47250900e-01 -1.32106197e+00 -3.58282886e-02 -2.01349998e+00
2.68455520e-02 -9.57690775e-02 -4.12298143e-01 6.11760378e-01
-2.47129917e-01 -3.06601614e-01 -1.72914118e-01 -4.34243321e-01
-2.68369794e-01 4.01487142e-01 9.04260397e-01 -3.74585688e-01
-1.13525674e-01 -1.66213438e-01 -9.14185941e-01 4.07967597e-01
7.29629815e-01 -7.89904118e-01 -9.02769044e-02 -4.06263947e-01
6.06349528e-01 1.17988653e-01 1.70646489e-01 -5.42294800e-01
3.12829584e-01 3.66564572e-01 3.51255715e-01 -2.76930928e-01
-2.22657114e-01 -9.15695906e-01 -4.56276804e-01 6.17249310e-01
-9.88158703e-01 3.43476027e-01 6.67023838e-01 3.31118166e-01
-2.25801945e-01 -6.82065427e-01 9.90866646e-02 -1.09931991e-01
-1.93077341e-01 -7.93429613e-02 -8.13452959e-01 2.27499947e-01
5.48382699e-01 6.28029630e-02 -2.77799100e-01 1.70530334e-01
-8.91638577e-01 5.69866598e-01 -4.56633061e-01 6.84774280e-01
7.43805707e-01 -9.18161273e-01 -9.32333648e-01 -3.07900440e-02
4.04894024e-01 9.79088992e-03 1.62693650e-01 9.95504379e-01
-3.91019583e-01 9.36449289e-01 -1.48283884e-01 -2.72501111e-01
-1.16124821e+00 6.94927514e-01 2.15415806e-01 -9.32349920e-01
-7.42888391e-01 5.67066967e-01 -1.12245888e-01 -6.96300089e-01
2.09256619e-01 -7.55979240e-01 -7.39180148e-01 6.01458073e-01
4.93715554e-01 -1.05932578e-01 6.48965061e-01 -5.35710976e-02
-6.97339773e-01 3.31736416e-01 -3.13127041e-01 1.08810708e-01
1.69131899e+00 3.49638194e-01 -2.28462517e-02 2.54052699e-01
1.43320441e+00 -2.28208289e-01 -1.74786061e-01 1.77612361e-02
5.73126197e-01 7.08621740e-01 5.16550392e-02 -1.20727956e+00
-4.30065840e-01 1.19663310e+00 7.13460028e-01 -8.07617158e-02
8.80141258e-01 -2.30910450e-01 3.85097444e-01 6.77957475e-01
-2.94387788e-01 -1.26605904e+00 -5.24712980e-01 4.84656334e-01
8.35796714e-01 -1.30738258e+00 2.23818004e-01 8.25212076e-02
-5.53833067e-01 1.52504718e+00 2.25009918e-01 2.28210539e-01
7.74294198e-01 3.87304455e-01 -1.69656366e-01 -6.39651656e-01
-8.04788888e-01 4.00716029e-02 5.34266233e-01 5.78099310e-01
7.46731758e-01 -7.22341090e-02 -8.19431603e-01 1.05748320e+00
-8.65148380e-02 2.34648883e-01 5.51385522e-01 8.52152050e-01
1.19843997e-01 -1.16103649e+00 -3.55753750e-02 8.94437969e-01
-1.02734578e+00 -6.17144823e-01 -1.84290275e-01 8.67927730e-01
-2.48313528e-02 7.75677145e-01 -1.35775581e-01 1.51030108e-01
5.08147061e-01 4.23291087e-01 1.95202336e-01 -9.95635450e-01
-1.41607296e+00 -3.56310695e-01 5.09304285e-01 -2.86712497e-01
-4.50538725e-01 -4.07686085e-01 -1.12744200e+00 6.27613783e-01
-2.71025419e-01 3.90390843e-01 8.16907823e-01 9.68743801e-01
6.05250001e-01 1.18284404e+00 -1.10483207e-02 -1.10123217e-01
-5.59975505e-01 -1.09744775e+00 2.13799074e-01 1.16177440e-01
5.56697667e-01 -2.17565924e-01 -1.19451806e-01 -1.13447279e-01] | [8.492820739746094, 8.705096244812012] |
6fc220c3-d998-4b0b-9e85-b2c68f0fb557 | fine-grained-identity-preserving-landmark | 2110.04708 | null | https://arxiv.org/abs/2110.04708v2 | https://arxiv.org/pdf/2110.04708v2.pdf | Fine-grained Identity Preserving Landmark Synthesis for Face Reenactment | Recent face reenactment works are limited by the coarse reference landmarks, leading to unsatisfactory identity preserving performance due to the distribution gap between the manipulated landmarks and those sampled from a real person. To address this issue, we propose a fine-grained identity-preserving landmark-guided face reenactment approach. The proposed method has two novelties. First, a landmark synthesis network which is designed to generate fine-grained landmark faces with more details. The network refines the manipulated landmarks and generates a smooth and gradually changing face landmark sequence with good identity preserving ability. Second, several novel loss functions including synthesized face identity preserving loss, foreground/background mask loss as well as boundary loss are designed, which aims at synthesizing clear and sharp high-quality faces. Experiments are conducted on our self-collected BeautySelfie and the public VoxCeleb1 datasets. The presented qualitative and quantitative results show that our method can reenact fine-grained higher quality faces with good ID-preserved appearance details, fewer artifacts and clearer boundaries than state-of-the-art works. Code will be released for reproduction. | ['Bin Fu', 'Gang Yu', 'Tao Chen', 'Weixi Zhang', 'Youcheng Ben', 'Haichao Zhang'] | 2021-10-10 | null | null | null | null | ['face-reenactment'] | ['computer-vision'] | [ 2.39652544e-01 4.18192148e-02 1.09543823e-01 -6.50516570e-01
-4.42212790e-01 -3.59207600e-01 5.79016328e-01 -3.75322700e-01
-5.84658496e-02 7.99710989e-01 2.75045276e-01 5.76376021e-01
-1.66504040e-01 -7.38875210e-01 -5.20409703e-01 -6.86669886e-01
1.23171769e-01 2.46036783e-01 -2.45232731e-02 -3.04789841e-01
1.20678566e-01 7.13351190e-01 -1.75301921e+00 1.09869644e-01
1.01305926e+00 9.83092844e-01 -2.59436965e-01 8.69776681e-02
-3.50015908e-02 2.27400869e-01 -3.55994582e-01 -8.82074893e-01
4.93114322e-01 -4.88279253e-01 -4.15400088e-01 2.54279226e-01
1.11599112e+00 -2.19436839e-01 -7.73268491e-02 1.35719180e+00
6.20403707e-01 7.95587599e-02 4.85440314e-01 -1.51074767e+00
-1.10114527e+00 1.83871597e-01 -1.02928734e+00 -2.75108904e-01
3.31002057e-01 -2.79722679e-02 6.44053757e-01 -9.92897391e-01
8.79965782e-01 1.75452530e+00 9.84669089e-01 9.82933700e-01
-1.36110163e+00 -1.30094492e+00 1.82416230e-01 1.12571634e-01
-1.74641943e+00 -8.87278199e-01 1.10552764e+00 -2.86837369e-01
-1.69042442e-02 2.98224181e-01 4.57060844e-01 1.04491806e+00
1.36921033e-01 1.98362678e-01 1.14976931e+00 -2.81687915e-01
-8.95526335e-02 2.28481546e-01 -2.95524031e-01 1.02933395e+00
2.82954007e-01 3.20353687e-01 -5.13580739e-01 -1.30534515e-01
1.14312243e+00 -3.05638332e-02 -4.17173654e-01 -4.50255603e-01
-9.88324165e-01 5.62467813e-01 4.12594914e-01 3.86740863e-01
-2.36861914e-01 -1.81595817e-01 2.81785309e-01 1.25418961e-01
5.77085733e-01 1.97541028e-01 3.27224284e-02 2.53969491e-01
-1.13160765e+00 1.35610461e-01 3.71031910e-01 1.01174831e+00
9.18842852e-01 1.19824253e-01 -4.19341981e-01 1.15812957e+00
3.99254948e-01 5.21753311e-01 2.66944706e-01 -9.31789458e-01
-6.97972476e-02 5.26968360e-01 -5.83972670e-02 -1.44901037e+00
-2.15029448e-01 -1.97281450e-01 -1.14749157e+00 5.75633466e-01
1.91350892e-01 9.21587199e-02 -1.02683520e+00 1.94714308e+00
5.87424755e-01 3.82225215e-01 -2.44223818e-01 8.94004703e-01
1.15042126e+00 3.62689555e-01 3.90358195e-02 -1.12819687e-01
1.56512046e+00 -8.53071809e-01 -1.02162075e+00 1.26752883e-01
-3.17251772e-01 -8.63791406e-01 1.06486988e+00 2.02214196e-01
-1.23607111e+00 -8.70688736e-01 -1.01619101e+00 -1.46716908e-01
-1.78779766e-01 1.33856550e-01 3.59300584e-01 9.95022893e-01
-1.28008795e+00 5.04998982e-01 -3.45223844e-01 -3.80059421e-01
9.80451822e-01 2.49240324e-01 -8.49571824e-01 -6.22662120e-02
-9.81454372e-01 6.32520139e-01 4.63650096e-03 3.43999445e-01
-7.22979069e-01 -1.19851911e+00 -1.05545533e+00 -1.41265064e-01
1.84318006e-01 -7.31843889e-01 7.00031638e-01 -1.14964676e+00
-1.68067849e+00 1.31840682e+00 -2.18642235e-01 6.06025644e-02
9.18001056e-01 1.30720571e-01 -6.04442775e-01 5.96067756e-02
2.75470704e-01 7.92963624e-01 1.33069110e+00 -1.60014081e+00
-5.41781902e-01 -5.46214700e-01 -3.40815693e-01 -1.14882842e-01
-2.79381543e-01 -1.56933558e-04 -4.36128795e-01 -1.12594354e+00
9.53664854e-02 -5.72646916e-01 9.02799219e-02 5.83914161e-01
-3.12788874e-01 -5.19584306e-02 9.46518004e-01 -7.99441397e-01
8.70277464e-01 -2.32465959e+00 1.42749874e-02 2.68871874e-01
3.70943964e-01 1.84494585e-01 -4.72355217e-01 -2.28518564e-02
-1.64111972e-01 1.99067712e-01 -3.11146855e-01 -6.48544431e-01
1.58783756e-02 -1.68365732e-01 -4.39820141e-02 6.60127580e-01
1.55108511e-01 8.18886101e-01 -8.05933535e-01 -6.56887054e-01
1.67611822e-01 9.93381023e-01 -5.44243693e-01 1.17087439e-01
1.76654592e-01 6.37625635e-01 -1.06593087e-01 9.48273599e-01
1.29160321e+00 3.49491984e-01 -3.04512143e-01 -6.07228935e-01
1.22690536e-02 -5.93822300e-01 -1.26546657e+00 1.59224129e+00
-3.89246464e-01 4.19728249e-01 5.92675507e-01 -2.34244734e-01
1.41923952e+00 1.94483638e-01 3.41254950e-01 -7.76394188e-01
1.97196022e-01 1.15197130e-01 -4.35880899e-01 -1.59352764e-01
3.51116985e-01 -5.15524030e-01 2.64196724e-01 5.35591394e-02
-6.13552928e-02 -3.06812190e-02 -3.90759334e-02 -1.66845486e-01
3.87494951e-01 1.53954417e-01 -2.09472273e-02 -5.68390429e-01
1.03896737e+00 -5.09997129e-01 9.59116697e-01 2.65111864e-01
-3.68356109e-01 9.46309090e-01 2.38942012e-01 -4.92665708e-01
-1.01205599e+00 -1.24557984e+00 -4.23352391e-01 8.33972931e-01
3.94750029e-01 -2.29528531e-01 -9.71950352e-01 -5.85245311e-01
1.32844439e-02 3.09154421e-01 -9.94802177e-01 -2.74370760e-01
-6.37252092e-01 -3.79125804e-01 6.26592934e-01 2.33633772e-01
1.08740032e+00 -1.23306191e+00 -3.42531508e-04 -5.65928966e-03
-6.76211044e-02 -8.59607399e-01 -1.03126895e+00 -1.00648320e+00
-5.35187006e-01 -1.21222782e+00 -9.12646830e-01 -1.13120162e+00
1.13503325e+00 -1.07562095e-01 1.00339293e+00 2.38060236e-01
-5.68593204e-01 2.00338051e-01 -2.12192759e-01 -1.15660757e-01
-3.74496460e-01 -3.70521247e-01 2.27563664e-01 7.39935219e-01
9.71340463e-02 -5.80012560e-01 -6.54121459e-01 4.78686988e-01
-8.11240554e-01 1.83467567e-02 3.07893723e-01 9.16763783e-01
5.74559093e-01 2.70555675e-01 7.34903634e-01 -8.37403357e-01
6.77097917e-01 8.26553777e-02 -6.74770594e-01 4.52524006e-01
-6.21941209e-01 -9.76624861e-02 6.73991084e-01 -4.91193593e-01
-1.41860819e+00 -1.01324923e-01 -2.61249393e-01 -5.14857769e-01
-2.37942696e-01 -4.75982785e-01 -4.94172335e-01 -5.23454309e-01
4.75080162e-01 2.40023315e-01 3.22652161e-01 -6.36219144e-01
5.67537546e-01 3.70004326e-01 9.30467248e-01 -7.72666514e-01
1.20332968e+00 8.07356417e-01 -5.42579964e-02 -7.64337778e-01
-2.71848232e-01 6.56674057e-02 -7.05754101e-01 -2.72754312e-01
6.58547819e-01 -6.05069339e-01 -9.82683182e-01 7.43253589e-01
-9.32797253e-01 1.83456670e-02 -4.13110852e-01 -5.58113232e-02
-5.74434102e-01 4.14180219e-01 -5.03745079e-01 -5.52308738e-01
-6.53742135e-01 -9.03793275e-01 1.07767808e+00 6.51030004e-01
-4.37628850e-02 -7.06416249e-01 1.16330206e-01 1.95932508e-01
5.33875883e-01 6.54251814e-01 7.30303884e-01 1.01600125e-01
-3.42982322e-01 8.98451917e-03 -4.66612369e-01 3.22051197e-01
7.54403472e-01 2.31709644e-01 -9.41327870e-01 -5.36278665e-01
-9.11034048e-02 2.64025517e-02 6.97999001e-01 2.80810714e-01
9.51650143e-01 -5.17506719e-01 -3.21076274e-01 9.98187661e-01
1.31688809e+00 1.66347563e-01 7.88502097e-01 1.22377157e-01
7.91180074e-01 9.09129202e-01 5.67665756e-01 3.75566006e-01
1.51169211e-01 6.22385502e-01 1.24936648e-01 -4.28657740e-01
-6.05103135e-01 -5.30454218e-01 5.23507893e-02 1.72048688e-01
-7.98140466e-02 2.73372144e-01 -4.08215344e-01 5.98370910e-01
-1.56596804e+00 -1.01068878e+00 2.27271348e-01 2.11962676e+00
8.86123598e-01 -4.05006796e-01 2.00111583e-01 6.79536164e-02
1.18242753e+00 1.56128109e-01 -4.70250160e-01 -1.53760836e-01
-2.31875151e-01 3.04424942e-01 2.38577239e-02 7.28302538e-01
-9.82052982e-01 1.13896167e+00 5.70264959e+00 1.03292143e+00
-1.13102937e+00 2.01606810e-01 8.13697755e-01 -3.16583812e-02
-2.77181447e-01 -4.62492436e-01 -7.79614151e-01 5.43448687e-01
1.98194116e-01 -2.81025797e-01 3.65028560e-01 7.06681609e-01
1.70800373e-01 4.13482666e-01 -8.70639145e-01 1.39872479e+00
3.54109824e-01 -1.45941174e+00 2.67157286e-01 -1.74943864e-01
8.62774968e-01 -8.59841943e-01 3.07895899e-01 -1.20712891e-01
5.82170449e-02 -1.30049038e+00 8.32030237e-01 8.26115131e-01
1.25614429e+00 -1.06169081e+00 4.80726153e-01 -3.60254347e-01
-1.47474265e+00 1.74237058e-01 -3.81259978e-01 3.87460589e-01
9.95442495e-02 4.48933691e-01 -5.31407654e-01 5.75668156e-01
7.79160440e-01 6.79540575e-01 -6.35928631e-01 1.05406225e+00
-1.01449825e-01 -6.67608976e-02 -1.24068655e-01 3.08907121e-01
-1.66474819e-01 -4.77156848e-01 4.43793058e-01 1.03043509e+00
2.92112619e-01 1.34337783e-01 -1.36489987e-01 1.27234638e+00
-3.45736682e-01 2.75176227e-01 -5.03366947e-01 4.41534489e-01
6.43865287e-01 1.46284342e+00 -6.50668204e-01 -3.92696261e-02
-9.35074165e-02 1.16397023e+00 7.63211846e-02 2.62604952e-01
-7.71694005e-01 -5.05245268e-01 9.66247976e-01 4.06635910e-01
-2.15261169e-02 1.18242197e-01 -3.14303637e-01 -8.62418950e-01
4.03586440e-02 -8.90528381e-01 2.80246258e-01 -4.64617163e-01
-1.73088336e+00 1.05977118e+00 -2.13210955e-01 -9.73156750e-01
2.57491410e-01 -2.34863952e-01 -6.79961681e-01 9.24329162e-01
-1.44800365e+00 -1.56555557e+00 -6.63117409e-01 8.18405569e-01
3.38319480e-01 -3.30196172e-01 5.11872828e-01 6.35616243e-01
-5.52523613e-01 1.17326415e+00 -1.69374928e-01 2.50221759e-01
1.00930643e+00 -7.47694850e-01 3.89287561e-01 7.55566835e-01
-1.06427357e-01 6.80084467e-01 4.32198137e-01 -6.51412785e-01
-9.20574188e-01 -1.23025286e+00 6.47431076e-01 -2.87324339e-01
4.46797945e-02 -5.73440373e-01 -9.25502717e-01 5.21991253e-01
6.51903376e-02 2.27032781e-01 3.03491145e-01 -1.87168002e-01
-4.68858153e-01 -5.55617213e-01 -1.97893107e+00 7.50366151e-01
1.25871599e+00 -3.65853041e-01 -4.69895154e-01 -9.86790061e-02
3.64681035e-01 -1.37507021e-01 -8.52549314e-01 6.36593342e-01
8.22454453e-01 -1.11449528e+00 1.13062418e+00 -1.97048083e-01
-2.43181046e-02 -5.34373164e-01 1.88649237e-01 -1.08188760e+00
-6.41502261e-01 -8.98528874e-01 3.99380326e-01 1.90096867e+00
-5.69219235e-03 -8.14312637e-01 8.12908649e-01 5.21096706e-01
2.22894058e-01 -5.52746952e-01 -1.04477954e+00 -7.36991107e-01
-4.29618210e-02 2.91669011e-01 1.09029543e+00 1.06026614e+00
-4.28839684e-01 1.59998480e-02 -4.88141596e-01 3.84054892e-02
1.11483741e+00 8.08194578e-02 7.22449243e-01 -1.30387616e+00
5.03457129e-01 -6.16738975e-01 -4.60215628e-01 -4.93192196e-01
3.27495247e-01 -6.62952423e-01 8.02571923e-02 -1.17418742e+00
1.11584291e-01 -8.05581093e-01 -9.78306904e-02 4.39342171e-01
-3.02486233e-02 9.09410596e-01 1.52500123e-01 -1.46114007e-01
-1.89330861e-01 9.21795547e-01 1.56351960e+00 -2.18368247e-01
-2.47628480e-01 -2.21507341e-01 -8.25665891e-01 6.85952187e-01
5.85518003e-01 -2.70519793e-01 -3.50158632e-01 -4.59834598e-02
-3.83420050e-01 -3.63463432e-01 4.97017264e-01 -1.05182147e+00
1.21369638e-01 -1.09426975e-01 6.24971330e-01 -3.60770732e-01
3.86757493e-01 -8.00072789e-01 5.18517792e-01 2.70268261e-01
-4.80124205e-02 -7.18448758e-02 2.80044019e-01 3.45000088e-01
-9.60200429e-02 1.14394203e-01 1.49882853e+00 -4.11853641e-02
-5.77795863e-01 7.36565351e-01 3.62730235e-01 4.32338752e-02
1.09980941e+00 -5.21765769e-01 -2.25188032e-01 -2.12197855e-01
-6.62989199e-01 -6.67158887e-03 8.67718816e-01 8.46819222e-01
9.22104478e-01 -1.71653938e+00 -1.25143421e+00 8.55156541e-01
3.34958024e-02 -2.09297895e-01 4.79801953e-01 4.64231342e-01
-5.33027589e-01 -3.82548235e-02 -8.14464211e-01 -3.71157974e-01
-1.46596360e+00 5.42394936e-01 5.05742431e-01 3.40291739e-01
-8.36222112e-01 1.12136054e+00 5.70002794e-01 -5.53115129e-01
1.77418366e-01 -3.56650911e-02 -1.58304229e-01 9.42944884e-02
7.84297407e-01 5.79452991e-01 -2.11307615e-01 -1.14448249e+00
-5.19656062e-01 1.26825809e+00 -1.45515278e-01 2.42405757e-02
1.09826446e+00 -2.29392409e-01 -4.12142903e-01 -1.83310091e-01
1.19262326e+00 3.52598101e-01 -1.43427074e+00 -1.93341330e-01
-3.63939434e-01 -1.10777938e+00 -1.78631619e-01 -6.95842743e-01
-1.45222497e+00 5.29871345e-01 9.97752249e-01 -1.83993906e-01
1.26968133e+00 -1.95883855e-01 8.49755287e-01 -4.68948692e-01
5.47807455e-01 -8.03418159e-01 6.38663918e-02 1.59105267e-02
1.35652506e+00 -1.12916827e+00 -1.53074607e-01 -7.12653041e-01
-3.14646602e-01 8.69706869e-01 7.74547637e-01 -1.80818304e-01
6.59275234e-01 1.04044780e-01 1.67250603e-01 -1.51400134e-01
-8.08436498e-02 6.19543828e-02 4.83048588e-01 9.76812482e-01
1.19890384e-01 -1.31025016e-01 -2.01123729e-01 7.60117710e-01
-5.13554931e-01 -7.38275498e-02 1.66584015e-01 3.11927438e-01
-1.56866580e-01 -1.05671513e+00 -7.08450556e-01 1.08831249e-01
-3.29153568e-01 3.68002541e-02 -3.72848898e-01 7.73833454e-01
5.10115206e-01 8.83199215e-01 6.07122518e-02 -2.15435475e-01
5.60725987e-01 -1.88331276e-01 7.74458170e-01 -2.85606891e-01
-4.53030616e-01 -1.36950716e-01 -2.97423065e-01 -5.92143238e-01
-2.37318024e-01 -4.08956259e-01 -1.12096369e+00 -7.59047210e-01
-3.50715704e-02 8.30637142e-02 2.90016830e-01 3.41903895e-01
5.21526217e-01 3.25828344e-01 7.12008297e-01 -9.95622098e-01
3.22435820e-03 -7.52548218e-01 -8.65674555e-01 6.85291409e-01
6.07404888e-01 -8.12997460e-01 -3.34258378e-01 1.87481195e-01] | [12.764107704162598, -0.03203541040420532] |
e51c2330-30ba-4016-9318-8b1ec0f806b6 | td3-with-reverse-kl-regularizer-for-offline | 2212.02125 | null | https://arxiv.org/abs/2212.02125v1 | https://arxiv.org/pdf/2212.02125v1.pdf | TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets | We consider an offline reinforcement learning (RL) setting where the agent need to learn from a dataset collected by rolling out multiple behavior policies. There are two challenges for this setting: 1) The optimal trade-off between optimizing the RL signal and the behavior cloning (BC) signal changes on different states due to the variation of the action coverage induced by different behavior policies. Previous methods fail to handle this by only controlling the global trade-off. 2) For a given state, the action distribution generated by different behavior policies may have multiple modes. The BC regularizers in many previous methods are mean-seeking, resulting in policies that select out-of-distribution (OOD) actions in the middle of the modes. In this paper, we address both challenges by using adaptively weighted reverse Kullback-Leibler (KL) divergence as the BC regularizer based on the TD3 algorithm. Our method not only trades off the RL and BC signals with per-state weights (i.e., strong BC regularization on the states with narrow action coverage, and vice versa) but also avoids selecting OOD actions thanks to the mode-seeking property of reverse KL. Empirically, our algorithm can outperform existing offline RL algorithms in the MuJoCo locomotion tasks with the standard D4RL datasets as well as the mixed datasets that combine the standard datasets. | ['TieYan Liu', 'Tao Qin', 'Jiang Bian', 'Lei Song', 'Xuyun Zhang', 'Wei Shen', 'Li Zhao', 'Chuheng Zhang', 'Yuanying Cai'] | 2022-12-05 | null | null | null | null | ['d4rl'] | ['robots'] | [-9.70742032e-02 -3.06646258e-01 -5.53846657e-01 -1.37671024e-01
-6.40383244e-01 -7.29450524e-01 4.91057783e-01 -4.09099571e-02
-7.79378414e-01 9.57691848e-01 1.22680888e-01 -8.59380588e-02
-3.32630008e-01 -6.42372847e-01 -8.21223617e-01 -1.14527738e+00
-5.13055205e-01 4.82006520e-01 2.67839372e-01 -2.97134101e-01
2.02976987e-01 2.64599919e-01 -1.43930280e+00 -6.05023094e-02
8.88814211e-01 1.08702934e+00 2.10813358e-01 5.42306244e-01
1.98660538e-01 7.45168567e-01 -6.71603084e-01 2.35811576e-01
5.89121282e-01 -7.41736352e-01 -4.06361550e-01 4.24417034e-02
1.42873764e-01 -3.41126263e-01 -2.13410497e-01 1.11087406e+00
5.74611306e-01 4.79206502e-01 6.10102892e-01 -1.32414865e+00
-2.64714152e-01 6.20034277e-01 -7.99506128e-01 9.22997966e-02
2.06484288e-01 7.19508171e-01 9.98262644e-01 -2.89741755e-02
3.92898828e-01 1.47649431e+00 3.53761822e-01 8.03336143e-01
-1.66049922e+00 -5.42458117e-01 6.60226285e-01 1.42281368e-01
-1.02309406e+00 -1.98003322e-01 5.46991110e-01 -3.53871375e-01
6.85120463e-01 -2.48558521e-02 8.92679870e-01 1.27542353e+00
3.69295627e-01 9.91990864e-01 1.32190454e+00 -2.88386084e-02
8.27675819e-01 -1.33302256e-01 -1.67849585e-01 5.79263926e-01
1.88449100e-01 4.73389417e-01 -4.59216356e-01 -2.75907129e-01
7.49811172e-01 -2.08331317e-01 -2.85824507e-01 -6.44742608e-01
-9.25113022e-01 8.59904110e-01 7.47764409e-02 -3.18645127e-02
-4.07999933e-01 4.15719032e-01 3.87074143e-01 6.15541101e-01
9.18248203e-03 5.55428803e-01 -7.14118958e-01 -3.38495970e-01
-3.60999852e-01 5.91193557e-01 6.50635302e-01 6.86793685e-01
8.34305525e-01 1.54943720e-01 -4.74660039e-01 7.31751561e-01
3.25893909e-01 6.02306426e-01 6.54661238e-01 -1.18129802e+00
6.36882246e-01 3.29358697e-01 4.75860029e-01 -5.98776758e-01
-3.98528934e-01 -2.74084657e-01 -4.10767883e-01 4.45724368e-01
8.49489987e-01 -7.03713834e-01 -8.65598679e-01 2.47066212e+00
4.51424509e-01 2.78188419e-02 9.22508687e-02 7.92365193e-01
-1.08469754e-01 4.50145900e-01 4.20216545e-02 -3.34856719e-01
8.10619593e-01 -6.49870813e-01 -8.88092279e-01 -4.91608441e-01
6.91619158e-01 1.34947412e-02 1.35563838e+00 3.76732349e-01
-9.17081118e-01 -1.22399092e-01 -1.09013975e+00 5.58066368e-01
-1.24777891e-01 7.85610601e-02 4.59223092e-01 2.37174004e-01
-8.27902734e-01 7.48428166e-01 -1.05548716e+00 -3.41161281e-01
2.77039409e-01 3.72909784e-01 4.64248769e-02 4.26081538e-01
-1.23880196e+00 8.82236660e-01 3.31757605e-01 -1.74899474e-01
-1.28023493e+00 -6.05444252e-01 -6.74232066e-01 -1.76853567e-01
9.09412861e-01 -2.27302611e-01 1.23980236e+00 -1.25688970e+00
-2.13487816e+00 3.46744776e-01 3.68196577e-01 -6.51120663e-01
6.95042253e-01 -1.66421294e-01 -7.44409040e-02 -8.90867785e-02
9.94662791e-02 4.85387474e-01 9.13539708e-01 -1.22679830e+00
-7.21128583e-01 -4.21906620e-01 1.48699716e-01 4.61586982e-01
-1.03442892e-01 -6.29471540e-01 -2.62481421e-01 -5.77216029e-01
-3.47424269e-01 -1.12234843e+00 -2.24390388e-01 -1.07388273e-01
-2.21799091e-01 -1.47495687e-01 7.13631511e-01 -1.09542891e-01
1.31818283e+00 -2.14081001e+00 4.68997359e-01 1.77276611e-01
-2.64509827e-01 -5.91942780e-02 -2.50895709e-01 3.93131584e-01
4.34077710e-01 -1.49789110e-01 -3.50924134e-01 -2.60539893e-02
1.91751465e-01 5.04598856e-01 -4.54243869e-01 7.94004083e-01
-8.65611881e-02 4.76235926e-01 -1.15520072e+00 -2.81253189e-01
-7.85673857e-02 -8.11140612e-02 -7.16525376e-01 3.72386158e-01
-5.39835751e-01 6.88379407e-01 -6.88717604e-01 3.21654201e-01
4.26904440e-01 1.27489567e-01 5.67321658e-01 2.13106096e-01
-2.44225934e-01 1.82065427e-01 -1.29042196e+00 1.57253182e+00
-4.73186433e-01 2.21713156e-01 2.70556897e-01 -9.82175708e-01
5.95401227e-01 -5.38063049e-02 7.60544419e-01 -7.47650266e-01
1.31155014e-01 2.07511157e-01 2.23790929e-01 -4.02083933e-01
-4.69627231e-02 -1.45028099e-01 -3.41014385e-01 4.72040206e-01
1.24600343e-01 -1.35050267e-01 2.99727768e-01 -2.00416416e-01
1.16153610e+00 3.47193718e-01 3.27307791e-01 -5.84913969e-01
2.31033191e-01 -1.50423348e-01 9.30455625e-01 1.02084899e+00
-5.68865538e-01 1.30355462e-01 1.04926801e+00 -3.27596106e-02
-4.81028080e-01 -1.07002735e+00 -2.03871597e-02 1.13818252e+00
4.21453416e-01 1.99049781e-03 -6.85435176e-01 -8.91145587e-01
3.78313363e-01 7.44236708e-01 -8.38272035e-01 -5.90845883e-01
-5.20394385e-01 -6.70464516e-01 5.97308397e-01 3.35149556e-01
5.24498284e-01 -9.96001184e-01 -1.02822781e+00 2.66239643e-01
3.19783054e-02 -7.49590874e-01 -7.76290953e-01 7.44136214e-01
-7.68052697e-01 -9.46862042e-01 -4.84638274e-01 -3.40990514e-01
4.47369903e-01 -1.02015689e-01 7.40133882e-01 -3.85416418e-01
1.80529654e-01 5.82074940e-01 -1.55817151e-01 -1.25893801e-01
-1.40633285e-01 -8.28791857e-02 4.28085417e-01 2.68781066e-01
9.72896516e-02 -4.53325421e-01 -6.21182084e-01 5.12902617e-01
-9.15697217e-01 -3.87602001e-01 4.54559565e-01 9.16273057e-01
6.39322102e-01 -2.62159631e-02 7.73106217e-01 -5.42279959e-01
7.70684302e-01 -6.18015885e-01 -9.98925030e-01 2.57295489e-01
-6.14874899e-01 5.97271144e-01 9.09503996e-01 -9.16562855e-01
-8.80143821e-01 3.04093231e-02 2.23036513e-01 -4.70856547e-01
1.02626152e-01 1.05716385e-01 -2.23326251e-01 1.81084037e-01
5.23440480e-01 1.81678638e-01 2.80609637e-01 -3.01500171e-01
2.54164815e-01 3.69229764e-01 1.01822717e-02 -1.00308764e+00
4.85589057e-01 5.04691720e-01 -1.28902367e-03 -7.00946271e-01
-8.14638734e-01 -1.49942972e-02 -2.12929487e-01 -4.00276184e-01
9.42550123e-01 -6.03533268e-01 -9.82066929e-01 6.14781559e-01
-5.39778411e-01 -1.10362101e+00 -5.27990043e-01 5.30041575e-01
-1.02162766e+00 1.32883474e-01 -4.53283846e-01 -9.57603514e-01
1.93026081e-01 -1.29746819e+00 8.13415766e-01 2.96905547e-01
-7.13708205e-03 -9.26659405e-01 4.71776038e-01 -2.92770773e-01
2.75566012e-01 2.40695909e-01 8.15126538e-01 -3.27521741e-01
-7.57234991e-02 2.40257740e-01 4.34266865e-01 2.07758293e-01
3.13705921e-01 -2.49374807e-01 -5.81312537e-01 -6.37081563e-01
-2.47429498e-02 -8.11372399e-01 9.20468390e-01 6.72481179e-01
1.04021919e+00 -5.63363135e-01 -8.64942744e-02 5.60748577e-01
1.30732369e+00 5.94026208e-01 3.17908823e-01 5.22143066e-01
3.25616688e-01 5.44646025e-01 8.75283837e-01 8.31851363e-01
1.75045162e-01 8.76805365e-01 5.13796210e-01 4.40993994e-01
3.60387266e-01 -5.81298411e-01 1.07568312e+00 1.47998124e-01
3.43647927e-01 -2.08682403e-01 -5.66487432e-01 2.43564785e-01
-2.25681782e+00 -9.89635170e-01 4.59326148e-01 2.65370989e+00
1.21972156e+00 2.32907489e-01 4.46699768e-01 -2.84807771e-01
4.26791430e-01 3.03690165e-01 -1.30981231e+00 -3.34511906e-01
-6.05420060e-02 -1.42633542e-01 8.51146936e-01 5.97120047e-01
-1.04192436e+00 7.99174845e-01 6.09702730e+00 9.12328601e-01
-1.21812737e+00 -1.70858130e-01 3.94993156e-01 -5.08418858e-01
-8.37841928e-02 -6.40078858e-02 -8.84457052e-01 7.73209810e-01
7.01827466e-01 3.44817117e-02 8.72149706e-01 7.40995347e-01
5.38682520e-01 -4.50747490e-01 -1.12656510e+00 7.39829779e-01
-3.18878949e-01 -7.74662495e-01 -2.18798339e-01 1.35398656e-01
6.78151846e-01 1.28972838e-02 3.00133377e-01 5.53146422e-01
8.41246307e-01 -7.08218277e-01 1.00242066e+00 4.51407552e-01
5.36503196e-01 -6.82658732e-01 2.46099725e-01 5.73167682e-01
-1.06890130e+00 -5.78152359e-01 -1.82190433e-01 7.59513974e-02
-6.43091500e-02 2.31262133e-01 -2.42812693e-01 3.58157679e-02
6.38902187e-01 7.49858737e-01 -1.50559202e-01 6.46236479e-01
-1.85672864e-01 5.70638597e-01 -5.14671624e-01 -2.70977020e-01
4.30193812e-01 -6.15248561e-01 7.19551861e-01 7.21251786e-01
6.14031143e-02 -2.65714109e-01 4.83973593e-01 8.98504436e-01
2.55414069e-01 -3.10539961e-01 -5.01632154e-01 -1.14541136e-01
4.35570925e-01 7.80047655e-01 -4.96159852e-01 1.45269958e-02
-3.65603939e-02 6.59464121e-01 5.49220562e-01 5.58138192e-01
-9.62788045e-01 -1.20306417e-01 1.07771325e+00 -4.41205725e-02
3.53209049e-01 -3.39999378e-01 -1.13209829e-01 -1.20912695e+00
-1.40775338e-01 -1.04762340e+00 6.05755031e-01 3.91922593e-02
-1.39132690e+00 1.10247105e-01 2.85652190e-01 -1.40998960e+00
-2.07180470e-01 -4.36443925e-01 -4.62857962e-01 3.61177504e-01
-1.25667894e+00 -4.36084121e-01 3.70207965e-01 5.67621410e-01
6.28292382e-01 -1.81767568e-02 3.04931313e-01 1.38973624e-01
-8.78939688e-01 5.42945802e-01 4.60515648e-01 -3.01452160e-01
7.30099857e-01 -1.42764997e+00 -4.00291145e-01 4.40213501e-01
-2.27493092e-01 3.49963307e-01 8.45217764e-01 -6.08438432e-01
-1.62691486e+00 -1.00547791e+00 -2.22503021e-01 -1.62873819e-01
8.20938766e-01 -2.65231997e-01 -6.41223013e-01 6.80959344e-01
4.06907350e-02 -1.39482960e-01 3.25391173e-01 -1.96295738e-01
-6.80557489e-02 -2.90003151e-01 -1.20719326e+00 9.11766887e-01
8.97255421e-01 -4.41950709e-02 -1.63132250e-01 -2.15246808e-02
4.39872801e-01 -2.45197088e-01 -4.86704975e-01 2.44238257e-01
5.54832995e-01 -8.35187733e-01 6.10853136e-01 -9.18659389e-01
6.46424741e-02 -3.80821288e-01 -2.60047734e-01 -1.67744899e+00
-6.32983372e-02 -7.89667130e-01 -3.03641677e-01 7.82674491e-01
3.67932707e-01 -7.91584671e-01 4.86196131e-01 2.97320873e-01
1.82894379e-01 -1.09458315e+00 -1.15237153e+00 -1.01349342e+00
2.63578743e-01 -2.47778744e-01 3.85731250e-01 5.57215273e-01
1.19395509e-01 1.91562325e-01 -5.39701581e-01 4.53741737e-02
6.54423356e-01 1.00251183e-01 7.40462959e-01 -6.39044702e-01
-7.63102293e-01 -6.35231733e-01 4.04652432e-02 -1.52786231e+00
2.92533726e-01 -5.48379838e-01 5.06069720e-01 -1.09035182e+00
-3.66926230e-02 -5.62326372e-01 -3.51144314e-01 6.11828804e-01
-8.03235397e-02 -5.67308843e-01 2.06686124e-01 7.92867765e-02
-7.94378161e-01 1.12687862e+00 1.24162745e+00 -1.01055592e-01
-7.29207814e-01 9.82821956e-02 -3.91951233e-01 7.50975668e-01
8.92794669e-01 -5.84620893e-01 -6.67972803e-01 -3.35230321e-01
1.21613957e-01 2.99596071e-01 2.24261545e-02 -9.46655929e-01
-1.25788882e-01 -9.00712609e-01 1.95500422e-02 -2.68759191e-01
2.30084673e-01 -7.31178463e-01 -1.73993528e-01 7.63645768e-01
-7.40409613e-01 -5.82264625e-02 5.73718585e-02 1.10408390e+00
2.48489857e-01 4.64380421e-02 1.31503201e+00 -9.03445184e-02
-4.04630363e-01 3.41452748e-01 -8.14119101e-01 5.96883059e-01
1.21357119e+00 2.30304077e-02 -1.84228256e-01 -5.09927869e-01
-4.74652886e-01 8.15698028e-01 3.98282290e-01 3.44027430e-01
3.22834522e-01 -1.40114093e+00 -1.70052081e-01 1.27071589e-01
2.14192434e-03 -1.82043448e-01 9.49135125e-02 1.03471065e+00
-8.55044350e-02 -2.82715224e-02 -4.31431502e-01 -4.71844226e-01
-7.14001656e-01 2.75716245e-01 7.55173564e-01 -5.56250393e-01
-4.59542096e-01 5.36306262e-01 1.57759741e-01 -4.88964111e-01
4.93730158e-01 -3.47747296e-01 -2.65157789e-01 2.09315613e-01
2.33680949e-01 5.13290107e-01 -3.75476390e-01 -3.06031615e-01
-2.60293603e-01 5.04826844e-01 1.15460835e-01 -5.57394505e-01
1.29078412e+00 -2.88348012e-02 3.55814517e-01 8.65821302e-01
1.02068090e+00 -7.82736018e-02 -2.01765871e+00 -7.12537253e-03
1.29875168e-02 -4.32758272e-01 -3.49099711e-02 -7.56957352e-01
-1.11790061e+00 4.02932525e-01 6.67550862e-01 3.36157948e-01
9.37367558e-01 -1.61577031e-01 6.54731870e-01 4.13132757e-01
5.88124275e-01 -1.72797573e+00 3.24388266e-01 6.99897349e-01
7.76823044e-01 -1.03824544e+00 -1.37641653e-01 4.80292857e-01
-1.12493098e+00 9.20426130e-01 9.27708983e-01 -3.89773428e-01
6.16525590e-01 3.21342796e-01 -5.95188625e-02 3.58629674e-02
-1.09634554e+00 -4.42086488e-01 -2.00018853e-01 4.76045161e-01
-1.24200687e-01 2.53164202e-01 -4.90282118e-01 4.51564729e-01
2.56786525e-01 -2.72788405e-01 4.38996643e-01 1.15807247e+00
-5.29921293e-01 -1.08180320e+00 -2.50112236e-01 5.21979094e-01
-3.11732739e-01 5.24267018e-01 -4.77648526e-01 6.52697504e-01
-4.69133146e-02 9.29424226e-01 -1.14851827e-02 -4.55620676e-01
4.40088630e-01 -2.18170777e-01 5.01004279e-01 -4.16293204e-01
-4.12590146e-01 1.08828865e-01 -1.75398231e-01 -9.56789136e-01
-1.75088808e-01 -8.63553345e-01 -1.47467244e+00 -1.20615307e-02
-1.36877611e-01 3.15520763e-02 1.47303775e-01 9.20176089e-01
3.51624489e-01 3.00379336e-01 9.09462333e-01 -8.18371952e-01
-1.42583776e+00 -7.19892800e-01 -8.76182079e-01 4.76790488e-01
7.03938723e-01 -1.20161891e+00 -7.74494886e-01 -4.72655118e-01] | [4.078127384185791, 2.1850500106811523] |
4eb43d0e-fce4-468f-90d0-3470054083a8 | same-scenario-adaptive-mixture-of-experts-for | 2112.13747 | null | https://arxiv.org/abs/2112.13747v6 | https://arxiv.org/pdf/2112.13747v6.pdf | MOEF: Modeling Occasion Evolution in Frequency Domain for Promotion-Aware Click-Through Rate Prediction | Promotions are becoming more important and prevalent in e-commerce to attract customers and boost sales, leading to frequent changes of occasions, which drives users to behave differently. In such situations, most existing Click-Through Rate (CTR) models can't generalize well to online serving due to distribution uncertainty of the upcoming occasion. In this paper, we propose a novel CTR model named MOEF for recommendations under frequent changes of occasions. Firstly, we design a time series that consists of occasion signals generated from the online business scenario. Since occasion signals are more discriminative in the frequency domain, we apply Fourier Transformation to sliding time windows upon the time series, obtaining a sequence of frequency spectrum which is then processed by Occasion Evolution Layer (OEL). In this way, a high-order occasion representation can be learned to handle the online distribution uncertainty. Moreover, we adopt multiple experts to learn feature representations from multiple aspects, which are guided by the occasion representation via an attention mechanism. Accordingly, a mixture of feature representations is obtained adaptively for different occasions to predict the final CTR. Experimental results on real-world datasets validate the superiority of MOEF and online A/B tests also show MOEF outperforms representative CTR models significantly. | ['Yang Huang', 'Xu He', 'Bo Cao', 'Chengjun Mao', 'Hong Wen', 'Jing Zhang', 'Yibin Shen', 'Xiaofeng Pan'] | 2021-12-27 | null | null | null | null | ['time-series-prediction'] | ['time-series'] | [-1.23272985e-01 -5.53601742e-01 -2.26224005e-01 -7.50674129e-01
-3.93038154e-01 -1.85862198e-01 5.70066333e-01 -1.41465053e-01
-2.60564297e-01 4.34456378e-01 1.77272022e-01 -2.73806825e-02
-5.40112376e-01 -7.48782814e-01 -5.86328685e-01 -6.31898582e-01
-5.49313203e-02 1.31932870e-01 5.20685650e-02 -4.00842756e-01
4.55898255e-01 -3.33464742e-02 -1.60202324e+00 1.97463617e-01
1.02832806e+00 1.36289406e+00 4.25528347e-01 1.68033689e-01
-3.51259261e-01 1.97998509e-01 -5.76635897e-01 -2.89198756e-01
1.71130985e-01 -1.83398828e-01 -1.21690601e-01 3.68231237e-01
-4.01750922e-01 -2.89968848e-01 -4.70744848e-01 7.62488186e-01
2.82378078e-01 7.44501054e-01 5.87212324e-01 -1.07349908e+00
-1.01403773e+00 7.75790155e-01 -6.79061770e-01 6.04424298e-01
3.11842740e-01 -3.19200084e-02 1.11021996e+00 -8.11064899e-01
3.43966246e-01 1.31950450e+00 3.86955887e-01 1.57579377e-01
-1.05368984e+00 -5.11512637e-01 1.11446166e+00 5.43180108e-01
-1.20928252e+00 1.68213919e-01 1.18955112e+00 -1.43707737e-01
6.03461325e-01 2.18985066e-01 6.65271819e-01 1.23135054e+00
4.99823272e-01 1.22570837e+00 7.43003428e-01 2.47236788e-01
1.10608518e-01 3.29578847e-01 2.21789345e-01 -3.90129149e-01
-2.03269139e-01 1.05296679e-01 -2.88015902e-01 8.27917531e-02
5.85746765e-01 6.36848092e-01 -2.14257509e-01 1.34219468e-01
-8.69875193e-01 9.47399676e-01 4.99846339e-01 3.31237674e-01
-8.86005342e-01 -2.87407517e-01 4.41427380e-01 7.45297551e-01
4.96044606e-01 6.67160079e-02 -4.92625564e-01 -1.32071689e-01
-3.72160047e-01 3.81653249e-01 6.56150043e-01 8.74710083e-01
3.48235697e-01 1.11181848e-02 -3.96617383e-01 8.82527351e-01
5.04003286e-01 2.10888669e-01 8.55074048e-01 -3.24827611e-01
4.04648274e-01 2.06000537e-01 3.69381040e-01 -1.30440080e+00
-3.75891328e-01 -1.11737728e+00 -7.88549125e-01 -7.45278835e-01
1.57184049e-01 7.20546618e-02 -4.43886429e-01 1.52978730e+00
3.95127118e-01 3.69507402e-01 -3.34321558e-01 1.09307039e+00
2.81108439e-01 9.55599844e-01 9.70007852e-02 -7.18784869e-01
1.22458613e+00 -4.92608428e-01 -1.05161858e+00 -4.71166056e-03
1.09637015e-01 -7.58765936e-01 1.16242909e+00 8.99528384e-01
-6.84085429e-01 -8.61728787e-01 -7.03650236e-01 3.73209476e-01
-2.64140248e-01 3.68144326e-02 7.98797131e-01 3.52841556e-01
-2.55884469e-01 6.70576453e-01 -5.03368914e-01 1.10497221e-01
1.75529882e-01 3.72516923e-02 4.66011077e-01 -4.43435013e-02
-1.71726036e+00 3.90563875e-01 3.13257039e-01 4.35090661e-01
-5.35918415e-01 -6.42116427e-01 -5.43782592e-01 1.00566097e-01
3.89764190e-01 -8.54231864e-02 1.32791507e+00 -7.38074183e-01
-1.47871697e+00 -6.75771534e-02 3.79840657e-02 -4.85710949e-01
5.00853717e-01 -2.46042997e-01 -1.23134720e+00 -3.83811086e-01
-4.42432202e-02 -1.53070852e-01 1.28495181e+00 -9.10737574e-01
-9.44563925e-01 -3.83185625e-01 -1.68037221e-01 2.58755058e-01
-4.67113554e-01 -2.48434991e-01 -3.11930329e-01 -7.77021110e-01
2.27046266e-01 -6.03488803e-01 -2.08990410e-01 -6.20064616e-01
-1.25086173e-01 -6.60757005e-01 7.53487706e-01 -7.26759493e-01
1.78335536e+00 -2.44359303e+00 -1.96032785e-02 3.50300938e-01
-2.01909989e-01 -1.55818522e-01 -1.12540275e-01 4.86120760e-01
6.96693175e-03 -1.92755431e-01 3.67384583e-01 2.08688457e-03
2.47504190e-01 1.18954755e-01 -6.87871993e-01 2.60818750e-01
8.07750002e-02 5.21108747e-01 -7.82057822e-01 3.63072217e-03
1.47654712e-01 4.38861698e-01 -6.03110850e-01 1.49253175e-01
-4.44330603e-01 6.50746942e-01 -9.98787284e-01 4.59497869e-01
8.82735968e-01 -3.70554179e-01 -1.24595188e-01 -1.87974423e-01
-2.02455893e-01 2.70950615e-01 -1.33603489e+00 1.41498530e+00
-8.20937932e-01 8.56910553e-03 -1.43283725e-01 -1.03814030e+00
1.19564795e+00 1.18754633e-01 3.93613964e-01 -1.04912937e+00
3.09247315e-01 2.08810046e-01 5.23002483e-02 -4.47223604e-01
6.66991889e-01 -4.58268113e-02 -1.93263546e-01 4.31891859e-01
-1.14512369e-01 3.30438137e-01 1.90158382e-01 -2.77479589e-02
5.76985955e-01 2.94261333e-02 -4.53346521e-02 1.80073842e-01
6.23372257e-01 -4.66378063e-01 6.38275623e-01 6.73538327e-01
-1.61941066e-01 2.00104892e-01 2.07055748e-01 -5.70294857e-01
-5.93472123e-01 -9.89762485e-01 -4.74894732e-01 1.29899228e+00
3.00168425e-01 -5.44957221e-02 6.45090938e-02 -5.06256819e-01
2.51106203e-01 1.11857092e+00 -5.21780789e-01 -4.82752770e-01
-3.74696642e-01 -8.03602934e-01 -5.45371294e-01 4.08347964e-01
3.30250919e-01 -1.05859983e+00 2.56782360e-02 9.53898609e-01
-1.61448151e-01 -6.40950322e-01 -8.24976623e-01 -1.10390395e-01
-7.97915280e-01 -6.09201908e-01 -8.26429605e-01 -3.61114204e-01
1.39312401e-01 4.96088088e-01 7.13344634e-01 -3.36525500e-01
-1.95795417e-01 3.22512597e-01 -5.24888515e-01 -4.94114071e-01
1.37499183e-01 -2.66830735e-02 1.09148055e-01 8.08138728e-01
6.69728100e-01 -7.14777350e-01 -9.28249419e-01 6.03587806e-01
-1.07688236e+00 -6.38413906e-01 5.39973438e-01 9.17509973e-01
6.62178516e-01 6.71045780e-01 1.20094419e+00 -6.99133933e-01
1.01714599e+00 -1.03985035e+00 -5.72776794e-01 3.91265228e-02
-7.30776906e-01 -2.74051189e-01 1.00207293e+00 -1.05310738e+00
-1.39676249e+00 -5.43178380e-01 5.21300957e-02 -4.81737673e-01
1.50272086e-01 8.03413987e-01 -1.73747819e-02 6.40495420e-01
2.69502640e-01 6.15997553e-01 -1.59563467e-01 -7.30890632e-01
4.92891401e-01 9.35646832e-01 7.08105639e-02 -4.05209005e-01
7.20316291e-01 2.05801442e-01 -6.13363683e-01 -4.70251620e-01
-9.06620324e-01 -7.64215887e-01 4.37014624e-02 -3.35227340e-01
3.24648887e-01 -8.04120719e-01 -7.72237301e-01 3.58624756e-01
-7.62635410e-01 3.37596625e-01 -3.05487543e-01 1.01285887e+00
-4.92245466e-01 5.44199981e-02 -6.95434213e-01 -9.71318722e-01
-9.39916878e-04 -7.72216916e-01 9.37786937e-01 6.23573184e-01
1.18940450e-01 -9.15810168e-01 -1.48213774e-01 6.87479302e-02
6.17885411e-01 -9.66792554e-02 6.64155781e-01 -8.17826688e-01
-4.04044211e-01 -5.74790418e-01 -9.44009721e-02 2.74431705e-01
2.34383687e-01 -2.65815228e-01 -6.62345111e-01 -2.50067919e-01
4.89414364e-01 9.95822325e-02 7.71570563e-01 5.57338834e-01
1.56185365e+00 -4.32446390e-01 -2.67028511e-01 2.64517486e-01
1.20667303e+00 6.59325778e-01 6.02812111e-01 2.98446238e-01
1.96955472e-01 6.03139818e-01 1.24074852e+00 1.07653284e+00
3.47074240e-01 5.36904275e-01 3.88760120e-01 5.14250398e-01
5.96710205e-01 -5.01285315e-01 1.93843246e-01 1.09731758e+00
-3.02756811e-03 -2.56424397e-01 -3.89288440e-02 3.83306414e-01
-1.91123188e+00 -1.09820342e+00 1.18648678e-01 2.30622196e+00
5.83704412e-01 2.42493138e-01 2.87205189e-01 8.31666738e-02
9.35839653e-01 2.21508965e-01 -9.60465431e-01 -1.80297390e-01
2.48762250e-01 -2.64207929e-01 1.02890590e-02 -1.08726986e-01
-9.70999420e-01 2.30384141e-01 4.87400246e+00 1.13301158e+00
-1.02974260e+00 -1.29571989e-01 6.71149850e-01 -2.20421422e-02
-5.98777056e-01 -3.03677320e-01 -9.56509233e-01 9.09773648e-01
8.43083620e-01 -6.37907803e-01 7.47962534e-01 9.03944552e-01
5.83344042e-01 5.55314541e-01 -7.88063347e-01 8.45834494e-01
-1.66939065e-01 -7.77540624e-01 -1.72223337e-02 8.72097388e-02
6.57796562e-01 -2.93902218e-01 5.16792297e-01 9.37913716e-01
7.27394074e-02 -5.02424061e-01 5.01508892e-01 9.90909755e-01
2.81767607e-01 -8.88215959e-01 6.12146616e-01 4.96170968e-01
-1.31259632e+00 -6.50799870e-01 -6.07613146e-01 2.42059663e-01
5.39732814e-01 8.24921548e-01 -4.05305177e-01 8.90021324e-01
5.82803786e-01 1.09800816e+00 -7.29625300e-02 1.19249511e+00
2.20473304e-01 5.52001119e-01 -3.30297381e-01 -3.14650714e-01
1.93759695e-01 -3.81735206e-01 6.18778467e-01 6.20961189e-01
7.31182635e-01 1.10041015e-01 2.31975183e-01 7.70937145e-01
1.76351562e-01 2.43905529e-01 -1.01966903e-01 -1.24421485e-01
4.52473938e-01 1.20716786e+00 -3.06136668e-01 -7.02742189e-02
-6.70161486e-01 7.95561969e-01 -9.75431055e-02 4.87912744e-01
-1.10234678e+00 -5.60532331e-01 2.32269660e-01 7.53259957e-02
6.39605761e-01 3.05334814e-02 4.25648391e-01 -1.27893281e+00
1.86017081e-01 -7.71901369e-01 6.03459418e-01 -5.38212359e-01
-2.02196217e+00 5.29900432e-01 -1.96474329e-01 -1.86259913e+00
-1.29110888e-01 -2.52007127e-01 -8.04732442e-01 8.02991390e-01
-1.56511581e+00 -5.65032959e-01 -1.21081933e-01 6.46363854e-01
9.05621052e-01 1.03139952e-02 3.03860337e-01 5.23831248e-01
-5.81135392e-01 5.74741006e-01 4.23618019e-01 -4.77497786e-01
5.56014538e-01 -9.35914099e-01 7.53286108e-02 2.68754125e-01
-6.95570856e-02 8.99821401e-01 6.86153114e-01 -6.38529301e-01
-1.50998998e+00 -1.22017419e+00 5.76458931e-01 7.66249448e-02
9.68404293e-01 -7.70426244e-02 -1.15619397e+00 5.47906399e-01
-2.70772785e-01 -1.37648180e-01 6.24211848e-01 3.95057708e-01
-2.28700042e-01 -4.34019357e-01 -9.89415288e-01 4.64894772e-01
8.86516988e-01 -3.26217145e-01 -7.08277822e-01 4.93172437e-01
9.58617687e-01 -1.57313675e-01 -1.16313720e+00 8.61179605e-02
4.59861100e-01 -5.17356932e-01 7.37764060e-01 -5.65853953e-01
1.26438320e-01 -2.15784416e-01 -1.08432047e-01 -1.45809579e+00
-5.88312805e-01 -7.97475219e-01 -2.29745179e-01 1.25454187e+00
2.01057941e-01 -1.00046039e+00 2.75236547e-01 4.13135171e-01
-8.11750069e-02 -6.38605952e-01 -8.42847288e-01 -9.62829709e-01
-3.95742178e-01 -4.97552216e-01 1.04648542e+00 7.56171882e-01
3.22712772e-02 2.59966284e-01 -5.39896905e-01 1.91932749e-02
4.93797749e-01 5.39231718e-01 4.51319605e-01 -1.25409031e+00
-6.68606520e-01 -4.83337045e-01 -9.11776945e-02 -1.55151296e+00
-2.49690175e-01 -6.25713050e-01 -9.61431265e-02 -1.09008980e+00
-1.58639565e-01 -5.14532268e-01 -9.16896880e-01 -1.91981584e-01
-2.50855863e-01 -3.29451323e-01 -1.26495719e-01 3.38703990e-01
-8.26806545e-01 1.13408983e+00 1.45651090e+00 -9.63205099e-02
-5.16883254e-01 7.69955397e-01 -7.85877824e-01 3.16546649e-01
6.02044702e-01 -1.96287066e-01 -5.62871337e-01 1.21938931e-02
2.30855867e-01 4.01950657e-01 -8.21708590e-02 -5.05154848e-01
-4.97148000e-02 -2.21592009e-01 3.89939785e-01 -8.26288044e-01
2.20015079e-01 -8.98265302e-01 2.19587341e-01 1.93997487e-01
-5.36754072e-01 -2.43783399e-01 -5.09657972e-02 1.41393244e+00
-2.54375935e-01 7.25284452e-03 1.47306040e-01 1.55630618e-01
-6.08238101e-01 7.58149326e-01 -2.70789802e-01 -2.87006676e-01
8.18294108e-01 -5.97323887e-02 -4.61956896e-02 -4.94443923e-01
-9.83912885e-01 4.91216809e-01 -3.22260737e-01 9.81997907e-01
4.06655043e-01 -1.56063616e+00 -6.50219798e-01 2.65948743e-01
1.96251050e-01 -2.87771016e-01 1.01785779e+00 8.41082692e-01
4.49807763e-01 3.78817439e-01 1.35924071e-01 -5.78243852e-01
-4.16585654e-01 8.72226834e-01 -1.04138784e-01 -3.99817318e-01
-6.10800683e-01 5.79343200e-01 2.21747980e-01 -2.36171439e-01
1.42026365e-01 -2.36942753e-01 -7.99696624e-01 3.58703047e-01
8.52162123e-01 3.04095149e-01 6.65321276e-02 -3.32376450e-01
-7.84600675e-02 3.13620746e-01 -7.08656073e-01 1.41552940e-01
1.49713111e+00 -6.14008009e-01 4.31386858e-01 6.40099049e-01
1.20791435e+00 -2.44942144e-01 -1.43995619e+00 -5.65715373e-01
-1.23647101e-01 -8.00218046e-01 4.01508696e-02 -5.35002053e-01
-1.11106801e+00 5.46005487e-01 5.41653872e-01 9.21722531e-01
1.32250547e+00 -2.00741172e-01 1.07124841e+00 2.27931677e-03
5.49443960e-01 -1.31590593e+00 5.26760109e-02 2.32970089e-01
9.79389727e-01 -1.01368546e+00 -3.58477950e-01 -1.54155418e-01
-7.52443433e-01 9.08712685e-01 5.08131444e-01 -3.36518824e-01
1.02665591e+00 -4.31532115e-01 -2.64408618e-01 8.69711116e-02
-1.02319658e+00 1.21709734e-01 2.95696974e-01 3.81127059e-01
2.49971896e-01 2.11401105e-01 -9.15602505e-01 1.34277678e+00
-3.55309583e-02 6.91896379e-02 3.24794888e-01 5.76557755e-01
-4.06731665e-01 -9.75616813e-01 -1.54543281e-01 8.16722095e-01
-4.48443204e-01 2.32593209e-01 4.56159323e-01 5.10576844e-01
-6.38653710e-02 9.90085900e-01 8.40608403e-02 -5.86815655e-01
5.13939202e-01 -1.22470155e-01 -3.67424041e-02 -3.84503484e-01
-4.41706777e-01 5.52302897e-01 -1.43664688e-01 -5.95495403e-01
2.62367558e-02 -9.90151703e-01 -1.01625347e+00 -6.46299869e-02
-7.35146821e-01 3.83290350e-01 7.22966790e-01 7.88241029e-01
4.62467372e-01 8.98229480e-01 1.47639155e+00 -6.19818747e-01
-1.28510308e+00 -1.05395389e+00 -1.12631130e+00 5.70408404e-01
8.16158578e-02 -8.36804271e-01 -7.51466036e-01 -3.88327360e-01] | [10.133788108825684, 5.558138847351074] |
d641b181-1109-43d3-bc18-5cab37f75aa7 | neural-models-for-factual-inconsistency | 2306.08872 | null | https://arxiv.org/abs/2306.08872v1 | https://arxiv.org/pdf/2306.08872v1.pdf | Neural models for Factual Inconsistency Classification with Explanations | Factual consistency is one of the most important requirements when editing high quality documents. It is extremely important for automatic text generation systems like summarization, question answering, dialog modeling, and language modeling. Still, automated factual inconsistency detection is rather under-studied. Existing work has focused on (a) finding fake news keeping a knowledge base in context, or (b) detecting broad contradiction (as part of natural language inference literature). However, there has been no work on detecting and explaining types of factual inconsistencies in text, without any knowledge base in context. In this paper, we leverage existing work in linguistics to formally define five types of factual inconsistencies. Based on this categorization, we contribute a novel dataset, FICLE (Factual Inconsistency CLassification with Explanation), with ~8K samples where each sample consists of two sentences (claim and context) annotated with type and span of inconsistency. When the inconsistency relates to an entity type, it is labeled as well at two levels (coarse and fine-grained). Further, we leverage this dataset to train a pipeline of four neural models to predict inconsistency type with explanations, given a (claim, context) sentence pair. Explanations include inconsistent claim fact triple, inconsistent context span, inconsistent claim component, coarse and fine-grained inconsistent entity types. The proposed system first predicts inconsistent spans from claim and context; and then uses them to predict inconsistency types and inconsistent entity types (when inconsistency is due to entities). We experiment with multiple Transformer-based natural language classification as well as generative models, and find that DeBERTa performs the best. Our proposed methods provide a weighted F1 of ~87% for inconsistency type classification across the five classes. | ['Vasudeva Varma', 'Manish Gupta', 'KV Aditya Srivatsa', 'Harshit Gupta', 'Abhinav Menon', 'Mukund Choudhary', 'Tathagata Raha'] | 2023-06-15 | null | null | null | null | ['natural-language-inference'] | ['natural-language-processing'] | [ 2.07999721e-01 5.47926426e-01 -6.17156386e-01 -4.37361747e-01
-9.62241948e-01 -4.49320465e-01 9.24080074e-01 5.64769506e-01
2.87804961e-01 1.17003727e+00 6.07875228e-01 -7.39315569e-01
-1.06171884e-01 -6.80805802e-01 -8.09165359e-01 8.09732154e-02
3.37699085e-01 7.23398864e-01 2.06762299e-01 -4.37560469e-01
8.08399141e-01 -2.88584977e-01 -1.40932131e+00 9.41043735e-01
1.30620956e+00 8.81360769e-01 -2.76786387e-01 5.15763640e-01
-6.22971058e-01 1.57295489e+00 -1.14316297e+00 -9.96296406e-01
-3.17236185e-01 -8.73952866e-01 -1.54232407e+00 -4.52062674e-02
6.45791292e-01 9.95268226e-02 3.96547318e-01 1.04049492e+00
1.25175983e-01 -4.11618918e-01 8.28091502e-01 -1.49707806e+00
-1.17641377e+00 1.25346303e+00 -4.23794210e-01 4.45927352e-01
6.74928784e-01 -3.44401538e-01 1.20524907e+00 -7.86159813e-01
9.14259255e-01 1.27086747e+00 8.46226871e-01 4.90148038e-01
-7.35096157e-01 -4.42312211e-01 2.24763393e-01 7.01652169e-01
-7.71606803e-01 -3.42870682e-01 9.61044908e-01 -3.13397884e-01
1.28130126e+00 3.02370727e-01 4.53163743e-01 1.36153710e+00
7.41302907e-01 6.41198993e-01 1.13345397e+00 -5.91406345e-01
3.07660192e-01 3.13699782e-01 6.40320837e-01 5.86921871e-01
6.44817591e-01 -6.46426260e-01 -5.83984613e-01 -4.39457208e-01
1.39517179e-02 -3.61955404e-01 -1.97749615e-01 4.48079616e-01
-1.05670762e+00 9.40137804e-01 1.01690538e-01 6.13159537e-01
-4.79519248e-01 9.61869285e-02 6.05092645e-01 4.83069420e-01
5.92067301e-01 4.67382461e-01 -7.13531256e-01 -1.36816606e-01
-7.62613237e-01 8.49501252e-01 1.11333394e+00 1.00745130e+00
4.39169437e-01 -1.37409911e-01 -3.92335922e-01 9.49192822e-01
2.49213308e-01 2.20517516e-01 7.16351569e-01 -9.73244846e-01
8.63366544e-01 1.03137720e+00 2.05727458e-01 -1.42285669e+00
-4.67443764e-01 -1.36692449e-01 -8.87105823e-01 -4.90416586e-01
4.56789993e-02 1.15568012e-01 -5.06101012e-01 1.72947037e+00
2.64729261e-01 -1.07490443e-01 4.55237627e-01 6.47881866e-01
1.24905038e+00 4.21850860e-01 -2.37210654e-02 -4.81836915e-01
1.84512603e+00 -8.78989816e-01 -1.28571486e+00 -4.46290255e-01
5.78674674e-01 -9.10913289e-01 9.98992562e-01 2.32704893e-01
-1.15073049e+00 -1.85877040e-01 -9.78397250e-01 -4.30385023e-01
-5.13029993e-01 1.42590687e-01 6.60395145e-01 4.10763144e-01
-6.18574500e-01 2.24009350e-01 -2.42699727e-01 -2.14396492e-01
2.31820330e-01 -7.10023269e-02 -3.55412215e-01 9.37553272e-02
-1.62392366e+00 1.20560110e+00 4.60465044e-01 -1.17033251e-01
-1.03762962e-01 -5.51136553e-01 -9.66557682e-01 -1.17089294e-01
6.65461123e-01 -1.09585214e+00 1.34132361e+00 -9.36963439e-01
-1.03500211e+00 8.81660819e-01 -5.27701616e-01 -8.10801983e-01
3.20771724e-01 -1.70310274e-01 -6.25908256e-01 -2.11147711e-01
7.61783957e-01 2.04239294e-01 6.07633650e-01 -1.36845219e+00
-5.44494271e-01 -4.13664103e-01 2.90180117e-01 3.47285606e-02
3.50627065e-01 1.55925110e-01 1.08407468e-01 -7.03830957e-01
5.54187834e-01 -6.58916771e-01 4.03141439e-01 -7.19659686e-01
-1.01393950e+00 -8.30641925e-01 8.66881430e-01 -9.80327547e-01
1.46929467e+00 -1.31872487e+00 -2.50926316e-01 -2.64815003e-01
1.44509912e-01 -9.51339751e-02 3.44076753e-01 4.18910474e-01
-1.48623571e-01 6.92019284e-01 -4.63323265e-01 -1.51237443e-01
2.43042260e-01 3.17777425e-01 -6.70401514e-01 -2.41005525e-01
4.49005306e-01 9.38307941e-01 -7.17953026e-01 -6.94793165e-01
-3.40162158e-01 -1.23722188e-01 -6.41480803e-01 -4.09831526e-03
-6.32186770e-01 6.83596209e-02 -3.68648380e-01 9.34454083e-01
6.63751781e-01 -2.52888590e-01 3.66630435e-01 -4.14501160e-01
1.05757415e-01 9.54276621e-01 -9.30149436e-01 1.32625401e+00
-3.71205747e-01 4.96394515e-01 -4.78155792e-01 -9.75354254e-01
7.22329378e-01 5.11170328e-01 6.93439171e-02 -5.86363137e-01
2.96500493e-02 4.16946203e-01 -3.33534591e-02 -1.04787982e+00
8.87099385e-01 -3.39409947e-01 -4.39353168e-01 6.16359055e-01
-1.49981096e-01 -2.67948180e-01 3.34072709e-01 5.40995061e-01
1.21022022e+00 -1.39644414e-01 6.62646890e-01 -5.35367765e-02
5.89529574e-01 3.20629090e-01 6.88621283e-01 8.74213636e-01
-1.16589867e-01 5.04954755e-01 9.64258671e-01 -6.16331756e-01
-8.82771969e-01 -7.74508893e-01 -1.05479881e-01 4.11023378e-01
2.10693046e-01 -5.40096402e-01 -6.10413194e-01 -1.14369094e+00
-6.22905456e-02 1.19080603e+00 -7.37018943e-01 5.32183126e-02
-6.91003799e-01 -7.81420529e-01 7.39695549e-01 3.03010970e-01
9.02402639e-01 -1.35464907e+00 -2.77254671e-01 3.22399050e-01
-1.03840053e+00 -1.17023468e+00 -1.35596052e-01 -1.28566906e-01
-5.00019431e-01 -1.54406238e+00 3.45460445e-01 -5.32115221e-01
3.82140458e-01 5.79244420e-02 1.52523518e+00 5.38896918e-01
1.72925651e-01 -5.58737367e-02 -3.69927168e-01 -5.33203900e-01
-8.19819152e-01 -1.90501958e-01 5.29975295e-02 -4.23437864e-01
4.06306267e-01 -2.47538820e-01 -1.84399292e-01 3.50877307e-02
-1.06101000e+00 1.75191507e-01 3.22441816e-01 1.09628880e+00
3.72198224e-01 4.17854525e-02 1.00133145e+00 -1.33485413e+00
1.16427314e+00 -9.75792944e-01 8.72659236e-02 5.37458539e-01
-8.07691336e-01 9.02805328e-02 6.25594378e-01 -1.06668226e-01
-1.33675826e+00 -8.44310999e-01 -2.92286336e-01 2.02042177e-01
-1.27396807e-01 8.34405899e-01 -1.34532034e-01 7.66686499e-01
7.72003114e-01 -8.13731477e-02 -4.26174611e-01 6.35144785e-02
4.27100480e-01 8.78997445e-01 5.44278562e-01 -9.02968585e-01
2.98086733e-01 2.04696834e-01 -4.02367622e-01 -2.77995825e-01
-1.32652247e+00 -2.43247766e-02 -3.66534144e-01 7.47095644e-02
6.94075227e-01 -4.91028011e-01 -3.22172076e-01 1.05331622e-01
-1.70281136e+00 2.71034300e-01 -9.66600254e-02 1.93535805e-01
-5.28584778e-01 4.93675947e-01 -6.30702198e-01 -7.76344657e-01
-5.87567687e-01 -8.46131325e-01 9.58807111e-01 8.89224336e-02
-6.86822891e-01 -9.12793517e-01 1.25554517e-01 9.22693253e-01
2.74079174e-01 3.16078722e-01 1.48836493e+00 -9.76660073e-01
-2.59047002e-01 -8.58508646e-02 -1.72194645e-01 1.35104023e-02
2.64193624e-01 5.96283674e-02 -5.98276615e-01 6.11814499e-01
3.53983283e-01 -4.40261036e-01 5.56955516e-01 3.95651907e-01
9.78038907e-01 -1.14912891e+00 -1.43952087e-01 -3.08534950e-01
1.17240167e+00 1.27325337e-02 7.29001999e-01 4.75411236e-01
3.32703441e-01 6.27103150e-01 5.89563847e-01 1.38114512e-01
1.05082202e+00 7.07454383e-01 2.00534031e-01 4.51977372e-01
-1.35918841e-01 -2.76299268e-01 2.41183609e-01 7.40866780e-01
-2.31842860e-03 -3.52692157e-01 -8.43294621e-01 6.64235473e-01
-2.13292265e+00 -1.69831932e+00 -5.64638376e-01 1.70719469e+00
1.23147106e+00 2.18185425e-01 -3.06861579e-01 3.66200417e-01
6.85354829e-01 8.43093824e-03 -2.01787218e-01 -9.58772600e-01
-3.62470597e-01 -1.47116154e-01 -3.30402821e-01 6.72372282e-01
-9.20668542e-01 1.04963255e+00 5.73026657e+00 7.06001997e-01
-6.95538163e-01 2.78581887e-01 6.88201308e-01 3.55348140e-01
-9.41349447e-01 3.38746756e-01 -7.19697833e-01 6.22935414e-01
6.51253581e-01 -5.08767888e-02 -1.02968630e-03 6.46165729e-01
2.64333099e-01 -4.81150478e-01 -9.25144911e-01 4.73758459e-01
5.53147018e-01 -1.77639830e+00 3.26732695e-01 -3.15435469e-01
9.24505889e-01 -5.19083202e-01 -2.57547915e-01 6.35663092e-01
2.28932902e-01 -9.17128682e-01 1.00888050e+00 3.71036440e-01
1.36937067e-01 -4.62688595e-01 1.37442398e+00 5.83795130e-01
-6.82789028e-01 -7.36510232e-02 -3.09033453e-01 -1.79925308e-01
2.37115085e-01 9.29842651e-01 -9.54961181e-01 8.79386544e-01
6.13314152e-01 4.60952193e-01 -5.62909245e-01 3.47609997e-01
-4.96610880e-01 6.67413831e-01 1.13712586e-02 -1.01657724e-02
-9.18741152e-02 9.51611251e-02 4.60010797e-01 1.18366563e+00
2.66356170e-01 2.27533534e-01 3.30794789e-02 1.28116012e+00
-3.77399474e-01 6.16099909e-02 -6.26109600e-01 3.33189547e-01
7.66246438e-01 9.65834975e-01 -5.48684657e-01 -7.06558526e-01
-2.40799785e-01 8.14335823e-01 4.59975451e-01 6.36928948e-03
-1.04994547e+00 7.68439770e-02 1.22804746e-01 -1.14539161e-01
-2.27382496e-01 3.49334389e-01 -8.20724964e-01 -1.38590384e+00
5.04915237e-01 -1.15155244e+00 6.05808318e-01 -9.84209418e-01
-1.53693902e+00 5.69788814e-01 1.01141647e-01 -8.75724733e-01
-4.95368093e-01 -2.08953172e-01 -8.93263400e-01 7.02922940e-01
-1.49984646e+00 -1.47702038e+00 -1.61797702e-01 1.67162016e-01
1.00776875e+00 -1.64383873e-02 7.04148471e-01 -3.43937874e-02
-5.24045169e-01 3.91268879e-01 -6.74448490e-01 -8.64299294e-03
6.61913991e-01 -1.39175212e+00 1.89810067e-01 8.23199570e-01
1.83214247e-01 1.08154249e+00 9.19596255e-01 -1.15444624e+00
-9.83008683e-01 -8.97455454e-01 1.84016109e+00 -8.05078149e-01
6.75409317e-01 2.44008780e-01 -1.12444198e+00 7.14169860e-01
5.55908442e-01 -3.21876049e-01 6.13408208e-01 4.05290514e-01
-6.23021245e-01 3.41915995e-01 -1.37654388e+00 4.66777056e-01
8.78503680e-01 -5.44640839e-01 -1.37005138e+00 6.29398584e-01
6.68894172e-01 -5.50529122e-01 -4.33712453e-01 4.12688941e-01
3.23665023e-01 -1.16016066e+00 5.60377061e-01 -9.33872461e-01
1.26077676e+00 -5.09869635e-01 -1.67195037e-01 -1.14055085e+00
-5.97788603e-04 -7.63673931e-02 -4.07213122e-01 1.41738284e+00
8.60649109e-01 -3.94144952e-01 3.25710386e-01 6.43696368e-01
-3.63748580e-01 -9.75748360e-01 -1.09369230e+00 -5.10550737e-01
1.89367652e-01 -6.49284005e-01 7.54386306e-01 1.35300767e+00
4.98101085e-01 6.50002360e-01 -2.16655627e-01 2.31448978e-01
9.54300389e-02 5.04637599e-01 6.18784308e-01 -9.98728633e-01
-9.06194523e-02 -5.07605314e-01 -1.08211331e-01 -4.74219203e-01
4.21137184e-01 -9.06321228e-01 -3.20175327e-02 -2.00923514e+00
4.88366067e-01 -3.44714493e-01 3.27891946e-01 5.63119113e-01
-5.04314542e-01 -4.73571010e-02 -2.57546127e-01 4.14555371e-01
-5.26787162e-01 3.16300243e-01 6.97652876e-01 -3.87137592e-01
1.34094069e-02 -1.21101357e-01 -9.73729908e-01 1.00717151e+00
8.25949252e-01 -4.69414055e-01 -3.10017407e-01 -3.46883357e-01
6.85456038e-01 2.05305591e-01 5.39824486e-01 -7.06340551e-01
1.04836218e-01 -3.54089588e-01 6.36883825e-02 -6.98669374e-01
-8.13423842e-02 -4.12094146e-01 1.40919805e-01 2.77040184e-01
-6.24332666e-01 4.34037596e-01 -6.80572465e-02 5.01546502e-01
-3.81277323e-01 -5.89266837e-01 2.81530976e-01 -2.17847139e-01
-4.56577778e-01 -3.69761050e-01 -2.68914670e-01 4.84255046e-01
6.14444196e-01 -5.20434380e-02 -1.17220902e+00 -4.01892960e-01
-4.10869479e-01 -8.21987540e-02 1.18777126e-01 6.62454545e-01
7.03112602e-01 -1.19815457e+00 -8.52884233e-01 -2.61086762e-01
3.50822538e-01 -1.84044674e-01 3.10262024e-01 9.59207475e-01
-3.41796219e-01 4.54272866e-01 1.05762914e-01 -4.06257153e-01
-1.15072680e+00 2.93878078e-01 2.25207835e-01 -6.91401958e-01
-3.68759602e-01 5.63910782e-01 -4.90955114e-01 -6.00163043e-01
-3.01523656e-01 -5.91422617e-01 -5.40889561e-01 1.64519949e-03
4.82193351e-01 1.06759354e-01 3.55883688e-01 -5.97570837e-01
-3.27588111e-01 3.35702717e-01 -2.33017236e-01 -3.52391116e-02
8.29297423e-01 -1.46656439e-01 -6.30949259e-01 5.10271072e-01
5.52070141e-01 3.75055283e-01 -1.93704396e-01 -2.47899406e-02
5.27851522e-01 -1.89058170e-01 -3.18088382e-01 -1.22788072e+00
-3.81705910e-01 3.70269924e-01 -8.97750780e-02 7.26238906e-01
5.65021574e-01 3.12861443e-01 7.43287265e-01 3.59799206e-01
2.92599499e-01 -1.13362229e+00 1.06634989e-01 8.27547967e-01
1.40417337e+00 -1.43783557e+00 6.48009256e-02 -6.10762060e-01
-8.74379635e-01 9.26605582e-01 7.88531244e-01 2.03944117e-01
1.59650967e-01 2.30487496e-01 7.78869539e-02 -7.01304197e-01
-1.09294021e+00 1.29378855e-01 2.64536232e-01 2.09314600e-01
8.61334503e-01 3.76721583e-02 -1.02861965e+00 1.25477707e+00
-5.26110232e-01 -1.30090415e-01 8.12810123e-01 8.06925893e-01
-5.05224764e-01 -9.38061535e-01 -4.02804285e-01 7.21945047e-01
-6.86954021e-01 -3.19722891e-01 -8.23427856e-01 7.73959279e-01
5.09113848e-01 1.26654673e+00 -1.34096488e-01 -1.13814853e-01
3.26984972e-01 3.12698632e-01 3.19452554e-01 -5.98439217e-01
-8.50525618e-01 -6.62051976e-01 6.96441174e-01 -2.63024062e-01
-6.59124553e-01 -4.37682182e-01 -1.48536837e+00 -3.78060609e-01
-5.10213673e-01 4.31029201e-01 6.56590819e-01 1.62173069e+00
3.59265924e-01 2.96566427e-01 2.17723399e-01 1.70683917e-02
-3.93102944e-01 -1.27396321e+00 -6.41245469e-02 7.59835124e-01
8.06884617e-02 -6.03914797e-01 -4.59574908e-01 2.24124014e-01] | [9.203853607177734, 9.447497367858887] |
3766e74b-0130-43be-b503-2d0bbc24006d | on-modality-bias-recognition-and-reduction | 2202.12690 | null | https://arxiv.org/abs/2202.12690v2 | https://arxiv.org/pdf/2202.12690v2.pdf | On Modality Bias Recognition and Reduction | Making each modality in multi-modal data contribute is of vital importance to learning a versatile multi-modal model. Existing methods, however, are often dominated by one or few of modalities during model training, resulting in sub-optimal performance. In this paper, we refer to this problem as modality bias and attempt to study it in the context of multi-modal classification systematically and comprehensively. After stepping into several empirical analysis, we recognize that one modality affects the model prediction more just because this modality has a spurious correlation with instance labels. In order to primarily facilitate the evaluation on the modality bias problem, we construct two datasets respectively for the colored digit recognition and video action recognition tasks in line with the Out-of-Distribution (OoD) protocol. Collaborating with the benchmarks in the visual question answering task, we empirically justify the performance degradation of the existing methods on these OoD datasets, which serves as evidence to justify the modality bias learning. In addition, to overcome this problem, we propose a plug-and-play loss function method, whereby the feature space for each label is adaptively learned according to the training set statistics. Thereafter, we apply this method on eight baselines in total to test its effectiveness. From the results on four datasets regarding the above three tasks, our method yields remarkable performance improvements compared with the baselines, demonstrating its superiority on reducing the modality bias problem. | ['Alberto del Bimbo', 'Mohan Kankanhalli', 'Zhiyong Cheng', 'Harry Cheng', 'Liqiang Nie', 'Yangyang Guo'] | 2022-02-25 | null | null | null | null | ['multi-modal-classification'] | ['miscellaneous'] | [ 3.70836765e-01 -1.69409037e-01 -4.43611532e-01 -3.34920138e-01
-1.04379559e+00 -5.17254353e-01 9.62558985e-01 -2.58861519e-02
-4.22635674e-01 5.98838329e-01 2.47111276e-01 -2.44542584e-01
-1.20421790e-01 -3.94403428e-01 -8.94851208e-01 -7.95929015e-01
2.62257338e-01 2.73092210e-01 1.20869800e-01 3.12426928e-02
3.47911894e-01 9.19702053e-02 -1.70053065e+00 6.44764483e-01
6.33275390e-01 1.21564484e+00 -5.92272915e-02 3.49857211e-01
-1.38073623e-01 9.94109094e-01 -4.01109725e-01 -5.34582436e-01
8.97261351e-02 -5.44481814e-01 -8.86131048e-01 1.40261963e-01
7.90437639e-01 -1.80749550e-01 -9.78770554e-02 8.29581439e-01
5.58503866e-01 4.03247066e-02 1.13982236e+00 -1.48812532e+00
-6.27244115e-01 3.84159386e-01 -7.18336642e-01 1.49564192e-01
4.05723244e-01 2.00047538e-01 1.34430969e+00 -9.66295481e-01
6.35340810e-01 1.38057435e+00 6.52530253e-01 6.43341422e-01
-1.39619362e+00 -4.17659849e-01 3.58960927e-01 2.87541240e-01
-1.09731805e+00 -6.18314266e-01 8.94983113e-01 -5.05957603e-01
5.07227480e-01 2.55396694e-01 5.75492680e-02 1.62707341e+00
-9.67291966e-02 1.18585241e+00 1.47037601e+00 -6.09905958e-01
8.86443928e-02 3.67399901e-01 2.28689641e-01 4.38969195e-01
-1.30936364e-02 2.18314901e-01 -6.61130726e-01 -3.30674350e-02
3.48866165e-01 -1.66510627e-01 -2.60116607e-01 -7.09135771e-01
-1.29694498e+00 6.84234262e-01 2.95911670e-01 3.01928639e-01
-2.63404816e-01 1.24189630e-01 4.08808500e-01 3.73552233e-01
4.24850285e-01 1.51507691e-01 -3.47063273e-01 -1.49617136e-01
-6.46280169e-01 2.11579278e-01 5.26286781e-01 5.45086503e-01
6.62624896e-01 -2.95350850e-01 -5.50931573e-01 1.17265582e+00
5.33131123e-01 4.76543307e-01 5.08588791e-01 -7.73932755e-01
5.36907554e-01 6.68724239e-01 4.83250767e-02 -7.83175945e-01
-5.12460053e-01 -2.14618444e-01 -8.39175463e-01 2.49932408e-01
9.40337718e-01 1.25758484e-01 -9.47922051e-01 2.05028152e+00
4.36028570e-01 1.35770198e-02 6.03117570e-02 9.12386119e-01
8.37574482e-01 1.39211625e-01 4.55731422e-01 -8.95939767e-02
1.49574208e+00 -9.82108712e-01 -6.22943044e-01 -1.64039448e-01
6.70671046e-01 -7.03064203e-01 1.56441319e+00 3.04934919e-01
-6.80837333e-01 -5.79885960e-01 -7.77595699e-01 1.61962390e-01
-4.18376595e-01 1.67101502e-01 4.91458625e-01 6.82485521e-01
-6.04282022e-01 3.52571696e-01 -4.52960372e-01 -4.61266190e-01
5.45697749e-01 -1.60882741e-01 -3.91212881e-01 -1.97541803e-01
-1.17678237e+00 1.04356730e+00 2.45049998e-01 -2.30343148e-01
-9.63015735e-01 -8.36791217e-01 -6.27912641e-01 -2.30075300e-01
3.84153306e-01 -6.99376702e-01 1.09488618e+00 -1.20611811e+00
-1.21721387e+00 1.10588002e+00 -1.11001380e-01 -2.49323636e-01
8.71979594e-01 -7.15748742e-02 -3.62324297e-01 1.65403932e-01
1.70636885e-02 7.17102408e-01 1.23009038e+00 -1.72382069e+00
-7.80572295e-01 -2.67932147e-01 3.62337768e-01 9.51476321e-02
-4.39728647e-01 -1.18201405e-01 -3.90904367e-01 -7.25807607e-01
-5.49540929e-02 -9.41693902e-01 3.08673590e-01 -1.84939176e-01
-4.69832122e-01 -4.16663498e-01 5.32832444e-01 -3.36512685e-01
1.14939356e+00 -2.36571407e+00 3.01484257e-01 1.43319778e-02
1.46668088e-02 -5.63441738e-02 -3.04301560e-01 3.06195945e-01
-2.31553078e-01 2.96953470e-02 -1.73480809e-01 -6.41120255e-01
3.33477348e-01 1.73329949e-01 -3.00317854e-01 4.11447197e-01
3.26744825e-01 8.24737072e-01 -5.99877477e-01 -7.03708410e-01
9.39429402e-02 3.71591628e-01 -3.78444731e-01 1.44410595e-01
-2.39730999e-01 5.65769851e-01 -1.94030404e-01 9.41654980e-01
5.91414928e-01 -5.22034705e-01 6.55597299e-02 -5.25368094e-01
2.30673999e-01 -1.58772860e-02 -1.02664351e+00 1.70476401e+00
-4.24684465e-01 3.42714459e-01 -3.44091177e-01 -1.09921646e+00
3.60531092e-01 2.90636331e-01 4.06056285e-01 -1.03481650e+00
2.32451875e-02 2.63268918e-01 -1.02845810e-01 -6.74837053e-01
3.38750273e-01 -4.77639198e-01 9.79012344e-03 4.15686280e-01
1.47023678e-01 3.59364986e-01 2.71443576e-01 1.51189148e-01
7.80767202e-01 2.11344585e-01 5.66648841e-02 -1.78203615e-03
5.69056451e-01 -8.17870423e-02 1.91344887e-01 8.41306508e-01
-4.32903558e-01 6.11230552e-01 6.44716322e-01 -1.10649876e-01
-6.90263569e-01 -1.00462210e+00 -3.37260157e-01 1.50423837e+00
1.40005365e-01 -1.36442974e-01 -4.79149491e-01 -1.13542557e+00
1.43449411e-01 6.85446024e-01 -1.01039040e+00 -2.49804676e-01
-9.70999375e-02 -8.60996664e-01 6.32030666e-01 5.40906131e-01
3.85072470e-01 -1.06114471e+00 -5.83277047e-01 -3.07244509e-01
-3.03760827e-01 -1.06668127e+00 -1.36625290e-01 2.67303079e-01
-6.66498184e-01 -1.31422508e+00 -8.21790993e-01 -5.00930429e-01
3.33737850e-01 2.94755280e-01 1.32119882e+00 1.26062483e-02
9.39241052e-02 8.35034668e-01 -5.48643947e-01 -2.30814472e-01
-4.23262388e-01 2.29650572e-01 -1.82378933e-01 3.45367134e-01
4.33915675e-01 -3.85852247e-01 -5.22058606e-01 4.33214396e-01
-1.20213664e+00 -3.53546292e-02 6.56173348e-01 9.51628864e-01
4.30050462e-01 -3.11332196e-01 7.34096289e-01 -9.54014182e-01
4.13313657e-01 -5.89176536e-01 -2.53632694e-01 4.32891607e-01
-6.14448667e-01 6.55879527e-02 3.25846463e-01 -5.20109892e-01
-9.75351095e-01 -6.19773893e-03 1.40612647e-01 -4.38751638e-01
-3.80741417e-01 6.55660987e-01 -2.89885104e-01 4.45410497e-02
6.52431250e-01 1.34024322e-01 5.60283735e-02 -5.66304803e-01
4.64663804e-01 4.77209330e-01 1.93094537e-01 -6.97303414e-01
7.29958892e-01 5.11566341e-01 -1.01020094e-03 -6.30860567e-01
-1.05063260e+00 -2.72199064e-01 -4.01561201e-01 -3.74938756e-01
8.29616249e-01 -8.55630457e-01 -6.39475465e-01 5.95417857e-01
-8.93872559e-01 -3.53154719e-01 -4.95628528e-02 3.66153389e-01
-5.55026591e-01 3.76844794e-01 -3.03405970e-01 -8.29451263e-01
3.31165552e-01 -1.07290661e+00 1.01102328e+00 -1.48023246e-03
-7.70113543e-02 -1.12804341e+00 1.41034156e-01 6.24088407e-01
3.74482125e-01 2.05778852e-01 1.23704875e+00 -7.48102903e-01
-3.58786911e-01 -1.58160087e-03 -4.57880288e-01 3.64012629e-01
-9.34025347e-02 -2.02319533e-01 -1.48198783e+00 -1.71086535e-01
-2.10672989e-01 -6.84881330e-01 1.16099977e+00 2.08117008e-01
1.08812702e+00 2.28376567e-01 -1.68260247e-01 2.41455659e-01
1.36823428e+00 -2.01508641e-01 5.57515323e-01 5.96410811e-01
7.90991008e-01 7.57489860e-01 7.32809842e-01 4.03824568e-01
6.28625810e-01 8.32390189e-01 7.10997760e-01 3.36245000e-02
-3.09794635e-01 -2.20446289e-01 3.49653661e-01 2.48110339e-01
6.16556183e-02 -2.24738449e-01 -8.59031916e-01 4.70222503e-01
-1.85962260e+00 -8.16384792e-01 -1.78381562e-01 2.22922230e+00
7.65050828e-01 -5.52789308e-02 5.26646137e-01 2.92508304e-01
4.22737598e-01 3.69951040e-01 -4.51791853e-01 4.12024334e-02
-3.01957369e-01 -2.86566138e-01 2.03245550e-01 1.88941076e-01
-1.28005385e+00 6.27049923e-01 6.34551764e+00 9.48941112e-01
-1.24247694e+00 2.69070596e-01 6.64190054e-01 9.80138313e-04
-4.59962189e-01 -2.12268010e-01 -6.56589866e-01 4.86948103e-01
8.55814576e-01 3.79306853e-01 3.88400078e-01 6.11919045e-01
-2.46711746e-02 -3.28541458e-01 -1.37848210e+00 1.09639096e+00
2.44067281e-01 -8.33054423e-01 1.35172144e-01 -1.56496167e-02
5.47757685e-01 -2.06333444e-01 3.40706944e-01 5.38950503e-01
-1.63126871e-01 -1.03225255e+00 1.00292766e+00 5.41780114e-01
5.53356886e-01 -4.38453108e-01 4.65868652e-01 3.22213620e-01
-7.75534570e-01 -2.42341891e-01 -6.32284954e-02 8.40351731e-02
1.06184840e-01 4.45287168e-01 -3.60948563e-01 6.21427178e-01
6.06894553e-01 5.70762634e-01 -8.82538199e-01 8.64508033e-01
2.34612683e-03 6.66892350e-01 -2.24435348e-02 1.55185252e-01
1.58409372e-01 1.38517797e-01 4.57705796e-01 1.07908607e+00
4.19919267e-02 -4.18298304e-01 -1.60566300e-01 7.03978181e-01
-1.94640949e-01 8.25099349e-02 -4.10707057e-01 -1.52850926e-01
2.32984588e-01 1.17213953e+00 -5.23182094e-01 -3.26530814e-01
-6.89832568e-01 8.29200983e-01 3.44066679e-01 4.30212438e-01
-1.14319575e+00 9.92452800e-02 3.67454797e-01 -1.72515791e-02
3.77857208e-01 2.40667805e-01 -3.81105602e-01 -1.18366277e+00
6.55657351e-02 -1.27541232e+00 5.93270481e-01 -6.78612530e-01
-1.73429251e+00 3.44842464e-01 1.06276356e-01 -1.35631335e+00
-1.57198399e-01 -7.77502120e-01 -9.94625688e-02 7.30141222e-01
-1.82726026e+00 -1.53019404e+00 -3.82077634e-01 7.44184732e-01
3.55865330e-01 -2.20040962e-01 7.02906013e-01 7.24591672e-01
-6.10603988e-01 8.67195010e-01 -8.30268785e-02 -1.23875447e-01
1.23053873e+00 -1.31955671e+00 -3.38940918e-01 5.62086344e-01
1.82385445e-01 3.84857476e-01 6.83840394e-01 -1.76595956e-01
-1.33314681e+00 -8.03344727e-01 8.57952297e-01 -8.69852364e-01
7.82584965e-01 -6.25771657e-02 -9.19446707e-01 4.98249292e-01
1.99428558e-01 2.58183852e-02 8.54148448e-01 4.28332478e-01
-7.99467802e-01 -3.50599061e-03 -9.67157423e-01 3.78261179e-01
9.85841155e-01 -6.54663622e-01 -6.44259632e-01 2.21208826e-01
3.78740281e-01 -2.39688143e-01 -7.69789279e-01 5.60337067e-01
6.90310597e-01 -1.23580003e+00 1.00053656e+00 -9.76646960e-01
9.44500029e-01 -2.63089687e-01 -5.59762776e-01 -1.27769732e+00
-1.73391223e-01 1.11222848e-01 -2.98508078e-01 1.55757987e+00
4.93115276e-01 -5.32257736e-01 6.40173078e-01 4.62482095e-01
8.07139277e-02 -6.03798628e-01 -9.97777343e-01 -6.92166388e-01
2.83192337e-01 -5.98589182e-01 4.07425851e-01 1.10091639e+00
-3.54419500e-01 5.84245026e-01 -5.70253015e-01 -5.44155715e-03
6.35915458e-01 1.43150434e-01 8.59620333e-01 -1.07133496e+00
-3.69664222e-01 -6.22817516e-01 -1.22089386e-01 -9.97887850e-01
3.24770033e-01 -7.27579892e-01 -5.64951934e-02 -1.15325022e+00
5.26337087e-01 -4.13487554e-01 -6.74804568e-01 5.10706842e-01
-4.30688173e-01 5.07474542e-01 4.73967731e-01 3.02256048e-01
-9.54302073e-01 4.39423710e-01 1.22499061e+00 -2.81806767e-01
1.63507521e-01 -4.98838127e-02 -7.58627772e-01 5.90600729e-01
4.36011106e-01 -2.69643158e-01 -3.46535087e-01 -3.20566744e-01
3.39754283e-01 -1.54721722e-01 7.82938540e-01 -7.71760046e-01
-1.81015596e-01 -5.67716099e-02 1.79255411e-01 -4.91997123e-01
4.13654774e-01 -1.14301336e+00 -2.24581629e-01 1.88596562e-01
-5.12025654e-01 -3.21268171e-01 1.60546139e-01 6.75872564e-01
-3.71001005e-01 -2.64442563e-01 7.94138134e-01 2.20917016e-01
-9.32618499e-01 -4.09428328e-02 -1.17874689e-01 3.74133050e-01
8.19967985e-01 -1.43784389e-01 -5.47374487e-01 -2.81358451e-01
-6.59626722e-01 1.38633177e-01 3.85288179e-01 6.78913534e-01
1.35126591e-01 -1.61539006e+00 -5.50847530e-01 7.79780373e-03
6.85569823e-01 -5.45127928e-01 5.63784242e-01 1.36402094e+00
3.83557975e-02 4.20915157e-01 -1.57466471e-01 -8.61385763e-01
-1.23140490e+00 6.14291728e-01 4.06177431e-01 -3.63863766e-01
-7.68765658e-02 6.90954149e-01 2.88233608e-01 -3.57425690e-01
4.52137649e-01 -2.30791345e-01 -3.44702005e-01 5.36257803e-01
4.66749460e-01 3.73565167e-01 3.68252443e-03 -6.45327628e-01
-5.16567349e-01 5.07185221e-01 1.15236260e-01 -1.70311913e-01
1.09163165e+00 -2.99800158e-01 1.00968666e-01 8.91769826e-01
1.18738496e+00 -1.20347686e-01 -1.34181333e+00 -2.04458281e-01
1.17573820e-01 -4.99524027e-01 -2.05150098e-01 -1.11318874e+00
-9.51499701e-01 8.96603048e-01 9.38936830e-01 5.46116769e-01
1.06801546e+00 1.15448080e-01 2.98158765e-01 4.89610396e-02
1.52542010e-01 -1.03758216e+00 3.20385933e-01 4.85731870e-01
7.74340272e-01 -1.85131574e+00 -3.43184918e-01 -1.52806923e-01
-9.60405707e-01 8.22225273e-01 4.76868927e-01 2.18235508e-01
5.28837383e-01 -2.63606042e-01 3.92572761e-01 -1.95455596e-01
-6.89599156e-01 -2.46446669e-01 5.05036414e-01 5.83395839e-01
5.98132253e-01 -1.34843603e-01 -2.74193883e-01 5.40395677e-01
3.72270226e-01 -7.74894550e-04 -1.06425630e-02 7.60544956e-01
-2.29570389e-01 -1.16352665e+00 -4.91676509e-01 3.86441290e-01
-3.93663287e-01 4.00585309e-02 -4.13870633e-01 9.46014762e-01
9.24791694e-02 9.64343786e-01 -2.47334003e-01 -3.43780816e-01
5.99331856e-01 4.19091046e-01 5.89217901e-01 -1.48792505e-01
-5.19201159e-01 -5.76249734e-02 1.22490421e-01 -5.91320038e-01
-8.65710914e-01 -6.75687313e-01 -7.81480670e-01 -4.92010824e-02
-1.87527835e-01 -3.12424541e-01 5.41993082e-01 1.07720649e+00
2.23618820e-01 6.76391065e-01 4.93160576e-01 -7.31241763e-01
-9.30876136e-01 -1.16794491e+00 -5.20391107e-01 1.02054465e+00
2.39889771e-01 -1.15304601e+00 -6.87920570e-01 3.33115309e-02] | [10.549508094787598, 1.664299726486206] |
e7b1bb04-744d-4085-bc08-aee82ca31b33 | hyperspectral-unmixing-with-endmember | 1703.06151 | null | http://arxiv.org/abs/1703.06151v1 | http://arxiv.org/pdf/1703.06151v1.pdf | Hyperspectral Unmixing with Endmember Variability using Semi-supervised Partial Membership Latent Dirichlet Allocation | A semi-supervised Partial Membership Latent Dirichlet Allocation approach is
developed for hyperspectral unmixing and endmember estimation while accounting
for spectral variability and spatial information. Partial Membership Latent
Dirichlet Allocation is an effective approach for spectral unmixing while
representing spectral variability and leveraging spatial information. In this
work, we extend Partial Membership Latent Dirichlet Allocation to incorporate
any available (imprecise) label information to help guide unmixing.
Experimental results on two hyperspectral datasets show that the proposed
semi-supervised PM-LDA can yield improved hyperspectral unmixing and endmember
estimation results. | ['Hao Sun', 'Alina Zare', 'Sheng Zou'] | 2017-03-17 | null | null | null | null | ['hyperspectral-unmixing'] | ['computer-vision'] | [ 3.87738913e-01 -4.24230725e-01 -6.03627741e-01 -2.04123318e-01
-6.46631539e-01 -7.34308183e-01 5.55476964e-01 -1.17519014e-01
2.47680172e-01 7.79705226e-01 2.64236063e-01 -3.32976788e-01
-2.30550557e-01 -8.29426646e-01 1.10582300e-01 -1.19260001e+00
2.07508773e-01 7.44794548e-01 -5.97105622e-01 5.36348403e-01
-5.06316237e-02 6.96732461e-01 -1.42323124e+00 2.17411265e-01
1.33030105e+00 4.25877273e-01 4.14107382e-01 3.94394130e-01
-1.03793018e-01 2.66663581e-01 -3.61364245e-01 7.18194664e-01
3.17014903e-01 -9.91785377e-02 -6.66990757e-01 9.56222773e-01
3.26008052e-01 -3.90672147e-01 1.38539121e-01 1.40008152e+00
4.67676550e-01 3.73851061e-01 1.36949706e+00 -1.13076770e+00
-5.87025285e-01 7.03654766e-01 -1.07077658e+00 -2.46381238e-01
-2.60673314e-01 -9.42189023e-02 7.21463859e-01 -8.16759169e-01
-5.55649353e-03 1.30191779e+00 6.97559953e-01 -1.62653357e-01
-1.33258319e+00 -7.48303950e-01 9.06772316e-02 2.83315554e-02
-1.87262058e+00 -2.08545879e-01 8.07451725e-01 -9.91568267e-01
7.62284875e-01 3.53589088e-01 5.02263069e-01 2.16337264e-01
-2.97722548e-01 7.53587663e-01 1.49307716e+00 -5.66308737e-01
4.44397420e-01 3.29425260e-02 4.82875288e-01 1.12792172e-01
4.67194438e-01 2.06023812e-01 -9.27200317e-02 -8.34049940e-01
5.26156723e-01 5.40017486e-01 -2.20352620e-01 -4.05444056e-01
-9.00290906e-01 8.36155713e-01 1.39359042e-01 -1.64573118e-01
-8.12706113e-01 -3.56725782e-01 -1.20485127e-01 -5.13243526e-02
1.11353564e+00 2.17988282e-01 -1.69346049e-01 4.07151014e-01
-1.67273903e+00 -2.59021819e-01 4.24678802e-01 8.99308324e-01
1.47887886e+00 5.43109298e-01 -6.27616420e-02 1.33675861e+00
8.86010289e-01 1.30272341e+00 4.87154871e-01 -8.85086715e-01
-2.15920687e-01 5.08453429e-01 6.20934725e-01 -6.91460192e-01
-2.27750748e-01 -1.48857668e-01 -9.21765208e-01 2.07226977e-01
-2.11839974e-01 -2.94551581e-01 -1.51272607e+00 1.08032644e+00
1.51082620e-01 3.31899107e-01 2.31251314e-01 9.26999748e-01
5.68942189e-01 1.21591079e+00 5.91330707e-01 -7.57108152e-01
1.02742112e+00 -7.43967712e-01 -9.15989816e-01 -2.98676193e-01
2.60609597e-01 -7.95524359e-01 5.10162592e-01 4.36830610e-01
-4.21287984e-01 -3.62637430e-01 -1.12171853e+00 4.67650533e-01
-2.61113763e-01 3.57694775e-01 7.18132019e-01 1.00551450e+00
-6.66777909e-01 2.65934229e-01 -9.86229241e-01 -1.29792064e-01
4.65130478e-01 8.10087174e-02 -1.16645731e-02 -3.35233212e-01
-9.52035546e-01 4.91472274e-01 1.02651072e+00 -3.04448847e-02
-1.22685516e+00 -5.17023563e-01 -8.34378898e-01 -9.66441110e-02
-2.17338890e-01 -1.48793727e-01 8.30097079e-01 -9.97677147e-01
-1.44215858e+00 7.72302449e-01 -5.41388571e-01 -9.40354168e-02
-1.67213738e-01 1.82604790e-01 -8.03517878e-01 3.11806530e-01
1.79831579e-01 6.38901711e-01 1.29454386e+00 -1.60241115e+00
-2.54083157e-01 -5.41997850e-01 -6.29906714e-01 5.44149339e-01
-5.64730346e-01 -2.49378145e-01 4.36630487e-01 -7.51280069e-01
8.50218296e-01 -1.08752644e+00 -2.26180241e-01 -4.15046632e-01
-2.11175308e-01 1.46327794e-01 1.24148130e+00 -9.44360495e-01
1.01056278e+00 -2.13327527e+00 2.41994597e-02 4.02408540e-01
-1.11169145e-02 5.31896412e-01 1.17401243e-03 3.19027364e-01
-4.11859781e-01 -1.01743145e-02 -1.00051081e+00 -2.73560256e-01
7.85241649e-02 2.58931071e-01 -4.35112298e-01 7.87228465e-01
-2.40887076e-01 5.52221894e-01 -1.02057433e+00 -5.05751595e-02
6.07317030e-01 5.32476366e-01 2.50697341e-02 3.67305018e-02
-4.08405095e-01 3.02302420e-01 9.43101123e-02 1.01999044e+00
1.43466067e+00 -8.64116997e-02 4.46717530e-01 -1.30609080e-01
-1.50658816e-01 -2.73899078e-01 -1.46895480e+00 1.55419767e+00
-8.53434727e-02 5.20318866e-01 3.28738421e-01 -8.87011886e-01
1.06946516e+00 6.20620847e-01 6.10869050e-01 2.92785347e-01
-2.57756323e-01 7.53596351e-02 -5.37201881e-01 -2.00355947e-01
5.67617893e-01 -8.52826178e-01 5.31031251e-01 8.51825058e-01
3.49025540e-02 -4.16552603e-01 -2.98900664e-01 -1.88743934e-01
-4.22915304e-03 3.69896255e-02 6.19562209e-01 -7.93619990e-01
3.24606091e-01 4.43754107e-01 4.35035259e-01 3.91962081e-01
-2.19416171e-01 4.43058789e-01 -3.26083481e-01 -1.15532778e-01
-1.04101694e+00 -1.13520634e+00 -6.36721671e-01 1.13312292e+00
-1.16432555e-01 1.71664029e-01 -3.37726980e-01 -7.21126795e-02
1.82929337e-02 9.33804989e-01 -1.05170950e-01 1.23740181e-01
4.97333407e-01 -1.85311258e+00 3.58743519e-01 3.95430505e-01
5.46913922e-01 -4.52657342e-01 3.43741655e-01 2.91296601e-01
-3.29275995e-01 -2.93598562e-01 -3.52870747e-02 2.15592813e-02
-1.08503592e+00 -8.52928579e-01 -1.10634267e+00 -5.72236657e-01
7.75868058e-01 8.30043852e-01 6.07898712e-01 -9.16551232e-01
-1.92861259e-01 3.92724484e-01 -4.08402264e-01 -5.39515853e-01
-5.64481616e-01 -1.89906627e-01 2.04952314e-01 1.64792687e-01
8.99236500e-01 -8.55287194e-01 -4.41206068e-01 5.31115711e-01
-1.36259413e+00 -6.42475933e-02 3.87837857e-01 6.31088674e-01
7.27621794e-01 6.63411200e-01 5.93604565e-01 -8.97530973e-01
4.20776397e-01 -7.95748770e-01 -5.86316943e-01 1.79626301e-01
-9.48171556e-01 -3.19930047e-01 -2.17641890e-01 -5.23395002e-01
-1.61199272e+00 1.54969215e-01 4.68543559e-01 -3.07841390e-01
-6.13252521e-01 8.78049314e-01 -5.10914803e-01 9.91873965e-02
8.83535326e-01 3.50221664e-01 -3.51434313e-02 -6.11423433e-01
6.32825971e-01 1.42402613e+00 2.33982816e-01 -5.29386878e-01
5.46926916e-01 9.69724357e-01 -2.19827980e-01 -1.45612919e+00
-7.79052198e-01 -1.24965382e+00 -9.92867172e-01 1.80650294e-01
7.04292178e-01 -1.62683046e+00 2.53750056e-01 8.86552274e-01
-7.00504899e-01 -2.84899950e-01 -2.74534464e-01 7.80644417e-01
-3.59587401e-01 9.48121011e-01 -1.74193054e-01 -1.11817992e+00
-3.12993646e-01 -7.77669609e-01 7.28696644e-01 -2.45581925e-01
-4.09407541e-03 -1.32566130e+00 3.01357478e-01 4.40894037e-01
2.60892212e-01 2.17506602e-01 7.89510071e-01 -3.80965471e-01
-1.01239853e-01 -2.02555582e-01 -4.82555836e-01 7.44063437e-01
8.05421650e-01 -1.38176769e-01 -1.36786330e+00 -3.72296154e-01
1.76343456e-01 2.02487614e-02 1.19554889e+00 8.66988361e-01
7.66051829e-01 -2.77352661e-01 -2.64280617e-01 5.95806241e-01
1.51875460e+00 6.36673868e-02 5.96458316e-01 -3.82879376e-02
1.04251075e+00 4.55148339e-01 4.78399247e-01 9.25029159e-01
8.33475292e-02 -1.26007959e-01 4.35273618e-01 -2.00686216e-01
3.29592645e-01 6.63015172e-02 1.99937403e-01 6.54573619e-01
1.20333120e-01 -9.90319997e-02 -1.25901115e+00 7.89387345e-01
-1.74779451e+00 -1.06218624e+00 -5.49978912e-01 2.10158706e+00
9.38880324e-01 -9.73286331e-01 -7.96560198e-02 2.31899038e-01
1.18558621e+00 5.41420221e-01 -5.94304323e-01 2.45981708e-01
-5.67650080e-01 -2.77151525e-01 8.11211646e-01 9.46234643e-01
-1.42774856e+00 1.05997503e+00 6.88701773e+00 8.42366934e-01
-8.99623930e-01 4.63857651e-01 3.47674668e-01 2.13812977e-01
-5.21512866e-01 2.00361252e-01 -5.68053007e-01 2.54096270e-01
6.30904257e-01 -7.34868795e-02 4.75623965e-01 5.59898198e-01
4.94446009e-01 -3.73155832e-01 -3.57015997e-01 1.07573545e+00
2.35191792e-01 -8.56460333e-01 4.25888389e-01 1.62257433e-01
1.61059618e+00 1.91821888e-01 2.75248215e-02 -3.14535886e-01
8.34457219e-01 -9.55661595e-01 1.30650297e-01 6.29675627e-01
8.91488075e-01 -7.74952888e-01 5.38597941e-01 6.09337091e-01
-1.04813910e+00 -3.04466090e-03 -8.66569757e-01 -2.25419924e-01
1.85872123e-01 1.25484383e+00 -9.05001640e-01 4.67262954e-01
7.49884918e-02 9.66619313e-01 2.51568258e-02 1.06762719e+00
-5.42367816e-01 9.20094371e-01 -4.47616100e-01 7.41890550e-01
1.85761794e-01 -7.02375948e-01 7.88825452e-01 1.18963647e+00
5.53580701e-01 4.03983325e-01 4.06051099e-01 1.05599475e+00
2.83825248e-01 1.06732503e-01 -3.78460765e-01 -4.99828845e-01
7.18090534e-01 1.08571196e+00 -6.06385469e-01 -6.57068431e-01
1.39276057e-01 9.03777599e-01 -6.14403665e-01 7.88130045e-01
-3.26232821e-01 1.61215648e-01 7.68367946e-01 1.58535808e-01
-2.89466772e-02 -7.06636190e-01 -3.77431899e-01 -1.30780351e+00
-8.18535626e-01 -5.84474087e-01 5.35880029e-01 -1.08613586e+00
-1.48824930e+00 8.58909041e-02 4.99084055e-01 -1.28854012e+00
-9.47169960e-03 -5.76756895e-01 -3.57538909e-01 1.44152594e+00
-1.86634731e+00 -1.48684800e+00 -4.32268232e-01 3.76183838e-01
2.07916155e-01 -3.58075023e-01 1.23606241e+00 -7.33559504e-02
-4.69030112e-01 -3.38062704e-01 9.69096124e-01 -3.55221510e-01
8.30075026e-01 -1.27492690e+00 -3.88072193e-01 1.00078988e+00
-7.27932677e-02 4.94909883e-01 4.67378765e-01 -1.00300455e+00
-7.25838244e-01 -1.62889504e+00 1.92327797e-01 1.04219176e-01
6.40795588e-01 5.03294051e-01 -7.88227677e-01 7.15344846e-01
1.13217622e-01 -4.33240831e-01 1.69823766e+00 6.00553453e-02
-2.93984056e-01 1.06906623e-01 -1.25526345e+00 1.24089397e-03
7.43118450e-02 -7.98093736e-01 -4.66665030e-01 8.17306280e-01
2.74480283e-01 2.58089781e-01 -1.04328597e+00 3.83595228e-01
2.97351569e-01 -1.97046280e-01 1.02249086e+00 -2.53646553e-01
-7.35361353e-02 -6.60987854e-01 -5.44055045e-01 -1.65845704e+00
-8.59171391e-01 -6.01273894e-01 -1.60417527e-01 1.20342672e+00
3.15710813e-01 -5.23062468e-01 7.06836402e-01 5.22899806e-01
-1.34314233e-02 6.55176461e-01 -3.23327512e-01 -7.33686626e-01
2.64376402e-01 -3.14929456e-01 7.32565522e-01 1.64166534e+00
1.70974806e-02 -1.60921738e-01 -6.22142315e-01 9.15662646e-01
1.12043762e+00 3.18315059e-01 3.52037281e-01 -1.70448506e+00
8.02342743e-02 -1.48801997e-01 4.34806459e-02 -8.61440480e-01
6.02122962e-01 -1.02419889e+00 6.09018281e-02 -1.69138598e+00
4.18286026e-01 -2.95601547e-01 -3.39597255e-01 5.83457828e-01
-3.16353232e-01 4.77591872e-01 -4.49209720e-01 9.08511519e-01
-1.84937138e-02 5.13071239e-01 7.30820596e-01 -6.69764578e-01
-6.44010246e-01 -5.83586320e-02 -6.26791954e-01 8.65024745e-01
1.16822326e+00 -5.05133808e-01 -5.78867555e-01 -4.39442426e-01
-5.06032333e-02 -2.72285134e-01 2.23766848e-01 -8.95698667e-01
-1.69660375e-02 -6.77658498e-01 2.99583286e-01 -9.91089642e-01
3.95542741e-01 -9.22562838e-01 5.18846452e-01 -6.26655519e-02
6.32797554e-02 -1.06044137e+00 5.07764995e-01 7.70230055e-01
-2.79720306e-01 -4.41909730e-01 1.03991461e+00 -1.87542319e-01
-9.72872436e-01 5.19239604e-01 -9.02110994e-01 -6.41576290e-01
8.46200049e-01 -3.54216278e-01 -1.26142561e-01 -1.84787452e-01
-1.39280176e+00 6.45902231e-02 6.26442730e-01 -2.52199590e-01
4.93845850e-01 -1.40728652e+00 -1.05441248e+00 3.98096949e-01
4.01770443e-01 -6.00893609e-02 5.81573725e-01 4.07711238e-01
-6.61724687e-01 4.53448355e-01 -3.07731777e-01 -6.65255010e-01
-1.08207965e+00 4.57961202e-01 3.65202814e-01 1.85766801e-01
1.10889010e-01 7.01257527e-01 8.93516839e-02 -7.34026492e-01
-2.15644717e-01 2.08056103e-02 -2.51982123e-01 6.65357172e-01
5.93116581e-01 8.73724997e-01 -1.83912888e-01 -8.32091749e-01
-1.30203050e-02 2.23425716e-01 4.58841115e-01 -2.65040576e-01
1.31705749e+00 -5.82558095e-01 -9.50183392e-01 6.39207006e-01
8.23469758e-01 -3.10881793e-01 -1.38970172e+00 -6.94190204e-01
-2.42950574e-01 -5.28490186e-01 8.14655483e-01 -9.62132573e-01
-5.00487506e-01 1.29973447e+00 7.96009123e-01 9.29969698e-02
1.18120217e+00 -4.38662440e-01 7.12890103e-02 3.91604632e-01
3.88364121e-02 -1.10034823e+00 -4.78700995e-01 3.34211260e-01
4.96733904e-01 -1.46825349e+00 5.24413109e-01 -4.35810775e-01
-6.00926936e-01 9.08662856e-01 5.93803376e-02 2.48145074e-01
1.15232337e+00 -5.37362173e-02 1.64952710e-01 -2.22489372e-01
1.18818544e-01 -2.55540520e-01 4.61950332e-01 1.10238791e+00
3.38212878e-01 9.23901677e-01 1.26294076e-01 2.83811301e-01
4.51670706e-01 -2.87657261e-01 3.47435117e-01 7.23503649e-01
-1.27601731e+00 -1.07764542e+00 -1.10336900e+00 5.56866705e-01
-5.20847365e-02 -5.58300316e-01 -3.69966656e-01 -3.16395581e-01
2.83510052e-02 1.18001187e+00 -1.21773332e-01 1.78360775e-01
-5.67117095e-01 5.21982849e-01 7.97929615e-03 -1.18843269e+00
5.27900875e-01 6.52609468e-01 -1.64513320e-01 3.69540185e-01
-1.07364857e+00 -6.43100679e-01 -8.63307357e-01 -3.09054822e-01
-7.37389624e-01 3.07767123e-01 6.98071480e-01 7.81214714e-01
4.96803783e-02 1.16456039e-02 6.02567017e-01 -1.22431374e+00
-5.04312098e-01 -1.44777489e+00 -1.52333772e+00 -2.79093906e-02
1.84973180e-01 -5.01368582e-01 -5.76126993e-01 5.40520847e-01] | [10.033674240112305, -2.021247386932373] |
11ca1c67-b175-4a65-96a1-c2003cfe2faa | semi-supervised-domain-adaptation-via-2 | 2305.02693 | null | https://arxiv.org/abs/2305.02693v2 | https://arxiv.org/pdf/2305.02693v2.pdf | Semi-supervised Domain Adaptation via Prototype-based Multi-level Learning | In semi-supervised domain adaptation (SSDA), a few labeled target samples of each class help the model to transfer knowledge representation from the fully labeled source domain to the target domain. Many existing methods ignore the benefits of making full use of the labeled target samples from multi-level. To make better use of this additional data, we propose a novel Prototype-based Multi-level Learning (ProML) framework to better tap the potential of labeled target samples. To achieve intra-domain adaptation, we first introduce a pseudo-label aggregation based on the intra-domain optimal transport to help the model align the feature distribution of unlabeled target samples and the prototype. At the inter-domain level, we propose a cross-domain alignment loss to help the model use the target prototype for cross-domain knowledge transfer. We further propose a dual consistency based on prototype similarity and linear classifier to promote discriminative learning of compact target feature representation at the batch level. Extensive experiments on three datasets, including DomainNet, VisDA2017, and Office-Home demonstrate that our proposed method achieves state-of-the-art performance in SSDA. | ['Wenkai Chen', 'Chuang Zhu', 'Xinyang Huang'] | 2023-05-04 | null | null | null | null | ['pseudo-label'] | ['miscellaneous'] | [ 1.65605381e-01 -1.27483308e-01 -7.90736020e-01 -7.90635586e-01
-9.97274578e-01 -6.78610623e-01 4.59160477e-01 -3.50021422e-02
-2.26099387e-01 6.27430141e-01 -7.91705474e-02 5.76717034e-02
4.78302613e-02 -5.74685097e-01 -6.82387352e-01 -6.58208072e-01
2.91223705e-01 6.74564600e-01 4.95074362e-01 7.11345747e-02
-2.13974506e-01 3.46422702e-01 -1.11172998e+00 6.03995323e-01
9.96989131e-01 1.21830881e+00 4.74477351e-01 -2.61218727e-01
-3.44700277e-01 4.69366759e-01 -3.01826298e-01 -6.26106262e-02
5.28759003e-01 -3.14743489e-01 -7.72711515e-01 3.13785851e-01
5.56352794e-01 -3.45371038e-01 -8.85886922e-02 1.00245774e+00
4.67498720e-01 9.46241319e-02 8.99512529e-01 -1.40806246e+00
-7.72779882e-01 4.00588930e-01 -7.67173469e-01 -2.93706097e-02
-2.28919480e-02 7.10575581e-02 6.95257902e-01 -1.09218538e+00
7.54334927e-01 1.32638228e+00 5.67103922e-01 6.24608219e-01
-1.19312811e+00 -1.16316736e+00 5.98854959e-01 3.41948122e-01
-1.48606861e+00 -4.34842885e-01 9.74988341e-01 -4.30887848e-01
4.10849750e-01 -4.12262201e-01 9.70463455e-02 1.11351895e+00
-3.89111012e-01 1.07482195e+00 1.32040417e+00 -4.63347852e-01
1.79244116e-01 7.00262785e-01 2.88685143e-01 4.61621493e-01
1.47328926e-02 1.02613077e-01 -4.40735310e-01 -2.24312708e-01
5.89065075e-01 8.75122845e-03 -1.93172798e-01 -1.09399331e+00
-1.14025962e+00 9.07709062e-01 4.52702254e-01 1.13427788e-01
-3.24327648e-01 -6.08010948e-01 3.95297378e-01 3.86519670e-01
5.37880063e-01 7.40658939e-02 -7.69561470e-01 3.87991041e-01
-8.01671326e-01 -2.93957330e-02 4.40006584e-01 1.37827480e+00
1.03011882e+00 -2.11114123e-01 -2.62426019e-01 1.26438046e+00
4.85910565e-01 6.96007013e-01 7.25287020e-01 -5.98591447e-01
7.31500328e-01 8.55433345e-01 5.68591543e-02 -3.13710332e-01
-1.08951451e-02 -4.67321187e-01 -5.97064853e-01 1.54694706e-01
4.56828386e-01 2.48718802e-02 -9.25144970e-01 1.78401423e+00
7.78437078e-01 4.24694866e-01 3.74386281e-01 7.71916926e-01
4.99106467e-01 6.87482953e-01 2.11286768e-01 -2.95108467e-01
1.17793071e+00 -1.27471578e+00 -2.40599290e-01 -3.80513340e-01
8.63440037e-01 -6.52449191e-01 1.10046959e+00 1.65559053e-01
-5.76217592e-01 -9.71037090e-01 -1.16858315e+00 9.32955295e-02
-4.08759564e-01 3.85318696e-01 7.71034360e-02 4.02648717e-01
-4.35348839e-01 4.41954166e-01 -4.88535583e-01 -4.02503967e-01
9.16115522e-01 2.10145384e-01 -4.48001623e-01 -6.11967981e-01
-1.10001886e+00 7.70208657e-01 7.45260119e-01 -4.16783929e-01
-9.86815870e-01 -1.00169098e+00 -7.99920976e-01 -2.01095611e-01
2.48699233e-01 -4.34937537e-01 1.19928479e+00 -1.27050674e+00
-1.38264143e+00 1.02530372e+00 -2.55118549e-01 -3.10886443e-01
4.54970360e-01 -2.19630063e-01 -5.39374888e-01 6.55338541e-02
2.85498321e-01 9.26868320e-01 8.01428974e-01 -1.40037668e+00
-9.65270162e-01 -5.29668987e-01 -2.92788744e-01 4.43882406e-01
-6.92076623e-01 -3.15821141e-01 -3.16385925e-01 -5.49312890e-01
-3.60855199e-02 -8.44396591e-01 9.93840694e-02 1.28998563e-01
-1.11877918e-01 -6.25506818e-01 1.03784454e+00 -4.28092778e-01
9.44963753e-01 -2.35149741e+00 -3.06624863e-02 2.42438361e-01
-1.28718272e-01 5.75926065e-01 -4.82512414e-01 -8.61279666e-03
-1.95418492e-01 -4.84616190e-01 -2.12038234e-01 -2.69344389e-01
-2.16609970e-01 1.51047423e-01 -4.72410202e-01 3.10772747e-01
3.30139428e-01 6.27116621e-01 -9.39293385e-01 -6.35965347e-01
9.16042253e-02 2.08287939e-01 -3.17766815e-01 4.71797973e-01
-1.30503014e-01 5.75156808e-01 -6.82397664e-01 6.42179251e-01
9.90187764e-01 -4.27542597e-01 2.50937939e-01 -3.28948289e-01
3.51757377e-01 7.33492523e-02 -1.19741786e+00 2.00916719e+00
-4.60884094e-01 1.69657990e-02 -6.07215986e-02 -1.15248799e+00
1.19132423e+00 4.03414220e-02 3.91621530e-01 -8.00364912e-01
-2.03243002e-01 3.39270234e-01 -1.17444552e-01 -1.20217174e-01
1.04354873e-01 -1.58211932e-01 6.95286989e-02 3.93324137e-01
3.42437148e-01 3.74921083e-01 -2.07238585e-01 4.62435484e-02
5.78064382e-01 4.75078106e-01 4.65892762e-01 -2.61312276e-01
6.88518345e-01 2.44945794e-01 7.55973041e-01 4.87001002e-01
-5.34176230e-01 4.13741112e-01 -1.18502781e-01 -2.93717116e-01
-1.03927922e+00 -1.16469681e+00 -2.42905274e-01 1.49219179e+00
3.89722794e-01 2.48015299e-01 -5.44381618e-01 -1.39930654e+00
3.18201423e-01 8.09774399e-01 -5.49216866e-01 -5.07099509e-01
-4.42874998e-01 -4.08482045e-01 2.46325314e-01 6.71859562e-01
7.04858243e-01 -8.57725859e-01 6.92287236e-02 2.86309391e-01
-1.92604408e-01 -1.19562089e+00 -6.97322249e-01 2.87653327e-01
-1.01180637e+00 -9.53817368e-01 -1.04605758e+00 -1.19300413e+00
8.66882324e-01 4.63741392e-01 7.85740972e-01 -5.53881347e-01
5.48445061e-02 3.08417052e-01 -4.90649581e-01 -1.53712735e-01
-5.16221464e-01 1.74840719e-01 2.94792950e-01 2.26704359e-01
8.31062376e-01 -4.93028343e-01 -3.29227835e-01 6.88213170e-01
-5.31623065e-01 2.93586813e-02 7.77257442e-01 8.94601285e-01
8.81709158e-01 -3.09851229e-01 9.61247325e-01 -1.06271088e+00
3.29913855e-01 -8.77677858e-01 -4.03738350e-01 6.49682522e-01
-8.09913158e-01 3.62756401e-02 8.21281135e-01 -1.01079226e+00
-1.19593143e+00 3.29681456e-01 4.06171948e-01 -9.11952078e-01
-3.69996190e-01 2.17046931e-01 -6.55162036e-01 -2.89701428e-02
8.26590598e-01 5.42797625e-01 -5.34934923e-03 -6.68215334e-01
4.87245470e-01 9.62927163e-01 4.25573140e-01 -7.73802757e-01
7.41524994e-01 3.10363621e-01 -3.35810214e-01 -3.50851893e-01
-1.04624701e+00 -8.24533880e-01 -9.99362707e-01 7.30577810e-03
4.52968985e-01 -1.41981936e+00 4.10870612e-02 4.77724999e-01
-8.94715905e-01 -5.37818432e-01 -4.14806813e-01 4.84121442e-01
-4.69912022e-01 3.98697674e-01 3.58576253e-02 -5.03478110e-01
-1.99442863e-01 -1.06306553e+00 9.49404895e-01 3.78940195e-01
1.36387423e-01 -9.52729225e-01 2.53372397e-02 3.38519394e-01
1.83473870e-01 -2.27544665e-01 8.50737333e-01 -1.30218422e+00
-2.45972425e-01 -1.18001923e-01 -4.88348275e-01 6.80967152e-01
4.03313547e-01 -7.74833798e-01 -1.05429852e+00 -6.56494796e-01
-1.26954928e-01 -8.71564865e-01 7.72404552e-01 2.16921031e-01
1.03457463e+00 -8.22755229e-03 -7.35649467e-01 6.05953991e-01
1.33727682e+00 1.61911666e-01 1.23106681e-01 3.24398428e-01
8.22147071e-01 6.25842273e-01 1.27362227e+00 3.81776392e-01
6.21661782e-01 7.58805811e-01 1.75385736e-02 9.00070965e-02
-5.04922688e-01 -4.23044562e-01 5.42875350e-01 7.23017156e-01
5.88759303e-01 -1.44294710e-04 -8.61590385e-01 7.23777711e-01
-1.75442684e+00 -5.56864262e-01 3.42008084e-01 2.28372741e+00
1.05733490e+00 4.65080999e-02 3.78657818e-01 -4.30292934e-01
9.96966362e-01 -1.37707636e-01 -1.11014926e+00 1.79963186e-01
-1.89917013e-02 -1.58073261e-01 5.66722512e-01 2.97314286e-01
-1.39961529e+00 9.47126627e-01 5.47060728e+00 1.38885331e+00
-1.12172794e+00 2.86091000e-01 5.31277657e-01 1.08337440e-01
-1.29191566e-03 -2.07775876e-01 -1.29728949e+00 6.72124028e-01
8.81469131e-01 -2.36572653e-01 1.85513169e-01 1.50305724e+00
-2.04691052e-01 1.95396557e-01 -1.46728849e+00 9.34376597e-01
-2.21332535e-02 -9.71692204e-01 3.24349940e-01 7.98845440e-02
7.86820710e-01 2.44602817e-03 6.32211566e-02 6.90772116e-01
4.91668284e-01 -4.70348924e-01 4.58554327e-01 2.84588933e-01
1.01844323e+00 -6.35378540e-01 4.41391051e-01 4.84436780e-01
-1.26918757e+00 -2.20018625e-01 -6.54204786e-01 5.09812772e-01
-1.28305793e-01 3.75712961e-01 -1.20457232e+00 7.79430926e-01
4.58171010e-01 9.28287506e-01 -6.44240856e-01 8.52620840e-01
1.67169012e-02 6.81583643e-01 -2.32794791e-01 3.31408203e-01
1.82664931e-01 -4.34557088e-02 2.04965532e-01 1.07967162e+00
2.51330405e-01 -2.51381975e-02 6.84571147e-01 6.49797261e-01
-1.84484839e-01 2.53503531e-01 -4.99408871e-01 5.84625490e-02
9.52273607e-01 9.89229798e-01 -3.51866275e-01 -5.96339583e-01
-5.96619606e-01 1.10903430e+00 5.82519412e-01 3.65229458e-01
-6.96460605e-01 -2.52787083e-01 6.17694318e-01 1.00705601e-01
4.43827182e-01 1.12573318e-01 -2.11130396e-01 -1.14004195e+00
1.35474533e-01 -8.19770575e-01 6.74517930e-01 -4.37028259e-01
-1.75323248e+00 2.93064803e-01 1.47892520e-01 -1.73193121e+00
-1.84521720e-01 -5.35392284e-01 -3.84669155e-01 1.07530046e+00
-1.81909728e+00 -1.68865561e+00 -2.12747648e-01 9.66194332e-01
6.83839262e-01 -7.08156765e-01 7.94910491e-01 4.84793633e-01
-2.84647077e-01 1.09451640e+00 5.11195540e-01 2.04971001e-01
1.40189540e+00 -9.24336970e-01 1.85556620e-01 5.67967176e-01
-3.90333943e-02 4.91164029e-01 1.26331881e-01 -6.61837161e-01
-9.78823781e-01 -1.48927486e+00 5.43330431e-01 -3.65726411e-01
3.80073816e-01 -1.83153570e-01 -1.29721892e+00 7.72769988e-01
-1.78820536e-01 2.52009541e-01 8.83997560e-01 1.51540309e-01
-8.61158490e-01 -4.92233813e-01 -1.42191184e+00 7.40650073e-02
9.14634287e-01 -5.34177840e-01 -7.53558457e-01 3.73057097e-01
8.12835217e-01 -8.38723406e-02 -9.21710968e-01 5.55937111e-01
5.25667727e-01 -4.91335362e-01 1.12911642e+00 -7.13297963e-01
2.04875693e-01 -3.65427315e-01 -2.63543397e-01 -1.48325717e+00
-5.17671764e-01 1.61062837e-01 -1.11471556e-01 1.48339355e+00
2.23448530e-01 -5.92135668e-01 7.14306653e-01 2.96632528e-01
-2.67045140e-01 -6.18863761e-01 -8.94166410e-01 -1.25692618e+00
4.92906004e-01 -1.20124243e-01 5.20222604e-01 1.47714221e+00
-1.44067869e-01 3.60165894e-01 -2.61292577e-01 4.17056113e-01
8.32409978e-01 4.50182259e-01 8.42271328e-01 -1.37733757e+00
-2.40935564e-01 -1.88959196e-01 -1.03311002e-01 -1.42662013e+00
2.87684917e-01 -1.27038896e+00 -2.14513876e-02 -1.12093079e+00
4.35826421e-01 -8.38973284e-01 -7.18931615e-01 7.07139730e-01
-1.68776035e-01 -2.83029303e-02 1.04480833e-01 6.26656711e-01
-9.35511172e-01 5.84038794e-01 1.32792056e+00 -1.55926198e-01
-2.43596882e-01 -1.18945837e-01 -7.77770698e-01 5.47247410e-01
5.77918887e-01 -6.20642006e-01 -6.50974870e-01 -3.43172580e-01
-6.40923202e-01 -2.29743063e-01 9.92199257e-02 -9.54821348e-01
1.85723007e-01 -3.45412880e-01 6.20895445e-01 -5.80484331e-01
1.57589480e-01 -1.01327682e+00 -3.56894970e-01 2.63289541e-01
-4.44743007e-01 -7.29489088e-01 3.54600757e-01 7.78920174e-01
-2.23676145e-01 -1.64560661e-01 1.35505950e+00 1.35609895e-01
-1.19750893e+00 5.04104853e-01 4.22445834e-01 2.81419784e-01
1.30625367e+00 -2.69391090e-01 -1.99497774e-01 1.13653593e-01
-7.00911045e-01 6.39647067e-01 5.24377823e-01 6.83923423e-01
3.64464670e-01 -1.76335347e+00 -6.59769356e-01 3.24310631e-01
6.73079014e-01 1.35213077e-01 4.87386614e-01 4.91536140e-01
1.69521645e-01 2.98827946e-01 -5.05487561e-01 -8.44786465e-01
-1.09170568e+00 8.28287244e-01 1.50424302e-01 -4.24854994e-01
-3.43876004e-01 9.67098713e-01 7.54133105e-01 -8.69606495e-01
2.43720204e-01 -1.96877886e-02 -1.08541578e-01 1.18033037e-01
7.19565570e-01 2.20679030e-01 -2.29369938e-01 -5.86607277e-01
-4.77710277e-01 5.15404642e-01 -5.61067879e-01 1.63773075e-01
1.10953259e+00 -3.92277926e-01 3.70954901e-01 4.66263890e-01
1.34544325e+00 -2.95993358e-01 -1.75559747e+00 -9.75689530e-01
-5.24972081e-02 -3.64295363e-01 -3.32765162e-01 -1.17174411e+00
-7.86018729e-01 9.95712698e-01 9.73790646e-01 -4.13406402e-01
1.17357326e+00 1.02176473e-01 8.03313613e-01 4.39033687e-01
4.55745399e-01 -1.21945691e+00 2.86893934e-01 4.11329567e-01
6.33421361e-01 -1.59286010e+00 -9.37967077e-02 -2.85476714e-01
-9.17336643e-01 9.74421382e-01 9.94164348e-01 -3.33562419e-02
6.77414477e-01 -2.50878334e-01 1.93105653e-01 3.14606190e-01
-4.38409626e-01 -5.28309867e-02 3.47602934e-01 9.48984504e-01
2.63491124e-02 1.48022085e-01 2.29217261e-01 9.42966640e-01
3.97099912e-01 1.13257177e-01 -3.94083597e-02 8.18129480e-01
-7.16607451e-01 -1.47740245e+00 -3.45518917e-01 2.63509125e-01
4.61309813e-02 -1.02907475e-02 -2.44191319e-01 7.52601683e-01
2.48443529e-01 6.47083342e-01 -1.24634035e-01 -4.14300591e-01
3.94584477e-01 6.92485273e-01 4.84621495e-01 -8.67125452e-01
-1.39522150e-01 3.22666392e-02 -2.52153963e-01 -3.24570268e-01
-4.46405619e-01 -7.08792806e-01 -1.16585398e+00 1.88624471e-01
-2.54714191e-01 8.91818926e-02 3.70181650e-01 1.00536752e+00
5.84870458e-01 2.33398512e-01 8.28545094e-01 -5.51384032e-01
-9.45548236e-01 -1.17859292e+00 -7.97918081e-01 6.18920028e-01
1.76252216e-01 -9.09836888e-01 -7.80310333e-02 2.01875225e-01] | [10.33215618133545, 3.02047061920166] |
a426a2ae-3d23-4e1b-9128-dccc3ddcc475 | neural-symbolic-entangled-framework-for | 2209.08779 | null | https://arxiv.org/abs/2209.08779v1 | https://arxiv.org/pdf/2209.08779v1.pdf | Neural-Symbolic Entangled Framework for Complex Query Answering | Answering complex queries over knowledge graphs (KG) is an important yet challenging task because of the KG incompleteness issue and cascading errors during reasoning. Recent query embedding (QE) approaches to embed the entities and relations in a KG and the first-order logic (FOL) queries into a low dimensional space, answering queries by dense similarity search. However, previous works mainly concentrate on the target answers, ignoring intermediate entities' usefulness, which is essential for relieving the cascading error problem in logical query answering. In addition, these methods are usually designed with their own geometric or distributional embeddings to handle logical operators like union, intersection, and negation, with the sacrifice of the accuracy of the basic operator - projection, and they could not absorb other embedding methods to their models. In this work, we propose a Neural and Symbolic Entangled framework (ENeSy) for complex query answering, which enables the neural and symbolic reasoning to enhance each other to alleviate the cascading error and KG incompleteness. The projection operator in ENeSy could be any embedding method with the capability of link prediction, and the other FOL operators are handled without parameters. With both neural and symbolic reasoning results contained, ENeSy answers queries in ensembles. ENeSy achieves the SOTA performance on several benchmarks, especially in the setting of the training model only with the link prediction task. | ['Huajun Chen', 'Hui Chen', 'Peng Ye', 'Wen Zhang', 'Zezhong Xu'] | 2022-09-19 | null | null | null | null | ['complex-query-answering'] | ['knowledge-base'] | [-3.54145467e-01 5.44803977e-01 -3.89494002e-01 -1.97758913e-01
-2.37046629e-01 -4.07464087e-01 3.25405926e-01 3.19895893e-01
-2.00912088e-01 3.92429441e-01 1.85218707e-01 -3.76742095e-01
-6.02106333e-01 -1.50644815e+00 -8.32817018e-01 -2.14145303e-01
-9.38695669e-02 7.81265795e-01 4.53367680e-01 -5.94281375e-01
-2.24582732e-01 2.47936726e-01 -1.38494396e+00 2.71902531e-01
1.19475842e+00 1.20024323e+00 -3.77156347e-01 3.36196095e-01
-5.04605472e-01 1.40151930e+00 -2.98493207e-01 -1.16930413e+00
2.50235964e-02 -3.44988406e-02 -8.75757337e-01 -9.51673746e-01
2.43625551e-01 -3.44913274e-01 -7.50517249e-01 1.09723341e+00
4.96389747e-01 -4.24274690e-02 5.03708065e-01 -1.63691103e+00
-1.01106763e+00 1.01817238e+00 2.13452473e-01 -1.06017485e-01
6.39784276e-01 -7.30079263e-02 1.51161683e+00 -9.42694008e-01
4.08213496e-01 1.47531140e+00 7.20264494e-01 2.59122849e-01
-1.33775294e+00 -3.99939656e-01 -1.25454396e-01 7.20060289e-01
-1.62120306e+00 -1.55244723e-01 8.15191865e-01 -2.05650151e-01
1.16085708e+00 3.07431072e-01 5.57025433e-01 6.93377852e-01
-1.89273525e-02 8.46712649e-01 4.12143588e-01 -2.27339730e-01
2.43341714e-01 3.31453115e-01 4.44594175e-01 9.39787805e-01
3.30649883e-01 -9.25872661e-03 -5.00370026e-01 -4.40388024e-01
4.15120035e-01 1.02906376e-01 -2.70677775e-01 -5.85608363e-01
-1.17334342e+00 1.00824559e+00 8.56770754e-01 1.05041154e-01
-2.04657421e-01 3.21061909e-01 4.90533143e-01 6.53811812e-01
5.78453802e-02 6.23461425e-01 -5.73923707e-01 4.92850691e-02
-4.08922106e-01 3.34540784e-01 1.30748701e+00 1.03521383e+00
8.93514395e-01 -3.13667655e-01 -3.76602352e-01 4.47516263e-01
1.93686023e-01 3.62241834e-01 4.16051969e-02 -8.46183479e-01
5.65996826e-01 1.30078483e+00 -1.58001304e-01 -1.47863364e+00
-3.29148740e-01 -3.60503376e-01 -6.81175411e-01 -1.95541024e-01
1.93670601e-01 1.93379611e-01 -1.97977319e-01 1.88335133e+00
3.81791651e-01 2.51965728e-02 3.84950399e-01 7.18297601e-01
9.55034018e-01 3.85699689e-01 5.74140716e-03 1.69128567e-01
1.36939323e+00 -9.90691781e-01 -8.17358792e-01 1.12463720e-01
1.09504426e+00 -8.58800635e-02 1.28046751e+00 -7.98288081e-03
-1.00007248e+00 -3.89653713e-01 -1.02569175e+00 -6.07137978e-01
-7.90376008e-01 1.96702145e-02 9.45866287e-01 1.64711922e-01
-8.97976518e-01 4.42919940e-01 -5.77760994e-01 -2.80178096e-02
2.08268031e-01 4.99550253e-01 -3.14380407e-01 -2.86579370e-01
-1.99151123e+00 1.14051449e+00 6.59639955e-01 2.26376742e-01
-2.28124410e-01 -9.66679573e-01 -1.03578329e+00 4.89042640e-01
8.79856288e-01 -1.06228995e+00 7.50890553e-01 -1.37576059e-01
-1.22809434e+00 3.72863144e-01 1.63611602e-02 -4.27696884e-01
3.08676243e-01 -2.75626123e-01 -5.26719809e-01 -1.50791239e-02
-4.27335352e-02 4.29230690e-01 3.68248731e-01 -7.29188263e-01
-9.70431715e-02 -5.45527518e-01 7.96877563e-01 2.05618843e-01
-3.81298870e-01 -4.60581332e-01 -3.85983795e-01 -3.02781582e-01
1.62398681e-01 -5.41238666e-01 1.32705167e-01 6.67873397e-02
-4.03680801e-01 -8.26779544e-01 7.09555566e-01 -6.11631811e-01
1.51188385e+00 -2.24667525e+00 4.59526360e-01 1.49591669e-01
4.74014550e-01 1.30490512e-01 3.86311822e-02 7.49032319e-01
1.10593490e-01 1.59307808e-01 -3.66079919e-02 -1.51913147e-02
6.60227537e-01 4.89563197e-01 -6.35423899e-01 5.82469553e-02
4.89445150e-01 1.57151222e+00 -9.11740065e-01 -7.25581050e-01
-9.41146761e-02 2.25911126e-01 -9.46960688e-01 6.07949123e-02
-7.33066022e-01 -2.69288898e-01 -4.92722064e-01 7.58506894e-01
5.22840977e-01 -3.30814898e-01 2.45439127e-01 -7.12126255e-01
4.75425005e-01 4.42083091e-01 -1.35759604e+00 1.62046838e+00
-3.64671052e-01 6.97408095e-02 -1.91900894e-01 -1.00325131e+00
7.60887980e-01 1.36956856e-01 1.47028342e-01 -7.95053303e-01
-2.48163462e-01 3.19025636e-01 -6.33503124e-02 -7.14761794e-01
4.24605310e-01 -2.73856670e-02 -2.71297038e-01 3.62100840e-01
9.06009302e-02 -1.27890676e-01 1.42516479e-01 6.02496982e-01
1.21956396e+00 -2.39433162e-02 5.44604436e-02 6.09079637e-02
6.13215029e-01 -7.84589630e-03 5.06768227e-01 6.09434485e-01
1.09365933e-01 -1.29160076e-01 9.99482453e-01 -4.44676250e-01
-5.12973785e-01 -1.19076335e+00 -2.66962387e-02 1.15808868e+00
3.73220861e-01 -7.51022696e-01 -2.02812761e-01 -8.59575868e-01
4.95741516e-01 8.54463935e-01 -4.07407165e-01 -7.44292855e-01
-4.31676656e-01 -2.71421224e-01 9.64783967e-01 6.26371384e-01
4.88430619e-01 -9.59240198e-01 -1.30289614e-01 8.04007426e-02
-2.93207198e-01 -1.05459845e+00 -1.42805248e-01 1.30610839e-01
-5.76253176e-01 -1.28804469e+00 5.53186536e-02 -5.74118495e-01
4.08239841e-01 -3.90578240e-01 1.23930550e+00 1.65733725e-01
4.23490368e-02 3.12075526e-01 -1.48216859e-01 -2.19808057e-01
-9.46713611e-02 1.07070051e-01 9.38015133e-02 -1.02888115e-01
6.99028432e-01 -6.55378222e-01 -4.68719751e-01 2.08456859e-01
-1.03261197e+00 -2.48640403e-01 3.39830041e-01 9.35796022e-01
4.11472917e-01 2.68976152e-01 5.82045853e-01 -7.15458333e-01
8.15328002e-01 -6.03042841e-01 -5.72794914e-01 7.25991905e-01
-7.51147211e-01 5.17663777e-01 7.34817564e-01 -3.11041862e-01
-6.31577313e-01 -5.55111647e-01 2.16013882e-02 -5.88669300e-01
4.86123294e-01 1.01148391e+00 -4.21322793e-01 -6.09899908e-02
6.42077684e-01 1.71945587e-01 2.12508142e-02 -2.73585975e-01
7.50716329e-01 2.00336650e-01 4.01749313e-01 -8.11051369e-01
8.02102327e-01 1.96228534e-01 2.38888040e-01 -1.61340699e-01
-8.94563675e-01 -1.11278199e-01 -3.77690881e-01 4.50845271e-01
5.98929346e-01 -7.64567733e-01 -1.09845710e+00 -3.47898453e-02
-1.25718045e+00 4.20418754e-02 -6.35648072e-01 4.36271161e-01
-3.59246373e-01 4.15768236e-01 -6.55395389e-01 -5.79173982e-01
-2.98967719e-01 -1.10447657e+00 8.28094482e-01 -1.99842788e-02
-9.78951305e-02 -1.07958734e+00 -6.18298389e-02 2.46870607e-01
5.28021157e-01 -3.29626314e-02 1.67021263e+00 -9.39349234e-01
-8.32450449e-01 -2.74641603e-01 -4.73631024e-01 3.19053173e-01
-2.70536721e-01 -3.54642868e-01 -6.64492011e-01 3.66343111e-02
-7.00729564e-02 -6.43388033e-01 7.21382380e-01 -3.36333513e-01
9.15582836e-01 -5.68611383e-01 -1.81347251e-01 5.97838461e-01
1.45872641e+00 -2.32267275e-01 6.80655360e-01 4.33869138e-02
7.21635103e-01 5.34630418e-01 3.00611228e-01 8.88468176e-02
1.03486550e+00 7.15099633e-01 5.91023326e-01 3.28601539e-01
1.06593356e-01 -7.10815012e-01 3.22017431e-01 8.09071541e-01
2.48827517e-01 1.58192024e-01 -9.92000401e-01 2.49837667e-01
-1.99948990e+00 -9.95145500e-01 -2.23687608e-02 1.91640854e+00
1.11528778e+00 -9.57694873e-02 -2.66018003e-01 1.65588334e-01
1.92537129e-01 3.05479467e-02 -6.54893219e-01 -2.95600057e-01
-2.99621671e-01 2.27249727e-01 1.88109443e-01 5.58608234e-01
-6.89794481e-01 1.00194144e+00 5.36957169e+00 7.52753735e-01
-7.77254343e-01 3.20572034e-02 -3.15650925e-02 9.80504602e-02
-6.83558404e-01 2.07352713e-01 -7.49821544e-01 2.06461549e-01
7.41528988e-01 -1.63954467e-01 8.03761303e-01 7.66173244e-01
-5.12025595e-01 1.01393491e-01 -1.54129648e+00 9.88515139e-01
-1.13743030e-01 -1.19331503e+00 1.21872865e-01 -2.51954228e-01
2.78656632e-01 -2.05889702e-01 -1.95950881e-01 1.07387662e+00
2.94332325e-01 -1.12406993e+00 4.20788616e-01 9.90442753e-01
6.55052364e-01 -5.81176400e-01 9.97046471e-01 4.35387224e-01
-1.08336973e+00 -4.01558399e-01 -3.99733514e-01 -3.90782282e-02
3.93303484e-02 6.46520078e-01 -5.04938900e-01 1.04006743e+00
4.61035073e-01 4.67855245e-01 -7.28652954e-01 5.28611422e-01
-4.06006664e-01 2.31187329e-01 -5.47915041e-01 -1.14588872e-01
-1.19424528e-02 -2.08364591e-01 3.19963485e-01 7.78858662e-01
1.33009627e-01 9.58282575e-02 1.38266131e-01 1.46481740e+00
-3.13779175e-01 3.80318239e-02 -6.80373251e-01 -3.12683672e-01
6.25735164e-01 8.42570961e-01 4.47014160e-02 -4.95237082e-01
-4.00567144e-01 7.08762705e-01 7.11960196e-01 5.80793381e-01
-9.45535481e-01 -6.40158534e-01 5.51934898e-01 -7.43089803e-03
2.16711760e-01 -4.51796167e-02 -2.53997177e-01 -1.46893978e+00
6.08093202e-01 -7.14544594e-01 6.47930086e-01 -6.03662610e-01
-1.35213375e+00 1.94932297e-01 9.66137126e-02 -5.80871820e-01
-1.05468594e-01 -6.37003362e-01 -4.86308515e-01 8.43641162e-01
-1.71409523e+00 -1.08658135e+00 -1.40441969e-01 7.70553172e-01
-2.97017664e-01 3.58166173e-02 9.66227651e-01 5.14489710e-01
-5.79736173e-01 7.73148477e-01 -2.64283121e-01 1.39190868e-01
4.43243146e-01 -1.24266016e+00 -2.35778809e-01 1.43036813e-01
3.46594341e-02 9.51705933e-01 2.69144446e-01 -4.70037758e-01
-1.92820644e+00 -9.97101367e-01 1.37723875e+00 -6.96717858e-01
9.81093943e-01 -4.15592283e-01 -1.04170489e+00 8.08696330e-01
-1.77367195e-01 3.31632107e-01 5.86620986e-01 4.32168782e-01
-7.09441721e-01 -3.10167640e-01 -9.65170979e-01 7.01302230e-01
1.19889355e+00 -1.10278499e+00 -8.57081592e-01 3.29603255e-01
1.37585270e+00 -2.83028543e-01 -1.27504957e+00 7.05684543e-01
4.69626874e-01 -8.61701667e-01 1.08086133e+00 -8.72405887e-01
3.13092589e-01 -4.72335607e-01 -4.56276149e-01 -8.20898414e-01
-1.69668570e-01 -1.62297323e-01 -8.29112411e-01 1.00420070e+00
4.21674192e-01 -8.79319549e-01 5.45792162e-01 7.82424569e-01
1.43881738e-01 -1.18066335e+00 -8.51900995e-01 -6.14611506e-01
-1.59843534e-01 -5.48736155e-01 1.04244566e+00 9.52676356e-01
3.09907705e-01 5.69776297e-01 6.00103885e-02 3.50019813e-01
2.73274690e-01 3.10987085e-01 7.65027761e-01 -1.25094891e+00
-4.20254380e-01 -3.60034853e-01 -6.63341880e-01 -8.67382526e-01
4.68520284e-01 -1.35330391e+00 -6.67032838e-01 -1.61991012e+00
-1.55248135e-01 -4.98096615e-01 -3.55657250e-01 6.31112397e-01
-1.44385219e-01 -4.85791773e-01 1.97624967e-01 1.14387304e-01
-7.74884224e-01 9.99534667e-01 1.04713202e+00 -5.03745735e-01
-9.02378187e-02 -2.21342385e-01 -6.72411978e-01 4.53589678e-01
3.50750059e-01 -2.32143283e-01 -8.47452223e-01 -5.83169520e-01
1.12082076e+00 7.34040439e-02 9.23043132e-01 -7.27125645e-01
7.56081641e-01 1.39134586e-01 -1.69769466e-01 -3.86232644e-01
3.39990109e-01 -9.67772007e-01 1.64406642e-01 2.71997869e-01
-3.15554529e-01 7.10044354e-02 6.10793792e-02 6.85153961e-01
-6.13874435e-01 -4.29136492e-02 1.43295154e-01 1.73158467e-01
-6.98451221e-01 3.00771803e-01 5.29347181e-01 2.92982548e-01
7.91355133e-01 1.45201907e-01 -5.36814809e-01 -2.59252399e-01
-8.82842958e-01 6.79067016e-01 2.04912826e-01 1.90564588e-01
7.65266597e-01 -1.56274807e+00 -3.65110546e-01 1.94764465e-01
3.65272135e-01 3.06726277e-01 1.54914856e-01 1.25228846e+00
-3.91350806e-01 6.44883931e-01 2.48871237e-01 -1.79936349e-01
-4.85055298e-01 8.98707509e-01 4.64996278e-01 -7.44686604e-01
-4.14647788e-01 7.45462120e-01 -5.36176488e-02 -9.29846823e-01
5.03712654e-01 -5.37101209e-01 -1.40594438e-01 1.03924841e-01
8.93458873e-02 3.92712712e-01 3.86880338e-02 -8.64141732e-02
-4.21979725e-01 3.33092272e-01 1.87068954e-01 3.17747116e-01
9.90201056e-01 2.50008196e-01 -6.63543999e-01 4.37494099e-01
1.18885052e+00 1.22629125e-02 -2.94703186e-01 -6.88227773e-01
1.88055158e-01 -8.19692835e-02 -2.12153301e-01 -7.15560317e-01
-7.32125938e-01 8.78517866e-01 4.79316115e-02 3.02129567e-01
8.20477247e-01 3.59332830e-01 7.11517811e-01 9.75804329e-01
4.64336604e-01 -7.91490197e-01 -4.12237421e-02 7.12820113e-01
9.18521821e-01 -1.06983840e+00 -1.90034479e-01 -4.78440940e-01
-4.55555320e-01 9.89171803e-01 6.06241703e-01 1.02111481e-01
7.25508690e-01 -3.71789709e-02 -4.79997963e-01 -5.79553366e-01
-9.04020309e-01 -1.78485349e-01 2.90910274e-01 2.77541995e-01
1.82686411e-02 1.89618245e-02 -3.13754022e-01 9.58963454e-01
-2.80415952e-01 1.36238158e-01 -1.41830996e-01 6.75392270e-01
-3.74961342e-03 -9.53153968e-01 2.27329712e-02 4.86453205e-01
-1.05990944e-02 -3.06975275e-01 -2.79910713e-01 7.75577068e-01
2.53358573e-01 5.89233160e-01 -2.13599935e-01 -5.94137490e-01
7.10027635e-01 4.46379304e-01 2.49997690e-01 -3.80935878e-01
-3.31597388e-01 -7.36959338e-01 1.78170308e-01 -7.59896696e-01
5.52311428e-02 -1.78495646e-02 -1.42810917e+00 -4.84178752e-01
-4.66455787e-01 3.34192276e-01 2.31030792e-01 7.92567670e-01
7.86859035e-01 3.72402728e-01 1.99250907e-01 1.49878591e-01
-1.13633132e+00 -7.06543326e-01 -6.06518924e-01 4.54730093e-01
1.04354672e-01 -7.46123075e-01 -3.76739711e-01 -4.87508565e-01] | [9.050335884094238, 7.7123122215271] |
f6374b3b-2c20-4cd3-8e65-a1ff75e0f8e7 | meta-causal-learning-for-single-domain | 2304.03709 | null | https://arxiv.org/abs/2304.03709v1 | https://arxiv.org/pdf/2304.03709v1.pdf | Meta-causal Learning for Single Domain Generalization | Single domain generalization aims to learn a model from a single training domain (source domain) and apply it to multiple unseen test domains (target domains). Existing methods focus on expanding the distribution of the training domain to cover the target domains, but without estimating the domain shift between the source and target domains. In this paper, we propose a new learning paradigm, namely simulate-analyze-reduce, which first simulates the domain shift by building an auxiliary domain as the target domain, then learns to analyze the causes of domain shift, and finally learns to reduce the domain shift for model adaptation. Under this paradigm, we propose a meta-causal learning method to learn meta-knowledge, that is, how to infer the causes of domain shift between the auxiliary and source domains during training. We use the meta-knowledge to analyze the shift between the target and source domains during testing. Specifically, we perform multiple transformations on source data to generate the auxiliary domain, perform counterfactual inference to learn to discover the causal factors of the shift between the auxiliary and source domains, and incorporate the inferred causality into factor-aware domain alignments. Extensive experiments on several benchmarks of image classification show the effectiveness of our method. | ['Jiebo Luo', 'Xinxiao wu', 'Zhi Gao', 'Jin Chen'] | 2023-04-07 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Chen_Meta-Causal_Learning_for_Single_Domain_Generalization_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Chen_Meta-Causal_Learning_for_Single_Domain_Generalization_CVPR_2023_paper.pdf | cvpr-2023-1 | ['counterfactual-inference'] | ['miscellaneous'] | [ 5.46201766e-01 2.31905058e-01 -5.23003519e-01 -5.93978763e-01
-6.44114435e-01 -6.96990132e-01 6.83179498e-01 -2.08522722e-01
-7.30770975e-02 1.03263927e+00 1.26930445e-01 -2.55932361e-01
-1.29650578e-01 -8.95217121e-01 -1.15657318e+00 -6.18270755e-01
3.45431775e-01 8.16096127e-01 4.17331576e-01 -9.40984339e-02
-5.44390343e-02 -9.77659449e-02 -1.30958307e+00 5.91528893e-01
1.16988742e+00 7.17163920e-01 4.39601809e-01 1.29576728e-01
-2.18940631e-01 6.98369384e-01 -8.80450845e-01 -2.90126681e-01
1.73818976e-01 -9.05960083e-01 -8.22122931e-01 2.05160648e-01
-1.23611093e-02 -4.90239978e-01 -9.69704315e-02 1.04491913e+00
4.39096503e-02 -1.51363732e-02 7.47567356e-01 -1.45577252e+00
-8.77535522e-01 6.70590997e-01 -5.09236395e-01 3.47839892e-01
3.08097869e-01 6.17693178e-02 6.73058093e-01 -5.09618223e-01
6.79084480e-01 1.46123636e+00 1.70366123e-01 7.41694570e-01
-1.33620322e+00 -1.14504755e+00 5.92676163e-01 4.76645291e-01
-8.74736130e-01 -6.69970661e-02 9.95204031e-01 -5.42940676e-01
5.78098536e-01 -4.23293948e-01 3.08822513e-01 1.52191973e+00
3.97047997e-02 6.86402559e-01 1.16345227e+00 -5.95667779e-01
3.71209919e-01 3.12469035e-01 -4.40592542e-02 3.29006553e-01
1.19500652e-01 3.28605205e-01 -6.20339334e-01 -2.71953374e-01
5.43394089e-01 -1.56028107e-01 -1.24311514e-01 -4.86476719e-01
-1.21240234e+00 7.25710034e-01 1.73159629e-01 8.27875733e-03
-3.11914712e-01 -2.44384006e-01 3.06938082e-01 5.14845908e-01
5.12498558e-01 3.29823494e-01 -1.00428796e+00 3.28858823e-01
-3.66888583e-01 4.61410403e-01 5.99921942e-01 1.04883683e+00
1.07734859e+00 -3.24753255e-01 7.28568137e-02 7.89343715e-01
1.05589308e-01 6.01151705e-01 7.03360260e-01 -7.56606877e-01
8.82593870e-01 8.31420839e-01 1.27494350e-01 -3.24719429e-01
2.34327540e-01 -2.29521692e-01 -5.18601537e-01 3.84201616e-04
5.07783294e-01 -3.61449927e-01 -9.95186746e-01 2.22372031e+00
6.56963170e-01 6.44878685e-01 2.76033551e-01 5.86583555e-01
4.07309830e-01 5.38451135e-01 1.29474342e-01 -2.34307155e-01
9.63855505e-01 -6.42148197e-01 -4.32345808e-01 -5.83801270e-01
6.54533267e-01 -3.96172255e-01 1.19261479e+00 3.99002910e-01
-7.41359353e-01 -8.48423064e-01 -1.11003006e+00 3.00981611e-01
-2.22150385e-01 -6.06310852e-02 1.75355867e-01 1.58584148e-01
-3.21383923e-01 5.60359299e-01 -6.26798511e-01 -4.70523909e-02
4.66126382e-01 2.13728502e-01 -2.41218045e-01 -3.33643466e-01
-1.67786968e+00 7.05636799e-01 1.01010084e+00 -7.40814507e-01
-1.30910504e+00 -1.20153844e+00 -7.81743884e-01 -1.16008148e-01
4.81678635e-01 -7.54975915e-01 1.20905674e+00 -1.35049462e+00
-1.28305566e+00 8.45756888e-01 -3.72811913e-01 -4.78389412e-01
2.72324950e-01 -1.90158769e-01 -6.21552110e-01 -2.32941061e-01
4.16795999e-01 4.90119725e-01 1.06301606e+00 -1.29862213e+00
-1.15888774e+00 -4.74316537e-01 3.78617272e-02 2.20977619e-01
-2.68846691e-01 -4.88742054e-01 -2.48944953e-01 -6.61387324e-01
-3.96965742e-02 -8.25952828e-01 3.25032510e-02 -5.11042297e-01
-2.81632274e-01 -3.14344317e-01 1.03795028e+00 -7.14972794e-01
1.14388633e+00 -2.30591798e+00 3.64327759e-01 1.37752846e-01
1.52880386e-01 4.90843281e-02 -2.75547802e-01 -1.01559013e-01
-4.74900514e-01 -9.24933106e-02 -5.05304575e-01 1.98440045e-01
-3.39372158e-01 5.90993881e-01 -9.10200357e-01 1.12353958e-01
3.76501948e-01 5.07497251e-01 -1.04188502e+00 -2.73743957e-01
5.41410185e-02 -4.78147268e-02 -6.61054373e-01 4.95574743e-01
-7.64119685e-01 8.60513747e-01 -6.62074924e-01 1.00070544e-01
8.11467946e-01 -1.31063089e-01 5.25869548e-01 4.35365662e-02
4.21009958e-01 5.75269699e-01 -1.08527398e+00 1.56244779e+00
-4.53854948e-01 2.47257650e-01 -3.91202241e-01 -1.34385657e+00
1.07636595e+00 1.21325463e-01 3.79422516e-01 -8.13642859e-01
-2.51886666e-01 2.68918425e-01 1.22508779e-01 -5.78895569e-01
-3.00052702e-01 -6.46936059e-01 -1.65174738e-01 5.40535986e-01
3.36804241e-01 -4.72844057e-02 -4.67857122e-02 -7.47786388e-02
9.67133582e-01 5.11720836e-01 4.82028097e-01 -2.82903314e-02
6.09308124e-01 2.46831521e-01 1.06572139e+00 3.63709450e-01
-5.99823147e-02 2.60695100e-01 8.46663117e-01 -4.28276181e-01
-1.09292674e+00 -1.47640920e+00 1.53427094e-01 1.18022263e+00
3.61349910e-01 -2.44688708e-02 -6.52691483e-01 -1.32575119e+00
1.72403589e-01 1.31526613e+00 -6.97912037e-01 -6.62622452e-01
-7.36176431e-01 -6.26148880e-01 2.82714456e-01 4.95173395e-01
7.03741312e-01 -7.85093248e-01 -2.08482638e-01 1.11941621e-01
-4.67334688e-01 -9.80542600e-01 -2.00936735e-01 2.08141863e-01
-9.64587271e-01 -1.26074052e+00 -3.68718088e-01 -8.93318832e-01
5.82892835e-01 -1.09558508e-01 1.14799130e+00 -3.91014099e-01
3.98979247e-01 -1.17063649e-01 -1.24776989e-01 -5.24417758e-01
-8.38777423e-01 -1.50112733e-01 6.05907962e-02 -1.24695443e-01
6.01168633e-01 -7.71598518e-01 -2.48842448e-01 7.61034667e-01
-9.68129337e-01 5.63666187e-02 5.16778350e-01 9.45494413e-01
7.00364947e-01 4.56701159e-01 8.67471039e-01 -1.37226355e+00
6.16319299e-01 -1.04593027e+00 -4.83269870e-01 5.26646674e-01
-6.42946661e-01 5.52114248e-01 9.12933230e-01 -1.00670969e+00
-1.52365375e+00 -3.57352383e-02 3.23247075e-01 -6.26225054e-01
-4.50025916e-01 5.30194759e-01 -8.57874155e-01 8.48817766e-01
9.53539550e-01 3.45532686e-01 -1.59027576e-01 -4.91308153e-01
3.01330596e-01 3.86845857e-01 6.44005597e-01 -9.54807043e-01
9.89823580e-01 4.89034712e-01 -2.56783396e-01 -3.22849788e-02
-1.06698966e+00 -2.24153414e-01 -8.74009430e-01 2.21937373e-01
6.29088283e-01 -9.55794454e-01 8.74372572e-02 3.70524704e-01
-1.06210601e+00 -6.86088324e-01 -2.68080890e-01 3.68270934e-01
-6.36421561e-01 9.09476429e-02 2.16976479e-01 -1.81823671e-01
2.60741651e-01 -9.91881669e-01 8.82818282e-01 6.36689514e-02
-2.41352558e-01 -1.27287698e+00 1.94628522e-01 2.15483457e-01
-2.43735552e-01 2.86235690e-01 1.56819987e+00 -9.72939909e-01
-3.18418473e-01 1.65328830e-01 -2.89355479e-02 5.20212591e-01
5.86339593e-01 -5.58757782e-01 -7.33457565e-01 -1.93601668e-01
1.86947137e-01 -3.01125258e-01 7.06310093e-01 3.76338482e-01
1.27544272e+00 -4.17876065e-01 -6.04533195e-01 5.07218063e-01
1.01780188e+00 5.63480616e-01 5.40787637e-01 4.35056120e-01
4.09651071e-01 7.28700876e-01 9.91279304e-01 3.28316748e-01
3.83963853e-01 5.69399238e-01 1.10727757e-01 1.33531719e-01
-2.51227498e-01 -8.27014208e-01 4.84969616e-01 2.94874012e-01
4.15716559e-01 -1.20767958e-01 -1.00783157e+00 7.20947385e-01
-1.70351923e+00 -8.16098750e-01 4.41579252e-01 2.25919199e+00
1.10424376e+00 3.52718055e-01 1.60988435e-01 -1.87005207e-01
9.77516890e-01 -1.73545122e-01 -1.20528996e+00 3.17232497e-02
8.36515576e-02 2.12873459e-01 2.82262504e-01 4.78442401e-01
-8.36147666e-01 9.83052969e-01 5.46631765e+00 7.25638092e-01
-1.04763687e+00 7.96190053e-02 5.29979467e-01 3.71022224e-02
-5.76658130e-01 3.63182455e-01 -8.81685257e-01 5.93834043e-01
7.73921967e-01 -6.10481381e-01 5.15814245e-01 1.00831079e+00
-3.79077345e-02 1.57002926e-01 -1.61705613e+00 5.21645904e-01
-4.55010124e-02 -9.60666835e-01 4.17755067e-01 -1.05401995e-02
8.61100554e-01 -2.57271022e-01 3.97199653e-02 7.33323812e-01
6.49720967e-01 -7.12370813e-01 5.13205707e-01 2.29464263e-01
9.67821002e-01 -7.56439447e-01 4.93946224e-01 8.38578761e-01
-8.74486268e-01 -3.07047516e-01 -4.19070870e-01 -1.12570778e-01
-2.30666578e-01 4.90824372e-01 -1.34902906e+00 3.96479398e-01
6.38690710e-01 8.29217553e-01 -4.05444980e-01 3.97518277e-01
-7.69199431e-01 7.41270304e-01 6.19781353e-02 4.10816282e-01
-3.38427454e-01 1.26411356e-02 6.01849735e-01 6.36155963e-01
2.69020766e-01 -7.31893033e-02 1.81528404e-01 1.16601598e+00
-2.12751582e-01 -5.30914903e-01 -7.02886760e-01 7.54023343e-02
7.68959939e-01 4.10025865e-01 -1.67156950e-01 -4.99303877e-01
-3.23855370e-01 9.30030823e-01 3.75826210e-01 6.34800613e-01
-1.00821328e+00 -2.28477225e-01 8.07191730e-01 2.03314871e-01
2.39506185e-01 2.11594537e-01 -3.27039719e-01 -1.21962309e+00
9.06559750e-02 -1.18601108e+00 6.64032876e-01 -6.33519828e-01
-1.44356763e+00 1.14910632e-01 5.82093954e-01 -1.32603431e+00
-6.24255896e-01 -3.94740939e-01 -7.26158321e-01 1.20554173e+00
-1.50043058e+00 -9.68334854e-01 -7.88613036e-02 8.60954523e-01
8.18491995e-01 -4.32624370e-01 7.01232731e-01 -8.65649283e-02
-2.89344519e-01 5.99932432e-01 2.87876632e-02 1.81931973e-01
1.02179468e+00 -1.11971700e+00 4.89868283e-01 7.92735100e-01
-1.42741770e-01 7.26486981e-01 6.61389291e-01 -9.50705111e-01
-7.05587029e-01 -1.37065649e+00 7.20343530e-01 -6.12852156e-01
5.68506122e-01 -4.26952094e-01 -1.26975167e+00 1.01908576e+00
-5.80755435e-03 -2.75597841e-01 7.94055164e-01 2.52358347e-01
-8.34725142e-01 -2.61071652e-01 -1.14507759e+00 4.53452379e-01
1.01934826e+00 -3.72928351e-01 -1.19302726e+00 1.49406940e-01
1.08241320e+00 -3.99874628e-01 -5.94134271e-01 5.09286702e-01
3.04147273e-01 -7.06324697e-01 8.93076479e-01 -1.07221711e+00
9.85420287e-01 -3.42162639e-01 -8.52530822e-02 -1.88312173e+00
-3.16050738e-01 8.52921456e-02 -1.81865975e-01 1.36682832e+00
5.93607187e-01 -7.29073703e-01 7.55235374e-01 2.68137187e-01
-4.84896637e-02 -4.31089580e-01 -8.81201208e-01 -7.26002991e-01
5.12736440e-01 -3.30152899e-01 1.04892147e+00 1.16635895e+00
-2.24451542e-01 5.66409767e-01 -1.03223793e-01 5.13755262e-01
6.12346113e-01 4.25803989e-01 8.75037730e-01 -1.19057274e+00
-5.43001950e-01 -1.83963906e-02 -2.44883131e-02 -9.69856441e-01
5.94697535e-01 -7.93767273e-01 -1.51322454e-01 -1.33168685e+00
2.20435634e-01 -3.22118133e-01 -4.43837225e-01 5.38680971e-01
-4.76271063e-01 -5.50149679e-01 -1.34605542e-01 2.78284520e-01
-2.52246439e-01 4.54402298e-01 1.40901613e+00 -1.78851530e-01
-3.41618657e-01 1.41239643e-01 -9.76442695e-01 7.72682488e-01
6.84470475e-01 -6.76402271e-01 -1.04806447e+00 -4.96578902e-01
9.57706291e-03 -5.41928597e-02 3.85591298e-01 -8.32281828e-01
-7.79674128e-02 -6.76214099e-01 6.77706778e-01 -4.09382552e-01
-2.06097767e-01 -8.63447428e-01 -4.03911471e-02 5.21656334e-01
-6.05674803e-01 -3.79272342e-01 3.96768957e-01 8.44105065e-01
-3.29140276e-01 -9.81809124e-02 9.08871114e-01 -1.63684525e-02
-1.00508606e+00 1.06894836e-01 2.27376550e-01 4.19748634e-01
1.23148727e+00 1.67791285e-02 -3.61486822e-01 -7.50393569e-02
-7.88615406e-01 3.82811993e-01 3.67128879e-01 7.51458526e-01
5.43012261e-01 -1.44003856e+00 -7.39810824e-01 4.73791093e-01
2.90017992e-01 3.06676030e-01 3.16795081e-01 1.74896270e-01
2.37861648e-01 1.30957782e-01 -3.57205123e-01 -6.89986110e-01
-1.05064380e+00 7.20872879e-01 4.09365714e-01 -5.52323163e-01
-1.59520909e-01 7.73037493e-01 8.22008669e-01 -7.49646068e-01
4.26413724e-03 -1.83733121e-01 -5.18677421e-02 -7.78584704e-02
4.54082668e-01 1.43742278e-01 -1.07416131e-01 5.14636897e-02
-2.94818252e-01 2.65286863e-01 -2.11637884e-01 -1.37248650e-01
1.24729383e+00 -2.02980936e-01 1.05236307e-01 5.28032959e-01
1.12076056e+00 -3.12348932e-01 -1.57607698e+00 -5.93765438e-01
1.59004554e-01 -4.83030260e-01 -4.76844281e-01 -1.07813418e+00
-6.26849294e-01 8.72712910e-01 4.64550197e-01 -3.00177902e-01
1.59703374e+00 3.10996890e-01 5.59583664e-01 1.22305796e-01
2.31349364e-01 -1.12286985e+00 3.87774915e-01 4.76682097e-01
8.00100327e-01 -1.11341727e+00 -2.31129035e-01 -4.00589854e-01
-8.91215920e-01 8.11392605e-01 1.04976034e+00 -9.54607502e-02
5.30944526e-01 1.37872085e-01 -1.54047266e-01 1.44490957e-01
-1.02250719e+00 9.93281975e-02 2.61417657e-01 1.06508946e+00
8.57653692e-02 8.20518211e-02 2.08678082e-01 8.01064074e-01
-1.85933560e-01 2.73284405e-01 7.46521428e-02 6.50972664e-01
-2.32496470e-01 -1.50583661e+00 -5.04425466e-01 4.29507941e-01
-7.07696825e-02 5.72127178e-02 -6.16879821e-01 8.96969140e-01
7.87802756e-01 6.72408938e-01 3.85153107e-02 -6.40650749e-01
5.86543381e-01 4.46439832e-01 4.86068547e-01 -9.87782657e-01
-4.70057409e-03 -9.21377316e-02 -2.09712252e-01 -2.59887666e-01
-2.85738349e-01 -6.68603241e-01 -1.24993753e+00 6.55295104e-02
1.11741535e-01 1.15265921e-01 3.55183929e-01 1.34959054e+00
4.22751695e-01 6.13654196e-01 7.31430948e-01 -8.30221996e-02
-7.94296026e-01 -9.22634721e-01 -3.98862451e-01 8.03622961e-01
4.24108952e-01 -9.99598384e-01 -3.30944121e-01 5.08829951e-01] | [10.338838577270508, 3.0937559604644775] |
fd843473-2cb2-4a68-933a-b25931eb68f1 | fcns-in-the-wild-pixel-level-adversarial-and | 1612.02649 | null | http://arxiv.org/abs/1612.02649v1 | http://arxiv.org/pdf/1612.02649v1.pdf | FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation | Fully convolutional models for dense prediction have proven successful for a
wide range of visual tasks. Such models perform well in a supervised setting,
but performance can be surprisingly poor under domain shifts that appear mild
to a human observer. For example, training on one city and testing on another
in a different geographic region and/or weather condition may result in
significantly degraded performance due to pixel-level distribution shift. In
this paper, we introduce the first domain adaptive semantic segmentation
method, proposing an unsupervised adversarial approach to pixel prediction
problems. Our method consists of both global and category specific adaptation
techniques. Global domain alignment is performed using a novel semantic
segmentation network with fully convolutional domain adversarial learning. This
initially adapted space then enables category specific adaptation through a
generalization of constrained weak learning, with explicit transfer of the
spatial layout from the source to the target domains. Our approach outperforms
baselines across different settings on multiple large-scale datasets, including
adapting across various real city environments, different synthetic
sub-domains, from simulated to real environments, and on a novel large-scale
dash-cam dataset. | ['Judy Hoffman', 'Fisher Yu', 'Trevor Darrell', 'Dequan Wang'] | 2016-12-08 | null | null | null | null | ['synthetic-to-real-translation'] | ['computer-vision'] | [ 7.16812193e-01 2.22106595e-02 -1.23227470e-01 -5.58529377e-01
-7.41935968e-01 -7.43228078e-01 7.11428106e-01 -6.25741854e-02
-3.60452294e-01 7.22430110e-01 1.40244022e-01 -9.25316885e-02
2.58755058e-01 -7.12109506e-01 -1.02239430e+00 -4.60266113e-01
2.69935638e-01 8.62012267e-01 8.06129336e-01 -2.31748998e-01
1.44390166e-01 4.91653204e-01 -1.32786727e+00 1.87475562e-01
8.60922575e-01 7.34204292e-01 2.83674419e-01 6.15635216e-01
-1.16224751e-01 5.43591738e-01 -6.83831632e-01 -4.60770987e-02
6.67757094e-01 -2.13891104e-01 -8.78746688e-01 5.01172543e-01
7.57209241e-01 -2.63541251e-01 -1.93585932e-01 9.95241463e-01
4.15302575e-01 2.92654425e-01 7.17737257e-01 -1.17782569e+00
-6.15412712e-01 2.28569612e-01 -6.06928527e-01 -6.74394146e-02
8.61415341e-02 4.36180085e-01 6.23358130e-01 -3.73533338e-01
8.01807225e-01 1.24591160e+00 8.74641538e-01 3.99553597e-01
-1.64800513e+00 -7.69545615e-01 5.55387139e-01 1.57076139e-02
-1.25266671e+00 -1.86983719e-01 8.48903835e-01 -5.77447176e-01
9.24631238e-01 -1.75328717e-01 3.34172010e-01 1.42607248e+00
-1.53665110e-01 4.73514438e-01 1.38944876e+00 -2.42974356e-01
4.85246032e-01 1.33521110e-01 -3.52148145e-01 5.55580966e-02
-5.56821264e-02 2.20629647e-01 -1.43027604e-01 1.19049683e-01
6.98707879e-01 -1.57446608e-01 7.02477172e-02 -8.95004630e-01
-1.12344372e+00 6.55959010e-01 6.54709995e-01 -3.37504223e-02
-5.07310629e-02 -4.46571130e-03 3.50880533e-01 2.48438880e-01
5.17319322e-01 5.93834877e-01 -7.54253983e-01 2.85585761e-01
-1.01583862e+00 5.84851623e-01 5.10853112e-01 1.05113041e+00
7.59361804e-01 1.52753502e-01 -3.24612945e-01 1.01746106e+00
-6.67631719e-03 7.62190223e-01 3.18586528e-01 -1.22202575e+00
5.88333189e-01 2.86630780e-01 3.85281742e-01 -8.23730528e-01
-5.91049612e-01 -4.39811587e-01 -6.96486712e-01 6.86072469e-01
8.82399261e-01 -1.75784871e-01 -1.56471241e+00 1.87484717e+00
3.51535738e-01 5.31490266e-01 -5.73597848e-02 9.02446508e-01
4.49435323e-01 4.74054873e-01 5.02848208e-01 5.15168250e-01
8.75017583e-01 -1.16651154e+00 -5.20012751e-02 -9.95749414e-01
3.64120066e-01 -6.71099067e-01 1.32593322e+00 2.87062854e-01
-7.53270984e-01 -7.60735333e-01 -9.54721689e-01 4.23263907e-02
-7.47860074e-01 -3.02315146e-01 1.62733808e-01 5.04021227e-01
-1.00327933e+00 5.41780531e-01 -6.26094460e-01 -8.32053959e-01
6.92496777e-01 2.49076590e-01 -2.43095145e-01 -3.14613491e-01
-1.07410896e+00 7.70797431e-01 5.34899831e-01 -5.00800729e-01
-8.52077901e-01 -8.48119557e-01 -8.49369228e-01 -1.20295450e-01
2.24836752e-01 -7.30167747e-01 1.24145162e+00 -1.76569033e+00
-1.32131660e+00 1.04814088e+00 1.71396330e-01 -6.98923349e-01
5.56710899e-01 -1.66025415e-01 -4.92861271e-01 -4.27135788e-02
4.69633818e-01 9.84351277e-01 1.05599761e+00 -1.55564821e+00
-5.75050831e-01 -3.79410118e-01 -8.43014643e-02 3.47472370e-01
2.88387481e-02 -1.81681916e-01 -4.80657399e-01 -9.24133182e-01
-7.86482096e-02 -1.00549161e+00 -6.27789319e-01 1.01999238e-01
-3.26251358e-01 4.54807937e-01 8.62726271e-01 -8.65394652e-01
6.45269036e-01 -2.15903139e+00 -3.48628387e-02 3.20419073e-01
-1.73871055e-01 3.61412764e-01 -3.83099079e-01 1.84140671e-02
-2.35440984e-01 -1.52526433e-02 -7.07850993e-01 -2.60457724e-01
-1.92408133e-02 2.65134811e-01 -3.53599787e-01 2.34114125e-01
2.79964149e-01 8.06128681e-01 -9.22063768e-01 -4.23767507e-01
3.70118231e-01 5.76840155e-02 -5.77773452e-01 1.87484711e-01
-5.62626064e-01 8.21349084e-01 -2.35741094e-01 5.41204810e-01
9.61917877e-01 -1.88323542e-01 -1.80690568e-02 2.52581894e-01
2.76832074e-01 -5.07759415e-02 -1.11137307e+00 2.00747347e+00
-4.24020320e-01 7.61858404e-01 4.07235622e-02 -1.28510690e+00
7.41789758e-01 -1.35435313e-01 3.40696245e-01 -1.10322154e+00
-2.51749247e-01 5.61819738e-03 -1.11142151e-01 -2.33046353e-01
4.50794667e-01 -1.20817959e-01 -3.96840364e-01 1.50226399e-01
-4.03872281e-02 -5.63934565e-01 -2.01641381e-01 7.18894154e-02
1.04627562e+00 5.79993308e-01 1.98842004e-01 -5.58648407e-02
1.28904298e-01 6.75328016e-01 5.49356520e-01 8.90801251e-01
-5.83976805e-01 1.07775176e+00 2.96584457e-01 -3.79361749e-01
-1.54792762e+00 -1.34953439e+00 -4.27234396e-02 1.21886694e+00
4.48442817e-01 3.30435008e-01 -8.09540868e-01 -8.06652665e-01
1.52461410e-01 8.40728462e-01 -6.43016994e-01 -3.08511496e-01
-5.07696688e-01 -5.46797872e-01 6.13085508e-01 7.72302747e-01
8.48865092e-01 -1.10492814e+00 -2.95846015e-01 2.27012485e-01
6.64867908e-02 -1.47477233e+00 -2.39156425e-01 2.85362422e-01
-6.50737524e-01 -8.40059936e-01 -7.82966197e-01 -8.27057898e-01
4.21328664e-01 1.38118014e-01 1.47554600e+00 -4.25744027e-01
-6.71425164e-02 2.57157475e-01 -2.14125276e-01 -3.38696390e-01
-4.78661895e-01 2.47176841e-01 -2.41897285e-01 -2.07477450e-01
4.15725082e-01 -5.36525130e-01 -7.10406065e-01 4.55285043e-01
-7.47620523e-01 1.07760496e-01 5.96494794e-01 7.85546124e-01
7.44232416e-01 -5.55524863e-02 3.77171010e-01 -1.14167809e+00
1.79569796e-01 -7.28652716e-01 -4.89110976e-01 4.49993350e-02
-4.04257625e-01 -7.34417811e-02 8.72039795e-01 -4.95773166e-01
-1.34863114e+00 3.86916608e-01 -2.20135450e-02 -3.64862561e-01
-9.28986669e-01 -9.93798897e-02 -4.39783007e-01 1.03989393e-01
1.14478672e+00 7.30616301e-02 -3.44858140e-01 -3.61403167e-01
4.20898378e-01 5.35785317e-01 8.15118670e-01 -5.06797194e-01
1.31124210e+00 6.93150878e-01 -7.91396946e-02 -6.64423764e-01
-8.17066908e-01 -3.71699691e-01 -9.74962831e-01 1.28270656e-01
9.74171758e-01 -1.12580848e+00 4.57912385e-01 7.78598964e-01
-7.23930061e-01 -1.25292468e+00 -4.12200928e-01 4.23469916e-02
-6.12258434e-01 2.20150247e-01 2.04243064e-02 6.36487454e-02
1.48700684e-01 -9.10834610e-01 1.18781471e+00 2.65247107e-01
-2.54053026e-01 -1.18554842e+00 1.68514058e-01 3.07747692e-01
5.41819096e-01 5.37045538e-01 7.63188839e-01 -6.67609990e-01
-5.20578146e-01 6.20634407e-02 -5.21560729e-01 5.14185011e-01
1.03952952e-01 -2.02070639e-01 -9.79938924e-01 -2.29554534e-01
-6.69965863e-01 -3.71864557e-01 8.88846755e-01 5.00183761e-01
1.49783933e+00 1.02176651e-01 -6.32145464e-01 9.33962822e-01
1.47167516e+00 3.31881666e-03 6.81379855e-01 7.82251954e-01
8.41719985e-01 4.19332415e-01 7.99037635e-01 1.02045655e-01
2.82344848e-01 9.04839635e-01 5.17769754e-01 -6.03632033e-01
-4.86338407e-01 -2.34283730e-01 4.36209291e-02 -3.83013129e-01
2.90877610e-01 -3.03110987e-01 -1.11993933e+00 9.14290607e-01
-1.77427387e+00 -9.24388111e-01 1.62399352e-01 2.29385734e+00
6.05215669e-01 4.11086500e-01 3.60590369e-01 -3.09129894e-01
5.87995052e-01 1.72075585e-01 -1.06195760e+00 -5.53323090e-01
-2.94197798e-01 5.22193313e-01 9.97886002e-01 3.31203729e-01
-1.62950718e+00 1.43476307e+00 6.22337866e+00 7.34186053e-01
-1.23254561e+00 1.90657899e-01 6.96263671e-01 2.90996544e-02
-1.04566753e-01 1.27765881e-02 -3.54931861e-01 5.18443108e-01
8.29796255e-01 2.26584256e-01 4.03972477e-01 1.08562195e+00
1.39853135e-01 -1.32499218e-01 -7.41397321e-01 7.08122790e-01
-5.62980548e-02 -1.13459361e+00 -1.47008047e-01 -1.90355614e-01
1.21982026e+00 4.08734351e-01 2.91364104e-01 3.42499197e-01
8.15176964e-01 -1.33327794e+00 5.87545753e-01 2.95353085e-01
9.73494411e-01 -5.65411925e-01 3.57657701e-01 2.38831297e-01
-9.71087635e-01 -1.89670563e-01 -2.32473120e-01 -6.24803491e-02
-9.23410431e-03 8.81081671e-02 -9.61493492e-01 1.68711066e-01
9.58525956e-01 7.55755305e-01 -8.80124032e-01 9.74353731e-01
-2.54564136e-01 6.75982296e-01 -3.58672172e-01 6.32733107e-01
3.77317995e-01 1.94936525e-02 4.89703327e-01 1.38337553e+00
1.75685108e-01 -2.28415698e-01 2.69475967e-01 8.00390601e-01
5.48049472e-02 -1.50506869e-01 -7.83211231e-01 4.44386512e-01
4.35318708e-01 8.83970201e-01 -8.14732671e-01 -3.17161620e-01
-5.29535472e-01 1.46327186e+00 2.84582704e-01 8.09128881e-01
-9.55906808e-01 -2.32370213e-01 9.95159745e-01 4.84836370e-01
5.44728220e-01 -5.28936349e-02 -7.30661511e-01 -9.34503615e-01
-2.95970500e-01 -8.11110556e-01 3.23669076e-01 -1.04979575e+00
-1.16804528e+00 2.74895966e-01 1.35979250e-01 -1.36207223e+00
-1.83316886e-01 -5.54845273e-01 -6.61366045e-01 9.93383586e-01
-1.62208211e+00 -1.45571959e+00 -6.42368913e-01 7.75540531e-01
7.63744354e-01 -2.91516364e-01 6.77002788e-01 1.06441304e-01
-3.57289553e-01 5.74880540e-01 3.74407321e-01 1.53871045e-01
1.31630957e+00 -1.58834124e+00 8.10817420e-01 1.21868289e+00
-4.09219079e-02 -1.29896011e-02 8.30391169e-01 -5.23682535e-01
-3.18407714e-01 -1.88239408e+00 3.35582823e-01 -6.09312892e-01
4.00393754e-01 -4.13872659e-01 -1.01153028e+00 9.34100211e-01
2.17235997e-01 1.12419501e-01 3.62044483e-01 -1.59339935e-01
-4.71780479e-01 -1.77139714e-01 -1.37021041e+00 8.08512151e-01
1.32528007e+00 -2.97804475e-01 -3.89311671e-01 4.47127044e-01
7.33385384e-01 -5.98447323e-01 -7.08809078e-01 3.53165090e-01
2.85227597e-01 -9.93048549e-01 1.37290573e+00 -6.22343957e-01
6.49615288e-01 -4.79777575e-01 -2.65259981e-01 -1.67630363e+00
-6.27026677e-01 -1.72916070e-01 2.76549011e-01 1.06393623e+00
3.32537949e-01 -5.30536950e-01 8.99718106e-01 5.10027945e-01
-2.67278016e-01 -9.39377546e-02 -6.47937834e-01 -7.96063066e-01
6.36882246e-01 -5.00434816e-01 7.95380890e-01 8.75715375e-01
-6.28609717e-01 2.00830609e-01 -2.48499602e-01 5.04078627e-01
6.31036401e-01 1.80035502e-01 1.23589802e+00 -1.20729160e+00
-3.28290582e-01 -5.06814420e-01 -4.80804026e-01 -1.02224004e+00
3.12072337e-01 -6.31349921e-01 2.30371524e-02 -1.54203379e+00
-1.01200724e-02 -6.47055387e-01 -1.86377987e-01 5.07643402e-01
-1.84240818e-01 4.64756101e-01 -2.66049504e-02 9.46036726e-02
-4.74963993e-01 2.12397128e-01 1.15194535e+00 -4.35294956e-01
-2.38467544e-01 3.21867131e-02 -7.35461593e-01 8.00932586e-01
1.08071423e+00 -2.64609963e-01 -5.31692624e-01 -5.31011939e-01
-1.15245998e-01 -4.87922519e-01 6.54991090e-01 -1.44859111e+00
-1.79886326e-01 -5.11570573e-01 7.54358888e-01 -2.29614988e-01
2.16076657e-01 -1.06324852e+00 1.17727838e-01 1.26608178e-01
-1.92454174e-01 -5.37779152e-01 6.17950022e-01 7.12422788e-01
-7.91830346e-02 2.80021012e-01 1.22363579e+00 -1.96208864e-01
-1.67629135e+00 2.11287692e-01 -1.02355536e-02 4.11403865e-01
1.23922801e+00 -7.07551479e-01 -2.42824957e-01 -2.54317880e-01
-8.33040833e-01 2.90805399e-01 1.13812280e+00 6.51223540e-01
1.55602992e-01 -1.09393942e+00 -5.89186132e-01 2.68306673e-01
4.20007318e-01 3.50898981e-01 3.77605915e-01 3.53215635e-01
-5.81511378e-01 1.43202677e-01 -4.83092099e-01 -8.62979412e-01
-9.88799334e-01 6.69885397e-01 6.08637512e-01 -3.53982329e-01
-6.07502937e-01 7.11208344e-01 5.12996137e-01 -9.09880459e-01
-6.94888830e-02 -3.17055166e-01 2.92955972e-02 -3.82841587e-01
8.18361565e-02 -1.91323087e-02 5.16344570e-02 -8.33175600e-01
-2.57196754e-01 7.26639271e-01 1.79066539e-01 -5.10490760e-02
1.03054154e+00 -3.03104490e-01 6.41123056e-01 1.32892519e-01
9.01408732e-01 -2.54036069e-01 -2.01020360e+00 -4.87837255e-01
-1.88951746e-01 -4.65048194e-01 -8.35635364e-02 -1.23181581e+00
-9.86035824e-01 7.92579591e-01 9.02432442e-01 -2.21862540e-01
1.31977284e+00 5.01459790e-03 8.31792951e-01 -3.59455049e-02
2.67631054e-01 -1.54365087e+00 1.26621291e-01 5.25973260e-01
5.33880115e-01 -1.72685087e+00 -2.12072268e-01 -2.56568193e-01
-9.78594780e-01 6.16604984e-01 9.71633315e-01 -2.99469352e-01
6.22223318e-01 5.59383072e-02 3.17698419e-01 5.03887534e-02
-2.01298401e-01 -4.65169162e-01 9.39094350e-02 1.41751683e+00
-8.96543786e-02 1.90490291e-01 5.15903652e-01 3.44621927e-01
-1.34191275e-01 -1.23924822e-01 2.93856055e-01 6.91373765e-01
-3.71246338e-01 -1.06274855e+00 -6.67484283e-01 2.79149473e-01
-1.36693582e-01 6.33647442e-02 -4.03238624e-01 1.08281422e+00
4.68018860e-01 6.92327738e-01 4.97218072e-01 -1.77128702e-01
4.99584675e-01 2.11271912e-01 3.09434980e-01 -8.12959969e-01
-2.34853715e-01 -1.74449027e-01 -9.49676707e-02 -7.38277435e-01
-4.27652627e-01 -1.05050826e+00 -1.09555888e+00 -1.60771832e-02
4.82128203e-01 -5.93326330e-01 3.79959136e-01 9.24376369e-01
4.23215985e-01 6.14878058e-01 4.20125425e-01 -9.81580555e-01
-1.73776522e-01 -9.36825931e-01 -6.15961671e-01 9.54378009e-01
3.00436199e-01 -7.83454120e-01 -8.12918693e-02 3.79615545e-01] | [9.800701141357422, 1.4420305490493774] |
dfb0d38e-343e-4369-99d7-88f67a82f2c0 | on-the-contribution-of-word-embeddings-to | null | null | https://aclanthology.org/C16-1265 | https://aclanthology.org/C16-1265.pdf | On the contribution of word embeddings to temporal relation classification | Temporal relation classification is a challenging task, especially when there are no explicit markers to characterise the relation between temporal entities. This occurs frequently in inter-sentential relations, whose entities are not connected via direct syntactic relations making classification even more difficult. In these cases, resorting to features that focus on the semantic content of the event words may be very beneficial for inferring implicit relations. Specifically, while morpho-syntactic and context features are considered sufficient for classifying event-timex pairs, we believe that exploiting distributional semantic information about event words can benefit supervised classification of other types of pairs. In this work, we assess the impact of using word embeddings as features for event words in classifying temporal relations of event-event pairs and event-DCT (document creation time) pairs. | ['Paramita Mirza', 'Sara Tonelli'] | 2016-12-01 | on-the-contribution-of-word-embeddings-to-1 | https://aclanthology.org/C16-1265 | https://aclanthology.org/C16-1265.pdf | coling-2016-12 | ['temporal-relation-classification', 'implicit-relations'] | ['natural-language-processing', 'natural-language-processing'] | [-3.12740505e-02 1.65520459e-01 -3.95220608e-01 -5.98912060e-01
-1.26007006e-01 -8.28422368e-01 1.12018871e+00 1.29584277e+00
-7.71323562e-01 7.39533365e-01 6.44005954e-01 -4.80916142e-01
-4.61357713e-01 -1.06944168e+00 -1.95942029e-01 -4.37562883e-01
-6.52855814e-01 4.47037965e-01 3.26905996e-01 -3.71130824e-01
2.13193238e-01 6.37518406e-01 -1.44477081e+00 3.18887264e-01
6.22011721e-01 9.57273602e-01 -1.43200442e-01 2.73029536e-01
-5.53531170e-01 1.02918160e+00 -6.25096619e-01 -5.65773010e-01
-2.23019332e-01 -4.05210704e-01 -1.16789055e+00 -2.96878874e-01
-2.02120483e-01 2.10514188e-01 -2.37963989e-01 6.82682455e-01
1.62739292e-01 4.27635521e-01 1.04079318e+00 -1.19176769e+00
-2.65096962e-01 8.09113801e-01 -2.13433102e-01 8.21896672e-01
6.84494197e-01 -4.14984137e-01 1.58825004e+00 -5.43658316e-01
7.51415849e-01 1.11736929e+00 4.90158677e-01 -5.82657531e-02
-1.30587327e+00 -3.64150584e-01 4.00804818e-01 7.02490509e-01
-1.29034829e+00 -3.26783687e-01 8.34237218e-01 -4.81338710e-01
1.29880011e+00 1.30819827e-01 6.65194035e-01 1.14971280e+00
2.40192369e-01 3.75242293e-01 9.32086051e-01 -5.99452317e-01
6.29198700e-02 3.04828510e-02 4.76279199e-01 1.71748593e-01
1.73637047e-01 1.78576022e-01 -6.54972732e-01 -1.36210546e-01
3.66823941e-01 -1.13141842e-01 -2.65506834e-01 -1.81160010e-02
-1.27267814e+00 8.56857002e-01 4.98905957e-01 9.60177422e-01
-5.26727557e-01 -4.01744731e-02 9.19650555e-01 3.86766672e-01
7.60418534e-01 5.77402771e-01 -6.67885125e-01 -4.24399555e-01
-4.84447777e-01 2.05585629e-01 7.60785520e-01 5.37155032e-01
6.16184890e-01 -3.94409388e-01 -9.72392857e-02 6.80079997e-01
4.89924774e-02 -3.44688892e-01 6.15821958e-01 -3.48236680e-01
2.82208890e-01 7.74791420e-01 1.14252649e-01 -1.31544363e+00
-5.67281365e-01 9.68061909e-02 -3.14024538e-01 -3.09871048e-01
4.51148659e-01 5.51338494e-02 -4.88501906e-01 1.78085482e+00
5.41717827e-01 2.44340062e-01 2.76488096e-01 7.14661419e-01
7.68273532e-01 5.05339980e-01 6.66705489e-01 -6.10274374e-01
1.68679678e+00 -2.37830535e-01 -1.03838778e+00 -1.82378352e-01
1.00348413e+00 -7.09615648e-01 7.81566739e-01 -3.37908953e-01
-6.42745852e-01 -2.32627183e-01 -7.47468412e-01 -1.85256690e-01
-1.03676176e+00 -4.63025272e-01 1.00001276e+00 9.15860236e-02
-2.10214615e-01 7.30805337e-01 -7.53873706e-01 -6.49560809e-01
1.36981860e-01 2.32758492e-01 -6.43019974e-01 3.13178360e-01
-1.78875542e+00 1.42681313e+00 9.15543497e-01 2.94371936e-02
-2.63013095e-01 -4.86800462e-01 -1.15286338e+00 -2.32383446e-03
3.17621619e-01 -7.96697661e-02 9.24254000e-01 -8.24567735e-01
-8.52975488e-01 1.05099845e+00 -2.78457582e-01 -5.62203050e-01
1.33020684e-01 -5.53379618e-02 -9.68047321e-01 1.16692640e-01
1.71641216e-01 3.17051828e-01 5.73153198e-01 -6.44639850e-01
-6.11760139e-01 -3.36632550e-01 3.91756982e-01 1.64244279e-01
-4.35942620e-01 3.93733323e-01 1.36513874e-01 -7.82577932e-01
1.66607946e-01 -5.97088456e-01 -4.90429327e-02 -1.77913025e-01
-1.30516469e-01 -9.74617958e-01 7.79335320e-01 -5.14068782e-01
1.34987009e+00 -2.34685898e+00 -7.12668002e-02 6.76522851e-02
-5.78696653e-02 8.89633875e-03 8.67324695e-02 7.49142945e-01
-4.54193711e-01 1.09246008e-01 -6.00663871e-02 6.30683526e-02
-1.08366303e-01 5.15459895e-01 -4.25158679e-01 3.99487585e-01
4.94336754e-01 8.12648058e-01 -1.04763758e+00 -6.76623166e-01
1.42593309e-01 4.18013155e-01 -1.05882227e-01 1.25887215e-01
-1.76653415e-01 3.23893130e-01 -5.92385054e-01 1.21549115e-01
-6.31721094e-02 -5.10915555e-03 5.15532672e-01 -3.17622900e-01
-2.55252779e-01 1.16629219e+00 -9.30282176e-01 1.30283809e+00
-6.94170058e-01 6.99541450e-01 -6.90008700e-01 -1.29585898e+00
7.76371956e-01 8.02689493e-01 5.72551429e-01 -6.59012020e-01
2.72546679e-01 9.29832682e-02 3.54483038e-01 -6.91804469e-01
4.20427710e-01 -5.97864032e-01 -2.59281546e-01 3.63809198e-01
7.45114088e-02 -6.86357021e-02 6.47913814e-01 7.31684640e-02
1.05969059e+00 1.03230000e-01 8.88015747e-01 -3.07951719e-01
4.33585286e-01 -1.33957313e-02 7.47366071e-01 2.64728367e-02
-1.22287028e-01 1.69187963e-01 8.86293948e-01 -4.68413025e-01
-6.45932913e-01 -1.22432566e+00 -5.97711444e-01 8.86490643e-01
7.68645778e-02 -9.47502136e-01 7.41806626e-02 -1.02527952e+00
-1.18463911e-01 9.32112098e-01 -9.76034403e-01 -9.88848060e-02
-5.68422318e-01 -5.47119796e-01 3.49337250e-01 6.91994905e-01
-1.42535251e-02 -1.07538056e+00 -6.74860716e-01 4.73778009e-01
-3.06234062e-01 -1.13730454e+00 -1.48498088e-01 6.87082648e-01
-8.40900242e-01 -1.26796329e+00 -6.67914301e-02 -7.46566594e-01
4.56120610e-01 -2.88595736e-01 1.15414548e+00 -1.00786015e-01
-9.28978398e-02 1.45686835e-01 -7.57556438e-01 -4.02720898e-01
-1.48987085e-01 -2.01993715e-03 -1.09100185e-01 5.35957627e-02
7.73996294e-01 -7.47018158e-01 -2.12317437e-01 1.38056710e-01
-9.38209713e-01 -2.75715679e-01 -1.53289558e-02 6.49710059e-01
3.27156961e-01 4.00045097e-01 4.68684167e-01 -8.95296156e-01
5.08888364e-01 -6.40078902e-01 -4.67131063e-02 2.48121604e-01
-4.53916758e-01 1.72033682e-01 5.45524836e-01 -8.49671006e-01
-1.09362853e+00 -3.22399527e-01 -9.67047662e-02 1.46411389e-01
-4.02092814e-01 9.52785015e-01 -5.35352156e-02 5.20736396e-01
7.29879797e-01 -1.57598540e-01 -4.11741942e-01 -1.69809446e-01
2.88622409e-01 4.07216877e-01 -2.58738939e-02 -7.02285111e-01
5.70439935e-01 3.77817661e-01 1.21970199e-01 -7.66728938e-01
-1.01698279e+00 -6.08696163e-01 -8.46167445e-01 -5.04420325e-02
1.21026278e+00 -6.02200866e-01 -3.82000238e-01 -1.49864197e-01
-1.26946306e+00 -4.16677073e-02 -5.09337008e-01 8.91862035e-01
-4.13226008e-01 1.56807899e-01 -5.49868464e-01 -4.87944961e-01
3.12766135e-01 -7.60000646e-01 7.21417546e-01 -5.98402619e-02
-1.07170081e+00 -1.53432035e+00 1.43661454e-01 -7.91347548e-02
1.09618967e-02 3.77636969e-01 1.18307042e+00 -1.08186722e+00
-3.80167440e-02 -3.34866047e-01 -1.12980314e-01 -1.41144633e-01
6.52409315e-01 1.30872512e-02 -7.03145146e-01 3.85609299e-01
-1.97648462e-02 -2.06543118e-01 6.68329120e-01 9.34763774e-02
6.73822403e-01 -3.05424631e-01 -5.52486002e-01 -1.42521515e-01
1.11251402e+00 3.43034416e-01 5.61703980e-01 2.30331838e-01
5.49979210e-01 1.28967035e+00 8.62258732e-01 3.25315684e-01
4.01185930e-01 8.27210248e-01 -1.32365420e-01 4.08030868e-01
5.40343262e-02 -1.02939546e-01 3.71805072e-01 5.23116946e-01
-1.03618167e-01 -2.59918511e-01 -9.77034569e-01 8.44302475e-01
-1.64445496e+00 -1.06271696e+00 -6.47216499e-01 1.93194699e+00
1.25808442e+00 1.65354624e-01 -8.43595490e-02 5.80554187e-01
5.42702377e-01 5.33555150e-01 1.86584786e-01 -4.98038352e-01
-4.75270264e-02 2.86341786e-01 3.26467380e-02 4.09535944e-01
-1.20959508e+00 8.78802001e-01 5.54760838e+00 6.89527452e-01
-8.98326695e-01 2.14529276e-01 2.82785624e-01 3.22542757e-01
-3.42211306e-01 2.92271405e-01 -5.17317832e-01 3.91911924e-01
1.08395493e+00 -2.42720023e-01 -2.11672366e-01 2.49492064e-01
2.15186968e-01 -3.70921969e-01 -1.61485350e+00 6.69761837e-01
-1.46005020e-01 -9.79501486e-01 -1.16746731e-01 -1.98927090e-01
2.99678057e-01 -5.44126749e-01 -3.41233045e-01 1.13620266e-01
-2.77988566e-03 -7.96943069e-01 6.78937435e-01 1.32093430e-01
3.31269920e-01 -6.28510416e-01 8.24731112e-01 -7.44801983e-02
-1.44158423e+00 3.60244125e-01 4.38701063e-02 -2.91370898e-01
5.01560092e-01 8.40810895e-01 -8.25489342e-01 6.05432093e-01
5.83349884e-01 9.93221283e-01 -4.84885275e-01 7.27360070e-01
-6.58383727e-01 5.61848104e-01 -3.44601154e-01 3.49363424e-02
7.28882328e-02 -1.49272531e-01 4.98137534e-01 1.28632414e+00
1.02708437e-01 3.24373096e-01 -6.90694004e-02 5.09229898e-01
2.37539873e-01 4.00140911e-01 -8.60821664e-01 -5.82903028e-01
3.02739263e-01 9.89401996e-01 -1.22300017e+00 -2.29357570e-01
-5.94871938e-01 9.56018865e-01 4.56505507e-01 1.48916930e-01
-8.44328642e-01 -3.32276136e-01 8.15989971e-01 7.56365731e-02
1.49633572e-01 -3.45703065e-01 -8.92744437e-02 -1.04157996e+00
6.25096187e-02 -2.08356977e-01 8.87176931e-01 -4.57456112e-01
-1.54837775e+00 5.04051864e-01 2.76085794e-01 -1.07908535e+00
-3.17638069e-01 -4.59613889e-01 -6.20937824e-01 5.29067695e-01
-1.36249149e+00 -1.09717369e+00 1.68885484e-01 5.05857885e-01
2.72229373e-01 4.05619562e-01 1.05237770e+00 2.57458627e-01
-2.37711683e-01 2.08133578e-01 -6.55077755e-01 3.42456192e-01
7.57915974e-01 -1.27729821e+00 -9.94730145e-02 6.98426306e-01
6.43465638e-01 7.28054345e-01 9.59121883e-01 -6.38043344e-01
-6.36941254e-01 -8.40144694e-01 1.88757932e+00 -4.47450578e-01
1.19681156e+00 -2.84251243e-01 -9.49483812e-01 8.30560446e-01
2.87697583e-01 1.41641662e-01 1.00128376e+00 8.77446115e-01
-5.36889851e-01 8.57132152e-02 -7.58053422e-01 8.22050631e-01
1.16279948e+00 -9.96054351e-01 -1.26993203e+00 3.74499112e-01
8.23199630e-01 -7.67355412e-02 -1.15284419e+00 4.00469631e-01
1.47406742e-01 -5.06860435e-01 9.87657964e-01 -8.28823566e-01
5.61037004e-01 -3.30458134e-01 -1.48350701e-01 -1.22218633e+00
-1.99292004e-02 -1.16871677e-01 -1.54480478e-02 1.68377411e+00
7.03754961e-01 -7.17107356e-01 3.11991125e-01 5.17711639e-01
7.75456354e-02 -3.41093749e-01 -1.01136351e+00 -9.51405048e-01
-1.00750037e-01 -7.13220000e-01 3.58963639e-01 1.62130666e+00
4.70745564e-01 5.96026719e-01 1.23618588e-01 4.10499834e-02
-3.09425294e-02 2.94013888e-01 -7.48673305e-02 -1.39377260e+00
-1.46085888e-01 -3.99913788e-01 -8.51570725e-01 -3.28616470e-01
8.22041035e-01 -1.03975403e+00 -1.14283599e-01 -1.50689447e+00
-2.46599644e-01 -6.58164322e-01 -3.97437632e-01 5.33949435e-01
-1.89954594e-01 2.09486522e-02 -1.83235005e-01 -1.34585008e-01
-2.71712542e-01 6.93308294e-01 8.72795284e-01 -1.36837348e-01
-2.15920031e-01 -6.34361133e-02 -1.48954660e-01 7.15190232e-01
6.89688087e-01 -7.27875054e-01 -4.80994433e-01 -6.74863607e-02
4.51208413e-01 8.37950557e-02 3.12809855e-01 -6.18605137e-01
5.11759520e-02 -4.31409538e-01 7.12017789e-02 -2.79505342e-01
3.37853670e-01 -1.16887152e+00 1.44861192e-01 1.76179126e-01
-5.86318791e-01 7.87289515e-02 9.51346755e-02 5.80727875e-01
-7.74499476e-01 -5.22890329e-01 3.51142347e-01 9.30765495e-02
-8.64408255e-01 6.98170960e-02 -6.16452575e-01 1.84603319e-01
1.27653396e+00 -5.64281680e-02 2.74169873e-02 -1.01506934e-01
-1.06021905e+00 -2.03084379e-01 1.79696620e-01 5.81035018e-01
4.15346384e-01 -1.39751256e+00 -3.45706850e-01 -2.89064348e-01
5.23545802e-01 -2.61849612e-01 -4.12249342e-02 1.02408171e+00
-1.54232979e-01 2.46397167e-01 1.19136028e-01 -1.56804398e-01
-1.36777306e+00 7.57619441e-01 -1.26069887e-02 -2.92141318e-01
-5.58180571e-01 9.54388261e-01 1.71883300e-01 -1.75671741e-01
-6.56731473e-03 -4.12418813e-01 -6.41924322e-01 1.00826979e+00
2.35305548e-01 5.30493818e-02 4.23920266e-02 -8.60965550e-01
-6.30888104e-01 2.88354486e-01 -7.69084916e-02 -3.44697475e-01
1.43597472e+00 -6.79680007e-03 -4.38313305e-01 9.64111984e-01
1.27335918e+00 1.02759756e-01 -5.41185796e-01 -1.79344445e-01
6.85769022e-01 -3.63921702e-01 -1.15338422e-01 -4.61095601e-01
-6.72570348e-01 7.41989076e-01 3.41066457e-02 6.11452162e-01
9.29424882e-01 4.12936002e-01 5.27330875e-01 1.72163490e-02
3.27843726e-01 -9.65209842e-01 -1.44397810e-01 6.48237288e-01
8.40502620e-01 -1.19070339e+00 1.88865624e-02 -7.36538053e-01
-5.27808905e-01 1.26496351e+00 3.57646734e-01 3.36885522e-03
9.68306422e-01 9.92648751e-02 -1.99090928e-01 -3.80081892e-01
-7.09733009e-01 -6.48478031e-01 4.64713901e-01 4.35387433e-01
1.08392906e+00 8.16256106e-02 -1.00242162e+00 2.38948062e-01
-2.42646903e-01 -4.76286143e-01 1.78764880e-01 1.04831362e+00
1.68882474e-01 -1.50830185e+00 -5.99697009e-02 5.11544764e-01
-7.01691270e-01 -2.38649175e-01 -3.16000193e-01 7.76379824e-01
3.57908875e-01 1.06267250e+00 5.74626088e-01 -5.88950627e-02
1.37058765e-01 2.86431372e-01 5.99004745e-01 -7.72959471e-01
-7.22264051e-01 -3.07330400e-01 7.82050192e-01 -5.01428545e-01
-8.40912282e-01 -9.80117977e-01 -1.53306484e+00 -1.26532406e-01
-3.02126229e-01 3.68515790e-01 3.62228006e-01 1.37901175e+00
-3.29648447e-03 6.07875824e-01 3.21819752e-01 -3.50717396e-01
1.14465080e-01 -7.86529839e-01 -4.76837754e-01 8.49075615e-01
9.89275351e-02 -1.00636899e+00 -3.86482984e-01 1.62267581e-01] | [9.165438652038574, 9.192998886108398] |
468cfba7-27fe-4b3d-b93f-ef8a668ea805 | deep-correlation-analysis-for-audio-eeg | 2105.08492 | null | https://arxiv.org/abs/2105.08492v2 | https://arxiv.org/pdf/2105.08492v2.pdf | Deep Correlation Analysis for Audio-EEG Decoding | The electroencephalography (EEG), which is one of the easiest modes of recording brain activations in a non-invasive manner, is often distorted due to recording artifacts which adversely impacts the stimulus-response analysis. The most prominent techniques thus far attempt to improve the stimulus-response correlations using linear methods. In this paper, we propose a neural network based correlation analysis framework that significantly improves over the linear methods for auditory stimuli. A deep model is proposed for intra-subject audio-EEG analysis based on directly optimizing the correlation loss. Further, a neural network model with a shared encoder architecture is proposed for improving the inter-subject stimulus response correlations. These models attempt to suppress the EEG artifacts while preserving the components related to the stimulus. Several experiments are performed using EEG recordings from subjects listening to speech and music stimuli. In these experiments, we show that the deep models improve the Pearson correlation significantly over the linear methods (average absolute improvements of 7.4% in speech tasks and 29.3% in music tasks). We also analyze the impact of several model parameters on the stimulus-response correlation. | ['Sriram Ganapathy', 'Jaswanth Reddy Katthi'] | 2021-05-18 | null | null | null | null | ['eeg-decoding', 'eeg-decoding'] | ['medical', 'time-series'] | [ 7.76491836e-02 -3.85477066e-01 5.36952794e-01 -5.25766432e-01
-8.27137709e-01 3.34191620e-02 2.08774060e-01 -1.89120993e-02
-5.42437196e-01 7.66749203e-01 2.18892559e-01 2.96974540e-01
-4.06582385e-01 -2.71748930e-01 -5.65708101e-01 -7.61576831e-01
-5.26905239e-01 -7.87129328e-02 -1.35927543e-01 -8.35679173e-02
2.83035129e-01 2.67095327e-01 -1.30692744e+00 3.62632185e-01
8.03406715e-01 1.29329777e+00 2.00972438e-01 4.79821771e-01
5.37788212e-01 6.57019794e-01 -9.33881819e-01 -1.45758435e-01
3.65884267e-02 -6.71492994e-01 -1.76338330e-01 -5.16030192e-01
8.42370465e-02 -3.00550889e-02 -3.29530060e-01 1.22751939e+00
1.16711605e+00 1.19314626e-01 4.91115600e-01 -1.15551555e+00
-3.04271191e-01 8.68953109e-01 -6.72838330e-01 4.52296764e-01
2.77953953e-01 -1.88158914e-01 6.81317270e-01 -9.58729565e-01
-1.73396930e-01 9.33210075e-01 7.02415586e-01 3.22724819e-01
-1.40265632e+00 -1.16077089e+00 -2.27295801e-01 8.10381949e-01
-1.90074050e+00 -5.41258752e-01 1.11528075e+00 -4.15842980e-01
1.05109441e+00 3.55903983e-01 5.63604593e-01 1.25456214e+00
5.64201772e-01 4.04315144e-01 1.21426332e+00 -3.05233836e-01
2.18427882e-01 1.88972995e-01 2.43500084e-01 -1.57044902e-01
-6.94124922e-02 1.95820659e-01 -1.15528929e+00 -1.07847847e-01
5.76444149e-01 -3.68849635e-01 -5.95291257e-01 1.00056916e-01
-1.04963863e+00 4.77554619e-01 4.36321080e-01 6.86760366e-01
-6.43763602e-01 1.12626940e-01 6.01007640e-01 2.59344906e-01
4.71807718e-01 7.33805895e-01 -3.52858782e-01 -3.16090941e-01
-1.22486866e+00 8.75466987e-02 6.00180209e-01 6.19975865e-01
2.60834306e-01 2.44226798e-01 -2.84383744e-01 1.12240303e+00
3.17690298e-02 3.67378443e-01 7.97439396e-01 -5.68061948e-01
3.37697387e-01 5.97719252e-02 -1.70738041e-01 -1.25240946e+00
-8.59549940e-01 -8.22316945e-01 -1.15868855e+00 -1.69700328e-02
1.07659355e-01 -2.48833984e-01 -2.68517137e-01 1.92318618e+00
-4.21917945e-01 3.18134397e-01 -8.95507485e-02 9.52421308e-01
6.74682915e-01 4.23693478e-01 -9.06882510e-02 -5.54743230e-01
1.19379914e+00 -5.38976192e-01 -1.25399983e+00 -1.84005916e-01
1.37414530e-01 -6.95038259e-01 9.78820503e-01 7.26377547e-01
-1.33352137e+00 -6.53281450e-01 -1.08815169e+00 1.99761063e-01
2.40198150e-02 8.29460993e-02 1.96896732e-01 4.95026529e-01
-9.27821755e-01 6.45462394e-01 -9.19137418e-01 1.07790411e-01
2.58836478e-01 7.63716102e-01 -3.65738809e-01 5.54965138e-01
-1.38574731e+00 1.03224039e+00 1.17246673e-01 2.11111903e-01
-6.57084823e-01 -8.68110061e-01 -2.97222316e-01 5.05260587e-01
-2.84443256e-02 -2.18531907e-01 8.17654550e-01 -9.57254648e-01
-1.53029466e+00 2.64994323e-01 -1.85677543e-01 -5.72418094e-01
1.78036481e-01 -3.98811698e-01 -5.31226158e-01 7.27794096e-02
-2.09285975e-01 5.25226057e-01 7.25114703e-01 -7.62962461e-01
-2.11659949e-02 -5.23640156e-01 -6.27344728e-01 -3.21376920e-02
-5.41145742e-01 2.72922665e-01 -6.31473958e-02 -8.20568144e-01
-7.51754595e-03 -8.37259471e-01 6.73111901e-02 -6.73311532e-01
-3.53429079e-01 -9.56472009e-03 9.04401764e-02 -7.61056662e-01
1.22559583e+00 -2.44791722e+00 1.33475587e-01 4.25783753e-01
8.54012594e-02 2.26899944e-02 -1.87515259e-01 2.19460785e-01
-5.54288387e-01 -2.02009127e-01 -2.15108722e-01 -4.50760394e-01
-1.20373726e-01 -2.49084339e-01 -1.12055570e-01 4.74565536e-01
2.30119098e-02 7.17739880e-01 -3.17098320e-01 -1.84186324e-02
-1.05947331e-01 8.52457106e-01 -5.54833293e-01 4.81645495e-01
5.93534231e-01 5.26367903e-01 3.12541991e-01 1.11341693e-01
7.79518425e-01 5.54884374e-02 2.79760379e-02 -5.01097262e-01
-1.30881950e-01 5.54105818e-01 -9.97617841e-01 1.80071878e+00
-5.26459754e-01 1.01062465e+00 -7.61936009e-02 -9.71747398e-01
1.10984147e+00 6.28380120e-01 6.06604517e-01 -1.10892236e+00
5.12745500e-01 2.51327813e-01 6.85927510e-01 -3.18185210e-01
-3.67604792e-02 -1.68393269e-01 2.55365729e-01 2.73291141e-01
2.30902672e-01 1.86951503e-01 5.68861794e-03 -3.05001028e-02
9.69258964e-01 -4.88068461e-01 2.18727142e-01 -6.13983929e-01
5.83367646e-01 -7.78275490e-01 5.31381726e-01 5.11294901e-01
-9.73188058e-02 6.25079989e-01 5.17290473e-01 -1.38251260e-01
-6.21936083e-01 -9.64941204e-01 -3.91930103e-01 6.04245424e-01
-5.78474924e-02 -5.66859007e-01 -8.67510736e-01 1.36110604e-01
-2.68762946e-01 7.34926343e-01 -6.71201766e-01 -5.78161955e-01
-2.56607324e-01 -9.70645010e-01 6.59327149e-01 8.01522434e-01
4.34180856e-01 -9.62433755e-01 -5.42786121e-01 2.60794163e-01
-4.92262542e-01 -1.10610449e+00 -3.60217631e-01 6.72436118e-01
-7.15535402e-01 -6.41992390e-01 -6.31094694e-01 -5.13005495e-01
3.87741059e-01 -5.99537343e-02 5.98936796e-01 -4.21309620e-01
-2.58457601e-01 -8.04482680e-03 -1.65746823e-01 -6.93868876e-01
2.04741687e-01 -1.55195341e-01 5.59709430e-01 2.08498448e-01
6.60283029e-01 -1.11167741e+00 -4.89184052e-01 3.05086046e-01
-5.69106758e-01 -1.72940716e-01 5.92152357e-01 9.90458548e-01
4.13773358e-01 2.16652885e-01 9.95570779e-01 -2.63074845e-01
1.10074425e+00 -2.01418519e-01 -4.61895645e-01 -9.29363668e-02
-5.48234999e-01 6.88320994e-02 7.28960097e-01 -6.32852852e-01
-8.25349092e-01 -2.13910028e-01 -1.41114086e-01 -3.86788249e-01
-1.74668543e-02 4.63670254e-01 -1.28010124e-01 -1.80902451e-01
7.06110179e-01 1.04627259e-01 -2.23432153e-01 -3.82037222e-01
-2.76056439e-01 7.09872246e-01 5.81226170e-01 -1.36630818e-01
3.31342876e-01 3.29001285e-02 3.18089649e-02 -8.38351190e-01
-3.46683085e-01 -2.47401059e-01 -5.47116220e-01 -1.83851585e-01
7.34659135e-01 -9.25134301e-01 -9.56965387e-01 3.65910798e-01
-1.32305086e+00 -1.58920929e-01 1.34794489e-01 1.28790343e+00
-6.03371203e-01 4.43953164e-02 -5.36147594e-01 -8.71913910e-01
-5.83845437e-01 -1.28752816e+00 5.84155321e-01 -9.95160267e-02
-5.54070294e-01 -4.59751993e-01 9.51243490e-02 -1.38914630e-01
5.49276829e-01 -2.37611845e-01 7.04616368e-01 -7.24236131e-01
7.98608288e-02 -8.62808898e-02 -1.38077661e-01 5.56171119e-01
6.14251122e-02 -5.97145796e-01 -1.26156855e+00 -2.48654321e-01
6.48475528e-01 4.87410016e-02 4.73777622e-01 7.32287169e-01
1.35252774e+00 -6.87561408e-02 3.24155129e-02 6.89329624e-01
1.17404282e+00 6.02710247e-01 9.44427192e-01 4.99316826e-02
3.55908960e-01 6.46794796e-01 -1.68717168e-02 5.45675337e-01
-1.08110964e-01 7.07826495e-01 8.81012678e-02 4.36427630e-02
5.41384853e-02 1.21614560e-01 2.82610238e-01 1.39507151e+00
-1.11730680e-01 -6.40970692e-02 -6.56639576e-01 4.10746634e-01
-1.64674294e+00 -8.96336615e-01 -3.26923162e-01 2.45613408e+00
7.77252734e-01 -7.77883409e-03 4.47124839e-02 6.75338328e-01
4.15281594e-01 -3.85702103e-01 -3.19083810e-01 -4.69814539e-01
-1.16112158e-01 6.90628827e-01 3.21703672e-01 2.92378753e-01
-6.65475965e-01 3.02656442e-01 6.71890354e+00 5.11300087e-01
-1.22995102e+00 1.59410939e-01 2.41676465e-01 -5.43154120e-01
2.30913565e-01 -5.40135562e-01 -4.33713615e-01 6.70023143e-01
1.32814682e+00 -3.81926000e-01 7.22016394e-01 4.09070522e-01
5.84865093e-01 -2.91722625e-01 -1.38963687e+00 1.72989321e+00
2.86234260e-01 -6.97933197e-01 -4.58055288e-01 -9.69557092e-02
3.88794780e-01 -1.45434979e-02 1.42529488e-01 -3.42899263e-02
-5.92009127e-01 -1.13580465e+00 6.81838572e-01 7.64139831e-01
5.79515576e-01 -1.10395312e+00 9.54004169e-01 3.02185953e-01
-9.11322832e-01 -1.42575696e-01 -4.02477324e-01 -3.01322967e-01
1.00895241e-01 8.79465580e-01 -5.07629573e-01 3.13025177e-01
9.74750042e-01 6.08101726e-01 -4.67255265e-01 1.17869008e+00
-2.92490870e-01 6.95125222e-01 -1.40105069e-01 -1.20332770e-01
-2.93830246e-01 -1.17128544e-01 5.68703234e-01 1.26362240e+00
5.27807117e-01 1.16255850e-01 -5.25408030e-01 1.14371371e+00
1.86319519e-02 2.15357274e-01 -5.30404925e-01 2.76348084e-01
4.04831618e-01 9.82605696e-01 -2.29993746e-01 -2.50123162e-02
-3.41374010e-01 8.28597307e-01 1.19698696e-01 3.71361822e-01
-9.02154982e-01 -8.96764934e-01 4.81494278e-01 -1.91180721e-01
-1.20876834e-01 -2.84295321e-01 -6.13116741e-01 -9.34394479e-01
2.41007239e-01 -9.18345630e-01 -1.56063601e-01 -9.67755377e-01
-1.29353857e+00 9.04860675e-01 2.22647022e-02 -1.16482317e+00
-2.88186371e-01 -4.34443563e-01 -3.74073923e-01 1.30290902e+00
-1.05321658e+00 -2.01265469e-01 -2.60100633e-01 8.54429603e-01
2.16445625e-01 -1.43316597e-01 9.80340898e-01 8.46725285e-01
-5.50693572e-01 8.62403393e-01 -1.48193330e-01 -1.42199412e-01
9.35357273e-01 -8.28715503e-01 -6.20205887e-02 9.43250477e-01
1.63194671e-01 8.86073887e-01 6.91519141e-01 -2.01115459e-01
-1.05435097e+00 -5.95771730e-01 1.04625559e+00 2.15432897e-01
5.27739167e-01 -7.56569743e-01 -1.06427979e+00 3.26659888e-01
5.54067135e-01 -3.14926714e-01 1.04267144e+00 1.79752484e-01
-1.06272176e-01 -6.68564379e-01 -7.99471140e-01 5.17564833e-01
7.15725958e-01 -7.92594552e-01 -6.81298256e-01 7.60753974e-02
2.46017382e-01 3.26886214e-02 -8.44155312e-01 2.97282904e-01
8.04446757e-01 -1.01328528e+00 7.65713036e-01 -2.53748238e-01
1.42067507e-01 -1.65116951e-01 -2.66630262e-01 -1.86529398e+00
-5.55559695e-01 -6.65411115e-01 2.02732399e-01 9.03079867e-01
2.89016575e-01 -5.83349049e-01 2.95240253e-01 5.92623889e-01
-1.67293161e-01 -4.01538938e-01 -1.01383209e+00 -1.02393663e+00
-1.51603460e-01 -7.70987928e-01 3.51572424e-01 5.72939813e-01
6.57931387e-01 6.44936919e-01 -6.20340109e-01 1.57065898e-01
4.95337814e-01 -5.41905820e-01 3.78789604e-01 -1.07111537e+00
-3.36227477e-01 -4.57949817e-01 -6.36312723e-01 -8.33477795e-01
1.42183945e-01 -7.74394393e-01 3.30183029e-01 -1.02908087e+00
3.00706506e-01 5.82825653e-02 -8.33403647e-01 1.86283827e-01
-7.07383603e-02 2.21718743e-01 5.10583706e-02 -7.37905651e-02
-7.43878633e-02 5.85523009e-01 7.02236533e-01 -4.89026718e-02
-4.05272394e-01 -3.25787924e-02 -5.06739259e-01 5.58485866e-01
1.00116980e+00 -7.16931939e-01 -4.44442987e-01 -5.05718827e-01
1.91084459e-01 8.06197971e-02 1.53429359e-01 -1.54092574e+00
5.73393345e-01 5.47881246e-01 5.24157405e-01 -4.90642607e-01
6.28335595e-01 -8.86210382e-01 2.33063266e-01 4.05757129e-01
-6.89034760e-01 2.58618206e-01 4.78121459e-01 2.78719604e-01
-4.93241847e-01 -2.17079502e-02 9.29093540e-01 2.86997527e-01
1.08028337e-01 -6.57116175e-02 -5.82314849e-01 -2.29184002e-01
7.33278334e-01 1.05460808e-01 1.34367486e-02 -4.70270544e-01
-8.06721210e-01 -1.52868897e-01 -5.26384115e-01 2.09868416e-01
7.38554597e-01 -1.45449650e+00 -7.21699178e-01 5.56319058e-01
-8.55479017e-02 -6.69028342e-01 3.63980234e-01 1.53894305e+00
1.97983995e-01 7.21482933e-01 -6.56985819e-01 -5.21411300e-01
-1.48339069e+00 4.77404922e-01 4.39905763e-01 2.89650373e-02
-2.57815003e-01 1.12474895e+00 4.11319375e-01 3.83335322e-01
5.85346401e-01 -4.99995619e-01 -3.83814096e-01 7.26067200e-02
9.96917427e-01 6.15360618e-01 5.36553204e-01 -4.95362967e-01
-6.85346425e-01 4.01622832e-01 1.12812407e-01 -4.23223555e-01
1.54632413e+00 6.99389204e-02 -3.07515115e-01 7.66352177e-01
1.41819263e+00 -3.47266383e-02 -7.66091406e-01 -2.30282359e-02
-1.74168497e-01 -3.86390001e-01 3.62849802e-01 -9.43040729e-01
-1.20539570e+00 1.40442669e+00 9.52507138e-01 4.12415229e-02
1.57570887e+00 -5.94657540e-01 4.77504671e-01 3.40485215e-01
4.72058177e-01 -1.00315762e+00 2.09078535e-01 2.58347005e-01
1.18811595e+00 -8.66656065e-01 -1.11606024e-01 -9.18497965e-02
-5.28778493e-01 1.21123791e+00 4.11561519e-01 -3.02588940e-01
6.86497152e-01 6.92415416e-01 -2.05360800e-01 -4.08775434e-02
-7.31998384e-01 2.59962142e-01 4.27642375e-01 5.32802761e-01
7.37143636e-01 1.92628875e-01 -6.35271847e-01 1.15580487e+00
-3.32992733e-01 1.32691264e-02 3.58609289e-01 3.18805903e-01
1.25898002e-02 -8.97139490e-01 -5.11721611e-01 4.94366109e-01
-6.98014975e-01 -4.14596766e-01 -4.47505116e-01 5.00417411e-01
-1.19961850e-01 1.21386051e+00 1.53260946e-01 -7.85609186e-01
6.20765984e-01 1.29883096e-01 5.84714651e-01 -2.66133398e-01
-8.42134953e-01 4.55181837e-01 -1.62562355e-01 -7.20303714e-01
-4.55753475e-01 -5.96299350e-01 -1.15572858e+00 -3.91395688e-02
-5.28234422e-01 2.44430333e-01 8.36947083e-01 7.47673035e-01
4.36812252e-01 1.06240809e+00 6.06168568e-01 -6.87508047e-01
-2.98076719e-01 -1.34621084e+00 -1.00208950e+00 2.08913594e-01
2.09523499e-01 -7.66893446e-01 -5.86140156e-01 -1.61591098e-01] | [13.162996292114258, 3.4216299057006836] |
da9ce070-7590-4038-aac5-e37f59d2d65e | understanding-the-impact-of-culture-in | 2305.04836 | null | https://arxiv.org/abs/2305.04836v1 | https://arxiv.org/pdf/2305.04836v1.pdf | Understanding the Impact of Culture in Assessing Helpfulness of Online Reviews | Online reviews have become essential for users to make informed decisions in everyday tasks ranging from planning summer vacations to purchasing groceries and making financial investments. A key problem in using online reviews is the overabundance of online that overwhelms the users. As a result, recommendation systems for providing helpfulness of reviews are being developed. This paper argues that cultural background is an important feature that impacts the nature of a review written by the user, and must be considered as a feature in assessing the helpfulness of online reviews. The paper provides an in-depth study of differences in online reviews written by users from different cultural backgrounds and how incorporating culture as a feature can lead to better review helpfulness recommendations. In particular, we analyze online reviews originating from two distinct cultural spheres, namely Arabic and Western cultures, for two different products, hotels and books. Our analysis demonstrates that the nature of reviews written by users differs based on their cultural backgrounds and that this difference varies based on the specific product being reviewed. Finally, we have developed six different review helpfulness recommendation models that demonstrate that taking culture into account leads to better recommendations. | ['Shivakant Mishra', 'Maram Kurdi', 'Omar Hammad', 'Nuha Albadi', 'Khaled Alanezi'] | 2023-04-27 | null | null | null | null | ['culture'] | ['speech'] | [-4.84912127e-01 -2.35632136e-01 -4.80987608e-01 -4.79900748e-01
-7.19556178e-04 -6.32511854e-01 6.76648498e-01 6.30120814e-01
-4.78949070e-01 3.73699307e-01 5.69789529e-01 -4.92451131e-01
-8.62371325e-02 -5.60281456e-01 -3.68092284e-02 -3.23492110e-01
6.37721717e-01 5.40905073e-02 -3.14590335e-02 -9.59387839e-01
9.84735966e-01 1.29631668e-01 -1.59040391e+00 1.42091334e-01
1.11165643e+00 4.86831993e-01 3.54376018e-01 5.60516059e-01
-6.33239746e-01 6.33520842e-01 -7.38753378e-01 -8.44280899e-01
2.94317324e-02 -5.15936911e-01 -1.80228516e-01 4.01846170e-01
2.24757846e-02 -1.81186795e-01 4.65524137e-01 9.30787146e-01
1.29080907e-01 5.23626618e-02 9.82600689e-01 -9.06563520e-01
-1.44086349e+00 6.75330102e-01 -4.79877889e-01 1.19221453e-02
3.50717276e-01 -5.77319264e-01 1.22018766e+00 -1.04975700e+00
5.15186906e-01 1.10597384e+00 4.16784912e-01 2.18758345e-01
-6.36717141e-01 -4.62599367e-01 6.26585722e-01 -3.28701809e-02
-8.95279646e-01 -2.16092080e-01 5.10640264e-01 -5.96246421e-01
6.70128644e-01 1.35103524e-01 9.63062882e-01 4.04479176e-01
6.64200962e-01 3.64607498e-02 1.10536122e+00 -7.21078336e-01
4.29303288e-01 1.07095611e+00 3.64657849e-01 -2.75550485e-02
8.08159649e-01 -6.86840713e-01 -3.94751638e-01 -5.89435920e-02
3.41525853e-01 4.10479397e-01 -1.47771239e-01 3.52539942e-02
-5.42206883e-01 1.19697165e+00 2.39411127e-02 4.44606632e-01
-4.52446431e-01 -4.95607227e-01 4.38259870e-01 5.73828220e-01
6.38137460e-01 5.90610862e-01 -3.11642855e-01 -3.73360574e-01
-3.42439294e-01 -1.19996831e-01 1.18467879e+00 6.61093533e-01
5.44225693e-01 -1.80076867e-01 5.08211911e-01 1.33806646e+00
5.70576191e-01 5.14082789e-01 5.95002592e-01 -5.06314397e-01
-6.37524500e-02 8.40978801e-01 3.59087110e-01 -1.52815187e+00
-4.86466847e-02 -3.92249018e-01 -2.80266821e-01 1.68484878e-02
5.59547432e-02 -3.38175088e-01 -3.00922006e-01 9.50328529e-01
4.03559841e-02 -9.74669278e-01 -8.99129212e-02 1.00047815e+00
7.67174184e-01 4.54022050e-01 -2.00815573e-02 -3.25538605e-01
1.38217485e+00 -1.07730269e+00 -9.86378431e-01 -4.23497498e-01
7.23862410e-01 -1.23656845e+00 1.16820633e+00 8.24226022e-01
-8.39618742e-01 -5.88654101e-01 -1.23523676e+00 7.76926950e-02
-7.59808660e-01 2.64143318e-01 6.19036078e-01 1.02960217e+00
-1.06805968e+00 4.57356185e-01 -4.98890094e-02 -9.58391786e-01
-4.67486203e-01 1.69306353e-01 -1.51064783e-01 -2.29609087e-01
-9.46450949e-01 1.23622704e+00 -6.11123800e-01 9.37267616e-02
1.33510143e-01 -8.80044624e-02 -6.51223719e-01 -3.42784703e-01
-7.05816522e-02 -1.12181976e-01 1.07169294e+00 -1.57559323e+00
-1.29329884e+00 5.14614224e-01 -1.64807528e-01 2.15914726e-01
-1.88547894e-02 -4.15716559e-01 -9.37672734e-01 -8.94205347e-02
2.96205670e-01 7.44541511e-02 7.17353344e-01 -1.19938385e+00
-8.64267468e-01 -3.21246862e-01 2.99722075e-01 4.48273510e-01
-6.30577445e-01 4.98106360e-01 -3.81102502e-01 -4.84285384e-01
-8.67488459e-02 -9.15116072e-01 -1.19900428e-01 -4.32172269e-01
2.37309903e-01 -1.19574927e-01 3.12057167e-01 -7.80406952e-01
1.49696720e+00 -1.91450882e+00 -1.05126738e-03 4.08284396e-01
8.02232791e-03 1.42973274e-01 1.04607316e-02 1.01008081e+00
4.56240624e-01 7.03060448e-01 5.34231901e-01 -1.08733103e-01
-1.71791408e-02 1.00739010e-01 8.19225088e-02 1.88188180e-01
7.79960528e-02 2.49449521e-01 -8.85363877e-01 1.33896455e-01
-1.90647990e-01 8.42914939e-01 -2.42770746e-01 -2.43713543e-01
3.60836327e-01 3.33007202e-02 -3.68078977e-01 6.39245987e-01
4.89983857e-01 -3.34265560e-01 3.22921962e-01 4.89542931e-01
-5.02511978e-01 5.46845615e-01 -7.04984009e-01 9.06590402e-01
-6.04240656e-01 6.78368926e-01 2.82439590e-01 -4.03196961e-01
1.42771089e+00 1.18950240e-01 6.99552149e-02 -9.87121999e-01
3.05129468e-01 5.98338068e-01 3.29938054e-01 -2.12824568e-01
1.35369992e+00 -2.18747675e-01 2.26154491e-01 9.80493903e-01
-8.79288316e-01 -2.00816959e-01 6.34525359e-01 5.19805789e-01
6.00181818e-01 -2.52539724e-01 4.86855835e-01 -4.78954107e-01
6.33075178e-01 1.55012995e-01 2.97980964e-01 3.70798379e-01
-2.33626544e-01 4.30633366e-01 5.38654208e-01 -1.80303603e-01
-1.01330125e+00 -6.48026243e-02 -3.76012665e-03 9.72450554e-01
7.21731111e-02 -6.55611396e-01 -4.60982531e-01 -3.94305587e-01
1.13246411e-01 7.17155159e-01 -7.43952811e-01 -9.74400789e-02
-9.96359736e-02 -4.82208669e-01 -4.17798102e-01 2.50401437e-01
2.42123622e-02 -7.20439732e-01 -4.79921490e-01 2.00299263e-01
6.40254244e-02 -6.65496290e-01 -6.29115880e-01 4.42477502e-02
-8.97392511e-01 -9.26346958e-01 -8.68953884e-01 -6.86133742e-01
9.67776775e-01 1.06023157e+00 1.19836509e+00 7.08291888e-01
2.18692198e-01 7.02518702e-01 -1.13418460e+00 -6.81306183e-01
-3.80346388e-01 2.38562569e-01 1.58832759e-01 -3.00249249e-01
9.41109180e-01 -8.09186250e-02 -5.23950517e-01 6.94487512e-01
-7.54027724e-01 -3.74139667e-01 3.68978858e-01 3.50856841e-01
-1.96779352e-02 9.98854414e-02 1.18022990e+00 -1.13626611e+00
1.35778356e+00 -9.02024686e-01 -1.79449804e-02 1.98649138e-01
-1.04201210e+00 -3.83383125e-01 5.94705820e-01 -2.17672929e-01
-1.05642831e+00 -7.13423967e-01 5.15158474e-02 5.92215657e-01
2.53077120e-01 8.60097408e-01 4.57904577e-01 -4.40311767e-02
6.69588625e-01 -3.22791457e-01 4.64974076e-01 -2.18629599e-01
-7.05480650e-02 9.36282277e-01 -6.04036927e-01 -7.12288767e-02
3.90789390e-01 2.60513902e-01 -7.11899519e-01 -1.04982316e+00
-4.82204884e-01 -7.64133751e-01 -5.46725392e-01 -5.64407229e-01
5.58821917e-01 -8.00046802e-01 -3.41193318e-01 9.23507214e-02
-6.78916335e-01 -7.93049783e-02 2.74513990e-01 6.37648046e-01
2.47441202e-01 2.71341622e-01 -6.54264450e-01 -1.04512668e+00
-3.27568620e-01 -1.07271183e+00 3.60286295e-01 5.16001761e-01
-5.96738756e-01 -1.34681714e+00 1.73096254e-01 6.31432533e-01
6.72143221e-01 -3.31861526e-01 8.68703187e-01 -5.82749426e-01
-2.45129596e-03 -3.37475628e-01 -4.49450649e-02 6.06857955e-01
5.71395397e-01 5.44281840e-01 -4.78927135e-01 1.94615610e-02
6.23207167e-03 1.32855829e-02 3.40050727e-01 3.35004330e-01
-2.20724329e-01 -1.15227722e-01 1.19560175e-01 -2.66711056e-01
1.35291660e+00 6.24650300e-01 7.08250761e-01 6.42509162e-01
3.62152189e-01 1.19158280e+00 1.30001688e+00 5.38165152e-01
5.46569526e-01 9.07144994e-02 2.12939128e-01 2.20665678e-01
4.01314795e-01 1.27777085e-01 7.10328221e-01 1.58591712e+00
-1.25752036e-02 5.09372056e-02 -5.11531591e-01 6.37989581e-01
-1.51867163e+00 -4.97869790e-01 -4.49267417e-01 2.27237415e+00
4.40696627e-01 -4.97546270e-02 2.57135570e-01 2.17270330e-01
6.27972424e-01 -1.56881019e-01 -2.47529015e-01 -1.36362469e+00
4.97146063e-02 -7.01475516e-02 4.02897865e-01 6.25256896e-01
-2.34462723e-01 5.32331645e-01 6.00853634e+00 -5.42486235e-02
-1.15973473e+00 -1.91486612e-01 7.97175586e-01 -5.55519061e-03
-7.44358003e-01 -4.92298305e-02 -9.26821470e-01 3.39553893e-01
8.50956202e-01 -2.10298851e-01 2.17819333e-01 8.38554859e-01
6.26977861e-01 -6.77761078e-01 -6.06309116e-01 5.82555354e-01
5.67081511e-01 -8.51141751e-01 -1.97549760e-01 1.69962928e-01
8.11845243e-01 -4.15495574e-01 1.11198559e-01 2.62382865e-01
1.68189704e-01 -7.45499134e-01 6.28152668e-01 2.89371967e-01
3.09589300e-02 -9.29585099e-01 9.61996794e-01 1.40331879e-01
-8.73835087e-01 2.49364022e-02 -7.00226247e-01 -9.17973816e-01
2.72808403e-01 7.94691026e-01 -5.71592212e-01 5.44004403e-02
7.23114133e-01 9.14985299e-01 -6.16012633e-01 6.78959370e-01
-2.79815763e-01 3.68255019e-01 3.29863697e-01 -7.06060171e-01
4.03911397e-02 -9.47563529e-01 -5.95050976e-02 8.23939502e-01
5.80162525e-01 2.09061176e-01 -2.52578825e-01 2.57175773e-01
3.42477947e-01 9.86014068e-01 -5.82922757e-01 -5.15545189e-01
4.79898304e-01 1.41817033e+00 -1.00842607e+00 -1.16319984e-01
-7.15918839e-01 7.73459792e-01 1.73730473e-03 3.06598961e-01
-3.41080576e-01 -4.53260273e-01 7.05273032e-01 4.05238777e-01
2.87943721e-01 -1.09817773e-01 -6.10815942e-01 -7.69064903e-01
-9.98684242e-02 -1.12082517e+00 -1.54868424e-01 -6.84466600e-01
-1.25906837e+00 4.25692528e-01 -6.42831028e-01 -1.10087872e+00
1.26653582e-01 -6.77529573e-01 -6.06545389e-01 1.21683180e+00
-1.58877432e+00 -6.87465847e-01 -2.49547616e-01 5.86848939e-03
5.68157852e-01 -1.01360336e-01 4.47900236e-01 4.66081262e-01
-5.49565077e-01 1.78314179e-01 2.53277589e-02 -5.09298027e-01
1.31905365e+00 -1.02894413e+00 9.59875286e-02 6.49155378e-01
-2.81090945e-01 1.20800066e+00 5.69954574e-01 -9.75056946e-01
-1.32066774e+00 -3.09665352e-01 1.43091893e+00 -3.24724197e-01
7.01633930e-01 2.22572565e-01 -6.53401792e-01 6.14447705e-02
7.09979832e-01 -1.09612167e+00 1.39492857e+00 6.56226635e-01
-1.83124989e-01 -7.29382709e-02 -9.10073280e-01 8.78159583e-01
4.16809559e-01 -4.07555252e-01 -1.83784008e-01 8.69422927e-02
4.39368516e-01 3.65208417e-01 -1.02816391e+00 -5.17122626e-01
8.31762731e-01 -1.12984610e+00 3.26969266e-01 -1.80209622e-01
8.27233374e-01 -1.23679675e-01 9.28123593e-02 -1.61112309e+00
-5.94024718e-01 -3.90871823e-01 6.01393819e-01 1.25227845e+00
7.94996917e-01 -8.95058155e-01 4.70568806e-01 1.20638311e+00
-1.29570723e-01 -7.30565131e-01 3.10652196e-01 -1.46111906e-01
1.74287245e-01 -2.25865424e-01 4.21394795e-01 8.91572833e-01
4.97364461e-01 5.21208227e-01 -3.13912451e-01 -4.21650589e-01
-1.39328778e-01 -4.17340547e-01 9.91549373e-01 -1.40029681e+00
-7.21780360e-02 -5.43061435e-01 5.25490679e-02 -6.44149840e-01
-3.64217013e-01 -2.49287605e-01 -3.02284241e-01 -1.93414688e+00
-4.08315323e-02 -6.19057953e-01 2.51756329e-02 -1.59684032e-01
-1.89678237e-01 2.56032735e-01 2.86765009e-01 4.04408574e-01
-2.37532750e-01 1.71185657e-02 1.32005847e+00 2.87649274e-01
-4.55913872e-01 4.42591272e-02 -1.74182427e+00 6.57176554e-01
9.36553776e-01 -1.48113683e-01 -7.19853878e-01 -3.65287602e-01
1.41119087e+00 -3.21883023e-01 -6.65098190e-01 -2.80512512e-01
1.80341259e-01 -2.81380981e-01 9.97987464e-02 -3.79196882e-01
1.25513241e-01 -7.84435213e-01 -2.05574129e-02 2.29644015e-01
-2.91701943e-01 8.24327469e-01 -1.03522614e-01 3.38448793e-01
-3.51520747e-01 -6.51015639e-01 3.39966685e-01 -1.43987373e-01
-4.55724031e-01 -4.21289295e-01 -8.28376174e-01 -2.34158963e-01
7.54552960e-01 -5.79540789e-01 -3.94933224e-01 -9.92148221e-01
-3.35874200e-01 6.44753799e-02 1.04848886e+00 6.89461231e-01
5.19262433e-01 -1.05765903e+00 -5.67360044e-01 -5.22512980e-02
2.29426175e-01 -7.42809534e-01 1.01736836e-01 9.73553002e-01
-7.07629919e-01 4.99379158e-01 -2.36438930e-01 5.47678620e-02
-1.33441520e+00 8.02009031e-02 -2.93220609e-01 -2.77051758e-02
-5.97975440e-02 7.18506336e-01 -3.55840214e-02 -2.58583069e-01
4.14996734e-03 -3.09470356e-01 -9.65604782e-01 7.85816252e-01
8.93578887e-01 6.75391555e-01 1.82269335e-01 -9.02723789e-01
-6.44012168e-02 7.00506508e-01 -5.48607171e-01 -2.74756134e-01
1.08740950e+00 -4.74548608e-01 -4.43813384e-01 8.41566205e-01
7.48194814e-01 6.81264341e-01 -5.42682111e-01 1.56392336e-01
-1.20300040e-01 -7.83433020e-01 -2.28543013e-01 -8.35613489e-01
-1.04499984e+00 6.07697725e-01 4.54376861e-02 6.12200201e-01
8.93111110e-01 -5.58317900e-01 4.63027716e-01 3.04915071e-01
3.76881450e-01 -1.78855062e+00 7.50208348e-02 5.44822514e-01
8.38636279e-01 -1.38028359e+00 3.55129749e-01 -4.78800356e-01
-1.35310805e+00 1.05866957e+00 4.55994248e-01 -1.06002480e-01
9.58402038e-01 -1.59634560e-01 6.37185812e-01 -2.46465318e-02
-8.12792003e-01 1.30512133e-01 3.29601884e-01 5.63101828e-01
1.24866068e+00 2.09939480e-01 -1.39046264e+00 7.15289712e-01
-1.45123735e-01 -2.75976181e-01 1.21004832e+00 1.01127636e+00
-6.90009177e-01 -1.59018219e+00 -4.10180449e-01 7.43552983e-01
-6.02918446e-01 -1.87028795e-01 -1.00589168e+00 6.47038281e-01
-2.30411917e-01 1.49902773e+00 -1.11600295e-01 -4.59073573e-01
-7.44160861e-02 -1.35908410e-01 -5.84942363e-02 -1.00353134e+00
-1.27173424e+00 1.76071927e-01 5.85807085e-01 9.88055840e-02
-6.61043584e-01 -7.88306773e-01 -1.08405626e+00 -6.19207025e-01
-6.75883472e-01 6.02742195e-01 1.30212915e+00 6.74847305e-01
4.24865246e-01 1.49681523e-01 5.82285762e-01 -4.71020341e-01
-3.15713882e-01 -1.02128029e+00 -9.70936894e-01 2.82683879e-01
-4.06186357e-02 -5.79338312e-01 -6.58390582e-01 -1.80949301e-01] | [10.946427345275879, 6.838450908660889] |
8df7743a-6e21-4a14-a406-897bbcc7ae83 | weakly-supervised-learning-of-rigid-3d-scene | 2102.08945 | null | https://arxiv.org/abs/2102.08945v1 | https://arxiv.org/pdf/2102.08945v1.pdf | Weakly Supervised Learning of Rigid 3D Scene Flow | We propose a data-driven scene flow estimation algorithm exploiting the observation that many 3D scenes can be explained by a collection of agents moving as rigid bodies. At the core of our method lies a deep architecture able to reason at the \textbf{object-level} by considering 3D scene flow in conjunction with other 3D tasks. This object level abstraction, enables us to relax the requirement for dense scene flow supervision with simpler binary background segmentation mask and ego-motion annotations. Our mild supervision requirements make our method well suited for recently released massive data collections for autonomous driving, which do not contain dense scene flow annotations. As output, our model provides low-level cues like pointwise flow and higher-level cues such as holistic scene understanding at the level of rigid objects. We further propose a test-time optimization refining the predicted rigid scene flow. We showcase the effectiveness and generalization capacity of our method on four different autonomous driving datasets. We release our source code and pre-trained models under \url{github.com/zgojcic/Rigid3DSceneFlow}. | ['Tolga Birdal', 'Leonidas J. Guibas', 'Andreas Wieser', 'Or Litany', 'Zan Gojcic'] | 2021-02-17 | null | http://openaccess.thecvf.com//content/CVPR2021/html/Gojcic_Weakly_Supervised_Learning_of_Rigid_3D_Scene_Flow_CVPR_2021_paper.html | http://openaccess.thecvf.com//content/CVPR2021/papers/Gojcic_Weakly_Supervised_Learning_of_Rigid_3D_Scene_Flow_CVPR_2021_paper.pdf | cvpr-2021-1 | ['scene-flow-estimation'] | ['computer-vision'] | [ 9.81834531e-03 2.17804372e-01 7.75638819e-02 -5.50088644e-01
-2.24909484e-01 -8.34025264e-01 9.40343738e-01 -2.79850550e-02
-3.31852049e-01 3.40237737e-01 2.77377129e-01 -3.81860703e-01
1.11121029e-01 -6.80682838e-01 -9.55827236e-01 -4.42938983e-01
-3.82147892e-03 6.39270961e-01 6.84354007e-01 -4.12239939e-01
3.22545856e-01 7.54141271e-01 -1.72763455e+00 1.21984072e-01
7.10502446e-01 7.06824183e-01 2.93019533e-01 1.11960781e+00
6.11160807e-02 1.20308340e+00 -1.42601371e-01 -3.41531396e-01
6.94652259e-01 -9.51836780e-02 -9.41962123e-01 3.46254975e-01
9.62870717e-01 -6.07892632e-01 -6.74985886e-01 8.62297952e-01
3.91219966e-02 4.38252568e-01 4.49434549e-01 -1.23733723e+00
-2.29275245e-02 2.30427813e-02 -3.44687760e-01 4.75757629e-01
2.58734763e-01 7.20068812e-01 8.50524485e-01 -7.66110003e-01
9.02630508e-01 1.35795450e+00 4.37617511e-01 5.57691276e-01
-1.15551138e+00 -1.91463321e-01 6.19348884e-01 2.58960187e-01
-8.71700823e-01 -7.57769227e-01 8.69752645e-01 -8.91319633e-01
1.09557366e+00 1.28062010e-01 6.09339416e-01 1.04405010e+00
1.81058869e-01 8.56026113e-01 7.57850885e-01 -2.76032910e-02
3.27857643e-01 -5.15092723e-02 2.02117771e-01 1.05776858e+00
3.09934705e-01 1.49038583e-01 -4.23135489e-01 3.91111106e-01
8.21714461e-01 -2.63800714e-02 -1.10282123e-01 -8.41488600e-01
-1.30891180e+00 7.41594672e-01 6.53431594e-01 -3.64736840e-02
-1.17461368e-01 3.95754695e-01 3.92608374e-01 -7.52120763e-02
5.62350035e-01 1.86091527e-01 -4.39201027e-01 -1.19982816e-01
-7.99623132e-01 6.49196625e-01 7.89298713e-01 1.13620985e+00
1.09381080e+00 1.59194335e-01 6.58861175e-02 1.16699956e-01
3.29217821e-01 4.87802148e-01 3.33191007e-02 -1.64355862e+00
5.83776951e-01 5.38135648e-01 2.27372572e-01 -9.00053263e-01
-5.15337706e-01 -3.29121649e-01 -5.04806936e-01 5.52488804e-01
6.47150397e-01 1.98743306e-02 -9.63724732e-01 1.66797531e+00
5.95425546e-01 3.21525961e-01 1.82769466e-02 1.28396952e+00
7.13574052e-01 4.78646070e-01 -1.21198252e-01 2.44390711e-01
1.15258622e+00 -1.30555880e+00 -3.28595012e-01 -5.38085938e-01
9.16773200e-01 -4.21187937e-01 1.03032577e+00 6.63962588e-02
-1.16717935e+00 -7.30997920e-01 -8.10409069e-01 -5.73838055e-01
-3.03055346e-01 -2.40340009e-01 8.70714009e-01 5.19601107e-01
-1.13772666e+00 4.36456561e-01 -1.29551125e+00 -4.75989848e-01
6.07553244e-01 1.11567818e-01 -3.95304203e-01 -2.75305547e-02
-6.50874138e-01 9.20857847e-01 2.17057392e-01 1.32224426e-01
-1.24111414e+00 -8.53263259e-01 -1.26306117e+00 -1.89442098e-01
3.17698687e-01 -1.20758188e+00 1.07939112e+00 -4.81597692e-01
-1.46551156e+00 1.17733431e+00 -4.52878505e-01 -6.35002792e-01
1.06831646e+00 -3.48390192e-01 2.07260564e-01 3.40199351e-01
2.02061594e-01 1.03607106e+00 4.96037811e-01 -1.29973626e+00
-6.76763713e-01 -3.62612039e-01 4.08009231e-01 2.59582758e-01
3.06612343e-01 -4.22032535e-01 -4.62080210e-01 -2.59530127e-01
-1.94323018e-01 -9.48402107e-01 -5.73109925e-01 1.24079406e-01
-4.19135988e-01 2.11613942e-02 9.24425483e-01 -3.43119591e-01
5.37562251e-01 -1.98891568e+00 2.94633061e-01 -1.63756177e-01
3.71533543e-01 -2.85070874e-02 -8.04063082e-02 4.31716219e-02
1.75695047e-01 -1.52554840e-01 -6.54713333e-01 -7.61342704e-01
1.70018882e-01 4.03064668e-01 -4.12417948e-01 7.45293498e-01
5.61307907e-01 9.63864267e-01 -8.39351237e-01 -3.68038982e-01
8.62463474e-01 4.88548309e-01 -1.07680738e+00 2.18994826e-01
-5.16280591e-01 8.35019171e-01 -5.83738208e-01 3.27351391e-01
6.82652056e-01 -2.40484416e-01 -4.04729664e-01 1.12552205e-02
-4.05341268e-01 4.29787546e-01 -1.16318834e+00 2.24018598e+00
-3.78827006e-01 9.17529106e-01 2.57970780e-01 -1.07875085e+00
6.68612480e-01 -2.69585788e-01 5.74503660e-01 -4.50944752e-01
2.53622532e-01 -5.35700191e-03 -1.60175711e-01 -6.59114838e-01
7.05187619e-01 1.83254868e-01 -7.23464787e-02 1.24909222e-01
1.20495006e-01 -6.72835827e-01 3.97055238e-01 3.76051426e-01
1.21512818e+00 6.98726237e-01 -1.37348369e-01 -6.58677161e-01
6.02354884e-01 4.66521025e-01 4.07637864e-01 7.26853609e-01
-4.70311165e-01 5.89994669e-01 3.69982630e-01 -8.41364980e-01
-1.21385455e+00 -8.64881575e-01 -8.12628567e-02 9.18752074e-01
6.10507071e-01 -3.46483827e-01 -7.54022717e-01 -5.12349904e-01
2.63810251e-02 6.23737335e-01 -6.91142619e-01 7.57514387e-02
-7.64500499e-01 -5.22151768e-01 2.48530746e-01 2.66688794e-01
4.90500629e-01 -8.55221927e-01 -1.09640110e+00 7.01492131e-02
-2.56184042e-01 -1.70814121e+00 -2.22990766e-01 1.73294678e-01
-8.40119004e-01 -1.08701420e+00 -2.95160055e-01 -3.92070115e-01
5.26846349e-01 3.82592380e-01 1.23894441e+00 -5.48149198e-02
-4.70490932e-01 4.79448676e-01 -1.19467184e-01 -2.09514424e-01
-3.63818526e-01 8.02750066e-02 3.55993994e-02 -3.06911208e-02
3.12493443e-01 -6.75658286e-01 -8.64186585e-01 2.12172985e-01
-7.94165373e-01 3.61726671e-01 1.30114272e-01 1.66310236e-01
3.45033318e-01 -2.65208453e-01 -2.36554027e-01 -6.78520262e-01
-1.70498326e-01 -2.79127657e-01 -9.69201326e-01 -3.99918258e-01
1.04020722e-01 1.85706928e-01 4.22505140e-01 9.76581499e-02
-1.13343501e+00 3.51741076e-01 -2.10471317e-01 -6.06745720e-01
-7.54231215e-01 -1.26907215e-01 -1.47437036e-01 2.65455917e-02
7.76990533e-01 -1.18803410e-02 -9.53715220e-02 -2.63560683e-01
6.83357596e-01 7.70057784e-03 6.82689667e-01 -6.44772947e-01
9.12303984e-01 1.16747987e+00 3.72947305e-01 -8.01214814e-01
-9.74396050e-01 -4.70866054e-01 -1.11817265e+00 -3.36471975e-01
1.31242144e+00 -1.15822148e+00 -9.72952783e-01 2.55320907e-01
-1.23912621e+00 -9.95649278e-01 -4.52132702e-01 4.39030677e-01
-1.06961024e+00 3.02233368e-01 -4.81889695e-01 -7.17517674e-01
1.61292687e-01 -1.37819195e+00 1.30997622e+00 -3.28463763e-02
-1.22003943e-01 -1.16872370e+00 5.97432330e-02 6.53099179e-01
2.15303361e-01 6.11673951e-01 5.59960902e-01 -2.81131744e-01
-1.13026810e+00 1.42693207e-01 -2.23224208e-01 -3.31274308e-02
-1.24334119e-01 1.50258884e-01 -1.24483323e+00 -2.68445592e-02
5.16460091e-03 -1.94537953e-01 1.26182806e+00 6.13211036e-01
1.05359375e+00 -3.14706564e-02 -2.45787784e-01 1.05132616e+00
1.36383498e+00 -3.24244827e-01 4.09133404e-01 3.90472889e-01
1.12722397e+00 1.00433040e+00 3.35384727e-01 3.29917908e-01
8.00372601e-01 6.33674920e-01 8.65009665e-01 -1.07072264e-01
-3.03024679e-01 -1.24918334e-01 4.22445178e-01 3.86919469e-01
-2.91623652e-01 -3.28594565e-01 -1.06885779e+00 6.21089637e-01
-1.98458791e+00 -1.25148499e+00 -5.31310380e-01 1.83848262e+00
2.23448619e-01 4.33472216e-01 2.57778138e-01 -1.57389939e-01
3.74472946e-01 2.98882931e-01 -7.37987280e-01 -2.49362037e-01
1.92354829e-03 -1.02896020e-01 6.46597385e-01 1.25849330e+00
-1.28895772e+00 1.32065272e+00 5.09108162e+00 2.24961281e-01
-9.65301931e-01 1.51800411e-02 6.58444226e-01 -2.21710101e-01
-3.93157780e-01 1.77107289e-01 -9.87632930e-01 1.59367546e-01
6.77315891e-01 1.51360244e-01 1.83688655e-01 7.14359522e-01
6.96698308e-01 -1.38437018e-01 -1.28202236e+00 7.57245898e-01
-7.74878263e-02 -1.48834527e+00 7.13695213e-02 2.42828056e-01
6.06671572e-01 6.24888718e-01 -1.56833857e-01 8.80217925e-02
5.98699212e-01 -7.71080256e-01 1.16621482e+00 4.99593467e-01
4.43717569e-01 -1.73863918e-01 2.72368759e-01 4.22695726e-01
-1.16493511e+00 -3.26130874e-02 -2.07529500e-01 -3.94821376e-01
4.35023278e-01 4.25543338e-01 -5.17557204e-01 5.67474723e-01
6.67941749e-01 1.13598478e+00 -5.77393115e-01 8.52475703e-01
-7.55959982e-03 2.53671616e-01 -5.38111567e-01 3.88931423e-01
5.01787782e-01 -3.36918712e-01 9.22064304e-01 1.45336568e+00
1.13914177e-01 9.31214541e-02 3.08759540e-01 1.10765564e+00
1.91562325e-01 -3.28214049e-01 -8.28920424e-01 5.33375978e-01
-1.19416654e-01 1.20888078e+00 -9.63405848e-01 -4.16163325e-01
-3.71540397e-01 8.15711856e-01 2.96266198e-01 4.80412900e-01
-8.36176038e-01 -7.48288771e-03 1.10073650e+00 3.73304844e-01
3.74631673e-01 -7.33657539e-01 -3.13692063e-01 -1.56711578e+00
9.36223418e-02 -2.38075152e-01 1.08946301e-01 -8.65782678e-01
-8.22214961e-01 3.55152398e-01 1.82403922e-02 -1.10976183e+00
-2.02864841e-01 -8.48967135e-01 -5.23163736e-01 6.67391658e-01
-1.79480040e+00 -1.11206365e+00 -6.68139458e-01 8.19462121e-01
8.73327434e-01 1.86022669e-01 2.98130989e-01 8.11448544e-02
-4.52499330e-01 -1.35142371e-01 -4.23095226e-01 2.11542603e-02
4.33481902e-01 -1.39101255e+00 6.67772353e-01 1.28590810e+00
6.67398572e-02 2.10496262e-01 9.17712271e-01 -3.80370140e-01
-1.35831821e+00 -1.24766922e+00 5.79456806e-01 -1.15660548e+00
7.02136099e-01 -7.84530282e-01 -7.00637221e-01 8.41822445e-01
1.37973279e-01 3.13841879e-01 1.50580585e-01 -2.86526769e-01
-2.26421267e-01 -4.40414660e-02 -8.76363099e-01 6.27961457e-01
1.56886911e+00 -3.45745623e-01 -4.57670480e-01 3.22457016e-01
9.30728793e-01 -6.41939461e-01 -5.57800293e-01 4.75296497e-01
1.84257135e-01 -1.28644836e+00 9.55244780e-01 -4.78540063e-01
7.07172453e-01 -5.44703126e-01 -1.73815876e-01 -8.79475415e-01
-1.09207943e-01 -8.35242689e-01 -2.14662150e-01 5.80155432e-01
2.68676966e-01 -3.74249697e-01 9.62607205e-01 8.88367534e-01
-7.34127581e-01 -1.34490699e-01 -7.63120532e-01 -4.92097110e-01
-1.30367614e-02 -8.44908416e-01 2.53463715e-01 8.98751438e-01
-4.48297262e-01 2.19617322e-01 -6.35922179e-02 4.13856059e-01
8.35536122e-01 1.58607483e-01 1.24939084e+00 -1.15096045e+00
-2.22755387e-01 -7.07113504e-01 -6.64481580e-01 -1.50514281e+00
3.17410111e-01 -9.56256568e-01 1.23512045e-01 -1.48785293e+00
-1.49501264e-01 -3.58202219e-01 2.58414030e-01 2.77006477e-01
6.21024109e-02 2.21145630e-01 3.68420273e-01 2.47273088e-01
-8.52542877e-01 6.33922398e-01 1.47457731e+00 -2.11608056e-02
-3.44497055e-01 -1.02895252e-01 -2.90758669e-01 9.11488235e-01
5.32379389e-01 -1.78253308e-01 -4.24991399e-01 -8.45205545e-01
6.39340207e-02 -4.25703637e-02 9.22975481e-01 -1.01994395e+00
2.59570450e-01 -2.73014367e-01 2.71936536e-01 -5.08696556e-01
5.58985770e-01 -8.01593363e-01 -1.72084764e-01 4.09022868e-01
-2.66879767e-01 -3.26856747e-02 3.99024338e-01 5.49121916e-01
1.74618941e-02 1.59281105e-01 6.78813636e-01 -4.12603468e-01
-9.41369236e-01 5.70538521e-01 -4.43167478e-01 1.59845069e-01
1.01890063e+00 -3.79860669e-01 -4.44498748e-01 -1.80066615e-01
-8.63386571e-01 3.48749816e-01 7.31739819e-01 6.15548193e-01
4.01384234e-01 -8.14852893e-01 -6.52909398e-01 2.54994273e-01
1.90806076e-01 7.07461774e-01 3.29404563e-01 7.96709478e-01
-9.89648461e-01 6.51080430e-01 -2.88759321e-01 -1.05245447e+00
-8.01434994e-01 4.29255188e-01 6.20799780e-01 3.23906317e-02
-1.00319636e+00 8.51350129e-01 7.56120682e-01 -5.28676152e-01
-5.52610233e-02 -7.40934432e-01 -4.39215545e-03 -3.58535469e-01
2.65403926e-01 2.16712058e-01 2.19619256e-02 -8.80730331e-01
-4.29569334e-01 7.01052248e-01 1.69031978e-01 -6.81949481e-02
1.39457357e+00 -4.40621823e-01 5.10858446e-02 3.38071674e-01
1.18349409e+00 -1.45476103e-01 -2.13614058e+00 2.39461716e-02
-1.78837121e-01 -5.56759417e-01 7.41770640e-02 -3.20380777e-01
-9.22216296e-01 1.15845335e+00 3.06793749e-01 1.05150983e-01
7.16640174e-01 1.52654201e-01 3.96121413e-01 4.37923640e-01
2.69524634e-01 -5.89283049e-01 -6.07558340e-02 7.49612331e-01
5.63320696e-01 -1.49349773e+00 -1.61811933e-01 -4.89374340e-01
-3.90091419e-01 1.01374578e+00 7.30709672e-01 -4.36823070e-01
4.71358061e-01 2.20316961e-01 2.40631644e-02 -3.18069756e-01
-8.70029807e-01 -5.63320696e-01 6.43464848e-02 5.43234468e-01
9.73870605e-03 -1.49590924e-01 4.28298026e-01 -1.13554269e-01
-4.82960016e-01 -2.66166657e-01 7.85498440e-01 7.73798943e-01
-4.89322037e-01 -6.85333669e-01 -3.27210538e-02 -1.60786584e-01
-1.24686547e-01 1.86763614e-01 -1.62596151e-01 8.05711985e-01
1.21492542e-01 8.33087921e-01 4.67628300e-01 -4.36967006e-03
4.67806339e-01 -1.72674030e-01 5.17840207e-01 -4.64822888e-01
-1.70605883e-01 -1.77725449e-01 -2.15335675e-02 -9.49951291e-01
-7.66785145e-01 -7.00816572e-01 -1.18633580e+00 -5.06829500e-01
3.32448870e-01 -1.90425277e-01 6.34065390e-01 1.04508448e+00
4.76834089e-01 4.55903053e-01 3.67657065e-01 -1.55923963e+00
2.47570574e-01 -6.01742446e-01 -5.10812066e-02 6.71634734e-01
8.66550326e-01 -7.01746762e-01 -4.42803204e-01 6.28071606e-01] | [8.52578353881836, -1.9497125148773193] |
ff47e1b2-3cbe-4fdb-9ec7-f531a12c3b22 | robust-benchmarking-for-machine-learning-of | 2007.16127 | null | https://arxiv.org/abs/2007.16127v1 | https://arxiv.org/pdf/2007.16127v1.pdf | Robust Benchmarking for Machine Learning of Clinical Entity Extraction | Clinical studies often require understanding elements of a patient's narrative that exist only in free text clinical notes. To transform notes into structured data for downstream use, these elements are commonly extracted and normalized to medical vocabularies. In this work, we audit the performance of and indicate areas of improvement for state-of-the-art systems. We find that high task accuracies for clinical entity normalization systems on the 2019 n2c2 Shared Task are misleading, and underlying performance is still brittle. Normalization accuracy is high for common concepts (95.3%), but much lower for concepts unseen in training data (69.3%). We demonstrate that current approaches are hindered in part by inconsistencies in medical vocabularies, limitations of existing labeling schemas, and narrow evaluation techniques. We reformulate the annotation framework for clinical entity extraction to factor in these issues to allow for robust end-to-end system benchmarking. We evaluate concordance of annotations from our new framework between two annotators and achieve a Jaccard similarity of 0.73 for entity recognition and an agreement of 0.83 for entity normalization. We propose a path forward to address the demonstrated need for the creation of a reference standard to spur method development in entity recognition and normalization. | ['David Sontag', "Chloe O'Connell", 'Yasmin Fatemi', 'Monica Agrawal', 'Ariel Levy'] | 2020-07-31 | null | null | null | null | ['entity-extraction'] | ['natural-language-processing'] | [ 3.44926447e-01 4.63463813e-01 -4.05589730e-01 -5.13955534e-01
-1.18195939e+00 -8.81156862e-01 2.58863389e-01 1.21188474e+00
-7.73147702e-01 8.89288247e-01 7.05061018e-01 -3.35879236e-01
-3.43711376e-01 -3.36463839e-01 -1.18525147e-01 -2.51529187e-01
1.77046135e-01 5.90427816e-01 -1.66526154e-01 -7.49819651e-02
-1.50658891e-01 3.04876536e-01 -8.26336682e-01 6.03761196e-01
6.99549735e-01 5.47936082e-01 -5.01263022e-01 6.42503500e-01
-1.27936766e-01 8.45755398e-01 -7.56683230e-01 -5.73686123e-01
8.81140828e-02 -3.05597514e-01 -9.94736373e-01 -4.47971046e-01
3.01801682e-01 -1.26698196e-01 -8.76494776e-03 9.46268380e-01
7.28191435e-01 -2.70179510e-01 8.08083892e-01 -9.38420951e-01
-6.86944127e-01 7.92785466e-01 1.85899641e-02 1.50562704e-01
4.04864490e-01 3.68239060e-02 9.89535391e-01 -5.70691705e-01
1.31975543e+00 3.81857157e-01 1.12229943e+00 7.54413724e-01
-1.15200078e+00 -7.56982982e-01 -3.04623485e-01 -3.28148305e-01
-1.60998297e+00 -7.32753694e-01 -2.33437434e-01 -8.03250253e-01
1.28785944e+00 4.36895519e-01 4.87991393e-01 6.02941632e-01
2.56747484e-01 1.40172780e-01 6.08962536e-01 -4.26864535e-01
6.36406094e-02 2.99134463e-01 3.01134139e-01 5.12814343e-01
9.67943966e-01 -3.87437373e-01 -2.59292513e-01 -6.14008129e-01
2.39096478e-01 -1.28662899e-01 -3.58609349e-01 -1.10376097e-01
-1.35435796e+00 4.60836381e-01 1.89364865e-01 5.47914386e-01
-3.73384327e-01 -2.96179593e-01 7.63665617e-01 6.44598901e-02
1.87117174e-01 1.11475766e+00 -6.07516468e-01 -1.81075111e-01
-1.16062093e+00 2.08531946e-01 1.08931506e+00 1.13116193e+00
-2.34769043e-02 -5.97344935e-01 -2.78116554e-01 7.28198588e-01
8.97055045e-02 9.47664082e-02 6.09581351e-01 -8.64309132e-01
4.36018914e-01 7.49986947e-01 2.17710331e-01 -6.31828845e-01
-8.67367148e-01 -3.95085007e-01 -6.61796987e-01 -2.60877222e-01
4.74426270e-01 -1.85577005e-01 -1.01438999e+00 1.68089652e+00
2.60059685e-01 -4.08449322e-01 5.40503263e-01 4.37553227e-01
1.26903665e+00 -1.21775195e-01 7.84393728e-01 -2.74192065e-01
1.69591951e+00 -3.94209415e-01 -1.17836988e+00 1.49973363e-01
1.43667042e+00 -1.00758457e+00 3.72684538e-01 4.25516479e-02
-9.63434100e-01 3.16951722e-02 -9.83102262e-01 -2.27427140e-01
-4.98236388e-01 5.99407330e-02 3.16290140e-01 9.03825164e-01
-7.75558472e-01 4.77339447e-01 -1.07000911e+00 -6.73577726e-01
6.62801683e-01 5.54194570e-01 -8.91702890e-01 8.54560286e-02
-1.08132493e+00 1.18375063e+00 6.40960515e-01 -1.51623592e-01
-1.47228092e-01 -1.24258757e+00 -8.80058467e-01 -1.23804301e-01
1.27705902e-01 -8.49623561e-01 1.35645473e+00 -2.33934283e-01
-5.33846021e-01 1.17243421e+00 8.16072226e-02 -3.58204067e-01
3.51273984e-01 9.22954530e-02 -7.44567275e-01 9.75127816e-02
5.09156525e-01 4.63986844e-01 -3.67128253e-01 -7.77169824e-01
-8.01875293e-01 -1.97487667e-01 -3.18578422e-01 1.57448590e-01
-3.26216310e-01 3.07112068e-01 -3.88833463e-01 -5.69694877e-01
5.79986461e-02 -9.04154181e-01 -4.32997078e-01 -1.36517316e-01
-2.68558681e-01 3.30982618e-02 1.49907187e-01 -9.16384041e-01
1.66039896e+00 -1.94734561e+00 -5.67292154e-01 2.03548819e-01
6.77841127e-01 3.71246457e-01 2.36275628e-01 4.62502927e-01
-4.09463733e-01 6.61268353e-01 -1.49268776e-01 -1.82274446e-01
-2.27397650e-01 2.61548702e-02 2.00468544e-02 4.71453577e-01
2.42979273e-01 1.02195179e+00 -9.25669193e-01 -6.43226206e-01
-1.76220685e-01 4.18786973e-01 -7.53480792e-01 3.51643451e-02
2.04805106e-01 1.86083928e-01 -2.82711267e-01 8.86205912e-01
2.89941341e-01 -4.92404550e-01 5.17775893e-01 -3.69418681e-01
-1.05610900e-02 5.72033942e-01 -1.16093469e+00 1.67511165e+00
1.56874284e-01 2.46806756e-01 1.39703289e-01 -3.04389685e-01
6.62041903e-01 8.36851060e-01 9.81554925e-01 -1.66856691e-01
2.36697689e-01 3.98541898e-01 2.15452373e-01 -7.31758296e-01
6.18742466e-01 -3.89553249e-01 -1.91520303e-01 2.09959269e-01
1.60377711e-01 -8.33917186e-02 3.43541771e-01 2.98648804e-01
1.44478881e+00 -3.51159424e-01 1.09183633e+00 -3.91377538e-01
2.79136151e-01 4.99567688e-01 6.94695473e-01 6.07702851e-01
-4.55438823e-01 8.09418619e-01 4.83310878e-01 -3.37904483e-01
-1.07045579e+00 -7.14701891e-01 -6.28412902e-01 5.49416065e-01
-4.75188702e-01 -1.17831516e+00 -6.36214435e-01 -7.00510204e-01
-4.60765278e-03 5.45495510e-01 -8.67042780e-01 -7.87836537e-02
-3.39635938e-01 -1.13929915e+00 1.31040144e+00 7.47924089e-01
-3.41155887e-01 -6.87257528e-01 -6.96972251e-01 5.97928047e-01
-2.02704027e-01 -1.40483379e+00 -5.12466550e-01 2.38721400e-01
-6.74753487e-01 -1.39874029e+00 -5.68116903e-01 -6.04880869e-01
7.07177579e-01 -5.17031014e-01 1.22482812e+00 1.30798221e-01
-5.39828718e-01 4.73847002e-01 -3.42970967e-01 -7.32805789e-01
-6.68681085e-01 3.78089786e-01 -2.00106837e-02 -7.96355128e-01
9.06432986e-01 1.33256525e-01 -6.46298885e-01 1.75827265e-01
-1.13494802e+00 -2.17229456e-01 5.29688358e-01 7.80641317e-01
7.07082152e-01 -5.48229873e-01 6.55144036e-01 -1.41350234e+00
8.16146970e-01 -4.99524325e-01 -1.63097680e-01 4.83158618e-01
-1.20009208e+00 -4.80098128e-02 2.89552361e-01 -1.59062222e-01
-6.90730631e-01 1.85421199e-01 -2.36668274e-01 3.52113284e-02
-2.16648400e-01 7.60861874e-01 2.18908980e-01 2.68710583e-01
1.04549694e+00 -5.45851409e-01 -2.28230115e-02 -2.62463093e-01
1.75487399e-01 8.65501106e-01 6.14923656e-01 -4.96943295e-01
3.12627435e-01 2.38408804e-01 -1.97574973e-01 -3.39971334e-01
-8.43405366e-01 -8.67733896e-01 -7.61302412e-01 3.77373576e-01
1.16495264e+00 -1.16314280e+00 -4.81828451e-01 -1.80669740e-01
-9.18800235e-01 -9.72305145e-03 -6.67834222e-01 7.20950484e-01
-7.61305168e-02 8.98927078e-02 -6.13384306e-01 -3.22965115e-01
-7.79583395e-01 -1.07531929e+00 9.94997323e-01 1.09910659e-01
-1.12209940e+00 -9.33475614e-01 6.01852417e-01 4.90236133e-01
3.00898522e-01 4.65356976e-01 8.13312411e-01 -1.49723959e+00
7.17793852e-02 -6.87284827e-01 -2.60416836e-01 -3.05597745e-02
5.41595519e-01 5.08507267e-02 -8.48025978e-01 -1.67288736e-01
-2.84917742e-01 -1.41918942e-01 2.75722653e-01 9.19352993e-02
6.44240379e-01 -2.21576139e-01 -6.20747387e-01 5.78118801e-01
1.30899608e+00 3.16717178e-01 4.16060597e-01 4.52627897e-01
6.48026109e-01 6.29600883e-01 3.92935991e-01 2.25767717e-01
5.31156659e-01 3.90859932e-01 -2.70386815e-01 -1.87294915e-01
-1.00234002e-01 3.98554653e-02 -2.64407218e-01 8.69399548e-01
-3.42826843e-02 -6.00916967e-02 -1.50165737e+00 7.95954347e-01
-1.48168707e+00 -6.46527112e-01 -2.31832653e-01 1.94463575e+00
1.29203796e+00 1.27887845e-01 -1.68944687e-01 -2.11793453e-01
4.56080645e-01 -4.14409876e-01 -2.48167396e-01 -2.56131262e-01
-1.04727454e-01 4.42411035e-01 7.73248196e-01 3.75178277e-01
-9.62537467e-01 6.20001554e-01 7.09052563e+00 2.27999255e-01
-7.57790089e-01 1.51923805e-01 4.25596625e-01 -2.46728018e-01
2.85715610e-02 -1.37488544e-01 -1.08522666e+00 1.09057575e-01
1.17992651e+00 -5.10601342e-01 -3.82268190e-01 6.75137699e-01
-6.29296079e-02 3.13544929e-01 -1.34885728e+00 8.32721233e-01
1.50958374e-01 -1.61784101e+00 -2.90441513e-01 1.63855106e-01
7.31037199e-01 2.18293503e-01 -3.14506829e-01 3.29916388e-01
3.21300209e-01 -1.25716937e+00 2.08054319e-01 4.13324207e-01
1.15879178e+00 -2.28576288e-01 1.31194663e+00 -3.35764319e-01
-1.17644584e+00 2.83962429e-01 -7.40268035e-03 4.80152428e-01
1.87890276e-01 3.88703734e-01 -1.62704515e+00 6.14089251e-01
5.34474790e-01 6.70279622e-01 -6.47920907e-01 1.16191494e+00
2.25664854e-01 3.07199836e-01 -3.05586427e-01 2.29499862e-01
8.85587782e-02 4.03342813e-01 1.94606632e-01 1.71858871e+00
1.32836774e-01 5.74363589e-01 5.11487462e-02 4.91265655e-01
-4.50851798e-01 7.55051494e-01 -5.17870247e-01 -2.95147300e-01
5.57208121e-01 1.34534407e+00 -8.36866856e-01 -5.85424662e-01
-4.50924397e-01 3.39918405e-01 5.86266369e-02 -2.61027515e-02
-5.92363536e-01 -4.93572772e-01 6.32396758e-01 8.97393897e-02
-7.09247950e-04 2.57441819e-01 -4.70911503e-01 -1.19710064e+00
-3.49245369e-02 -1.15011108e+00 9.72096980e-01 -5.13246000e-01
-1.28703415e+00 6.70664370e-01 -4.17947918e-02 -1.26690423e+00
-2.85552859e-01 -6.34701133e-01 2.76088379e-02 8.88323605e-01
-1.16608024e+00 -9.59644616e-01 -2.59653062e-01 3.29665631e-01
-1.34987265e-01 -7.51995221e-02 1.45682299e+00 6.80755198e-01
-3.94985259e-01 1.02679074e+00 1.23281702e-01 6.89498663e-01
1.41976261e+00 -1.23585844e+00 3.13243628e-01 4.51430738e-01
-1.37802482e-01 1.17205739e+00 5.72657764e-01 -9.78215635e-01
-8.03336143e-01 -1.11106682e+00 1.25697958e+00 -1.14420021e+00
7.05763519e-01 -7.85205662e-02 -1.10655403e+00 8.87781024e-01
1.58216078e-02 3.45593179e-03 1.75681221e+00 2.04110563e-01
-5.46198964e-01 3.06416988e-01 -1.30238605e+00 4.33165103e-01
7.46173263e-01 -5.60960174e-01 -9.12750125e-01 3.10166329e-01
4.89655882e-01 -6.87653303e-01 -1.77339876e+00 5.47640264e-01
8.23370993e-01 -2.03795061e-01 7.71319926e-01 -1.16573179e+00
5.16715422e-02 -3.16518813e-01 -2.07365781e-01 -8.31655622e-01
-1.96064577e-01 -4.30053473e-01 2.79446095e-01 1.24120295e+00
9.05916095e-01 -4.95325387e-01 7.79853821e-01 1.40326464e+00
-1.90978006e-01 -5.18580019e-01 -7.51197517e-01 -2.75271446e-01
2.02521697e-01 -2.54474759e-01 5.34825623e-01 1.47686183e+00
5.79862535e-01 3.31999391e-01 2.37688273e-01 1.39270052e-01
1.82229280e-01 -4.07770365e-01 5.29792190e-01 -1.32861269e+00
1.71648100e-01 -4.44042146e-01 -6.65950298e-01 -5.30417776e-03
-2.13372618e-01 -1.22047114e+00 -1.88961908e-01 -1.70871019e+00
4.76508111e-01 -6.60318136e-01 -5.15590727e-01 8.85696530e-01
-2.96481967e-01 3.54604572e-01 2.96851378e-02 4.72736359e-01
-7.06551194e-01 -1.54316023e-01 6.88927889e-01 6.89837616e-03
-4.35519874e-01 -5.05236387e-01 -1.17535520e+00 5.96257985e-01
6.90479100e-01 -1.07772553e+00 -1.07297502e-01 -1.92426771e-01
2.96300322e-01 -1.88018426e-01 -1.80114925e-01 -8.96911740e-01
5.17724395e-01 -5.56569025e-02 4.32896942e-01 -3.80652517e-01
-1.64309964e-01 -8.10887396e-01 3.87632132e-01 5.30392706e-01
-6.18716061e-01 2.24543467e-01 5.02905130e-01 1.66843712e-01
-1.38062373e-01 -2.95679897e-01 5.51871300e-01 -7.93670565e-02
-1.10966980e-01 -1.82433203e-02 -2.92313188e-01 5.19554615e-01
8.96038830e-01 -1.05752632e-01 -5.31729460e-01 9.81233045e-02
-1.10249269e+00 3.16056341e-01 6.12306654e-01 2.55552202e-01
1.73870083e-02 -1.04580867e+00 -8.12874436e-01 -1.52465194e-01
6.25606656e-01 -1.83354169e-02 1.03534624e-01 1.02425051e+00
-7.71867275e-01 7.58513212e-01 -1.98223352e-01 -4.27747697e-01
-1.59099376e+00 3.37845504e-01 4.71141756e-01 -6.78583562e-01
-5.48844814e-01 5.08815348e-01 -4.24307697e-02 -5.94842553e-01
1.23805441e-01 -6.94088876e-01 -3.31840813e-01 3.78041714e-01
6.99036002e-01 -2.47333329e-02 6.79060221e-01 -5.82302868e-01
-7.41874933e-01 2.41533265e-01 -4.80404437e-01 3.08488440e-02
1.44259715e+00 2.65743494e-01 -9.73129421e-02 1.59393102e-01
1.01691973e+00 3.86723608e-01 -2.59300232e-01 -1.71253681e-02
2.84563541e-01 9.03564617e-02 -2.49494910e-01 -1.11807692e+00
-6.14297390e-01 2.11703345e-01 6.59564853e-01 3.17345895e-02
8.63480210e-01 -3.21810786e-03 3.94421846e-01 4.71804738e-01
-1.89780340e-01 -1.03913248e+00 -8.02852750e-01 3.27837527e-01
3.46786827e-01 -1.20303130e+00 5.85844874e-01 -3.48215938e-01
-6.43042326e-01 1.02201438e+00 2.09362760e-01 4.37337339e-01
7.05584764e-01 6.56835496e-01 4.61398244e-01 -5.43671131e-01
-6.79164231e-01 8.35628062e-02 4.89677936e-01 4.65833455e-01
1.09358799e+00 5.46709634e-02 -6.70796216e-01 1.10600078e+00
-3.45645219e-01 3.67721468e-01 5.78729391e-01 1.20569921e+00
1.44960687e-01 -1.26587939e+00 -2.90750831e-01 7.97809184e-01
-1.20927238e+00 -3.35445583e-01 -3.09655577e-01 1.00674045e+00
3.19496155e-01 6.86765373e-01 -1.03819892e-01 -1.19860834e-02
7.62007415e-01 4.76343215e-01 1.73915431e-01 -1.03148639e+00
-1.12417114e+00 6.37257770e-02 4.57676291e-01 -3.36954266e-01
-6.32201731e-01 -9.06489789e-01 -1.38576329e+00 1.48254275e-01
-3.73550326e-01 4.26684231e-01 5.91447234e-01 7.66134858e-01
6.07024550e-01 7.00508475e-01 -4.68878359e-01 1.50904000e-01
-3.46177489e-01 -8.16947699e-01 -1.09910965e-01 6.38367474e-01
2.85582215e-01 -3.44025522e-01 -2.67350618e-02 6.06375873e-01] | [8.414449691772461, 8.663819313049316] |
e2b511d8-15b4-4ed6-bfa9-3849bc08d053 | interactive-image-manipulation-with-complex | 2211.15352 | null | https://arxiv.org/abs/2211.15352v1 | https://arxiv.org/pdf/2211.15352v1.pdf | Interactive Image Manipulation with Complex Text Instructions | Recently, text-guided image manipulation has received increasing attention in the research field of multimedia processing and computer vision due to its high flexibility and controllability. Its goal is to semantically manipulate parts of an input reference image according to the text descriptions. However, most of the existing works have the following problems: (1) text-irrelevant content cannot always be maintained but randomly changed, (2) the performance of image manipulation still needs to be further improved, (3) only can manipulate descriptive attributes. To solve these problems, we propose a novel image manipulation method that interactively edits an image using complex text instructions. It allows users to not only improve the accuracy of image manipulation but also achieve complex tasks such as enlarging, dwindling, or removing objects and replacing the background with the input image. To make these tasks possible, we apply three strategies. First, the given image is divided into text-relevant content and text-irrelevant content. Only the text-relevant content is manipulated and the text-irrelevant content can be maintained. Second, a super-resolution method is used to enlarge the manipulation region to further improve the operability and to help manipulate the object itself. Third, a user interface is introduced for editing the segmentation map interactively to re-modify the generated image according to the user's desires. Extensive experiments on the Caltech-UCSD Birds-200-2011 (CUB) dataset and Microsoft Common Objects in Context (MS COCO) datasets demonstrate our proposed method can enable interactive, flexible, and accurate image manipulation in real-time. Through qualitative and quantitative evaluations, we show that the proposed model outperforms other state-of-the-art methods. | ['Jinjia Zhou', 'Man M. Ho', 'Zhiqiang Zhang', 'Ryugo Morita'] | 2022-11-25 | null | null | null | null | ['image-manipulation'] | ['computer-vision'] | [ 7.44108379e-01 -2.04310209e-01 8.68135393e-02 -2.20021904e-01
-1.06451577e-02 -5.89435279e-01 3.25596303e-01 -1.21475615e-01
-6.13123000e-01 3.39848459e-01 -2.98339069e-01 -7.30546638e-02
-1.41247511e-01 -8.54340136e-01 -6.72101021e-01 -7.33986795e-01
3.52679431e-01 2.60848701e-01 8.08663666e-01 -4.42290187e-01
5.65890610e-01 5.78617394e-01 -1.88981497e+00 1.12809122e-01
1.14320505e+00 7.76618481e-01 9.46617007e-01 3.04669827e-01
-2.62877584e-01 2.63272583e-01 -4.77752358e-01 -5.49599640e-02
3.61836255e-01 -2.61405587e-01 -6.01171196e-01 5.71806848e-01
2.80103534e-01 -5.14452517e-01 -2.34351447e-03 1.46018016e+00
3.81029278e-01 2.95656353e-01 4.74443644e-01 -1.23017037e+00
-7.53560662e-01 5.50827563e-01 -7.94498563e-01 4.49068025e-02
2.00227261e-01 3.25553179e-01 3.51204723e-01 -6.44718826e-01
7.86362529e-01 1.34301519e+00 -7.55112171e-02 4.62637514e-01
-1.11968505e+00 -7.64823794e-01 5.50484538e-01 9.30970088e-02
-1.33860731e+00 -1.25342920e-01 8.46993029e-01 -3.61072212e-01
4.68895048e-01 5.11754930e-01 6.34623289e-01 5.59297085e-01
1.40747637e-01 5.94049692e-01 9.15258586e-01 -4.95665252e-01
2.11015791e-02 2.12624803e-01 -1.73860520e-01 7.93111026e-01
-3.75915901e-03 4.78568263e-02 -7.28374347e-02 3.30821097e-01
1.06564867e+00 8.34936351e-02 -5.28442979e-01 -5.01004994e-01
-1.56083989e+00 3.73013467e-01 3.95298958e-01 4.60834354e-01
-1.90925628e-01 -8.56643319e-02 3.33605021e-01 3.71291675e-02
1.64376855e-01 4.66763049e-01 -4.19682503e-01 4.24089395e-02
-7.70918190e-01 3.03958625e-01 2.83569276e-01 1.22844899e+00
7.58788884e-01 4.72541042e-02 -3.23992044e-01 7.88360775e-01
8.97467658e-02 5.31370819e-01 5.51165164e-01 -1.03382564e+00
5.73823035e-01 7.42561698e-01 3.48920196e-01 -1.31723309e+00
-1.79681137e-01 -6.24823645e-02 -9.10203755e-01 6.13682806e-01
3.62758517e-01 -9.72706417e-04 -1.15622866e+00 1.54576433e+00
5.41376114e-01 -9.59011540e-02 -2.95149803e-01 1.05469978e+00
8.32505465e-01 6.77746832e-01 1.06331557e-01 -2.83903062e-01
1.34750342e+00 -9.85494018e-01 -9.52052832e-01 -1.35708660e-01
2.23208040e-01 -7.63763249e-01 1.43035638e+00 2.86999196e-01
-1.25126851e+00 -7.37869084e-01 -9.74305749e-01 -1.30177483e-01
-5.62517703e-01 2.76718765e-01 2.38162100e-01 3.85412991e-01
-6.47185981e-01 3.41787398e-01 -6.03405833e-01 -2.01196834e-01
3.29529285e-01 3.44773829e-01 -2.95110852e-01 3.47303003e-02
-1.03430307e+00 5.61445892e-01 8.33662868e-01 1.18535951e-01
-4.61050361e-01 -6.38875425e-01 -7.67866969e-01 9.39505324e-02
7.28944600e-01 -5.39695919e-01 8.53872955e-01 -1.25920308e+00
-1.68836832e+00 7.54536152e-01 9.07524303e-02 8.98220092e-02
7.53650248e-01 -2.61077378e-02 -1.89704359e-01 2.79081464e-01
1.19280286e-01 9.52784121e-01 9.92182493e-01 -1.38198245e+00
-9.09002841e-01 -3.87030572e-01 1.96172237e-01 4.69512850e-01
-2.68601090e-01 -2.61590108e-02 -1.14921308e+00 -1.13428271e+00
2.94193983e-01 -9.21893120e-01 -2.99272865e-01 4.22257096e-01
-5.98403871e-01 1.15053117e-01 1.31652021e+00 -4.62590426e-01
1.24790132e+00 -2.33880997e+00 3.62105340e-01 1.39952675e-01
-5.01510128e-02 5.34515262e-01 -2.48380139e-01 -1.37770362e-02
-1.22767361e-02 4.15093094e-01 -4.08716798e-01 -7.74729252e-02
-3.27974558e-01 1.25505492e-01 -4.14777137e-02 1.23589009e-01
-1.75709262e-01 7.71021247e-01 -7.48485327e-01 -7.61719823e-01
8.13776374e-01 3.24495375e-01 -5.29001355e-01 -4.15872410e-03
-4.10876632e-01 6.60078704e-01 -5.78663170e-01 6.18679166e-01
8.74864817e-01 1.58130422e-01 -1.91259250e-01 -6.48452461e-01
-2.85688162e-01 -5.64227402e-01 -1.48990452e+00 1.47268152e+00
-2.20438853e-01 3.97959530e-01 2.91129529e-01 -8.16443026e-01
6.76606596e-01 -8.99765864e-02 3.76800001e-01 -7.89978862e-01
2.90027291e-01 -1.67818621e-01 -8.14351588e-02 -8.87013972e-01
5.89581013e-01 3.07159603e-01 1.34891391e-01 4.09045190e-01
-6.04017675e-01 -4.07980174e-01 4.15338576e-01 5.90830632e-02
3.01481485e-01 2.39577353e-01 2.69521028e-01 -2.19813555e-01
8.20764005e-01 6.76742196e-02 4.84278411e-01 6.76973224e-01
-7.25513771e-02 5.55680931e-01 1.74664259e-01 -1.46845132e-01
-7.76073515e-01 -8.61131728e-01 -8.80566984e-02 1.11306143e+00
8.65815997e-01 -3.74374837e-02 -1.04444468e+00 -6.23107553e-01
-1.56901017e-01 8.09065044e-01 -4.73269284e-01 6.99205771e-02
-7.19413161e-01 -4.21079695e-01 6.01528622e-02 4.49656636e-01
1.12528062e+00 -1.42483699e+00 -9.69616711e-01 4.85286042e-02
-3.98488224e-01 -1.00268769e+00 -8.30189168e-01 -3.20714235e-01
-7.97856033e-01 -9.07411814e-01 -5.85384965e-01 -1.01546597e+00
1.15813768e+00 6.04673028e-01 5.07680535e-01 3.52189064e-01
-4.94696587e-01 1.98037490e-01 -3.77202481e-01 -2.42657200e-01
-3.58532727e-01 -1.36019766e-01 -3.72519046e-01 6.56439364e-02
-2.76700884e-01 -2.65429229e-01 -5.74442267e-01 8.21107566e-01
-1.44741440e+00 4.92962390e-01 5.23471951e-01 6.00380182e-01
8.66177380e-01 6.29093289e-01 3.96594048e-01 -9.16040421e-01
4.61007327e-01 1.88983381e-01 -7.01142788e-01 3.26154023e-01
-2.95888424e-01 -1.00137098e-02 5.91732860e-01 -8.87500167e-01
-1.32143044e+00 1.78170100e-01 1.42323717e-01 -3.39706659e-01
-1.68240383e-01 3.11369330e-01 -5.94307423e-01 -1.52996719e-01
3.24845850e-01 2.83661574e-01 9.45931822e-02 -2.10399583e-01
5.91818035e-01 7.07050085e-01 6.76606774e-01 -4.66155857e-01
9.38298285e-01 5.09499073e-01 -1.31370336e-01 -7.72443235e-01
-3.89958948e-01 -4.12115976e-02 -8.78195107e-01 -3.85918975e-01
1.05825102e+00 -4.37789738e-01 -6.66046023e-01 6.62090182e-01
-8.67307663e-01 -3.89280438e-01 -1.59836058e-02 1.61108539e-01
-3.87010902e-01 5.09751022e-01 -2.69747615e-01 -4.12389457e-01
-2.94360071e-01 -1.58597445e+00 1.07896829e+00 4.33735937e-01
1.00228295e-01 -6.92422450e-01 -8.38815928e-01 3.28991354e-01
4.66108263e-01 4.98444855e-01 1.13248670e+00 -1.36591559e-02
-8.14623058e-01 -6.95124567e-02 -3.31385076e-01 1.76065922e-01
5.27841985e-01 2.67215580e-01 -2.29580864e-01 -1.79890841e-01
-2.78496146e-01 8.64901692e-02 5.04972696e-01 2.08224401e-01
1.71073425e+00 -3.98620069e-01 -5.28424025e-01 6.07931435e-01
1.19283020e+00 5.39744377e-01 7.93681145e-01 5.11220217e-01
6.65549219e-01 6.29621446e-01 1.14777434e+00 2.33893722e-01
1.15703449e-01 8.90447438e-01 5.56362629e-01 -1.36938274e-01
4.88088280e-03 -7.46395364e-02 -4.14689220e-02 3.01791459e-01
-8.07496533e-02 -3.06162268e-01 -4.98626709e-01 2.67325640e-01
-1.83598053e+00 -9.04680133e-01 -2.36374930e-01 2.16611338e+00
8.14070940e-01 1.40029311e-01 -2.76839614e-01 4.59438637e-02
9.27637637e-01 2.34724898e-02 -6.62324011e-01 -7.45989159e-02
2.02624783e-01 -1.79080635e-01 3.66010249e-01 3.67637128e-01
-1.14073753e+00 1.17611825e+00 5.20169497e+00 1.01406479e+00
-1.45000446e+00 -2.24593982e-01 5.10454357e-01 1.21504450e-02
-6.22231774e-02 -2.95794100e-01 -6.14475727e-01 5.98478258e-01
-1.48472369e-01 -3.30380887e-01 6.60516500e-01 6.67317986e-01
5.12714505e-01 -5.02366006e-01 -9.22329366e-01 1.04498613e+00
5.27343750e-02 -1.05116391e+00 5.02409518e-01 -3.07967782e-01
7.15765297e-01 -7.45368242e-01 2.97662139e-01 1.69838056e-01
-2.80049771e-01 -7.33271241e-01 9.38821793e-01 5.69268525e-01
9.39929545e-01 -8.24064255e-01 3.21718961e-01 6.35848761e-01
-1.23299193e+00 -7.91562349e-02 -3.34144771e-01 3.62804949e-01
1.90404266e-01 3.38821858e-01 -4.49466169e-01 4.47749406e-01
8.10257435e-01 3.98110747e-01 -8.20470750e-01 8.63738894e-01
-1.36488304e-01 4.77968454e-02 -3.27659518e-01 9.24401656e-02
3.06947902e-02 -3.93812120e-01 6.74281955e-01 1.03119004e+00
2.21754998e-01 4.23566490e-01 2.70813286e-01 1.09550548e+00
-6.27027533e-04 3.21719706e-01 -3.79775107e-01 9.06045884e-02
4.69301194e-01 1.25532174e+00 -1.02139544e+00 -4.85038489e-01
-5.75463921e-02 1.22686529e+00 -3.71691473e-02 5.90315223e-01
-1.05738091e+00 -7.57590950e-01 6.97379932e-02 2.89585978e-01
4.53781396e-01 -2.45208338e-01 -1.77526087e-01 -9.09421325e-01
9.21323746e-02 -9.02975917e-01 1.10392747e-02 -1.13712764e+00
-7.03959465e-01 5.53444088e-01 3.86239976e-01 -1.33004451e+00
5.28697409e-02 -3.39739859e-01 -4.14128393e-01 7.21807718e-01
-1.19886911e+00 -1.00381708e+00 -8.57252955e-01 6.55174971e-01
8.76898706e-01 8.61035436e-02 2.84479797e-01 2.97018290e-01
-5.61448634e-01 4.41049546e-01 -1.31616563e-01 1.10382169e-01
6.51796520e-01 -8.93067300e-01 -8.75065997e-02 7.91096509e-01
-2.93560535e-01 5.56755066e-01 6.74292803e-01 -7.48664320e-01
-1.13009584e+00 -1.35437882e+00 2.56058455e-01 -5.63554317e-02
1.30772352e-01 -2.60525972e-01 -9.72601831e-01 6.38004541e-01
1.20798074e-01 7.35136569e-02 -8.91742557e-02 -8.47612619e-01
1.72275513e-01 -2.13418826e-01 -1.38351226e+00 1.08743691e+00
1.00967777e+00 -2.99330652e-02 -4.20826375e-01 1.96669772e-01
7.12232053e-01 -7.40061104e-01 -4.14496034e-01 6.96544647e-01
5.51283836e-01 -9.66387212e-01 1.04235101e+00 -1.29468217e-01
3.54949087e-01 -7.91775882e-01 2.78886426e-02 -1.13867807e+00
-1.39741585e-01 -3.68581414e-01 4.09866959e-01 1.29466641e+00
2.14302577e-02 -4.81098592e-01 4.24923807e-01 7.88812459e-01
1.37574628e-01 -7.29030550e-01 -5.60633421e-01 -5.60169220e-01
-2.22675815e-01 -1.72023714e-01 6.65778995e-01 8.42729986e-01
-3.06541890e-01 -1.60436958e-01 -9.70498025e-02 2.87723809e-01
4.74742949e-01 1.47224694e-01 8.73000741e-01 -9.11363125e-01
4.17335853e-02 -5.66247463e-01 -2.98988253e-01 -1.21481395e+00
-8.47053155e-02 -5.28520048e-01 1.28237993e-01 -1.56547272e+00
1.20105758e-01 -5.24309337e-01 2.22613543e-01 3.90225440e-01
-3.92928183e-01 2.23789349e-01 4.44434136e-01 1.22630276e-01
-5.13422430e-01 4.64373052e-01 1.86344600e+00 -2.77848512e-01
-5.30841351e-01 3.25547042e-03 -4.53441024e-01 7.63233840e-01
7.32855380e-01 -1.54070556e-01 -6.27234042e-01 -4.15168256e-01
-1.18197352e-01 1.83405310e-01 4.12712008e-01 -8.24197590e-01
1.55640393e-01 -5.42953789e-01 3.63428980e-01 -7.95616806e-01
4.87193279e-02 -1.13789856e+00 1.23513773e-01 4.32105660e-01
-3.70943367e-01 -8.79886467e-03 2.77860910e-01 4.94250119e-01
-3.36255170e-02 -4.74018425e-01 1.01767671e+00 -2.36386284e-01
-8.57551396e-01 2.80305028e-01 -4.79526579e-01 -1.59634069e-01
1.54289007e+00 -3.19885314e-01 -2.11032689e-01 -2.59120494e-01
-6.73860073e-01 4.23842520e-01 5.58019400e-01 6.43430173e-01
6.73716843e-01 -1.16204894e+00 -4.37595516e-01 2.81774133e-01
6.46887198e-02 3.19991052e-01 4.59895581e-01 6.18268311e-01
-7.03532159e-01 2.34512668e-02 -2.57690370e-01 -7.02753723e-01
-1.53923893e+00 8.85139346e-01 3.62621635e-01 1.38623074e-01
-6.82076812e-01 2.93879330e-01 5.82031131e-01 -3.13103408e-01
3.16242129e-01 -6.19468033e-01 -3.56763780e-01 -1.11959279e-01
5.37094653e-01 2.89913803e-01 -2.95406103e-01 -5.14795482e-01
4.77807038e-03 9.52288747e-01 -1.45406201e-01 -6.38638586e-02
8.73155057e-01 -5.74571788e-01 -1.46132082e-01 9.15848613e-02
8.40067804e-01 -1.97892189e-02 -1.21755278e+00 -1.59936652e-01
-4.49814647e-01 -8.32931697e-01 8.83874521e-02 -8.83279085e-01
-1.32268763e+00 6.81380391e-01 6.94887340e-01 7.53807202e-02
1.39104116e+00 -2.87509292e-01 5.16106665e-01 3.73882145e-01
3.76781046e-01 -1.12627137e+00 2.89876401e-01 2.09577784e-01
1.14180338e+00 -9.59173679e-01 5.44771589e-02 -8.73290122e-01
-8.17070007e-01 1.14789891e+00 9.72188234e-01 1.91936359e-01
4.85566676e-01 2.83288270e-01 -1.02871954e-01 -7.13714063e-02
-9.94471237e-02 -6.85620531e-02 2.94052362e-01 5.58042705e-01
-2.02638097e-02 -2.04793364e-01 -3.43936592e-01 3.74309808e-01
-9.75604579e-02 -1.99861471e-02 4.92522299e-01 9.28040922e-01
-6.11606836e-01 -7.96816468e-01 -5.66761851e-01 3.86179656e-01
-1.92224815e-01 4.37059700e-02 5.87277254e-03 1.08457696e+00
4.06435788e-01 9.00845230e-01 1.77815799e-02 -2.77035497e-02
4.48082417e-01 -3.09753895e-01 4.26420331e-01 -5.22399962e-01
-3.25102895e-01 2.47070149e-01 -3.80014181e-01 -5.14114678e-01
-5.43226004e-01 -4.55045998e-01 -1.55538654e+00 1.19923102e-02
-4.87073421e-01 -1.37862280e-01 6.69573963e-01 8.27848256e-01
3.07444245e-01 7.57103443e-01 4.69249278e-01 -1.09511626e+00
-2.07703844e-01 -7.85996377e-01 -3.95156413e-01 6.12663388e-01
8.91870260e-02 -7.76134074e-01 -2.31926635e-01 5.15509486e-01] | [11.235116004943848, -1.089045524597168] |
ef729db5-0e5e-4d09-aebc-903c20770d4f | radfusion-benchmarking-performance-and | 2111.11665 | null | https://arxiv.org/abs/2111.11665v2 | https://arxiv.org/pdf/2111.11665v2.pdf | RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR | Despite the routine use of electronic health record (EHR) data by radiologists to contextualize clinical history and inform image interpretation, the majority of deep learning architectures for medical imaging are unimodal, i.e., they only learn features from pixel-level information. Recent research revealing how race can be recovered from pixel data alone highlights the potential for serious biases in models which fail to account for demographics and other key patient attributes. Yet the lack of imaging datasets which capture clinical context, inclusive of demographics and longitudinal medical history, has left multimodal medical imaging underexplored. To better assess these challenges, we present RadFusion, a multimodal, benchmark dataset of 1794 patients with corresponding EHR data and high-resolution computed tomography (CT) scans labeled for pulmonary embolism. We evaluate several representative multimodal fusion models and benchmark their fairness properties across protected subgroups, e.g., gender, race/ethnicity, age. Our results suggest that integrating imaging and EHR data can improve classification performance and robustness without introducing large disparities in the true positive rate between population groups. | ['Matthew P. Lungren', 'Nigam Shah', 'Lei Xing', 'Daniel Rubin', 'Imon Banerjee', 'Marcello Chang', 'Timothy J. Amrhein', 'Alaa Youssef', 'Jason Alan Fries', 'Shih-Cheng Huang', 'Yuyin Zhou'] | 2021-11-23 | null | null | null | null | ['pulmonary-embolism-detection'] | ['medical'] | [ 3.30856055e-01 1.18526824e-01 -6.47762060e-01 -7.29818642e-01
-1.25469947e+00 -5.32498360e-01 3.68895203e-01 6.49645329e-01
-5.65724969e-01 7.06681013e-01 8.76576662e-01 -8.31400573e-01
-1.12310544e-01 -6.18494749e-01 -5.14803946e-01 -6.59816206e-01
-8.84641260e-02 4.84713972e-01 -6.22494578e-01 5.44245124e-01
-3.14381033e-01 3.13559979e-01 -8.47020745e-01 5.56546867e-01
7.22997665e-01 9.88627434e-01 -2.84204811e-01 7.99982131e-01
2.14179054e-01 1.09288573e+00 -2.36353412e-01 -3.48647296e-01
3.29305887e-01 -4.88330156e-01 -4.36022669e-01 -3.15491259e-02
9.93619800e-01 -7.02829003e-01 -1.05135632e+00 7.50421584e-01
1.03463507e+00 -4.64617580e-01 8.71848702e-01 -9.25738394e-01
-7.59837508e-01 8.33882570e-01 -6.61968350e-01 4.32510167e-01
-7.31716678e-02 5.51069915e-01 8.87337446e-01 -2.56291240e-01
6.32195592e-01 8.09087574e-01 1.18371427e+00 4.60366130e-01
-1.18702435e+00 -4.94704664e-01 -1.41289026e-01 -1.64852977e-01
-1.07552099e+00 -3.10130686e-01 1.18719973e-01 -6.82336628e-01
3.85699183e-01 5.63064337e-01 6.15893543e-01 1.24617553e+00
4.39082623e-01 4.64963943e-01 1.26584733e+00 1.41941374e-02
-2.39474744e-01 -2.07638964e-01 3.16308677e-01 8.48533392e-01
5.43453157e-01 2.12904826e-01 -2.71734953e-01 -7.75466383e-01
9.30991054e-01 5.15207827e-01 -2.92399555e-01 -3.24096203e-01
-1.79048085e+00 6.33472383e-01 4.05452222e-01 -4.79385406e-02
-6.02643907e-01 2.95496374e-01 3.97768229e-01 2.70169582e-02
3.49787297e-03 2.46789515e-01 -3.41259331e-01 1.66293696e-01
-9.16638017e-01 2.63515748e-02 6.33607686e-01 3.64297777e-01
3.72967422e-01 -1.68879956e-01 -6.27543449e-01 5.96527636e-01
2.54815146e-02 7.70359159e-01 4.37260479e-01 -1.26751733e+00
2.71970361e-01 4.99788016e-01 -1.47143379e-01 -7.24157035e-01
-9.37282145e-01 -5.85567713e-01 -1.19924581e+00 -2.08884612e-01
7.74149895e-01 -6.41881824e-01 -1.25967383e+00 1.88095582e+00
9.47497487e-02 1.97623596e-01 -3.20627540e-02 8.57065022e-01
1.23816228e+00 -2.16338977e-01 7.80699074e-01 1.86136737e-01
1.99038875e+00 -1.72662720e-01 -3.48007202e-01 -1.02473885e-01
8.01297843e-01 -3.25132012e-01 6.51105881e-01 -1.19551681e-02
-1.10010886e+00 -1.17390662e-01 -5.63686132e-01 2.90324036e-02
-1.18950039e-01 2.38637120e-01 8.00956786e-01 9.86324728e-01
-8.59946251e-01 2.67853111e-01 -1.08272040e+00 -4.23618048e-01
1.00231671e+00 4.64598238e-01 -4.52711046e-01 -2.87197590e-01
-1.11386001e+00 7.50055075e-01 1.06637336e-01 -2.27366999e-01
-9.07793999e-01 -1.56831336e+00 -8.19237649e-01 7.14603662e-02
2.58248985e-01 -1.56585717e+00 9.91461754e-01 -7.50190377e-01
-5.86411953e-01 1.01188815e+00 -4.32422757e-02 -6.32685363e-01
6.79941177e-01 2.30080053e-01 -4.82689261e-01 3.31016332e-01
8.50441158e-02 9.21231091e-01 3.71421099e-01 -9.38949466e-01
-7.75463402e-01 -7.02541649e-01 -3.88327330e-01 2.48961404e-01
-2.44619384e-01 -2.32401818e-01 -1.11630909e-01 -7.40938902e-01
-1.33954100e-02 -1.00698340e+00 -7.45717525e-01 7.72351027e-02
-4.08206910e-01 3.51566702e-01 1.57116920e-01 -9.76728916e-01
1.24400377e+00 -2.01811671e+00 -3.07626635e-01 2.60670274e-01
9.36560512e-01 -2.66683847e-01 1.19498827e-01 -2.71348357e-01
-3.54875475e-01 4.83747423e-01 -3.38813931e-01 -4.17820700e-02
-2.58003324e-01 1.35269672e-01 1.52740955e-01 7.04055130e-01
1.00236021e-01 1.54192472e+00 -6.62501454e-01 -7.74137378e-01
2.03818172e-01 6.47448003e-01 -6.85009599e-01 -2.63998270e-01
3.25053632e-01 7.67722547e-01 -4.86930698e-01 9.13909376e-01
4.50961947e-01 -1.00268853e+00 3.41554791e-01 -4.13934559e-01
2.05125540e-01 1.40046224e-01 -7.01867759e-01 1.71127701e+00
-7.87142217e-02 3.11427593e-01 2.98791885e-01 -7.36956954e-01
2.64256954e-01 4.56047833e-01 1.28068268e+00 -6.45051360e-01
2.08169699e-01 1.12612143e-01 3.19265395e-01 -4.88609523e-01
1.40695795e-01 -2.94255048e-01 -2.01267544e-02 4.75267977e-01
-5.30832827e-01 2.72859991e-01 -3.47382963e-01 2.42456928e-01
1.60017085e+00 -4.71973538e-01 1.16500646e-01 9.98843554e-03
1.53941542e-01 4.60208923e-01 7.04607427e-01 1.20735192e+00
-5.07201135e-01 1.07452285e+00 4.37155396e-01 -5.60130239e-01
-1.18564451e+00 -1.34875345e+00 -6.70055568e-01 6.67052329e-01
-2.66342342e-01 -1.53219208e-01 -2.06819221e-01 -6.64764702e-01
3.78686428e-01 1.02641754e-01 -8.25449347e-01 -1.05692104e-01
-5.84793508e-01 -1.48832548e+00 9.69804823e-01 7.21087933e-01
2.78441936e-01 -4.38838273e-01 -1.01703286e+00 1.56339660e-01
-3.16009820e-01 -1.05754602e+00 -3.44020873e-01 -4.87810411e-02
-1.13267612e+00 -1.38715446e+00 -1.24130321e+00 -3.71051669e-01
4.62695241e-01 -1.93124533e-01 1.66580737e+00 2.98571717e-02
-7.72178590e-01 9.67937946e-01 6.82538236e-03 -3.85174900e-01
-4.64901179e-01 2.64477611e-01 -4.44854587e-01 -1.56351104e-01
4.71700758e-01 -2.43819252e-01 -1.31485367e+00 4.70096692e-02
-7.55735576e-01 4.83965836e-02 1.03276372e+00 9.72628474e-01
6.07511699e-01 -4.96669501e-01 5.40305376e-01 -1.26078808e+00
2.14093596e-01 -7.91724622e-01 8.79093334e-02 4.91867185e-01
-6.61625862e-01 -2.14258164e-01 -1.79053828e-01 -2.44576305e-01
-1.08375823e+00 2.29997113e-01 2.42844641e-01 -2.28021219e-01
-4.94150072e-01 7.61767209e-01 4.24472988e-01 6.27338439e-02
7.15387225e-01 -1.73528031e-01 2.20433608e-01 -2.68193692e-01
7.78692886e-02 6.33873641e-01 8.88701677e-01 -5.98969996e-01
1.94879055e-01 8.65525842e-01 2.72756457e-01 -5.59365869e-01
-7.42497623e-01 -3.45756710e-01 -3.09943348e-01 9.03258175e-02
1.17400146e+00 -1.34569228e+00 -7.36136436e-01 2.29094222e-01
-4.68101710e-01 -1.30659938e-01 -4.23353463e-01 9.87465680e-01
-2.34222263e-01 3.61802757e-01 -7.81127036e-01 -4.27853793e-01
-4.53380257e-01 -1.28219259e+00 1.07698834e+00 4.71938811e-02
-4.37944770e-01 -1.01407099e+00 9.84084979e-03 5.03769159e-01
5.85447848e-01 8.02980959e-01 1.40298057e+00 -5.71915269e-01
-5.78707755e-01 -1.01687461e-01 -5.61312914e-01 -1.11346468e-01
1.51046515e-01 -1.94511265e-01 -7.59945989e-01 -3.45965214e-02
-3.55746180e-01 -2.60933220e-01 1.13307846e+00 1.13683438e+00
1.44144082e+00 2.68882096e-01 -5.05962074e-01 9.57313180e-01
1.22824204e+00 2.29334198e-02 5.32540619e-01 2.46135946e-02
8.58603060e-01 3.40723276e-01 -1.60037860e-01 7.24069059e-01
8.59529614e-01 5.72617864e-04 3.39111507e-01 -6.73520625e-01
-2.93981820e-01 8.28767121e-02 -3.18298548e-01 1.25783309e-01
-2.64081787e-02 2.17829272e-02 -1.41148067e+00 5.22093177e-01
-1.47809744e+00 -6.70480609e-01 -3.28664184e-01 2.07996440e+00
7.99775720e-01 -3.20007682e-01 1.51709244e-01 -4.96776700e-01
7.63119638e-01 1.56254381e-01 -9.99912679e-01 3.12193006e-01
-6.28432810e-01 1.49731547e-01 1.26790130e+00 2.61512604e-02
-1.19200981e+00 1.02212615e-01 7.60527945e+00 1.63187221e-01
-1.14334583e+00 2.19578341e-01 1.51775849e+00 -3.54751885e-01
-6.29019976e-01 -3.39842439e-01 -1.70898736e-01 7.26984590e-02
1.00103176e+00 1.69196784e-01 7.88761303e-02 2.95486182e-01
2.61739269e-02 -1.77621320e-01 -1.19482505e+00 1.11615062e+00
7.76284710e-02 -1.54970205e+00 -1.50875494e-01 4.10424918e-01
7.92045534e-01 5.39334714e-01 6.58407390e-01 2.21911386e-01
6.78458095e-01 -1.41333687e+00 1.58581838e-01 6.24922514e-01
1.20910156e+00 -1.91781476e-01 6.24637723e-01 -2.41289437e-01
-6.45298958e-01 -1.97583809e-01 8.43277499e-02 3.71194273e-01
1.43549100e-01 5.11359394e-01 -7.20904887e-01 4.68263686e-01
7.49476969e-01 9.01721358e-01 -8.00516307e-01 9.63296354e-01
5.80387950e-01 6.81258440e-01 -2.85210133e-01 7.80647635e-01
1.84797943e-01 1.22635521e-01 1.60379171e-01 9.85313952e-01
5.46721160e-01 4.77257550e-01 1.91840827e-01 6.05781913e-01
-2.02164799e-01 1.50987267e-01 -3.86554122e-01 -2.35333145e-01
2.15740398e-01 1.31187177e+00 -5.50476134e-01 -6.39828622e-01
-9.47681546e-01 2.14885354e-01 -2.02237740e-01 4.56165582e-01
-9.49211478e-01 4.13728923e-01 6.62414610e-01 4.31701005e-01
-1.10367641e-01 6.20730072e-02 -9.58912671e-01 -1.39173436e+00
-4.74899948e-01 -1.04200435e+00 1.15268755e+00 -5.73888719e-01
-1.58120871e+00 1.34375274e-01 -2.66201288e-01 -7.85659850e-01
-8.26453343e-02 -6.55416012e-01 -1.22540794e-01 1.04332316e+00
-1.57906866e+00 -1.14167571e+00 -5.13429761e-01 7.87780762e-01
-2.21369863e-01 -2.99973547e-01 6.45390391e-01 5.83853364e-01
-5.69722354e-01 7.88186789e-01 -6.02873266e-02 5.76684237e-01
1.27028668e+00 -1.25529170e+00 1.77258346e-02 9.76203158e-02
-1.84729725e-01 6.32229686e-01 2.72291958e-01 -8.31384957e-01
-1.38969779e+00 -9.44440424e-01 4.75696236e-01 -9.64955747e-01
4.60044146e-01 4.06153202e-01 -7.60904014e-01 8.76103520e-01
7.83800185e-02 1.54835477e-01 1.29501283e+00 1.85237363e-01
-4.71607178e-01 8.35840963e-03 -1.28073120e+00 6.07454121e-01
8.96038949e-01 -4.76639748e-01 -3.22460651e-01 -1.27562396e-02
3.23464245e-01 -5.20385742e-01 -1.59066105e+00 7.98648238e-01
8.21848869e-01 -7.94675469e-01 1.27927303e+00 -1.06892002e+00
5.83429873e-01 1.18391708e-01 -2.49123529e-01 -8.74071300e-01
-3.14098835e-01 -6.30069971e-02 3.93838435e-02 6.52720273e-01
6.16496921e-01 -7.08770394e-01 1.11411464e+00 1.30297995e+00
2.43713036e-02 -6.44981444e-01 -7.64277637e-01 5.45406006e-02
3.88899446e-01 -3.80279601e-01 6.37975991e-01 1.22625327e+00
-3.25436920e-01 -1.00541107e-01 -2.34807521e-01 2.58266121e-01
6.29489720e-01 1.23133257e-01 4.12535906e-01 -1.35276139e+00
-4.18269068e-01 -5.02731740e-01 -2.93401301e-01 -4.55601752e-01
1.80916339e-02 -1.05044115e+00 -6.25810742e-01 -1.55538321e+00
8.84803176e-01 -7.97217548e-01 -7.34409034e-01 5.27346492e-01
-5.13659477e-01 3.88911515e-01 -1.39553668e-02 3.15068424e-01
-3.65298241e-01 -2.52455436e-02 1.29030526e+00 -3.01583886e-01
6.64734766e-02 -2.19062775e-01 -1.02141976e+00 5.12012661e-01
6.72509611e-01 -4.38952297e-01 -6.94774836e-02 -5.86446583e-01
1.58737287e-01 5.80604553e-01 8.55813384e-01 -9.03823256e-01
1.33363008e-01 -1.71743169e-01 1.00355673e+00 -5.45991004e-01
4.15040292e-02 -8.86189044e-01 2.94820160e-01 8.47744763e-01
-6.46574318e-01 4.61115807e-01 -3.81681621e-02 6.93512857e-01
-2.96820775e-02 4.28860843e-01 5.10365784e-01 -4.77363557e-01
-3.84529591e-01 6.76644027e-01 -4.43129182e-01 4.50154543e-01
7.86950409e-01 2.29234695e-02 -6.13437533e-01 -4.10880983e-01
-1.07676840e+00 3.67542952e-01 3.71498048e-01 1.13197370e-02
1.99036360e-01 -1.21799707e+00 -1.13792777e+00 6.80251140e-03
1.81608766e-01 -1.64126039e-01 7.24746406e-01 1.44417095e+00
-5.42888105e-01 3.27449918e-01 -1.25829145e-01 -9.21012521e-01
-1.08084238e+00 5.00589848e-01 6.79165006e-01 -2.78716564e-01
-6.29000425e-01 2.77629733e-01 4.96018678e-01 -3.98087353e-01
1.14546679e-01 -3.83100569e-01 2.58759975e-01 2.29302589e-02
3.18270415e-01 3.43670845e-01 -6.83382750e-02 -5.63728571e-01
-3.06680053e-01 3.45786542e-01 5.16556241e-02 -1.15984417e-01
1.19809747e+00 -2.33862564e-01 1.15870543e-01 9.72870290e-02
1.02493310e+00 -1.76211655e-01 -1.09642160e+00 -4.09171790e-01
-1.82451189e-01 -2.97108144e-01 2.26189911e-01 -1.13274205e+00
-1.39121771e+00 8.31305206e-01 9.67258573e-01 -2.37469062e-01
9.01728749e-01 7.23977163e-02 6.66112363e-01 1.22427769e-01
-1.85749352e-01 -6.79160357e-01 -3.92722636e-01 5.05588353e-02
-9.02843941e-03 -1.73541439e+00 1.51448324e-01 -1.07581809e-01
-8.56460690e-01 7.57683754e-01 4.05850232e-01 3.72636735e-01
8.06936085e-01 3.48317027e-01 4.61207062e-01 -2.23830044e-01
-7.00741351e-01 -1.78435668e-01 2.42560610e-01 4.29676950e-01
9.10446286e-01 3.83595705e-01 -4.89279516e-02 5.73110282e-01
8.19784701e-02 6.83918893e-02 3.15551549e-01 8.13270032e-01
-1.04087651e-01 -8.93076301e-01 -6.87665105e-01 1.12724388e+00
-1.01992095e+00 -3.32846433e-01 -1.33765593e-01 6.85175776e-01
1.54486999e-01 4.44840699e-01 2.75802344e-01 -1.32275769e-03
1.49287939e-01 2.03172922e-01 3.06215495e-01 -4.60895687e-01
-8.82983208e-01 9.91109461e-02 4.89009842e-02 -4.28923279e-01
-3.95620793e-01 -1.03141940e+00 -9.92812157e-01 -3.41989577e-01
4.29730982e-01 -3.57314855e-01 4.85534608e-01 5.76377451e-01
5.81068039e-01 8.75634551e-01 1.28219500e-01 -1.22789934e-01
-6.78396881e-01 -4.56842273e-01 -3.89408946e-01 6.81512475e-01
5.59927166e-01 -1.72850251e-01 -5.92149720e-02 9.41911936e-02] | [15.028770446777344, -2.13090443611145] |
992831d0-c988-4bc1-8e48-03f86a061d3c | greedy-infomax-for-biologically-plausible | 1905.11786 | null | https://arxiv.org/abs/1905.11786v3 | https://arxiv.org/pdf/1905.11786v3.pdf | Putting An End to End-to-End: Gradient-Isolated Learning of Representations | We propose a novel deep learning method for local self-supervised representation learning that does not require labels nor end-to-end backpropagation but exploits the natural order in data instead. Inspired by the observation that biological neural networks appear to learn without backpropagating a global error signal, we split a deep neural network into a stack of gradient-isolated modules. Each module is trained to maximally preserve the information of its inputs using the InfoNCE bound from Oord et al. [2018]. Despite this greedy training, we demonstrate that each module improves upon the output of its predecessor, and that the representations created by the top module yield highly competitive results on downstream classification tasks in the audio and visual domain. The proposal enables optimizing modules asynchronously, allowing large-scale distributed training of very deep neural networks on unlabelled datasets. | ["Peter O'Connor", 'Sindy Löwe', 'Bastiaan S. Veeling'] | 2019-05-28 | putting-an-end-to-end-to-end-gradient | http://papers.nips.cc/paper/8568-putting-an-end-to-end-to-end-gradient-isolated-learning-of-representations | http://papers.nips.cc/paper/8568-putting-an-end-to-end-to-end-gradient-isolated-learning-of-representations.pdf | neurips-2019-12 | ['self-supervised-image-classification'] | ['computer-vision'] | [ 4.33179796e-01 6.10673070e-01 -9.47416425e-02 -5.09423673e-01
-4.17335689e-01 -6.12245977e-01 5.62916338e-01 3.03765982e-01
-6.65213645e-01 8.19638908e-01 2.38401055e-01 2.42388751e-02
-4.49315179e-03 -7.52439857e-01 -1.11795592e+00 -8.26987147e-01
-2.51800954e-01 3.49755108e-01 2.37457097e-01 -2.14816281e-03
1.33177508e-02 5.42813778e-01 -1.53564048e+00 6.77836061e-01
2.60252804e-01 1.03105187e+00 1.53544784e-01 8.75637412e-01
6.45296425e-02 1.19562936e+00 -4.13469374e-01 -8.76749158e-02
3.36466074e-01 -4.96104598e-01 -9.38884556e-01 -4.54808995e-02
4.34799284e-01 -3.30150053e-02 -4.28343862e-01 7.33840644e-01
5.27414083e-01 6.89594150e-02 6.78880215e-01 -9.59430337e-01
-5.67129433e-01 8.34675372e-01 -8.88732672e-02 1.40415549e-01
-2.94026315e-01 8.62810016e-02 1.10347164e+00 -6.82542324e-01
8.94413888e-01 9.02008235e-01 6.94587409e-01 6.75034702e-01
-1.70852947e+00 -4.56766546e-01 5.06680727e-01 -9.77466926e-02
-9.56092358e-01 -7.75751948e-01 5.39643228e-01 -3.23210329e-01
1.12783396e+00 -9.29675922e-02 3.97754043e-01 1.08312011e+00
1.40382543e-01 8.00629318e-01 9.26795423e-01 -4.22408521e-01
4.24220026e-01 1.72351435e-01 4.80087213e-02 9.89315033e-01
-1.07496798e-01 1.10329472e-01 -9.28619385e-01 -3.35842790e-03
5.25645316e-01 6.28648624e-02 -1.31737798e-01 -4.98754144e-01
-1.05627573e+00 5.87065279e-01 8.89551997e-01 4.39219415e-01
-2.31791630e-01 5.53585589e-01 4.14563864e-01 8.71971130e-01
4.02369738e-01 4.91510928e-01 -9.43946004e-01 1.86667651e-01
-8.57104897e-01 -2.66812235e-01 7.08298028e-01 5.32248795e-01
1.14304078e+00 -3.77870910e-02 -7.20209628e-02 6.61022186e-01
3.08806598e-01 -5.89282736e-02 8.75354469e-01 -1.21344888e+00
2.64179647e-01 4.53362226e-01 -3.39130044e-01 -5.66426694e-01
-5.55479765e-01 -9.25458252e-01 -8.69164586e-01 5.47282100e-01
4.15818363e-01 -3.68411660e-01 -7.66164303e-01 2.20076728e+00
-1.48542095e-02 8.88522193e-02 1.51376531e-01 4.83960956e-01
3.74856263e-01 5.10245562e-01 -5.33960499e-02 -2.11249039e-01
4.92206424e-01 -1.19129503e+00 -1.17149390e-01 -4.79038477e-01
9.59720969e-01 -1.13031521e-01 4.11206663e-01 4.04728293e-01
-1.28896332e+00 -6.48673892e-01 -1.03752422e+00 -1.45951197e-01
-3.63278985e-01 -6.28219694e-02 5.34190893e-01 4.48575094e-02
-1.62096727e+00 1.12207639e+00 -8.65366459e-01 -1.67636469e-01
7.53108084e-01 5.70370376e-01 -5.77704132e-01 2.49998972e-01
-8.41567695e-01 7.55387902e-01 3.79174799e-01 4.21606936e-02
-1.41684449e+00 -5.18597364e-01 -5.99172294e-01 1.87232286e-01
-2.46592969e-01 -7.81079590e-01 1.22952306e+00 -1.67338002e+00
-1.73019481e+00 1.17982626e+00 -3.19605172e-01 -8.82865369e-01
4.02526766e-01 -1.04588568e-01 1.86416283e-01 1.37308881e-01
-1.16257392e-01 1.02697468e+00 1.09570408e+00 -1.02460194e+00
-5.77626646e-01 -4.42325860e-01 -1.99071884e-01 9.14718732e-02
-6.42203212e-01 -3.55892807e-01 -2.21723355e-02 -4.21755433e-01
3.35787714e-01 -7.56428242e-01 -3.56056511e-01 2.79273659e-01
-1.32510453e-01 -1.30498096e-01 4.09332991e-01 -3.35021198e-01
6.52361453e-01 -2.35976911e+00 5.98936439e-01 2.26279393e-01
4.13536161e-01 2.74186954e-02 -4.25217867e-01 4.51895863e-01
-3.04614484e-01 -5.61256595e-02 -4.59157437e-01 -5.41975558e-01
-7.43785128e-02 2.67921895e-01 -5.27627647e-01 6.58019423e-01
2.87486851e-01 1.02297509e+00 -1.02807295e+00 -9.10412446e-02
-2.04086125e-01 3.27407509e-01 -5.55935025e-01 2.77905703e-01
-1.83186844e-01 4.73367512e-01 1.53312087e-01 1.33634165e-01
2.88587213e-01 -5.33540905e-01 3.71524990e-01 1.76416904e-01
4.82150391e-02 6.80327296e-01 -1.01541710e+00 2.11414695e+00
-6.15496516e-01 7.69042790e-01 3.51595253e-01 -1.52806652e+00
9.21090066e-01 4.65633035e-01 3.37956846e-01 -6.39294326e-01
-3.98199223e-02 3.31437618e-01 -3.84898372e-02 4.35828492e-02
-2.72513241e-01 -1.67919263e-01 4.77689840e-02 6.57303870e-01
7.95562625e-01 3.49273145e-01 6.17936440e-02 3.47047180e-01
1.53769970e+00 1.98474705e-01 7.79090822e-02 -1.81866050e-01
3.62582028e-01 -2.94477522e-01 5.15537322e-01 9.08904672e-01
-1.67235732e-01 5.62541962e-01 5.67574382e-01 -2.43942142e-01
-8.44868958e-01 -1.29949510e+00 -1.12916209e-01 1.92848229e+00
-2.16977298e-01 -2.74980366e-01 -5.88305056e-01 -8.60054374e-01
2.29396615e-02 2.15483069e-01 -8.13947022e-01 -5.10372519e-01
-4.08990264e-01 -3.77301216e-01 6.63366020e-01 5.22219241e-01
4.17336971e-01 -1.28132772e+00 -5.79617560e-01 3.73760670e-01
3.46513897e-01 -5.60655415e-01 -1.57164671e-02 1.13407493e+00
-1.36116755e+00 -7.47662067e-01 -6.97620571e-01 -1.21247780e+00
9.61860359e-01 -1.20626338e-01 1.23000729e+00 8.69529613e-04
-2.31369928e-01 2.60645419e-01 2.59430297e-02 5.69560193e-02
-4.51982826e-01 4.38625425e-01 -1.68094322e-01 9.83460993e-02
1.03283031e-02 -1.05523753e+00 -4.80107367e-01 -4.01599929e-02
-6.91337943e-01 4.71668877e-02 7.86617398e-01 1.02949190e+00
4.68912810e-01 -2.91180074e-01 8.33963573e-01 -9.81749833e-01
3.54465574e-01 -5.97853541e-01 -4.71570075e-01 2.51816940e-02
-6.51976109e-01 6.90290570e-01 8.41409564e-01 -2.77133018e-01
-8.48764300e-01 5.56979597e-01 -2.84244027e-02 -3.58151831e-02
-4.48118657e-01 4.01008755e-01 1.67975873e-01 1.85062382e-02
9.67211068e-01 3.57919484e-01 -7.70387203e-02 -6.08831704e-01
5.87788403e-01 3.41874450e-01 7.21868038e-01 -3.80343676e-01
4.58274037e-01 5.08698165e-01 -4.70550954e-02 -2.90346235e-01
-9.04185712e-01 -2.80255795e-01 -8.14490199e-01 -4.48685586e-02
6.37621760e-01 -1.05028355e+00 -7.62349367e-01 4.88528758e-01
-1.26395905e+00 -5.32374561e-01 -7.34699190e-01 1.37656808e-01
-6.15321159e-01 -1.16944686e-01 -8.24742079e-01 -4.48211730e-01
-1.52380586e-01 -6.56475663e-01 7.62721300e-01 9.80031639e-02
-2.59037822e-01 -1.14294672e+00 4.89612311e-01 -1.86348304e-01
3.95673752e-01 -1.22491293e-01 6.85405195e-01 -7.39510655e-01
-4.72492397e-01 -5.89827932e-02 2.73895711e-02 6.65035605e-01
-9.56930667e-02 -3.04396629e-01 -1.53622115e+00 -4.10415143e-01
-2.51903795e-02 -8.40244174e-01 1.63911998e+00 1.82264686e-01
1.10672176e+00 -3.65100443e-01 -3.41074526e-01 8.68457615e-01
1.22020268e+00 -4.65654194e-01 3.36718738e-01 3.51223707e-01
3.66207600e-01 7.86871791e-01 -3.81715864e-01 1.81663349e-01
-2.96762250e-02 4.72195558e-02 7.14947939e-01 -3.17386538e-02
-1.87583551e-01 -4.29430723e-01 7.69699812e-01 7.96458721e-01
1.88824534e-01 7.04439953e-02 -6.05482459e-01 7.24282265e-01
-2.07044363e+00 -9.11989331e-01 2.90038496e-01 2.25330353e+00
1.19168043e+00 3.08517098e-01 -1.87965527e-01 2.39153519e-01
5.27920902e-01 2.21909478e-01 -7.25411296e-01 -5.72351575e-01
-3.62033129e-01 5.85351408e-01 5.69857895e-01 5.77390790e-01
-1.04956794e+00 9.51946735e-01 6.88968897e+00 4.23405141e-01
-1.13957930e+00 2.92353928e-01 7.15405941e-01 -2.91307420e-01
-3.41048330e-01 1.02419138e-01 -5.81429064e-01 2.12298870e-01
1.20047271e+00 3.50993797e-02 5.35454094e-01 7.24974215e-01
-2.81915814e-01 3.23566832e-02 -1.48024845e+00 5.58608294e-01
-2.80232370e-01 -1.51530361e+00 -1.53488472e-01 -1.02370612e-01
9.43463624e-01 6.11651480e-01 1.11090228e-01 2.23729268e-01
7.01358676e-01 -1.20235729e+00 5.76963961e-01 6.52409196e-01
3.24397653e-01 -6.01214290e-01 2.85665244e-01 6.52111351e-01
-7.99118578e-01 -3.43806624e-01 -5.34079671e-01 -4.30402935e-01
-2.81009704e-01 7.99947858e-01 -9.05944824e-01 -6.85692132e-02
4.23261553e-01 9.26588058e-01 -6.62514031e-01 9.49684322e-01
-6.38765037e-01 9.07429993e-01 -4.04747516e-01 1.84233218e-01
1.64713249e-01 5.40753528e-02 3.01085085e-01 1.40742385e+00
1.57921184e-02 -5.03862977e-01 -1.65528342e-01 7.59595275e-01
-6.88860714e-01 -9.77816209e-02 -8.89428794e-01 -5.21653444e-02
2.87037581e-01 1.30978370e+00 -4.91777271e-01 -3.83311898e-01
-1.67537928e-01 1.32158339e+00 1.01871586e+00 5.16177356e-01
-2.50229686e-01 -3.08080137e-01 5.01275063e-01 -5.04966117e-02
5.75857818e-01 -7.09895939e-02 -5.43624103e-01 -9.36812341e-01
-6.16110042e-02 -5.10572433e-01 3.45873117e-01 -5.27194560e-01
-1.19339979e+00 5.45597017e-01 -7.20562100e-01 -9.33605731e-01
-5.93530595e-01 -6.96036279e-01 -6.19100273e-01 7.31312454e-01
-1.44914448e+00 -7.80689240e-01 1.16858222e-01 5.67010224e-01
1.50251895e-01 -2.77336985e-01 1.08191895e+00 1.13960393e-01
-2.19872311e-01 5.60518920e-01 5.72663188e-01 2.65784085e-01
6.98290765e-01 -1.26791346e+00 1.19302817e-01 6.58271790e-01
6.75811291e-01 6.14638925e-01 4.13977295e-01 -1.66497275e-01
-9.92912114e-01 -1.14356267e+00 1.00882852e+00 -2.09089726e-01
6.96722567e-01 -5.47403932e-01 -8.65521491e-01 8.33372474e-01
4.42204654e-01 3.43191773e-01 4.97917533e-01 3.12867850e-01
-7.67726362e-01 -4.54540312e-01 -7.88435161e-01 2.12788224e-01
1.27185416e+00 -7.82830715e-01 -6.09381020e-01 3.89538527e-01
5.45537531e-01 1.25976801e-02 -5.22240758e-01 1.99307621e-01
2.97577918e-01 -1.09102738e+00 7.07040429e-01 -9.48506474e-01
5.46136498e-01 -1.02786817e-01 5.34831844e-02 -1.51375556e+00
-3.89849246e-01 -7.08290815e-01 -3.28626961e-01 1.02854359e+00
8.38639200e-01 -7.85001278e-01 8.16941917e-01 9.82632861e-02
-2.31262118e-01 -4.81317967e-01 -1.08699739e+00 -6.02232277e-01
3.06771457e-01 -1.57347292e-01 -6.07255511e-02 7.71461189e-01
1.48341373e-01 6.49416685e-01 -1.41809493e-01 6.45829588e-02
5.37137330e-01 2.21644700e-01 3.33159983e-01 -1.31992340e+00
-8.57071817e-01 -5.52992225e-01 -4.86953288e-01 -1.31490731e+00
4.53567684e-01 -1.57087982e+00 2.58532703e-01 -1.25877106e+00
1.89207345e-01 -1.92091867e-01 -8.94960761e-01 8.59346092e-01
1.64486915e-01 3.57193857e-01 1.00005940e-02 3.47105324e-01
-8.62343550e-01 4.72545445e-01 8.03378522e-01 -3.10688704e-01
-6.25466928e-02 -2.66269110e-02 -8.49016666e-01 7.43353009e-01
8.65296662e-01 -9.33183193e-01 -2.98656315e-01 -8.11840594e-01
5.61559379e-01 -4.84941244e-01 4.36637461e-01 -1.05884242e+00
5.71601570e-01 3.40912402e-01 6.73416972e-01 1.03814214e-01
1.76871344e-01 -6.72392547e-01 -3.49234492e-01 6.61649883e-01
-1.08409691e+00 -2.71923780e-01 6.73994794e-02 6.73825860e-01
-3.73354286e-01 -4.01222765e-01 9.41169918e-01 -2.61045635e-01
-4.37528461e-01 1.17275611e-01 -5.66106796e-01 4.48949747e-02
6.92223012e-01 1.58910975e-01 -3.79225314e-01 -3.79316241e-01
-1.07655847e+00 1.28296912e-01 2.94506133e-01 3.46980169e-02
4.53806460e-01 -1.18460584e+00 -6.68378890e-01 3.46841961e-01
-3.85246202e-02 3.80777419e-02 -2.75185823e-01 6.90368533e-01
-2.61553824e-01 2.34584257e-01 -2.53381312e-01 -5.89558363e-01
-8.40444267e-01 3.48767221e-01 5.84447920e-01 -3.86684597e-01
-3.38613838e-01 1.35375726e+00 2.90859580e-01 -7.53200889e-01
4.56256002e-01 -7.45823532e-02 7.00839013e-02 4.35746685e-02
4.06854093e-01 7.01659769e-02 2.45498657e-01 -2.02362657e-01
-2.88478941e-01 1.46067053e-01 -1.82192445e-01 -4.84033048e-01
1.62104321e+00 6.98234290e-02 -2.72696733e-01 7.59920418e-01
1.64977372e+00 -1.83650553e-01 -1.52007055e+00 -4.12939698e-01
2.73508877e-01 1.53561428e-01 1.61213607e-01 -7.14172542e-01
-1.11178493e+00 1.23431802e+00 5.80533683e-01 7.71642998e-02
1.02775359e+00 1.87527373e-01 4.84902024e-01 9.88847256e-01
1.46215886e-01 -1.20644307e+00 2.90011257e-01 8.55548501e-01
8.35432708e-01 -9.40012276e-01 -3.30316991e-01 4.04545426e-01
-2.74053991e-01 1.23056245e+00 3.69063228e-01 -5.29078603e-01
6.56869709e-01 4.38733518e-01 4.05270644e-02 1.24373868e-01
-1.42343438e+00 -2.13504285e-01 1.88803934e-02 7.21023321e-01
4.58066791e-01 -3.49546671e-01 4.03226204e-02 4.03210998e-01
1.62130177e-01 1.08838558e-01 1.46809578e-01 1.06829476e+00
-7.63290584e-01 -1.13201618e+00 5.16323037e-02 3.27854782e-01
-3.39798689e-01 -2.48587087e-01 -6.43416286e-01 1.34440288e-01
1.45594090e-01 5.69032550e-01 2.07577050e-01 -3.08045626e-01
-1.19824365e-01 4.66158092e-01 4.78407800e-01 -8.53476286e-01
-8.57383192e-01 -1.25141919e-01 -7.17949122e-02 -5.91023505e-01
-4.31824416e-01 -3.67021084e-01 -1.53721130e+00 -1.24609042e-02
2.61271484e-02 1.63430482e-01 6.03568912e-01 9.89482760e-01
6.59071624e-01 7.09484994e-01 8.96808624e-01 -8.44030857e-01
-6.98188663e-01 -8.99705589e-01 -4.68008846e-01 4.22872186e-01
5.56902289e-01 -1.91213310e-01 -6.24732852e-01 3.46132338e-01] | [9.424918174743652, 2.727818727493286] |
34ad50ba-926a-41e5-8692-09ceb8413a72 | coper-continuous-patient-state-perceiver | 2208.03196 | null | https://arxiv.org/abs/2208.03196v2 | https://arxiv.org/pdf/2208.03196v2.pdf | COPER: Continuous Patient State Perceiver | In electronic health records (EHRs), irregular time-series (ITS) occur naturally due to patient health dynamics, reflected by irregular hospital visits, diseases/conditions and the necessity to measure different vitals signs at each visit etc. ITS present challenges in training machine learning algorithms which mostly are built on assumption of coherent fixed dimensional feature space. In this paper, we propose a novel COntinuous patient state PERceiver model, called COPER, to cope with ITS in EHRs. COPER uses Perceiver model and the concept of neural ordinary differential equations (ODEs) to learn the continuous time dynamics of patient state, i.e., continuity of input space and continuity of output space. The neural ODEs help COPER to generate regular time-series to feed to Perceiver model which has the capability to handle multi-modality large-scale inputs. To evaluate the performance of the proposed model, we use in-hospital mortality prediction task on MIMIC-III dataset and carefully design experiments to study irregularity. The results are compared with the baselines which prove the efficacy of the proposed model. | ['David A. Clifton', "Odhran O'Donoghue", 'Anshul Thakur', 'Vinod Kumar Chauhan'] | 2022-08-05 | null | null | null | null | ['mortality-prediction', 'irregular-time-series'] | ['medical', 'time-series'] | [ 9.50873713e-04 3.10456641e-02 1.33770317e-01 -3.43776554e-01
-5.00154436e-01 -1.90036863e-01 -6.37958646e-02 5.61505198e-01
-8.85277838e-02 5.47737122e-01 5.38044095e-01 -2.57758647e-01
-4.33471739e-01 -5.61026931e-01 -3.83766621e-01 -4.03673828e-01
-4.71829087e-01 2.23300755e-01 -6.52669430e-01 -2.48506576e-01
-3.40653569e-01 2.51154840e-01 -1.04102302e+00 4.07490104e-01
5.75276256e-01 1.00499964e+00 5.09379141e-04 8.64803791e-01
1.56579554e-01 9.54116940e-01 -5.10058582e-01 3.02123547e-01
1.83690175e-01 -4.06062394e-01 -3.76743704e-01 -5.12154624e-02
-3.27675164e-01 -2.50765324e-01 -6.53314471e-01 6.58613503e-01
8.74098063e-01 -2.19250508e-02 7.57622778e-01 -8.88728380e-01
-6.61119044e-01 3.27467918e-01 -7.50007704e-02 4.57942724e-01
4.92717266e-01 2.53194690e-01 4.58084911e-01 -4.40736473e-01
4.10796762e-01 1.13466465e+00 1.26794052e+00 7.53424823e-01
-1.16627109e+00 -5.77104390e-02 -1.08646661e-01 -1.23903319e-01
-1.35562372e+00 -2.39429176e-01 9.18490052e-01 -4.60146517e-01
7.45143890e-01 4.47148055e-01 7.37526953e-01 1.26831996e+00
7.34453082e-01 6.97774291e-01 9.96918082e-01 4.23566289e-02
3.65509719e-01 1.58129349e-01 2.09874421e-01 5.19892693e-01
-3.42564564e-03 2.38303348e-01 -1.75978482e-01 -5.32104671e-01
8.71298313e-01 8.62519681e-01 -4.79360878e-01 2.54790694e-01
-1.50678706e+00 5.14874876e-01 4.24519420e-01 3.77651453e-01
-1.04508150e+00 -1.35309130e-01 6.25942111e-01 6.49141490e-01
1.26482099e-01 1.34467572e-01 -7.64079988e-01 -1.01096928e-01
-5.41731477e-01 -9.01873857e-02 9.36317205e-01 7.44424939e-01
-2.25994334e-01 2.03750376e-02 -4.27509397e-01 4.60588068e-01
3.73949170e-01 6.57896578e-01 1.05427146e+00 -7.37625062e-01
2.63530433e-01 6.73197329e-01 9.81992558e-02 -1.20485938e+00
-1.02119482e+00 -4.57552612e-01 -1.91838574e+00 -5.68013608e-01
8.21307115e-03 -4.20994222e-01 -7.41980076e-01 1.65266323e+00
3.05426329e-01 5.46362996e-01 6.72407866e-01 6.39084756e-01
1.02024925e+00 7.49062240e-01 1.04163863e-01 -7.43385911e-01
1.37319934e+00 -2.41635382e-01 -1.11168134e+00 4.46282446e-01
7.26101816e-01 -3.22226614e-01 9.31729138e-01 2.29154304e-01
-9.52110946e-01 -7.29338109e-01 -6.22428715e-01 3.17728609e-01
-3.78525198e-01 1.66609958e-01 3.13818961e-01 7.69962445e-02
-8.43436122e-01 9.01954532e-01 -1.27745771e+00 -3.33308846e-01
2.26713434e-01 2.06484839e-01 -1.72827363e-01 2.48970941e-01
-1.48879230e+00 4.53539819e-01 2.20032498e-01 3.72254431e-01
-7.14771688e-01 -8.23714375e-01 -8.10959816e-01 1.13219038e-01
-2.98084587e-01 -1.04737616e+00 1.03375483e+00 -6.49478436e-01
-1.17625654e+00 5.13514817e-01 8.80877823e-02 -5.84953487e-01
5.13930440e-01 -5.36161773e-02 -7.72971272e-01 1.21920951e-01
-3.61954242e-01 1.24450736e-01 5.24308324e-01 -8.67838919e-01
-1.04283422e-01 -4.44710851e-01 -4.93369579e-01 4.01045084e-02
-2.86217749e-01 -4.82701838e-01 1.52913541e-01 -6.78819478e-01
2.13074476e-01 -9.00663257e-01 -4.24299061e-01 -1.01843752e-01
-4.81036514e-01 -1.14703961e-01 6.29065454e-01 -7.25376666e-01
1.53922379e+00 -2.42308283e+00 -1.18952431e-01 1.21025018e-01
4.39095229e-01 1.55970231e-01 1.30152181e-02 6.96157396e-01
-2.51639754e-01 -1.86179474e-01 -2.90030509e-01 -2.49154970e-01
-3.17287534e-01 4.53370392e-01 -3.09217900e-01 4.99039441e-01
2.07602650e-01 9.76552129e-01 -8.11819196e-01 -5.14307737e-01
2.08389282e-01 8.67618322e-01 -2.39266530e-01 6.82132065e-01
4.14681472e-02 9.04240131e-01 -7.18549490e-01 6.63353443e-01
3.89790475e-01 -5.72586656e-01 -8.02301466e-02 -3.45880628e-01
-9.46728699e-03 -1.62280366e-01 -1.20660460e+00 1.58328509e+00
-3.82427454e-01 1.00635968e-01 -3.59851062e-01 -1.21813524e+00
9.62994099e-01 1.04309285e+00 1.10197544e+00 -6.32316411e-01
2.27307320e-01 6.21162076e-03 -7.41195353e-03 -1.20072269e+00
-2.68799841e-01 -2.25627676e-01 -4.71833013e-02 1.42696932e-01
-3.85296702e-01 3.93984705e-01 -5.39767444e-01 -6.73518255e-02
1.35822761e+00 -2.55948693e-01 6.08724892e-01 -2.31937438e-01
5.07063210e-01 -1.93152621e-01 7.69309044e-01 7.06683517e-01
-4.19170409e-01 7.13677704e-01 3.61605912e-01 -1.05302203e+00
-8.02134514e-01 -1.07503390e+00 -3.82628500e-01 1.96629524e-01
-2.64333431e-02 -5.31066805e-02 -3.36830407e-01 -3.28842878e-01
9.99838784e-02 2.84238487e-01 -8.60080361e-01 -5.29957056e-01
-4.72870141e-01 -1.00150836e+00 6.18025541e-01 6.58106744e-01
3.14168096e-01 -1.43101645e+00 -1.21433449e+00 6.51156485e-01
-3.22052866e-01 -7.97465205e-01 -3.53265941e-01 1.73098207e-01
-1.32365263e+00 -9.66447651e-01 -8.90026033e-01 -6.80342317e-01
5.45287669e-01 -2.96169639e-01 1.12862837e+00 -4.07130159e-02
-7.09117055e-01 7.77749717e-01 -9.45710689e-02 -5.32186508e-01
-5.36111176e-01 -1.34483054e-01 3.17435980e-01 1.17451817e-01
3.06268185e-01 -6.44848466e-01 -1.09902239e+00 9.34233423e-03
-1.16127813e+00 4.10291627e-02 4.75010097e-01 9.95393574e-01
8.55654895e-01 -2.02166159e-02 9.65765774e-01 -9.44973230e-01
9.65481937e-01 -9.89168882e-01 -1.32172048e-01 2.79772788e-01
-7.44246542e-01 8.94696340e-02 8.82855654e-01 -6.33584440e-01
-6.28474057e-01 1.50072634e-01 -3.37813050e-02 -5.87802827e-01
-5.11328697e-01 7.39790201e-01 3.96380007e-01 6.85523152e-01
7.85975754e-01 5.27382374e-01 8.88941959e-02 -5.84851980e-01
-7.22449347e-02 9.48452353e-01 6.95901811e-01 -3.03531289e-01
3.92601311e-01 4.53166187e-01 1.61597073e-01 -6.05302572e-01
-7.71682322e-01 -5.74518561e-01 -4.49720830e-01 8.30164924e-02
8.54083180e-01 -1.12879443e+00 -1.07945132e+00 4.10191804e-01
-1.06021821e+00 -1.74322516e-01 -7.32569993e-01 6.68233871e-01
-6.43026471e-01 2.49437571e-01 -1.08215666e+00 -1.07773888e+00
-7.93164134e-01 -6.95558846e-01 1.13338804e+00 2.01173797e-01
-2.92828590e-01 -1.32886350e+00 5.38272798e-01 -3.65053207e-01
6.53037786e-01 9.41428840e-01 9.32662904e-01 -6.68211937e-01
-7.83198923e-02 -4.61306304e-01 4.20774613e-03 2.52144456e-01
5.52170277e-01 -3.47118199e-01 -7.61241794e-01 -3.48637998e-01
6.19578779e-01 -4.85278778e-02 4.35971498e-01 7.48517454e-01
1.18120456e+00 -4.98256624e-01 -2.59479940e-01 7.82278895e-01
1.51840174e+00 4.25456166e-01 4.67556566e-01 -1.03978842e-01
4.51331496e-01 3.51632684e-01 2.44968534e-01 1.05198586e+00
7.12305427e-01 7.07746595e-02 2.39402860e-01 -5.03629565e-01
3.05449575e-01 -7.53142834e-02 2.99386680e-01 1.49598300e+00
-1.18753418e-01 4.75509465e-02 -9.13938940e-01 4.23618585e-01
-1.94414759e+00 -9.02860284e-01 -1.33258805e-01 1.97698748e+00
9.41877663e-01 -2.52258062e-01 3.00523918e-02 2.19031453e-01
4.89664197e-01 -2.55969405e-01 -7.90242314e-01 -2.26359650e-01
-6.47095889e-02 -8.63074586e-02 1.32569641e-01 1.69896290e-01
-9.29784298e-01 9.96209607e-02 6.15400743e+00 -7.50384778e-02
-1.27066648e+00 -1.02706924e-01 7.46241510e-01 1.85798690e-01
9.42427516e-02 -6.68321609e-01 -2.32642382e-01 5.82326889e-01
1.29480684e+00 -1.35071337e-01 4.60735798e-01 6.01020753e-01
6.52361512e-01 4.69256133e-01 -1.25401962e+00 1.40496302e+00
-2.82799155e-01 -8.52679729e-01 -2.65541106e-01 -2.76020885e-01
5.72313488e-01 5.14448956e-02 1.38598487e-01 4.23304796e-01
-6.72741532e-02 -1.18400550e+00 -5.29203899e-02 1.15765703e+00
8.67109895e-01 -2.61073798e-01 9.75237668e-01 5.01637161e-01
-1.28271151e+00 -2.22384900e-01 -3.06289375e-01 7.21687973e-02
1.27219364e-01 4.51594830e-01 -6.50984228e-01 5.31040907e-01
5.67618310e-01 1.03772080e+00 -2.72180706e-01 1.01079762e+00
6.73177183e-01 6.89037323e-01 -3.63646418e-01 3.09666246e-01
-7.17473626e-02 3.88904549e-02 4.38188016e-01 1.25368977e+00
5.74186802e-01 5.55945218e-01 2.82744557e-01 7.17404723e-01
2.94247150e-01 1.87874392e-01 -8.49158525e-01 -9.44558159e-02
1.40691832e-01 1.01846194e+00 -1.72905311e-01 -5.86359203e-01
-3.53494138e-01 9.77878273e-01 -2.68799186e-01 5.05931377e-01
-8.32900822e-01 -1.41541734e-01 2.98676193e-01 1.47672132e-01
-2.17982635e-01 9.85110849e-02 -1.01818696e-01 -1.40433013e+00
-2.62344871e-02 -1.00793338e+00 8.35338056e-01 -4.66127425e-01
-1.56182683e+00 8.36538851e-01 -3.12356442e-01 -1.66261840e+00
-2.65088528e-01 -3.45491707e-01 -6.09783888e-01 7.49036849e-01
-1.53007650e+00 -6.61633551e-01 -5.41849792e-01 1.28142560e+00
3.91693056e-01 -8.27069506e-02 1.39676178e+00 5.13259292e-01
-4.77874190e-01 3.46332610e-01 2.92535186e-01 2.44907066e-01
4.71228272e-01 -1.28634584e+00 7.31093138e-02 8.75306204e-02
-2.74482548e-01 6.79191887e-01 6.37379825e-01 -5.94514072e-01
-1.65693545e+00 -1.32651949e+00 7.70280361e-01 -4.89679247e-01
3.08743298e-01 1.22774772e-01 -1.09046817e+00 5.59486806e-01
-2.11267188e-01 5.50171733e-01 8.09156418e-01 -3.62300903e-01
-2.51414385e-02 -2.35249355e-01 -1.37183309e+00 1.17976725e-01
7.27275610e-01 -5.00581443e-01 -8.18505466e-01 3.81834984e-01
7.70372391e-01 -5.50428867e-01 -1.41529095e+00 7.22883880e-01
5.18519998e-01 -4.93822157e-01 9.77613509e-01 -1.16738403e+00
2.77847141e-01 -1.84126899e-01 -2.89660573e-01 -1.34527087e+00
-2.70395070e-01 -7.03313231e-01 -5.63261330e-01 7.17347205e-01
6.00478575e-02 -8.09378207e-01 2.53702402e-01 6.96787536e-01
1.04792573e-01 -1.00226426e+00 -7.73347974e-01 -4.90443617e-01
-2.90434003e-01 -8.83113518e-02 6.42166972e-01 1.22687042e+00
1.51233524e-01 2.38658607e-01 -4.96883035e-01 3.22170824e-01
5.09934962e-01 -6.45891251e-03 2.01073766e-01 -1.47814441e+00
-6.12865865e-01 2.36873925e-02 -4.14966911e-01 -6.37431026e-01
-5.81434071e-01 -6.64712608e-01 -1.28520904e-02 -1.48552501e+00
1.05858788e-01 -3.50996315e-01 -1.06692183e+00 2.21650839e-01
-2.32212082e-01 -3.54948848e-01 -4.88603264e-02 4.18761462e-01
-5.70008278e-01 5.51125348e-01 1.32836413e+00 -6.94133788e-02
-8.02562177e-01 2.94342965e-01 -4.27682698e-01 5.80480218e-01
7.15726972e-01 -4.99846458e-01 -4.10198629e-01 -1.24188296e-01
7.72148743e-02 1.06617725e+00 5.04114509e-01 -1.04557705e+00
1.03221126e-01 -6.49738535e-02 4.00453448e-01 -3.86681348e-01
1.57157138e-01 -1.24704850e+00 4.53344494e-01 9.40807223e-01
-6.21234119e-01 6.56721413e-01 1.50088295e-01 7.76091576e-01
-4.02838588e-01 4.26073492e-01 5.42172492e-01 -2.52960891e-01
1.42245814e-02 6.02769554e-01 -1.51051700e-01 2.40349501e-01
7.22893894e-01 2.45079145e-01 4.88515608e-02 -3.77094954e-01
-1.22335064e+00 2.06927150e-01 -2.14499354e-01 3.82863164e-01
7.46088684e-01 -1.45661855e+00 -8.18684578e-01 3.09479922e-01
1.90719068e-01 2.35876948e-01 5.19280910e-01 1.12551272e+00
-4.37661678e-01 2.30424806e-01 9.18505862e-02 -7.73359299e-01
-9.20592725e-01 8.28086317e-01 4.89992857e-01 -4.46141481e-01
-1.15138841e+00 6.20095134e-02 1.43581063e-01 -4.29107517e-01
5.29596865e-01 -8.37487936e-01 -4.03173238e-01 -1.82542413e-01
5.89519680e-01 5.94581664e-02 -2.99146444e-01 -3.81192625e-01
-2.26601303e-01 5.22676051e-01 3.22033554e-01 3.20106238e-01
1.54732299e+00 -2.44042426e-01 1.78286314e-01 9.74722862e-01
1.31319296e+00 -5.79449713e-01 -9.11936343e-01 -4.08170015e-01
-1.29397914e-01 2.79476285e-01 -2.15644538e-01 -8.00515592e-01
-9.23019230e-01 9.84593987e-01 1.37965226e+00 5.98872721e-01
1.30978823e+00 -2.96166778e-01 1.10901201e+00 6.45466983e-01
-2.82689650e-02 -8.67217243e-01 -4.96533737e-02 1.62495464e-01
7.88678825e-01 -1.30557680e+00 -6.43406272e-01 2.47543588e-01
-7.98586786e-01 1.16746628e+00 1.33848250e-01 -2.08957329e-01
1.09187412e+00 3.65288049e-01 4.28219676e-01 -2.46571958e-01
-1.04495132e+00 2.41839841e-01 1.58069983e-01 4.90269542e-01
5.60943127e-01 3.26410294e-01 -9.17931274e-02 9.40280676e-01
4.71464060e-02 5.79474390e-01 2.94341743e-01 7.74072230e-01
-1.23127699e-01 -4.89482313e-01 -4.00643677e-01 5.08966267e-01
-5.83421230e-01 -4.22617346e-02 3.58164728e-01 3.61773819e-01
9.14551541e-02 7.83998907e-01 -6.46861270e-02 -1.44295439e-01
6.79099381e-01 2.60654449e-01 4.41996455e-02 -3.65811586e-01
-6.46009445e-01 2.91508250e-02 -5.41988015e-01 -6.37652099e-01
-3.17142457e-01 -6.02594376e-01 -1.45087004e+00 1.37736693e-01
1.95755407e-01 -1.51059693e-02 5.25231242e-01 7.39881635e-01
6.86506569e-01 9.86243606e-01 8.85694563e-01 -1.68168426e-01
-1.19992077e+00 -9.33838010e-01 -5.96865416e-01 1.05357373e+00
9.91466820e-01 1.84612498e-02 -2.85059363e-01 4.23062503e-01] | [7.962932109832764, 6.2210307121276855] |
6b87cd1e-f4a7-41b0-b72e-9c8ffdc2f3e7 | multimodal-unsupervised-image-to-image | 1804.04732 | null | http://arxiv.org/abs/1804.04732v2 | http://arxiv.org/pdf/1804.04732v2.pdf | Multimodal Unsupervised Image-to-Image Translation | Unsupervised image-to-image translation is an important and challenging
problem in computer vision. Given an image in the source domain, the goal is to
learn the conditional distribution of corresponding images in the target
domain, without seeing any pairs of corresponding images. While this
conditional distribution is inherently multimodal, existing approaches make an
overly simplified assumption, modeling it as a deterministic one-to-one
mapping. As a result, they fail to generate diverse outputs from a given source
domain image. To address this limitation, we propose a Multimodal Unsupervised
Image-to-image Translation (MUNIT) framework. We assume that the image
representation can be decomposed into a content code that is domain-invariant,
and a style code that captures domain-specific properties. To translate an
image to another domain, we recombine its content code with a random style code
sampled from the style space of the target domain. We analyze the proposed
framework and establish several theoretical results. Extensive experiments with
comparisons to the state-of-the-art approaches further demonstrates the
advantage of the proposed framework. Moreover, our framework allows users to
control the style of translation outputs by providing an example style image.
Code and pretrained models are available at https://github.com/nvlabs/MUNIT | ['Ming-Yu Liu', 'Serge Belongie', 'Jan Kautz', 'Xun Huang'] | 2018-04-12 | multimodal-unsupervised-image-to-image-1 | http://openaccess.thecvf.com/content_ECCV_2018/html/Xun_Huang_Multimodal_Unsupervised_Image-to-image_ECCV_2018_paper.html | http://openaccess.thecvf.com/content_ECCV_2018/papers/Xun_Huang_Multimodal_Unsupervised_Image-to-image_ECCV_2018_paper.pdf | eccv-2018-9 | ['multimodal-unsupervised-image-to-image'] | ['computer-vision'] | [ 7.21894443e-01 -1.42148614e-01 -1.08276501e-01 -6.75669730e-01
-7.34961629e-01 -9.87166524e-01 6.51046991e-01 -3.82675409e-01
-1.14993013e-01 6.29848421e-01 -1.30226508e-01 -1.70558542e-02
1.61341444e-01 -7.58792281e-01 -1.03034270e+00 -8.43537569e-01
7.33345628e-01 7.12677419e-01 -9.70441103e-02 -2.01744940e-02
1.19079933e-01 2.16929466e-01 -1.29990804e+00 3.85482967e-01
8.84505510e-01 7.44964600e-01 5.34264565e-01 7.04619527e-01
-2.49226958e-01 5.80978513e-01 -4.77608562e-01 -4.40936565e-01
2.37500623e-01 -9.43903983e-01 -6.88900173e-01 6.13453805e-01
6.82075500e-01 -2.34453648e-01 -2.54994363e-01 1.56383276e+00
1.61414921e-01 5.02241924e-02 1.03323555e+00 -1.52988386e+00
-1.27215850e+00 1.46080449e-01 -4.52662498e-01 -4.66858149e-01
2.51019955e-01 7.23122358e-02 7.92106271e-01 -8.90545189e-01
9.57639694e-01 1.20527935e+00 -5.66931255e-03 7.25605905e-01
-1.73158526e+00 -4.65347797e-01 -5.24469838e-02 -2.30254307e-01
-1.29873180e+00 -4.02334392e-01 9.66812849e-01 -5.61472416e-01
1.26384079e-01 8.07132870e-02 2.92738199e-01 1.17510033e+00
1.42696910e-02 7.54098892e-01 1.41775298e+00 -5.83623111e-01
2.64310658e-01 4.45992410e-01 -3.61184269e-01 6.49864852e-01
6.76134676e-02 1.28254592e-01 -5.90885818e-01 2.84643695e-02
1.03322446e+00 1.28688902e-01 -2.41218686e-01 -8.65503013e-01
-1.38569760e+00 8.00626516e-01 5.40821433e-01 1.07997298e-01
-5.94549589e-02 5.99372759e-02 -6.24133572e-02 5.00567675e-01
1.33206800e-01 1.13072798e-01 -5.10896556e-02 1.12069860e-01
-8.84007633e-01 2.32740521e-01 6.45782351e-01 1.34826291e+00
1.13126504e+00 -5.07480577e-02 -6.33841306e-02 8.91283870e-01
2.70824790e-01 9.57346916e-01 2.58528471e-01 -1.03529358e+00
5.02635002e-01 4.73615706e-01 1.64057404e-01 -9.85110641e-01
3.18027020e-01 -1.26475632e-01 -9.57115650e-01 4.56139386e-01
5.14966309e-01 -2.36430839e-02 -9.85631585e-01 1.90386009e+00
8.62002075e-02 -1.57341719e-01 2.07223624e-01 9.91382360e-01
5.56138277e-01 8.44191670e-01 -1.71599984e-01 -1.28105888e-02
1.12927973e+00 -9.96453285e-01 -6.05863094e-01 -3.43147874e-01
2.67287306e-02 -1.05171096e+00 1.37739587e+00 1.66160360e-01
-1.07719505e+00 -6.71260178e-01 -8.17284465e-01 -1.88681647e-01
-2.22117022e-01 4.40930545e-01 9.37023535e-02 4.71220016e-01
-1.13022709e+00 8.98755938e-02 -4.73991752e-01 -6.41447365e-01
2.88105249e-01 1.80314466e-01 -5.82348943e-01 -2.93012440e-01
-8.69034767e-01 6.36578560e-01 3.47528219e-01 -2.74448156e-01
-1.05878234e+00 -2.32628062e-01 -8.30798090e-01 -1.99096590e-01
9.17425901e-02 -9.47163820e-01 1.35070682e+00 -1.76953983e+00
-1.58442163e+00 1.14906096e+00 -5.14779925e-01 -5.15547022e-02
5.39699197e-01 2.50738245e-02 -1.27241582e-01 4.02441114e-01
2.28263974e-01 1.05407596e+00 1.23628283e+00 -1.85365129e+00
-4.82419789e-01 -1.69329241e-01 1.70726836e-01 4.12931442e-01
-3.58769357e-01 -6.33234605e-02 -7.37484872e-01 -7.37174988e-01
4.70654741e-02 -1.09296465e+00 8.32206905e-02 3.49801302e-01
-5.97142696e-01 3.64472359e-01 8.40585887e-01 -4.37925100e-01
7.32096732e-01 -2.29391527e+00 5.64708591e-01 1.59042835e-01
3.60698439e-03 -1.59700215e-01 -3.45310211e-01 4.68725592e-01
1.24849472e-02 -5.76870143e-02 -7.29045451e-01 -5.03615499e-01
1.11939823e-02 3.90975714e-01 -3.62254709e-01 3.54846835e-01
3.60728025e-01 9.08637285e-01 -9.00064766e-01 -6.26609027e-01
2.07523093e-01 5.26368916e-01 -4.60358113e-01 5.09927332e-01
-3.15533102e-01 8.81295323e-01 -3.56903255e-01 5.42891383e-01
8.21898341e-01 -2.65506983e-01 2.56127983e-01 -2.75025755e-01
1.18177995e-01 -3.32479656e-01 -9.80428576e-01 1.86280739e+00
-3.93950135e-01 7.42991209e-01 -5.51022440e-02 -1.03153920e+00
1.10569024e+00 1.38755113e-01 1.82975739e-01 -5.12521267e-01
9.56812277e-02 1.73933804e-01 -1.75275296e-01 -4.08555567e-01
4.76501256e-01 -4.25311923e-01 -2.72690594e-01 4.58407879e-01
1.77022189e-01 -5.07971704e-01 1.37090757e-01 2.75307119e-01
5.15676141e-01 3.38725030e-01 -9.60463099e-03 -1.64206326e-01
5.02048254e-01 8.03985745e-02 3.33811283e-01 6.32144332e-01
-5.51664792e-02 1.14469695e+00 5.86582482e-01 -1.22233734e-01
-1.28657413e+00 -1.61688304e+00 8.81597102e-02 8.86639476e-01
4.51966345e-01 2.74915621e-02 -9.80141878e-01 -5.31444848e-01
-2.22573012e-01 5.87073565e-01 -6.68157578e-01 7.95793999e-03
-2.96050310e-01 -1.85554042e-01 4.32602912e-01 2.04958051e-01
8.06177616e-01 -1.01511621e+00 -4.12461042e-01 -1.92813218e-01
-5.42102337e-01 -1.15651226e+00 -9.27941620e-01 -1.60018355e-01
-7.90440142e-01 -8.47483993e-01 -1.09386158e+00 -1.27619767e+00
1.31978655e+00 2.92173564e-01 1.20544612e+00 -2.73597568e-01
2.20034309e-02 7.63654351e-01 -2.49372452e-01 -3.30952704e-02
-7.40445793e-01 -8.69335234e-02 -1.01575553e-01 5.06907523e-01
2.93626692e-02 -4.46874797e-01 -6.53752148e-01 4.24538672e-01
-1.41920757e+00 4.26702738e-01 6.07217669e-01 8.89564276e-01
8.26690376e-01 -9.78415608e-02 2.90385604e-01 -9.55238938e-01
5.94568968e-01 -3.10607702e-01 -5.09828925e-01 3.49931717e-01
-1.65576607e-01 1.76979005e-01 6.55288219e-01 -6.10019088e-01
-1.25708222e+00 5.93525887e-01 4.67319727e-01 -5.85844517e-01
-2.92469203e-01 3.30082119e-01 -4.54778969e-01 2.53431052e-02
6.51654482e-01 6.17511272e-01 3.16366553e-01 -2.82068253e-01
6.90652490e-01 6.40619040e-01 8.58256578e-01 -8.79795730e-01
1.15040362e+00 5.93764782e-01 -2.30937272e-01 -7.10072994e-01
-5.14169514e-01 -8.14290121e-02 -7.98564911e-01 -2.15266347e-01
9.70608771e-01 -8.82973671e-01 -2.43110076e-01 4.27902460e-01
-1.27387905e+00 -4.34487581e-01 -1.17491648e-01 1.16708592e-01
-8.89307857e-01 1.93990216e-01 -1.81607544e-01 -5.78537583e-01
5.40089495e-02 -1.28125274e+00 1.13812423e+00 3.71459156e-01
-8.43554661e-02 -1.01845098e+00 -4.29502875e-02 1.42570376e-01
4.21826094e-01 4.01269138e-01 9.25978243e-01 -9.27353352e-02
-7.63023496e-01 -1.01335030e-02 -3.89923781e-01 5.20378292e-01
4.04488683e-01 1.13484003e-01 -6.77667618e-01 -2.13030219e-01
-4.31282446e-02 -4.76837099e-01 6.17320895e-01 1.65346175e-01
8.95591676e-01 -1.75809249e-01 -5.39267510e-02 6.29137933e-01
1.68381786e+00 1.52041137e-01 6.63180828e-01 1.04833409e-01
7.59111106e-01 6.29666150e-01 4.42302704e-01 9.44011137e-02
4.12872910e-01 7.53279388e-01 3.08313787e-01 -2.69834995e-01
-2.02877313e-01 -5.98721623e-01 5.06728888e-01 4.58395004e-01
1.35270461e-01 -2.29361728e-01 -6.06034458e-01 6.13995850e-01
-1.77061522e+00 -8.24632645e-01 1.10111937e-01 2.26571131e+00
9.26926136e-01 -1.51569128e-01 2.09749918e-02 -3.28531623e-01
1.00667596e+00 -5.70067242e-02 -6.23671472e-01 -3.70663702e-01
-3.34108770e-01 1.01296417e-03 2.47973919e-01 5.93875289e-01
-1.05974293e+00 1.05922055e+00 5.86569309e+00 7.18195081e-01
-1.31392479e+00 -1.13288881e-02 7.26786017e-01 1.33647174e-01
-5.07929683e-01 1.60919219e-01 -3.03202868e-01 4.65146810e-01
4.64859039e-01 -3.63263786e-01 7.22581565e-01 7.43397951e-01
8.53869244e-02 -8.00470337e-02 -1.23947346e+00 1.19697118e+00
2.12158233e-01 -1.18808115e+00 4.80852544e-01 -3.24761346e-02
1.07993960e+00 -3.26290041e-01 4.48618352e-01 -4.21313159e-02
2.61745900e-01 -9.64980304e-01 9.35543299e-01 6.88734055e-01
1.29669213e+00 -5.69418371e-01 2.32972637e-01 2.11403802e-01
-1.01022315e+00 2.13542953e-01 -4.45681036e-01 1.43853009e-01
3.96487489e-02 3.45290273e-01 -4.76094723e-01 5.20228148e-01
4.92237866e-01 7.02900946e-01 -5.44812918e-01 7.55491138e-01
-3.95606279e-01 3.65554780e-01 -8.57317261e-03 2.43118331e-01
1.13508537e-01 -5.40272117e-01 4.26346719e-01 1.05270362e+00
5.50192714e-01 -2.08911389e-01 1.89785436e-01 1.32529569e+00
-3.47126305e-01 9.30208489e-02 -9.90606189e-01 -6.46347180e-02
4.16966200e-01 1.14568925e+00 -6.28278792e-01 -5.32694638e-01
-4.04163599e-01 1.69544482e+00 2.03069866e-01 7.82448053e-01
-8.07853699e-01 -3.64169478e-01 5.87632835e-01 -1.25139192e-01
2.17792094e-01 -2.30175301e-01 -3.92866611e-01 -1.35607767e+00
1.53013408e-01 -1.03184807e+00 3.74638699e-02 -1.11921310e+00
-1.34959972e+00 8.24388564e-01 1.75477400e-01 -1.66462278e+00
-1.46524474e-01 -5.45413852e-01 -5.45277476e-01 9.93740678e-01
-1.28875446e+00 -1.38373232e+00 -4.77372825e-01 8.95603359e-01
6.05271101e-01 -2.67928958e-01 8.10071290e-01 1.06261648e-01
-6.69867620e-02 5.77325761e-01 3.73608768e-01 2.73979425e-01
1.02369440e+00 -1.28961802e+00 1.92992702e-01 8.13186109e-01
2.50063658e-01 6.31009579e-01 7.07001388e-01 -4.99303758e-01
-1.38678229e+00 -1.16003835e+00 6.96605265e-01 -5.09162664e-01
4.04285908e-01 -4.56844270e-01 -7.34848440e-01 6.33282483e-01
5.86957157e-01 -4.01570499e-02 3.90455812e-01 -5.90837061e-01
-4.78018641e-01 -1.39418453e-01 -1.16598034e+00 8.58521104e-01
8.85087132e-01 -6.71958983e-01 -4.54317689e-01 1.37737870e-01
5.24853826e-01 -4.50032264e-01 -5.64015627e-01 1.36348307e-02
5.61723471e-01 -1.05221009e+00 8.25127721e-01 -2.54691541e-01
8.64019394e-01 -6.72514021e-01 -4.02725607e-01 -1.36448264e+00
-1.29694641e-01 -5.59827983e-01 4.16934282e-01 1.32978058e+00
4.23587680e-01 -5.10226190e-01 6.37341142e-01 6.18021429e-01
2.73634136e-01 -3.16039801e-01 -6.25438452e-01 -7.68938184e-01
3.47382396e-01 -1.44205913e-01 4.53196704e-01 8.10240149e-01
-3.29455733e-01 4.70209062e-01 -5.94772637e-01 2.40221620e-01
7.95902014e-01 4.47778493e-01 1.04337680e+00 -8.20806205e-01
-4.20927048e-01 -3.17536533e-01 -2.65060902e-01 -1.25991726e+00
1.68892086e-01 -9.40575480e-01 2.28440776e-01 -1.52922261e+00
4.40555066e-01 -2.03255981e-01 3.08284629e-03 3.18868458e-01
-6.71181269e-03 5.97675860e-01 4.94083583e-01 4.88667130e-01
-3.59903663e-01 5.82330942e-01 1.55640185e+00 -4.32275414e-01
-6.18789867e-02 -2.39349574e-01 -8.06839108e-01 5.12228131e-01
9.72134888e-01 -4.60530251e-01 -7.72527039e-01 -7.98485339e-01
-8.40458721e-02 1.19277038e-01 5.05771399e-01 -7.30587602e-01
1.37856692e-01 -4.61574137e-01 4.26153421e-01 -2.94354320e-01
2.93498218e-01 -9.05768931e-01 3.43610644e-01 1.33704871e-01
-5.44033885e-01 2.41453163e-02 -8.89016036e-03 4.67711568e-01
-5.11682332e-01 -1.52183279e-01 9.94693279e-01 -8.44296739e-02
-5.39133430e-01 2.65876204e-01 -2.06908390e-01 1.52056105e-04
9.15608168e-01 -3.14992040e-01 -2.40353316e-01 -7.09087074e-01
-6.74818099e-01 -1.02589734e-01 1.08505440e+00 4.87147987e-01
8.75397801e-01 -1.72159100e+00 -7.37088382e-01 4.33140337e-01
4.66183245e-01 -6.58540428e-02 1.51000693e-01 4.92109060e-01
-6.07205391e-01 2.53477506e-02 -4.66259867e-01 -8.75886798e-01
-1.21843636e+00 4.72591966e-01 2.36042589e-01 1.42200321e-01
-3.75170678e-01 5.74826241e-01 8.48261356e-01 -6.43301129e-01
-5.55499047e-02 -8.42967331e-02 2.40147606e-01 -3.60971153e-01
3.22696686e-01 -1.99734330e-01 -4.52368736e-01 -9.79965448e-01
-1.92242682e-01 8.92668426e-01 1.62764132e-01 -5.84136486e-01
8.91214967e-01 -3.96744937e-01 -2.77324319e-01 4.23288077e-01
1.43304729e+00 -1.31839335e-01 -1.42967582e+00 -3.90134752e-01
-3.12031031e-01 -7.18985617e-01 -4.04713094e-01 -7.67286599e-01
-1.08934999e+00 9.40538526e-01 6.17780089e-01 5.25319949e-04
1.41993475e+00 4.62471060e-02 4.51559782e-01 2.37515330e-01
2.55290121e-01 -9.07176852e-01 4.26415086e-01 4.02640194e-01
1.12300003e+00 -1.25579667e+00 -4.75339115e-01 -3.17347944e-01
-1.09728992e+00 1.16849375e+00 5.33207178e-01 -2.51838535e-01
3.67663801e-01 -5.91807999e-02 4.25800145e-01 1.00746289e-01
-4.46555376e-01 -2.13280156e-01 3.30505997e-01 9.25246596e-01
3.98328543e-01 1.75247848e-01 1.08787283e-01 1.88079417e-01
-1.50639519e-01 1.32053196e-01 5.81906974e-01 7.32310414e-01
-2.11680591e-01 -1.46565413e+00 -7.37695217e-01 -7.45169912e-03
-6.28176704e-02 -4.64827120e-02 -5.52575946e-01 4.87465233e-01
8.91396105e-02 9.19818282e-01 3.30147259e-02 -2.79706895e-01
2.71382868e-01 1.12249136e-01 6.40911758e-01 -6.05507851e-01
3.99085507e-02 2.00504482e-01 -4.16664839e-01 -2.92783260e-01
-5.49299300e-01 -5.71545005e-01 -1.05198991e+00 -1.61458254e-01
2.46448800e-01 -1.01592526e-01 5.54399848e-01 5.71723104e-01
3.08221757e-01 2.84828246e-01 7.66829193e-01 -9.83197272e-01
-2.10233092e-01 -6.42056227e-01 -4.84551638e-01 9.19444025e-01
4.05989945e-01 -6.15664482e-01 -2.07143173e-01 9.78987038e-01] | [11.661535263061523, -0.3345124125480652] |
48de4ec3-8d86-4e50-aaa6-d5759062ce05 | a-short-review-on-applications-of-deep | 1812.06292 | null | http://arxiv.org/abs/1812.06292v2 | http://arxiv.org/pdf/1812.06292v2.pdf | A short review on Applications of Deep learning for Cyber security | Deep learning is an advanced model of traditional machine learning. This has
the capability to extract optimal feature representation from raw input
samples. This has been applied towards various use cases in cyber security such
as intrusion detection, malware classification, android malware detection, spam
and phishing detection and binary analysis. This paper outlines the survey of
all the works related to deep learning based solutions for various cyber
security use cases. Keywords: Deep learning, intrusion detection, malware
detection, Android malware detection, spam & phishing detection, traffic
analysis, binary analysis. | ['Soman Kp', 'Vinayakumar R', 'Mohammed Harun Babu R'] | 2018-12-15 | null | null | null | null | ['android-malware-detection'] | ['miscellaneous'] | [ 6.19868599e-02 -2.60303736e-01 -5.62654376e-01 -1.35819539e-01
3.92951757e-01 -5.77806532e-01 6.68290496e-01 2.33426586e-01
-1.17494568e-01 5.75521767e-01 -2.59681791e-01 -1.10202527e+00
-5.95861785e-02 -6.55212462e-01 -9.85398516e-02 -4.05948550e-01
-2.69283712e-01 1.56753421e-01 6.42821416e-02 -3.34009349e-01
8.13641787e-01 8.06307077e-01 -1.30147576e+00 3.80993098e-01
3.95168304e-01 1.10243642e+00 -4.51652020e-01 1.32910919e+00
-2.35364273e-01 5.09831309e-01 -1.03360605e+00 -3.88671428e-01
1.89765483e-01 3.10891289e-02 -7.17497230e-01 -3.53674293e-01
6.53068796e-02 -2.89846510e-01 -4.58689153e-01 1.12093639e+00
4.06129599e-01 -2.28193891e-03 8.57313633e-01 -1.47575212e+00
-6.46297097e-01 -2.10963599e-02 -7.94063389e-01 1.04906499e+00
5.21428287e-01 3.96986604e-02 1.29764900e-01 -5.90421140e-01
1.59989700e-01 1.33313084e+00 8.96589816e-01 5.27109563e-01
-4.19004142e-01 -8.32384586e-01 -4.20847297e-01 4.63690192e-01
-8.18170249e-01 -9.30047631e-02 4.51375812e-01 -4.85990226e-01
1.36517072e+00 2.23685905e-01 6.57998145e-01 1.49087548e+00
1.12714016e+00 6.22457623e-01 1.14879048e+00 -2.10441619e-01
1.13058768e-01 3.47623914e-01 9.20455515e-01 6.14086270e-01
4.47728455e-01 7.13194847e-01 1.08651429e-01 -5.50447285e-01
1.28903240e-01 4.50041294e-01 4.07614022e-01 5.06691873e-01
-3.05665672e-01 1.16232705e+00 3.81509751e-01 4.93471593e-01
-2.83731014e-01 -8.46141800e-02 1.13974285e+00 8.22232604e-01
2.01079965e-01 2.97134429e-01 -1.09601951e+00 -3.72660935e-01
-5.65740108e-01 7.81266242e-02 1.08429241e+00 3.81745487e-01
5.62253177e-01 6.59756601e-01 5.03685415e-01 6.39132619e-01
7.53867507e-01 4.38469172e-01 1.19913852e+00 -4.91637737e-01
-1.60889089e-01 7.38047600e-01 -5.32186568e-01 -1.13083971e+00
-4.62503821e-01 2.03665514e-02 -5.69001555e-01 4.24080878e-01
-1.76629260e-01 -5.57731628e-01 -1.13044453e+00 6.34102583e-01
3.44119549e-01 8.01307142e-01 1.51382416e-01 -2.59917021e-01
8.43126059e-01 7.80898511e-01 1.78006470e-01 3.65582891e-02
1.59718049e+00 -4.21857268e-01 -5.27622104e-01 -3.46209168e-01
3.37588668e-01 -9.00497973e-01 7.98422933e-01 5.16010106e-01
-2.95434505e-01 -4.21319455e-01 -1.15191841e+00 1.66872233e-01
-1.43583274e+00 -2.86991477e-01 1.05395901e+00 1.61870229e+00
-7.24114716e-01 4.53842789e-01 -8.45483422e-01 -4.70470995e-01
9.80327547e-01 9.88797843e-01 -2.17198491e-01 1.17705896e-01
-9.43204165e-01 9.78027940e-01 6.72457755e-01 -4.41219836e-01
-1.08882463e+00 -1.18353851e-01 -8.46477926e-01 1.39946729e-01
2.33152151e-01 3.13597955e-02 1.33628666e+00 -8.60180259e-01
-1.44989932e+00 8.07834566e-01 1.02001816e-01 -7.43587852e-01
-3.42609823e-01 -2.23638847e-01 -7.88182735e-01 -4.33628321e-01
-4.09919530e-01 -5.92749603e-02 1.27921009e+00 -6.18834198e-01
-3.89149338e-01 -7.89410949e-01 -1.93653002e-01 -3.82551163e-01
-3.77191484e-01 3.02000850e-01 6.27073169e-01 -3.96716028e-01
-6.43658161e-01 -9.99395847e-01 -1.09421194e-01 -9.32174146e-01
-4.06895697e-01 -3.19623142e-01 2.36622405e+00 -8.58601093e-01
9.48767066e-01 -2.06573820e+00 -3.40587795e-01 3.21379781e-01
2.48242766e-01 1.22714460e+00 1.14335768e-01 4.08735752e-01
-1.77333444e-01 5.08902907e-01 -1.87531603e-03 3.37970257e-01
-3.89269799e-01 1.59687638e-01 6.38821796e-02 4.38357472e-01
-1.38815558e-02 1.05255997e+00 -6.74603343e-01 -2.69161552e-01
6.92949891e-01 5.42156875e-01 -1.56440765e-01 -6.68419003e-02
-5.67552559e-02 1.61656260e-01 -5.37864983e-01 1.19381905e+00
5.04294217e-01 8.49637911e-02 1.92372911e-02 1.74184769e-01
2.43896037e-01 1.15003780e-01 -5.39366901e-01 6.70135617e-01
-7.43359745e-01 1.23454809e+00 2.30350196e-02 -1.19466603e+00
8.80792677e-01 2.11581931e-01 4.42121327e-01 -2.77553856e-01
9.79905725e-01 3.12700093e-01 6.90048337e-01 -7.80114770e-01
3.35141093e-01 2.32572988e-01 -1.07905001e-03 7.44975567e-01
3.24997634e-01 5.60653090e-01 -1.78306729e-01 -4.60926406e-02
1.18307722e+00 -5.36974132e-01 8.62276793e-01 -8.81491229e-02
1.08138967e+00 -4.38016444e-01 4.65253554e-02 5.07408440e-01
-7.48132169e-01 -4.29775476e-01 4.55045760e-01 -7.85472989e-01
-7.08361566e-01 -8.36124897e-01 -6.65415600e-02 1.31043756e+00
-3.37847024e-01 -2.10796326e-01 -9.93240893e-01 -1.50785303e+00
-8.09810981e-02 3.79187763e-01 -6.82850778e-01 -7.49439597e-01
-9.56738532e-01 -9.04822052e-01 7.85774350e-01 3.01131010e-01
7.78288782e-01 -1.45810771e+00 -6.80842757e-01 1.40491694e-01
7.08813310e-01 -9.50078011e-01 1.70386985e-01 2.50529468e-01
-9.54955339e-01 -1.71155357e+00 -5.45108505e-02 -8.13861072e-01
1.43447325e-01 7.37677887e-02 8.15579653e-01 4.05650407e-01
-8.39669466e-01 3.67766559e-01 -4.69583213e-01 -9.38802421e-01
-6.04144156e-01 3.38834792e-01 2.87435025e-01 -4.01021063e-01
1.11641729e+00 -3.87264520e-01 -1.80362314e-01 -8.83463621e-02
-9.43274558e-01 -1.36957192e+00 5.80465376e-01 8.98830593e-01
-3.64364773e-01 5.57407439e-01 6.17548287e-01 -1.05627704e+00
1.29790378e+00 -9.67299461e-01 -4.10854906e-01 -1.29360676e-01
-7.04825521e-01 -3.44401032e-01 7.65848756e-01 -7.70768046e-01
-6.56029046e-01 -1.28906980e-01 -6.86389446e-01 2.77848393e-02
-5.61789215e-01 2.56353021e-01 -1.35665238e-01 -5.98256588e-01
9.95045662e-01 3.18156540e-01 2.89834321e-01 -5.29643297e-01
8.23711604e-03 1.23259115e+00 4.17817533e-02 1.33860543e-01
5.93094468e-01 -2.40923520e-02 8.53036344e-02 -1.36100161e+00
-1.64685130e-01 -4.69943106e-01 -7.27689266e-01 9.20922905e-02
8.06534529e-01 -1.39974743e-01 -1.11346114e+00 8.92371297e-01
-1.02511907e+00 6.64242432e-02 1.76333174e-01 1.67473271e-01
-2.37600394e-02 4.32892263e-01 -8.27132225e-01 -8.57118130e-01
-6.16444528e-01 -1.17306864e+00 8.39006245e-01 5.61354220e-01
-2.07930818e-01 -1.57588756e+00 1.58321723e-01 1.33906782e-01
6.85285807e-01 3.84932280e-01 8.10094953e-01 -1.52405107e+00
2.19903618e-01 -9.50680673e-01 -1.59385502e-01 7.20911682e-01
5.40957570e-01 2.44719833e-01 -9.23029423e-01 -8.55455771e-02
3.61142606e-01 -1.00043349e-01 7.54840493e-01 5.67951739e-01
1.28630090e+00 -7.24519372e-01 -6.61114216e-01 6.33511543e-01
1.30551457e+00 1.06560457e+00 8.22304547e-01 4.76149112e-01
8.34988654e-01 4.53397125e-01 2.98550457e-01 2.16196448e-01
-2.62600005e-01 8.96195788e-03 6.60570025e-01 3.52720559e-01
3.53358626e-01 4.72743005e-01 6.08942509e-01 9.39044282e-02
1.91046000e-01 -1.53130546e-01 -1.10789740e+00 -1.90120950e-01
-1.26628375e+00 -9.20440853e-01 -1.98115990e-01 1.74517715e+00
4.43932414e-02 8.90480205e-02 4.14339870e-01 7.92561769e-01
6.42804086e-01 2.75792390e-01 -5.97970426e-01 -1.40987682e+00
6.40981317e-01 6.90375984e-01 5.85551441e-01 4.85133678e-01
-1.42569387e+00 1.37282026e+00 6.96337652e+00 6.79285109e-01
-1.59537828e+00 5.43654442e-01 7.64583528e-01 3.54166120e-01
6.06763124e-01 -4.12417054e-01 -1.00287974e+00 7.67780125e-01
1.75311816e+00 -1.54487535e-01 2.95015335e-01 1.16569376e+00
-1.32033393e-01 -1.62181221e-02 -6.54933631e-01 9.57297266e-01
2.06703946e-01 -1.19825721e+00 -1.70659095e-01 5.52474797e-01
5.44166684e-01 1.71517551e-01 5.46098650e-01 7.66957045e-01
2.60391645e-02 -1.30960286e+00 -5.40698886e-01 -9.15324315e-02
2.77580917e-01 -1.21818340e+00 1.08810949e+00 1.41428709e-01
-8.11441481e-01 -8.59897912e-01 -2.22423002e-01 -2.55998105e-01
-2.66605616e-02 3.02255571e-01 -1.36213124e+00 -1.10367827e-01
5.50267637e-01 8.72431874e-01 -7.49452889e-01 6.86451077e-01
1.90691322e-01 6.56081438e-01 4.22395691e-02 -4.39314991e-01
5.69624722e-01 1.27444714e-01 4.27397221e-01 1.30615127e+00
1.71641856e-02 -2.18889728e-01 2.15321228e-01 2.03654677e-01
9.23500806e-02 -7.60308355e-02 -1.19430888e+00 -6.03210390e-01
1.89256325e-01 1.31603813e+00 -8.92331421e-01 -5.84397614e-01
-2.06705436e-01 5.69782794e-01 -4.81936723e-01 3.53132077e-02
-6.34821475e-01 -1.03290045e+00 1.08907640e+00 1.74736455e-01
-4.29876894e-02 -3.81198883e-01 -4.79912996e-01 -9.25301433e-01
-7.23572135e-01 -1.32200599e+00 5.43118238e-01 1.12643294e-01
-1.07908511e+00 6.08663678e-01 1.33190364e-01 -7.46921599e-01
-6.64387643e-01 -1.52863073e+00 -1.23751140e+00 4.00876582e-01
-8.32267046e-01 -9.19000328e-01 -1.39801547e-01 7.21128583e-01
9.54994798e-01 -1.28359747e+00 5.46495020e-01 3.94618899e-01
-6.88744843e-01 4.16365534e-01 1.02424053e-02 1.88027084e-01
-2.83165220e-02 -1.14767861e+00 7.15786755e-01 6.24301553e-01
9.07923561e-03 8.28342378e-01 4.25442994e-01 -9.22015786e-01
-1.33520734e+00 -8.13596368e-01 1.89118132e-01 -4.61590320e-01
5.74197829e-01 -3.10536563e-01 -7.99134731e-01 7.63488352e-01
4.10227895e-01 -2.08041966e-02 1.16534901e+00 5.73639274e-02
-2.88240284e-01 -2.40785927e-02 -1.69031072e+00 2.07817897e-01
1.24477744e-01 -4.75698411e-01 -2.02438980e-01 5.94008803e-01
3.48701537e-01 -1.13782860e-01 -5.65479815e-01 1.55046329e-01
7.63874114e-01 -9.83182609e-01 1.29026270e+00 -1.12658620e+00
7.03810230e-02 3.42599213e-01 5.35257980e-02 -8.96173656e-01
-3.15471515e-02 -4.79977876e-01 -1.06898391e+00 7.21803844e-01
8.23852420e-02 -8.43668699e-01 1.14346707e+00 -4.92191054e-02
-8.85365605e-02 -8.98727715e-01 -8.38698089e-01 -6.96842670e-01
9.49077532e-02 -4.24509495e-01 6.69093609e-01 1.03962314e+00
-3.64884675e-01 4.51174498e-01 -4.44510102e-01 -1.50181219e-01
3.95648688e-01 -8.57785881e-01 5.88233471e-01 -1.51527047e+00
-2.49224782e-01 -6.57233775e-01 -9.30193126e-01 -1.96115747e-01
4.63692725e-01 -3.03724557e-01 -5.62287688e-01 -1.13844287e+00
-4.06253040e-01 -6.62597194e-02 -2.24507079e-01 3.87607783e-01
2.80924439e-01 4.11166936e-01 -1.52701125e-01 -2.63989389e-01
-2.18136504e-01 -9.28091928e-02 6.16445482e-01 -3.39970887e-01
-5.09050131e-01 7.04633474e-01 -6.83859408e-01 1.12561381e+00
1.38305891e+00 -4.73638266e-01 -3.90046418e-01 3.30533713e-01
-1.36813864e-01 -4.27529901e-01 2.05326989e-01 -7.66156018e-01
-2.10578084e-01 -2.39276245e-01 7.08700120e-01 -4.21584666e-01
4.78594840e-01 -8.28721344e-01 -6.19733334e-01 1.22827518e+00
2.60414094e-01 3.23080510e-01 4.51669455e-01 5.96242666e-01
8.11104998e-02 -5.16665161e-01 1.12730134e+00 -3.05230528e-01
-1.15985346e+00 3.63816142e-01 -1.04127896e+00 -6.28074110e-01
1.69066882e+00 -5.76198637e-01 -4.34984297e-01 -1.57426119e-01
-7.30569541e-01 -4.22580749e-01 -9.86143425e-02 7.49902904e-01
8.85170102e-01 -9.55860019e-01 -1.62705824e-01 4.44455922e-01
-4.38911349e-01 -9.47727203e-01 -2.38765225e-01 5.13223052e-01
-7.96518087e-01 6.12234354e-01 -8.59807611e-01 -1.79095015e-01
-1.93073261e+00 8.25696409e-01 2.67388940e-01 -2.02336118e-01
-7.67662898e-02 6.26193643e-01 -5.89995086e-01 -3.13403517e-01
1.79795712e-01 9.61225256e-02 -8.52506697e-01 -2.78647095e-01
8.69495392e-01 1.15183139e+00 -7.52919987e-02 -8.91231894e-01
-5.31732440e-01 2.67326415e-01 -6.35087729e-01 4.18985009e-01
9.17176127e-01 3.85266453e-01 -2.71073610e-01 5.08442037e-02
1.77693534e+00 -3.38542968e-01 -3.14798534e-01 5.09386599e-01
4.46691573e-01 -5.93227744e-01 1.99047429e-03 -8.34510684e-01
-9.77174461e-01 1.21013463e+00 1.24918211e+00 9.11640942e-01
8.72814119e-01 -4.18322861e-01 1.15400028e+00 9.26922739e-01
4.76168022e-02 -9.82521355e-01 3.61786574e-01 1.06148279e+00
3.64742696e-01 -1.75505674e+00 5.65107502e-02 -3.48809026e-02
-1.51362538e-01 1.32907104e+00 8.93738747e-01 -7.13466167e-01
1.52591646e+00 5.94270051e-01 -1.84536159e-01 -6.18563235e-01
-2.48659998e-01 1.96789175e-01 2.18688443e-01 1.32324219e+00
6.07625246e-01 -8.67167711e-02 -2.05433816e-01 1.06989546e-02
-1.62982687e-01 -4.46780324e-01 5.66511512e-01 1.15237033e+00
-6.83493018e-01 -1.39244342e+00 -5.70554912e-01 1.01228845e+00
-1.23717868e+00 -9.48756859e-02 -1.15813863e+00 8.43806624e-01
1.53141826e-01 9.24171865e-01 -1.21980213e-01 -8.93217862e-01
-2.33055204e-01 6.51986152e-02 1.41003653e-01 -7.55784035e-01
-1.21543896e+00 -5.03502011e-01 -1.78787723e-01 -2.27214009e-01
1.57994345e-01 -2.00429708e-01 -9.56760466e-01 -6.59981191e-01
-2.82722980e-01 8.62285960e-03 1.43278313e+00 1.08888531e+00
3.75957578e-01 5.26774526e-01 6.05689704e-01 -9.83506024e-01
-2.52325356e-01 -1.13681984e+00 -2.52547801e-01 -2.34345257e-01
7.00116932e-01 -8.68596971e-01 -2.03049958e-01 -2.11900741e-01] | [14.425592422485352, 9.681670188903809] |
db2835b2-4ace-4438-a103-3eee4d4f450e | lambada-backward-chaining-for-automated | 2212.13894 | null | https://arxiv.org/abs/2212.13894v2 | https://arxiv.org/pdf/2212.13894v2.pdf | LAMBADA: Backward Chaining for Automated Reasoning in Natural Language | Remarkable progress has been made on automated reasoning with natural text, by using Language Models (LMs) and methods such as Chain-of-Thought and Selection-Inference. These techniques search for proofs in the forward direction from axioms to the conclusion, which suffers from a combinatorial explosion of the search space, and thus high failure rates for problems requiring longer chains of reasoning. The classical automated reasoning literature has shown that reasoning in the backward direction (i.e. from the intended conclusion to supporting axioms) is significantly more efficient at proof-finding. Importing this intuition into the LM setting, we develop a Backward Chaining algorithm, called LAMBADA, that decomposes reasoning into four sub-modules. These sub-modules are simply implemented by few-shot prompted LM inference. We show that LAMBADA achieves sizable accuracy boosts over state-of-the-art forward reasoning methods on challenging logical reasoning datasets, particularly when deep and accurate proof chains are required. | ['Mehran Kazemi', 'Deepak Ramachandran', 'Xin Xu', 'Deepti Bhatia', 'Najoung Kim'] | 2022-12-20 | null | null | null | null | ['lambada', 'logical-reasoning'] | ['natural-language-processing', 'reasoning'] | [ 2.89712518e-01 6.85580134e-01 -3.88916641e-01 -5.52603826e-02
-8.52570653e-01 -8.34086955e-01 7.97155857e-01 3.98977876e-01
1.70253664e-02 7.70040274e-01 1.24022849e-01 -1.36242139e+00
-4.02022660e-01 -1.12494385e+00 -8.71364415e-01 -2.34692767e-02
-1.40187830e-01 6.41956031e-01 4.32386577e-01 -1.21764310e-01
4.14898545e-01 -1.44594349e-03 -1.19979227e+00 5.79842269e-01
7.97401369e-01 4.91056383e-01 -3.27194989e-01 9.79526937e-01
-5.35586476e-01 2.04456854e+00 -7.11134747e-02 -9.34680343e-01
-2.14131884e-02 -5.82263410e-01 -1.49611008e+00 -6.42869592e-01
5.29827833e-01 -7.55468965e-01 -2.65568227e-01 1.23951852e+00
-1.84797823e-01 -1.72108486e-01 4.32397276e-01 -1.59188402e+00
-4.19842094e-01 1.48350000e+00 -4.01066303e-01 4.43724021e-02
9.24559474e-01 4.25349772e-02 1.65208185e+00 -6.74753428e-01
1.01430047e+00 1.60868430e+00 8.25928748e-01 5.53597152e-01
-1.42756164e+00 -3.89399409e-01 1.56316891e-01 8.59003901e-01
-1.01359618e+00 -4.41267043e-01 6.54712498e-01 -4.65615809e-01
1.36200881e+00 2.26227835e-01 2.88479626e-01 8.50659728e-01
2.70056993e-01 1.02830219e+00 1.14371598e+00 -8.93492222e-01
3.10815901e-01 -5.77734672e-02 3.57536167e-01 1.13423908e+00
4.51033890e-01 -4.70968425e-01 -6.67146325e-01 -3.13520700e-01
2.20564321e-01 -4.06747609e-01 5.70836514e-02 -4.30262148e-01
-1.21770978e+00 9.64455545e-01 2.92985095e-03 -2.26939358e-02
5.50012998e-02 3.63859266e-01 6.82101548e-01 4.84541625e-01
-6.34353086e-02 5.37471116e-01 -6.39842093e-01 -1.59384891e-01
-9.77057397e-01 9.21094060e-01 1.35760689e+00 9.54489946e-01
1.02935575e-01 -7.35830545e-01 -1.55552536e-01 2.78359473e-01
3.58941317e-01 5.28549790e-01 -2.28039816e-01 -1.63625073e+00
8.67587388e-01 7.83905804e-01 3.43061537e-01 -8.37262809e-01
-3.53821039e-01 -5.36066592e-02 -3.22173744e-01 6.83085173e-02
7.11172044e-01 -3.97722758e-02 -1.82613194e-01 2.08488083e+00
4.51382458e-01 -2.79706031e-01 3.93044859e-01 4.70284522e-01
5.86034417e-01 5.36997080e-01 -4.68180664e-02 -2.73975611e-01
1.38802373e+00 -1.11249447e+00 -7.17253983e-01 -1.73146099e-01
1.22107804e+00 -3.26989532e-01 9.50166523e-01 7.86444128e-01
-1.65656745e+00 2.58162260e-01 -9.27103817e-01 -5.45541584e-01
-2.23388985e-01 -2.60131985e-01 1.06201458e+00 -1.12061866e-01
-9.62876856e-01 4.45484638e-01 -5.95730424e-01 -1.95870623e-01
5.07499635e-01 -1.66786984e-01 -2.10590169e-01 -4.97099698e-01
-1.40435779e+00 1.12233186e+00 2.91000456e-01 8.19378905e-03
-8.45227361e-01 -9.05204773e-01 -9.99355376e-01 2.35255331e-01
1.08338177e+00 -9.12807822e-01 1.98485446e+00 -2.86663592e-01
-1.28062701e+00 7.99571872e-01 -3.97166699e-01 -8.67491722e-01
1.00294161e+00 -4.37895715e-01 -6.34424537e-02 2.68740863e-01
4.21565741e-01 3.41856658e-01 3.75568897e-01 -7.95652568e-01
-6.52646542e-01 -1.73080936e-01 8.87425900e-01 -2.75289744e-01
1.96254924e-01 3.02579433e-01 1.14962108e-01 -4.78463806e-03
3.25040758e-01 -7.78952539e-01 6.08082749e-02 3.32400084e-01
-6.60427272e-01 -9.22284842e-01 4.63791221e-01 -5.35436749e-01
1.45140374e+00 -1.49487352e+00 3.08786720e-01 1.40656516e-01
6.03700280e-01 -2.79337112e-02 3.66962701e-01 8.86870563e-01
5.33860140e-02 1.91012740e-01 -1.09752696e-02 7.11159483e-02
7.03067958e-01 1.30743638e-01 -8.90287876e-01 9.22792181e-02
1.40878141e-01 1.09862351e+00 -1.24485087e+00 -1.02226090e+00
1.13336593e-02 -4.23068345e-01 -8.40118408e-01 -1.15114609e-02
-1.00434864e+00 -4.11764085e-01 -3.01136792e-01 5.27219236e-01
5.62114418e-01 -8.17670107e-01 6.52729452e-01 2.33558208e-01
-4.31155413e-02 1.07821345e+00 -1.07206023e+00 1.79044759e+00
-4.57517892e-01 6.70576811e-01 1.46657646e-01 -7.63757765e-01
2.26415798e-01 1.40255481e-01 -2.33037829e-01 -4.26472843e-01
-3.55898179e-02 2.28688315e-01 1.59689575e-01 -7.86434054e-01
-3.98516245e-02 -3.63810986e-01 5.46861626e-02 7.95305252e-01
-1.45450577e-01 -1.97918996e-01 7.61382103e-01 9.60708439e-01
1.59579158e+00 5.04761755e-01 3.83133084e-01 -1.13750421e-01
8.06780875e-01 6.63576007e-01 4.35499132e-01 1.10113454e+00
8.72650445e-02 -3.16982865e-01 1.10654759e+00 -4.37413692e-01
-9.71968889e-01 -9.94129777e-01 1.72384590e-01 9.65286911e-01
-1.36566460e-01 -1.17408836e+00 -8.01456749e-01 -8.13145518e-01
2.39489257e-01 1.19754410e+00 -3.65373313e-01 -4.05160524e-03
-6.10292792e-01 2.37315103e-01 9.79699433e-01 6.85922205e-01
6.31167829e-01 -8.49725604e-01 -9.03714299e-01 1.43723384e-01
-4.87451613e-01 -1.26503682e+00 5.77822089e-01 9.04042050e-02
-7.68137038e-01 -1.50261211e+00 1.03921376e-01 -3.79592150e-01
6.04915440e-01 3.78484204e-02 1.15318692e+00 4.53761458e-01
-4.77781184e-02 1.48810253e-01 -1.98100477e-01 -4.59088355e-01
-7.86319613e-01 -2.94602156e-01 -1.37801141e-01 -7.98195541e-01
4.47290808e-01 -4.67539132e-01 -7.42177591e-02 -3.20732743e-01
-4.31632519e-01 6.20854557e-01 4.85090673e-01 8.10496390e-01
-5.32523496e-03 3.53353977e-01 1.04290828e-01 -1.03761828e+00
7.13292956e-01 -3.29451412e-01 -8.47727060e-01 6.23526633e-01
-8.39550376e-01 5.27600408e-01 9.43274200e-01 3.46958414e-02
-1.01441658e+00 -7.11238563e-01 2.80315787e-01 -1.69138581e-01
1.66515514e-01 7.74416268e-01 3.24649602e-01 4.56922323e-01
6.64764881e-01 6.09647334e-02 9.34626535e-03 -8.14323686e-03
6.14809573e-01 2.27647677e-01 7.19841242e-01 -1.29829431e+00
1.11531842e+00 3.46418858e-01 6.11226499e-01 -3.34471315e-02
-1.45041776e+00 -3.74475420e-02 -3.34372044e-01 -8.04259107e-02
3.66863698e-01 -6.95298731e-01 -1.24938715e+00 -1.47132771e-02
-1.40671968e+00 -8.05419624e-01 -3.73341702e-02 1.55118793e-01
-8.21769178e-01 5.74459434e-01 -9.53780174e-01 -1.21858013e+00
-4.36852396e-01 -8.23266268e-01 7.64244497e-01 -1.94269747e-01
-9.40420151e-01 -9.56102371e-01 7.16159567e-02 5.62499702e-01
-8.74042585e-02 -1.33796483e-01 1.62478685e+00 -7.74480700e-01
-6.72987819e-01 4.90829488e-03 -5.21288931e-01 5.14022782e-02
-4.88131732e-01 1.38011798e-01 -6.72481716e-01 2.99439728e-01
-2.56771356e-01 -6.99401855e-01 5.62854826e-01 -1.68396029e-04
8.81328762e-01 -7.12823868e-01 -4.60762352e-01 8.53956640e-02
1.13319838e+00 -3.69065821e-01 5.23878992e-01 6.39604688e-01
1.01856805e-01 4.68546599e-01 6.18558586e-01 1.33584306e-01
6.90377235e-01 2.28539184e-01 4.41564433e-02 4.91014004e-01
-3.25466432e-02 -8.42666626e-01 1.78563207e-01 1.08591489e-01
7.26074576e-02 4.39747386e-02 -1.26890957e+00 5.10286093e-01
-2.21193075e+00 -1.49953222e+00 -3.44582617e-01 1.52655089e+00
1.28112137e+00 5.97310960e-01 -1.60162732e-01 6.40832901e-01
1.22243971e-01 -2.33754799e-01 -3.57146740e-01 -7.61832535e-01
1.30822375e-01 1.26166180e-01 -6.24054857e-03 8.57576847e-01
-7.11657524e-01 8.98533762e-01 6.70172548e+00 6.02685094e-01
-3.75393242e-01 -1.20171659e-01 -1.26604438e-01 -1.39662102e-01
-4.75105077e-01 6.33853793e-01 -6.05343938e-01 1.19767804e-02
7.38900423e-01 -1.71102136e-01 6.97425604e-01 1.07589638e+00
-3.06138657e-02 -4.56691295e-01 -1.65998399e+00 5.69136143e-01
-4.33360040e-02 -1.72000694e+00 -3.09638269e-02 -2.88694054e-01
4.99103814e-01 -4.33276743e-01 -4.32372957e-01 4.81852829e-01
8.45914066e-01 -7.37700164e-01 1.16704488e+00 2.35643491e-01
4.84876573e-01 -5.04499555e-01 7.23742604e-01 7.44926393e-01
-7.65602827e-01 -5.99832356e-01 1.18883543e-01 -7.59232521e-01
-4.96860147e-02 4.88813818e-01 -1.14967299e+00 4.56096560e-01
3.74411285e-01 5.18428266e-01 -2.43591011e-01 4.36185807e-01
-1.02116883e+00 6.75351977e-01 -2.64959812e-01 -4.66589540e-01
2.62830704e-01 -4.18214500e-02 5.46543300e-01 1.34178305e+00
-2.48909786e-01 2.66955465e-01 -1.16201520e-01 1.53818440e+00
-4.03727703e-02 -5.28681874e-01 -6.12077177e-01 -1.67706788e-01
5.88273525e-01 1.11312366e+00 -4.93667692e-01 -8.17234814e-01
-3.79711121e-01 4.71261591e-01 6.10038817e-01 1.25516489e-01
-9.22992826e-01 -4.58488733e-01 2.97178060e-01 -7.12283840e-03
1.34594902e-01 -3.04405481e-01 -3.57124537e-01 -1.04928088e+00
3.57580215e-01 -1.05892253e+00 6.40141010e-01 -1.30185378e+00
-1.03458083e+00 -3.60401124e-01 4.07149285e-01 -4.48209435e-01
-5.41644990e-01 -8.45150173e-01 -6.50829732e-01 6.75204396e-01
-1.60430181e+00 -1.06420267e+00 7.08279833e-02 2.72760421e-01
6.06918871e-01 3.92485470e-01 8.27552021e-01 -2.47674286e-01
-2.68082529e-01 4.39524233e-01 -5.52230835e-01 2.92847008e-01
2.92821199e-01 -1.33415461e+00 2.30513096e-01 1.11018622e+00
-8.03027302e-02 1.22068799e+00 9.10086095e-01 -6.43264711e-01
-2.20562577e+00 -5.90060294e-01 1.63533902e+00 -8.28876853e-01
1.45112765e+00 -3.33512306e-01 -5.24474800e-01 1.04267871e+00
2.19396539e-02 -4.09250319e-01 1.40571699e-01 5.72353899e-01
-9.30576622e-01 1.56216651e-01 -1.01096404e+00 1.19719172e+00
1.31988716e+00 -9.00555015e-01 -1.28693032e+00 6.42000139e-01
6.83849514e-01 -4.82700557e-01 -5.11287153e-01 2.10376501e-01
7.87208974e-01 -9.11021292e-01 8.45313966e-01 -1.07152963e+00
1.29632652e+00 -4.49194402e-01 -1.93184808e-01 -5.25524557e-01
-2.02359661e-01 -1.00490093e+00 -7.87944376e-01 1.05836022e+00
7.00896919e-01 -4.87271130e-01 3.21209192e-01 9.33132470e-01
1.67666703e-01 -8.89629722e-01 -5.87860584e-01 -6.54347658e-01
1.61397114e-01 -7.94253469e-01 3.34837675e-01 7.13767231e-01
1.18855441e+00 6.88458085e-01 3.49257678e-01 3.05404216e-02
7.63451815e-01 5.87691069e-01 9.88546610e-01 -1.21006083e+00
-3.70536596e-01 -6.68335259e-01 6.12700656e-02 -8.25336277e-01
6.95167303e-01 -1.27970874e+00 1.21482827e-01 -2.12342453e+00
6.02319002e-01 -2.15871379e-01 2.03781605e-01 7.79856861e-01
-2.80350745e-02 -5.06918550e-01 7.55074918e-02 -1.80366375e-02
-1.06014907e+00 -1.48590714e-01 1.09364164e+00 -2.88286239e-01
4.23381418e-01 -4.19259071e-01 -6.96279287e-01 1.14755678e+00
3.99689347e-01 -2.96938837e-01 -4.95408684e-01 -3.31606239e-01
1.33604693e+00 2.60635674e-01 7.37653732e-01 -7.88932621e-01
7.08217263e-01 -4.34825122e-01 -1.38748273e-01 -4.99746293e-01
-3.71245667e-02 -5.17066002e-01 -1.60209730e-01 6.71979129e-01
-1.06019235e+00 1.90060019e-01 1.04049835e-02 3.25951368e-01
2.18838096e-01 -4.93226051e-01 2.39827186e-01 -3.41906428e-01
-5.75415611e-01 -4.56541955e-01 -2.47182280e-01 4.58554626e-01
6.81080520e-01 3.20176244e-01 -6.42323434e-01 -2.51724094e-01
-3.69141877e-01 4.55425888e-01 3.13682824e-01 -1.86907068e-01
4.46804494e-01 -8.44991684e-01 -6.31879985e-01 -3.05377096e-01
2.60741301e-02 2.33962893e-01 -9.84387919e-02 1.40529478e+00
-5.98495483e-01 7.90538430e-01 4.08188254e-01 -3.28590423e-01
-1.36072910e+00 8.40569735e-01 1.90228075e-01 -6.09906793e-01
-1.01601720e+00 9.17199075e-01 -3.34335178e-01 -4.06042665e-01
1.50307789e-01 -8.59536231e-01 3.65294784e-01 -4.04041767e-01
7.65759170e-01 5.32516122e-01 -1.20295279e-01 3.18352550e-01
-6.89056814e-01 2.67894000e-01 -4.11968641e-02 -2.61276811e-01
1.09343314e+00 1.36593878e-01 -7.31388390e-01 4.26781803e-01
4.85225141e-01 1.74560964e-01 -5.73472202e-01 -3.12088281e-01
2.73205459e-01 -7.50784129e-02 -8.84718373e-02 -1.25548136e+00
5.04118996e-03 8.04287314e-01 -7.32797742e-01 4.52928960e-01
4.49349880e-01 3.21223944e-01 6.31555676e-01 1.11982203e+00
6.48762047e-01 -1.07834637e+00 -3.21579427e-01 6.32261038e-01
6.72833562e-01 -9.46391940e-01 3.63601208e-01 -2.93939620e-01
-2.65463620e-01 1.31862962e+00 3.56654227e-01 6.87340870e-02
6.74962550e-02 6.24778032e-01 -3.85106355e-01 -3.37307006e-01
-1.44643819e+00 2.32281536e-01 -3.12184483e-01 8.41514543e-02
2.82091528e-01 6.86786920e-02 -1.75425664e-01 5.76433480e-01
-4.31527436e-01 5.36104620e-01 5.43298841e-01 1.31840265e+00
-2.93347418e-01 -7.95320511e-01 -4.61653411e-01 1.06550649e-01
-3.91896367e-01 -2.72942483e-01 -6.40858829e-01 9.63790238e-01
-2.02709794e-01 1.37708569e+00 -3.54799479e-01 3.08246687e-02
-1.83266625e-01 5.24686277e-01 1.15978849e+00 -3.54259461e-01
-1.71635244e-02 -6.73298657e-01 7.72281110e-01 -6.42898381e-01
-2.19050020e-01 -6.21759772e-01 -1.71869648e+00 -1.00692379e+00
-3.49646211e-01 3.05504501e-01 3.35253358e-01 1.44497430e+00
1.95421353e-01 4.51099992e-01 2.33831443e-03 -1.29333690e-01
-1.13132453e+00 -6.36362731e-01 -7.42195919e-02 8.76906067e-02
4.05273795e-01 -6.17150366e-01 -4.39789027e-01 7.99330324e-02] | [9.144688606262207, 7.182344436645508] |
5e490658-4421-40ec-9e21-282c17954bb3 | learning-non-metric-visual-similarity-for | 1709.01353 | null | http://arxiv.org/abs/1709.01353v2 | http://arxiv.org/pdf/1709.01353v2.pdf | Learning Non-Metric Visual Similarity for Image Retrieval | Measuring visual similarity between two or more instances within a data
distribution is a fundamental task in image retrieval. Theoretically,
non-metric distances are able to generate a more complex and accurate
similarity model than metric distances, provided that the non-linear data
distribution is precisely captured by the system. In this work, we explore
neural networks models for learning a non-metric similarity function for
instance search. We argue that non-metric similarity functions based on neural
networks can build a better model of human visual perception than standard
metric distances. As our proposed similarity function is differentiable, we
explore a real end-to-end trainable approach for image retrieval, i.e. we learn
the weights from the input image pixels to the final similarity score.
Experimental evaluation shows that non-metric similarity networks are able to
learn visual similarities between images and improve performance on top of
state-of-the-art image representations, boosting results in standard image
retrieval datasets with respect standard metric distances. | ['George Vogiatzis', 'Noa Garcia'] | 2017-09-05 | learning-non-metric-visual-similarity-for-1 | https://openreview.net/forum?id=Skvd-myR- | https://openreview.net/pdf?id=Skvd-myR- | iclr-2018-1 | ['instance-search'] | ['computer-vision'] | [ 2.89008975e-01 -3.40849340e-01 -1.14696033e-01 -9.57300484e-01
-7.85895526e-01 -6.40467525e-01 8.29783201e-01 2.99775243e-01
-6.50998831e-01 4.03605849e-02 1.17838494e-01 -1.59827933e-01
-6.87743664e-01 -7.31435061e-01 -6.69409752e-01 -3.58908594e-01
-2.16271922e-01 5.39569318e-01 6.82489127e-02 -3.26163411e-01
5.48868179e-01 7.94055641e-01 -1.84859776e+00 4.73798692e-01
5.00849009e-01 1.40155733e+00 3.57944340e-01 8.44807327e-01
-1.64619118e-01 5.92348218e-01 -5.90585411e-01 -5.01993985e-04
4.25170749e-01 -3.36617231e-01 -7.60837197e-01 -3.60650986e-01
1.14107776e+00 -1.58029482e-01 -5.30005634e-01 1.24488986e+00
5.48111737e-01 2.08791971e-01 1.20070434e+00 -1.30841088e+00
-1.46184862e+00 3.99945140e-01 -3.17244470e-01 4.16250080e-01
4.22927141e-01 -1.26072869e-01 1.10754538e+00 -1.03321588e+00
4.85490888e-01 1.37456584e+00 5.83882034e-01 3.82706940e-01
-1.17700756e+00 -3.45873147e-01 -2.39933684e-01 7.54929364e-01
-1.53851032e+00 8.68735835e-02 7.07058907e-01 -3.28897923e-01
8.83442998e-01 3.34057301e-01 3.49149555e-01 7.25584686e-01
2.13876352e-01 7.35505044e-01 1.07320929e+00 -5.40332019e-01
5.18810563e-02 -7.86983371e-02 5.86744174e-02 5.50387681e-01
-8.54827166e-02 3.82194132e-01 -3.46031427e-01 5.83745837e-02
5.87780893e-01 4.39574808e-01 -2.11665750e-01 -9.06605542e-01
-1.30868781e+00 9.09907520e-01 1.27219200e+00 8.07717085e-01
-2.76868641e-01 4.52666521e-01 2.58545756e-01 7.17501223e-01
1.72830284e-01 7.74577200e-01 -3.83479856e-02 8.45060945e-02
-1.07541072e+00 1.90379277e-01 5.00849605e-01 6.89873278e-01
9.31147337e-01 -2.91960537e-01 -6.02058411e-01 8.97805452e-01
8.40445682e-02 6.24494553e-01 9.01848078e-01 -1.00754309e+00
-2.47346442e-02 5.70204258e-01 -9.44499671e-02 -1.34839213e+00
-4.31846291e-01 -1.14977166e-01 -7.85322130e-01 5.16611099e-01
4.95140463e-01 7.01698840e-01 -9.77805018e-01 1.76554286e+00
-2.15855524e-01 5.99879622e-02 -1.06293254e-01 1.11037874e+00
7.44257271e-01 5.05801439e-01 -9.80443433e-02 3.95042419e-01
1.09869170e+00 -7.62753963e-01 -2.92984724e-01 -1.11234352e-01
5.09717584e-01 -8.75613987e-01 1.29210532e+00 1.48436382e-01
-1.19446909e+00 -9.08595502e-01 -1.38573742e+00 -2.95222729e-01
-9.71367896e-01 -1.66297749e-01 3.59681368e-01 3.53845626e-01
-1.42237866e+00 9.41282988e-01 -4.31018174e-01 -4.81452674e-01
3.16634625e-01 2.58973151e-01 -4.26310271e-01 -3.87591809e-01
-1.15981078e+00 1.21245384e+00 4.10437912e-01 -1.56084940e-01
-6.86097741e-01 -7.39042938e-01 -9.56391335e-01 3.04819822e-01
-2.37937659e-01 -4.24261808e-01 1.11739159e+00 -1.11116171e+00
-8.75642061e-01 1.37700188e+00 3.18634748e-01 -5.59096515e-01
3.31117928e-01 6.47848099e-02 -2.18833178e-01 2.76809752e-01
-1.96523905e-01 1.14528763e+00 8.32312763e-01 -1.22675514e+00
-5.72053075e-01 -2.58202106e-01 1.20343670e-01 8.91392231e-02
-4.85065132e-01 -7.79521912e-02 2.29775757e-02 -4.76109147e-01
-1.18917994e-01 -7.61037529e-01 3.86596173e-02 7.23535419e-01
9.68312994e-02 -5.39326251e-01 7.32743382e-01 -3.14056873e-01
9.11948860e-01 -2.09526587e+00 1.70767322e-01 5.31768858e-01
1.58148229e-01 5.25964856e-01 -8.75629544e-01 3.40501517e-01
-3.55446517e-01 -1.30429059e-01 -1.46310017e-01 -7.75442496e-02
3.78156841e-01 2.44537532e-01 -1.80001125e-01 4.94304687e-01
1.97978318e-01 1.18512273e+00 -9.78981912e-01 -3.09794694e-01
3.76246572e-01 7.38438427e-01 -1.33861363e-01 3.57045203e-01
7.18491226e-02 -2.93135852e-01 4.44761515e-02 3.96761090e-01
6.53930128e-01 -1.94315955e-01 -2.47528628e-01 -3.01620841e-01
3.11695993e-01 -1.40760541e-01 -9.40800130e-01 2.22948098e+00
-7.50687301e-01 1.09990323e+00 -4.64778066e-01 -1.24822783e+00
1.28931999e+00 -1.91124469e-01 3.82647008e-01 -1.46052372e+00
3.19454782e-02 1.95763692e-01 1.00550398e-01 -2.39599496e-01
5.27247846e-01 1.68025255e-01 8.67203549e-02 6.79185212e-01
2.17947111e-01 -2.53501952e-01 3.41558635e-01 9.35182646e-02
8.75975370e-01 -1.33525461e-01 2.32831627e-01 -4.21447366e-01
7.93709695e-01 -3.29618037e-01 -1.20211869e-01 1.04373109e+00
-2.45452628e-01 9.63418961e-01 1.68835908e-01 -7.53645778e-01
-1.26746500e+00 -1.47500956e+00 -2.58411676e-01 1.22365797e+00
3.50305587e-01 -1.41866386e-01 -6.63336515e-01 -5.46402514e-01
2.03484684e-01 2.76730657e-01 -8.28650475e-01 -7.37652123e-01
-5.16264677e-01 -1.48135841e-01 4.03860748e-01 6.86569691e-01
3.03088993e-01 -1.21440852e+00 -5.43232262e-01 -7.92523175e-02
6.24472387e-02 -7.25677669e-01 -7.97223985e-01 1.76249027e-01
-4.75087583e-01 -1.04068100e+00 -9.90218639e-01 -1.16496634e+00
6.03554308e-01 6.31706536e-01 1.59381163e+00 2.22935483e-01
-8.79179955e-01 7.62959719e-01 -2.37940505e-01 -2.82042563e-01
-4.15668756e-01 -1.21534482e-01 -1.96147606e-01 -1.32601693e-01
7.75754809e-01 -4.26689357e-01 -1.19674885e+00 4.16921556e-01
-1.22314489e+00 -6.00023270e-01 6.06205940e-01 9.22432899e-01
6.42748177e-01 -4.13614094e-01 3.66883039e-01 -1.60213098e-01
8.27486753e-01 -2.30666637e-01 -4.41794574e-01 5.93244195e-01
-6.76152408e-01 4.94680196e-01 4.75982130e-01 -8.36222470e-01
-3.99225146e-01 -2.08964929e-01 2.70413160e-01 -5.84584355e-01
-1.46040007e-01 3.18470210e-01 3.19968432e-01 -4.34675753e-01
1.24356318e+00 1.67790383e-01 2.37608954e-01 -1.54093578e-01
7.72973537e-01 6.61753416e-01 5.76048374e-01 -4.21701968e-01
7.62927830e-01 4.56230521e-01 2.24418774e-01 -3.45345080e-01
-7.87744284e-01 -7.30495036e-01 -7.04978704e-01 2.52039526e-02
8.05290401e-01 -5.15341520e-01 -7.13958740e-01 1.52017787e-01
-1.07894015e+00 -2.64938354e-01 -5.68692923e-01 5.04979610e-01
-8.17942977e-01 2.78672785e-01 -3.08656245e-01 -2.93748111e-01
-3.49382460e-01 -9.31169748e-01 1.18047118e+00 2.78236330e-01
-2.55759090e-01 -1.23261642e+00 3.61896008e-01 -9.37168673e-02
8.04657638e-01 1.00989960e-01 1.01013196e+00 -7.26527095e-01
-4.49944884e-01 -3.14133286e-01 -7.22747326e-01 6.05308473e-01
1.85827255e-01 -1.64480552e-01 -8.91306639e-01 -4.37274098e-01
-1.40515983e-01 -5.94194531e-01 9.23400342e-01 2.86861479e-01
1.44715250e+00 -4.23581637e-02 -1.28214300e-01 6.88517869e-01
1.53021419e+00 1.09747415e-02 7.75594652e-01 3.46721500e-01
5.39812922e-01 6.75013542e-01 6.37996316e-01 6.24039769e-02
2.13121787e-01 8.18479180e-01 5.27397871e-01 -4.39175367e-01
-4.42568749e-01 -5.57556637e-02 -3.90470475e-02 4.16246116e-01
3.99114460e-01 -1.30179793e-01 -8.55570853e-01 6.25941694e-01
-1.70424092e+00 -1.08463407e+00 2.31059089e-01 2.36564302e+00
7.55873382e-01 -1.66388929e-01 8.40346068e-02 1.33557245e-01
6.48198366e-01 1.19104840e-01 -4.48165238e-01 -8.02357614e-01
-1.05272913e-02 3.71585369e-01 2.92238533e-01 4.44818556e-01
-9.87617195e-01 6.14633560e-01 6.64538956e+00 8.73334110e-01
-1.36707389e+00 -1.70446932e-01 3.67350280e-01 -1.38195097e-01
-2.39945173e-01 -4.84413683e-01 -1.46780893e-01 3.59586924e-01
7.81180561e-01 -2.08992556e-01 5.37054241e-01 8.93635094e-01
-3.80673766e-01 2.66904771e-01 -1.69853222e+00 1.58117735e+00
6.11477971e-01 -1.28650975e+00 3.34161550e-01 -1.03001311e-01
7.62634575e-01 1.60117909e-01 5.06889820e-01 1.55672178e-01
1.82720229e-01 -1.55391467e+00 4.91183251e-01 9.09244359e-01
7.15207815e-01 -8.28191698e-01 6.56636357e-01 6.13246709e-02
-9.74818349e-01 -8.81161541e-02 -8.70778024e-01 2.25068167e-01
-1.75743416e-01 2.25581616e-01 -7.46869028e-01 2.34090865e-01
6.92384541e-01 8.57363999e-01 -1.00189018e+00 1.36876297e+00
1.33158386e-01 -1.65594369e-01 -1.61247700e-01 -1.07981443e-01
5.88355720e-01 1.28373448e-02 5.85175194e-02 1.29614735e+00
5.62005997e-01 -5.10086834e-01 1.34109147e-02 9.02992249e-01
-4.28403877e-02 -3.36047001e-02 -9.39867973e-01 1.80424795e-01
2.82438934e-01 1.22119296e+00 -4.01566893e-01 -2.13621676e-01
-3.10909063e-01 1.11890411e+00 5.16476214e-01 3.38807344e-01
-5.70192218e-01 -6.44780397e-01 8.54361594e-01 -1.18620850e-01
3.07475179e-01 -1.25751168e-01 1.14842281e-02 -7.03621626e-01
1.18249714e-01 -8.42698455e-01 5.51255941e-01 -1.07386601e+00
-1.66867816e+00 6.49016321e-01 -1.35365933e-01 -1.37617481e+00
-5.89720547e-01 -1.12543023e+00 -4.79703248e-01 8.55446398e-01
-1.75394499e+00 -1.13907111e+00 -6.51043832e-01 8.10723603e-01
1.31241158e-01 -1.85369387e-01 9.34929192e-01 2.29263678e-01
5.69629133e-01 7.38622129e-01 3.30413103e-01 1.13849618e-01
9.43328679e-01 -1.58309257e+00 4.54872131e-01 3.95490795e-01
9.48039711e-01 4.78027254e-01 4.59330857e-01 1.44214869e-01
-1.11793435e+00 -5.93318880e-01 8.59095454e-01 -6.13529086e-01
6.96117282e-01 -3.13869745e-01 -1.05410206e+00 2.21989393e-01
3.06168944e-01 4.45201606e-01 6.45663381e-01 -2.21766010e-01
-9.80769038e-01 -4.52223301e-01 -1.16756845e+00 4.91124332e-01
1.08305144e+00 -1.00258899e+00 -6.91631198e-01 4.04351383e-01
3.68009537e-01 -1.02346942e-01 -8.49394500e-01 3.33654672e-01
7.05797493e-01 -1.09961009e+00 1.61940932e+00 -6.25749230e-01
3.49041492e-01 -3.55002642e-01 -5.79135716e-01 -1.47612929e+00
-4.26545292e-01 -1.91689089e-01 1.60911426e-01 8.07774901e-01
5.93573190e-02 -3.00927848e-01 5.31764925e-01 3.60071093e-01
2.83521473e-01 -6.77036941e-01 -9.01973367e-01 -1.16608274e+00
4.59303379e-01 -1.77567631e-01 6.54098392e-01 7.60862708e-01
-1.65076673e-01 -6.54100394e-03 -7.36868382e-02 -1.14359975e-01
6.96353734e-01 2.52427518e-01 3.87327164e-01 -1.27363062e+00
-9.82127041e-02 -9.58885729e-01 -1.29087961e+00 -9.37078357e-01
3.94399345e-01 -1.27313066e+00 1.36823565e-01 -1.59719408e+00
2.14528710e-01 -3.90193045e-01 -7.78160810e-01 2.00015262e-01
1.86239202e-02 7.14260459e-01 3.46718490e-01 -7.89493769e-02
-6.51325345e-01 4.09424782e-01 1.25248933e+00 -7.01431572e-01
1.69983357e-01 -4.09841567e-01 -5.40518165e-01 3.73969555e-01
6.32587373e-01 -4.76907194e-01 -6.74411118e-01 -5.80948591e-01
2.45688245e-01 -2.96692580e-01 5.00738740e-01 -1.10353160e+00
4.02656317e-01 1.05649456e-01 5.53625226e-01 -3.17339271e-01
3.10875416e-01 -1.04806530e+00 -3.93234104e-01 4.12327051e-01
-8.01505506e-01 3.64084095e-01 -2.14198351e-01 3.35352331e-01
-5.59098363e-01 -4.00883555e-01 7.52325773e-01 2.32126638e-02
-8.18242431e-01 3.35619450e-01 9.16011781e-02 1.54949605e-01
8.56997609e-01 -4.45823342e-01 -3.75854492e-01 -5.15788972e-01
-4.78214055e-01 1.09373033e-02 3.88721436e-01 8.10984135e-01
8.17821324e-01 -1.81716514e+00 -6.95496917e-01 4.10807468e-02
5.88220060e-01 -5.67201912e-01 -4.91729528e-02 2.73668826e-01
-4.67123210e-01 4.68692899e-01 -6.48610473e-01 -9.88817036e-01
-1.42956090e+00 9.46422637e-01 5.17811120e-01 -1.06612116e-01
-2.79850483e-01 6.77361846e-01 3.35895509e-01 -4.81915355e-01
5.07757902e-01 -4.90569353e-01 -6.39261082e-02 2.51050144e-02
8.00262153e-01 2.28545278e-01 9.34136808e-02 -5.85125625e-01
-4.03411239e-01 1.08340418e+00 -2.11990416e-01 -3.87353636e-02
1.10793138e+00 -2.54472508e-03 2.82587707e-02 3.94931257e-01
1.91409266e+00 -8.40206087e-01 -1.11402118e+00 -5.01738429e-01
8.03083181e-02 -6.92963541e-01 -7.78922290e-02 -9.25023675e-01
-9.74919975e-01 1.10816920e+00 1.29567456e+00 2.63530582e-01
1.06915021e+00 1.45792112e-01 5.46168208e-01 8.39915156e-01
2.50432670e-01 -9.69823122e-01 6.15959406e-01 3.59838516e-01
1.23144770e+00 -1.54622090e+00 -1.67649969e-01 2.89157182e-01
-3.42684925e-01 1.20180428e+00 3.78993243e-01 -5.77890813e-01
6.61547780e-01 -8.44416469e-02 3.30000341e-01 -1.27502710e-01
-3.43614399e-01 -3.48030329e-01 9.09905493e-01 9.84718978e-01
3.79626751e-01 -1.33643925e-01 -1.21948883e-01 -3.44038486e-01
-1.27086401e-01 -2.27087274e-01 5.55329882e-02 7.39123642e-01
-3.61302733e-01 -1.07712734e+00 -1.87754586e-01 1.96256220e-01
-9.51091945e-02 -1.61708146e-01 -4.98703718e-01 6.28087580e-01
-1.12084009e-01 7.31980920e-01 5.49372733e-01 -1.47090524e-01
4.30081010e-01 -1.84134349e-01 8.65587234e-01 -2.22305253e-01
-4.87849742e-01 -7.12646663e-01 -5.27758241e-01 -9.23180103e-01
-4.57358301e-01 -1.99566111e-01 -9.68241096e-01 -1.57050818e-01
-3.76221016e-02 -4.69304658e-02 1.03569889e+00 6.84658885e-01
3.43285084e-01 1.78524777e-01 7.26758838e-01 -9.66457903e-01
-8.41637909e-01 -9.20060158e-01 -4.54503119e-01 1.08897364e+00
4.89098936e-01 -5.40370047e-01 -4.16491508e-01 -1.20903656e-01] | [9.822032928466797, 2.1884400844573975] |
175ceffe-c870-48c7-b071-7a126846c57c | localization-guided-learning-for-pedestrian | 1808.09102 | null | http://arxiv.org/abs/1808.09102v1 | http://arxiv.org/pdf/1808.09102v1.pdf | Localization Guided Learning for Pedestrian Attribute Recognition | Pedestrian attribute recognition has attracted many attentions due to its
wide applications in scene understanding and person analysis from surveillance
videos. Existing methods try to use additional pose, part or viewpoint
information to complement the global feature representation for attribute
classification. However, these methods face difficulties in localizing the
areas corresponding to different attributes. To address this problem, we
propose a novel Localization Guided Network which assigns attribute-specific
weights to local features based on the affinity between proposals pre-extracted
proposals and attribute locations. The advantage of our model is that our local
features are learned automatically for each attribute and emphasized by the
interaction with global features. We demonstrate the effectiveness of our
Localization Guided Network on two pedestrian attribute benchmarks (PA-100K and
RAP). Our result surpasses the previous state-of-the-art in all five metrics on
both datasets. | ['Xihui Liu', 'Jing Shao', 'Pengze Liu', 'Junjie Yan'] | 2018-08-28 | null | null | null | null | ['pedestrian-attribute-recognition'] | ['computer-vision'] | [-1.80780590e-01 -3.85196418e-01 -1.67884931e-01 -9.27738011e-01
-4.61418420e-01 -3.59697282e-01 7.90560782e-01 4.51506555e-01
-5.14803588e-01 6.90593541e-01 3.60577911e-01 2.99214482e-01
2.80435886e-02 -8.84675682e-01 -4.83745933e-01 -6.83895230e-01
-8.78427699e-02 5.19275427e-01 5.37412763e-01 -6.45275638e-02
1.70337707e-01 5.03289342e-01 -1.60323441e+00 2.67743647e-01
7.49372780e-01 1.25575137e+00 -7.95076266e-02 2.13465139e-01
-1.24100074e-02 2.64467478e-01 -4.99641001e-01 -5.38199484e-01
2.79883325e-01 -1.96553409e-01 -5.96956849e-01 2.24936485e-01
9.66985047e-01 -3.37224990e-01 -2.84326643e-01 1.00421166e+00
4.62552130e-01 1.66674301e-01 7.06715703e-01 -1.42615938e+00
-5.37607849e-01 9.23295692e-02 -6.26607716e-01 2.60849863e-01
5.90617001e-01 1.33183315e-01 1.03035808e+00 -1.04086745e+00
3.88323545e-01 1.32676065e+00 7.17281401e-01 3.27191234e-01
-1.17696488e+00 -4.38292742e-01 7.50709653e-01 6.72268748e-01
-1.85076392e+00 -4.14908916e-01 8.51255119e-01 -4.11358774e-01
6.63786054e-01 6.87635913e-02 8.02763700e-01 1.03155994e+00
7.87359327e-02 9.34007764e-01 8.81360173e-01 -2.11762980e-01
1.15725800e-01 1.76010489e-01 1.95202097e-01 7.36075461e-01
2.41068706e-01 -8.69965404e-02 -7.21036494e-01 -1.81229576e-01
5.14344394e-01 1.73502311e-01 -1.06814779e-01 -8.25557590e-01
-1.15788674e+00 6.54781461e-01 5.85152030e-01 -2.35452086e-01
-4.76626247e-01 -5.25745563e-02 4.35863435e-01 -5.16238995e-02
5.26991963e-01 2.04537094e-01 -4.47385877e-01 -4.33638170e-02
-5.10012031e-01 2.23972768e-01 3.72751474e-01 1.02957129e+00
8.94089103e-01 -2.93925524e-01 -5.09645760e-01 8.13181758e-01
3.27158749e-01 4.21967506e-01 -5.11650592e-02 -7.58332551e-01
3.95150691e-01 9.61148381e-01 1.73271820e-01 -1.26214457e+00
-3.89919370e-01 -3.64574581e-01 -6.96974874e-01 1.13610532e-02
5.85977852e-01 4.38040495e-02 -7.22177386e-01 1.71948004e+00
4.94600534e-01 2.06908315e-01 -2.68222541e-01 1.08260250e+00
8.07001233e-01 4.37754303e-01 5.03897786e-01 3.50884378e-01
1.51243901e+00 -9.60986555e-01 -3.56121123e-01 -3.87138635e-01
3.02297771e-01 -5.78192234e-01 8.74669015e-01 8.94040912e-02
-4.69135344e-01 -7.36173928e-01 -8.44514966e-01 2.70240426e-01
-5.47048032e-01 4.41384077e-01 6.64339304e-01 7.25399673e-01
-9.52759624e-01 1.26301467e-01 -4.47035193e-01 -8.70359898e-01
7.80388892e-01 4.15838331e-01 -5.51701665e-01 -1.27339393e-01
-9.70686674e-01 7.45311499e-01 1.47258937e-01 3.35432100e-03
-8.96125793e-01 -3.74631524e-01 -9.36926544e-01 1.23422205e-01
4.15133417e-01 -7.78510511e-01 7.05998659e-01 -6.39446557e-01
-1.35134196e+00 7.77030408e-01 -3.32384169e-01 -2.74933547e-01
3.99648845e-01 -5.89436650e-01 -3.34916174e-01 1.14385515e-01
3.48413080e-01 9.19873536e-01 6.77614212e-01 -1.06258225e+00
-9.63742673e-01 -5.80622613e-01 1.20485216e-01 2.65146703e-01
-4.65436846e-01 3.88349183e-02 -5.00065267e-01 -6.56579792e-01
1.09127499e-01 -7.56321430e-01 -3.17650884e-01 3.26123178e-01
-3.53569448e-01 -4.76963937e-01 9.25171077e-01 -3.54941219e-01
7.33980238e-01 -2.12971711e+00 -4.17518094e-02 1.79198742e-01
2.60473073e-01 2.17293382e-01 -1.16829313e-01 1.41458079e-01
2.75941402e-01 -3.16682905e-01 1.57062799e-01 -3.63584191e-01
-9.44778696e-02 3.10661681e-02 -4.38363999e-02 6.78995132e-01
2.43996263e-01 7.61276543e-01 -8.88606727e-01 -7.47009575e-01
3.75001967e-01 5.97496152e-01 -3.93755913e-01 1.03079297e-01
2.30804220e-01 4.46646005e-01 -7.00315356e-01 8.57182622e-01
7.59503245e-01 3.37349288e-02 -3.34835760e-02 -5.01033068e-01
-3.92682031e-02 5.08462116e-02 -1.25031507e+00 1.60243225e+00
-1.02523439e-01 5.84741056e-01 -2.41701677e-01 -9.50940013e-01
1.01359546e+00 1.46493599e-01 4.08083230e-01 -4.28543001e-01
-3.02495854e-03 -1.39478624e-01 -3.59401435e-01 -2.10120231e-01
4.36264932e-01 4.64122832e-01 -2.17996240e-01 5.06420359e-02
8.64680260e-02 5.20316780e-01 -1.66660715e-02 1.60600141e-01
6.16022587e-01 2.53621787e-01 6.20942354e-01 -4.83422816e-01
9.28981245e-01 -2.76077688e-01 7.53445685e-01 8.90934169e-01
-6.06391072e-01 5.30428529e-01 3.82466257e-01 -1.13759172e+00
-8.59132946e-01 -1.11561060e+00 -7.23057166e-02 1.33339870e+00
5.38673162e-01 -5.76004326e-01 -7.39261925e-01 -1.15718591e+00
-4.16413806e-02 3.81177664e-01 -6.64926052e-01 -8.15533251e-02
-5.85862935e-01 -5.34949422e-01 3.69554520e-01 1.04796851e+00
9.28904414e-01 -9.12451625e-01 -6.76615417e-01 1.23389736e-01
-3.67937058e-01 -1.40329206e+00 -6.58109307e-01 -3.17646652e-01
-5.05072117e-01 -9.69400883e-01 -5.17523527e-01 -5.72127938e-01
8.17368090e-01 4.50913578e-01 1.07702959e+00 -6.52858689e-02
-2.87992656e-01 6.84570551e-01 -2.59948820e-01 -3.64155710e-01
2.32549444e-01 2.80326217e-01 4.72734809e-01 5.77390790e-01
8.03886592e-01 -2.72468716e-01 -7.76790321e-01 8.15044224e-01
-1.32746518e-01 -2.66451120e-01 6.70677066e-01 6.23204112e-01
5.27450681e-01 -2.93661743e-01 5.35123765e-01 -4.53869909e-01
2.79441386e-01 -1.17148146e-01 -6.28618538e-01 3.64871144e-01
-1.63536876e-01 1.29873436e-02 4.80514586e-01 -2.39762038e-01
-9.79952693e-01 4.67929572e-01 6.56765848e-02 -3.95566858e-02
-6.65985823e-01 2.56112255e-02 -7.62938201e-01 -2.60470599e-01
4.45816398e-01 1.36079714e-01 -1.31393507e-01 -1.85921848e-01
2.37396881e-01 3.57918203e-01 5.28289080e-01 -8.88797581e-01
6.47414982e-01 6.25524104e-01 1.50333956e-01 -7.80281246e-01
-9.95532274e-01 -6.45868719e-01 -9.91240919e-01 -5.00608563e-01
1.05182993e+00 -9.02549088e-01 -9.12308633e-01 5.82686782e-01
-1.11298263e+00 3.37160021e-01 -2.55693793e-01 4.70723838e-01
-4.30671453e-01 5.37878752e-01 -1.39406309e-01 -6.80415332e-01
-6.88795969e-02 -1.27220249e+00 1.11553395e+00 3.16371769e-01
-1.36353835e-01 -7.10645795e-01 -3.59001875e-01 -1.64212491e-02
6.08238876e-01 1.70601442e-01 5.35602033e-01 -6.84263229e-01
-6.98106110e-01 -5.93664825e-01 -5.31467319e-01 7.89295062e-02
3.54519784e-01 -3.20382923e-01 -1.04925811e+00 -2.23272756e-01
-4.88777608e-01 -2.42895722e-01 1.05398560e+00 4.80952442e-01
1.23240125e+00 -2.23921135e-01 -7.25340068e-01 5.72123587e-01
1.09760273e+00 -1.78033650e-01 4.77235794e-01 5.03833473e-01
6.12824202e-01 5.67766130e-01 7.75547743e-01 5.27485549e-01
4.58859801e-01 1.24375570e+00 4.95692700e-01 -6.64363503e-02
3.24032158e-02 -1.32792696e-01 1.82445899e-01 -1.02544524e-01
-4.98069137e-01 -1.61875203e-01 -7.74893284e-01 6.11916661e-01
-2.12212634e+00 -9.94940162e-01 6.66733459e-02 2.44083595e+00
2.59282649e-01 2.15543702e-01 4.40045983e-01 -2.58386910e-01
8.89761150e-01 2.25204065e-01 -1.31739080e-01 9.12252218e-02
-1.86344922e-01 -3.37480396e-01 3.40756178e-01 2.84089863e-01
-1.85443985e+00 1.02374327e+00 6.06247473e+00 6.61788642e-01
-5.78909755e-01 -1.47155762e-01 8.29176843e-01 2.65580684e-01
3.42324764e-01 -1.75833732e-01 -1.22914851e+00 3.64900172e-01
3.62488687e-01 2.32062459e-01 -1.29260093e-01 1.13996160e+00
-1.33626387e-01 -1.16023026e-01 -1.22434938e+00 8.23593140e-01
1.99417934e-01 -1.12318754e+00 3.96728516e-01 3.21459584e-02
2.59036154e-01 -3.74068320e-01 2.02598929e-01 2.28632838e-01
1.49819300e-01 -8.36405635e-01 5.48323214e-01 6.05013430e-01
5.72049022e-01 -9.04626131e-01 1.07477891e+00 3.68937152e-03
-1.73599911e+00 -6.19582273e-02 -6.16065323e-01 -9.28943306e-02
1.92447498e-01 2.56067485e-01 -6.78846478e-01 4.71907794e-01
9.14756417e-01 7.37650812e-01 -8.44981074e-01 1.35953856e+00
-2.25313008e-01 3.91990751e-01 -3.32713932e-01 5.41531369e-02
2.76192307e-01 -3.71014178e-02 5.84615111e-01 1.38403726e+00
1.97947636e-01 1.16095863e-01 6.82248950e-01 6.14825249e-01
2.31351808e-01 1.21127829e-01 -5.91610253e-01 6.17692649e-01
5.71366191e-01 1.31548858e+00 -7.12061405e-01 -3.70170265e-01
-6.42032504e-01 8.86923671e-01 2.49204323e-01 2.89493889e-01
-8.60926867e-01 -2.90849268e-01 1.05991650e+00 2.54668444e-01
4.35804307e-01 -3.51367384e-01 -1.10330088e-02 -9.73310292e-01
8.20447281e-02 -5.72486758e-01 5.53626001e-01 -2.82366484e-01
-1.44282818e+00 6.95231438e-01 2.51115471e-01 -1.30572963e+00
-7.51703456e-02 -6.50370061e-01 -5.01960993e-01 6.84836209e-01
-1.28135550e+00 -1.53736901e+00 -9.00013506e-01 6.56678319e-01
6.24790668e-01 -4.63191211e-01 7.96323299e-01 3.49891126e-01
-4.16991830e-01 8.67435813e-01 -4.49352115e-01 4.22046989e-01
1.00875151e+00 -1.08983970e+00 4.47521836e-01 7.55591273e-01
1.17569482e-02 5.70284009e-01 6.18713260e-01 -4.72288549e-01
-7.80375898e-01 -1.16628790e+00 8.98532867e-01 -7.92403638e-01
2.01088354e-01 -4.45447922e-01 -6.91838920e-01 5.98321140e-01
2.34571815e-01 4.89386111e-01 5.97692490e-01 2.56702244e-01
-5.24808526e-01 -5.19060791e-01 -1.10151815e+00 3.50082040e-01
1.22788525e+00 -1.33093357e-01 -2.73317069e-01 9.67386365e-02
3.58140141e-01 -1.40682772e-01 -5.53432345e-01 3.80804479e-01
6.02931678e-01 -8.59221518e-01 1.41356683e+00 -5.37973106e-01
2.12561209e-02 -5.62832117e-01 -5.24372935e-01 -1.27951384e+00
-6.31288350e-01 -7.04457462e-02 2.04851359e-01 1.43412435e+00
1.66037902e-01 -5.98377466e-01 7.85302460e-01 4.77154583e-01
-9.51679647e-02 -6.37656271e-01 -1.09758246e+00 -8.10430050e-01
-5.37301362e-01 -7.23299459e-02 8.83405864e-01 6.85342610e-01
-4.38183546e-01 4.24475610e-01 -4.23828304e-01 3.60190660e-01
9.31416452e-01 -2.75499430e-02 9.74469602e-01 -1.53034651e+00
2.04560250e-01 -4.56609190e-01 -1.22482729e+00 -1.19204795e+00
9.66394097e-02 -4.09988642e-01 2.07142141e-02 -1.48600101e+00
4.90340561e-01 -4.83813137e-01 -3.74420941e-01 6.53695226e-01
-4.23211962e-01 4.34547603e-01 1.22877397e-01 9.97120067e-02
-1.07749736e+00 7.60217547e-01 7.02662528e-01 -3.68233323e-01
-2.15363521e-02 1.94185853e-01 -4.49846089e-01 8.66305292e-01
7.57009625e-01 -2.59808987e-01 -1.85830250e-01 -2.81097263e-01
-2.18285605e-01 -5.60553908e-01 8.94329071e-01 -1.53773081e+00
3.84618491e-01 -1.83837920e-01 8.24274719e-01 -7.56621480e-01
6.09933615e-01 -8.42205763e-01 -4.88350689e-01 8.79385620e-02
-1.98811397e-01 3.90325695e-01 1.44150227e-01 8.69146883e-01
-2.42517307e-01 2.03261554e-01 7.66706765e-01 -6.93502799e-02
-1.25962627e+00 4.21624959e-01 -3.80029529e-01 -9.52943042e-02
1.22593570e+00 -4.11363363e-01 -3.16781491e-01 -5.19056499e-01
-5.17018259e-01 1.80889294e-01 4.76929337e-01 4.21627730e-01
9.45469975e-01 -1.48608601e+00 -8.40051174e-01 3.73054385e-01
5.02736568e-01 -2.19092891e-01 1.18977092e-01 7.78305948e-01
-2.39861578e-01 5.44315755e-01 -5.41776538e-01 -9.71848607e-01
-1.34701538e+00 6.41708076e-01 2.68101782e-01 1.23350419e-01
-7.11321354e-01 8.78601789e-01 5.45631409e-01 -3.06364000e-01
2.77158260e-01 1.52318016e-01 -4.39610213e-01 -1.26908690e-01
4.50389057e-01 3.76782358e-01 -2.16747627e-01 -1.02599037e+00
-8.59268010e-01 9.33833241e-01 -3.42135042e-01 2.84969866e-01
1.09377706e+00 -1.78041056e-01 3.92159745e-02 -7.91396275e-02
8.18381190e-01 7.26039261e-02 -1.52579939e+00 -4.65907604e-01
-6.32517934e-02 -8.08165431e-01 -3.95030260e-01 -4.86244649e-01
-1.03123772e+00 7.67386734e-01 8.64578366e-01 -1.75839856e-01
9.56954241e-01 2.53177315e-01 4.42537308e-01 5.12319326e-01
5.58610618e-01 -1.02607393e+00 2.68010736e-01 3.32067788e-01
5.66425204e-01 -1.38800025e+00 2.68645853e-01 -6.06066823e-01
-7.62780845e-01 9.59813595e-01 1.07242084e+00 -3.51231098e-02
4.93733734e-01 -2.00314745e-01 6.64237142e-02 -1.67700127e-01
-1.85970739e-01 -6.58541843e-02 6.03015602e-01 8.87308300e-01
3.30943137e-01 1.39258087e-01 -1.69830602e-02 4.96022671e-01
2.12620303e-01 -4.08415198e-01 1.26479998e-01 6.76336646e-01
-6.46778643e-01 -1.06541228e+00 -3.73396009e-01 2.36910045e-01
-1.16286770e-01 8.47683400e-02 -5.18773198e-01 8.16273749e-01
2.61774778e-01 8.22867632e-01 4.37038504e-02 -3.50078881e-01
2.52581537e-01 -5.76330945e-02 3.12156439e-01 -2.50540972e-01
-1.83532253e-01 -2.34627888e-01 6.62038177e-02 -7.85596848e-01
-5.79201043e-01 -8.89932930e-01 -6.77327752e-01 -1.27897605e-01
-1.84157759e-01 6.29873276e-02 2.63262659e-01 8.64477694e-01
5.47166765e-01 3.33117306e-01 3.05083334e-01 -9.41647112e-01
-2.53554493e-01 -7.55464971e-01 -1.75100937e-01 4.71641362e-01
1.67777181e-01 -1.16704381e+00 1.06755935e-01 -1.59458071e-01] | [14.40774154663086, 0.9984171986579895] |
db97ffc0-06fd-4c72-b95b-19ead1c9baf6 | grey-box-models-for-wave-loading-prediction | 2105.13813 | null | https://arxiv.org/abs/2105.13813v2 | https://arxiv.org/pdf/2105.13813v2.pdf | Grey-box models for wave loading prediction | The quantification of wave loading on offshore structures and components is a crucial element in the assessment of their useful remaining life. In many applications the well-known Morison's equation is employed to estimate the forcing from waves with assumed particle velocities and accelerations. This paper develops a grey-box modelling approach to improve the predictions of the force on structural members. A grey-box model intends to exploit the enhanced predictive capabilities of data-based modelling whilst retaining physical insight into the behaviour of the system; in the context of the work carried out here, this can be considered as physics-informed machine learning. There are a number of possible approaches to establish a grey-box model. This paper demonstrates two means of combining physics (white box) and data-based (black box) components; one where the model is a simple summation of the two components, the second where the white-box prediction is fed into the black box as an additional input. Here Morison's equation is used as the physics-based component in combination with a data-based Gaussian process NARX - a dynamic variant of the more well-known Gaussian process regression. Two key challenges with employing the GP-NARX formulation that are addressed here are the selection of appropriate lag terms and the proper treatment of uncertainty propagation within the dynamic GP. The best performing grey-box model, the residual modelling GP-NARX, was able to achieve a 29.13\% and 5.48\% relative reduction in NMSE over Morison's Equation and a black-box GP-NARX respectively, alongside significant benefits in extrapolative capabilities of the model, in circumstances of low dataset coverage. | ['Elizabeth J Cross', 'Ulf T Tygesen', 'Timothy J Rogers', 'Daniel J Pitchforth'] | 2021-05-10 | null | null | null | null | ['physics-informed-machine-learning'] | ['graphs'] | [ 1.02962762e-01 9.53683257e-02 7.77564883e-01 1.24700837e-01
-7.63604581e-01 -4.28186357e-01 6.03251636e-01 3.39589387e-01
-2.83699065e-01 9.05605078e-01 9.93338227e-02 -6.10565484e-01
-1.09430480e+00 -8.83835793e-01 -3.80297929e-01 -1.23903000e+00
-2.87490129e-01 5.76729536e-01 5.08376122e-01 -4.15015608e-01
2.57215858e-01 6.93641663e-01 -1.39627993e+00 -2.79042810e-01
6.53105497e-01 8.60780776e-01 1.44471094e-01 7.56587803e-01
1.18790984e-01 6.10578656e-01 -4.02483344e-01 3.21311550e-03
2.71366775e-01 -2.62535244e-01 -3.75297844e-01 -3.79050404e-01
-4.24980193e-01 1.76126584e-01 2.14785278e-01 4.26339626e-01
7.45778620e-01 4.20180589e-01 8.14220369e-01 -6.95902884e-01
2.04810709e-01 1.55355573e-01 -3.33853483e-01 3.48061025e-01
1.56957820e-01 8.43352675e-02 4.08560961e-01 -7.10675418e-01
5.30235097e-02 1.04271472e+00 1.01907933e+00 -6.16884157e-02
-1.29193997e+00 -3.25178564e-01 -3.10971051e-01 -4.61433828e-01
-1.41568244e+00 -7.50982165e-02 4.78927881e-01 -9.71930921e-01
1.09835970e+00 3.58214706e-01 7.50490487e-01 2.91706562e-01
5.16313672e-01 -2.06456661e-01 1.39960074e+00 -4.54713553e-01
5.10268331e-01 5.03687598e-02 1.64343137e-02 3.92131247e-02
4.22132194e-01 7.84676492e-01 -3.68407786e-01 -3.83312285e-01
6.75395608e-01 -3.36413145e-01 -2.85218269e-01 1.00681953e-01
-3.22000891e-01 8.85927260e-01 7.75776729e-02 2.78620273e-01
-5.80570281e-01 1.80969402e-01 9.57635045e-02 1.43055692e-01
8.63541901e-01 3.39106917e-01 -6.57352567e-01 -3.77578974e-01
-1.13792169e+00 5.99287808e-01 1.00121891e+00 3.39010656e-01
5.54018617e-01 6.06292963e-01 1.52331904e-01 6.01808071e-01
9.23681259e-01 8.58256817e-01 2.02590853e-01 -5.20179629e-01
1.56954885e-01 3.49259198e-01 1.43323123e-01 -7.11348772e-01
-5.92338502e-01 -6.48374021e-01 -2.87777364e-01 8.03567290e-01
3.85415494e-01 -7.36541390e-01 -1.01275277e+00 1.28849292e+00
3.69378686e-01 3.11020344e-01 3.89032096e-01 4.76385951e-01
4.57083762e-01 9.19751108e-01 1.83537811e-01 -2.44725123e-01
1.16106522e+00 -2.79206902e-01 -4.66052055e-01 -6.04114942e-02
4.67935979e-01 -8.02529156e-01 4.83050346e-01 3.34422976e-01
-1.05546069e+00 -3.38793516e-01 -9.79595304e-01 7.29909480e-01
-3.99874717e-01 -2.94220567e-01 2.77279854e-01 8.45658362e-01
-1.18412364e+00 9.14334238e-01 -1.05004144e+00 -1.27633825e-01
-1.39977202e-01 3.83414745e-01 -2.30154291e-01 4.14697856e-01
-1.10578549e+00 1.29284883e+00 2.51339346e-01 5.30564845e-01
-7.31279969e-01 -9.16064680e-01 -7.37886846e-01 2.43546396e-01
8.06589797e-02 -3.70662630e-01 1.09482825e+00 -1.39113575e-01
-1.62546110e+00 9.93123055e-02 2.18105689e-01 -4.30685312e-01
5.61847985e-01 -1.91425204e-01 -3.30096871e-01 3.12211290e-02
-2.64215022e-01 -1.88926265e-01 6.13674462e-01 -1.58347511e+00
-6.04868114e-01 -1.40069023e-01 -2.56421179e-01 9.35874954e-02
5.02492011e-01 1.48239017e-01 8.01944584e-02 -6.07137620e-01
2.43246973e-01 -1.12854123e+00 -2.65969068e-01 -6.12434387e-01
1.41476244e-01 1.22499734e-01 7.33008325e-01 -1.00457513e+00
1.24411845e+00 -1.72672045e+00 -3.84841557e-03 5.86007237e-01
-2.78044105e-01 3.90647650e-01 6.26733601e-01 1.16789699e+00
-2.27829203e-01 -1.56318042e-02 -7.69343138e-01 -2.96616733e-01
-1.45711541e-01 6.44201100e-01 -2.50579745e-01 5.39104879e-01
3.16801518e-01 2.71384090e-01 -5.83442390e-01 1.94620397e-02
4.20274198e-01 7.58221924e-01 -1.66448310e-01 -5.81375808e-02
3.13126594e-01 6.44640625e-01 -2.06216171e-01 2.25543916e-01
7.48513579e-01 6.19408011e-01 -2.97883838e-01 2.56523699e-01
-5.76186478e-01 -7.30396137e-02 -1.44912827e+00 9.10744667e-01
-5.35954893e-01 4.98348236e-01 2.11173445e-01 -7.89704025e-01
1.35308623e+00 5.89628518e-01 2.45537505e-01 -1.48806602e-01
1.09081291e-01 4.30968881e-01 3.79976451e-01 -5.36983073e-01
2.98697859e-01 -9.35563624e-01 2.46105611e-01 5.67658879e-02
-1.46076918e-01 -5.42802691e-01 -8.14297888e-03 -3.95734966e-01
7.75657773e-01 5.58263183e-01 1.38324782e-01 -8.91231179e-01
5.71837485e-01 4.57090437e-02 4.02351350e-01 4.36295688e-01
2.39413902e-01 5.32709122e-01 3.82829756e-01 -2.30112270e-01
-8.01552594e-01 -6.91246688e-01 -4.52803493e-01 4.37981755e-01
-2.54051656e-01 7.09570795e-02 -4.46640700e-01 2.91276108e-02
1.42196536e-01 9.04440343e-01 -6.93450093e-01 -8.35546032e-02
-4.56310272e-01 -1.42545855e+00 5.72557211e-01 3.69051278e-01
-9.79500636e-02 -7.25364983e-01 -8.00214171e-01 5.70578575e-01
5.63325524e-01 -3.17270070e-01 6.91458046e-01 5.95551252e-01
-1.07877278e+00 -7.14865685e-01 -6.00329638e-01 -7.75635242e-02
4.07710761e-01 -4.88554716e-01 7.39527762e-01 4.36912440e-02
2.14305624e-01 2.84689426e-01 -5.25765777e-01 -9.99090433e-01
-6.19852960e-01 -4.77515876e-01 -1.79623663e-01 -2.33866796e-01
-2.34369878e-02 -6.62996769e-01 -3.97887111e-01 1.47092730e-01
-1.01441991e+00 -5.91464877e-01 4.61601287e-01 5.59879720e-01
3.26218873e-01 4.95269358e-01 5.17773211e-01 -6.73106313e-01
6.24313474e-01 -5.37161648e-01 -7.86239922e-01 -1.00440994e-01
-7.26195991e-01 -9.22562107e-02 1.91476777e-01 -2.04227731e-01
-1.30501044e+00 -1.93411350e-01 -6.61261737e-01 -1.96217671e-02
-2.28361905e-01 1.11759615e+00 2.93788407e-02 -4.03896064e-01
4.17291969e-01 -9.75303799e-02 1.64469123e-01 -7.05521464e-01
-2.62506604e-01 4.95156676e-01 2.31649831e-01 -8.24199736e-01
9.89908397e-01 3.60441476e-01 5.86696208e-01 -1.03753209e+00
-1.83371320e-01 -7.19057143e-01 -4.66762513e-01 -3.98540467e-01
6.55275822e-01 -7.45642483e-01 -3.92908484e-01 6.43557072e-01
-6.14731729e-01 -5.17033398e-01 -5.32736242e-01 6.18407011e-01
-4.09524441e-01 1.22610010e-01 -3.27800542e-01 -1.68640792e+00
-3.90791446e-01 -1.17365348e+00 1.00332808e+00 2.94979125e-01
-1.09754592e-01 -1.45677698e+00 4.21297073e-01 -7.02243373e-02
6.05743289e-01 7.54540980e-01 7.49570668e-01 -6.93355203e-01
9.70164463e-02 -5.44686735e-01 2.77672321e-01 5.24980962e-01
-1.84991017e-01 2.72147834e-01 -1.10512829e+00 -1.46753967e-01
6.39358938e-01 5.07555068e-01 3.72158319e-01 5.35898983e-01
7.14726970e-02 5.81359304e-02 -3.04524004e-02 3.71174067e-01
2.16439891e+00 5.73322356e-01 6.88065588e-01 6.30675614e-01
1.46964669e-01 8.26448083e-01 5.59815705e-01 4.20495510e-01
-1.06316589e-01 4.71462160e-01 5.09786427e-01 -9.96514857e-02
2.03050151e-01 1.53522059e-01 4.28979062e-02 6.31647289e-01
-7.13921070e-01 -1.35738969e-01 -1.35371208e+00 3.70019794e-01
-1.67318916e+00 -9.88313317e-01 -7.81288743e-01 2.47549558e+00
3.93876344e-01 5.59329450e-01 -2.75779516e-01 5.00988483e-01
3.46351653e-01 -2.24739894e-01 2.10844815e-01 -7.48911381e-01
-1.78915709e-02 4.35624242e-01 9.58966970e-01 7.97752380e-01
-8.72432172e-01 4.76890913e-04 5.90434599e+00 7.11791158e-01
-9.12447870e-01 9.77468863e-02 1.42237797e-01 3.79202932e-01
-6.71464056e-02 4.46395367e-01 -9.36556935e-01 5.54125071e-01
1.43499613e+00 -7.83259645e-02 -8.12864453e-02 4.16947693e-01
9.32053566e-01 -7.25246966e-01 -3.06311667e-01 2.15433091e-01
-1.74686864e-01 -9.21575189e-01 -2.89969623e-01 4.26915377e-01
7.02483594e-01 -1.17608316e-01 -4.09441620e-01 2.96428859e-01
1.88202664e-01 -7.66297460e-01 9.38671350e-01 1.13664198e+00
3.12168121e-01 -6.86953425e-01 1.48669076e+00 5.05025327e-01
-1.07357895e+00 -1.78377599e-01 -2.73588717e-01 -6.01835430e-01
8.49944055e-01 5.75816989e-01 -4.40265596e-01 1.15696371e+00
6.94278598e-01 7.67533705e-02 -1.21336669e-01 1.44149423e+00
-7.92567357e-02 1.10691118e+00 -8.75459909e-01 3.18690419e-01
3.85219902e-01 -6.45861506e-01 8.21332455e-01 1.21165049e+00
7.60577440e-01 1.11772768e-01 -2.08181992e-01 4.31579769e-01
1.03158772e+00 1.45032138e-01 -2.64016747e-01 4.29333687e-01
1.93991005e-01 1.11075044e+00 -6.17423058e-01 -5.11944145e-02
-3.66643876e-01 2.44634151e-02 -4.18066651e-01 2.63623476e-01
-6.68572664e-01 -2.24211872e-01 4.96778488e-01 4.37094927e-01
3.82544994e-01 -1.47249490e-01 -4.27554816e-01 -7.84005150e-02
-2.65947729e-01 -3.38239640e-01 1.82458088e-01 -1.02487767e+00
-1.09924448e+00 5.88121474e-01 7.95332849e-01 -1.18454981e+00
-3.37109834e-01 -9.35502350e-01 -9.73021924e-01 1.75550687e+00
-1.35682094e+00 -9.94508445e-01 -9.89331678e-02 -2.02403337e-01
1.95620388e-01 1.36474013e-01 8.76663148e-01 5.71386069e-02
-3.39432597e-01 -3.14447969e-01 7.36661077e-01 -4.02718842e-01
6.93905801e-02 -1.48045957e+00 1.95561517e-02 9.51906264e-01
-4.74306285e-01 4.47982073e-01 1.41130698e+00 -9.28621531e-01
-9.94651735e-01 -7.25299060e-01 6.94694877e-01 -3.11343759e-01
1.01286161e+00 1.36397719e-01 -1.26254976e+00 1.79661289e-01
2.75800470e-02 -2.29511157e-01 7.53237903e-01 -3.24309945e-01
6.55931890e-01 -3.46764997e-02 -1.12595129e+00 9.53545272e-02
6.23653084e-02 -1.37679189e-01 -1.04308558e+00 -1.66551396e-02
3.27748865e-01 -5.02065480e-01 -1.42600226e+00 8.23785365e-01
5.50785840e-01 -7.95894027e-01 7.34311581e-01 -2.42747590e-01
3.33051831e-02 -5.55834293e-01 6.22715242e-03 -1.27441645e+00
5.23395836e-03 -7.20541000e-01 1.14635482e-01 1.34058356e+00
6.13883555e-01 -9.25307810e-01 3.83636028e-01 9.69085574e-01
-3.64870548e-01 -1.01864564e+00 -1.17660570e+00 -8.78676236e-01
4.02520925e-01 -6.88236058e-01 4.09951538e-01 3.75469118e-01
-3.40170205e-01 -1.82941467e-01 -1.10458873e-01 6.59676850e-01
4.25360829e-01 -5.06763637e-01 5.59900761e-01 -1.54244864e+00
-3.85247558e-01 -1.79213613e-01 -4.53718871e-01 -2.10648730e-01
-5.20965755e-01 -2.11787641e-01 2.57900029e-01 -1.72749615e+00
-5.59730947e-01 -4.89905298e-01 -5.48061021e-02 4.08921251e-03
-1.57739505e-01 2.81103961e-02 7.46246502e-02 2.98686475e-01
8.74333799e-01 3.43961030e-01 7.54015267e-01 6.03012860e-01
-3.96899045e-01 5.50812781e-01 -2.88192570e-01 7.71405220e-01
8.08696985e-01 -7.09118783e-01 -4.82035369e-01 -1.25400394e-01
4.95040655e-01 2.03880340e-01 5.19792497e-01 -1.28725946e+00
1.67758435e-01 1.45494789e-02 8.58714730e-02 -6.79137349e-01
4.25330818e-01 -1.11332095e+00 9.71517861e-01 4.90014970e-01
2.25764424e-01 2.89977670e-01 7.13530123e-01 6.73596025e-01
-3.54012012e-01 -9.14477944e-01 6.73520684e-01 -1.34349838e-01
-4.25698608e-01 -2.14536861e-01 -5.19224644e-01 -4.24912095e-01
1.08379698e+00 -5.64146221e-01 -2.17442110e-01 -3.04930151e-01
-1.14199209e+00 -5.38958609e-02 3.00927401e-01 -2.35379905e-01
1.47598997e-01 -4.92072135e-01 -7.59117246e-01 -5.45709208e-02
-3.82048488e-01 1.41975537e-01 4.76145536e-01 1.13856244e+00
-1.00364852e+00 2.55926162e-01 1.43160760e-01 -3.72123718e-01
-9.46485221e-01 2.48354629e-01 7.40021229e-01 -3.42502832e-01
-4.71595436e-01 8.88579667e-01 -1.40111074e-01 -3.10902745e-01
-4.09286439e-01 -3.20810229e-01 -4.71060544e-01 1.66932255e-01
2.04485863e-01 7.56908536e-01 4.04852033e-01 -9.98644471e-01
-1.35126442e-01 8.31948578e-01 8.61206353e-01 -3.87080342e-01
1.56328464e+00 -3.62237006e-01 -1.04129568e-01 8.70351434e-01
6.61165714e-01 2.66437143e-01 -1.59101260e+00 2.30461597e-01
2.07663789e-01 -9.40842852e-02 5.11143148e-01 -9.17449117e-01
-6.48877084e-01 7.37109244e-01 4.95940030e-01 5.77424824e-01
1.12263465e+00 -2.89827287e-01 4.86607142e-02 -1.40701219e-01
2.31506415e-02 -8.71003747e-01 -1.06608689e+00 3.21227312e-01
1.14921546e+00 -7.30208695e-01 3.24215710e-01 -5.99044144e-01
-4.81658936e-01 1.12881243e+00 -1.57440118e-02 -2.26876274e-01
1.11464262e+00 6.82904363e-01 1.27865449e-01 -3.97885740e-01
-5.56352675e-01 -3.43836904e-01 2.89902151e-01 5.53937852e-01
1.54647216e-01 -1.42055392e-01 -5.58940411e-01 6.84777260e-01
-2.05460280e-01 -6.24167547e-02 3.48939687e-01 1.21881282e+00
-5.26703238e-01 -9.91334617e-01 -8.71768653e-01 4.83245581e-01
-6.59911990e-01 -1.57132745e-01 3.16511035e-01 1.06712949e+00
2.86971241e-01 1.09798610e+00 -1.36897370e-01 -7.49051347e-02
6.48276329e-01 2.70152152e-01 -1.43096015e-01 -5.14451563e-01
-9.36781168e-01 4.29201216e-01 3.06946844e-01 7.89952204e-02
-6.15951657e-01 -9.84919071e-01 -1.00456202e+00 -1.07780822e-01
-6.67684555e-01 6.01740897e-01 1.19138885e+00 1.24846303e+00
-2.00773522e-01 6.42692029e-01 2.28185430e-01 -1.24761939e+00
-6.22130156e-01 -1.26647067e+00 -8.90644193e-01 -1.18551090e-01
1.27565684e-02 -1.00601685e+00 -9.24845278e-01 -6.47688955e-02] | [6.406726360321045, 3.280604600906372] |
2f02887a-8c2a-46ff-a09a-e6466dc430b5 | physics-inspired-spatiotemporal-graph-ai | 2306.15728 | null | https://arxiv.org/abs/2306.15728v1 | https://arxiv.org/pdf/2306.15728v1.pdf | Physics-inspired spatiotemporal-graph AI ensemble for gravitational wave detection | We introduce a novel method for gravitational wave detection that combines: 1) hybrid dilated convolution neural networks to accurately model both short- and long-range temporal sequential information of gravitational wave signals; and 2) graph neural networks to capture spatial correlations among gravitational wave observatories to consistently describe and identify the presence of a signal in a detector network. These spatiotemporal-graph AI models are tested for signal detection of gravitational waves emitted by quasi-circular, non-spinning and quasi-circular, spinning, non-precessing binary black hole mergers. For the latter case, we needed a dataset of 1.2 million modeled waveforms to densely sample this signal manifold. Thus, we reduced time-to-solution by training several AI models in the Polaris supercomputer at the Argonne Leadership Supercomputing Facility within 1.7 hours by distributing the training over 256 NVIDIA A100 GPUs, achieving optimal classification performance. This approach also exhibits strong scaling up to 512 NVIDIA A100 GPUs. We then created ensembles of AI models to process data from a three detector network, namely, the advanced LIGO Hanford and Livingston detectors, and the advanced Virgo detector. An ensemble of 2 AI models achieves state-of-the-art performance for signal detection, and reports seven misclassifications per decade of searched data, whereas an ensemble of 4 AI models achieves optimal performance for signal detection with two misclassifications for every decade of searched data. Finally, when we distributed AI inference over 128 GPUs in the Polaris supercomputer and 128 nodes in the Theta supercomputer, our AI ensemble is capable of processing a decade of gravitational wave data from a three detector network within 3.5 hours. | ['Huihuo Zheng', 'E. A. Huerta', 'Minyang Tian'] | 2023-06-27 | null | null | null | null | ['gravitational-wave-detection'] | ['miscellaneous'] | [-3.26127797e-01 -2.10494488e-01 4.65282440e-01 1.95775449e-01
-5.85847199e-01 -6.00531518e-01 8.29108417e-01 -5.10940313e-01
-3.77783030e-01 1.39734462e-01 -3.13981891e-01 -8.00456762e-01
-7.40865096e-02 -1.03183198e+00 -4.42404181e-01 -8.77600729e-01
-7.08225667e-01 8.56374681e-01 4.40600872e-01 -5.74763156e-02
7.74072856e-02 8.17736149e-01 -1.20472872e+00 -2.85060471e-03
3.20486426e-01 1.16635323e+00 -1.89509287e-01 1.30741763e+00
5.00859201e-01 7.80206263e-01 -4.43352401e-01 -2.22755112e-02
4.41540241e-01 -4.41082299e-01 -2.74178296e-01 -5.46160817e-01
4.10247535e-01 1.26330517e-02 -1.09299719e+00 9.07340646e-01
7.48270273e-01 1.91912055e-01 4.06129867e-01 -1.16060054e+00
-1.67201772e-01 5.19287169e-01 -4.45619792e-01 1.08450198e+00
-1.77871466e-01 8.76948059e-01 9.96747911e-01 -7.50460625e-01
5.01667082e-01 7.83710420e-01 8.83870482e-01 -5.41083962e-02
-8.40164900e-01 -7.54717469e-01 -8.06649506e-01 1.42097086e-01
-1.18127346e+00 -4.78544354e-01 6.33600533e-01 -5.49439967e-01
1.57156909e+00 2.61165559e-01 9.34741199e-01 8.00380647e-01
1.98222056e-01 1.31483972e-01 6.29721403e-01 -1.48193374e-01
2.74080902e-01 -6.61975622e-01 3.21495682e-01 9.11020517e-01
3.50391775e-01 8.03010523e-01 -8.49731088e-01 -7.82866180e-01
8.40647340e-01 -6.40676260e-01 -2.61901289e-01 2.72798628e-01
-1.11431897e+00 1.11296129e+00 3.20884228e-01 2.62572229e-01
-3.86420101e-01 5.95353186e-01 4.17636126e-01 2.72143096e-01
4.72643912e-01 7.72837996e-01 -2.19361156e-01 -4.15456295e-01
-8.89427185e-01 4.35147613e-01 9.94934440e-01 4.88139391e-01
6.99357867e-01 8.20792437e-01 1.58414841e-01 1.70680583e-01
2.29203716e-01 1.01491237e+00 3.05225879e-01 -5.73358595e-01
1.80707395e-01 1.72541797e-01 -9.15173590e-02 -1.03674138e+00
-1.15616608e+00 -8.77029240e-01 -9.11913514e-01 2.72031486e-01
4.29942727e-01 -6.49095774e-01 -9.75588441e-01 1.19130206e+00
2.77136683e-01 7.21175730e-01 4.23055254e-02 1.19657934e+00
1.08852637e+00 7.10286856e-01 -4.16711241e-01 7.64707699e-02
1.56865358e+00 -6.48191929e-01 1.41626254e-01 -5.56528330e-01
7.24670768e-01 -5.79712272e-01 2.45956197e-01 2.30369166e-01
-1.02388871e+00 -3.15972418e-01 -1.16175878e+00 1.98411837e-01
-1.15216821e-02 -7.68624693e-02 1.16133535e+00 4.37176228e-01
-1.09087598e+00 5.53967297e-01 -1.20542574e+00 7.48536140e-02
7.37893302e-03 2.92353719e-01 2.33139217e-01 3.85101587e-01
-1.15489519e+00 5.68716109e-01 3.14498454e-01 -1.72033608e-01
-9.91242707e-01 -8.38203669e-01 -5.81067860e-01 2.46991307e-01
-2.27818683e-01 -9.29442823e-01 9.65018868e-01 -3.30027610e-01
-1.10631514e+00 7.60397553e-01 1.65303901e-01 -9.71499622e-01
9.55472514e-02 5.26418209e-01 -9.05810356e-01 3.54709864e-01
-9.80335474e-02 -1.36000559e-01 8.02046657e-01 -5.31718254e-01
-4.56595659e-01 -3.09255958e-01 -3.99420083e-01 1.53847998e-02
4.45130199e-01 4.23965365e-01 -3.57352942e-01 -3.86040211e-01
5.28764069e-01 -1.11757731e+00 -7.34210163e-02 -7.63217688e-01
-1.72092378e-01 -2.17033163e-01 8.14912021e-01 -4.70441341e-01
5.80002606e-01 -2.17896271e+00 -2.09647883e-02 4.13939595e-01
6.95991695e-01 2.06709355e-01 -2.18696240e-02 1.90325052e-01
-1.38921544e-01 -2.50091940e-01 -4.31288779e-02 -1.93326950e-01
-1.74494967e-01 -1.16866268e-01 -4.29731756e-01 8.03426087e-01
-3.98380272e-02 9.28419054e-01 -7.86923587e-01 3.87957901e-01
-7.97060728e-02 2.47475892e-01 -4.99303848e-01 4.70574610e-02
-2.95277853e-02 5.92043221e-01 -2.39937276e-01 5.01987636e-01
7.70970345e-01 -3.80842239e-01 -9.44085121e-02 -8.28321725e-02
-2.94096828e-01 5.03067970e-01 -9.36948299e-01 1.36498320e+00
-5.80474660e-02 9.68415737e-01 4.47284251e-01 -1.16704845e+00
1.02468991e+00 1.16272159e-01 5.48884988e-01 -7.26884723e-01
2.95903265e-01 1.96525663e-01 5.71009099e-01 -3.77883554e-01
6.80828452e-01 -2.35120416e-01 -1.49297506e-01 7.67025232e-01
2.91431308e-01 -3.54862601e-01 1.27257437e-01 3.51013392e-01
1.82192564e+00 -5.50727725e-01 -4.44323868e-01 -3.42339516e-01
-8.44041258e-02 3.82670999e-01 5.42218685e-01 1.40391123e+00
-4.10527140e-02 4.84888822e-01 4.24390823e-01 -9.95276093e-01
-1.11359918e+00 -8.67083013e-01 -1.53533950e-01 9.99005497e-01
-2.29891706e-02 -5.02237380e-01 -1.23620532e-01 -4.34079356e-02
1.50701463e-01 6.39507234e-01 1.41266724e-02 -3.88565421e-01
-6.88451290e-01 -1.68720365e+00 1.08513451e+00 2.46803656e-01
5.96619308e-01 -9.88459468e-01 -7.65618801e-01 1.19091332e-01
2.27334663e-01 -1.06710303e+00 2.01142550e-01 2.51587391e-01
-3.63831699e-01 -1.13614047e+00 9.01006311e-02 -4.22590226e-01
1.01624757e-01 2.19817102e-01 1.35352719e+00 2.23612368e-01
-6.53705478e-01 6.22746609e-02 -2.50810057e-01 -3.17790866e-01
-4.68633264e-01 -2.93402314e-01 5.91715813e-01 -1.80830106e-01
4.38592881e-01 -5.98964393e-01 -3.82108390e-01 2.02275217e-01
-3.42669725e-01 -6.66044727e-02 2.59217709e-01 7.49543488e-01
-7.33576268e-02 1.67486861e-01 5.83237037e-02 -2.04547524e-01
2.94114172e-01 -7.86590517e-01 -1.21503711e+00 -2.07067624e-01
-1.54325530e-01 7.58183673e-02 5.74393630e-01 -4.45382506e-01
-6.43626988e-01 -2.46660814e-01 -3.57844271e-02 -4.29970950e-01
2.18296587e-01 6.18614376e-01 8.32150638e-01 -7.61498213e-01
1.00502622e+00 3.35553527e-01 4.23655510e-02 -4.85685989e-02
2.62989879e-01 4.44471657e-01 8.74744177e-01 -5.24055839e-01
1.08478558e+00 4.84715134e-01 3.21221948e-01 -1.08397543e+00
-3.45243156e-01 -5.70964515e-01 -1.06735431e-01 -2.50189573e-01
7.67957449e-01 -1.05227935e+00 -1.15415323e+00 7.65084565e-01
-1.15517437e+00 -3.43211472e-01 8.65209401e-02 9.11654651e-01
-2.13944718e-01 3.10438246e-01 -8.94711673e-01 -8.43116224e-01
-6.19616628e-01 -9.21140254e-01 8.56461346e-01 2.50956625e-01
1.91509068e-01 -6.99409604e-01 2.63618559e-01 4.90950607e-02
7.52644479e-01 9.66716558e-02 5.08959591e-01 -6.31421983e-01
-7.15302050e-01 -3.37574065e-01 -5.49055219e-01 -3.43675554e-01
-6.21001661e-01 -1.15755804e-01 -7.13833272e-01 -5.21173954e-01
4.08571959e-01 -1.36589915e-01 1.13642168e+00 5.94782293e-01
6.59213841e-01 5.77303208e-02 -4.15591031e-01 1.20554066e+00
1.13169920e+00 3.79393250e-01 2.70769328e-01 2.34022159e-02
7.12051153e-01 -7.86102116e-02 -1.22659028e-01 5.06288648e-01
4.80701327e-02 6.28924847e-01 3.91466171e-01 -1.11150853e-01
-2.84362640e-02 4.22992259e-01 1.34240285e-01 8.72222364e-01
-5.09047210e-01 -6.40428141e-02 -1.34205079e+00 3.22850555e-01
-1.70182216e+00 -1.25716138e+00 -8.48310590e-01 2.10930490e+00
3.77155915e-02 2.86173671e-01 8.21437761e-02 -4.78038430e-01
4.81123805e-01 3.25930059e-01 -5.36064446e-01 -2.65136391e-01
-2.76632518e-01 4.13977057e-01 9.49695826e-01 4.92407203e-01
-1.05851626e+00 7.55844295e-01 6.47098780e+00 5.88469923e-01
-1.43561101e+00 3.51161569e-01 3.04122537e-01 -3.51733625e-01
-1.21738523e-01 1.77992821e-01 -7.05983222e-01 5.61563730e-01
1.31399667e+00 -3.12892318e-01 8.79272699e-01 7.38809705e-01
-2.96560768e-02 -1.86509997e-01 -5.43988585e-01 1.36366963e+00
1.58551946e-01 -1.83300996e+00 -7.21276581e-01 1.88954368e-01
4.74816799e-01 1.15019250e+00 -3.39120209e-01 4.48956788e-01
5.65212071e-01 -7.76851833e-01 5.50774872e-01 4.77880031e-01
6.66750491e-01 -7.16663003e-01 5.85836470e-01 4.83930022e-01
-1.02971113e+00 9.68368798e-02 -6.75478280e-01 -5.33332407e-01
3.97597373e-01 7.70132899e-01 -1.11185443e+00 6.23107314e-01
8.02432954e-01 1.67851329e-01 -3.83115202e-01 9.66083944e-01
-2.86684763e-02 1.02796865e+00 -9.34683442e-01 -2.92248368e-01
4.76631910e-01 -3.91975492e-01 1.11187017e+00 1.00767601e+00
5.55278778e-01 4.35613424e-01 1.13662474e-01 9.81607497e-01
-5.44037148e-02 -7.04154551e-01 -8.44080627e-01 -2.78828815e-02
3.72116715e-01 1.50581324e+00 -7.91455626e-01 -5.08794248e-01
-4.13783669e-01 3.15718502e-01 2.57454932e-01 3.01504433e-01
-9.53270555e-01 -3.95362318e-01 7.58457601e-01 -4.10748236e-02
1.93879142e-01 -7.43108273e-01 -3.86068076e-01 -1.22985578e+00
-3.60768020e-01 -4.43053931e-01 5.21114826e-01 -8.39247227e-01
-1.11586261e+00 7.55778909e-01 -3.17336947e-01 -9.47037458e-01
-4.38766569e-01 -7.42184103e-01 -1.22122204e+00 1.06161106e+00
-7.44761467e-01 -8.16989541e-01 -4.07046884e-01 1.60882026e-01
-1.41664878e-01 -7.10626304e-01 5.88303924e-01 1.50610670e-01
-4.59858477e-01 5.44264801e-02 8.18224475e-02 3.44891787e-01
1.58758149e-01 -1.00868404e+00 1.18727839e+00 1.32667339e+00
2.77078450e-01 3.31597656e-01 9.59821105e-01 -8.59050512e-01
-2.06924129e+00 -9.86213148e-01 4.15300488e-01 -2.66965449e-01
1.24026597e+00 -4.48694974e-01 -9.44087386e-01 8.06032956e-01
1.21835522e-01 6.24441683e-01 2.36493707e-01 2.09007263e-01
-2.16777757e-01 2.73223698e-01 -9.06943560e-01 1.92291126e-01
1.19542074e+00 -5.73403358e-01 -4.34557438e-01 9.06011462e-01
4.14787084e-01 -8.17844748e-01 -5.52422464e-01 4.45814312e-01
9.38886032e-02 -8.84883642e-01 8.94773960e-01 -6.21866524e-01
-1.29246563e-01 -4.71081614e-01 2.31764033e-01 -1.32722580e+00
-7.15302825e-01 -8.95866752e-01 -2.39981368e-01 2.75835186e-01
2.62964249e-01 -1.01628304e+00 8.62321734e-01 2.41518870e-01
-6.39681697e-01 -2.36323982e-01 -1.38843799e+00 -7.79992402e-01
-1.11586526e-01 -8.82953048e-01 2.95748591e-01 9.72174108e-01
-8.72806013e-02 3.63798887e-01 -2.96682924e-01 7.90776253e-01
8.05429399e-01 4.32723820e-01 7.46017992e-01 -1.16442144e+00
-7.82581925e-01 -6.72490776e-01 -7.57950008e-01 -8.56178522e-01
-8.84587839e-02 -1.29470420e+00 -1.69740766e-01 -8.62409890e-01
-1.70868635e-01 -6.37060046e-01 2.56129950e-01 3.32045615e-01
1.81932896e-01 5.68018198e-01 -7.34723210e-02 2.99391180e-01
-3.99699986e-01 1.54374152e-01 4.48760867e-01 -1.59279909e-02
-2.11324841e-02 -1.59931988e-01 -7.19176084e-02 6.08372629e-01
6.76190555e-01 -4.66712594e-01 2.77591228e-01 -6.16333663e-01
6.17475927e-01 4.44581151e-01 7.56534994e-01 -1.41683388e+00
7.86898673e-01 3.03197861e-01 4.53095645e-01 -6.58539414e-01
3.89985651e-01 2.05345690e-01 4.48010832e-01 5.05882442e-01
5.95564544e-01 8.16900656e-02 3.54643315e-01 1.61390290e-01
-1.94790009e-02 -1.88879743e-01 7.49492884e-01 -2.39845589e-01
-6.27432227e-01 3.66024107e-01 -5.23593307e-01 1.76078036e-01
8.31485331e-01 4.74134177e-01 -9.15738106e-01 -3.05547893e-01
-7.19803929e-01 2.27952316e-01 2.36923322e-01 1.19235948e-01
2.94687480e-01 -1.01766384e+00 -9.07437623e-01 7.06307530e-01
-3.14282387e-01 -2.49549784e-02 3.59471440e-01 9.00085092e-01
-9.95985448e-01 3.31485987e-01 8.28783661e-02 -8.59684229e-01
-9.69045579e-01 1.89577103e-01 6.84129238e-01 -4.69086729e-02
-9.73354518e-01 1.12221611e+00 -1.21554516e-01 -3.37490708e-01
-5.28905571e-01 -4.19023186e-02 2.58740664e-01 -1.49001107e-01
6.14142954e-01 3.78778368e-01 4.40114856e-01 -6.42008066e-01
-3.98267299e-01 4.16808814e-01 3.88452917e-01 -7.62171000e-02
1.21197689e+00 5.63977182e-01 -3.19803983e-01 -3.71369384e-02
9.44610357e-01 -1.61721949e-02 -8.21579039e-01 -1.70510307e-01
-1.43633991e-01 -5.65821305e-02 5.36976576e-01 -4.46423739e-01
-1.00305951e+00 5.36415994e-01 3.36567909e-01 8.45409334e-01
7.71260083e-01 4.45396334e-01 6.59501016e-01 4.69414830e-01
5.61922133e-01 -6.29675090e-01 -3.14296901e-01 1.16947818e+00
6.13496184e-01 -8.65025699e-01 -6.76980838e-02 -6.20254688e-03
-4.40569669e-01 1.37157798e+00 3.70921195e-01 -5.21663666e-01
5.31488478e-01 6.29233360e-01 -2.80605108e-01 -9.70815420e-01
-7.78453410e-01 -1.21346794e-01 2.65885055e-01 2.19852582e-01
-1.54490218e-01 3.65814596e-01 -3.11998911e-02 3.60086262e-01
-6.50588274e-01 -6.16874635e-01 6.34917438e-01 6.43784821e-01
-4.87811208e-01 -3.45868707e-01 -5.42372048e-01 8.04337084e-01
-1.48689255e-01 -3.47070575e-01 -2.05444489e-02 4.57813263e-01
-2.26627350e-01 8.25015306e-01 7.01370597e-01 -4.83359039e-01
-4.79698963e-02 1.80149972e-01 2.70910174e-01 -4.18154508e-01
-6.41604125e-01 -6.44348860e-02 3.79786074e-01 -4.39829528e-01
1.03308477e-01 -5.68169832e-01 -1.37927282e+00 -5.86087465e-01
-1.88387319e-01 3.72683495e-01 8.48343432e-01 9.61095750e-01
6.50448799e-01 4.57849294e-01 6.27689183e-01 -1.31410432e+00
-3.94036949e-01 -1.17396510e+00 -7.65300810e-01 -6.54923171e-02
2.21953019e-01 -5.68375528e-01 -1.08122480e+00 -6.87120795e-01] | [7.6314005851745605, 3.1263036727905273] |
3a8e6845-48ea-4cf4-a7c3-08b13aa74937 | transferable-curricula-through-difficulty | 2306.13028 | null | https://arxiv.org/abs/2306.13028v1 | https://arxiv.org/pdf/2306.13028v1.pdf | Transferable Curricula through Difficulty Conditioned Generators | Advancements in reinforcement learning (RL) have demonstrated superhuman performance in complex tasks such as Starcraft, Go, Chess etc. However, knowledge transfer from Artificial "Experts" to humans remain a significant challenge. A promising avenue for such transfer would be the use of curricula. Recent methods in curricula generation focuses on training RL agents efficiently, yet such methods rely on surrogate measures to track student progress, and are not suited for training robots in the real world (or more ambitiously humans). In this paper, we introduce a method named Parameterized Environment Response Model (PERM) that shows promising results in training RL agents in parameterized environments. Inspired by Item Response Theory, PERM seeks to model difficulty of environments and ability of RL agents directly. Given that RL agents and humans are trained more efficiently under the "zone of proximal development", our method generates a curriculum by matching the difficulty of an environment to the current ability of the student. In addition, PERM can be trained offline and does not employ non-stationary measures of student ability, making it suitable for transfer between students. We demonstrate PERM's ability to represent the environment parameter space, and training with RL agents with PERM produces a strong performance in deterministic environments. Lastly, we show that our method is transferable between students, without any sacrifice in training quality. | ['Pradeep Varakantham', 'Sidney Tio'] | 2023-06-22 | null | null | null | null | ['transfer-learning', 'starcraft'] | ['miscellaneous', 'playing-games'] | [-5.11786602e-02 2.71860927e-01 7.70663545e-02 -6.91784993e-02
-3.44506353e-01 -8.05184603e-01 3.74002665e-01 3.35348129e-01
-8.14423800e-01 9.50200438e-01 -5.19602410e-02 -2.32049689e-01
-4.45149451e-01 -1.11967242e+00 -9.46123719e-01 -5.82439363e-01
-2.11430788e-01 6.25390589e-01 3.23298454e-01 -7.48414338e-01
3.08504462e-01 6.37256205e-01 -1.92903733e+00 -5.96318096e-02
1.09948337e+00 1.73683882e-01 6.57270133e-01 9.65169072e-01
1.01589076e-01 9.57293510e-01 -7.31964707e-01 9.32478979e-02
2.53387809e-01 -6.88589633e-01 -9.91417527e-01 -4.05505806e-01
1.09342776e-01 -2.57269770e-01 -1.78839028e-01 7.44574130e-01
6.08120143e-01 7.16192544e-01 7.33036816e-01 -1.16268420e+00
-7.13977337e-01 7.48069942e-01 -6.59645200e-02 -6.04598224e-03
6.40104473e-01 2.21620545e-01 5.97353518e-01 -2.79041857e-01
5.33096433e-01 1.25020730e+00 4.95407224e-01 9.85691488e-01
-1.12513268e+00 -5.28644264e-01 2.08501652e-01 1.06172673e-01
-8.97577286e-01 1.43974081e-01 4.67354327e-01 -4.82318252e-01
6.55933917e-01 4.10426632e-02 9.26475167e-01 1.11975455e+00
-3.97940800e-02 9.22617257e-01 1.38672602e+00 -6.06934488e-01
4.18439329e-01 4.61995542e-01 -2.07442909e-01 6.31024122e-01
4.80530784e-02 4.53009754e-01 -5.33533216e-01 2.80707628e-01
1.15890777e+00 -3.65812570e-01 -1.12014711e-01 -7.75087953e-01
-1.14777470e+00 8.05052996e-01 4.28705752e-01 3.22468609e-01
-3.11597914e-01 3.52134258e-01 1.21652775e-01 7.80987084e-01
-8.59373733e-02 1.06665587e+00 -5.20131111e-01 -2.91514635e-01
-2.92681962e-01 6.80737019e-01 7.69182503e-01 1.01514053e+00
6.25126302e-01 9.81913209e-02 -1.00314707e-01 6.65073037e-01
2.62104094e-01 5.86289227e-01 7.68668234e-01 -1.12985182e+00
1.98161796e-01 5.52036762e-01 4.45382744e-01 -5.88239491e-01
-4.78560090e-01 -5.22378922e-01 -1.72242656e-01 7.70905793e-01
5.07273793e-01 -3.81918907e-01 -7.31495559e-01 2.11230445e+00
5.33608973e-01 1.33508742e-01 4.06222612e-01 7.74867952e-01
4.57919478e-01 7.56103992e-01 2.85581708e-01 -8.82451087e-02
1.01991892e+00 -8.47215891e-01 -2.84356862e-01 -1.34664163e-01
8.56169164e-01 -3.42751473e-01 1.41291821e+00 6.43934548e-01
-1.49422336e+00 -8.33451092e-01 -9.91687357e-01 2.71511316e-01
-6.27026439e-01 -4.66949165e-01 6.17695987e-01 8.61080587e-01
-1.15096998e+00 8.75918627e-01 -7.59483635e-01 -3.40902418e-01
1.67937521e-02 7.29122102e-01 -1.50343090e-01 9.33454335e-02
-1.17970407e+00 1.28363132e+00 4.76398349e-01 -5.64590454e-01
-1.35312021e+00 -7.61321425e-01 -8.35533500e-01 3.29259753e-01
7.42809325e-02 -6.96219146e-01 1.47659278e+00 -9.73160446e-01
-2.24247527e+00 5.00959277e-01 6.26410365e-01 -3.61904085e-01
5.10213494e-01 -2.21840516e-01 7.69755542e-02 -2.73401551e-02
-2.49128878e-01 9.07979965e-01 4.24796641e-01 -1.33989072e+00
-6.88006639e-01 -1.68906853e-01 4.61332709e-01 7.46395767e-01
-6.01763904e-01 8.04368220e-03 2.31715977e-01 -2.90530413e-01
-1.65000170e-01 -1.07981384e+00 -4.73809153e-01 -4.10393834e-01
5.66899836e-01 -6.18008196e-01 3.14966112e-01 -9.56774503e-02
8.69367003e-01 -1.86134589e+00 3.42385083e-01 2.67247409e-01
-1.20029993e-01 2.27392703e-01 -4.64822322e-01 4.85938281e-01
-2.57030930e-02 -9.63005647e-02 1.29061431e-01 1.42920762e-01
2.91566253e-01 2.07537964e-01 -6.74862787e-02 1.97214857e-01
-1.06645688e-01 7.30458796e-01 -1.36154127e+00 -4.28175241e-01
1.74361765e-01 2.74777830e-01 -8.83526802e-01 6.25172436e-01
-2.15921715e-01 7.13886082e-01 -5.31630993e-01 7.01253414e-02
2.08152998e-02 1.72217697e-01 2.24652570e-02 6.84616864e-01
-1.92780122e-01 2.17838809e-01 -1.28033650e+00 1.56665444e+00
-8.35729122e-01 3.23188990e-01 -1.07340343e-01 -8.69858325e-01
1.04392779e+00 4.34685737e-01 3.85997415e-01 -8.78345668e-01
-4.92577702e-02 5.34530245e-02 4.08718199e-01 -5.42552650e-01
5.33627629e-01 -7.94364437e-02 -1.94153145e-01 4.73486662e-01
1.85982123e-01 -6.25814497e-01 2.80028641e-01 -1.46931127e-01
1.17141974e+00 6.36126637e-01 7.12709203e-02 -3.26694369e-01
4.07070786e-01 1.61389872e-01 3.77254635e-01 9.77283776e-01
-3.09933931e-01 -4.18888405e-02 1.95175081e-01 -2.88163602e-01
-1.05958939e+00 -1.12902701e+00 2.52903968e-01 1.75194013e+00
6.70366064e-02 8.78797024e-02 -1.00826406e+00 -6.46243513e-01
-1.21980213e-01 7.68398225e-01 -5.64978063e-01 -3.74262303e-01
-9.89274800e-01 -4.17311221e-01 5.20251811e-01 5.09790540e-01
2.66984344e-01 -1.63577020e+00 -1.11872745e+00 3.79091591e-01
2.24590257e-01 -6.98225498e-01 -1.04676008e-01 3.41134518e-01
-8.34399760e-01 -6.59858704e-01 -8.38004053e-01 -1.13002193e+00
8.58770370e-01 1.00171596e-01 1.04918969e+00 2.33244479e-01
-1.19711921e-01 8.17527413e-01 -3.65581214e-01 -7.18770325e-01
-5.13446331e-01 -9.97208711e-03 6.08142078e-01 -6.74900353e-01
1.12891905e-02 -7.59580553e-01 -6.08753145e-01 4.20974195e-01
-7.46801674e-01 2.47862730e-02 6.68499172e-01 8.25572431e-01
6.15469180e-02 1.65187016e-01 8.31610858e-01 -7.76104331e-01
9.68888938e-01 -4.12040591e-01 -7.20810413e-01 2.18133941e-01
-7.32118726e-01 3.42104226e-01 9.34591055e-01 -8.12519908e-01
-1.13775086e+00 5.79953082e-02 4.55605146e-03 -6.17154539e-02
-4.00223076e-01 3.51007670e-01 1.10864580e-01 -2.29722515e-01
9.86633301e-01 7.27122352e-02 -1.85565174e-01 -1.69463888e-01
1.73817039e-01 1.75305530e-01 5.10233879e-01 -1.41523886e+00
9.60724115e-01 -2.51762778e-01 -7.08108619e-02 -5.71463943e-01
-5.71541488e-01 -2.10425392e-01 -4.57825214e-01 -3.43782455e-01
6.28541291e-01 -6.60484254e-01 -1.29304969e+00 1.27816454e-01
-7.41404831e-01 -1.08476102e+00 -6.86044693e-01 8.65768135e-01
-1.04768336e+00 -1.38757423e-01 -6.12111330e-01 -9.15998936e-01
1.77706823e-01 -1.20382786e+00 4.47763920e-01 7.55827844e-01
-1.09220237e-01 -1.09988713e+00 4.77363348e-01 3.47276390e-01
5.16175985e-01 -1.58530213e-02 9.63921249e-01 -6.43028557e-01
-4.29593205e-01 1.60883918e-01 3.61762613e-01 9.89161953e-02
-3.22883934e-01 -2.19511628e-01 -6.21289968e-01 -5.11835635e-01
-2.05481201e-01 -9.32877958e-01 1.08876437e-01 3.78369875e-02
1.04917979e+00 -8.40854421e-02 -7.23929098e-03 2.24395007e-01
1.21658313e+00 5.47730982e-01 5.29043198e-01 6.22781694e-01
3.36788356e-01 9.01403129e-01 6.87999129e-01 2.94787884e-01
4.34156746e-01 6.04800701e-01 3.03657651e-01 5.53808808e-02
7.75721073e-02 -4.51157063e-01 6.71623230e-01 8.87644053e-01
-3.84631336e-01 -1.64954454e-01 -1.01748276e+00 5.76708555e-01
-1.76715803e+00 -9.89398777e-01 2.44395182e-01 2.31347561e+00
1.03307104e+00 6.27357066e-02 2.95856267e-01 -9.93000120e-02
2.86700577e-01 -5.87959647e-01 -4.65513647e-01 -7.60092437e-01
2.28805482e-01 5.09171903e-01 4.54884380e-01 5.23356676e-01
-4.78596479e-01 1.06458724e+00 6.85271025e+00 4.43016708e-01
-6.49275005e-01 -8.16081092e-02 2.96448708e-01 2.56365418e-01
-1.97001323e-01 -1.29268900e-01 -8.97200465e-01 2.01069847e-01
1.27235186e+00 -1.56656131e-01 5.54035485e-01 8.81428540e-01
3.26391071e-01 -4.56789806e-02 -1.25810635e+00 4.93403077e-01
-2.74491102e-01 -7.38326490e-01 -1.96736783e-01 2.48796847e-02
9.90206838e-01 -4.74910468e-01 3.05303991e-01 1.11515737e+00
1.10638118e+00 -1.32289207e+00 5.35707295e-01 3.72098744e-01
2.17243031e-01 -1.04516864e+00 6.12853765e-01 7.10792243e-01
-7.28621423e-01 -3.63109887e-01 -5.00672638e-01 -1.92609087e-01
-5.43809295e-01 -3.78996164e-01 -1.14210212e+00 1.66575179e-01
5.48730552e-01 -7.09274337e-02 -5.10874271e-01 1.04489255e+00
-2.65634596e-01 4.87491101e-01 -2.15941072e-01 -5.64638555e-01
3.25185865e-01 -1.41707748e-01 1.55744329e-01 1.07150137e+00
4.36955750e-01 3.92090976e-01 5.13835490e-01 7.85997808e-01
1.67195052e-01 3.31499606e-01 -6.63942158e-01 1.53287485e-01
5.56986094e-01 9.84325111e-01 -7.35099018e-01 -9.94782671e-02
-1.26772761e-01 7.06977844e-01 6.37457907e-01 1.90894857e-01
-7.42462456e-01 -3.47014934e-01 4.18861389e-01 1.94098130e-02
1.81547012e-02 -2.60090798e-01 -7.19087049e-02 -6.44987881e-01
-5.61324298e-01 -1.21637988e+00 1.03976063e-01 -8.83532226e-01
-8.60213101e-01 2.77691334e-01 2.78114885e-01 -1.18524241e+00
-3.68773162e-01 -8.68855119e-01 -5.40747344e-01 7.00587213e-01
-1.17788124e+00 -7.65198231e-01 -3.87082338e-01 8.40413094e-01
4.89657611e-01 -3.53361785e-01 9.77247655e-01 -3.50488760e-02
-4.17374164e-01 6.97195113e-01 8.63746926e-03 -7.62969181e-02
7.34638035e-01 -1.73801565e+00 5.78155741e-02 3.32364827e-01
-1.10789999e-01 6.38314545e-01 1.07260156e+00 -3.73488367e-01
-1.43776417e+00 -6.14485383e-01 2.51685768e-01 -5.45649767e-01
4.88159418e-01 -1.34110585e-01 -7.23602355e-01 5.06749153e-01
2.61161059e-01 -2.95391709e-01 5.03506422e-01 3.12132478e-01
-7.99487531e-02 1.28228083e-01 -1.13062680e+00 8.91297281e-01
1.02718759e+00 -1.46318242e-01 -7.67086983e-01 3.81923765e-01
7.93705165e-01 -6.33911550e-01 -1.06627524e+00 2.58791596e-01
4.32771087e-01 -7.65296757e-01 1.00014377e+00 -9.22853053e-01
3.92446876e-01 -1.15456305e-01 2.35076204e-01 -1.77848041e+00
-4.74879414e-01 -5.67798257e-01 9.74015146e-03 1.03482938e+00
3.36961567e-01 -3.44436586e-01 1.02255404e+00 5.89621842e-01
-2.94918031e-01 -6.59266293e-01 -3.32472056e-01 -9.10404623e-01
5.78129113e-01 -8.23653676e-03 5.89712143e-01 1.02326822e+00
3.66548210e-01 1.68522969e-01 -1.39723778e-01 1.64108619e-01
3.82410228e-01 -1.64497524e-01 9.18845654e-01 -1.37439239e+00
-7.59934127e-01 -5.19445837e-01 -1.79358125e-01 -8.81444991e-01
2.86069602e-01 -6.37990594e-01 4.27585363e-01 -1.23387337e+00
-1.34621382e-01 -8.94840896e-01 -4.44115192e-01 3.78935844e-01
-1.23565443e-01 -2.70935625e-01 1.09663934e-01 -1.71734706e-01
-7.02217758e-01 3.37105006e-01 1.56095433e+00 3.06700468e-01
-5.88819861e-01 1.22137636e-01 -4.72117633e-01 7.73718774e-01
1.10048163e+00 -5.07602036e-01 -9.22806025e-01 -3.53239089e-01
5.51237524e-01 3.21626514e-01 8.88443068e-02 -1.35174334e+00
4.02209401e-01 -6.90928400e-01 6.04721546e-01 -5.03251515e-02
1.17417976e-01 -8.19190800e-01 -6.82713091e-02 6.04915500e-01
-6.86321557e-01 3.62489045e-01 2.25694433e-01 2.27215633e-01
1.31921604e-01 -7.77168930e-01 9.32094395e-01 -3.68006080e-01
-5.10920167e-01 -8.83158669e-02 -6.29809201e-01 1.25155866e-01
1.15788245e+00 -1.69617638e-01 -3.81768882e-01 -3.54507327e-01
-6.45040154e-01 5.03541410e-01 4.00983334e-01 2.69063354e-01
4.67026800e-01 -1.04717720e+00 -6.75967574e-01 -2.44846698e-02
-1.04123652e-01 8.95956904e-02 1.56161442e-01 4.30986077e-01
-7.41577327e-01 1.95973232e-01 -7.75228560e-01 -2.19324902e-01
-1.15453029e+00 6.66098893e-01 3.20444167e-01 -5.36515057e-01
-3.13169509e-01 9.48072314e-01 2.37211168e-01 -9.09792721e-01
5.04610419e-01 -1.96983978e-01 -4.98329222e-01 -2.26508364e-01
6.18367136e-01 2.47765988e-01 -2.64382154e-01 2.56600436e-02
2.06284478e-01 3.65394652e-01 -7.10455701e-02 -3.86756182e-01
1.50225472e+00 1.58097401e-01 4.50185657e-01 3.50710928e-01
5.54170072e-01 3.76746170e-02 -1.35847664e+00 8.45985711e-02
1.68415189e-01 -3.71197611e-02 -3.12388420e-01 -8.82964969e-01
-4.90645230e-01 6.99337482e-01 7.43380010e-01 1.35624722e-01
8.83109272e-01 -3.02202076e-01 2.29868367e-01 9.07270133e-01
6.08377814e-01 -1.38854253e+00 5.56376576e-01 6.83601081e-01
6.14662528e-01 -1.17123830e+00 -1.80160716e-01 9.31589007e-02
-5.07073939e-01 1.07511520e+00 1.21804512e+00 -3.39118004e-01
-9.57859866e-03 2.96755105e-01 -9.59874764e-02 1.70492232e-01
-9.18471932e-01 -1.88273087e-01 5.67083731e-02 9.26492929e-01
5.96742451e-01 3.37797739e-02 -1.22106113e-01 3.75919640e-01
-6.18579805e-01 -1.76668093e-01 8.73825312e-01 1.14395809e+00
-8.95381033e-01 -1.28335881e+00 -6.53108299e-01 -1.39028162e-01
-1.09480113e-01 2.70426154e-01 -1.19626924e-01 9.84330714e-01
2.34991103e-01 7.09630013e-01 -2.13722304e-01 -1.51026592e-01
6.17999196e-01 1.29584298e-01 9.88621831e-01 -8.35076034e-01
-1.04758596e+00 -4.43545163e-01 -2.19516501e-01 -4.03260589e-01
-2.37726822e-01 -6.10018551e-01 -1.55425906e+00 -2.64971524e-01
3.61212306e-02 5.59908867e-01 7.81643569e-01 7.71677136e-01
-2.10955024e-01 7.53929794e-01 5.80197871e-01 -7.60825992e-01
-8.72416377e-01 -7.04496264e-01 -3.58225763e-01 3.83326530e-01
1.22056507e-01 -7.28618324e-01 -1.72504827e-01 -4.30616625e-02] | [4.027013301849365, 1.4789998531341553] |
f433a4a3-6fc8-4b75-a001-fa205e04678b | when-vision-fails-text-attacks-against-vit | 2306.07033 | null | https://arxiv.org/abs/2306.07033v1 | https://arxiv.org/pdf/2306.07033v1.pdf | When Vision Fails: Text Attacks Against ViT and OCR | While text-based machine learning models that operate on visual inputs of rendered text have become robust against a wide range of existing attacks, we show that they are still vulnerable to visual adversarial examples encoded as text. We use the Unicode functionality of combining diacritical marks to manipulate encoded text so that small visual perturbations appear when the text is rendered. We show how a genetic algorithm can be used to generate visual adversarial examples in a black-box setting, and conduct a user study to establish that the model-fooling adversarial examples do not affect human comprehension. We demonstrate the effectiveness of these attacks in the real world by creating adversarial examples against production models published by Facebook, Microsoft, IBM, and Google. | ['Nicolas Papernot', 'Ross Anderson', 'Ilia Shumailov', 'Jenny Blessing', 'Nicholas Boucher'] | 2023-06-12 | null | null | null | null | ['optical-character-recognition'] | ['computer-vision'] | [ 7.81021774e-01 5.03587902e-01 1.59149170e-01 -7.81459138e-02
-5.23743868e-01 -1.26451457e+00 9.48993564e-01 -1.46390137e-03
-2.00129434e-01 4.24616098e-01 -1.87714532e-01 -7.66911030e-01
5.41427910e-01 -8.66993070e-01 -1.08106565e+00 -2.65508592e-01
-6.32694513e-02 5.81698492e-02 1.29998639e-01 -2.96665847e-01
2.97770798e-01 6.22849464e-01 -1.32275391e+00 6.12811327e-01
7.86976099e-01 1.56545505e-01 -5.96878469e-01 1.30645049e+00
1.17336400e-01 9.10824120e-01 -1.36028266e+00 -8.96106124e-01
5.54278791e-01 -4.58727747e-01 -5.28199792e-01 -1.23677850e-01
8.20723474e-01 -4.20593202e-01 -5.77520907e-01 1.19999385e+00
4.44644302e-01 -2.37154309e-02 6.93572819e-01 -1.91510689e+00
-1.33448505e+00 5.07952690e-01 -3.96257758e-01 -4.52933833e-02
7.21309185e-01 7.96157897e-01 5.02666771e-01 -2.02814817e-01
6.07152760e-01 1.68719220e+00 3.24076951e-01 1.03064919e+00
-1.38466525e+00 -8.14916372e-01 1.33200157e-02 -1.90695047e-01
-9.72614884e-01 -2.61310428e-01 6.46712899e-01 -4.29310590e-01
8.10814500e-01 7.73484528e-01 4.58347321e-01 1.65443540e+00
4.44708288e-01 6.22721791e-01 1.23306787e+00 -9.05823767e-01
2.65085578e-01 1.36824459e-01 -2.39825070e-01 9.25191939e-01
3.18374783e-01 4.49223191e-01 -3.84649545e-01 -6.00149333e-01
6.05526507e-01 -4.21156913e-01 -1.49470091e-01 -3.80526245e-01
-9.26720917e-01 9.87167358e-01 4.37087089e-01 -2.07347497e-01
3.15700293e-01 6.65144563e-01 3.14198732e-01 5.33140004e-01
2.24484559e-02 8.51887286e-01 -2.95374654e-02 2.14617237e-01
-2.86801040e-01 2.13196650e-01 7.22667813e-01 9.13802564e-01
2.47158408e-01 5.70223749e-01 -2.76894808e-01 2.68785357e-01
2.22909406e-01 8.71343017e-01 4.72166717e-01 -9.33921933e-01
6.01186872e-01 3.28001112e-01 1.90111548e-01 -1.11336482e+00
-2.53536552e-02 3.80769491e-01 -2.85375595e-01 1.07746243e+00
6.68717682e-01 -5.25313079e-01 -1.33460629e+00 1.66907215e+00
1.74526200e-01 -4.70141135e-02 1.68622807e-01 3.39111179e-01
6.49044633e-01 6.09309018e-01 4.85431582e-01 3.87893856e-01
9.42158759e-01 -6.58490241e-01 -5.36592722e-01 -5.03561199e-01
6.56960011e-01 -6.49412751e-01 1.45572126e+00 1.90158740e-01
-9.92056549e-01 -3.70598495e-01 -1.41889000e+00 -9.21917185e-02
-7.96260238e-01 -4.15095031e-01 4.40471947e-01 1.49103510e+00
-7.74884045e-01 4.02489096e-01 -6.32743001e-01 -1.24664411e-01
5.43254256e-01 2.32735395e-01 -3.68130356e-01 3.19956392e-02
-1.29749429e+00 1.06479836e+00 3.12071294e-01 -3.02022964e-01
-1.06261253e+00 -5.15501440e-01 -1.15267122e+00 -5.60880043e-02
1.23600692e-01 -6.37437224e-01 1.24198258e+00 -1.50886440e+00
-1.24541616e+00 1.00879610e+00 1.75345004e-01 -4.58594441e-01
1.00629830e+00 -2.47948840e-02 -5.16257823e-01 3.63897562e-01
-4.82879072e-01 7.51421571e-01 1.56355464e+00 -1.67194581e+00
-1.34144306e-01 -1.61876827e-01 5.53520918e-01 1.40119031e-01
-5.34091532e-01 1.85666963e-01 8.41086730e-02 -1.08549845e+00
-7.38384068e-01 -1.06595349e+00 -1.55766308e-01 4.09993470e-01
-9.43585694e-01 5.10409594e-01 1.12917185e+00 -6.05156004e-01
9.60512519e-01 -2.21855116e+00 -2.03919321e-01 4.31125015e-01
2.38034382e-01 4.76450831e-01 -4.82381910e-01 4.44547296e-01
-3.11110526e-01 9.33239102e-01 -2.64370024e-01 6.30028620e-02
2.98389941e-01 -7.32243285e-02 -7.17305243e-01 3.95966887e-01
3.65884304e-02 1.33465719e+00 -6.48611009e-01 -3.99753779e-01
9.78953093e-02 4.24196333e-01 -4.54780668e-01 1.20303720e-01
-5.34892857e-01 2.54485365e-02 -3.38833511e-01 4.52407926e-01
3.88623536e-01 1.72250718e-01 -1.37347141e-02 3.52018744e-01
6.30466521e-01 -3.68937254e-01 -6.25313818e-01 8.80945146e-01
-2.51356214e-01 1.01592612e+00 -1.22823007e-01 -1.52677462e-01
4.97695416e-01 1.00556493e-01 -4.77954030e-01 -5.93830705e-01
7.25808293e-02 -3.78907502e-01 1.68998823e-01 -4.41937149e-01
2.67089546e-01 -1.01601053e-02 -4.26974684e-01 7.58300483e-01
-6.37918353e-01 -5.88519871e-01 -2.64598406e-03 5.95121562e-01
1.25087082e+00 6.77289115e-03 1.83678672e-01 4.12764966e-01
3.24010141e-02 1.88217491e-01 -2.25551277e-01 1.24339426e+00
-2.10378289e-01 5.38237453e-01 8.38326991e-01 -2.84286588e-01
-1.35758877e+00 -1.27783918e+00 3.87748778e-01 1.18860662e+00
-4.97466289e-02 -3.36429656e-01 -1.19155514e+00 -1.12451816e+00
3.22486937e-01 1.24752343e+00 -1.01130486e+00 -6.84079945e-01
-3.97308946e-01 -2.68907040e-01 1.14042151e+00 5.13726950e-01
2.08277941e-01 -1.26497805e+00 -6.12023115e-01 -4.09085721e-01
5.19125164e-01 -8.77478123e-01 -5.35962999e-01 -1.65323257e-01
-3.78068775e-01 -1.20797980e+00 -4.70153242e-01 -6.65749371e-01
1.01491427e+00 -6.19131364e-02 1.00938916e+00 5.27251363e-01
-4.22260642e-01 7.46467948e-01 -2.13489726e-01 -7.96341121e-01
-1.27973032e+00 -3.20684522e-01 -3.80110353e-01 -3.71425390e-01
1.46689132e-01 -2.54480362e-01 -1.20077156e-01 1.45807192e-01
-1.38808858e+00 1.42614782e-01 7.58091435e-02 4.69535559e-01
-8.94017220e-02 -4.66907434e-02 2.35948712e-01 -1.24371910e+00
1.03075039e+00 -3.44152264e-02 -6.63171113e-01 3.83559823e-01
-2.13222474e-01 -1.53779790e-01 9.81573164e-01 -9.71640110e-01
-7.65120864e-01 8.80612954e-02 2.10061222e-01 -4.33502465e-01
-3.05825204e-01 7.65125304e-02 -3.13429356e-01 -5.42983830e-01
1.18712103e+00 -7.68511835e-03 -7.74478167e-02 6.05689324e-02
7.73613513e-01 5.61485469e-01 5.70005774e-01 -4.75734562e-01
1.76068485e+00 3.11749488e-01 -1.55387744e-01 -5.57134032e-01
-2.97627479e-01 7.83230424e-01 -2.80289322e-01 -1.37775689e-01
7.88182020e-01 -4.85427082e-01 -8.51329207e-01 5.70470870e-01
-9.98807728e-01 -6.73503101e-01 -1.43709660e-01 -3.55280191e-01
-4.95024920e-01 4.70944166e-01 -4.64039266e-01 -6.40046716e-01
-8.25511590e-02 -9.44581926e-01 6.26033425e-01 1.43138707e-01
-4.30954188e-01 -8.99853706e-01 -2.47703880e-01 3.90948981e-01
2.71798611e-01 7.12722480e-01 1.57218897e+00 -9.78962898e-01
-5.64847350e-01 -5.41055143e-01 4.18425687e-02 1.44687191e-01
7.27150217e-02 6.25969529e-01 -9.96169508e-01 -3.91780764e-01
-5.01478076e-01 -4.86342043e-01 3.81781965e-01 -2.66656578e-01
1.24349058e+00 -8.08496714e-01 -2.97734529e-01 5.55107296e-01
9.89831686e-01 4.41618264e-01 9.07676399e-01 4.21635568e-01
1.08525145e+00 3.63989860e-01 1.08453624e-01 4.54274900e-02
-2.20918342e-01 3.76912445e-01 6.91641629e-01 -2.56764621e-01
7.58178532e-02 -6.10147536e-01 3.32245022e-01 -2.77446955e-01
5.32797039e-01 -7.02130318e-01 -1.02108705e+00 1.91530824e-01
-1.37835717e+00 -1.06335640e+00 1.50372177e-01 2.09856176e+00
9.01986003e-01 6.13815248e-01 3.06171142e-02 1.60313770e-02
8.87762308e-01 2.54032850e-01 -5.75257361e-01 -1.03179848e+00
-4.21923511e-02 4.00779843e-01 4.79215264e-01 5.23655474e-01
-1.09021676e+00 1.13038528e+00 7.98694897e+00 5.70591986e-01
-1.04184806e+00 -2.17532411e-01 6.87355161e-01 -3.80888283e-01
-6.56214714e-01 -2.41224915e-01 -1.97953478e-01 5.14218986e-01
8.83826256e-01 -5.80366492e-01 5.80711782e-01 8.58842492e-01
4.75870222e-02 1.07665718e-01 -1.15836000e+00 4.44515318e-01
1.95251182e-01 -1.16048324e+00 5.01407504e-01 -1.15479261e-01
7.26467669e-01 -6.82208896e-01 7.05180526e-01 3.82705331e-01
8.55209768e-01 -1.72310638e+00 7.01408207e-01 5.57617098e-02
9.39246535e-01 -1.08746767e+00 -7.65590295e-02 7.68861249e-02
-3.13110262e-01 -1.27223507e-01 -3.73845100e-02 5.91183491e-02
-2.23178908e-01 -2.07050964e-01 -8.81293416e-01 -1.83664188e-01
2.40974143e-01 -1.45743608e-01 -1.16063297e+00 6.36424601e-01
-7.15768576e-01 5.61850309e-01 1.06342928e-02 -5.40002696e-02
3.90889980e-02 4.32152510e-01 5.26457548e-01 1.05447567e+00
-1.23177737e-01 -2.90764928e-01 -1.84999779e-01 9.28868890e-01
-3.93924236e-01 -1.02142215e-01 -1.21447432e+00 -4.87881273e-01
3.65912557e-01 8.81387651e-01 -5.35344124e-01 -2.45781302e-01
-2.07901567e-01 1.32441866e+00 7.69724101e-02 6.57736719e-01
-1.09087026e+00 -7.59993732e-01 6.20039165e-01 9.14379060e-02
8.27757493e-02 -2.42207527e-01 -4.12277967e-01 -7.81017840e-01
-7.12003484e-02 -1.67247880e+00 2.09739834e-01 -1.43555462e+00
-1.04064631e+00 5.02390862e-01 -3.02551370e-02 -7.69727528e-01
-4.18634713e-01 -7.84114122e-01 -8.65154266e-01 8.81310105e-01
-6.77642465e-01 -1.26256919e+00 -1.22243702e-01 6.57156706e-01
1.09227955e-01 -3.01738262e-01 1.02557027e+00 -4.79480326e-01
-5.49760222e-01 1.15592754e+00 1.86549518e-02 5.05500615e-01
6.53801262e-01 -1.34166455e+00 1.34985924e+00 1.12184346e+00
2.41463989e-01 6.90049529e-01 9.94903564e-01 -9.79744554e-01
-1.28565943e+00 -1.07728219e+00 2.99565703e-01 -8.44963789e-01
7.13216543e-01 -8.50258291e-01 -8.36262107e-01 1.16865957e+00
4.71157074e-01 2.76852716e-02 5.02559900e-01 -5.35604298e-01
-9.53293264e-01 5.98925471e-01 -1.51521671e+00 1.46763861e+00
7.85875380e-01 -8.97416413e-01 -6.12368166e-01 5.76415181e-01
9.70429063e-01 -6.09816074e-01 -3.35402548e-01 5.78833595e-02
5.68546474e-01 -6.80518031e-01 1.09998667e+00 -1.31061423e+00
7.20756650e-01 -2.18941644e-01 1.13481291e-01 -1.46664464e+00
1.72522411e-01 -1.11794031e+00 -1.88442647e-01 1.03148806e+00
5.44547439e-01 -6.94317400e-01 6.78819418e-01 1.07740819e+00
3.75687689e-01 -8.90658423e-02 -6.60135686e-01 -6.20311201e-01
4.79212791e-01 -2.15156734e-01 4.85613525e-01 1.00271797e+00
-9.61209740e-03 2.44042706e-02 -4.96833950e-01 2.55466312e-01
3.79702598e-01 -4.20450687e-01 9.85740542e-01 -6.03446841e-01
-3.91460270e-01 -3.50668252e-01 -5.01205981e-01 -3.35391939e-01
4.10357237e-01 -6.24280870e-01 -2.36971140e-01 -1.11040592e+00
-5.43301553e-02 -4.32127602e-02 1.06257081e-01 8.04626346e-01
-5.04630208e-01 5.28989017e-01 7.06607640e-01 -1.38019070e-01
-1.25768334e-01 6.73198029e-02 1.26409829e+00 -4.94375318e-01
1.68261707e-01 -2.48505592e-01 -8.28228176e-01 8.32369089e-01
8.07287395e-01 -7.32874274e-01 -6.55853927e-01 -3.79569978e-01
3.60660076e-01 -3.49914461e-01 6.58223569e-01 -8.25752735e-01
-1.28838569e-01 -3.57233822e-01 8.33945096e-01 1.72578499e-01
3.13976675e-01 -7.86220253e-01 6.68249279e-03 5.91072679e-01
-8.38399887e-01 2.25460872e-01 7.48003781e-01 4.88647550e-01
4.13559884e-01 -3.47547591e-01 9.47382152e-01 -8.95938650e-02
-3.72162163e-01 -1.30875438e-01 -8.02033663e-01 1.69330090e-01
1.40294588e+00 -3.11859071e-01 -9.72783804e-01 -8.44786584e-01
-6.56393528e-01 -1.16480671e-01 1.12373805e+00 5.56544304e-01
4.48478967e-01 -1.02356267e+00 -4.82986033e-01 2.94303834e-01
4.92485948e-02 -7.99828589e-01 -2.28012968e-02 -2.63482749e-01
-8.46007228e-01 -1.28289655e-01 -4.44890410e-01 -4.07874212e-02
-1.65775096e+00 1.19324362e+00 4.23183024e-01 2.06117198e-01
-5.05082607e-01 7.11303532e-01 3.65327775e-01 -2.60448992e-01
3.42385530e-01 1.61112741e-01 2.05671057e-01 -4.86133009e-01
6.06951654e-01 5.41899577e-02 -2.20974073e-01 -3.35363477e-01
-1.59089416e-01 1.22423247e-01 -1.12866379e-01 -3.88832152e-01
6.29124045e-01 2.73430228e-01 3.44243199e-01 -4.20594998e-02
1.09756660e+00 5.49152613e-01 -1.10414827e+00 3.58567655e-01
-5.49242675e-01 -5.80325067e-01 -5.22171617e-01 -1.21143770e+00
-8.37384760e-01 8.55760753e-01 6.15582287e-01 6.69135511e-01
9.10278141e-01 -5.43190181e-01 4.42101389e-01 6.15367591e-01
-3.50173153e-02 -6.20924592e-01 3.34764749e-01 2.24886402e-01
1.04935765e+00 -9.71206963e-01 -3.13432962e-02 -5.11536241e-01
-8.56425226e-01 8.33995819e-01 8.02230597e-01 -3.28168236e-02
7.10314065e-02 7.26026475e-01 4.78097975e-01 1.46511257e-01
-5.26019037e-01 3.96352112e-01 2.03973144e-01 1.28972232e+00
3.08571178e-02 -1.44137338e-01 2.75548637e-01 -3.95169370e-02
-4.34312463e-01 -3.47493052e-01 8.94378483e-01 1.32091105e+00
-2.02282578e-01 -1.02147222e+00 -9.57685947e-01 2.92645544e-01
-7.29344726e-01 -3.59831840e-01 -1.08127654e+00 1.21720994e+00
-3.25063795e-01 1.00174761e+00 -1.65277809e-01 -3.76198322e-01
2.01959550e-01 3.25620949e-01 6.79677963e-01 -5.09783864e-01
-9.65323091e-01 -6.27552509e-01 2.36262038e-01 -3.78010571e-01
2.55138069e-01 -6.73699155e-02 -9.77467716e-01 -5.84054112e-01
2.61583149e-01 -2.99302220e-01 5.25551558e-01 6.38956547e-01
2.32083499e-01 4.26838160e-01 4.89036828e-01 -6.38947368e-01
-5.43241262e-01 -4.65784848e-01 -7.47053251e-02 7.97401667e-01
3.01844478e-01 -1.77039430e-01 -6.70294523e-01 3.72162282e-01] | [5.923095226287842, 8.0703706741333] |
b82d6796-73d6-4c34-a9ae-55c3f1faea8f | topology-aware-loss-for-aorta-and-great | 2307.03137 | null | https://arxiv.org/abs/2307.03137v1 | https://arxiv.org/pdf/2307.03137v1.pdf | Topology-Aware Loss for Aorta and Great Vessel Segmentation in Computed Tomography Images | Segmentation networks are not explicitly imposed to learn global invariants of an image, such as the shape of an object and the geometry between multiple objects, when they are trained with a standard loss function. On the other hand, incorporating such invariants into network training may help improve performance for various segmentation tasks when they are the intrinsic characteristics of the objects to be segmented. One example is segmentation of aorta and great vessels in computed tomography (CT) images where vessels are found in a particular geometry in the body due to the human anatomy and they mostly seem as round objects on a 2D CT image. This paper addresses this issue by introducing a new topology-aware loss function that penalizes topology dissimilarities between the ground truth and prediction through persistent homology. Different from the previously suggested segmentation network designs, which apply the threshold filtration on a likelihood function of the prediction map and the Betti numbers of the ground truth, this paper proposes to apply the Vietoris-Rips filtration to obtain persistence diagrams of both ground truth and prediction maps and calculate the dissimilarity with the Wasserstein distance between the corresponding persistence diagrams. The use of this filtration has advantage of modeling shape and geometry at the same time, which may not happen when the threshold filtration is applied. Our experiments on 4327 CT images of 24 subjects reveal that the proposed topology-aware loss function leads to better results than its counterparts, indicating the effectiveness of this use. | ['Cigdem Gunduz-Demir', 'Rustu Turkay', 'Ilke Ali Gurses', 'Sinan Unver', 'Seher Ozcelik'] | 2023-07-06 | null | null | null | null | ['computed-tomography-ct', 'anatomy'] | ['methodology', 'miscellaneous'] | [ 1.45417780e-01 5.06457508e-01 -1.91342577e-01 -2.87704140e-01
-4.67804037e-02 -3.76325607e-01 5.12334466e-01 3.95482600e-01
-6.13417804e-01 5.73381007e-01 -3.46323788e-01 -1.63420841e-01
-2.53366381e-01 -9.70773220e-01 -7.61173546e-01 -7.77538538e-01
-3.95559072e-01 7.97964633e-01 5.59417069e-01 -1.24485180e-01
9.64769125e-02 6.75197899e-01 -1.22057736e+00 -2.87178636e-01
1.05972755e+00 8.37718666e-01 1.74286619e-01 4.94517505e-01
-1.35900527e-01 2.28786901e-01 -2.24357843e-01 -4.64765161e-01
6.18396342e-01 -5.10830820e-01 -9.82693911e-01 2.62768835e-01
4.53558743e-01 -2.69580875e-02 7.26698861e-02 1.28009856e+00
8.12836960e-02 7.40222558e-02 9.19227302e-01 -9.37108815e-01
-8.09329897e-02 3.02360654e-01 -4.66174811e-01 6.31723851e-02
-9.67608616e-02 -2.29016408e-01 1.07033503e+00 -5.09785354e-01
8.29551816e-01 1.01495922e+00 7.31097400e-01 1.36246890e-01
-1.27022660e+00 -9.24589410e-02 -2.21381649e-01 1.11921944e-01
-1.21892738e+00 1.49562836e-01 9.53573942e-01 -7.59604156e-01
1.19540036e-01 2.27837160e-01 6.61766887e-01 3.45974237e-01
3.48674446e-01 3.57864708e-01 9.38730299e-01 -4.30396050e-01
1.75247133e-01 3.42312068e-01 1.62710577e-01 1.02228642e+00
3.78985822e-01 -2.86916763e-01 3.54219943e-01 -1.54130729e-02
1.15100229e+00 -1.35881230e-01 -3.88992429e-01 -9.95887339e-01
-1.09742951e+00 8.61720145e-01 6.63438082e-01 5.64226806e-01
-2.99850345e-01 -1.97789058e-01 2.98246831e-01 5.47019355e-02
4.05379474e-01 4.16287273e-01 -1.37235492e-01 3.72452348e-01
-9.21095371e-01 4.04852554e-02 9.32179451e-01 5.38877904e-01
1.00162065e+00 -3.06172371e-01 2.23421782e-01 4.78577137e-01
1.25292316e-01 -5.68781979e-02 1.62181139e-01 -9.14720595e-01
2.87768483e-01 8.95869970e-01 -1.98461920e-01 -1.41951394e+00
-5.14471650e-01 -6.65385544e-01 -9.85219121e-01 3.17832917e-01
1.03749025e+00 2.14302093e-01 -8.72297883e-01 1.71999764e+00
5.71765065e-01 -6.20028228e-02 -2.39032745e-01 1.14190173e+00
3.99975032e-01 2.31275126e-01 -8.28462765e-02 -5.99433146e-02
1.25406075e+00 -5.92109442e-01 -2.87470788e-01 2.00946018e-01
6.03291512e-01 -6.44353688e-01 9.16410387e-01 1.72436342e-01
-9.34886158e-01 -3.20725292e-01 -1.13606286e+00 2.11114362e-01
-1.68891475e-01 2.25949883e-01 3.01485062e-01 5.59132814e-01
-7.11294353e-01 1.05462837e+00 -8.97261143e-01 -4.48205471e-01
2.47843668e-01 2.89627433e-01 -1.20955192e-01 4.41946685e-01
-9.45222259e-01 1.12133288e+00 4.19193417e-01 7.01984167e-02
-3.26270521e-01 -5.50613225e-01 -4.84622180e-01 6.57933112e-03
4.22267050e-01 -5.58208883e-01 5.60754478e-01 -1.12519538e+00
-1.22916377e+00 8.42269719e-01 4.52531219e-01 -4.77192372e-01
1.09979928e+00 3.50892305e-01 5.80517352e-02 5.44044197e-01
-3.19590196e-02 5.31955957e-01 6.34190679e-01 -9.73556280e-01
-2.20249206e-01 -2.50401616e-01 4.47565645e-01 3.90246324e-02
-6.20019510e-02 -5.88381827e-01 -1.77911729e-01 -5.11278987e-01
6.29090011e-01 -8.44453454e-01 -4.02478039e-01 4.55412835e-01
-5.95880568e-01 -1.28961399e-01 7.71860540e-01 -7.53570676e-01
6.52575016e-01 -2.10652590e+00 1.81024745e-01 6.76608324e-01
2.23070547e-01 3.14688496e-02 9.50612798e-02 1.26438692e-01
-5.56576848e-02 2.21720457e-01 -5.87343574e-01 1.28247172e-01
-2.73435056e-01 2.33616099e-01 2.64255017e-01 9.60062861e-01
1.24472238e-01 2.64110833e-01 -6.07767999e-01 -8.95280242e-01
8.59491080e-02 4.80380148e-01 -5.23434162e-01 -2.51224339e-01
-2.55784184e-01 6.79963470e-01 -5.61236858e-01 -4.65149842e-02
6.75658643e-01 -2.25499347e-01 2.19571382e-01 -4.67438608e-01
-1.26566947e-01 2.38896444e-01 -1.34420860e+00 1.32339787e+00
-2.04406634e-01 2.99465835e-01 1.32461935e-01 -1.34504414e+00
9.13768649e-01 3.64799887e-01 7.39628792e-01 -2.89002597e-01
2.39607885e-01 1.97740331e-01 2.85460442e-01 -2.37438530e-01
7.74798021e-02 -2.62342721e-01 2.94559509e-01 2.02452227e-01
-2.14423075e-01 -4.48605455e-02 3.61677706e-01 3.69502492e-02
6.62280917e-01 2.72296797e-02 2.22865835e-01 -7.76588857e-01
7.76460767e-01 1.53907994e-02 8.07248771e-01 3.78930688e-01
1.39044493e-01 6.94930077e-01 8.44023645e-01 -6.05954528e-01
-1.36667025e+00 -1.15497398e+00 -6.08224690e-01 3.21142524e-01
2.66583443e-01 -7.75862252e-03 -8.05603564e-01 -7.13615179e-01
-2.81082422e-01 3.80046725e-01 -4.98206109e-01 5.39776757e-02
-6.98218644e-01 -5.93610823e-01 2.14599550e-01 2.11653456e-01
7.63546288e-01 -5.89711547e-01 -9.32785571e-01 7.42133930e-02
-3.00658375e-01 -1.10107458e+00 -3.83431256e-01 -1.05410479e-01
-1.21268880e+00 -1.38049173e+00 -7.83263862e-01 -7.54906595e-01
1.00088549e+00 -3.07382882e-01 7.03660071e-01 3.30713838e-01
-4.06278461e-01 1.32516801e-01 -1.61789447e-01 7.46548548e-02
-5.06061852e-01 1.09335206e-01 -1.48194954e-01 1.71485662e-01
-3.60681087e-01 -7.58601785e-01 -6.21826291e-01 5.41287124e-01
-8.84372473e-01 7.32896104e-02 4.10556853e-01 7.30351686e-01
7.17592061e-01 2.78960526e-01 2.37161875e-01 -7.63287783e-01
1.36916623e-01 -2.44659811e-01 -7.07883775e-01 3.15935612e-01
-5.39714396e-01 1.83629781e-01 6.50934517e-01 -4.59723234e-01
-6.08576000e-01 1.60200357e-01 3.62775363e-02 -2.11246341e-01
5.80726415e-02 4.44934905e-01 1.32252406e-02 -3.89968216e-01
5.51288843e-01 5.15283179e-03 2.90098906e-01 -5.53243935e-01
-4.47467268e-02 7.02166259e-02 3.10307205e-01 -5.18982649e-01
6.02351844e-01 5.93599617e-01 6.80138826e-01 -1.04629874e+00
-4.68984157e-01 -3.89437437e-01 -8.82281363e-01 -2.07370728e-01
9.78401303e-01 -1.80908933e-01 -6.05393171e-01 5.05280457e-02
-1.16894293e+00 -5.12197614e-03 -3.52115840e-01 7.27827013e-01
-7.10093915e-01 7.48862565e-01 -4.68504995e-01 -4.88964677e-01
-1.62679404e-01 -1.29947746e+00 5.57323515e-01 1.15160653e-02
2.95217894e-02 -1.23285830e+00 -7.43948370e-02 9.07905176e-02
2.20118433e-01 7.20974207e-01 1.39095592e+00 -6.53252065e-01
-7.68962443e-01 -1.84469163e-01 -9.86793116e-02 5.96154034e-01
-3.36874556e-03 1.55154467e-01 -4.02882308e-01 -1.37378916e-01
2.28871971e-01 2.58366883e-01 7.00505853e-01 4.28885639e-01
8.99913371e-01 -3.28512847e-01 -1.65062696e-01 4.67749447e-01
1.62522864e+00 5.79345152e-02 5.18548489e-01 2.65438169e-01
6.48903012e-01 9.98825312e-01 2.51310617e-01 1.26617700e-01
4.77915369e-02 8.93974066e-01 5.29952407e-01 -8.49500373e-02
-1.11474104e-01 -5.45916595e-02 3.29926014e-02 7.32201874e-01
-3.55373442e-01 2.66231596e-01 -9.47107911e-01 4.32852894e-01
-1.59824491e+00 -7.33936608e-01 -3.19903851e-01 2.53194690e+00
7.35212147e-01 3.13341081e-01 3.18339139e-01 6.75759241e-02
8.96932900e-01 -6.18716516e-02 -4.55454350e-01 -3.41972947e-01
-1.32013813e-01 1.14943452e-01 6.53786063e-01 5.71888566e-01
-8.44185591e-01 3.89090627e-01 5.06021023e+00 7.83063948e-01
-1.28610647e+00 8.48706663e-02 4.57262844e-01 3.19739759e-01
-1.40329763e-01 2.47766495e-01 -4.81622547e-01 3.69705379e-01
3.54461014e-01 -1.42044257e-02 -6.05360568e-02 7.45681763e-01
1.10401832e-01 -3.02017361e-01 -9.14481163e-01 3.93138945e-01
-2.39421248e-01 -1.16939187e+00 -4.55801673e-02 2.95742422e-01
4.19403881e-01 -3.10347199e-01 -1.34531885e-01 -3.89000416e-01
-3.14526230e-01 -7.62286365e-01 6.11475587e-01 5.95027149e-01
3.38138103e-01 -7.47882366e-01 7.08810508e-01 4.04145926e-01
-1.12104058e+00 3.79526854e-01 -4.07464296e-01 1.87940255e-01
1.76399335e-01 7.41049767e-01 -1.20155597e+00 6.44452095e-01
3.40809524e-01 3.84033918e-01 -5.01230061e-01 1.39931262e+00
2.08120551e-02 3.92684102e-01 -5.50426185e-01 2.99308542e-02
2.37046018e-01 -7.78561890e-01 1.11082065e+00 8.04433644e-01
2.33080134e-01 -2.07651928e-01 2.69430101e-01 1.06878924e+00
2.04887599e-01 5.66541493e-01 -4.22464520e-01 1.69731051e-01
-1.35953531e-01 1.29477811e+00 -1.32976925e+00 -1.06072888e-01
-4.41667624e-02 4.23145503e-01 -5.55052310e-02 1.82097867e-01
-6.24519050e-01 -3.41626763e-01 3.17082256e-01 6.07769251e-01
3.43308121e-01 -2.96190590e-01 -4.23980445e-01 -9.48021829e-01
2.02886090e-01 -4.15109158e-01 1.34747565e-01 -2.98699439e-01
-1.09625149e+00 5.12582958e-01 1.29486650e-01 -1.24560201e+00
4.14439328e-02 -5.81957042e-01 -7.63907850e-01 6.36584580e-01
-9.68482971e-01 -8.12371492e-01 4.93764281e-02 3.91833752e-01
9.80421603e-02 2.90971607e-01 3.67891818e-01 2.19402745e-01
-2.54700035e-01 2.56743342e-01 3.16346553e-03 2.22561941e-01
3.09582144e-01 -1.33265173e+00 -1.73074350e-01 7.01055229e-01
-5.44037968e-02 5.36448479e-01 1.02785325e+00 -7.27376878e-01
-7.17109442e-01 -8.06318462e-01 7.58352757e-01 5.12201060e-03
5.70665717e-01 -2.00855404e-01 -1.04973924e+00 3.89877319e-01
-1.06327385e-01 -1.21587701e-01 6.90621212e-02 -1.20115593e-01
-3.81543040e-02 -1.35427654e-01 -1.25653517e+00 4.91841823e-01
6.60510361e-01 -5.23890480e-02 -3.53908390e-01 5.02869427e-01
3.79612625e-01 -2.61518925e-01 -1.02189493e+00 6.10182643e-01
5.93726218e-01 -1.03922987e+00 9.01603460e-01 -3.76948774e-01
3.04038703e-01 -3.86524916e-01 8.36337060e-02 -1.01690125e+00
2.46986654e-02 -1.91048697e-01 5.98349571e-01 1.02960837e+00
3.55881780e-01 -6.45415783e-01 9.40593481e-01 3.48450601e-01
4.60528582e-02 -9.66945112e-01 -1.18241692e+00 -8.63853455e-01
2.92329937e-01 8.35082978e-02 2.46400177e-01 9.64744806e-01
-3.18539143e-01 6.75228657e-03 -5.98154729e-04 7.22263604e-02
9.38795030e-01 -6.77899877e-03 4.28302228e-01 -1.65701079e+00
-2.90294498e-01 -5.07663846e-01 -8.28385770e-01 -8.01364541e-01
-4.37492132e-02 -1.09700894e+00 -1.60642460e-01 -1.31529343e+00
-5.78180365e-02 -8.06793272e-01 8.39800313e-02 1.65568843e-01
4.60364491e-01 2.53978707e-02 1.41277969e-01 2.58597881e-01
-1.08630985e-01 4.00558531e-01 1.77031684e+00 4.78778966e-02
-2.07975253e-01 3.38182658e-01 -6.31748065e-02 1.09383571e+00
8.26212227e-01 -4.85362142e-01 -2.24648669e-01 6.36525676e-02
1.71379313e-01 1.93150625e-01 6.66604877e-01 -9.83620763e-01
2.24233657e-01 9.86221209e-02 1.55256078e-01 -4.74455684e-01
2.51733631e-01 -9.99688804e-01 3.59528452e-01 7.00054109e-01
-3.34458500e-01 -3.11939958e-02 -2.92577416e-01 5.56777060e-01
2.36457717e-02 -6.95760667e-01 1.17238092e+00 -2.93437839e-01
-1.96918815e-01 1.80772081e-01 -1.58541754e-01 -3.29538509e-02
1.03358114e+00 -5.05082369e-01 -1.31358057e-01 -2.87473351e-01
-8.60943496e-01 -8.48485306e-02 6.36690676e-01 -6.35267645e-02
3.64334881e-01 -1.01107633e+00 -4.86442029e-01 1.29892260e-01
-3.20572406e-01 1.88767672e-01 4.45468202e-02 1.38546562e+00
-8.52346599e-01 2.08213687e-01 -4.70387161e-01 -8.47799599e-01
-1.25177455e+00 1.29016802e-01 7.18608975e-01 -4.03371662e-01
-8.03930342e-01 2.93799311e-01 3.10914427e-01 -3.95274788e-01
2.16945589e-01 -4.37115610e-01 -2.10017115e-01 -2.29833834e-02
-1.29226923e-01 5.52715182e-01 1.78308133e-02 -7.52814829e-01
-1.89062044e-01 8.31981242e-01 1.64678525e-02 1.23420700e-01
1.13490975e+00 1.87391918e-02 -3.90792966e-01 3.39672416e-01
1.30263281e+00 -4.73045604e-03 -1.18101203e+00 -2.01870322e-01
1.28739089e-01 -2.28230238e-01 -1.01704560e-01 -4.57788259e-01
-1.28722596e+00 8.67879510e-01 5.20218551e-01 4.35433805e-01
8.35740566e-01 9.34119374e-02 6.32544100e-01 1.30404696e-01
1.90952793e-01 -9.73690808e-01 1.04159683e-01 2.98007816e-01
7.56544173e-01 -7.53652632e-01 1.28483344e-02 -7.16635883e-01
-2.82317311e-01 1.36572647e+00 3.86904210e-01 -4.91592616e-01
7.02934742e-01 -2.94918269e-01 -2.09953278e-01 -1.39467165e-01
4.92199622e-02 -2.09904566e-01 5.87421536e-01 2.55661160e-01
2.71575272e-01 1.77666601e-02 -8.86593401e-01 6.77026436e-02
-3.23640168e-01 -2.98954397e-01 6.73703313e-01 6.59756660e-01
-5.85899293e-01 -1.22485125e+00 -3.33312929e-01 4.57926184e-01
-5.72718382e-01 2.97285408e-01 -1.99720278e-01 1.07153058e+00
3.18947643e-01 4.32206988e-01 5.13604581e-02 -1.02453910e-01
2.99533516e-01 -6.55843467e-02 5.67696095e-01 -4.09024179e-01
-3.88390958e-01 3.80669488e-03 -7.81724900e-02 -1.62866816e-01
-5.87546468e-01 -6.21188521e-01 -1.27012849e+00 -1.15569115e-01
-3.45420271e-01 3.05632412e-01 8.22992742e-01 1.05593920e+00
-9.01995078e-02 1.77533269e-01 5.46904981e-01 -6.45965159e-01
-6.01476192e-01 -6.19147956e-01 -8.08172584e-01 4.98300284e-01
3.08046639e-01 -8.50131869e-01 -5.24917483e-01 -4.92146574e-02] | [14.221311569213867, -2.5754659175872803] |
f9f39121-6068-4a99-ab34-1948912f8fb6 | extensions-to-brahmic-script-processing | null | null | https://aclanthology.org/2022.lrec-1.692 | https://aclanthology.org/2022.lrec-1.692.pdf | Extensions to Brahmic script processing within the Nisaba library: new scripts, languages and utilities | The Brahmic family of scripts is used to record some of the most spoken languages in the world and is arguably the most diverse family of writing systems. In this work, we present several substantial extensions to Brahmic script functionality within the open-source Nisaba library of finite-state script normalization and processing utilities (Johny et al., 2021). First, we extend coverage from the original ten scripts to an additional ten scripts of South Asia and beyond, including some used to record endangered languages such as Dogri. Second, we augment the language layer so that scripts used by multiple languages in distinct ways can be processed correctly for more languages, such as the Bengali script when used for the low-resource language Santali. We document key changes to the finite-state engine required to support these new languages and scripts. Finally, we add new script processing utilities, including lightweight script-level reading normalization that (unlike existing visual normalization) does not preserve visual invariance, and a fixed-input transliteration mechanism specifically tailored to Brahmic text entry with ASCII characters. | ['Brian Roark', 'Lawrence Wolf-Sonkin', 'Raiomond Doctor', 'Cibu Johny', 'Alexander Gutkin'] | null | null | null | null | lrec-2022-6 | ['transliteration'] | ['natural-language-processing'] | [ 2.96824753e-01 -3.46468300e-01 4.75279205e-02 -6.15289032e-01
-3.95199955e-01 -1.24531639e+00 8.61807883e-01 -1.99008241e-01
-5.86408019e-01 3.24703395e-01 4.38772082e-01 -6.91240907e-01
1.76448628e-01 -5.44692695e-01 -8.29201266e-02 -2.65411556e-01
3.90271097e-01 6.62412226e-01 3.66251320e-01 -8.02707016e-01
2.93909907e-01 8.78560960e-01 -1.20801687e+00 3.20895195e-01
6.04905725e-01 -2.21691102e-01 6.90593347e-02 1.21455610e+00
-3.48121226e-01 8.19594741e-01 -7.51525939e-01 -6.50727510e-01
2.42158636e-01 -5.05554795e-01 -1.06134665e+00 -2.23625153e-01
7.62491047e-01 -4.23515081e-01 -3.93194288e-01 7.46832490e-01
4.53499287e-01 9.75262746e-02 4.23533738e-01 -7.22953439e-01
-5.16846895e-01 9.75034416e-01 -2.91789591e-01 2.55035937e-01
4.23273116e-01 2.95029193e-01 6.98010802e-01 -7.26964355e-01
8.22305322e-01 1.26805902e+00 8.25050950e-01 5.10356903e-01
-1.06415236e+00 -4.13332343e-01 -2.15533763e-01 -2.06720963e-01
-1.23993993e+00 -8.03454041e-01 1.30954623e-01 -4.97613817e-01
1.28860486e+00 8.11657846e-01 3.96900594e-01 8.71833086e-01
-1.05959170e-01 2.45518565e-01 1.11450541e+00 -6.39848948e-01
-2.80520111e-01 -1.25022233e-01 1.93363070e-01 7.97767758e-01
-7.93627370e-03 -7.60035932e-01 -3.91336352e-01 -2.21999511e-01
8.03025544e-01 -3.86914164e-01 3.20724815e-01 2.40532339e-01
-1.37831831e+00 6.52203381e-01 -2.77591765e-01 4.55559433e-01
2.81339198e-01 -4.92525324e-02 8.93894374e-01 1.37500271e-01
3.22621644e-01 3.56845677e-01 -3.41692865e-01 -7.19873548e-01
-1.34127545e+00 1.57286748e-01 7.85777569e-01 1.12817264e+00
5.41456759e-01 4.82998699e-01 -8.49271193e-02 1.29667902e+00
1.94911972e-01 6.30777657e-01 4.50032026e-01 -7.36998022e-01
6.14723802e-01 4.73481387e-01 -1.79446578e-01 -2.60956019e-01
-5.21609664e-01 3.59263271e-02 -5.85358918e-01 1.08372442e-01
5.69130719e-01 8.49043652e-02 -1.32014775e+00 1.44877911e+00
2.26621196e-01 -8.94384146e-01 -1.29492968e-01 5.14163494e-01
8.17916274e-01 7.02093542e-01 4.91011590e-02 2.03699642e-03
1.55599308e+00 -6.36205316e-01 -6.44379914e-01 -2.95108199e-01
6.00274205e-01 -1.44469202e+00 1.61195600e+00 2.04040453e-01
-1.08447659e+00 -2.44149342e-01 -1.10538638e+00 -5.67812204e-01
-6.20194077e-01 3.40374380e-01 6.27633274e-01 1.11474597e+00
-1.16844356e+00 3.42597187e-01 -1.12215066e+00 -1.34496903e+00
1.30307198e-01 9.88716185e-02 -4.21281546e-01 1.68227106e-01
-9.67125058e-01 1.33468914e+00 6.50156975e-01 -1.29597709e-01
-3.51498932e-01 -4.06726241e-01 -8.42711747e-01 -2.79933989e-01
-4.55860188e-03 8.60163197e-02 1.42153037e+00 -7.91847944e-01
-1.67143083e+00 1.30765784e+00 -4.34349254e-02 2.20022157e-01
8.55152011e-01 -1.83544874e-01 -6.82276905e-01 1.40924407e-02
1.33620128e-01 2.78525412e-01 5.91262221e-01 -7.89150774e-01
-3.00694615e-01 -2.01940522e-01 -1.38328388e-01 3.64099473e-01
-3.59088570e-01 1.20179629e+00 -9.86511230e-01 -1.04003501e+00
-4.00592126e-02 -8.66695702e-01 2.87144743e-02 -4.10092697e-02
-3.23342770e-01 3.07173789e-01 9.57234204e-01 -1.50873923e+00
1.50225580e+00 -1.99729252e+00 -6.65474162e-02 5.20799398e-01
-1.02982491e-01 4.39541668e-01 -1.62745759e-01 7.62120664e-01
-3.22483145e-02 1.39104828e-01 -5.38453460e-01 -2.80559450e-01
6.68384582e-02 8.32273602e-01 -1.68859959e-01 7.25056171e-01
-4.34067547e-02 7.24284589e-01 -5.16935468e-01 -6.04234934e-01
2.55485594e-01 2.72373825e-01 -2.86495596e-01 4.03855667e-02
4.12146619e-04 6.56725317e-02 3.14764291e-01 7.70416558e-01
7.07723439e-01 2.76792109e-01 4.03128833e-01 7.18299970e-02
-8.33482146e-01 5.05278111e-01 -1.36160147e+00 1.62301695e+00
-3.82616490e-01 7.78726637e-01 2.07610294e-01 -1.70085818e-01
8.30132723e-01 1.04035474e-01 -2.37615064e-01 -1.71495065e-01
-1.07535169e-01 2.08252162e-01 -2.85013914e-02 -3.68942887e-01
1.07184017e+00 1.99355651e-02 -3.68281126e-01 7.17881680e-01
1.97034851e-01 -6.88447952e-01 8.49770844e-01 6.29370511e-01
7.30067313e-01 4.89997327e-01 7.36710191e-01 -3.41214448e-01
4.84730899e-01 2.35244855e-01 3.18278283e-01 9.33487713e-01
-5.97842000e-02 7.95134127e-01 5.35076678e-01 -2.76492208e-01
-1.80958235e+00 -1.13439691e+00 -3.03574026e-01 1.94812620e+00
-7.36783504e-01 -7.40334332e-01 -9.33021605e-01 -2.00946003e-01
-5.11043131e-01 8.93043935e-01 -4.69361991e-01 2.58088738e-01
-8.11696172e-01 -8.20337534e-01 1.65130579e+00 5.97226381e-01
5.22291481e-01 -1.04476762e+00 -4.91959304e-01 9.17272791e-02
-2.54270546e-02 -1.03044307e+00 -7.26970971e-01 2.63627052e-01
-4.89645034e-01 -7.38905787e-01 -5.17539382e-01 -7.50035644e-01
4.62700307e-01 -2.85932660e-01 7.82435715e-01 -1.81716140e-02
-3.68863434e-01 4.69135165e-01 -3.81802499e-01 -1.90344393e-01
-1.19564617e+00 2.95770198e-01 1.65570423e-01 -5.34945011e-01
8.86132047e-02 7.44625106e-02 3.93585950e-01 1.47475317e-01
-1.23597968e+00 3.64046901e-01 4.13970388e-02 5.10279298e-01
4.81663011e-02 -4.43374336e-01 -2.49546215e-01 -1.16834509e+00
4.13205743e-01 -4.35727369e-03 -6.16183698e-01 6.24729633e-01
-1.30762219e-01 -1.51812702e-01 9.71133590e-01 -2.31247038e-01
-1.55725849e+00 2.19411641e-01 -5.31316459e-01 5.41052103e-01
-2.38115087e-01 4.50327992e-01 -2.73223042e-01 -7.00575411e-02
7.55899191e-01 4.08222377e-01 -1.39793485e-01 -6.58374250e-01
7.55874515e-01 1.18879783e+00 1.27340817e+00 -7.15134323e-01
1.11975670e+00 3.37452531e-01 -3.59039277e-01 -1.31421506e+00
-2.48733878e-01 -3.88621986e-01 -1.22115064e+00 -1.96300209e-01
7.58142591e-01 -6.91645145e-01 -2.67056435e-01 9.69518006e-01
-1.23015952e+00 -5.36715031e-01 -1.37136504e-01 1.79926872e-01
-3.72119576e-01 5.78892469e-01 -1.00284541e+00 -4.95996565e-01
-5.29656351e-01 -9.62538838e-01 6.94503248e-01 3.93607497e-01
-6.82768524e-01 -8.68049800e-01 4.81572717e-01 1.00271523e-01
5.28390646e-01 -4.02679807e-03 1.06782067e+00 -7.62881458e-01
3.67199063e-01 1.86781604e-02 -3.15227360e-01 3.05580378e-01
2.97504365e-01 7.98699200e-01 -7.98480928e-01 -3.58026296e-01
-4.41066772e-01 -1.09774582e-01 3.54276925e-01 -4.20918286e-01
4.61510301e-01 -2.88954973e-01 4.29973155e-01 8.83783877e-01
1.07178283e+00 1.31679311e-01 7.56277084e-01 6.11723363e-01
9.41644430e-01 4.01112467e-01 2.34303921e-02 5.25890648e-01
3.37285280e-01 5.66292465e-01 -2.79429317e-01 -2.82780349e-01
-2.74431497e-01 -1.65549174e-01 6.95452511e-01 1.28230858e+00
-3.70616019e-01 7.92508498e-02 -1.18966329e+00 3.84273916e-01
-1.49471927e+00 -1.11819279e+00 -4.92889255e-01 2.11680961e+00
1.19284797e+00 -1.65746585e-01 2.46949136e-01 -3.29934582e-02
6.02192283e-01 3.26982915e-01 -2.92545527e-01 -1.13923109e+00
-7.31114805e-01 5.61217308e-01 8.64634573e-01 6.12172902e-01
-1.20988309e+00 1.68905973e+00 7.51867390e+00 5.83955646e-01
-1.04365921e+00 8.92952010e-02 2.88862139e-02 -1.02719463e-01
-1.26498297e-01 1.47436365e-01 -8.36326063e-01 1.64241806e-01
9.40030277e-01 -1.50448918e-01 7.85023868e-01 4.99233425e-01
4.75230634e-01 -1.17861770e-01 -6.32235408e-01 7.31897354e-01
4.52128947e-01 -1.13692784e+00 6.71816543e-02 -3.95804018e-01
5.71284533e-01 2.86695361e-01 -3.02213728e-01 1.02370478e-01
9.42069829e-01 -1.00073147e+00 1.24981165e+00 2.86753833e-01
1.41796815e+00 -7.16090977e-01 2.82521755e-01 -1.88740969e-01
-1.11087406e+00 4.05249953e-01 -3.77748758e-01 -1.33731723e-01
2.16350541e-01 -7.97605813e-02 -7.83711135e-01 2.47817412e-01
8.44083965e-01 6.25800073e-01 -1.36452138e+00 5.59704840e-01
-4.00971115e-01 1.22648215e+00 -5.50503910e-01 4.01342362e-02
1.99641943e-01 -1.83014378e-01 6.02507472e-01 2.09534025e+00
6.23757532e-03 -5.42048030e-02 -3.90538089e-02 3.11247408e-01
2.01938465e-01 5.40247023e-01 -3.52483422e-01 -2.26469517e-01
2.44107336e-01 1.36388516e+00 -1.14895618e+00 -6.93012655e-01
-5.02187848e-01 1.56682909e+00 2.51280248e-01 3.56791556e-01
-8.46779287e-01 -7.98880816e-01 7.76963532e-01 5.77064930e-03
4.30609025e-02 -7.61549711e-01 -5.25197744e-01 -1.36381507e+00
-2.37849131e-01 -1.32836938e+00 6.84626579e-01 -9.68348086e-01
-8.78033221e-01 4.07153964e-01 1.53885305e-01 -7.78350830e-01
-1.17556132e-01 -7.70648241e-01 -5.74853063e-01 1.04488587e+00
-5.51953733e-01 -1.65537703e+00 -7.11345598e-02 7.64843702e-01
4.79280174e-01 -2.71417230e-01 1.00652313e+00 3.10864329e-01
-6.61093235e-01 7.16836691e-01 5.22182047e-01 6.67007923e-01
1.03832006e+00 -1.35417938e+00 1.10649693e+00 1.55783474e+00
2.68389005e-02 1.04790187e+00 6.57541573e-01 -9.13897395e-01
-1.20044196e+00 -9.28948104e-01 9.67947304e-01 -4.51940358e-01
9.09119010e-01 -9.43572938e-01 -9.72552359e-01 1.25384033e+00
3.25684607e-01 -6.11152887e-01 7.19342411e-01 -2.24371806e-01
-6.88425124e-01 2.92888820e-01 -1.05977976e+00 1.06973422e+00
8.21553588e-01 -7.08121419e-01 -7.08996356e-01 2.45708302e-01
3.31490904e-01 -6.91025972e-01 -8.30466628e-01 -4.17619646e-01
7.52092481e-01 -5.19509375e-01 5.96589386e-01 -7.77181447e-01
1.93334162e-01 -7.08750904e-01 -2.33139515e-01 -1.18930697e+00
-4.51172203e-01 -9.78751063e-01 6.42656922e-01 1.72269046e+00
2.27460206e-01 -6.80099964e-01 2.45174050e-01 5.21723211e-01
-2.74055421e-01 5.71464658e-01 -9.53272164e-01 -7.61179984e-01
2.31435910e-01 -6.39634371e-01 5.50703108e-01 1.22606063e+00
7.64375404e-02 1.96592480e-01 -6.76545680e-01 -4.67671454e-02
2.50988483e-01 -5.13686836e-01 8.21588099e-01 -7.22289741e-01
-3.20190519e-01 -4.84206438e-01 -3.61620367e-01 -4.97778714e-01
-2.93910831e-01 -1.29408979e+00 5.04080467e-02 -1.62590253e+00
2.48208255e-01 -1.40314028e-01 4.49018151e-01 1.21662879e+00
-3.32367048e-02 6.16949737e-01 5.44833362e-01 3.31397593e-01
-2.29529262e-01 -1.21762432e-01 6.00204289e-01 1.73235804e-01
-2.47792587e-01 -4.67631906e-01 -5.71365774e-01 7.68656790e-01
8.80435169e-01 -3.36369812e-01 1.58410072e-01 -7.09455609e-01
3.13484102e-01 -7.37822175e-01 7.35432208e-02 -7.71535039e-01
1.16436258e-01 -6.06616080e-01 6.92719996e-01 -4.60647196e-01
-1.91313878e-01 -2.57174999e-01 2.62954354e-01 4.10821766e-01
-1.33499563e-01 4.89263773e-01 5.44227898e-01 -6.48477316e-01
4.18534636e-01 -3.41606885e-01 1.18044043e+00 -2.03883976e-01
-9.40312147e-01 -3.24593991e-01 -1.34653628e+00 1.62837178e-01
6.63121939e-01 -3.40464652e-01 -6.92736983e-01 -1.52353153e-01
-2.54839569e-01 -1.96185634e-01 9.55875397e-01 4.91233230e-01
8.45791996e-02 -9.22468424e-01 -8.57307673e-01 3.58826637e-01
2.90092081e-01 -5.17646670e-01 -1.64509714e-01 3.37951839e-01
-1.63510692e+00 1.23512894e-01 -6.19204283e-01 -1.93234995e-01
-1.56132805e+00 -7.34746754e-02 9.35573801e-02 7.16392919e-02
-4.98866618e-01 3.85876834e-01 -4.51943427e-01 -1.19668484e+00
-3.06396425e-01 -1.39381170e-01 7.95704778e-03 -1.64077301e-02
7.06131518e-01 6.85368717e-01 3.92419755e-01 -1.26334321e+00
-6.48412049e-01 4.30274308e-01 -2.31377661e-01 -6.23233020e-01
1.22719526e+00 -1.27621301e-04 -6.56311989e-01 5.41778266e-01
7.80438781e-01 6.06787741e-01 -6.84402108e-01 7.55474046e-02
-4.61880639e-02 -7.33503178e-02 -5.12573481e-01 -1.13134527e+00
-3.56480867e-01 6.34601951e-01 3.91006142e-01 -2.71208346e-01
8.56775105e-01 -1.18984550e-01 1.98407501e-01 4.11454946e-01
-2.21176699e-01 -1.51983917e+00 -7.12396920e-01 1.30238855e+00
7.50287533e-01 -5.81063747e-01 5.73666155e-01 -1.32769151e-02
-8.01553428e-01 1.41391635e+00 5.30058265e-01 6.45493209e-01
1.47612551e-02 6.86641157e-01 6.01290464e-01 8.40900913e-02
-1.76691338e-01 -1.09360710e-01 -4.57958952e-02 7.25920796e-01
8.52873743e-01 2.97705263e-01 -6.14694357e-01 3.32389235e-01
-8.40142429e-01 -4.23121959e-01 1.03221071e+00 1.29107165e+00
-2.69583791e-01 -1.25814104e+00 -1.06009686e+00 6.18079007e-01
-4.59065199e-01 -5.60310066e-01 -6.32631719e-01 8.30187857e-01
-8.35943094e-04 6.27648473e-01 3.41274232e-01 -3.43539678e-02
3.89306068e-01 2.97788769e-01 4.38319445e-01 -6.95128739e-01
-1.11860991e+00 8.49421397e-02 3.43199760e-01 -1.25031471e-01
1.62895352e-01 -8.19032907e-01 -1.23822975e+00 -7.76295245e-01
2.79066414e-01 -3.35842997e-01 7.75271833e-01 8.16893578e-01
-2.59013802e-01 8.72591585e-02 -4.34411839e-02 -7.98526466e-01
-3.00106227e-01 -1.03174520e+00 -5.65346777e-01 2.85577238e-01
-3.14862520e-01 1.38848662e-01 1.87263321e-02 6.30329847e-01] | [10.535441398620605, 10.380023956298828] |
cbc00d0f-c325-483c-a359-526a7207fad2 | self-paced-learning-with-adaptive-deep-visual | 1807.09200 | null | http://arxiv.org/abs/1807.09200v1 | http://arxiv.org/pdf/1807.09200v1.pdf | Self-Paced Learning with Adaptive Deep Visual Embeddings | Selecting the most appropriate data examples to present a deep neural network
(DNN) at different stages of training is an unsolved challenge. Though
practitioners typically ignore this problem, a non-trivial data scheduling
method may result in a significant improvement in both convergence and
generalization performance. In this paper, we introduce Self-Paced Learning
with Adaptive Deep Visual Embeddings (SPL-ADVisE), a novel end-to-end training
protocol that unites self-paced learning (SPL) and deep metric learning (DML).
We leverage the Magnet Loss to train an embedding convolutional neural network
(CNN) to learn a salient representation space. The student CNN classifier
dynamically selects similar instance-level training examples to form a
mini-batch, where the easiness from the cross-entropy loss and the true
diverseness of examples from the learned metric space serve as sample
importance priors. To demonstrate the effectiveness of SPL-ADVisE, we use deep
CNN architectures for the task of supervised image classification on several
coarse- and fine-grained visual recognition datasets. Results show that, across
all datasets, the proposed method converges faster and reaches a higher final
accuracy than other SPL variants, particularly on fine-grained classes. | ['Vithursan Thangarasa', 'Graham W. Taylor'] | 2018-07-24 | null | null | null | null | ['fine-grained-visual-recognition'] | ['computer-vision'] | [ 8.22174847e-02 -2.55894721e-01 -3.34755093e-01 -7.75256753e-01
-7.49734402e-01 -3.25278252e-01 5.22411287e-01 1.81192741e-01
-7.49874830e-01 5.59988320e-01 6.30687922e-02 -1.58948570e-01
-3.21032912e-01 -6.12075984e-01 -7.41208792e-01 -7.50425518e-01
-6.39996529e-02 3.69954884e-01 -7.32046813e-02 2.55794793e-01
2.09320083e-01 6.42792165e-01 -1.68782830e+00 3.22169989e-01
9.70290244e-01 1.40283549e+00 2.37003744e-01 5.18088520e-01
-1.83630690e-01 7.93784857e-01 -5.38257897e-01 -3.64020884e-01
3.97384256e-01 -2.40410820e-01 -6.49887443e-01 -1.28620461e-01
7.57599473e-01 -3.01420212e-01 -1.78262249e-01 8.67974997e-01
7.10584700e-01 2.86905318e-01 7.25757003e-01 -1.38208485e+00
-7.10778177e-01 5.51881671e-01 -3.89001131e-01 5.69576144e-01
-5.00011683e-01 3.01881135e-01 1.23555028e+00 -1.20365608e+00
3.17475617e-01 1.16172945e+00 5.47095656e-01 7.05309033e-01
-1.39508128e+00 -7.88686037e-01 3.57576787e-01 3.48300010e-01
-1.19401479e+00 -3.29397261e-01 9.13231432e-01 -4.37033921e-01
7.28236079e-01 -6.33184686e-02 4.41181958e-01 1.11839092e+00
1.40293181e-01 9.72657263e-01 9.65403080e-01 -2.33662337e-01
6.74907327e-01 2.44947448e-01 2.59101421e-01 4.76073027e-01
2.14277491e-01 2.51347154e-01 -6.96800172e-01 1.28089935e-01
4.42003518e-01 2.74697840e-01 3.48008759e-02 -6.24000907e-01
-8.81997168e-01 9.65057731e-01 7.76044607e-01 5.92185482e-02
-4.25669312e-01 8.78486484e-02 4.67781752e-01 4.82436061e-01
7.06532061e-01 5.18212676e-01 -5.13754964e-01 -2.64079511e-01
-9.20112908e-01 2.59849489e-01 5.00064909e-01 6.35513365e-01
8.55495214e-01 1.07150108e-01 -5.29428184e-01 9.72106159e-01
-1.41886529e-02 8.55982900e-02 7.71909356e-01 -6.80096567e-01
3.75090182e-01 7.70565987e-01 -2.65213937e-01 -6.28979921e-01
-2.83479273e-01 -8.78684759e-01 -8.47953618e-01 4.46061313e-01
2.76695430e-01 -3.01771998e-01 -9.55009222e-01 1.81946838e+00
3.44267964e-01 9.08237547e-02 1.35001794e-01 9.01076496e-01
6.23529673e-01 6.18104815e-01 4.25324023e-01 1.08772919e-01
9.98755693e-01 -1.10747528e+00 -3.61466348e-01 -2.99693137e-01
6.25878990e-01 -2.83847690e-01 1.25013828e+00 2.16535196e-01
-8.92168403e-01 -8.15873206e-01 -1.12302911e+00 -1.35140508e-01
-3.86816800e-01 2.00619563e-01 3.70209187e-01 2.19064206e-01
-8.80554318e-01 9.45617080e-01 -6.55725300e-01 -6.68531731e-02
9.79097307e-01 2.60447711e-01 -8.29752386e-02 -2.51020610e-01
-8.80490959e-01 7.47734845e-01 5.23328006e-01 -1.38770804e-01
-1.09017158e+00 -1.30209231e+00 -6.62951648e-01 2.60208637e-01
-1.00517003e-02 -3.70996118e-01 1.16861439e+00 -1.26497459e+00
-1.27772510e+00 8.10967445e-01 1.15362480e-01 -7.17243612e-01
5.72206438e-01 -2.32219607e-01 -3.72083113e-02 -1.70330033e-01
1.05721474e-01 1.01375544e+00 9.65177834e-01 -8.17607045e-01
-8.51080239e-01 -2.29099587e-01 -1.15112886e-01 3.89939159e-01
-8.35894704e-01 -2.54363567e-01 -1.14797965e-01 -7.23442674e-01
-2.06941456e-01 -6.51078165e-01 -4.19858396e-02 3.73268515e-01
-1.01297483e-01 -7.21411109e-01 6.93196893e-01 -1.66410699e-01
1.05525184e+00 -2.47270203e+00 1.93248659e-01 -2.62519494e-02
3.08381587e-01 3.15844983e-01 -3.43378544e-01 2.78020259e-02
-2.40057141e-01 -1.09219626e-01 -1.34374991e-01 -5.19371867e-01
9.40965191e-02 2.19311476e-01 -2.40441710e-01 3.59239191e-01
6.40476286e-01 8.40546131e-01 -9.28204119e-01 -1.48433447e-01
1.45310611e-01 3.52702796e-01 -5.44539511e-01 4.84637469e-01
-2.00435415e-01 1.33390486e-01 -2.24938214e-01 4.79821593e-01
4.79693532e-01 -3.75863612e-01 -2.64736831e-01 -1.91976637e-01
3.09061911e-02 1.63608149e-01 -9.72958386e-01 1.50763202e+00
-5.79048038e-01 7.86530793e-01 -3.80663007e-01 -1.00284231e+00
1.10791087e+00 -2.11527377e-01 2.58384556e-01 -9.93049383e-01
-6.55098632e-02 6.04091696e-02 1.13112219e-01 -2.99092650e-01
3.06392550e-01 5.52904680e-02 1.95484221e-01 4.00436997e-01
2.03802451e-01 3.49180371e-01 6.88153058e-02 -1.20352320e-01
9.21975851e-01 -4.07647863e-02 1.34258598e-01 -4.21938360e-01
1.39682725e-01 -7.55169988e-02 6.89957261e-01 6.20195866e-01
-4.95464712e-01 4.46903616e-01 4.98104781e-01 -9.46969688e-01
-1.20521140e+00 -1.02814507e+00 -2.53276765e-01 1.57495832e+00
-8.71952772e-02 -1.14153296e-01 -6.54078007e-01 -9.39481616e-01
2.96651185e-01 7.55962312e-01 -8.77987623e-01 -5.79772055e-01
-3.69201094e-01 -6.58391833e-01 7.44456053e-02 7.67796993e-01
5.20976126e-01 -1.27854228e+00 -7.00401664e-01 4.91560027e-02
3.88697296e-01 -8.91663969e-01 -5.23877025e-01 5.44813991e-01
-8.93906355e-01 -8.24003518e-01 -7.57178664e-01 -8.68072748e-01
9.46935296e-01 7.78172389e-02 1.10712731e+00 -1.88810095e-01
-5.02869666e-01 -5.07577918e-02 -2.20961675e-01 -3.87930065e-01
-1.74722359e-01 2.84265637e-01 2.93952469e-02 2.17666715e-01
6.26180828e-01 -3.70753437e-01 -7.90354908e-01 1.50147170e-01
-7.25502253e-01 8.43990371e-02 7.03006208e-01 1.04051971e+00
6.71581566e-01 8.42890795e-03 6.23134673e-01 -7.34952092e-01
7.46213973e-01 -5.44967949e-01 -6.57769561e-01 9.27000046e-02
-9.03480053e-01 5.04706979e-01 9.64287579e-01 -6.29501104e-01
-5.94153345e-01 -1.89341325e-02 6.16858788e-02 -8.31173003e-01
-1.81219339e-01 3.75914156e-01 -1.77806877e-02 1.10923961e-01
8.86061847e-01 2.32216522e-01 3.91450524e-02 -4.10681248e-01
3.22677255e-01 5.83151877e-01 2.40133628e-01 -6.05449975e-01
6.81836128e-01 3.74278948e-02 -2.28535041e-01 -4.15416151e-01
-1.26677740e+00 -2.20099494e-01 -4.88000453e-01 -9.73596126e-02
7.20732033e-01 -1.02531922e+00 -5.07446408e-01 3.07371676e-01
-7.35131502e-01 -6.75486445e-01 -7.43463755e-01 3.81214142e-01
-2.97451466e-01 -3.22959036e-01 -2.82207012e-01 -6.07715666e-01
-4.27399874e-01 -1.14779758e+00 8.29895139e-01 4.91724938e-01
-1.69796735e-01 -1.04536808e+00 1.09823989e-02 1.63293593e-02
5.53957760e-01 3.29685122e-01 9.11739647e-01 -9.36150372e-01
-4.37581748e-01 -1.00936674e-01 -3.98615092e-01 6.99486673e-01
1.86242476e-01 -7.27861151e-02 -1.19781637e+00 -5.54047227e-01
-2.12147102e-01 -8.23509157e-01 9.86926138e-01 3.67676586e-01
1.72463834e+00 -3.07103246e-01 5.09531759e-02 9.09452200e-01
1.41714907e+00 -2.59163193e-02 2.51099795e-01 5.21462798e-01
7.09514439e-01 5.61337769e-01 6.76235974e-01 5.91815233e-01
3.19266737e-01 4.26852793e-01 4.63797331e-01 -5.15971817e-02
-2.07427099e-01 -1.88840598e-01 2.58244962e-01 5.28943241e-01
4.29396123e-01 1.53487980e-01 -8.63279879e-01 6.48930132e-01
-1.63212359e+00 -7.54439056e-01 6.19750679e-01 2.14772058e+00
1.04479170e+00 2.38900810e-01 2.15142310e-01 3.72604690e-02
6.25285387e-01 2.17448935e-01 -1.14536870e+00 -5.46798646e-01
4.93172929e-02 2.37980261e-01 4.74180281e-01 2.22982436e-01
-1.18359852e+00 8.91263604e-01 5.32670307e+00 8.83632123e-01
-1.42611217e+00 3.72526771e-03 1.13443744e+00 -2.59803534e-01
-1.97384477e-01 -4.51061189e-01 -1.03438783e+00 6.24079406e-01
1.09520233e+00 -2.02127054e-01 3.23994309e-01 1.35166740e+00
6.78230599e-02 3.53549570e-01 -1.50690639e+00 1.16571951e+00
-4.95919026e-02 -1.50627708e+00 2.22412497e-01 -1.54665202e-01
8.59285295e-01 2.63951480e-01 3.81037652e-01 5.10078192e-01
3.75187486e-01 -1.05122924e+00 7.54308224e-01 3.06734115e-01
8.61798525e-01 -1.12219226e+00 4.98300314e-01 2.28289083e-01
-9.18053031e-01 -5.11175871e-01 -6.62745595e-01 1.23000912e-01
-4.66790944e-01 6.70673013e-01 -8.49914134e-01 1.48720983e-02
7.41278052e-01 9.65535760e-01 -6.23233438e-01 1.11289752e+00
9.85222403e-03 6.18806422e-01 1.89473312e-02 -3.63010645e-01
4.28244382e-01 1.00820102e-01 1.38748214e-01 1.16434073e+00
3.62286344e-02 -2.27261961e-01 2.77483091e-02 9.41337228e-01
-4.87542272e-01 -7.63698891e-02 -2.56500006e-01 1.24858133e-02
6.42714858e-01 1.28835130e+00 -4.45307314e-01 -2.36285955e-01
-1.19852282e-01 8.38578522e-01 8.82133365e-01 3.02119941e-01
-6.42522335e-01 -4.45058137e-01 1.04215634e+00 -1.62102565e-01
5.09876192e-01 1.75183583e-02 -5.33930719e-01 -9.00435150e-01
4.62866612e-02 -8.10561001e-01 5.35671413e-01 -3.10099840e-01
-1.54396629e+00 6.98596060e-01 -1.65641189e-01 -1.39784920e+00
-1.35607794e-01 -7.53458858e-01 -6.87330902e-01 8.31827104e-01
-1.98677468e+00 -5.80315411e-01 -4.98646408e-01 4.10821915e-01
8.73663902e-01 -4.10327524e-01 6.06371760e-01 2.71851271e-01
-8.19208622e-01 1.05710483e+00 3.81090015e-01 2.43473455e-01
6.56893611e-01 -1.45293880e+00 4.94970471e-01 6.27662897e-01
1.30449846e-01 2.38811404e-01 3.86409789e-01 -1.65840670e-01
-1.19502950e+00 -1.58250403e+00 6.67026579e-01 -2.70522445e-01
4.73569036e-01 -5.00643253e-01 -8.66537869e-01 2.64878631e-01
1.82176214e-02 5.05279005e-01 6.48983419e-01 2.65147742e-02
-5.63227773e-01 -7.40089774e-01 -1.10168600e+00 6.27480030e-01
8.99352431e-01 -5.07922828e-01 -4.67968881e-01 4.14490253e-01
8.49343121e-01 -2.86923707e-01 -7.51707673e-01 2.04494074e-01
3.25714499e-01 -7.70345867e-01 8.22127342e-01 -8.37342799e-01
5.64462960e-01 -5.03765931e-03 -1.07333310e-01 -1.57991624e+00
-4.62697536e-01 -3.93105805e-01 -1.75038412e-01 1.02953601e+00
4.33891296e-01 -4.68354762e-01 9.76087451e-01 7.26435840e-01
-1.01564787e-01 -1.15342224e+00 -8.28790247e-01 -8.01458657e-01
2.29482472e-01 -2.40524009e-01 5.22402525e-01 9.27588522e-01
-4.81023759e-01 2.63926566e-01 -9.19251516e-02 3.63499559e-02
8.69527698e-01 1.27262056e-01 5.60565412e-01 -1.35835266e+00
-2.07917318e-01 -6.73023641e-01 -4.99086618e-01 -8.79956126e-01
2.57055491e-01 -9.36568022e-01 6.05150014e-02 -1.29468775e+00
1.72116950e-01 -6.30424500e-01 -7.68293440e-01 5.89053810e-01
-2.61673778e-01 -1.45834647e-02 7.70037919e-02 1.27241135e-01
-6.61906481e-01 7.83149481e-01 1.06729591e+00 -1.74183965e-01
-1.94705471e-01 2.34569889e-02 -6.77984357e-01 2.63066530e-01
7.45636106e-01 -6.03154361e-01 -6.21404827e-01 -5.34157097e-01
-2.39286385e-02 -4.88270491e-01 3.23929220e-01 -1.11730492e+00
3.43364209e-01 -1.05582654e-01 7.15736866e-01 -4.14452463e-01
5.70370071e-02 -6.70832038e-01 -4.53881621e-01 5.15313268e-01
-9.76486027e-01 4.26861085e-02 2.95873731e-01 5.03441453e-01
-7.95051977e-02 -1.63914576e-01 1.11568010e+00 2.22603470e-01
-7.89319634e-01 7.92275250e-01 1.67592421e-01 4.18329328e-01
1.02565885e+00 -2.39703074e-01 -1.78923234e-01 3.83526944e-02
-4.77025896e-01 2.68409908e-01 1.42530501e-01 6.72024965e-01
8.30987990e-01 -1.48964500e+00 -7.13030338e-01 3.89735281e-01
4.50570643e-01 3.65156084e-01 1.13162622e-01 3.95379603e-01
-3.23283523e-01 1.09071516e-01 -4.07832950e-01 -8.62069011e-01
-9.05731022e-01 4.24097836e-01 4.19993222e-01 -9.25667584e-02
-5.25393546e-01 1.15875435e+00 2.31142744e-01 -4.00863767e-01
6.91689312e-01 -5.36668718e-01 -9.73093137e-02 1.59867495e-01
7.48773277e-01 2.55322963e-01 9.20674428e-02 -6.70161322e-02
-2.92895198e-01 2.99187392e-01 -5.38750768e-01 3.03409576e-01
1.52760160e+00 1.17024265e-01 4.00938213e-01 5.17807722e-01
1.61891639e+00 -7.20315635e-01 -2.01939750e+00 -5.56150198e-01
1.14968270e-01 -3.86326134e-01 2.65746772e-01 -7.06280470e-01
-1.13771176e+00 9.37254310e-01 9.81927276e-01 -7.25444630e-02
1.01298642e+00 -1.77853286e-01 5.21992803e-01 4.21301037e-01
-7.44960681e-02 -1.22273362e+00 3.97744298e-01 4.15107757e-01
8.23911309e-01 -1.49948692e+00 -2.20619142e-01 4.19187844e-01
-7.36368001e-01 1.18868613e+00 9.46892500e-01 -3.48084301e-01
6.15561843e-01 7.58667439e-02 6.65098280e-02 3.55628654e-02
-1.07050788e+00 4.82128523e-02 4.07884330e-01 3.12442839e-01
2.41702750e-01 -8.78252611e-02 2.12181091e-01 3.81742358e-01
-1.25735998e-01 -4.26927954e-02 2.91843303e-02 7.96007514e-01
-4.25718129e-01 -7.37435162e-01 2.28521332e-01 5.76588094e-01
-1.29225791e-01 -8.11668038e-02 -9.06640664e-02 5.18963099e-01
1.05792888e-01 3.94648015e-01 5.35084724e-01 -3.95054400e-01
3.00084352e-01 2.80711614e-02 1.62576243e-01 -5.83078504e-01
-4.99599695e-01 -5.12273729e-01 -3.18445563e-01 -6.36850059e-01
-3.18307579e-02 -4.99261379e-01 -1.09230733e+00 -2.00006306e-01
-9.39189084e-03 2.37905458e-02 7.85233915e-01 8.83021951e-01
6.29468262e-01 6.17786586e-01 1.06355715e+00 -7.16057956e-01
-1.04888940e+00 -8.09919238e-01 -3.82080704e-01 5.30308604e-01
5.93059421e-01 -5.82299054e-01 -5.10788500e-01 -1.57713532e-01] | [9.601006507873535, 2.96291446685791] |
a3172c97-277a-4ac2-a054-c03fb992c2a7 | semantic-similarity-computing-for-scientific | 2203.12593 | null | https://arxiv.org/abs/2203.12593v1 | https://arxiv.org/pdf/2203.12593v1.pdf | Semantic Similarity Computing for Scientific Academic Conferences fused with domain features | Aiming at the problem that the current general-purpose semantic text similarity calculation methods are difficult to use the semantic information of scientific academic conference data, a semantic similarity calculation algorithm for scientific academic conferences by fusion with domain features is proposed. First, the domain feature information of the conference is obtained through entity recognition and keyword extraction, and it is input into the BERT network as a feature and the conference information. The structure of the Siamese network is used to solve the anisotropy problem of BERT. The output of the network is pooled and normalized, and finally the cosine similarity is used to calculate the similarity between the two sessions. Experimental results show that the SBFD algorithm has achieved good results on different data sets, and the Spearman correlation coefficient has a certain improvement compared with the comparison algorithm. | ['Ang Li', 'Yawen Li', 'Runyu Yu'] | 2022-03-21 | null | null | null | null | ['keyword-extraction'] | ['natural-language-processing'] | [-3.43455434e-01 -5.20709574e-01 -7.25470558e-02 -3.68466169e-01
-2.90139079e-01 -2.09415048e-01 5.80140829e-01 3.70370388e-01
-7.49417305e-01 7.75036633e-01 9.56458375e-02 1.19186461e-01
-8.52949202e-01 -1.05665183e+00 4.95778508e-02 -4.61151600e-01
1.56054869e-01 6.74425602e-01 4.33488369e-01 -3.05824131e-01
8.38922620e-01 5.71701527e-01 -1.86489081e+00 1.82165831e-01
1.25786626e+00 1.20410371e+00 3.65867764e-01 5.97719029e-02
-9.28608596e-01 3.45861316e-01 -1.01611364e+00 -1.63988382e-01
7.90201128e-02 -4.68010694e-01 -9.17344987e-01 -4.86080170e-01
-3.71039331e-01 5.03496528e-01 -2.82484353e-01 1.29561746e+00
5.75222492e-01 6.75184369e-01 6.98068738e-01 -1.57661688e+00
-3.91933173e-01 6.27195477e-01 -2.77114272e-01 3.89874727e-01
5.40601611e-01 -8.29218566e-01 9.12539840e-01 -9.62482154e-01
7.18473315e-01 1.53960574e+00 4.80832905e-01 -1.16474174e-01
-2.69117147e-01 -9.22449946e-01 -2.59090960e-01 9.62763488e-01
-1.68370509e+00 1.78641021e-01 9.13490593e-01 4.65562865e-02
5.96588731e-01 2.73269743e-01 7.11238563e-01 5.81063271e-01
5.94526865e-02 4.16018665e-01 8.68469417e-01 -3.23641568e-01
2.67593980e-01 1.93537652e-01 3.86323333e-01 2.84155667e-01
5.88093102e-01 -3.33238780e-01 -4.83469605e-01 -2.18225479e-01
3.99076521e-01 3.83170068e-01 -1.11151986e-01 -1.99671775e-01
-1.37746668e+00 7.79469192e-01 5.24209023e-01 1.15680051e+00
-2.15802908e-01 -7.01645851e-01 5.04502654e-01 5.07481277e-01
3.88748378e-01 6.55924439e-01 -3.90318394e-01 -2.33128175e-01
-1.02377272e+00 3.05359185e-01 1.11239111e+00 8.03661644e-01
5.17888904e-01 -5.15732884e-01 3.71397883e-02 9.79166269e-01
3.00870001e-01 4.87177044e-01 8.17651629e-01 -1.04516053e+00
3.37772220e-01 9.94485974e-01 -1.53941303e-01 -1.50562489e+00
-3.19721431e-01 -2.74753749e-01 -8.38182688e-01 -2.58257210e-01
3.54575753e-01 5.95514895e-03 -4.75180507e-01 1.09661782e+00
2.00956047e-01 3.35976481e-01 2.34842345e-01 1.08300483e+00
1.42824340e+00 7.35348463e-01 -1.82033274e-02 -4.04788435e-01
1.18683374e+00 -6.73792839e-01 -1.18550563e+00 4.57125843e-01
3.53704125e-01 -1.06511986e+00 3.75648081e-01 4.19892937e-01
-9.19576228e-01 -5.63394666e-01 -1.07447851e+00 2.39857331e-01
-1.04128742e+00 -1.57429371e-02 5.22083223e-01 9.31819007e-02
-8.75778019e-01 9.39879596e-01 -1.46294758e-01 -7.37395346e-01
8.06668252e-02 2.55036920e-01 -3.81710112e-01 -2.67619312e-01
-1.80303717e+00 1.04707909e+00 9.55867171e-01 -4.04899985e-01
1.15955427e-01 -7.00454831e-01 -6.02919042e-01 4.44449306e-01
3.11482558e-03 -5.27598560e-01 6.29077733e-01 -6.75097525e-01
-1.25333524e+00 5.40727794e-01 -4.12822440e-02 -6.57176152e-02
2.68270969e-01 3.45908105e-01 -1.08869660e+00 3.09865177e-01
3.04305196e-01 1.22036517e-01 1.33743465e-01 -9.78622317e-01
-1.11005104e+00 -4.70263690e-01 -4.25866932e-01 5.04166543e-01
-7.45433271e-01 3.21525902e-01 -6.04549527e-01 -5.68279564e-01
5.30281663e-01 -4.66511905e-01 -1.00630075e-01 -2.62155533e-01
3.09537649e-01 -9.60582733e-01 1.08337259e+00 -5.60533881e-01
1.46087897e+00 -2.08851027e+00 1.53753638e-01 1.07401955e+00
1.60265774e-01 3.50469500e-01 4.36428413e-02 4.42581952e-01
-1.83308601e-01 -1.01001792e-01 5.38864993e-02 4.78450865e-01
-3.08524877e-01 4.63672914e-02 3.07966471e-01 1.80620641e-01
-6.94927752e-01 3.65027755e-01 -1.06609631e+00 -1.16507602e+00
2.46445969e-01 1.43712446e-01 -8.69859681e-02 2.55306870e-01
4.93135393e-01 -1.80199116e-01 -8.99186134e-01 5.28016925e-01
7.84225106e-01 -2.38932237e-01 2.63599485e-01 -4.56971496e-01
-6.48168847e-02 -1.31235356e-02 -1.56969845e+00 2.04327822e+00
-1.76637888e-01 3.30698729e-01 -2.89795529e-02 -1.39811802e+00
1.44495296e+00 3.74778956e-01 8.61389160e-01 -7.52201378e-01
4.49050218e-01 5.55791974e-01 6.30681068e-02 -5.37957549e-01
3.13494623e-01 1.06123924e-01 2.11788621e-02 2.80476063e-01
1.70866996e-01 -4.04792905e-01 6.32749140e-01 5.51714301e-01
8.35775912e-01 -3.67259353e-01 2.02269942e-01 -5.55755138e-01
1.08028710e+00 2.75592536e-01 6.45934582e-01 3.86018008e-01
-8.93300623e-02 3.09296519e-01 4.88229468e-02 -1.85551330e-01
-9.41842318e-01 -9.82829571e-01 -2.14523166e-01 6.95476949e-01
6.54882491e-01 -4.62545156e-01 -6.41502023e-01 -5.37956834e-01
3.50857913e-01 5.60810030e-01 -2.38885537e-01 -3.43662798e-01
-6.88755438e-02 -3.52488339e-01 2.61868328e-01 3.17689419e-01
8.85537982e-01 -7.25144565e-01 2.29974434e-01 2.05444455e-01
-3.11762184e-01 -8.33906293e-01 -2.82674342e-01 -3.20225239e-01
-7.88660705e-01 -1.16961539e+00 -7.00258374e-01 -1.17997622e+00
5.40328383e-01 4.75690395e-01 6.70281649e-01 8.04881454e-02
-1.80887491e-01 1.40526816e-01 -4.91273135e-01 -4.45286691e-01
-7.44900703e-02 -4.28349189e-02 3.65718156e-01 -2.39142492e-01
9.24606144e-01 -6.04469419e-01 -3.40144515e-01 3.40386093e-01
-7.49961436e-01 -5.34164846e-01 3.73788744e-01 8.02204609e-01
6.94258362e-02 4.61493373e-01 7.85207748e-01 -2.85475403e-01
1.20036161e+00 -5.14146388e-01 -4.01755005e-01 3.74692231e-01
-1.01767647e+00 -8.93173143e-02 5.30583084e-01 -1.80026487e-01
-1.24648023e+00 -5.15176833e-01 3.71494293e-01 -4.93700176e-01
4.74436171e-02 6.66165650e-01 -3.11401963e-01 -2.45158926e-01
3.75459731e-01 5.36113754e-02 3.47490251e-01 -5.68594337e-01
1.20909877e-01 1.37014711e+00 3.67072850e-01 -5.13281822e-01
6.80020392e-01 1.59912780e-01 1.15628392e-01 -5.05466044e-01
-6.41993821e-01 -9.70131099e-01 -4.84532684e-01 -2.70339429e-01
8.08239222e-01 -6.93190396e-01 -1.11377227e+00 2.05279186e-01
-1.33005559e+00 1.07770073e+00 -1.81953162e-01 1.20766556e+00
-1.67229697e-01 5.60754657e-01 -4.85897958e-01 -3.53972077e-01
-3.26436043e-01 -6.00956202e-01 3.01108420e-01 7.22311735e-01
-1.34430349e-01 -1.15913832e+00 -1.41264230e-01 3.98187995e-01
4.89075780e-01 -2.17716560e-01 8.01893890e-01 -1.39408135e+00
5.68810478e-02 -4.50329304e-01 -4.23346192e-01 4.20940489e-01
2.67470449e-01 -4.49359715e-02 -4.39881831e-01 -1.37713850e-01
1.53697118e-01 3.25684249e-01 4.55321580e-01 1.37749672e-01
1.44315457e+00 1.24224104e-01 -6.86589003e-01 3.39598179e-01
1.22422659e+00 6.89705849e-01 3.53189409e-01 5.92806935e-01
3.64719540e-01 6.29608333e-01 1.12526453e+00 5.02083361e-01
2.48270303e-01 1.39303789e-01 -8.52605104e-02 7.09980279e-02
1.50274396e-01 9.03956220e-03 -4.04349774e-01 1.57792020e+00
-4.04803455e-01 -7.91332200e-02 -9.01189387e-01 6.24405026e-01
-1.97795737e+00 -1.16906464e+00 -2.99277455e-01 2.06196642e+00
7.54350245e-01 2.14251019e-02 -3.03274930e-01 3.80201995e-01
1.12007391e+00 -1.26000032e-01 -3.53783108e-02 -3.36943597e-01
-3.48699361e-01 1.74394414e-01 4.30557013e-01 4.62579168e-02
-7.74538457e-01 6.46493733e-01 6.63452005e+00 1.42346084e+00
-6.96407974e-01 4.24179211e-02 -3.80018167e-02 1.15712378e-02
-3.21742266e-01 -1.79863386e-02 -3.62186790e-01 6.95943952e-01
9.11800206e-01 -1.17527437e+00 3.02310199e-01 6.26426816e-01
1.40407905e-01 -1.28847092e-01 -6.88922286e-01 1.48549712e+00
3.53183120e-01 -1.18942666e+00 1.92255914e-01 -2.79389739e-01
7.54976690e-01 -2.66165614e-01 -3.88251364e-01 6.44354671e-02
4.92170244e-01 -7.37887621e-01 -8.94833654e-02 9.73209500e-01
3.09778273e-01 -1.13811791e+00 1.20836091e+00 2.75060356e-01
-1.25891864e+00 -1.64466817e-02 -5.78616023e-01 -5.71406744e-02
-5.24252728e-02 1.03465629e+00 -6.06367230e-01 1.29583240e+00
9.99692857e-01 1.19350731e+00 -3.58694553e-01 1.36768746e+00
2.41166532e-01 1.72739953e-01 -4.78014052e-01 -4.66181874e-01
1.39566049e-01 -6.78561687e-01 5.94918609e-01 9.27300096e-01
7.70207524e-01 2.06395730e-01 5.81374057e-02 7.14661896e-01
-6.09992519e-02 7.22053707e-01 -5.67216218e-01 -1.81246459e-01
8.60047936e-01 1.46993530e+00 -6.34218574e-01 -8.64108562e-01
-2.55240560e-01 6.99719727e-01 -1.36761039e-01 3.04336071e-01
-6.19048953e-01 -1.44298935e+00 4.70512301e-01 -4.38105375e-01
7.49593973e-02 6.22527525e-02 -4.61284041e-01 -8.85983288e-01
-8.48245621e-02 -4.15977776e-01 7.70048022e-01 -9.80351269e-01
-1.65527534e+00 1.48600608e-01 1.96342804e-02 -1.45911610e+00
6.87128827e-02 -6.20599091e-01 -7.44068742e-01 1.06206322e+00
-1.14863980e+00 -4.79214251e-01 -5.07593513e-01 9.29909647e-01
1.76878691e-01 -8.02413464e-01 6.32931828e-01 4.44001138e-01
-2.29437798e-01 2.19216198e-01 6.02693379e-01 3.93430628e-02
9.39710677e-01 -8.93428385e-01 -4.25964057e-01 3.28618675e-01
-2.97163486e-01 6.04697526e-01 5.79773486e-01 -8.00345600e-01
-1.09861362e+00 -6.27343833e-01 1.44250238e+00 -1.43097699e-01
8.05274367e-01 4.16796952e-01 -9.66498256e-01 -1.62684381e-01
2.86411494e-01 -2.25022286e-01 7.74603665e-01 -5.72477169e-02
-3.70109342e-02 -3.47052246e-01 -1.39736068e+00 2.46284604e-01
1.02989995e+00 -2.80485779e-01 -1.36990082e+00 4.13042277e-01
7.97610283e-01 -4.60020192e-02 -1.51260149e+00 4.44007486e-01
2.57753372e-01 -3.57898146e-01 1.17257595e+00 -6.85438871e-01
2.80165881e-01 -4.48040009e-01 -7.05182105e-02 -1.49889922e+00
-4.21668559e-01 1.51947781e-01 4.89983916e-01 1.39561415e+00
1.64791271e-01 -7.00490534e-01 4.67219830e-01 3.06761205e-01
1.19436227e-01 -1.45056218e-01 -9.38846886e-01 -8.96863878e-01
-5.27607165e-02 1.44327536e-01 1.00786066e+00 1.55295014e+00
6.10711813e-01 2.67169148e-01 3.58128041e-01 -3.91533971e-01
4.93904203e-01 2.31572613e-01 1.47843316e-01 -2.09495187e+00
6.68310106e-01 -5.93176603e-01 -5.98842621e-01 -3.63489091e-01
4.24270540e-01 -1.20644569e+00 -3.48499924e-01 -1.98085570e+00
1.72692373e-01 -3.34739715e-01 -7.78461337e-01 -7.30461255e-03
-5.38630486e-02 -2.73038864e-01 1.36710390e-01 3.68507653e-01
-6.62072837e-01 6.40400231e-01 1.46722150e+00 -1.26117229e-01
-4.44582012e-03 -9.89039391e-02 -5.53265810e-01 7.40887702e-01
6.32192194e-01 -4.73370671e-01 -3.11134070e-01 6.14001490e-02
-1.33303314e-01 5.56990728e-02 -1.81120664e-01 -1.21350729e+00
8.57462466e-01 -4.09926862e-01 5.58566451e-01 -6.81423604e-01
7.81566128e-02 -1.30747736e+00 -6.92352504e-02 3.66077453e-01
-3.28489244e-01 1.72629729e-01 -3.41832727e-01 4.63057876e-01
-7.85497785e-01 -3.48507583e-01 4.76904541e-01 -7.47852325e-02
-7.76806712e-01 1.86838329e-01 -1.02896653e-01 1.90432400e-01
1.07264066e+00 -2.38422394e-01 -1.26307458e-01 -1.48983002e-01
-5.81266940e-01 4.93572623e-01 2.40373001e-01 7.63551950e-01
6.01788819e-01 -1.73752296e+00 -6.39855981e-01 -2.23966181e-01
6.60440102e-02 -2.03985929e-01 1.28384382e-01 7.08669543e-01
-4.92346436e-01 5.33902466e-01 -4.15134579e-01 -3.16624820e-01
-1.35810876e+00 5.22204757e-01 1.26552016e-01 -3.10089495e-02
-1.76007047e-01 4.66940463e-01 -5.42680979e-01 -5.29554904e-01
1.36597365e-01 1.95417151e-01 -1.01774848e+00 3.87701422e-01
3.50824952e-01 7.57785201e-01 2.58785099e-01 -5.64019084e-01
-6.65251970e-01 6.81679428e-01 4.89495769e-02 -1.42967731e-01
1.24530935e+00 -4.91682217e-02 -7.16144145e-01 2.60953784e-01
1.46187568e+00 -2.40418360e-01 9.70989093e-02 -6.30925059e-01
1.55570060e-01 -5.91369152e-01 1.65767372e-01 -7.29552031e-01
-1.18563545e+00 5.54940939e-01 6.15599096e-01 1.70289755e-01
9.18995798e-01 -1.76127806e-01 8.06363165e-01 5.97203374e-01
2.37357751e-01 -1.90056586e+00 -4.18220729e-01 6.77008152e-01
5.14477849e-01 -1.13668466e+00 9.40819755e-02 -4.26589578e-01
-5.05809009e-01 1.34239030e+00 6.73337758e-01 -1.30709067e-01
1.09445679e+00 -5.19432053e-02 -9.60740745e-02 -2.00314060e-01
-3.12243134e-01 -6.71771467e-02 5.49765468e-01 4.96008366e-01
3.26412261e-01 -1.76862404e-01 -1.46324956e+00 8.19006026e-01
-3.01202774e-01 1.89347908e-01 6.19562715e-02 8.44112992e-01
-7.40970612e-01 -1.16044283e+00 -6.10894203e-01 6.16308033e-01
-3.96789908e-01 1.07297748e-01 -3.89006436e-01 6.24657631e-01
1.26887172e-01 1.16274881e+00 3.60564113e-01 -4.63967144e-01
4.22378838e-01 6.68737218e-02 -1.05175339e-01 -1.64429709e-01
-6.23525202e-01 -2.59209812e-01 -1.64510727e-01 -5.54069400e-01
-7.36457169e-01 -4.70162213e-01 -1.73978174e+00 -5.39238632e-01
-2.78640658e-01 1.25297630e+00 1.02036846e+00 1.05339170e+00
3.58865947e-01 6.57491267e-01 9.53240335e-01 -2.55980670e-01
-3.14315259e-01 -9.83445406e-01 -9.47540104e-01 9.78195608e-01
-4.34602261e-01 -8.09532762e-01 -7.83441961e-01 -3.07844549e-01] | [9.62845516204834, 8.436957359313965] |
72bab474-f9bf-4d31-9011-e04ab661e565 | ruber-an-unsupervised-method-for-automatic | 1701.03079 | null | http://arxiv.org/abs/1701.03079v2 | http://arxiv.org/pdf/1701.03079v2.pdf | RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems | Open-domain human-computer conversation has been attracting increasing
attention over the past few years. However, there does not exist a standard
automatic evaluation metric for open-domain dialog systems; researchers usually
resort to human annotation for model evaluation, which is time- and
labor-intensive. In this paper, we propose RUBER, a Referenced metric and
Unreferenced metric Blended Evaluation Routine, which evaluates a reply by
taking into consideration both a groundtruth reply and a query (previous
user-issued utterance). Our metric is learnable, but its training does not
require labels of human satisfaction. Hence, RUBER is flexible and extensible
to different datasets and languages. Experiments on both retrieval and
generative dialog systems show that RUBER has a high correlation with human
annotation. | ['Lili Mou', 'Chongyang Tao', 'Rui Yan', 'Dongyan Zhao'] | 2017-01-11 | null | null | null | null | ['dialogue-evaluation', 'open-domain-dialog'] | ['natural-language-processing', 'natural-language-processing'] | [-2.28439227e-01 1.85951754e-01 3.59417498e-02 -7.19782948e-01
-9.28192437e-01 -8.86249781e-01 6.65387571e-01 4.64168042e-02
-5.34104943e-01 7.43220866e-01 3.89829159e-01 -1.46162003e-01
-5.48370667e-02 -6.31425261e-01 2.90920824e-01 -4.15684253e-01
5.91652036e-01 9.82106268e-01 4.99897510e-01 -5.94107509e-01
4.90533598e-02 -5.23584485e-02 -1.02710450e+00 2.44522579e-02
8.36713850e-01 1.00400567e+00 3.38248223e-01 5.52758574e-01
-4.40829277e-01 7.10560024e-01 -8.98871660e-01 -7.85755455e-01
-1.93601072e-01 -5.48134387e-01 -1.50534308e+00 4.31457954e-03
-9.17338207e-02 -3.16845298e-01 7.10578561e-02 9.60404158e-01
6.39716685e-01 2.18373895e-01 6.28974259e-01 -1.18737948e+00
-7.28300810e-01 7.14561880e-01 3.94829623e-02 -1.73524886e-01
8.14963460e-01 2.44520918e-01 1.36321843e+00 -5.95645607e-01
3.81651551e-01 1.46448803e+00 3.54086190e-01 8.83941650e-01
-8.49513710e-01 -3.41032177e-01 -1.18926018e-01 -4.08517756e-02
-1.23206723e+00 -1.79584086e-01 6.45165145e-01 -4.27574784e-01
6.00215673e-01 5.29011071e-01 3.65914144e-02 1.05660248e+00
-3.01268190e-01 5.55630386e-01 9.71658409e-01 -4.02498126e-01
1.62400454e-01 5.48387110e-01 5.74741066e-01 5.20121992e-01
-3.21056724e-01 -3.64318013e-01 -1.29961714e-01 -4.88351673e-01
3.73965710e-01 -1.31908908e-01 -3.18083048e-01 -5.32265753e-02
-9.98219550e-01 8.79199982e-01 1.50390580e-01 5.88828802e-01
-1.11236952e-01 -4.96167183e-01 4.66273338e-01 5.05164921e-01
3.22141081e-01 6.32417560e-01 -4.51314032e-01 -4.45110798e-01
-2.90544361e-01 1.77118331e-01 1.46229899e+00 8.45803261e-01
9.75795150e-01 -4.69527990e-01 -3.02247405e-01 1.24238837e+00
3.84800762e-01 5.37154436e-01 6.82935596e-01 -1.09746277e+00
2.10954905e-01 1.13399827e+00 2.84621119e-01 -9.71140385e-01
-3.51188302e-01 2.41943106e-01 -5.88053405e-01 -3.00138026e-01
5.64952672e-01 -3.65107775e-01 -5.22846170e-02 1.83181787e+00
3.82230610e-01 -3.86793554e-01 3.28695863e-01 1.15705657e+00
1.31797683e+00 5.28132260e-01 9.99046788e-02 -4.11367267e-01
1.44474232e+00 -1.02772856e+00 -8.90746653e-01 -2.55244616e-02
6.47164106e-01 -9.31928277e-01 1.55421579e+00 1.40383169e-01
-8.44051838e-01 -3.63858223e-01 -7.19161570e-01 -2.58388489e-01
-3.24448407e-01 -2.10721999e-01 3.22214276e-01 6.23993218e-01
-7.89390445e-01 1.25475809e-01 -2.67007142e-01 -5.20783842e-01
-5.29835880e-01 3.44209522e-01 -1.61502048e-01 2.55949646e-01
-1.48083413e+00 1.02047884e+00 1.76668599e-01 -3.19542825e-01
-7.29334414e-01 7.68813165e-03 -6.46996081e-01 1.88937888e-01
6.50753677e-01 -4.04151052e-01 1.81929219e+00 -6.57961845e-01
-1.88311970e+00 1.02899766e+00 -1.92900553e-01 -1.98317483e-01
4.03680444e-01 1.13775732e-03 -5.68339586e-01 -9.41633135e-02
-3.07246414e-03 2.48465210e-01 3.80316108e-01 -1.06092453e+00
-3.40841442e-01 -3.94711167e-01 5.88448226e-01 3.08489114e-01
-6.21276975e-01 4.57220316e-01 -5.61736286e-01 -1.43465579e-01
-1.08348697e-01 -9.22451854e-01 -7.61754587e-02 -3.93627107e-01
-3.20618749e-01 -9.49759305e-01 6.46192312e-01 -4.73610908e-01
1.59708786e+00 -2.06295395e+00 -4.78716679e-02 3.53739969e-02
3.72827321e-01 4.73268181e-01 3.65438163e-02 6.06265724e-01
4.58086669e-01 4.83891517e-02 -2.67257065e-01 -2.04664961e-01
4.23229337e-01 3.13771069e-01 -2.01767132e-01 -1.38926193e-01
-3.81622821e-01 6.57765388e-01 -1.01958978e+00 -1.06279004e+00
9.86177623e-02 3.39568555e-02 -5.01732349e-01 8.96588922e-01
-5.02517045e-01 5.26225924e-01 -7.22866833e-01 3.91878128e-01
4.33464140e-01 -4.13878024e-01 1.89270198e-01 6.78333491e-02
5.56424670e-02 3.86446178e-01 -9.24854696e-01 1.66909420e+00
-6.23892486e-01 3.32113743e-01 1.30942777e-01 -4.33686793e-01
1.40787864e+00 6.10085368e-01 1.70851305e-01 -4.85585362e-01
4.42919731e-01 2.58567214e-01 -1.01999715e-01 -6.92099512e-01
6.33197606e-01 -7.31644258e-02 -5.73791087e-01 8.59150648e-01
1.18393242e-01 -2.91856050e-01 1.41753286e-01 3.85479689e-01
1.02077615e+00 -2.91742355e-01 4.63756889e-01 -2.01089725e-01
1.10771954e+00 -1.00130111e-01 4.62260395e-01 5.10289907e-01
-4.12474275e-01 3.42491657e-01 5.70212305e-01 -2.44332686e-01
-5.02301931e-01 -8.06020141e-01 9.44981575e-02 1.56365144e+00
3.67685080e-01 -5.07111311e-01 -1.19420290e+00 -7.53149450e-01
-3.27794433e-01 5.31958580e-01 -2.04682559e-01 -6.54670745e-02
-4.38787252e-01 -2.50304937e-01 7.54824519e-01 1.43520292e-02
6.73299730e-01 -1.18329453e+00 -3.41200143e-01 2.18197405e-01
-6.98744655e-01 -1.08485031e+00 -8.67331147e-01 -2.14212358e-01
-3.60884666e-01 -1.08742237e+00 -6.13552332e-01 -9.27528799e-01
2.24105537e-01 2.42707610e-01 1.36891735e+00 1.91542223e-01
2.51634955e-01 5.67245483e-01 -4.54430699e-01 -1.37118876e-01
-8.46378624e-01 1.78008348e-01 1.29953120e-02 1.14072539e-01
8.22573662e-01 -1.21417530e-01 -4.99056429e-01 1.10626030e+00
-5.91823876e-01 -2.19116211e-01 2.63551652e-01 7.87676096e-01
8.70323461e-03 -5.89557946e-01 6.63559854e-01 -8.29734564e-01
1.33241761e+00 -3.65010470e-01 -5.04854739e-01 6.42447472e-01
-6.99865103e-01 2.53054518e-02 5.31153500e-01 -2.93607563e-01
-1.49210107e+00 -2.55180687e-01 -2.72648275e-01 -3.00168321e-02
-2.78339416e-01 4.57802713e-01 -4.15039450e-01 2.17694640e-01
8.32655311e-01 -1.21931382e-01 1.23537011e-01 -6.78442001e-01
2.77638674e-01 1.44198179e+00 6.11396074e-01 -7.75256038e-01
3.83164287e-01 2.02368349e-02 -6.83858931e-01 -7.62289226e-01
-1.03935981e+00 -7.73677051e-01 -4.14604425e-01 -3.72844398e-01
9.93943334e-01 -5.11272013e-01 -1.22834754e+00 1.97148800e-01
-1.48880851e+00 -1.02383524e-01 9.90826637e-02 3.19603026e-01
-4.48182821e-01 5.52291453e-01 -6.59557998e-01 -8.84057224e-01
-5.80887973e-01 -1.15304387e+00 9.42200005e-01 2.90068001e-01
-6.91785872e-01 -1.00700438e+00 4.12916809e-01 7.59436548e-01
4.12564814e-01 -1.95084333e-01 7.28830159e-01 -1.21416938e+00
-2.78090537e-01 -2.09639296e-01 -1.73936337e-01 4.56812799e-01
1.57489762e-01 -2.57855684e-01 -1.06324971e+00 8.09527859e-02
1.97880819e-01 -8.11793566e-01 2.09030837e-01 -3.21531534e-01
8.47078204e-01 -5.80904305e-01 -1.55519517e-02 -9.93614197e-02
8.22015941e-01 2.07858473e-01 4.07521725e-01 5.06378897e-03
3.00988168e-01 8.15496504e-01 8.73906314e-01 5.45923531e-01
5.63562036e-01 9.03907895e-01 6.56161979e-02 1.05842248e-01
2.73591280e-01 -1.69709459e-01 1.65652841e-01 1.04678249e+00
6.04743836e-03 -4.46041077e-01 -8.44498396e-01 3.44437480e-01
-1.91032243e+00 -8.60184610e-01 -4.82171066e-02 2.12689519e+00
1.24940801e+00 -6.29987344e-02 5.67084700e-02 -4.06445116e-02
7.83035398e-01 9.89003405e-02 -3.42460871e-01 -4.91504997e-01
1.32242423e-02 -8.05109069e-02 -2.73695260e-01 8.37318838e-01
-6.21143460e-01 9.29642618e-01 5.89075947e+00 6.37201607e-01
-7.81603634e-01 3.89412999e-01 4.19542581e-01 4.78553623e-01
-2.41309509e-01 5.55489436e-02 -8.24981570e-01 4.13546652e-01
8.82232666e-01 -4.98453736e-01 3.00453067e-01 1.02368140e+00
-2.06058361e-02 7.56546780e-02 -1.26288748e+00 9.83330786e-01
5.97902238e-02 -7.82385767e-01 -1.54652402e-01 -9.56214815e-02
3.11379254e-01 -2.86847264e-01 -4.08911169e-01 7.10257888e-01
6.50605500e-01 -6.67730033e-01 1.08558387e-01 3.10995311e-01
4.57407564e-01 -3.56675386e-01 9.56693113e-01 6.22267544e-01
-8.46626163e-01 2.83998609e-01 -2.80732840e-01 4.12065983e-02
2.02293769e-01 1.15896434e-01 -1.04563868e+00 1.66267201e-01
4.57189828e-01 1.00095332e-01 -2.57898599e-01 5.37463009e-01
-1.53068930e-01 4.06795830e-01 -1.31634146e-01 -5.46565413e-01
1.83783725e-01 -2.96344787e-01 4.61222112e-01 1.23002255e+00
1.26555013e-02 3.92680615e-01 6.99858606e-01 6.52373195e-01
-1.21183239e-01 4.31189001e-01 -4.65805292e-01 4.10984410e-03
6.59758747e-01 1.33366764e+00 -1.54883623e-01 -3.45622599e-01
-4.82874066e-01 8.69454443e-01 2.61606127e-01 7.38136694e-02
-8.29783797e-01 -4.36762840e-01 4.96366829e-01 -2.36189023e-01
-3.39499742e-01 1.00854933e-01 3.14536132e-02 -1.01570630e+00
-1.23775654e-01 -9.94593084e-01 7.64516592e-01 -6.47377670e-01
-1.42592287e+00 9.67511654e-01 -1.13342553e-01 -1.17046273e+00
-7.01760113e-01 -3.18393975e-01 -5.25495827e-01 8.40830088e-01
-1.09650242e+00 -7.74042010e-01 -8.04343164e-01 8.30218136e-01
5.39293051e-01 -1.81891099e-01 1.37433183e+00 2.87577093e-01
-4.77178156e-01 6.09260798e-01 -3.69935095e-01 3.30728382e-01
1.12670231e+00 -1.23496079e+00 -6.77831247e-02 1.51992306e-01
-1.18185550e-01 7.48142719e-01 8.26243758e-01 -2.58184284e-01
-1.02427804e+00 -5.91003418e-01 1.25972915e+00 -5.10079443e-01
8.32349002e-01 -1.90062985e-01 -1.17260146e+00 4.88234967e-01
6.10147119e-01 -4.63218927e-01 1.02441430e+00 2.92431891e-01
-3.01227510e-01 -1.58443093e-01 -1.10661161e+00 4.52347100e-01
7.20061421e-01 -6.21817470e-01 -9.63475943e-01 4.38334703e-01
1.01825237e+00 -4.53627557e-01 -1.01668429e+00 2.77003169e-01
1.70964926e-01 -9.82228339e-01 6.09611869e-01 -4.94665921e-01
-4.93711717e-02 -5.07510528e-02 -2.62336642e-01 -1.01454425e+00
2.54194438e-02 -9.59655285e-01 1.22941710e-01 1.58773303e+00
4.58549589e-01 -6.70885861e-01 4.16913092e-01 1.16889000e+00
-9.47457626e-02 -4.14718777e-01 -7.23348439e-01 -6.85004234e-01
-1.75509691e-01 -1.47731945e-01 8.36807847e-01 9.41303790e-01
7.24461913e-01 1.05145860e+00 -4.13088441e-01 -2.30490312e-01
1.64614275e-01 3.03769350e-01 1.16906631e+00 -1.53238845e+00
-3.38287324e-01 -3.71659815e-01 -2.50963941e-02 -1.33894825e+00
2.87926406e-01 -5.36795855e-01 1.75107181e-01 -1.34969687e+00
1.24792650e-01 -6.06731713e-01 -7.34404474e-02 3.32087696e-01
-2.08597735e-01 -6.01967238e-02 -5.42217307e-02 4.56879050e-01
-1.07698166e+00 7.01487362e-01 1.19362378e+00 -1.68567166e-01
-3.39096367e-01 2.98964798e-01 -6.95827484e-01 8.45630288e-01
8.23064685e-01 -3.06605101e-01 -3.70582312e-01 -2.55149007e-01
-5.01279207e-03 3.96803975e-01 8.24125856e-02 -7.06271350e-01
3.35072756e-01 -3.53546083e-01 -5.90571940e-01 -2.77233601e-01
4.06927645e-01 -7.38549054e-01 -1.31308779e-01 1.70069098e-01
-5.58198988e-01 -8.78446363e-03 -4.39365864e-01 3.81074131e-01
-4.50281739e-01 -6.68878973e-01 7.71855831e-01 -3.17611068e-01
-6.03665233e-01 1.94710165e-01 -1.40049621e-01 4.94183064e-01
8.25890005e-01 2.24075168e-01 -4.47460502e-01 -7.31429517e-01
-5.76923370e-01 4.66838270e-01 3.24501544e-01 5.15217423e-01
4.09834951e-01 -1.03168941e+00 -5.94795167e-01 -3.01959217e-01
3.79849195e-01 -1.39576882e-01 -2.44861725e-03 3.78412843e-01
-2.36832336e-01 6.07007802e-01 1.79310009e-01 -5.93142986e-01
-1.44852841e+00 4.90473628e-01 2.13461727e-01 -4.68624681e-01
-7.80722648e-02 5.42044580e-01 1.90810412e-01 -8.67320418e-01
6.06093526e-01 -3.64009786e-04 -5.02626956e-01 -2.27582622e-02
6.74156845e-01 3.54033619e-01 -7.18299374e-02 -7.11458981e-01
-1.73783645e-01 1.99808791e-01 2.89143343e-02 -3.31357241e-01
7.30327427e-01 -4.55382943e-01 -2.92520881e-01 5.72140515e-01
1.11341143e+00 -3.19921151e-02 -6.34511530e-01 -7.19359756e-01
2.07828254e-01 -2.53632605e-01 -3.55278373e-01 -7.89839208e-01
-6.35266304e-01 7.22074032e-01 3.58385891e-01 6.77704155e-01
7.13003814e-01 2.44688734e-01 1.09320891e+00 9.50298965e-01
6.28795922e-01 -1.22160769e+00 4.14607644e-01 9.04587686e-01
9.50294077e-01 -1.51598763e+00 -4.32878077e-01 -3.97965789e-01
-9.27841485e-01 7.77775407e-01 1.02663589e+00 5.32999754e-01
5.87286651e-01 -1.33155420e-01 6.24409437e-01 -2.83001661e-01
-7.35330224e-01 -2.20932990e-01 1.53870687e-01 3.61704051e-01
6.62382782e-01 1.61458686e-01 -5.61237574e-01 8.69182944e-01
-3.47764462e-01 -2.13421181e-01 2.43384928e-01 6.67484403e-01
-7.38597453e-01 -1.27371120e+00 -1.82816997e-01 4.73382100e-02
-2.91296214e-01 1.01706065e-01 -8.62233639e-01 4.47425902e-01
-2.96227127e-01 1.53720486e+00 -2.46900350e-01 -3.87219399e-01
3.30126643e-01 2.27538526e-01 -3.23664583e-02 -7.52036452e-01
-8.22463691e-01 -1.66853622e-01 3.94837976e-01 -2.95798063e-01
-4.82419133e-01 -3.16292197e-01 -1.29002154e+00 -3.82660270e-01
-6.96404040e-01 8.23797286e-01 3.77345532e-01 9.43462133e-01
2.06912234e-01 -1.09791063e-01 8.19548607e-01 -1.76140025e-01
-8.20845664e-01 -1.35211885e+00 -3.07002246e-01 6.37379408e-01
-4.15367298e-02 -5.90009749e-01 -3.78858715e-01 -1.43859714e-01] | [12.79433822631836, 7.990901947021484] |
00e2c2b5-a796-40fb-bfae-9407fe615108 | grassmann-averages-for-scalable-robust-pca | null | null | http://openaccess.thecvf.com/content_cvpr_2014/html/Hauberg_Grassmann_Averages_for_2014_CVPR_paper.html | http://openaccess.thecvf.com/content_cvpr_2014/papers/Hauberg_Grassmann_Averages_for_2014_CVPR_paper.pdf | Grassmann Averages for Scalable Robust PCA | As the collection of large datasets becomes increasingly automated, the occurrence of outliers will increase -- "big data" implies "big outliers''. While principal component analysis (PCA) is often used to reduce the size of data, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortunately, state-of-the-art approaches for robust PCA do not scale beyond small-to-medium sized datasets. To address this, we introduce the Grassmann Average (GA), which expresses dimensionality reduction as an average of the subspaces spanned by the data. Because averages can be efficiently computed, we immediately gain scalability. GA is inherently more robust than PCA, but we show that they coincide for Gaussian data. We exploit that averages can be made robust to formulate the Robust Grassmann Average (RGA) as a form of robust PCA. Robustness can be with respect to vectors (subspaces) or elements of vectors; we focus on the latter and use a trimmed average. The resulting Trimmed Grassmann Average (TGA) is particularly appropriate for computer vision because it is robust to pixel outliers. The algorithm has low computational complexity and minimal memory requirements, making it scalable to "big noisy data." We demonstrate TGA for background modeling, video restoration, and shadow removal. We show scalability by performing robust PCA on the entire Star Wars IV movie. | ['Michael J. Black', 'Soren Hauberg', 'Aasa Feragen'] | 2014-06-01 | null | null | null | cvpr-2014-6 | ['shadow-removal', 'video-restoration'] | ['computer-vision', 'computer-vision'] | [ 6.18773550e-02 -4.63862300e-01 3.74526292e-01 -1.10328675e-03
-9.60566700e-01 -7.32618034e-01 5.15082955e-01 -6.81784227e-02
-2.42112637e-01 3.32917958e-01 2.05715030e-01 -1.11776225e-01
-3.38079721e-01 -4.44587052e-01 -5.51497579e-01 -1.11672604e+00
-2.69058228e-01 2.67826051e-01 1.14111312e-01 -7.33739287e-02
2.16537282e-01 9.21481907e-01 -1.49447346e+00 -1.32771358e-01
7.95332134e-01 8.63567770e-01 -1.31603897e-01 8.09536397e-01
1.16889365e-01 4.36093003e-01 -6.52050674e-01 -3.37994009e-01
7.49715090e-01 -1.71316057e-01 -3.03215533e-01 6.92419231e-01
5.97260237e-01 -1.70211196e-02 -3.76120299e-01 1.25936818e+00
4.50187862e-01 2.50746876e-01 3.62622023e-01 -1.46284711e+00
-4.44568723e-01 5.60644418e-02 -8.45499039e-01 7.55962655e-02
3.10694844e-01 2.40993500e-02 8.01196039e-01 -9.67612207e-01
6.89730942e-01 1.30147696e+00 9.19778347e-01 1.11582369e-01
-1.44653249e+00 -1.32366881e-01 1.04168780e-01 -3.67747694e-02
-1.48576915e+00 -5.15357018e-01 8.24897170e-01 -4.85825360e-01
5.40313900e-01 7.65475512e-01 5.57012200e-01 8.00533772e-01
1.79608300e-01 7.09879637e-01 1.10347843e+00 -4.17227387e-01
3.99916828e-01 -3.79433662e-01 3.21542859e-01 3.94006193e-01
6.70902252e-01 -1.67682990e-02 -3.94017220e-01 -4.38040227e-01
5.84443331e-01 1.88284621e-01 -5.19196987e-01 -7.62309134e-01
-1.28195655e+00 7.16832757e-01 -8.40768740e-02 9.05965716e-02
-4.53237802e-01 6.75494894e-02 2.91866273e-01 4.31562275e-01
4.56708789e-01 4.20605451e-01 -2.50211030e-01 -2.57562965e-01
-1.04847109e+00 4.60548788e-01 8.54293406e-01 8.55953395e-01
6.80714548e-01 2.51863331e-01 9.68793109e-02 8.49178493e-01
6.14701062e-02 7.82143295e-01 4.18779343e-01 -1.39312816e+00
2.87063122e-01 3.54306787e-01 1.69754609e-01 -1.53478098e+00
-5.51771820e-01 -1.53577268e-01 -1.03345561e+00 4.04153168e-01
5.54242671e-01 2.58006066e-01 -8.90383959e-01 1.47459340e+00
2.92047173e-01 1.34590760e-01 8.23721811e-02 7.57311344e-01
3.15595061e-01 4.69710439e-01 -5.45864284e-01 -7.32167244e-01
1.02347147e+00 -4.88628149e-01 -8.70760918e-01 -1.92018136e-01
2.74363607e-01 -7.82891929e-01 9.82186735e-01 8.52815032e-01
-8.70086968e-01 -2.25327089e-01 -1.10679495e+00 1.91093534e-01
-2.70586520e-01 -1.53366148e-01 5.01609921e-01 7.57186472e-01
-1.06594253e+00 8.71012092e-01 -1.00452828e+00 -6.05706453e-01
2.35125154e-01 2.66954541e-01 -7.53574669e-01 -1.54975414e-01
-3.25378925e-01 7.57067978e-01 1.88866910e-02 1.80464715e-01
-6.14384055e-01 -3.81621629e-01 -7.32742250e-01 -2.10972682e-01
4.31196153e-01 -4.88235205e-01 7.74697363e-01 -8.56289625e-01
-1.16719413e+00 7.59729922e-01 -3.90612453e-01 -3.04448038e-01
6.94837034e-01 -4.36434150e-01 -5.12442589e-01 2.90425211e-01
-1.71185303e-02 2.65706866e-03 1.47180545e+00 -1.42873847e+00
-4.61283565e-01 -5.88726461e-01 -5.20711601e-01 -1.58174440e-01
-3.26438487e-01 3.82769972e-01 -6.50924444e-01 -9.19076622e-01
8.93548846e-01 -1.27867293e+00 -5.34033477e-01 -2.53447533e-01
-3.67464095e-01 3.24637473e-01 9.59618866e-01 -8.57553065e-01
1.30338204e+00 -2.54126501e+00 1.58039838e-01 5.62519491e-01
1.92261562e-01 -2.55233441e-02 -1.82063147e-01 2.15930149e-01
-4.21007037e-01 -3.68686882e-03 -5.19335330e-01 -3.69650066e-01
-7.28543922e-02 5.30053973e-01 -5.29519916e-01 1.05039966e+00
6.70731887e-02 3.07478607e-01 -7.23653257e-01 -2.17183515e-01
3.08472186e-01 3.84624839e-01 -5.36672354e-01 -7.75564834e-03
3.13551277e-01 2.02862278e-01 8.42081849e-03 8.12321424e-01
1.01774609e+00 2.03073323e-01 -1.69829503e-02 -2.07150802e-01
-1.35666743e-01 -5.30239522e-01 -1.72622752e+00 1.34944749e+00
1.55780539e-01 7.56423235e-01 4.30051148e-01 -9.30636823e-01
9.38945830e-01 1.13680102e-01 9.12763178e-01 -1.17307350e-01
-3.72247398e-02 2.88614273e-01 -2.12629229e-01 -4.24809963e-01
6.86312258e-01 3.82221751e-02 -6.31172135e-02 9.18710306e-02
-2.40016907e-01 -3.27510595e-01 5.02948046e-01 2.70349622e-01
1.41329718e+00 -1.56797674e-02 3.79033804e-01 -3.71801466e-01
2.95868278e-01 3.91020812e-02 8.10365379e-01 7.31509447e-01
-3.64347875e-01 1.13234818e+00 6.10844553e-01 -4.52889591e-01
-9.00609851e-01 -1.28497386e+00 -2.30060294e-02 7.33457744e-01
-1.03316613e-01 -6.96991682e-01 -7.43090153e-01 -4.11322773e-01
1.86278880e-01 3.16224635e-01 -3.36168855e-01 1.11087732e-01
-6.13208055e-01 -1.21464193e+00 1.66353226e-01 2.74953961e-01
1.83117166e-01 -5.29461086e-01 -3.78737897e-01 2.43666828e-01
-4.18929085e-02 -1.25863588e+00 -1.83177218e-01 8.84215906e-02
-1.10015655e+00 -1.17803800e+00 -5.81676364e-01 -1.86683387e-01
8.57851923e-01 6.31544828e-01 1.03695846e+00 -1.22403592e-01
-3.30837935e-01 7.96769619e-01 -4.37060148e-01 -3.92100781e-01
-3.29310626e-01 -6.76777661e-01 7.09717989e-01 2.23235667e-01
3.47238094e-01 -7.18633413e-01 -2.13227257e-01 3.14625561e-01
-9.86749232e-01 -4.84941214e-01 4.70128566e-01 7.54126370e-01
8.28216136e-01 4.69838977e-01 -8.86915475e-02 -6.78633213e-01
6.86358035e-01 -1.06011830e-01 -7.36735225e-01 3.29012983e-02
-4.89066154e-01 -1.59850925e-01 6.54426038e-01 -2.63055205e-01
-6.03894293e-01 2.81668454e-01 1.77918881e-01 -8.29961777e-01
-2.00765297e-01 3.35501075e-01 -3.86005253e-01 -2.90757388e-01
6.20753348e-01 2.20443774e-02 1.33816134e-02 -5.93896687e-01
5.90704203e-01 5.12754023e-01 9.68042195e-01 -5.22973120e-01
1.10813367e+00 9.40043807e-01 3.34859133e-01 -1.46123719e+00
-4.03832942e-01 -8.09758782e-01 -8.00088763e-01 -1.60803407e-01
6.69548869e-01 -6.79092705e-01 -5.37735462e-01 3.90189886e-01
-8.69535387e-01 2.02465445e-01 -5.27841151e-01 3.66962790e-01
-7.31428862e-01 8.82371366e-01 -4.29531455e-01 -8.19771230e-01
-4.28532101e-02 -1.09750021e+00 8.31224740e-01 -1.28262907e-01
-2.71863431e-01 -6.77250504e-01 1.75672889e-01 7.95689449e-02
1.34654477e-01 5.76997638e-01 5.97983003e-01 -6.04185998e-01
-3.78985852e-01 -7.68426120e-01 -6.64534569e-02 6.48372650e-01
1.60885900e-02 4.19823676e-01 -1.01831973e+00 -6.15240395e-01
3.95548284e-01 5.40318072e-01 8.34873915e-01 5.45706809e-01
1.10893035e+00 -4.27660704e-01 -1.72997892e-01 7.86356211e-01
1.38289940e+00 -1.47069246e-01 7.44425058e-01 5.72127223e-01
9.50045347e-01 6.29220247e-01 6.40628815e-01 6.70840144e-01
-8.25465098e-02 5.88995516e-01 4.05315489e-01 1.04591742e-01
9.11890864e-02 1.82342961e-01 6.46101832e-01 1.15887296e+00
-4.16517466e-01 1.90400109e-01 -9.51666832e-01 4.35453802e-01
-1.94272661e+00 -1.16596377e+00 -4.92572308e-01 2.52047014e+00
1.39273211e-01 5.49978809e-03 1.18522860e-01 5.38384020e-01
5.33617973e-01 2.91095465e-01 -1.50175273e-01 -1.61571607e-01
-5.54141104e-01 -3.74945588e-02 7.65784919e-01 4.50209767e-01
-1.38585436e+00 6.18541598e-01 7.16353559e+00 6.51515603e-01
-7.59546816e-01 1.39926672e-02 8.00020024e-02 -1.89520314e-01
-4.87823263e-02 1.58502594e-01 -4.38788682e-01 4.04791415e-01
7.75896132e-01 -9.59320366e-02 3.70719075e-01 1.08689010e+00
3.79030585e-01 -3.67450900e-02 -8.82748425e-01 1.40719140e+00
3.13658416e-01 -9.04680252e-01 3.37395519e-02 2.45482355e-01
7.41506219e-01 1.16224149e-02 -2.39203013e-02 -7.71818608e-02
2.25544497e-01 -7.23748505e-01 5.41679919e-01 5.14859676e-01
3.20939064e-01 -8.02807987e-01 5.25283277e-01 1.11571305e-01
-1.11520243e+00 -3.51992935e-01 -8.17526042e-01 3.83475386e-02
1.60248592e-01 9.95461464e-01 -3.51298451e-01 5.86744130e-01
8.15086067e-01 7.48264015e-01 -8.55161130e-01 1.22168970e+00
6.55913576e-02 2.65537381e-01 -6.03669226e-01 5.96021831e-01
-7.82840624e-02 -9.00578916e-01 1.01941931e+00 1.10282385e+00
7.88507998e-01 6.40623346e-02 3.30511183e-01 2.15933278e-01
2.47410446e-01 1.09609216e-01 -7.67703831e-01 -7.88879097e-02
2.09654525e-01 1.26531219e+00 -9.94735718e-01 -2.13863149e-01
-6.00799918e-01 1.13604403e+00 -1.21291660e-01 5.64032674e-01
-3.44160050e-01 -2.62513608e-01 1.05232513e+00 -3.28719988e-02
3.01143497e-01 -5.19922495e-01 -4.14877683e-01 -1.34330106e+00
1.27554670e-01 -1.33040905e+00 5.30971408e-01 -6.76973641e-01
-1.39975083e+00 3.72682005e-01 -2.05954731e-01 -1.63005972e+00
-6.95627853e-02 -8.74973536e-01 -4.11919951e-01 3.57726842e-01
-7.67159522e-01 -9.20005202e-01 -4.24953401e-01 7.62662470e-01
3.24295819e-01 -2.10371107e-01 8.13653827e-01 1.65189669e-01
-7.75939584e-01 2.40793377e-01 6.28522813e-01 -2.99752951e-02
7.94987977e-01 -1.33609807e+00 4.04651016e-01 1.63090253e+00
3.17417651e-01 6.92599952e-01 1.30745280e+00 -7.07269192e-01
-1.87590647e+00 -8.16457868e-01 3.55692267e-01 -8.04226577e-01
9.24400389e-01 -9.93874222e-02 -8.28186154e-01 8.10851276e-01
-2.79519051e-01 2.41492972e-01 6.93607569e-01 8.64496306e-02
-3.64767611e-01 -3.85689646e-01 -9.52171683e-01 7.71190286e-01
8.86585951e-01 -4.24524367e-01 -4.64831501e-01 3.51684958e-01
4.15056616e-01 -1.41213566e-01 -9.39877212e-01 4.16299164e-01
2.37639606e-01 -1.26358581e+00 1.13493490e+00 -4.82037336e-01
-2.52407134e-01 -7.05041349e-01 -5.78818679e-01 -1.26509678e+00
-3.82422715e-01 -1.03448200e+00 -2.88581967e-01 1.05272603e+00
-7.67435879e-02 -5.36895096e-01 6.80002034e-01 8.14835131e-01
-2.37576604e-01 -2.23327011e-01 -1.09259140e+00 -1.21876431e+00
-2.92662323e-01 -8.87622595e-01 4.07673746e-01 1.08089328e+00
8.31357315e-02 -2.53648818e-01 -5.61876059e-01 4.75322902e-01
9.63863671e-01 4.50375713e-02 1.26312459e+00 -1.45861053e+00
-2.38286957e-01 -4.76663947e-01 -8.81126046e-01 -6.90347552e-01
-1.42949194e-01 -4.96107638e-01 1.32424742e-01 -1.14668345e+00
9.20841843e-03 -1.22609526e-01 -8.97692963e-02 1.47734657e-01
-1.90090582e-01 3.10176313e-01 4.15133327e-01 4.73595768e-01
-3.99848819e-01 1.93575799e-01 6.10875964e-01 3.47260535e-02
-3.29430282e-01 4.35579903e-02 -4.71700698e-01 1.25724077e+00
4.47811633e-01 -3.54921520e-01 3.32129076e-02 -1.28379211e-01
2.22264513e-01 -3.18322986e-01 1.38388291e-01 -1.17283833e+00
6.68247715e-02 -8.50407332e-02 3.79754037e-01 -5.30854940e-01
3.81883115e-01 -1.06259418e+00 3.79497766e-01 1.53743446e-01
3.35761279e-01 3.33542407e-01 -2.58338358e-02 7.07595706e-01
-3.51482391e-01 -1.40879899e-01 6.68698072e-01 -5.75275049e-02
-7.47608721e-01 2.72552401e-01 -3.62940401e-01 -2.33614609e-01
1.04180157e+00 -3.74393940e-01 -2.60416389e-01 -4.88746583e-01
-8.08015347e-01 -1.68461457e-01 9.78240550e-01 1.15319230e-01
7.27547824e-01 -1.30774558e+00 -5.37607551e-01 3.97761703e-01
3.08938269e-02 -9.79762077e-02 1.24401614e-01 1.24920559e+00
-8.41661572e-01 -5.65087646e-02 1.44213187e-02 -7.71849990e-01
-1.52905667e+00 9.54822361e-01 -4.86606658e-02 -4.13079038e-02
-7.31898963e-01 6.81869268e-01 2.96956040e-02 -1.17122538e-01
2.24379867e-01 -1.56948790e-01 1.34419888e-01 2.99153775e-01
8.29780638e-01 8.36692452e-01 1.54434163e-02 -8.99394989e-01
-3.40384573e-01 8.03673744e-01 2.46004611e-01 -1.00153454e-01
1.38710225e+00 -3.31364036e-01 -6.00756466e-01 4.79096234e-01
1.05432618e+00 5.64993262e-01 -1.24326229e+00 1.33237824e-01
3.34310174e-01 -9.12825346e-01 -1.67874292e-01 4.77821715e-02
-9.54262614e-01 7.58991957e-01 5.44225216e-01 5.27953506e-01
1.40457642e+00 -3.11967582e-01 3.93818408e-01 5.20512640e-01
2.87990004e-01 -1.08872318e+00 -1.87096879e-01 5.16705394e-01
9.81393814e-01 -1.10281956e+00 4.56581801e-01 -5.20511210e-01
-5.48875570e-01 1.14101160e+00 6.46365210e-02 -2.56236106e-01
5.75539649e-01 3.38068694e-01 3.01258981e-01 -3.83133776e-02
-2.29352817e-01 -2.79344290e-01 1.40331179e-01 7.98341393e-01
-1.31941408e-01 6.97939619e-02 3.00399046e-02 4.03528333e-01
-3.22631329e-01 -3.76285076e-01 8.67603242e-01 9.02829528e-01
-5.43932676e-01 -8.88166845e-01 -1.21978188e+00 5.21923602e-01
-4.60936069e-01 6.17364421e-02 -3.12707454e-01 7.17681348e-01
-1.66709512e-01 9.81031239e-01 -6.57418370e-02 -3.59571904e-01
4.91134197e-01 9.12619829e-02 2.91454464e-01 -1.31589979e-01
-1.17014162e-01 4.88552064e-01 4.83996747e-03 -1.11649084e+00
-5.06150126e-01 -9.05811787e-01 -8.01093996e-01 -6.47553563e-01
-1.66817069e-01 8.80835857e-03 6.68257475e-01 7.17995405e-01
2.23539069e-01 2.32767817e-02 5.34583688e-01 -1.07338297e+00
-6.24223828e-01 -6.80646360e-01 -1.05272520e+00 8.32122803e-01
4.24752146e-01 -3.75426531e-01 -8.08196664e-01 3.03059578e-01] | [7.611686706542969, 4.258675575256348] |
d28c073a-3e9b-44fd-8d8a-fb644b1eba02 | 3d-human-tongue-reconstruction-from-single-in | 2106.12302 | null | https://arxiv.org/abs/2106.12302v1 | https://arxiv.org/pdf/2106.12302v1.pdf | 3D human tongue reconstruction from single "in-the-wild" images | 3D face reconstruction from a single image is a task that has garnered increased interest in the Computer Vision community, especially due to its broad use in a number of applications such as realistic 3D avatar creation, pose invariant face recognition and face hallucination. Since the introduction of the 3D Morphable Model in the late 90's, we witnessed an explosion of research aiming at particularly tackling this task. Nevertheless, despite the increasing level of detail in the 3D face reconstructions from single images mainly attributed to deep learning advances, finer and highly deformable components of the face such as the tongue are still absent from all 3D face models in the literature, although being very important for the realness of the 3D avatar representations. In this work we present the first, to the best of our knowledge, end-to-end trainable pipeline that accurately reconstructs the 3D face together with the tongue. Moreover, we make this pipeline robust in "in-the-wild" images by introducing a novel GAN method tailored for 3D tongue surface generation. Finally, we make publicly available to the community the first diverse tongue dataset, consisting of 1,800 raw scans of 700 individuals varying in gender, age, and ethnicity backgrounds. As we demonstrate in an extensive series of quantitative as well as qualitative experiments, our model proves to be robust and realistically captures the 3D tongue structure, even in adverse "in-the-wild" conditions. | ['Stefanos Zafeiriou', 'Vasileios Triantafyllou', 'Stylianos Moschoglou', 'Stylianos Ploumpis'] | 2021-06-23 | null | http://openaccess.thecvf.com//content/CVPR2022/html/Ploumpis_3D_Human_Tongue_Reconstruction_From_Single_In-the-Wild_Images_CVPR_2022_paper.html | http://openaccess.thecvf.com//content/CVPR2022/papers/Ploumpis_3D_Human_Tongue_Reconstruction_From_Single_In-the-Wild_Images_CVPR_2022_paper.pdf | cvpr-2022-1 | ['robust-face-recognition', '3d-face-reconstruction', 'face-hallucination', 'face-reconstruction'] | ['computer-vision', 'computer-vision', 'computer-vision', 'computer-vision'] | [ 1.35162398e-01 4.45057958e-01 2.72048593e-01 -3.69129449e-01
-7.05311954e-01 -5.34850359e-01 6.38560474e-01 -3.20527375e-01
-6.98784590e-02 3.75312954e-01 3.22994024e-01 1.44084752e-01
1.92911282e-01 -4.87295806e-01 -7.42107034e-01 -7.28388488e-01
2.88854897e-01 8.43140781e-01 -1.52459264e-01 -2.31851578e-01
-2.09255189e-01 8.84139717e-01 -1.83999836e+00 -1.61044206e-02
3.76097500e-01 9.84389007e-01 -1.07654147e-01 1.80238903e-01
4.40508593e-03 1.85573965e-01 -2.49001577e-01 -9.43963826e-01
3.71317714e-01 -5.15108585e-01 -4.97211039e-01 5.01704037e-01
6.23274267e-01 -3.65616471e-01 -3.28022838e-01 7.76333988e-01
6.54423594e-01 -1.78214088e-01 5.56319118e-01 -9.17548537e-01
-5.68565667e-01 -9.47345942e-02 -5.99023521e-01 -4.38844323e-01
5.42218268e-01 2.94867188e-01 6.33780122e-01 -8.79740119e-01
1.03875589e+00 1.24299514e+00 7.49240041e-01 1.03646588e+00
-1.31034935e+00 -5.32820404e-01 -2.16259211e-01 -3.26176643e-01
-1.15223432e+00 -7.60627925e-01 1.01968527e+00 -4.49818492e-01
5.88421583e-01 1.02534652e-01 8.39759409e-01 1.45281017e+00
-1.34977892e-01 5.89976430e-01 1.44402611e+00 -5.63108623e-01
1.51704550e-01 1.28324166e-01 -6.64556742e-01 8.14150035e-01
-5.84906563e-02 5.38586266e-02 -5.69043219e-01 -6.18080050e-02
9.07722771e-01 -1.66792333e-01 -1.68583065e-01 -5.09610057e-01
-8.45180809e-01 6.52505934e-01 1.44872233e-01 8.97981375e-02
-4.16049391e-01 2.85506696e-02 1.24658033e-01 -2.25325078e-02
7.78713822e-01 -1.45506442e-01 -2.27733567e-01 -1.74442530e-01
-8.66254151e-01 4.28658336e-01 6.74886286e-01 6.62686169e-01
5.25792301e-01 2.58153617e-01 2.90027261e-01 7.59475887e-01
4.65287536e-01 7.39210963e-01 2.70039618e-01 -1.08803380e+00
5.71090989e-02 6.97537899e-01 -1.52559966e-01 -6.66437507e-01
-2.68515199e-01 -3.41755211e-01 -7.72557199e-01 6.05619192e-01
5.61197221e-01 5.13974205e-02 -1.09164524e+00 1.85876691e+00
7.61706769e-01 7.41209984e-02 -2.09853798e-01 9.60699320e-01
8.80542636e-01 1.67912722e-01 -2.65315384e-01 -9.41917151e-02
1.41466773e+00 -3.11855465e-01 -3.97572398e-01 -1.87055260e-01
1.67208090e-02 -8.65952253e-01 8.90394688e-01 3.66901100e-01
-1.26320314e+00 -1.46112934e-01 -5.66436589e-01 -5.55770732e-02
1.89352524e-03 -3.25035751e-01 5.78005075e-01 9.03114021e-01
-1.25632060e+00 5.07778585e-01 -8.25857341e-01 -5.48553586e-01
9.43251252e-01 3.84140909e-01 -1.05884922e+00 -2.07294717e-01
-5.88799775e-01 9.63843882e-01 -3.71627897e-01 1.77352637e-01
-8.33694994e-01 -7.66797662e-01 -8.86986494e-01 -2.32077345e-01
2.80349225e-01 -8.68085265e-01 1.08229005e+00 -9.91320252e-01
-1.57958782e+00 1.56801629e+00 -2.20224664e-01 -9.07876641e-02
8.51675391e-01 2.01457158e-01 -7.85513520e-02 1.41856983e-01
-2.26735294e-01 6.54526889e-01 1.04111850e+00 -1.54405618e+00
1.39085263e-01 -9.94323134e-01 -2.34698936e-01 5.92775978e-02
-6.71288744e-02 1.28588051e-01 -5.68370104e-01 -5.98643661e-01
8.65612030e-02 -9.51782107e-01 6.99473545e-02 5.13572395e-01
-1.65460229e-01 1.21332273e-01 8.27651858e-01 -9.33071256e-01
3.16482425e-01 -1.94929671e+00 3.16727042e-01 2.08515115e-02
2.62938380e-01 4.03078884e-01 8.35940912e-02 4.06708479e-01
-6.06487580e-02 1.04956023e-01 -5.40762484e-01 -1.04405940e+00
6.02119043e-02 1.76289037e-01 -1.18850786e-02 7.24391341e-01
2.56896883e-01 1.05499184e+00 -6.05977118e-01 -4.09830958e-01
1.88865229e-01 1.16710114e+00 -4.83421743e-01 2.87912488e-01
-2.22890034e-01 1.00426447e+00 -2.39471585e-01 8.40109944e-01
6.91668689e-01 2.31477633e-01 4.97026518e-02 5.86598320e-03
9.84267369e-02 -2.21275851e-01 -7.13103116e-01 1.91535830e+00
-4.05672550e-01 5.08247197e-01 5.95055580e-01 -6.26523077e-01
8.74851048e-01 6.89214289e-01 6.11928642e-01 -7.72139072e-01
2.38540754e-01 4.50694889e-01 -2.33791664e-01 -4.83596087e-01
1.59432013e-02 -8.56366456e-01 2.08406761e-01 2.87845492e-01
1.36101276e-01 -5.69746256e-01 -2.88143814e-01 -1.67300075e-01
6.74912572e-01 4.99167204e-01 -7.27918595e-02 3.29897404e-02
3.31090569e-01 -3.17437559e-01 1.78727850e-01 -6.07590601e-02
-9.93267819e-02 1.16832960e+00 5.01735389e-01 -4.64344859e-01
-1.13826764e+00 -1.05066752e+00 -3.16197306e-01 1.86028644e-01
-3.47904682e-01 -1.22126173e-02 -1.02330160e+00 -5.92968166e-01
9.31254998e-02 2.81078100e-01 -9.11658525e-01 6.17540302e-03
-4.77709889e-01 -4.51567203e-01 6.67717159e-01 1.10704139e-01
4.55355316e-01 -1.18212867e+00 -4.56517816e-01 -6.35765716e-02
-2.94577293e-02 -1.25042808e+00 -3.56623918e-01 -2.91928530e-01
-7.10302114e-01 -9.18085694e-01 -9.57347572e-01 -6.79497361e-01
6.96891785e-01 -1.64970130e-01 1.12024736e+00 1.27532586e-01
-5.32108009e-01 5.05896091e-01 -2.36083880e-01 -3.99272293e-01
-5.94080091e-01 -3.18082392e-01 1.15262933e-01 3.97425056e-01
-8.59163404e-02 -9.56784427e-01 -6.00796521e-01 2.07182989e-01
-9.11636770e-01 5.36045432e-02 2.91263998e-01 5.28368354e-01
5.91185212e-01 -2.88388640e-01 4.59243774e-01 -6.76954091e-01
3.89734894e-01 -2.44411141e-01 -4.65223521e-01 -6.41592890e-02
-2.38972634e-01 -1.01046570e-01 3.31845611e-01 -2.05306619e-01
-1.05184472e+00 1.18828319e-01 -8.37804317e-01 -5.83682716e-01
-4.82895404e-01 4.42690179e-02 -4.92747009e-01 -2.27111742e-01
5.15679836e-01 2.30972081e-01 5.99532783e-01 -7.89065719e-01
1.79383978e-01 6.19612694e-01 4.90705132e-01 -5.06419182e-01
1.01325858e+00 9.02750373e-01 4.06335056e-01 -9.74970639e-01
-5.14923275e-01 -3.81786749e-02 -6.99373007e-01 -4.38496351e-01
9.13586617e-01 -7.66818881e-01 -9.98897433e-01 8.44627142e-01
-1.01847506e+00 -4.70095515e-01 -4.07197803e-01 1.05820009e-02
-6.37916148e-01 2.29530290e-01 -2.92875946e-01 -9.50935364e-01
-3.48540366e-01 -1.37424707e+00 1.50309658e+00 2.04530001e-01
-1.79559037e-01 -1.21042693e+00 -1.97640322e-02 7.74599850e-01
4.39649075e-01 9.91799533e-01 7.37509429e-01 2.37291828e-02
-3.93374562e-01 -3.86687934e-01 2.34864473e-01 4.34236467e-01
1.63054824e-01 -9.55015868e-02 -1.47332573e+00 -2.04422995e-01
-1.30568305e-02 -4.33190644e-01 7.03773499e-01 1.50935113e-01
6.25322282e-01 -1.63308561e-01 4.46647219e-02 6.34142995e-01
1.23562360e+00 -2.12289914e-01 7.45909333e-01 -2.84763306e-01
7.72953033e-01 9.68209565e-01 -2.83603254e-03 2.78722852e-01
3.09122503e-01 1.00753009e+00 7.99703360e-01 -1.43901899e-01
-7.24649370e-01 -3.17010760e-01 2.83149451e-01 3.54196548e-01
-3.55888605e-01 -4.18589413e-02 -7.68801093e-01 4.46413606e-01
-1.21356773e+00 -8.45533431e-01 5.78131042e-02 2.34023428e+00
6.11063361e-01 -1.30411521e-01 2.67272890e-01 1.14115946e-01
4.65894222e-01 -6.65413588e-02 -6.00828290e-01 -3.11792940e-01
-2.76210934e-01 5.06343961e-01 -1.87648416e-01 4.63454485e-01
-6.18018389e-01 8.52330565e-01 5.17162752e+00 5.81509769e-01
-1.33426547e+00 6.42558858e-02 7.48804569e-01 -4.73732464e-02
-4.95601654e-01 -1.23840846e-01 -5.57063401e-01 2.86583036e-01
6.21168971e-01 2.50262380e-01 4.69379067e-01 5.44965506e-01
2.33333901e-01 7.83531889e-02 -9.31061924e-01 1.09473073e+00
3.35717291e-01 -1.20830786e+00 7.88622573e-02 5.07406831e-01
6.36476338e-01 -7.78290927e-02 2.57475495e-01 -1.50033534e-01
-1.72680154e-01 -1.37426674e+00 1.01360571e+00 5.34552515e-01
1.27266800e+00 -6.74844682e-01 3.49714190e-01 3.94734085e-01
-7.88627207e-01 3.30982685e-01 7.87108317e-02 1.62783563e-01
3.57882023e-01 5.42544961e-01 -7.65531123e-01 4.72538918e-01
5.63840806e-01 3.87564927e-01 -3.56428117e-01 7.95797467e-01
-1.27668202e-01 4.12835926e-01 -3.27360928e-01 4.83824432e-01
-3.16915251e-02 -2.04623997e-01 5.50836980e-01 6.82609856e-01
4.48705941e-01 8.46878141e-02 -3.08039308e-01 8.80616069e-01
-4.86023009e-01 -1.37601513e-03 -7.63263404e-01 -7.41907358e-02
-7.84121454e-02 1.35497046e+00 -6.88152254e-01 2.91801065e-01
-2.38381907e-01 1.04636216e+00 2.64781743e-01 9.88778695e-02
-4.89930451e-01 1.99026257e-01 7.59421587e-01 6.26974046e-01
2.32785866e-01 -2.99262732e-01 -9.63326246e-02 -1.04622567e+00
3.18263471e-01 -8.46118867e-01 -1.12379692e-01 -8.66302311e-01
-1.24954474e+00 7.47461140e-01 -6.17454126e-02 -8.43638778e-01
-3.48888248e-01 -6.05293810e-01 -4.03501749e-01 1.00638223e+00
-1.39366531e+00 -1.62719464e+00 -3.86686593e-01 5.94718337e-01
3.61815214e-01 -4.54727113e-02 1.16687799e+00 2.60227084e-01
-3.46428037e-01 5.40142655e-01 -2.25353345e-01 -3.12360004e-02
6.35252655e-01 -8.26681852e-01 5.45515716e-01 4.64634001e-01
1.70675188e-01 5.38209438e-01 7.19856858e-01 -4.53481823e-01
-1.72194779e+00 -7.18024611e-01 7.71448553e-01 -7.23667741e-01
1.80137485e-01 -6.95961595e-01 -8.33940923e-01 6.09563351e-01
3.68036740e-02 2.33865529e-01 4.48584378e-01 -2.31827304e-01
-5.14062166e-01 -1.05166875e-01 -1.57260597e+00 5.45503199e-01
1.12085950e+00 -4.86811250e-01 -2.12622568e-01 2.29572967e-01
1.91514924e-01 -5.91977537e-01 -8.87231588e-01 3.87651920e-01
8.99370790e-01 -1.25156248e+00 9.24291551e-01 -1.81048527e-01
3.55392367e-01 -1.79982893e-02 -8.69274884e-02 -1.24119103e+00
3.29369634e-01 -8.49921882e-01 -5.23999780e-02 1.36785293e+00
1.23242855e-01 -5.57264566e-01 1.14925361e+00 6.59358561e-01
-1.31849155e-01 -9.13963914e-01 -1.40883601e+00 -4.26159203e-01
2.72287071e-01 -3.41456801e-01 5.36513805e-01 6.63687050e-01
-5.11950850e-01 7.36985430e-02 -4.20554429e-01 -1.88788280e-01
7.55715728e-01 7.75546283e-02 8.35045815e-01 -1.48082614e+00
-3.07785094e-01 -4.46587890e-01 -5.71112990e-01 -6.60683632e-01
3.46094131e-01 -1.01820862e+00 -2.62864411e-01 -1.44851339e+00
1.15500256e-01 -3.56039524e-01 4.71147597e-01 4.71269548e-01
2.39122033e-01 8.46882403e-01 9.92434919e-02 3.12968269e-02
7.62845725e-02 6.06928945e-01 1.53758097e+00 1.57199353e-01
1.69199988e-01 3.46248932e-02 -7.40237892e-01 7.07035184e-01
4.71374422e-01 -2.88145304e-01 -2.65096068e-01 -4.98375654e-01
3.44928280e-02 1.55970991e-01 5.75609803e-01 -7.05611289e-01
-2.39293948e-01 1.56347796e-01 4.91309404e-01 6.35912549e-03
9.48407948e-01 -9.90675032e-01 4.93781328e-01 2.20341757e-01
1.76007897e-01 -1.49639457e-01 3.64526778e-01 2.97786415e-01
6.63056597e-02 1.41385093e-01 1.03351879e+00 -3.38183492e-01
-2.06080571e-01 5.62381208e-01 1.76891759e-02 4.98762242e-02
8.95320296e-01 -3.90728801e-01 5.58262244e-02 -5.24684787e-01
-7.45256245e-01 -2.36002281e-01 9.29640412e-01 3.67569536e-01
6.57150388e-01 -1.10720825e+00 -9.31079149e-01 5.24295509e-01
2.15023104e-02 1.92356557e-01 4.05811578e-01 8.12475026e-01
-6.12483442e-01 -3.09999119e-02 -1.55259326e-01 -6.42263055e-01
-1.35219383e+00 2.20102131e-01 5.18100917e-01 2.77609024e-02
-8.07010233e-01 6.96595669e-01 1.09444320e-01 -5.70847511e-01
8.20400417e-02 2.59653389e-01 1.59034863e-01 -1.71264224e-02
3.58552456e-01 7.52801746e-02 3.68257701e-01 -1.22443879e+00
-3.86251211e-01 9.80056167e-01 2.59613782e-01 -2.01004639e-01
1.52540445e+00 5.24794720e-02 -1.16474539e-01 2.71851510e-01
1.18093300e+00 2.10711911e-01 -1.54988253e+00 1.52787611e-01
-4.57587987e-01 -5.43739498e-01 -1.65458217e-01 -7.46599495e-01
-1.33352208e+00 1.08879423e+00 5.09002984e-01 -1.49486125e-01
1.06060970e+00 2.32529774e-01 7.98108280e-01 -2.09141284e-01
5.85236609e-01 -3.93907577e-01 1.02871545e-01 1.87947720e-01
1.04368734e+00 -1.10639644e+00 -1.82864890e-01 -4.41411495e-01
-5.59161365e-01 8.84432614e-01 1.66844040e-01 2.08951849e-02
5.91482997e-01 3.89059842e-01 3.10776055e-01 -2.47686386e-01
-3.07058901e-01 -2.64813248e-02 1.44899264e-01 9.59509373e-01
4.64184523e-01 -1.83634117e-01 1.84521452e-01 1.94268301e-01
-2.79960155e-01 -5.99253364e-02 2.99104780e-01 6.70710385e-01
2.55736690e-02 -1.37578332e+00 -4.14916009e-01 2.95210779e-02
-5.14404178e-01 2.45622739e-01 -5.44083357e-01 8.86215389e-01
1.83570683e-01 8.00907135e-01 -1.01277009e-01 -6.34924918e-02
6.34820759e-01 3.50503415e-01 1.01287222e+00 -5.10544538e-01
-6.63996637e-01 5.27605675e-02 -9.66352448e-02 -3.93914014e-01
-2.62688935e-01 -8.51504683e-01 -1.17926407e+00 -4.68694627e-01
5.47900796e-02 -2.15182424e-01 1.06865954e+00 8.75667155e-01
3.72063756e-01 1.34451985e-01 5.05175114e-01 -1.42697906e+00
-3.12718093e-01 -7.74097741e-01 -6.95136845e-01 7.46536970e-01
4.04850572e-01 -7.11928725e-01 -3.35816056e-01 8.65041241e-02] | [12.759668350219727, -0.28265926241874695] |
54c30328-72b8-4b54-89b6-3e5daa0014dd | vision-transformers-for-small-histological | 2305.17370 | null | https://arxiv.org/abs/2305.17370v1 | https://arxiv.org/pdf/2305.17370v1.pdf | Vision Transformers for Small Histological Datasets Learned through Knowledge Distillation | Computational Pathology (CPATH) systems have the potential to automate diagnostic tasks. However, the artifacts on the digitized histological glass slides, known as Whole Slide Images (WSIs), may hamper the overall performance of CPATH systems. Deep Learning (DL) models such as Vision Transformers (ViTs) may detect and exclude artifacts before running the diagnostic algorithm. A simple way to develop robust and generalized ViTs is to train them on massive datasets. Unfortunately, acquiring large medical datasets is expensive and inconvenient, prompting the need for a generalized artifact detection method for WSIs. In this paper, we present a student-teacher recipe to improve the classification performance of ViT for the air bubbles detection task. ViT, trained under the student-teacher framework, boosts its performance by distilling existing knowledge from the high-capacity teacher model. Our best-performing ViT yields 0.961 and 0.911 F1-score and MCC, respectively, observing a 7% gain in MCC against stand-alone training. The proposed method presents a new perspective of leveraging knowledge distillation over transfer learning to encourage the use of customized transformers for efficient preprocessing pipelines in the CPATH systems. | ['Kjersti Engan', 'Tahlita CM Zuiverloon', 'Farbod Khoraminia', 'Trygve Eftestol', 'Neel Kanwal'] | 2023-05-27 | null | null | null | null | ['whole-slide-images'] | ['computer-vision'] | [ 2.55139649e-01 3.50106746e-01 2.94710129e-01 -1.26266584e-01
-1.16648245e+00 -3.57218266e-01 3.16603631e-01 3.56672585e-01
-4.60040957e-01 4.68609273e-01 -3.15676391e-01 -5.86211205e-01
-8.41565952e-02 -6.65720940e-01 -7.34762371e-01 -1.10772228e+00
3.22755665e-01 2.33035192e-01 5.60557067e-01 3.20168346e-01
1.32939428e-01 6.29130840e-01 -1.08426464e+00 4.22787875e-01
1.21158648e+00 9.68588710e-01 3.45147282e-01 7.93509603e-01
-1.18072510e-01 9.04254913e-01 -6.47174180e-01 -6.44066513e-01
-5.78500032e-02 -1.76008299e-01 -7.59246945e-01 -1.23676427e-01
3.87318581e-01 -3.48082423e-01 -2.48664215e-01 8.39542091e-01
7.00522363e-01 -4.44158226e-01 6.53292000e-01 -1.10057473e+00
-5.87217331e-01 5.54531813e-01 -5.07656753e-01 4.56230462e-01
-2.93321729e-01 6.78628862e-01 6.19989693e-01 -7.42316544e-01
4.67189640e-01 5.76891482e-01 9.80094194e-01 5.64922988e-01
-1.03875804e+00 -4.44257468e-01 -4.16897267e-01 5.61353028e-01
-1.12917650e+00 -2.70275503e-01 4.19198364e-01 -4.69474941e-01
9.94051218e-01 3.60261828e-01 5.96912503e-01 1.02179909e+00
3.52852613e-01 9.93452728e-01 1.15640891e+00 -4.17528898e-01
1.74180940e-01 4.60176796e-01 1.63058490e-01 9.08088088e-01
4.72088873e-01 -4.25916225e-01 -4.53318387e-01 1.95250269e-02
6.05471373e-01 2.74996888e-02 -4.02303457e-01 -2.77887080e-02
-1.04769683e+00 4.11763668e-01 4.51910794e-01 4.15233076e-01
-1.96804404e-01 2.63737119e-03 5.53209305e-01 3.97505239e-02
4.43871945e-01 5.77309191e-01 -2.98275411e-01 9.35925692e-02
-1.06751633e+00 -3.01202714e-01 4.65390831e-01 6.63389981e-01
4.35871571e-01 -2.07104996e-01 -6.55414879e-01 8.06577146e-01
-8.30150545e-02 5.55741668e-01 5.95837772e-01 -6.32564723e-01
-1.01576731e-01 8.35820913e-01 -4.49916720e-01 -6.34181321e-01
-3.49657089e-01 -9.08702552e-01 -7.64543533e-01 5.64176999e-02
5.69942534e-01 9.41328555e-02 -1.30047429e+00 1.13771832e+00
4.18117553e-01 5.45853794e-01 8.11419170e-03 7.33065963e-01
8.37081015e-01 2.57425457e-01 6.13472201e-02 -1.21269494e-01
1.41283894e+00 -1.01123011e+00 -5.40583372e-01 1.34952158e-01
8.93199801e-01 -6.45659626e-01 1.23452425e+00 7.20515013e-01
-9.43399847e-01 -2.24887520e-01 -9.94617701e-01 -3.55561525e-01
-2.45943040e-01 5.33165872e-01 5.94722629e-01 6.09730721e-01
-1.11778522e+00 5.18651426e-01 -1.16063917e+00 -4.10519212e-01
8.48527670e-01 3.54553461e-01 -3.13006163e-01 -2.61477172e-01
-5.57567358e-01 9.09218550e-01 -1.28980398e-01 3.00602555e-01
-1.13039374e+00 -1.14782310e+00 -4.14879292e-01 1.78370699e-01
2.86830038e-01 -5.16109586e-01 1.16284704e+00 -4.26650196e-01
-1.54014063e+00 9.15963948e-01 1.73047006e-01 -4.72948104e-01
7.17147768e-01 -8.44890922e-02 -4.96238880e-02 5.58183551e-01
-1.30973920e-01 4.26119566e-01 7.01959670e-01 -8.69500935e-01
-6.26371145e-01 -1.83586463e-01 -2.84197003e-01 -3.22171062e-01
-7.16340721e-01 -2.64194518e-01 -5.76843381e-01 -2.85652786e-01
-1.84827864e-01 -7.65830398e-01 -1.21576518e-01 3.63687396e-01
-4.93425578e-01 -2.67166138e-01 6.61245167e-01 -8.96252573e-01
8.52199733e-01 -2.27820373e+00 -4.33695942e-01 1.21615119e-01
4.43183124e-01 6.64533138e-01 -1.70475587e-01 -4.78934012e-02
1.67359412e-01 -8.64606351e-02 4.58128825e-02 -2.68746197e-01
-2.32462123e-01 1.18550874e-01 2.29121931e-02 6.01667285e-01
5.50981820e-01 1.00038874e+00 -8.63117874e-01 -7.65671194e-01
3.47781107e-02 5.00322223e-01 -5.13254046e-01 2.88639247e-01
-1.27582565e-01 2.89851159e-01 -1.48473144e-01 7.35724807e-01
6.82166338e-01 -6.24189258e-01 5.89229278e-02 -3.21137398e-01
7.00569451e-02 2.61278063e-01 -5.72476625e-01 1.40554917e+00
-3.88366282e-01 9.04131830e-01 -6.70800805e-02 -1.09859824e+00
6.91569805e-01 4.43025917e-01 4.38495934e-01 -6.59756660e-01
2.87057851e-02 3.82815182e-01 9.15081427e-02 -1.02623439e+00
2.65217498e-02 -1.36413798e-01 4.43396688e-01 1.19405970e-01
3.57992858e-01 -9.10664722e-02 1.69605389e-01 2.40627453e-01
1.53420615e+00 -3.63023803e-02 -3.79011519e-02 -9.10907909e-02
4.80947584e-01 1.72192752e-01 5.79434693e-01 5.56107640e-01
-3.28432471e-01 5.32660186e-01 6.05928242e-01 -3.17038745e-01
-9.58188713e-01 -1.03822541e+00 -2.61831254e-01 6.81778073e-01
-2.07504332e-01 -4.62593324e-02 -7.26628840e-01 -8.31811249e-01
-1.15613714e-01 3.53718221e-01 -6.30338609e-01 -2.27933392e-01
-3.42553437e-01 -9.35630679e-01 8.44696641e-01 5.87548316e-01
3.90165061e-01 -6.20695412e-01 -6.56048238e-01 1.06617376e-01
-2.32158765e-01 -1.11350834e+00 -2.01733127e-01 2.90827155e-01
-8.25981796e-01 -1.23355019e+00 -7.87693799e-01 -6.80227458e-01
9.82097149e-01 2.82648236e-01 6.52928829e-01 3.38410318e-01
-7.16898918e-01 1.94291815e-01 -2.44523630e-01 -7.41391301e-01
-4.25261170e-01 1.37751615e-02 -2.62170076e-01 -7.63475299e-02
3.98077399e-01 -3.86666447e-01 -7.71336496e-01 -1.02291405e-01
-8.93713892e-01 1.42378300e-01 1.13808799e+00 1.11313605e+00
6.84731960e-01 -6.26514032e-02 4.77133244e-01 -1.03042674e+00
2.41684183e-01 -2.05588952e-01 -4.41509902e-01 4.87025768e-01
-8.12573671e-01 2.64076460e-02 6.63544714e-01 -5.89424253e-01
-1.12463355e+00 -3.33347507e-02 -1.71037689e-01 -4.95719671e-01
5.36704734e-02 4.39291626e-01 1.45898357e-01 -2.20736325e-01
8.42741787e-01 3.04421186e-01 2.69891489e-02 -2.48486310e-01
-1.00737281e-01 6.10566795e-01 7.45974004e-01 -1.37461886e-01
6.79192603e-01 4.48210597e-01 -1.08396001e-02 -7.01248467e-01
-8.32528651e-01 -5.77014506e-01 -2.75018126e-01 -1.34171471e-01
5.73163331e-01 -8.21618795e-01 -6.57748103e-01 6.73934340e-01
-8.63543093e-01 -5.26115835e-01 -2.49489561e-01 4.09325421e-01
-1.16638295e-01 4.46475685e-01 -8.71549845e-01 -5.70551693e-01
-8.68551731e-01 -1.19618142e+00 9.39822137e-01 4.72054631e-01
9.97248739e-02 -8.28296065e-01 -8.26559290e-02 7.10491955e-01
5.17171443e-01 8.02329108e-02 1.08083427e+00 -8.13355625e-01
-5.80132961e-01 -2.74930179e-01 -3.87375861e-01 5.23062110e-01
-3.27094086e-02 3.14220160e-01 -1.49714756e+00 -2.70041883e-01
1.06843263e-01 -2.41473794e-01 9.79497433e-01 3.21228087e-01
1.43543828e+00 -8.06063563e-02 -5.79552829e-01 6.02193296e-01
1.32865155e+00 -1.05132930e-01 6.91247761e-01 2.30245635e-01
5.67214906e-01 3.39406639e-01 3.19285691e-01 1.46218985e-01
3.04402441e-01 1.36916399e-01 3.16473007e-01 -5.66281378e-01
-5.29508471e-01 -9.75542422e-03 3.09632152e-01 7.50684738e-01
1.63098261e-01 -4.76701260e-02 -1.20624173e+00 7.90446043e-01
-1.48187625e+00 -5.93033493e-01 -5.28004289e-01 1.84319186e+00
1.18290102e+00 1.48138210e-01 -3.49210352e-01 3.86776924e-01
3.83949399e-01 -5.84388673e-01 -5.46255708e-01 -9.57463011e-02
2.25821719e-01 4.13039714e-01 4.36030805e-01 1.35318652e-01
-8.39935720e-01 5.97437203e-01 5.75663519e+00 9.72352207e-01
-1.59978485e+00 2.48939469e-01 7.64282346e-01 -9.94744748e-02
-1.37336925e-01 -4.12194461e-01 -6.63449705e-01 3.34568560e-01
1.16431880e+00 -2.30745282e-02 -1.57742441e-01 8.07578444e-01
1.94011241e-01 -2.20236719e-01 -1.11513352e+00 7.01196551e-01
3.02698128e-02 -1.39866197e+00 -5.31670302e-02 1.87808666e-02
4.56854373e-01 2.94678621e-02 1.50438830e-01 4.46154088e-01
7.65537024e-02 -9.04154003e-01 1.48600176e-01 4.74803180e-01
9.93135273e-01 -3.52235138e-01 1.24827445e+00 2.30275899e-01
-5.47260642e-01 2.36350261e-02 -4.12310839e-01 3.41876715e-01
-4.03188705e-01 1.16675282e+00 -1.70094883e+00 4.97779161e-01
7.12623656e-01 3.52930814e-01 -9.75573778e-01 1.55074859e+00
-2.25990862e-01 9.79914546e-01 -2.66187221e-01 1.02988340e-01
3.46166044e-02 3.12011600e-01 1.89121991e-01 1.54439723e+00
4.38672870e-01 -1.43142700e-01 -2.45085746e-01 6.57621801e-01
-1.86558008e-01 -3.25792432e-02 -5.28593622e-02 -7.67183080e-02
3.19887340e-01 1.69397867e+00 -9.49617088e-01 -4.84947622e-01
-3.50551188e-01 7.18936980e-01 3.33645523e-01 4.94116098e-02
-8.90605450e-01 -3.36686999e-01 1.66522399e-01 1.33028850e-01
2.39781484e-01 2.13838026e-01 -6.27541244e-01 -1.00508606e+00
-6.06607161e-02 -8.16640675e-01 3.63165230e-01 -6.43683553e-01
-1.36544740e+00 3.05131674e-01 -5.93016505e-01 -1.05413628e+00
2.04144627e-01 -8.87258112e-01 -7.66010046e-01 6.00742280e-01
-1.88806677e+00 -1.31759810e+00 -6.24040723e-01 5.22560179e-01
4.08279717e-01 2.54842937e-01 6.87273145e-01 3.46330762e-01
-7.20556855e-01 8.72207105e-01 1.65605783e-01 1.78551808e-01
9.97630119e-01 -1.42608118e+00 -1.25729263e-01 9.42090213e-01
-1.13954850e-01 4.20656413e-01 5.35827219e-01 -2.68715590e-01
-1.48738444e+00 -1.18574917e+00 8.18754733e-01 -4.33008194e-01
6.64717376e-01 -8.19158107e-02 -1.20963764e+00 4.36745763e-01
-5.62277436e-02 2.50800222e-01 1.05502999e+00 -1.26483098e-01
-3.25398386e-01 -3.60618383e-01 -1.33305264e+00 4.80131388e-01
4.39422846e-01 -5.56478441e-01 -3.79538149e-01 4.38601375e-01
4.53481257e-01 -4.21902955e-01 -8.60100865e-01 2.94755012e-01
4.47225630e-01 -7.15409160e-01 6.76661909e-01 -1.36134937e-01
5.67608893e-01 -2.47255191e-01 4.98674244e-01 -1.16677272e+00
-2.12549612e-01 -2.69598126e-01 -8.17684755e-02 1.13164985e+00
4.48076278e-01 -4.50832307e-01 7.88047314e-01 5.75619996e-01
-5.20920932e-01 -8.97498786e-01 -9.16270077e-01 -5.44769168e-01
1.24660350e-01 -2.96589673e-01 1.85535565e-01 9.42559004e-01
2.31881842e-01 3.33752967e-02 2.94727623e-01 4.78342921e-01
5.75442135e-01 -2.21533224e-01 5.22995055e-01 -1.19328642e+00
-4.09286171e-01 -2.73225158e-01 -3.67692709e-01 -5.17391503e-01
-3.09359252e-01 -1.08305907e+00 1.26761019e-01 -1.49421608e+00
4.89710927e-01 -4.36666846e-01 -4.18479711e-01 8.49087179e-01
-4.45508748e-01 5.04316568e-01 -5.48911057e-02 1.13084346e-01
-4.92293507e-01 1.61833405e-01 1.38126564e+00 -4.27716315e-01
1.39454558e-01 -3.01982403e-01 -6.86172783e-01 5.25968611e-01
8.23183298e-01 -5.07300019e-01 -3.62116843e-01 -5.04767954e-01
3.29413339e-02 -2.31648728e-01 4.59878206e-01 -1.25315428e+00
6.59188867e-01 7.02406317e-02 5.65735698e-01 -4.29887414e-01
3.20500694e-02 -5.62263429e-01 -5.70815429e-02 7.85828412e-01
-2.10625246e-01 -5.12395024e-01 2.85833478e-01 3.92927289e-01
-2.71515977e-02 -2.74879873e-01 8.88638973e-01 -2.92537026e-02
-2.28892297e-01 8.99625793e-02 -4.29255694e-01 -3.66283983e-01
1.05869150e+00 -2.68552125e-01 -8.65499198e-01 3.17212403e-01
-5.77326000e-01 3.78264517e-01 1.39905348e-01 -7.71823004e-02
6.52350962e-01 -6.49411798e-01 -6.87295198e-01 1.15446359e-01
1.18678547e-01 4.03964758e-01 5.08790970e-01 1.45133317e+00
-6.25960231e-01 3.59896034e-01 -2.24712715e-01 -8.66093874e-01
-1.34926879e+00 4.45711523e-01 5.07436454e-01 -6.93946302e-01
-7.35112011e-01 1.13763916e+00 7.23573416e-02 -1.42472863e-01
1.73718393e-01 -6.31304801e-01 2.64876219e-03 -9.82348397e-02
6.36818290e-01 3.62318397e-01 6.90596163e-01 3.88790637e-01
-3.41061711e-01 1.77665744e-02 -6.31710351e-01 3.15788895e-01
1.54851949e+00 2.08470657e-01 -1.03662141e-01 1.43970817e-01
8.67128193e-01 -1.54122353e-01 -1.26978087e+00 -1.88778892e-01
9.23449323e-02 -1.62415668e-01 3.86585861e-01 -1.09308791e+00
-1.16054189e+00 1.13565969e+00 6.34194911e-01 3.52208242e-02
1.14867735e+00 -9.05364230e-02 8.41670215e-01 3.41835171e-01
1.64449289e-01 -9.76274431e-01 2.66788721e-01 2.34917685e-01
4.22771394e-01 -1.14043891e+00 -9.95551422e-02 -4.12586600e-01
-4.63938624e-01 1.27019250e+00 6.78648531e-01 1.28288716e-01
1.34209946e-01 6.35058820e-01 2.65241623e-01 -2.82537282e-01
-1.08449161e+00 3.81162427e-02 8.14980268e-02 7.60181308e-01
4.92371172e-01 -1.00962393e-01 -2.76225120e-01 6.58078432e-01
1.78752448e-02 4.11469996e-01 8.57092917e-01 7.11184263e-01
-3.22329253e-01 -6.75283313e-01 -2.46389985e-01 7.02268004e-01
-5.97782791e-01 -6.82493225e-02 -5.84770739e-02 4.94503856e-01
3.14640641e-01 8.14992189e-01 -1.14898607e-01 -1.47255093e-01
2.04591930e-01 1.02319762e-01 4.27888274e-01 -5.64970315e-01
-8.19746256e-01 5.23456484e-02 -1.48711309e-01 -4.39204872e-01
-1.75024912e-01 -3.89440387e-01 -1.35659039e+00 -2.80729145e-01
-5.54245770e-01 2.60698749e-03 6.08798146e-01 1.02306473e+00
3.29015046e-01 9.17183042e-01 3.15589637e-01 -3.71398360e-01
-7.16419041e-01 -9.05898213e-01 -3.26957434e-01 1.34776145e-01
4.02417362e-01 -3.77088428e-01 -2.86955386e-01 4.66052413e-01] | [15.030715942382812, -2.8591551780700684] |
c3b516ba-d043-4960-95a0-b7f0d447c48b | farspredict-a-benchmark-dataset-for-link | 2303.14647 | null | https://arxiv.org/abs/2303.14647v1 | https://arxiv.org/pdf/2303.14647v1.pdf | Farspredict: A benchmark dataset for link prediction | Link prediction with knowledge graph embedding (KGE) is a popular method for knowledge graph completion. Furthermore, training KGEs on non-English knowledge graph promote knowledge extraction and knowledge graph reasoning in the context of these languages. However, many challenges in non-English KGEs pose to learning a low-dimensional representation of a knowledge graph's entities and relations. This paper proposes "Farspredict" a Persian knowledge graph based on Farsbase (the most comprehensive knowledge graph in Persian). It also explains how the knowledge graph structure affects link prediction accuracy in KGE. To evaluate Farspredict, we implemented the popular models of KGE on it and compared the results with Freebase. Given the analysis results, some optimizations on the knowledge graph are carried out to improve its functionality in the KGE. As a result, a new Persian knowledge graph is achieved. Implementation results in the KGE models on Farspredict outperforming Freebases in many cases. At last, we discuss what improvements could be effective in enhancing the quality of Farspredict and how much it improves. | ['Mohsen Jahanshahi', 'Behrouz Minaei-Bidgoli', 'Najmeh Torabian'] | 2023-03-26 | null | null | null | null | ['knowledge-graph-embedding', 'knowledge-graph-completion'] | ['graphs', 'knowledge-base'] | [-7.16049254e-01 9.19959724e-01 -5.54374933e-01 -6.13185279e-02
1.30245611e-01 -4.99306977e-01 3.96723330e-01 3.55426848e-01
-5.53767860e-01 9.35786068e-01 3.64721924e-01 -2.97440588e-01
-6.18155956e-01 -1.59935534e+00 -6.76347911e-01 4.10679681e-03
-4.49365437e-01 9.58267808e-01 4.57940876e-01 -6.31173313e-01
-2.92492539e-01 4.51025575e-01 -1.09783173e+00 1.10426098e-01
8.93901408e-01 2.08653361e-01 8.96781012e-02 3.64735395e-01
-6.07180417e-01 9.88119245e-01 -5.26526928e-01 -1.25117421e+00
-6.50148317e-02 3.04126769e-01 -1.39431751e+00 -5.94873905e-01
3.84863824e-01 7.48959705e-02 -8.87935162e-01 7.48959899e-01
3.02022994e-01 1.42710507e-01 7.15773344e-01 -1.61516714e+00
-1.00926721e+00 1.30151665e+00 -7.34553963e-04 -4.92283925e-02
5.65420866e-01 -4.81796265e-01 1.25891638e+00 -8.85120451e-01
1.25021386e+00 1.41039741e+00 9.44699585e-01 1.21398099e-01
-7.41389096e-01 -5.03491998e-01 -1.86457768e-01 1.10535312e+00
-1.66048157e+00 9.13653448e-02 5.12003005e-01 -3.72106910e-01
1.51738882e+00 1.48991376e-01 9.28010106e-01 5.93738973e-01
7.25428015e-02 6.31326258e-01 5.11242688e-01 -6.31981134e-01
-3.17182958e-01 3.57164353e-01 7.70409644e-01 1.17773795e+00
9.90544498e-01 -1.52496681e-01 -6.03652835e-01 -7.47539923e-02
5.77942610e-01 -6.63497329e-01 -3.96908432e-01 -6.88530087e-01
-1.05894649e+00 7.92547822e-01 8.00481260e-01 2.65642285e-01
-2.73972869e-01 9.89724603e-03 4.49146777e-01 3.38382065e-01
1.22250021e-01 5.96323967e-01 -6.04203165e-01 1.15447089e-01
-3.09985310e-01 1.31221086e-01 1.34490573e+00 1.16242075e+00
1.02147937e+00 1.50758728e-01 1.38349444e-01 8.29589844e-01
1.74419358e-01 4.10510957e-01 1.07879296e-01 -5.38423657e-01
7.03853905e-01 1.25738847e+00 3.63244899e-02 -1.34245884e+00
-5.61511099e-01 -3.06120425e-01 -4.25905675e-01 -2.02138051e-01
2.53851652e-01 -7.43315294e-02 -5.95728934e-01 1.23023450e+00
3.14977109e-01 6.22514598e-02 6.63204253e-01 4.79466051e-01
1.49993360e+00 5.60237169e-01 1.66980729e-01 1.93399876e-01
1.42617023e+00 -8.48686516e-01 -9.23639238e-01 -9.83636007e-02
1.03111553e+00 -3.65744323e-01 7.04860806e-01 -1.15936317e-01
-3.87744665e-01 -3.59524667e-01 -1.05668926e+00 -3.06574225e-01
-1.21133280e+00 8.50374401e-02 1.05344713e+00 6.82223618e-01
-8.25853169e-01 5.91694713e-01 -7.15314627e-01 -6.69585347e-01
3.24431419e-01 4.21243101e-01 -9.65615451e-01 -3.61288160e-01
-1.82507920e+00 1.50578976e+00 1.64109504e+00 -2.32937738e-01
-1.59887105e-01 -7.01320052e-01 -1.37802637e+00 2.46524855e-01
7.08737612e-01 -6.94241703e-01 4.28154439e-01 -9.03046057e-02
-8.77277672e-01 7.20601380e-01 1.49602279e-01 -6.54155850e-01
-6.72592297e-02 -2.48186439e-01 -9.24499512e-01 -7.53649622e-02
1.41938075e-01 5.77353299e-01 1.19848512e-01 -1.13988805e+00
-4.35812563e-01 -2.44702339e-01 3.51581126e-01 1.54294357e-01
-5.27502835e-01 -3.69123966e-01 -8.10853124e-01 -2.34448805e-01
-1.52395412e-01 -7.12291956e-01 2.42564648e-01 -6.99968398e-01
-5.63022673e-01 -5.93893290e-01 8.16772997e-01 -1.06137002e+00
1.48425531e+00 -1.99008942e+00 2.61559129e-01 5.28922319e-01
3.51299524e-01 5.54071188e-01 -2.40176409e-01 8.93641114e-01
-1.66071713e-01 1.43727362e-01 2.77831137e-01 5.88420630e-01
1.75719604e-01 8.26408148e-01 2.82340753e-03 3.37906480e-02
-1.10569715e-01 1.41726792e+00 -1.06316769e+00 -7.30373859e-01
1.44159660e-01 4.78639305e-01 -4.30035442e-01 -9.08340961e-02
-2.27282614e-01 -3.25046360e-01 -4.39145803e-01 5.73382795e-01
3.85227770e-01 -1.18225634e-01 8.83960068e-01 -7.00061023e-01
2.57746607e-01 -8.14113952e-03 -1.34347224e+00 1.38901043e+00
-2.95114189e-01 5.00747800e-01 -5.05980313e-01 -8.31702948e-01
9.24029946e-01 4.38452885e-02 2.87484795e-01 -4.19555664e-01
-1.43128082e-01 7.26420619e-03 6.77787438e-02 -5.52511513e-01
9.56733227e-01 2.90297478e-01 9.32281166e-02 1.12053841e-01
6.25700414e-01 7.03843683e-02 6.48192763e-01 7.70725071e-01
1.04467118e+00 3.11878353e-01 7.12919235e-01 -1.54043183e-01
3.74080211e-01 4.18043673e-01 6.64808214e-01 2.72285521e-01
2.04421863e-01 -5.57951927e-01 5.02519786e-01 -5.28557658e-01
-5.74538887e-01 -1.02302074e+00 2.18813438e-02 7.47329354e-01
1.33961767e-01 -1.36581910e+00 -3.49921763e-01 -1.05960250e+00
4.53279346e-01 1.00982845e+00 -4.21127945e-01 -1.97430268e-01
-4.17693377e-01 -6.92349613e-01 8.57927740e-01 5.93636394e-01
6.35842860e-01 -1.12925875e+00 -5.71788400e-02 2.21644670e-01
-2.10366234e-01 -1.26979673e+00 5.71593037e-03 1.47694666e-02
-5.32724082e-01 -1.73042035e+00 -4.54066284e-02 -1.01291299e+00
4.04853374e-01 -1.66379079e-01 1.38163209e+00 1.59118306e-02
-1.24411143e-01 8.18768501e-01 -5.91911972e-01 -5.04857123e-01
-3.56818527e-01 2.37831250e-01 1.55381843e-01 -6.93121374e-01
7.45029509e-01 -5.01369417e-01 1.18831486e-01 3.80884409e-02
-7.63698280e-01 -2.23832279e-01 4.30379421e-01 7.47869790e-01
4.77863461e-01 8.34242880e-01 6.14283741e-01 -1.33321619e+00
6.16660178e-01 -3.27768058e-01 -5.43547213e-01 7.64121890e-01
-9.39293921e-01 4.17102098e-01 2.83843786e-01 2.65311971e-02
-1.00642967e+00 -2.17423916e-01 -8.47621560e-02 -1.92555308e-01
4.10292625e-01 1.10008073e+00 -3.99304539e-01 -1.26585513e-01
7.45217144e-01 -8.60400870e-02 -2.44768545e-01 -4.37716633e-01
1.00609231e+00 2.56411999e-01 4.02314991e-01 -6.39398158e-01
7.45650709e-01 -8.42408314e-02 1.91965532e-02 -9.79988515e-01
-5.74698031e-01 -3.11925858e-01 -6.99276149e-01 6.10911846e-02
7.64100611e-01 -9.96027410e-01 -8.57075334e-01 -1.85509607e-01
-1.05826533e+00 -1.37880176e-01 -4.66151714e-01 6.34700418e-01
-1.79838166e-01 5.28023183e-01 -6.71084523e-01 -4.05948281e-01
-3.86917055e-01 -3.73139650e-01 2.84546852e-01 -3.02936789e-02
-3.87386560e-01 -1.46029043e+00 2.71626532e-01 4.13200170e-01
-4.98940125e-02 7.47995824e-02 1.57022619e+00 -9.08606887e-01
-5.86110651e-01 -7.32014626e-02 -3.03160816e-01 1.95906192e-01
4.24027704e-02 -1.81082580e-02 -3.71892005e-01 -1.88238442e-01
-9.58569646e-01 -1.58706442e-01 7.78999031e-01 -9.91282836e-02
4.98636663e-01 -4.06352907e-01 -6.34014249e-01 5.22704899e-01
1.70107460e+00 -2.33422662e-03 8.93202841e-01 8.12204659e-01
1.04672897e+00 5.18693507e-01 6.60669744e-01 1.85141303e-02
8.89618099e-01 6.08990908e-01 2.38692880e-01 3.44682932e-01
-4.81854945e-01 -7.41567314e-01 4.24540669e-01 1.35462606e+00
-4.39739406e-01 -1.12017021e-01 -1.15657640e+00 7.72828758e-01
-1.86817646e+00 -9.60242033e-01 -4.21636909e-01 1.74961364e+00
9.11097646e-01 -1.45992801e-01 -1.76334068e-01 2.62698755e-02
5.19506216e-01 1.52069042e-04 -1.57306388e-01 -3.12450767e-01
-4.78811175e-01 3.70914519e-01 8.62245142e-01 7.92938948e-01
-8.51210833e-01 1.61880898e+00 5.95541668e+00 8.04837942e-01
-4.38569546e-01 3.61910164e-02 -6.05582058e-01 7.30009198e-01
-3.73483539e-01 2.95513839e-01 -9.78256941e-01 -1.03159323e-01
7.81796813e-01 -5.97884774e-01 3.58699650e-01 9.62042749e-01
-6.38105810e-01 1.63741380e-01 -8.37927938e-01 1.03759301e+00
1.40576798e-03 -1.57461476e+00 4.39223230e-01 2.09723860e-02
4.92623359e-01 -9.51953605e-03 -7.05120742e-01 1.03454411e+00
8.67442548e-01 -9.68590379e-01 5.68208136e-02 5.96026778e-01
6.75069392e-01 -9.63642895e-01 1.00951827e+00 1.33812860e-01
-1.30521965e+00 1.80915684e-01 -7.09358931e-01 2.99764007e-01
2.23201737e-02 6.25846028e-01 -1.32385528e+00 1.54625833e+00
6.83823884e-01 9.65636551e-01 -9.47316527e-01 6.50901198e-01
-8.14647079e-01 4.47067976e-01 -6.71924204e-02 1.00999892e-01
-2.48472318e-01 -2.39120930e-01 4.38143075e-01 1.36734462e+00
2.81490654e-01 -1.58054393e-03 1.76602483e-01 5.63029945e-01
-2.99689084e-01 3.92479241e-01 -9.34772730e-01 -4.59751874e-01
6.35616004e-01 1.15785575e+00 -3.27498376e-01 -4.18938249e-01
-5.50270915e-01 8.42224956e-01 8.06405783e-01 4.31910396e-01
-5.55924714e-01 -6.40664637e-01 4.01343942e-01 9.47619528e-02
2.92361140e-01 -1.12989813e-01 3.76223922e-01 -1.34300399e+00
-1.66097566e-01 -5.90213120e-01 9.27340090e-01 -1.02275252e+00
-1.19020212e+00 5.47834218e-01 2.86568314e-01 -5.81191421e-01
-9.47495997e-02 -8.78151655e-01 6.41954504e-03 6.50703847e-01
-1.45829761e+00 -1.34159291e+00 -3.67271304e-02 8.70799601e-01
-1.68861166e-01 -4.51227456e-01 1.37288892e+00 3.67924601e-01
-4.47622359e-01 5.13802052e-01 -7.63202459e-02 6.53841913e-01
5.45051098e-01 -1.54877675e+00 2.83176452e-01 5.86177051e-01
6.76721096e-01 7.02347279e-01 4.77581888e-01 -1.21680093e+00
-1.51029611e+00 -1.24578834e+00 1.19139433e+00 -5.78541398e-01
9.60708499e-01 7.12268203e-02 -1.12445164e+00 1.36427164e+00
3.02875549e-01 -1.61289617e-01 7.42895067e-01 8.56824815e-01
-6.50018752e-01 -2.41978541e-02 -8.28001499e-01 6.26739085e-01
1.21242678e+00 -4.61486757e-01 -1.28561568e+00 2.68879056e-01
7.40513146e-01 -2.86219358e-01 -1.65151644e+00 5.06358743e-01
3.41118217e-01 -4.53186721e-01 1.07083559e+00 -8.16047490e-01
-2.34350320e-02 -4.62449133e-01 -2.05574200e-01 -1.83855665e+00
-5.06082118e-01 -8.41517523e-02 -7.15295732e-01 1.09241855e+00
5.39527237e-01 -7.98017085e-01 9.50683475e-01 2.16852590e-01
3.73875536e-02 -4.52253133e-01 -7.41716027e-01 -1.13040471e+00
2.17017233e-02 -2.25483805e-01 5.90814888e-01 1.45633972e+00
4.93762910e-01 8.93732846e-01 -3.38918865e-01 3.92610788e-01
5.10873199e-01 1.07615530e-01 9.04481471e-01 -1.48327398e+00
-4.01770584e-02 1.94044366e-01 -1.03285456e+00 -3.29692692e-01
6.67024493e-01 -1.50872517e+00 -7.84746766e-01 -2.18710065e+00
8.09886307e-02 -3.06575745e-01 -1.68979928e-01 1.04529381e+00
-1.82370126e-01 -3.21013540e-01 1.84462681e-01 -4.13815156e-02
-5.60041368e-01 5.03390670e-01 1.16893995e+00 -4.54404265e-01
-9.55300182e-02 -7.01435983e-01 -4.94051129e-01 5.80188096e-01
7.89822876e-01 -4.53583896e-01 -7.33686805e-01 -2.85649329e-01
6.49279356e-01 -1.79336518e-02 1.94624305e-01 -6.77619457e-01
3.72869402e-01 3.55349556e-02 1.61557466e-01 -5.77590525e-01
3.48219216e-01 -8.52019608e-01 5.18725157e-01 3.12174261e-01
3.85018557e-01 -7.01420084e-02 4.70092028e-01 5.51069975e-01
-5.29408634e-01 -2.72110283e-01 1.59219533e-01 4.87117358e-02
-1.57192874e+00 1.39818862e-01 -1.15732467e-02 1.20175928e-01
8.90129507e-01 -2.13507444e-01 -5.66982985e-01 -8.46129954e-02
-1.16241574e+00 3.63076061e-01 1.39740616e-01 4.77961898e-01
7.02593267e-01 -1.56287456e+00 -6.41845822e-01 -1.28459996e-02
5.92095792e-01 -2.81246632e-01 4.32087705e-02 5.04844010e-01
-7.75789320e-01 5.95243335e-01 -3.35289091e-01 1.31152302e-01
-1.35426950e+00 7.66875386e-01 1.35150284e-01 -5.52177787e-01
-7.58224905e-01 4.46457863e-01 -5.76139152e-01 -9.40277278e-01
8.51316750e-02 -6.55258298e-02 -7.71629810e-01 2.42426828e-01
7.71953538e-02 6.45103931e-01 9.49035734e-02 -7.20408678e-01
-4.70027357e-01 3.34732741e-01 -7.04203546e-02 2.84797341e-01
1.45080805e+00 2.37387702e-01 -5.43446004e-01 1.45504773e-01
6.87500179e-01 4.77922082e-01 -2.23136902e-01 -2.84204900e-01
4.14107740e-01 -2.09286764e-01 -2.22059846e-01 -9.81614709e-01
-1.00014329e+00 2.11709172e-01 1.64839998e-01 -1.00815408e-01
6.07744575e-01 1.49137482e-01 6.03958309e-01 1.13664854e+00
7.77526498e-01 -1.10189402e+00 -6.00389123e-01 9.02022660e-01
8.61444712e-01 -9.46918786e-01 3.72017264e-01 -9.54592466e-01
-7.35107839e-01 1.09605527e+00 6.21133506e-01 1.27882361e-01
9.23271358e-01 -1.43900394e-01 -4.67116870e-02 -6.69987440e-01
-4.97972399e-01 -4.96491432e-01 4.81178045e-01 9.69790280e-01
3.13426495e-01 4.52251554e-01 -5.31011879e-01 9.18964982e-01
-6.11453712e-01 8.14840849e-03 4.09898430e-01 7.63484001e-01
-3.18041146e-01 -1.51108479e+00 -2.10688785e-01 4.84299183e-01
-1.17829926e-01 -2.76651859e-01 -7.39649415e-01 1.61549556e+00
3.01846057e-01 7.25328743e-01 -6.10104144e-01 -5.85237801e-01
7.08007395e-01 3.32007378e-01 5.96620262e-01 -7.54928946e-01
-2.97740579e-01 -7.63985693e-01 8.50089967e-01 -5.08682966e-01
-3.64273131e-01 8.09142590e-02 -1.56732893e+00 -6.14050865e-01
-4.26233858e-01 6.47115588e-01 2.47699901e-01 5.32185078e-01
4.17317003e-01 5.79367638e-01 -4.36186939e-01 8.33524615e-02
1.07872956e-01 -8.37687731e-01 -1.04034555e+00 4.81575102e-01
-7.21881747e-01 -8.65750730e-01 1.74740255e-01 7.13232206e-03] | [8.843306541442871, 7.9552154541015625] |
085c29d6-40a2-47ba-8c66-3891f3f2de3a | a-multibias-mitigated-and-sentiment-knowledge | 2207.08104 | null | https://arxiv.org/abs/2207.08104v1 | https://arxiv.org/pdf/2207.08104v1.pdf | A Multibias-mitigated and Sentiment Knowledge Enriched Transformer for Debiasing in Multimodal Conversational Emotion Recognition | Multimodal emotion recognition in conversations (mERC) is an active research topic in natural language processing (NLP), which aims to predict human's emotional states in communications of multiple modalities, e,g., natural language and facial gestures. Innumerable implicit prejudices and preconceptions fill human language and conversations, leading to the question of whether the current data-driven mERC approaches produce a biased error. For example, such approaches may offer higher emotional scores on the utterances by females than males. In addition, the existing debias models mainly focus on gender or race, where multibias mitigation is still an unexplored task in mERC. In this work, we take the first step to solve these issues by proposing a series of approaches to mitigate five typical kinds of bias in textual utterances (i.e., gender, age, race, religion and LGBTQ+) and visual representations (i.e, gender and age), followed by a Multibias-Mitigated and sentiment Knowledge Enriched bi-modal Transformer (MMKET). Comprehensive experimental results show the effectiveness of the proposed model and prove that the debias operation has a great impact on the classification performance for mERC. We hope our study will benefit the development of bias mitigation in mERC and related emotion studies. | ['Dawei Song', 'Yazhou Zhang', 'Fang Ma', 'Jinglin Wang'] | 2022-07-17 | null | null | null | null | ['multimodal-emotion-recognition', 'multimodal-emotion-recognition'] | ['computer-vision', 'speech'] | [-1.36986107e-01 1.66016862e-01 -2.30798185e-01 -8.39404821e-01
-1.31313801e-01 -2.26395905e-01 6.70487940e-01 -1.01630658e-01
-2.48807669e-01 7.12400496e-01 8.46996725e-01 1.49281081e-02
3.27657044e-01 -6.64109230e-01 -3.13965142e-01 -7.50122666e-01
4.75459903e-01 1.02908360e-02 -5.12516499e-01 -6.76365077e-01
5.03214598e-01 2.90874362e-01 -1.53683245e+00 4.73910868e-01
7.83090830e-01 1.20364285e+00 -6.55405045e-01 2.75768816e-01
-5.39289534e-01 1.01472235e+00 -7.13369906e-01 -1.17886615e+00
-4.69686747e-01 -3.55559707e-01 -7.08346248e-01 -1.60579488e-01
1.56809717e-01 -2.90146291e-01 -4.87056188e-02 1.19002080e+00
8.23730350e-01 -1.63239524e-01 7.98567712e-01 -1.68417430e+00
-6.67005360e-01 6.89209282e-01 -8.36802542e-01 -9.85001773e-02
4.95567471e-01 -1.88684136e-01 6.65075004e-01 -1.15861857e+00
4.69476581e-01 1.96038306e+00 6.10802412e-01 8.43870878e-01
-7.77732074e-01 -1.06577396e+00 4.55624849e-01 1.01316430e-01
-1.23755062e+00 -5.35742402e-01 1.12965989e+00 -4.06928748e-01
3.09600174e-01 6.42637908e-01 4.84375685e-01 1.61736941e+00
1.42562479e-01 8.20192218e-01 1.48117900e+00 -2.84759820e-01
-6.30549267e-02 7.52911866e-01 2.31833026e-01 6.67137563e-01
-7.96438232e-02 -6.21814206e-02 -8.52056324e-01 -2.49637976e-01
2.03563243e-01 2.45568603e-02 -1.03558220e-01 4.66730297e-02
-1.05775452e+00 9.92655277e-01 4.30364102e-01 2.54978150e-01
-2.11578250e-01 -2.41111204e-01 7.53634512e-01 1.26129106e-01
7.87363291e-01 6.04799502e-02 -2.24423006e-01 -2.77312279e-01
-4.84280944e-01 7.42793754e-02 5.85408092e-01 7.10753381e-01
7.40192950e-01 4.12693284e-02 -2.59757578e-01 1.16109741e+00
3.57304633e-01 7.21225679e-01 4.03605342e-01 -4.73428071e-01
2.05015615e-01 8.55864644e-01 4.30026688e-02 -1.88467824e+00
-5.74748397e-01 2.53744479e-02 -1.10207367e+00 -1.76712528e-01
1.55593976e-01 -4.97284770e-01 -5.14820755e-01 2.06686997e+00
5.15055597e-01 -3.46578538e-01 1.66536659e-01 1.23704875e+00
1.32125890e+00 7.43387222e-01 4.46156621e-01 -2.77186334e-01
1.62865412e+00 -6.24260962e-01 -1.27087855e+00 -2.84484982e-01
5.34685552e-01 -8.77830625e-01 9.64764893e-01 2.71041334e-01
-6.99401736e-01 -2.10870087e-01 -5.67381859e-01 -4.18797880e-02
-7.38346875e-01 3.18541944e-01 9.13836241e-01 1.00845528e+00
-4.60084528e-01 -3.10238656e-02 -9.59150642e-02 -5.12781680e-01
3.25886726e-01 1.08337387e-01 -3.17007929e-01 1.23745129e-01
-1.55834293e+00 1.02775896e+00 -9.26729217e-02 4.66697961e-01
-4.28836256e-01 -4.13729340e-01 -8.40007067e-01 -3.78913850e-01
2.25461870e-01 -2.46434063e-01 8.44348550e-01 -1.72270691e+00
-1.36760283e+00 1.10169780e+00 -4.51959312e-01 8.42014402e-02
3.85256439e-01 -2.51419008e-01 -7.52673507e-01 -1.11292347e-01
-1.44005150e-01 7.56498694e-01 9.40774441e-01 -1.43740427e+00
-4.64727044e-01 -7.44279683e-01 1.49425074e-01 4.43156660e-01
-7.85333812e-01 6.01389945e-01 -1.00080214e-01 -6.08669460e-01
-9.52618867e-02 -7.38594413e-01 7.43131414e-02 -7.08810091e-02
-4.06208575e-01 -2.87040800e-01 8.02595735e-01 -9.02702212e-01
1.33522499e+00 -2.20741439e+00 2.79192477e-01 1.30647957e-01
-6.57221675e-02 3.75265107e-02 2.18223989e-01 3.57438415e-01
-9.56138875e-03 3.52276355e-01 1.92845106e-01 -1.84696391e-01
2.99083710e-01 9.32232887e-02 -3.81441474e-01 4.21105325e-01
2.28842244e-01 6.87688053e-01 -7.02779531e-01 -9.40064549e-01
1.27546325e-01 6.98414147e-01 -5.03267944e-01 3.24549317e-01
3.06442797e-01 4.48276818e-01 -3.44187170e-01 9.47214246e-01
8.89969528e-01 3.75577062e-01 9.99253839e-02 -6.89630568e-01
-2.43843511e-01 -2.35514212e-02 -8.49843621e-01 1.03771400e+00
-4.53939676e-01 4.89257336e-01 3.48957598e-01 -7.72093952e-01
1.30320072e+00 2.08011881e-01 1.89080462e-01 -7.26042747e-01
7.25808382e-01 1.14104807e-01 -2.04174668e-01 -8.04305613e-01
6.90727711e-01 -5.60813665e-01 -4.25630182e-01 2.49081641e-01
-3.62177163e-01 8.02777410e-02 -3.38746190e-01 2.78096795e-01
2.30656132e-01 -1.96786314e-01 1.39138736e-02 -2.38194153e-01
7.06512749e-01 -1.84262991e-01 7.14186072e-01 2.29678288e-01
-5.71454048e-01 1.52596369e-01 7.55140603e-01 -3.49793047e-01
-5.45509815e-01 -5.13214350e-01 -3.70581187e-02 1.45953882e+00
3.67464274e-01 -8.16414431e-02 -7.01871395e-01 -8.11224759e-01
-1.74441606e-01 6.63502097e-01 -7.66733289e-01 -4.49019909e-01
-1.04923673e-01 -1.00236595e+00 7.11955190e-01 3.71673822e-01
6.25180304e-01 -1.15387189e+00 -4.34660614e-01 -2.71837503e-01
-5.96165478e-01 -9.11053181e-01 -1.47338852e-01 -2.34083354e-01
-4.12287563e-01 -7.26558745e-01 -8.16503465e-01 -7.83679187e-01
9.34319198e-01 -1.48310317e-02 1.02112997e+00 8.97484571e-02
-9.77893695e-02 4.00759488e-01 -6.27400815e-01 -8.22333157e-01
-1.56078979e-01 -2.58184016e-01 1.01724736e-01 5.82985818e-01
7.70729661e-01 -8.87425840e-02 -7.19810247e-01 4.73385602e-01
-6.99864209e-01 1.17700011e-01 3.63361657e-01 8.52990270e-01
-1.39856175e-01 -2.63055801e-01 7.60600090e-01 -8.45254540e-01
8.35361421e-01 -5.91113806e-01 7.04253837e-02 1.98288128e-01
-3.31687063e-01 -4.86660510e-01 2.48777643e-01 -5.72872221e-01
-1.67299390e+00 -4.22551960e-01 -3.79388422e-01 -1.89353183e-01
-2.89937019e-01 5.60821593e-01 -3.29673380e-01 -8.09473544e-02
2.74476737e-01 -6.53786287e-02 3.32748033e-02 -7.73047581e-02
1.33566216e-01 1.26289606e+00 1.40946284e-01 -7.47808039e-01
2.29336351e-01 5.81021667e-01 -4.09012973e-01 -8.79722476e-01
-8.86439860e-01 -2.07949311e-01 -8.49603042e-02 -8.71186733e-01
8.61611366e-01 -9.75470245e-01 -9.33637917e-01 6.59775078e-01
-1.21568716e+00 2.22285613e-01 4.72200662e-01 3.74812961e-01
1.71949584e-02 3.00249487e-01 -6.08896494e-01 -1.42273486e+00
-4.61695969e-01 -9.39087093e-01 1.19938743e+00 4.65846956e-01
-6.21172309e-01 -7.38788664e-01 -1.84172288e-01 6.28323376e-01
3.76404971e-01 2.79277384e-01 1.08684874e+00 -4.72098023e-01
2.97794819e-01 4.16996889e-03 -4.91793543e-01 2.75721550e-01
-1.45884184e-02 2.02906221e-01 -1.07526052e+00 1.76573284e-02
-8.82964432e-02 -8.25972617e-01 4.31569487e-01 1.67844538e-02
1.14578021e+00 -4.53811765e-01 -1.45064250e-01 2.20610484e-01
1.06799674e+00 2.44683310e-01 8.42668474e-01 -4.74777917e-04
6.23259425e-01 1.32364202e+00 1.08525538e+00 7.99740434e-01
5.54580510e-01 3.83731633e-01 5.97437918e-01 -5.35368443e-01
3.69789451e-01 -2.43736759e-01 4.93022621e-01 8.63295674e-01
-9.70781669e-02 -3.34814712e-02 -7.02285886e-01 5.97576737e-01
-1.73283613e+00 -9.75319147e-01 -2.69101650e-01 1.66856408e+00
8.26134205e-01 -3.59495074e-01 -8.57440531e-02 1.16753682e-01
8.99673462e-01 4.03254002e-01 -3.92820269e-01 -1.09119332e+00
-3.47402692e-01 -2.19582513e-01 -6.24339059e-02 2.44391188e-01
-9.42889094e-01 9.49790120e-01 5.28461695e+00 6.77527785e-01
-1.39027536e+00 -5.25796227e-02 1.14683878e+00 1.19190052e-01
-4.93425339e-01 -2.67619044e-01 -6.69396818e-01 4.89843965e-01
4.80768502e-01 -2.05524433e-02 2.38633111e-01 8.52693319e-01
2.97679603e-01 -1.21362939e-01 -7.09966421e-01 1.28738868e+00
4.88083094e-01 -7.26542830e-01 5.00777923e-02 -1.74683616e-01
4.80950624e-01 -6.42756939e-01 1.85932189e-01 7.06491470e-01
-9.13014412e-02 -1.01931596e+00 7.52051532e-01 4.92379695e-01
5.98021150e-01 -9.94307220e-01 9.00296807e-01 2.18748525e-01
-5.54523468e-01 -8.15557837e-02 -3.86030048e-01 -1.37222901e-01
7.86589533e-02 5.57697356e-01 -3.78085464e-01 3.57243299e-01
9.53395307e-01 4.92635161e-01 -3.80357474e-01 2.74197429e-01
-7.25390576e-03 4.57644075e-01 7.10259452e-02 -5.77193260e-01
4.11564633e-02 -1.97174594e-01 3.88766140e-01 1.54153097e+00
2.54080027e-01 3.09721649e-01 -2.98784643e-01 6.13600910e-01
-1.34893492e-01 6.09372079e-01 -6.87072635e-01 -2.10219279e-01
2.77498066e-01 1.51975703e+00 -3.61475497e-01 -3.50027949e-01
-3.81080776e-01 8.72342706e-01 2.22306892e-01 3.63012016e-01
-1.04076493e+00 -2.60086089e-01 6.88815117e-01 -3.32063347e-01
-2.46482760e-01 4.21705753e-01 -3.48634511e-01 -1.25575960e+00
-2.88858652e-01 -1.24232817e+00 4.73626494e-01 -9.21975970e-01
-1.50486422e+00 3.99931908e-01 -1.78086087e-01 -8.19024026e-01
2.08322734e-01 -6.82533741e-01 -5.09148479e-01 6.54428780e-01
-1.39864230e+00 -1.19242072e+00 -3.85068685e-01 6.19691730e-01
2.82405436e-01 -1.19155087e-02 7.81004667e-01 4.51027274e-01
-9.24926937e-01 7.28964806e-01 -5.06171346e-01 2.77442396e-01
1.08410013e+00 -7.36052215e-01 -6.15189493e-01 3.61732543e-01
-4.94307011e-01 6.27076089e-01 9.07410026e-01 -5.13422549e-01
-1.46372604e+00 -7.59353936e-01 1.10950220e+00 -1.01364397e-01
4.94406730e-01 -4.27870750e-01 -6.05324984e-01 5.31556547e-01
5.39854825e-01 -5.08163989e-01 9.54450190e-01 5.85341990e-01
-4.19950843e-01 -1.25262678e-01 -1.42110956e+00 9.71443951e-01
8.17347109e-01 -3.22678298e-01 -5.32599688e-01 2.45735166e-03
2.78106362e-01 -3.19974869e-01 -7.87088633e-01 6.21543050e-01
7.75776505e-01 -1.24771738e+00 7.03656793e-01 -6.99261904e-01
8.24809134e-01 1.59980506e-01 -1.99279994e-01 -1.34906387e+00
1.45945266e-01 -2.65026420e-01 2.97911227e-01 1.90384746e+00
2.96400279e-01 -6.99857831e-01 6.12339437e-01 9.21862483e-01
1.76212534e-01 -7.77554333e-01 -7.16603339e-01 1.25668004e-01
2.22912766e-02 -3.57035160e-01 8.17619860e-01 1.32657039e+00
3.54951769e-01 4.34585392e-01 -9.09356534e-01 1.44419270e-02
1.94064632e-01 2.11580873e-01 9.45513368e-01 -9.92801368e-01
4.62322116e-01 -3.93337637e-01 -2.07021415e-01 -6.60530806e-01
3.79051000e-01 -4.55217004e-01 -1.33326650e-01 -1.14085972e+00
3.39373976e-01 -3.45668793e-01 -1.70654148e-01 3.39339495e-01
-1.44029543e-01 2.42397055e-01 4.12396155e-02 -3.52559447e-01
-4.92276490e-01 9.45117831e-01 1.18239868e+00 -2.50938088e-01
1.48862913e-01 -4.30748641e-01 -1.13839233e+00 1.02123940e+00
8.25037181e-01 -2.42679939e-01 -1.06786221e-01 -2.50794411e-01
6.29091263e-01 9.34928097e-03 3.87455046e-01 -2.30422527e-01
-1.03422433e-01 -4.12593603e-01 4.83470052e-01 -5.33594012e-01
6.35912001e-01 -8.53039443e-01 -2.15857536e-01 2.28800207e-01
-2.85326928e-01 2.13726573e-02 1.76170170e-01 1.79381996e-01
-5.24295986e-01 -1.73619520e-02 7.19936788e-01 -3.56071219e-02
-6.21441364e-01 -4.99217026e-02 -3.79107177e-01 4.47560214e-02
8.80335510e-01 -8.83380473e-02 -6.37284815e-01 -7.52838612e-01
-4.50474173e-01 4.01922077e-01 1.03426501e-01 7.75684416e-01
7.49267340e-01 -1.55050063e+00 -7.09826171e-01 -5.81672741e-03
2.86198795e-01 -6.17489457e-01 4.65108156e-01 1.17729700e+00
-1.12084514e-02 7.26872906e-02 -3.06249410e-01 -3.10684681e-01
-1.73836327e+00 2.36591920e-01 1.90893784e-01 1.26389414e-01
2.16311797e-01 9.55218554e-01 3.35112691e-01 -7.70620048e-01
4.52736259e-01 1.74835145e-01 -6.03847325e-01 6.46058857e-01
4.69911307e-01 4.40024048e-01 -2.39714086e-01 -1.35554826e+00
-5.99257648e-01 5.84761679e-01 -2.12187618e-02 -1.21876616e-02
9.38349009e-01 -3.57594192e-01 -4.67909783e-01 6.28621221e-01
1.14280355e+00 2.02382028e-01 -4.17508870e-01 1.16002351e-01
-2.96621561e-01 -6.26695454e-01 -9.80899930e-02 -1.08059633e+00
-1.09705377e+00 1.13212872e+00 6.18354380e-01 8.20355788e-02
1.14028025e+00 -7.19698519e-02 5.38621545e-01 2.72406321e-02
3.67021143e-01 -1.45772243e+00 6.62526265e-02 3.91429365e-01
1.16664577e+00 -1.47655547e+00 -1.67845339e-01 -5.61694264e-01
-1.25868678e+00 8.88432324e-01 9.42048073e-01 4.70397204e-01
4.88089412e-01 -3.69970575e-02 6.66645765e-01 -3.86942625e-01
-7.00817347e-01 -2.37514582e-02 1.40137851e-01 3.87030989e-01
8.31044137e-01 1.66926622e-01 -7.62790859e-01 8.90898705e-01
-1.96886629e-01 -2.45282069e-01 1.75334021e-01 7.39567816e-01
-1.48015678e-01 -7.41837919e-01 -8.21574450e-01 2.86583692e-01
-5.87983191e-01 9.97173339e-02 -9.57473338e-01 5.22097409e-01
3.54755014e-01 1.22954607e+00 -7.97839239e-02 -4.88619596e-01
4.01293486e-01 3.02419692e-01 9.87496674e-02 -6.35686740e-02
-8.15768778e-01 -8.39565843e-02 5.43730974e-01 -4.92933750e-01
-6.98781490e-01 -5.48679888e-01 -1.07457364e+00 -4.81946826e-01
-3.47732902e-01 8.58154893e-02 8.15176725e-01 7.73933530e-01
2.71541297e-01 2.30376139e-01 7.67831802e-01 -6.06056690e-01
-1.72981843e-01 -9.48283792e-01 -3.22492331e-01 8.55517387e-01
8.68752673e-02 -7.94174612e-01 -5.76547384e-01 -3.08939576e-01] | [13.091179847717285, 5.301527500152588] |
054844f3-ce01-45ab-9422-d92d442477a6 | internet-of-things-fault-detection-and | 2307.01234 | null | https://arxiv.org/abs/2307.01234v1 | https://arxiv.org/pdf/2307.01234v1.pdf | Internet of Things Fault Detection and Classification via Multitask Learning | This paper presents a comprehensive investigation into developing a fault detection and classification system for real-world IIoT applications. The study addresses challenges in data collection, annotation, algorithm development, and deployment. Using a real-world IIoT system, three phases of data collection simulate 11 predefined fault categories. We propose SMTCNN for fault detection and category classification in IIoT, evaluating its performance on real-world data. SMTCNN achieves superior specificity (3.5%) and shows significant improvements in precision, recall, and F1 measures compared to existing techniques. | ['Mohammad Arif Ul Alam'] | 2023-07-03 | null | null | null | null | ['classification-1', 'fault-detection', 'specificity'] | ['methodology', 'miscellaneous', 'natural-language-processing'] | [-9.22233537e-02 -2.74659663e-01 -2.43286774e-01 -2.19218820e-01
-2.34307185e-01 -2.92325795e-01 1.04985945e-03 2.03775272e-01
3.83839123e-02 6.24562442e-01 -4.31479037e-01 -5.59103072e-01
-2.21809939e-01 -6.79500103e-01 1.28014326e-01 -2.99868882e-01
-1.93260834e-01 8.69317591e-01 6.85185611e-01 1.87195554e-01
3.75735104e-01 4.18256193e-01 -1.93352318e+00 4.85611409e-01
5.19011855e-01 1.50930035e+00 3.02565042e-02 7.90391207e-01
-4.36556228e-02 1.21700633e+00 -1.76709545e+00 8.79579782e-02
1.20670922e-01 -2.79916599e-02 -1.07813132e+00 2.50824094e-01
2.07860962e-01 -6.30265698e-02 -4.81446385e-01 6.48328960e-01
5.53290725e-01 -3.78596604e-01 3.09749722e-01 -1.98815489e+00
-2.72139132e-01 7.23912179e-01 2.14931980e-01 5.21740377e-01
2.88586050e-01 -6.16282644e-03 7.57092297e-01 -7.63509810e-01
4.62875098e-01 4.67898011e-01 9.97590721e-01 4.18967545e-01
-6.30297184e-01 -4.09396738e-01 -5.67795336e-01 3.57031763e-01
-1.72046781e+00 -8.18169564e-02 1.07892960e-01 -3.19926679e-01
1.50082302e+00 7.22635210e-01 6.02740526e-01 2.90469766e-01
6.69831932e-01 7.76550651e-01 7.01106012e-01 -3.48697156e-01
5.32429576e-01 -3.33205372e-01 5.54351270e-01 6.66393340e-01
4.46222931e-01 -3.71073872e-01 -4.99577850e-01 -2.88136065e-01
5.55164933e-01 2.71852672e-01 -2.30557378e-02 1.33641005e-01
-8.04277360e-01 3.61187100e-01 -2.16868520e-03 5.20708025e-01
-1.63766190e-01 3.25219363e-01 1.07556736e+00 5.55476069e-01
5.65655231e-01 6.32258475e-01 -1.01884758e+00 -5.58794618e-01
-7.13805139e-01 -1.12585835e-01 7.86562145e-01 1.50173199e+00
1.28949046e-01 4.40503746e-01 -4.36528891e-01 1.12184942e+00
-8.79884288e-02 3.45764041e-01 6.02260590e-01 -8.44169855e-01
1.55339077e-01 9.42196131e-01 -3.13308164e-02 -5.12675703e-01
-4.69713032e-01 -6.63557351e-01 -5.01925528e-01 -3.28580409e-01
-2.16227353e-01 -8.85740593e-02 -1.43014383e+00 7.23691046e-01
-5.71475923e-02 -1.06056981e-01 6.83403313e-02 4.40024465e-01
8.75684261e-01 2.84600854e-01 -2.78549194e-01 -2.68149406e-01
1.34776783e+00 -8.79421830e-01 -9.54698265e-01 -3.79483737e-02
1.00268865e+00 -8.25762987e-01 7.27631152e-01 6.65018976e-01
-7.65161276e-01 -2.94642508e-01 -8.34718943e-01 3.38516831e-01
-3.43385875e-01 3.91464233e-01 6.79941416e-01 8.59615505e-01
-1.06227541e+00 1.60992205e-01 -6.23120248e-01 -7.27028072e-01
5.71215570e-01 5.93092024e-01 -1.35596812e-01 -4.24375623e-01
-8.56422484e-01 5.34940064e-01 4.00365055e-01 -1.57178238e-01
-1.02007258e+00 -4.46301699e-01 -2.90553719e-01 -5.42696603e-02
6.79555953e-01 -5.62519312e-01 1.65331495e+00 -2.47553289e-01
-8.73232841e-01 2.43219271e-01 1.69163477e-02 -5.99605083e-01
6.32169172e-02 -1.91090450e-01 -8.42543602e-01 3.34147841e-01
3.82385373e-01 1.65962800e-02 3.43642294e-01 -8.53767931e-01
-9.67766404e-01 8.58318284e-02 6.42485800e-04 -4.22285907e-02
-4.18112040e-01 2.50306845e-01 -4.48824227e-01 -5.97462714e-01
3.70684713e-01 -6.00133538e-01 2.36940483e-04 -2.35743642e-01
-4.47716624e-01 -6.29039705e-01 1.36412859e+00 -2.53308773e-01
1.50813818e+00 -1.71932960e+00 -7.76442707e-01 1.47838071e-01
5.12067139e-01 5.39063811e-01 3.33085716e-01 8.05559516e-01
-1.87195428e-02 1.12205625e-01 2.12160703e-02 1.87600777e-01
-1.84564352e-01 4.89163697e-01 3.10729053e-02 8.65570009e-02
-7.62197077e-02 6.86567068e-01 -9.00752127e-01 -3.96734953e-01
2.33179927e-01 -3.43424141e-01 -2.71576673e-01 3.56889933e-01
-2.04662964e-01 -2.88608432e-01 -2.20092908e-01 1.31207824e+00
3.38802934e-01 -2.13054135e-01 2.50348687e-01 -2.17257589e-01
-9.57187638e-03 4.03225601e-01 -7.50214577e-01 8.96587312e-01
-3.50216717e-01 8.46810699e-01 -6.23352051e-01 -1.04141307e+00
1.12307084e+00 7.80248940e-01 8.48811746e-01 -4.39221799e-01
3.36711884e-01 1.86963052e-01 1.00836419e-01 -8.25364232e-01
3.93919647e-01 3.46823901e-01 -2.81691700e-01 5.49300432e-01
2.47484267e-01 -2.99698591e-01 5.04706681e-01 1.57112882e-01
2.06817317e+00 -8.48420501e-01 1.30427063e-01 -4.09839660e-01
-3.14870290e-02 3.65968466e-01 6.08721256e-01 9.20879006e-01
-3.96659493e-01 6.45959496e-01 4.56207335e-01 -8.10259819e-01
-9.15239394e-01 -6.82362258e-01 -8.61941501e-02 5.30536294e-01
-1.19943954e-01 -7.82722354e-01 -8.83184850e-01 -1.08095944e+00
3.72802131e-02 3.75760674e-01 -4.22801465e-01 -4.02981013e-01
-1.63026169e-01 -7.99863875e-01 1.04077065e+00 7.12988496e-01
7.78228343e-01 -1.02108347e+00 -8.42366219e-01 1.31659493e-01
-2.06033856e-01 -1.00333357e+00 -2.95108467e-01 7.12728322e-01
-6.83240235e-01 -1.46679366e+00 1.45354524e-01 -8.35455716e-01
6.90967679e-01 3.04435194e-01 1.33090436e+00 6.18956447e-01
-8.54676366e-01 2.43793771e-01 -6.36071205e-01 -4.26323265e-01
2.46242490e-02 8.00059661e-02 2.21475363e-01 -6.41104519e-01
4.30071384e-01 8.50008950e-02 -1.65276513e-01 7.68872738e-01
-8.65505278e-01 -5.30537546e-01 4.24668074e-01 1.03832495e+00
1.55217126e-01 8.67778599e-01 7.42772162e-01 -9.88311887e-01
6.16266131e-01 -5.43179870e-01 -3.78705204e-01 4.58012283e-01
-1.19623923e+00 -6.01751983e-01 3.91086131e-01 -2.18552306e-01
-7.02792943e-01 -2.40901932e-01 -2.52871156e-01 -2.88206011e-01
-1.95590854e-01 6.62576854e-01 -7.84137547e-02 -2.67880410e-02
7.04843760e-01 7.43053705e-02 -3.50437164e-01 -2.61024505e-01
-2.04315349e-01 1.34413445e+00 4.03551072e-01 -4.62347537e-01
1.44066185e-01 3.34970988e-02 -3.85190070e-01 -6.98580801e-01
-7.03271806e-01 -6.88053668e-01 -5.30775905e-01 -2.35183418e-01
2.24032804e-01 -4.73472238e-01 -7.65606999e-01 9.50522125e-01
-7.45356083e-01 -3.25965822e-01 -4.19588089e-01 4.82858866e-02
-2.18919054e-01 9.65586901e-02 -8.73387635e-01 -6.54318511e-01
-7.29106545e-01 -8.88114333e-01 9.12234247e-01 -2.37357050e-01
-2.06647694e-01 -7.37493157e-01 -3.33220303e-01 2.05153778e-01
3.19129020e-01 -3.93624008e-01 6.93674505e-01 -9.38336134e-01
-2.66410291e-01 -5.72186947e-01 -3.07776839e-01 4.04848814e-01
3.94579113e-01 2.99221516e-01 -6.34130359e-01 -2.40626246e-01
3.45776714e-02 -2.24979371e-01 2.18865141e-01 5.45062684e-02
1.57007849e+00 -3.27745348e-01 -5.15989959e-01 9.04983729e-02
1.23004115e+00 8.19368005e-01 4.88606095e-01 1.60447776e-01
7.33474016e-01 8.19440186e-02 1.24310434e+00 5.84229589e-01
1.76062450e-01 4.67965603e-01 3.57685417e-01 2.29640096e-01
-2.53844410e-01 3.93863171e-01 -7.35832453e-02 1.17134511e+00
5.05794227e-01 -8.48575115e-01 -1.61705637e+00 8.14167619e-01
-1.77884746e+00 -6.00050807e-01 -6.55870020e-01 1.53483105e+00
5.05691648e-01 3.27899456e-01 1.44610018e-01 9.02256191e-01
6.91674709e-01 -7.39372671e-01 -3.96524787e-01 -2.77929246e-01
2.21985579e-02 2.75557548e-01 6.69222534e-01 -2.89631635e-01
-1.01957548e+00 6.87625647e-01 8.45099640e+00 7.48742461e-01
-1.08636212e+00 2.97053277e-01 3.84735644e-01 1.00856096e-01
2.14416355e-01 -2.65582263e-01 -4.36104149e-01 5.27164102e-01
1.17610955e+00 -1.52438730e-01 -1.29317775e-01 8.50436687e-01
-1.47306502e-01 -1.84548020e-01 -9.54490662e-01 7.61107624e-01
2.14939445e-01 -1.32010257e+00 -2.59546757e-01 -2.47241840e-01
7.60400593e-01 2.63912082e-01 -3.04754287e-01 1.04775116e-01
5.43282330e-01 -6.65072143e-01 8.57930958e-01 2.22146749e-01
9.66208100e-01 -8.45880985e-01 1.68287373e+00 -1.69910192e-01
-1.11051965e+00 -7.05564678e-01 -2.56488323e-01 -1.86527222e-01
-1.30797356e-01 1.06893897e+00 -1.38003671e+00 8.08676958e-01
1.13280606e+00 6.11954212e-01 -6.69468403e-01 1.33262420e+00
-1.54612334e-02 8.11182082e-01 -2.11804524e-01 -4.45354097e-02
-2.46065035e-01 7.76624441e-01 -1.35163173e-01 1.03475308e+00
3.88797194e-01 -4.54232953e-02 6.58205390e-01 -8.00687969e-02
-7.00942278e-02 -2.94848591e-01 -4.77916449e-01 -7.45658129e-02
1.10181272e+00 1.05738461e+00 -1.17077863e+00 -7.59089470e-01
-4.40298855e-01 5.94128251e-01 -2.19675198e-01 2.33827382e-02
-6.93057120e-01 -7.33567774e-01 5.62035084e-01 -1.32762283e-01
2.04170331e-01 1.21833105e-02 -7.07504690e-01 -7.78062403e-01
-2.94128675e-02 -8.32527697e-01 6.60367131e-01 -8.56626987e-01
-1.27666032e+00 8.83476079e-01 1.38408706e-01 -1.35178924e+00
4.75016609e-03 -5.74925065e-01 -4.41873312e-01 2.49403298e-01
-3.68398696e-01 -1.03588951e+00 -4.10968125e-01 2.88017184e-01
7.52867341e-01 -3.60984206e-01 6.68641031e-01 6.77017987e-01
-1.01961291e+00 6.74289644e-01 -6.06054105e-02 8.17284510e-02
5.92574418e-01 -1.26846540e+00 7.67875493e-01 9.01541471e-01
-2.11417377e-01 4.53541845e-01 5.23752868e-01 -1.08864558e+00
-1.38567662e+00 -1.58531773e+00 7.89878190e-01 -5.24414003e-01
6.16241097e-01 -2.84611076e-01 -4.98169839e-01 7.11396456e-01
-1.06846862e-01 4.21009719e-01 5.16803563e-01 -2.66962964e-02
-1.17969729e-01 -2.22883329e-01 -1.55932522e+00 -2.31953934e-02
1.15865147e+00 -7.55746961e-01 -1.16343714e-01 4.80328768e-01
5.75717747e-01 -2.21941784e-01 -1.43187380e+00 5.54485559e-01
3.35334122e-01 -5.09551704e-01 5.63445091e-01 -2.70115823e-01
-6.13227151e-02 -6.05693400e-01 -1.38268664e-01 -1.18860531e+00
-1.33348301e-01 -1.86011538e-01 -1.64747491e-01 1.15290141e+00
1.68611169e-01 -6.77070200e-01 6.75511062e-01 2.05866054e-01
-8.46216440e-01 -8.69213045e-01 -8.10723543e-01 -9.41474497e-01
-7.01303303e-01 -7.31551170e-01 7.80229688e-01 9.91308391e-01
4.03922170e-01 7.35517815e-02 -2.50663370e-01 1.59916356e-01
4.44175117e-02 -1.83064476e-01 5.70056379e-01 -1.34388494e+00
1.52814910e-01 1.33792832e-01 -8.70941699e-01 -4.75700855e-01
-4.46372241e-01 -6.18376076e-01 4.92695719e-01 -1.61763394e+00
1.54039776e-02 -7.78862596e-01 -3.21986616e-01 1.07908177e+00
1.34969980e-01 6.85209692e-01 -2.33000502e-01 4.72756296e-01
-8.84663522e-01 -6.69300649e-03 4.67730433e-01 -1.10980839e-01
3.60708684e-01 -6.29542321e-02 -8.13907832e-02 3.81823868e-01
1.10229254e+00 -6.07334077e-01 -6.34910464e-01 -4.74055976e-01
-2.34439656e-01 7.05757290e-02 -1.24526653e-03 -1.43098736e+00
4.93588418e-01 -1.40379369e-01 1.68331817e-01 -9.13314819e-01
-2.03394264e-01 -8.50813031e-01 4.29698884e-01 9.07874942e-01
1.40811756e-01 4.91599709e-01 7.68979415e-02 -1.56488404e-01
-1.58234820e-01 -5.10847270e-01 3.04132015e-01 -3.47156301e-02
-9.74581420e-01 1.61831632e-01 -1.15548348e+00 -2.45929524e-01
1.09713221e+00 2.69163456e-02 -9.94238198e-01 9.05170962e-02
-4.76277262e-01 6.71638474e-02 5.61826229e-01 4.47254419e-01
8.58658195e-01 -1.13778770e+00 -1.02135994e-01 3.32067609e-01
6.94591939e-01 -2.01431215e-01 -2.97136486e-01 5.14983416e-01
-7.46953309e-01 5.95328510e-01 -2.94349402e-01 -7.63774872e-01
-1.44344473e+00 5.34366786e-01 4.81150001e-01 7.82031417e-02
-3.61187100e-01 6.38851821e-01 -4.93181288e-01 -5.42881906e-01
2.46185437e-01 -4.66713428e-01 9.67249721e-02 -2.89791048e-01
2.14786723e-01 7.29589045e-01 8.37618291e-01 -9.90060344e-02
-5.99645495e-01 -3.31127131e-03 1.44881099e-01 4.33285415e-01
9.79435980e-01 4.63801110e-03 -4.02099550e-01 6.67193651e-01
6.15788698e-01 -6.15449965e-01 -4.17917699e-01 2.42529273e-01
5.23128390e-01 -4.57137853e-01 -9.51090455e-02 -1.31182122e+00
-1.25844562e+00 3.38444680e-01 8.44337344e-01 8.57586980e-01
1.29328406e+00 1.07156418e-01 8.66653681e-01 6.09783351e-01
6.62468612e-01 -1.17238772e+00 1.89746633e-01 7.50364780e-01
3.49446863e-01 -7.00720072e-01 -1.41581595e-01 -8.60706270e-01
-1.47073582e-01 9.34116781e-01 1.09738350e+00 1.09729797e-01
6.77096426e-01 7.21297681e-01 3.42415601e-01 -7.29721069e-01
-1.28230870e+00 -1.10817954e-01 -1.13488950e-01 7.22935438e-01
4.16081041e-01 1.94508106e-01 -3.74127716e-01 2.52133518e-01
1.47030372e-02 2.13622063e-01 7.08217025e-01 1.63032496e+00
-5.99422038e-01 -1.18603420e+00 -3.42050463e-01 1.22977436e+00
-6.50842488e-01 1.29999444e-01 -5.00816107e-01 6.57451034e-01
4.40493286e-01 1.37107766e+00 3.57380509e-01 -9.14213002e-01
5.09908974e-01 -5.15122386e-03 1.12439893e-01 -9.85240459e-01
-7.43636191e-01 -1.95844814e-01 6.43242121e-01 -4.59181011e-01
-6.19286336e-02 -5.08431911e-01 -1.32022989e+00 -1.86241388e-01
-6.47665620e-01 6.41418695e-01 6.18030906e-01 1.05692172e+00
5.53461194e-01 1.19041812e+00 7.81213462e-01 9.56964493e-03
6.36536777e-02 -1.35161030e+00 -5.47549605e-01 -2.13563573e-02
-2.37379149e-02 -7.12045908e-01 1.29172839e-02 6.59645125e-02] | [7.002501964569092, 2.4330663681030273] |
36841194-a826-40c4-874a-1c7eceae6fa4 | zero-shot-next-item-recommendation-using | 2304.03153 | null | https://arxiv.org/abs/2304.03153v1 | https://arxiv.org/pdf/2304.03153v1.pdf | Zero-Shot Next-Item Recommendation using Large Pretrained Language Models | Large language models (LLMs) have achieved impressive zero-shot performance in various natural language processing (NLP) tasks, demonstrating their capabilities for inference without training examples. Despite their success, no research has yet explored the potential of LLMs to perform next-item recommendations in the zero-shot setting. We have identified two major challenges that must be addressed to enable LLMs to act effectively as recommenders. First, the recommendation space can be extremely large for LLMs, and LLMs do not know about the target user's past interacted items and preferences. To address this gap, we propose a prompting strategy called Zero-Shot Next-Item Recommendation (NIR) prompting that directs LLMs to make next-item recommendations. Specifically, the NIR-based strategy involves using an external module to generate candidate items based on user-filtering or item-filtering. Our strategy incorporates a 3-step prompting that guides GPT-3 to carry subtasks that capture the user's preferences, select representative previously watched movies, and recommend a ranked list of 10 movies. We evaluate the proposed approach using GPT-3 on MovieLens 100K dataset and show that it achieves strong zero-shot performance, even outperforming some strong sequential recommendation models trained on the entire training dataset. These promising results highlight the ample research opportunities to use LLMs as recommenders. The code can be found at https://github.com/AGI-Edgerunners/LLM-Next-Item-Rec. | ['Ee-Peng Lim', 'Lei Wang'] | 2023-04-06 | null | null | null | null | ['sequential-recommendation'] | ['miscellaneous'] | [ 1.60946220e-01 -1.94159389e-01 -7.11860657e-01 -5.74067235e-01
-7.38300264e-01 -4.68920201e-01 5.63796043e-01 -8.20481032e-02
-3.77986223e-01 3.54685247e-01 5.00228405e-01 -4.56672013e-01
-3.55542004e-01 -7.92258680e-01 -5.42331874e-01 -2.17967734e-01
4.85948287e-02 4.21535641e-01 2.07565263e-01 -4.74876136e-01
5.92556477e-01 9.27200094e-02 -1.71248257e+00 8.06435823e-01
8.52639854e-01 7.84302711e-01 5.82741261e-01 7.35187173e-01
-2.19730631e-01 6.58194959e-01 -1.95926979e-01 -4.19678271e-01
3.92688334e-01 -2.04740196e-01 -5.31732619e-01 -2.48521730e-01
4.23200101e-01 -5.57582080e-01 -2.50836492e-01 7.44308352e-01
3.93627167e-01 1.09861529e+00 5.69553971e-01 -9.26574826e-01
-1.09208632e+00 9.80492473e-01 3.09017650e-03 3.89518112e-01
7.08178163e-01 1.03217192e-01 1.49782002e+00 -1.32374990e+00
4.90895212e-01 1.23995614e+00 2.34452322e-01 7.22300589e-01
-9.45651233e-01 -4.91348475e-01 4.85179484e-01 9.17475820e-02
-1.12730837e+00 -4.90664035e-01 3.32129866e-01 -3.63967419e-01
1.05131316e+00 5.72417915e-01 3.23311210e-01 1.27609384e+00
6.13874942e-02 1.01183307e+00 7.14344501e-01 -3.26406062e-01
3.15047830e-01 3.90631437e-01 6.95459247e-01 3.58697116e-01
-1.07172973e-01 5.80868386e-02 -6.06885314e-01 -3.88587713e-01
5.87783873e-01 5.33176064e-01 -1.73362449e-01 3.00858021e-01
-1.02169120e+00 9.52417970e-01 8.08459371e-02 2.30926469e-01
-5.59027493e-01 -2.30289072e-01 -1.67426784e-02 4.66899216e-01
6.38776064e-01 8.97189915e-01 -6.17649555e-01 -7.48819411e-02
-9.07637239e-01 3.73035699e-01 8.32168460e-01 9.94946241e-01
4.71388549e-01 -3.06816608e-01 -8.47636402e-01 1.15526700e+00
2.86208957e-01 3.73510480e-01 5.96895397e-01 -7.91373491e-01
3.98416311e-01 2.05120832e-01 4.96479988e-01 -1.01033580e+00
-2.04079628e-01 -4.10675526e-01 -4.05772030e-01 -3.54994088e-01
1.09778598e-01 -2.47160092e-01 -6.64251029e-01 1.48983741e+00
1.85490862e-01 4.79439735e-01 -6.95149004e-02 1.18247294e+00
1.01991630e+00 1.05545533e+00 2.43223131e-01 -4.05071139e-01
1.29194868e+00 -1.13763523e+00 -3.61004025e-01 -3.15994322e-01
4.70964640e-01 -6.94665730e-01 1.63916516e+00 6.30563021e-01
-9.68661487e-01 -8.05670261e-01 -6.56393588e-01 1.63263127e-01
-2.45728001e-01 3.02802563e-01 8.61288011e-01 3.02870780e-01
-6.62325919e-01 9.12705600e-01 -4.40585703e-01 -5.06773531e-01
1.67698249e-01 3.63630682e-01 1.42907515e-01 -1.90444052e-01
-1.45707464e+00 5.25237918e-01 9.37228575e-02 -2.79940039e-01
-7.20255494e-01 -8.63572776e-01 -3.23439091e-01 3.10378611e-01
7.06201017e-01 -6.60397768e-01 1.51650822e+00 -8.19130182e-01
-1.75987554e+00 1.01680353e-01 -2.23798603e-01 -4.09430683e-01
-5.63573018e-02 -5.87472975e-01 -7.84661889e-01 -1.69893056e-01
-1.08976603e-01 3.61332744e-01 8.27078402e-01 -7.65552580e-01
-9.94603097e-01 -1.85626727e-02 3.58975291e-01 3.99932683e-01
-6.83573425e-01 2.95321941e-01 -7.79533744e-01 -7.98929214e-01
-2.43265107e-01 -9.66025591e-01 -5.36209762e-01 -6.18790388e-01
-1.39504090e-01 -6.00861847e-01 5.40723540e-02 -2.64729351e-01
1.80381536e+00 -1.93598723e+00 -2.18384743e-01 1.87479153e-01
-1.75276726e-01 6.31926894e-01 -6.19796455e-01 6.92521095e-01
3.53360474e-01 2.99216267e-02 6.53205812e-01 -3.83376986e-01
8.47666636e-02 3.91816050e-02 -6.63429797e-01 -1.17159486e-01
-3.01997155e-01 9.83740985e-01 -1.06935465e+00 6.61962181e-02
2.20116571e-01 2.21591368e-01 -8.05769145e-01 5.16485989e-01
-4.88116294e-01 1.81679785e-01 -6.51774704e-01 3.47175717e-01
2.89470345e-01 -4.08434063e-01 7.84918070e-02 -1.60577640e-01
-9.11314711e-02 7.11574495e-01 -1.29150879e+00 1.47481716e+00
-3.68526995e-01 -8.36211070e-02 -3.86489242e-01 -5.09273052e-01
8.18568468e-01 2.14509234e-01 2.76155978e-01 -7.14324832e-01
4.18903455e-02 -1.26798689e-01 -1.57583117e-01 -6.44005239e-01
8.52582753e-01 1.36176750e-01 -6.45989925e-02 7.72468388e-01
1.18267268e-01 5.87421775e-01 4.05723393e-01 6.08744502e-01
1.01716053e+00 -8.61701518e-02 2.92909920e-01 -1.15429357e-01
4.49059576e-01 -1.08779758e-01 5.93302011e-01 1.31353581e+00
3.26326340e-01 4.73264039e-01 -1.53468147e-01 -3.44801903e-01
-4.86470997e-01 -7.99094617e-01 2.57578582e-01 2.09239626e+00
-3.18028331e-02 -7.96150029e-01 -2.24971220e-01 -8.06825221e-01
-3.13768163e-02 1.29052508e+00 -5.31771839e-01 -1.52862847e-01
-2.25768209e-01 -6.05926216e-01 -5.08965254e-02 3.62182111e-01
-2.90043086e-01 -1.14673734e+00 -2.05554754e-01 3.25508624e-01
-1.91822439e-01 -7.18419969e-01 -1.03857446e+00 -1.47249103e-01
-7.51033187e-01 -7.69892395e-01 -4.62206930e-01 -4.32504535e-01
7.06883788e-01 7.18755960e-01 1.11652827e+00 1.88656032e-01
3.14609587e-01 4.10819232e-01 -8.29801619e-01 -1.47930592e-01
-2.20888048e-01 -3.74362711e-03 6.07621551e-01 9.20066610e-02
5.75049698e-01 -5.82332969e-01 -8.38369370e-01 5.76327622e-01
-5.87999165e-01 1.08818740e-01 5.53745747e-01 6.09803796e-01
6.07931554e-01 -1.48860276e-01 8.81400824e-01 -1.44280815e+00
1.11437237e+00 -9.07397628e-01 -3.38857859e-01 4.38736886e-01
-9.35190558e-01 -1.33988798e-01 1.12030184e+00 -8.52531195e-01
-1.11861432e+00 -2.12300420e-01 -5.16927123e-01 -2.38353714e-01
-2.70580769e-01 6.58128917e-01 1.22651055e-01 2.05123067e-01
8.12554181e-01 1.33498758e-01 -5.59126675e-01 -8.66658568e-01
6.47634506e-01 9.32608962e-01 2.55977869e-01 -5.60357451e-01
4.71635818e-01 4.01685610e-02 -7.12228239e-01 -4.83046561e-01
-1.45273793e+00 -9.40373778e-01 -2.13618919e-01 -1.95591718e-01
2.74318427e-01 -8.31795752e-01 -5.81181586e-01 -2.46335924e-01
-6.68081522e-01 -2.90602744e-01 -2.19033077e-01 6.60897911e-01
-2.04270288e-01 2.90508986e-01 -8.44769835e-01 -8.51305425e-01
-1.01261735e+00 -7.67232299e-01 5.20438135e-01 4.49523032e-01
-4.46155131e-01 -8.51921141e-01 7.32797831e-02 4.36995149e-01
4.52457935e-01 -8.44848216e-01 6.53153181e-01 -1.23458505e+00
-2.85919428e-01 -2.46297136e-01 1.56736851e-01 1.84266925e-01
5.57122566e-03 -2.53920108e-01 -6.01009607e-01 -3.80187839e-01
-2.77486533e-01 -6.27201274e-02 6.53566897e-01 4.10813421e-01
1.07457125e+00 -6.62131965e-01 -2.86289364e-01 3.96262795e-01
1.19477415e+00 2.21870601e-01 2.42441520e-01 -4.67621088e-02
4.29295331e-01 2.67413110e-01 1.27903628e+00 7.56340683e-01
3.24113399e-01 6.90299511e-01 2.33822353e-02 3.80197972e-01
6.30591530e-03 -6.65972412e-01 6.16987348e-01 1.00123012e+00
-2.37633437e-01 -5.83840251e-01 -2.95870632e-01 2.84496486e-01
-2.08942008e+00 -1.09452438e+00 -1.05786145e-01 2.43713379e+00
5.48480868e-01 1.63368776e-01 1.59371197e-01 -4.92538303e-01
3.58444244e-01 -8.09720531e-02 -6.03248239e-01 -4.29555804e-01
2.37879276e-01 7.10650906e-02 2.26143152e-01 4.96194124e-01
-9.07231390e-01 1.17952001e+00 5.94058084e+00 9.95834768e-01
-8.43686819e-01 1.24232791e-01 4.92267340e-01 -5.37585437e-01
-5.20539880e-01 5.16524613e-02 -1.34501982e+00 6.78223312e-01
1.12048769e+00 -3.80107194e-01 7.90952861e-01 9.31229293e-01
6.11324430e-01 9.12104696e-02 -9.84951973e-01 7.51281798e-01
2.30722979e-01 -1.41760933e+00 3.76897275e-01 -5.89136705e-02
8.62018943e-01 2.27604270e-01 1.12832315e-01 8.67235005e-01
5.44583261e-01 -6.70839071e-01 3.37044239e-01 8.53910863e-01
5.15673578e-01 -6.24255478e-01 3.91595542e-01 9.49430883e-01
-9.79780495e-01 -5.18720984e-01 -8.83474052e-01 -2.70540327e-01
3.43521863e-01 5.50140500e-01 -8.94617021e-01 3.60309899e-01
5.42758346e-01 7.49987245e-01 -3.55314702e-01 1.08635008e+00
-2.85667241e-01 9.77699876e-01 -1.09870493e-01 -2.55476415e-01
1.62811235e-01 -3.54032129e-01 5.76726258e-01 1.27940714e+00
7.13414788e-01 6.93800092e-01 4.51272517e-01 5.12709916e-01
-1.15983844e-01 6.13567054e-01 -1.88323170e-01 -1.53657779e-01
7.13528693e-01 1.58442724e+00 -4.39664602e-01 -5.80390215e-01
-7.21719921e-01 8.74920130e-01 3.85503054e-01 4.22437757e-01
-7.40062833e-01 -2.03730166e-02 7.70250499e-01 3.93635005e-01
3.70781928e-01 8.26058537e-02 1.49660870e-01 -1.40989602e+00
-5.31776607e-01 -1.06428885e+00 6.86196148e-01 -8.12129676e-01
-1.64976501e+00 5.43546140e-01 -1.34745091e-01 -1.21654809e+00
-2.44228646e-01 -3.81875426e-01 -9.06570852e-01 6.77607954e-01
-1.05558515e+00 -8.38670731e-01 1.70653120e-01 6.91420615e-01
1.12590313e+00 -2.68774241e-01 8.72253895e-01 4.10402894e-01
-5.30816257e-01 7.43059695e-01 1.46360397e-01 -3.12384993e-01
9.22128379e-01 -9.25641894e-01 4.67273623e-01 8.98187280e-01
5.49218655e-01 1.21903777e+00 7.35839784e-01 -7.14150310e-01
-1.68405557e+00 -1.19044065e+00 9.23704565e-01 -6.04880929e-01
5.14895022e-01 -2.70060688e-01 -8.20751846e-01 6.89002335e-01
-9.60561037e-02 -1.73000723e-01 1.07243836e+00 6.10994101e-01
-1.33469701e-01 3.40202078e-02 -7.24317849e-01 7.42042661e-01
1.19016898e+00 -1.90451249e-01 -7.76298821e-01 5.37994742e-01
8.35939169e-01 -8.80121440e-02 -8.32179427e-01 1.96451336e-01
6.72824383e-01 -6.15007877e-01 1.10523486e+00 -1.05969155e+00
3.15580130e-01 -1.23054311e-01 -2.01571599e-01 -1.39032781e+00
-1.03192222e+00 -7.80731320e-01 -6.20705962e-01 1.25985646e+00
6.85124516e-01 -2.88259119e-01 7.14255631e-01 9.50570524e-01
-1.63887411e-01 -9.01837826e-01 -1.10260881e-01 -5.42488515e-01
-3.35232496e-01 -7.10932195e-01 5.58916569e-01 7.03238904e-01
2.56997675e-01 7.62768209e-01 -1.06402433e+00 1.50988162e-01
2.26779133e-01 5.29698908e-01 7.49264300e-01 -1.29796875e+00
-8.18950772e-01 -2.47119725e-01 5.76848745e-01 -1.74049759e+00
-1.38869703e-01 -1.08505380e+00 -4.06951830e-02 -1.62085962e+00
2.95192301e-01 -4.44626302e-01 -8.71861279e-01 4.48773652e-01
-4.28555995e-01 9.90456566e-02 2.66675323e-01 3.34243834e-01
-1.23833179e+00 2.45783329e-01 1.24091160e+00 2.80127376e-01
-5.35750926e-01 7.41220534e-01 -1.14407873e+00 6.13220632e-01
6.79706216e-01 -5.68107367e-01 -7.16693401e-01 -2.20704615e-01
5.75672746e-01 1.17042772e-01 -3.20917785e-01 -6.68924391e-01
5.47381461e-01 -6.12163901e-01 1.30390182e-01 -6.03813171e-01
3.67423296e-01 -4.29727137e-01 1.06286779e-01 -8.53013918e-02
-7.76888192e-01 -2.13370666e-01 -2.60647595e-01 6.07111990e-01
2.97554910e-01 -3.83438021e-01 2.56204665e-01 -3.27978104e-01
-1.00361288e+00 7.71475732e-01 -6.11670971e-01 -1.84935391e-01
6.78302050e-01 1.98369920e-01 -1.57583311e-01 -5.08317649e-01
-7.96917021e-01 2.86763370e-01 1.43778101e-01 8.80046070e-01
7.77068913e-01 -1.23906434e+00 -5.87170720e-01 2.39112198e-01
2.25886554e-01 -7.75885284e-01 5.31870961e-01 6.90688372e-01
3.65376115e-01 5.51474035e-01 1.58258632e-01 1.18499532e-01
-1.34311843e+00 8.94502223e-01 -2.93874800e-01 -3.48781735e-01
-5.82097828e-01 1.13945675e+00 5.65673131e-03 -4.85126168e-01
3.09823990e-01 -1.09099999e-01 -7.16362536e-01 -9.15850047e-03
1.04521608e+00 3.05418044e-01 -1.82761356e-01 -3.19347829e-01
-5.09727485e-02 1.14276186e-01 -3.69491607e-01 1.69253454e-01
1.41455412e+00 -4.22988743e-01 1.87598839e-01 3.82949531e-01
7.59794891e-01 2.87894398e-01 -1.08032918e+00 -5.95252633e-01
-3.95875946e-02 -7.49503970e-01 -1.32276686e-02 -9.51728165e-01
-7.64918625e-01 5.10604203e-01 1.22925982e-01 2.13036731e-01
9.72180009e-01 -4.18971591e-02 1.09682822e+00 6.75593317e-01
4.75601435e-01 -1.23072410e+00 7.86108896e-02 7.34220803e-01
6.29832327e-01 -1.31269372e+00 -6.56636134e-02 -1.91877708e-01
-9.95581329e-01 9.01410580e-01 7.17248976e-01 -2.22970679e-01
7.81135976e-01 -2.45497242e-01 -8.02168399e-02 2.55151056e-02
-1.50493193e+00 -1.79001659e-01 9.22564328e-01 1.36253238e-01
7.07157075e-01 2.80497998e-01 -6.09279513e-01 1.57010055e+00
-2.68084016e-02 2.60894656e-01 2.31729090e-01 3.59238505e-01
-8.11987460e-01 -1.27581489e+00 -1.34263178e-02 1.08256960e+00
-4.53255266e-01 -5.34553051e-01 -2.29399148e-02 -8.03942308e-02
3.65989916e-02 1.31920576e+00 -3.16355735e-01 -8.02622259e-01
3.92987967e-01 2.98888404e-02 -1.35580935e-02 -1.13019824e+00
-7.51699984e-01 7.06133246e-02 2.31507793e-01 -8.58348191e-01
5.07313460e-02 -5.61241448e-01 -9.86795783e-01 -3.14394027e-01
-3.14049363e-01 4.82029378e-01 2.31902659e-01 9.43490088e-01
7.45399594e-01 2.80709803e-01 6.65701032e-01 -7.11072326e-01
-8.34524870e-01 -1.00291121e+00 -4.97570962e-01 5.22924721e-01
-1.05434492e-01 -5.08538246e-01 -2.36749485e-01 -3.21813226e-01] | [10.190428733825684, 5.7052812576293945] |
f47cfc09-ae34-40e2-a94c-ea5e6f5f2f64 | a-multi-stream-convolutional-neural-network-1 | 2011.03756 | null | https://arxiv.org/abs/2011.03756v2 | https://arxiv.org/pdf/2011.03756v2.pdf | A Multi-stream Convolutional Neural Network for Micro-expression Recognition Using Optical Flow and EVM | Micro-expression (ME) recognition plays a crucial role in a wide range of applications, particularly in public security and psychotherapy. Recently, traditional methods rely excessively on machine learning design and the recognition rate is not high enough for its practical application because of its short duration and low intensity. On the other hand, some methods based on deep learning also cannot get high accuracy due to problems such as the imbalance of databases. To address these problems, we design a multi-stream convolutional neural network (MSCNN) for ME recognition in this paper. Specifically, we employ EVM and optical flow to magnify and visualize subtle movement changes in MEs and extract the masks from the optical flow images. And then, we add the masks, optical flow images, and grayscale images into the MSCNN. After that, in order to overcome the imbalance of databases, we added a random over-sampler after the Dense Layer of the neural network. Finally, extensive experiments are conducted on two public ME databases: CASME II and SAMM. Compared with many recent state-of-the-art approaches, our method achieves more promising recognition results. | ['Li Zhao', 'Baolin Song', 'Ke Li', 'Jinming Liu'] | 2020-11-07 | null | null | null | null | ['micro-expression-recognition'] | ['computer-vision'] | [ 4.14411984e-02 -6.72128797e-01 -3.45880501e-02 -5.31339049e-01
-1.81842089e-01 2.59428490e-02 2.06481710e-01 -2.38372475e-01
-5.40128827e-01 5.38457811e-01 -2.60908734e-02 -7.31615797e-02
-5.31183416e-03 -7.94463634e-01 -2.30772451e-01 -7.45446503e-01
2.08612740e-01 -2.16248900e-01 1.17759623e-01 -1.36596724e-01
2.85465896e-01 5.62804222e-01 -1.31903052e+00 2.71775603e-01
8.85295689e-01 1.18168092e+00 -2.16003120e-01 2.13955030e-01
-4.33956593e-01 9.11251485e-01 -6.82503283e-01 -2.78269470e-01
-1.33846849e-01 -6.66368961e-01 -5.42684793e-01 4.74167950e-02
8.55216309e-02 -5.37946582e-01 -6.13770843e-01 1.08849728e+00
6.98813736e-01 1.75676450e-01 4.98006850e-01 -1.27921820e+00
-5.71454585e-01 7.70030022e-02 -9.52690125e-01 4.54407662e-01
1.32693782e-01 2.88143992e-01 4.91660416e-01 -7.52822459e-01
4.22218353e-01 1.29773510e+00 4.54954356e-01 4.75680381e-01
-9.60219800e-01 -1.09601021e+00 2.17589475e-02 4.59302336e-01
-1.27127111e+00 -5.97191632e-01 1.04487491e+00 -3.00336391e-01
4.63219315e-01 1.38527244e-01 7.42964089e-01 9.53234196e-01
6.68778345e-02 8.86326790e-01 1.14640355e+00 5.11037698e-03
-4.44173366e-02 -1.35255069e-03 -7.11114258e-02 7.47541130e-01
-5.61056621e-02 -1.34326950e-01 -3.40251267e-01 2.07506627e-01
9.29792345e-01 2.83529937e-01 -4.66610312e-01 1.32686362e-01
-1.10913312e+00 5.53031564e-01 4.85472351e-01 6.36731982e-01
-3.33369970e-01 -1.47445694e-01 5.74048817e-01 1.00495309e-01
2.53987670e-01 5.35121895e-02 -8.36404189e-02 -3.82791251e-01
-1.01671219e+00 -2.10391954e-01 3.93825531e-01 1.01845168e-01
5.62940538e-01 1.95915729e-01 -1.33644059e-01 9.05531228e-01
9.05091316e-02 1.98564067e-01 7.92901397e-01 -7.05939829e-01
4.53425288e-01 8.64120007e-01 -1.02702305e-01 -1.65709543e+00
-5.57926953e-01 -5.55168629e-01 -1.44408417e+00 1.54914886e-01
3.32514077e-01 -6.50809780e-02 -6.66290700e-01 1.65607023e+00
2.57639647e-01 5.28074384e-01 -9.28138867e-02 1.18476224e+00
8.87745559e-01 8.53713989e-01 -6.93181083e-02 -4.43565428e-01
1.02335262e+00 -7.92198718e-01 -9.26994205e-01 6.06804304e-02
5.75120747e-01 -6.53197646e-01 1.07704818e+00 5.98759711e-01
-8.24783444e-01 -6.55205190e-01 -9.87028599e-01 3.94144878e-02
-1.77096203e-01 3.63539308e-01 6.73663497e-01 4.05452341e-01
-5.44027507e-01 5.63136160e-01 -8.06393445e-01 -6.76565245e-02
8.97597790e-01 3.68623376e-01 -3.65584403e-01 3.47025879e-02
-1.10739136e+00 4.92773801e-01 1.31304547e-01 7.52530932e-01
-4.09279853e-01 -3.16797286e-01 -6.86051071e-01 1.16888970e-01
3.41993384e-02 -1.69289634e-01 8.92384470e-01 -1.27757931e+00
-1.80309415e+00 7.22011685e-01 -1.23616926e-01 5.12704924e-02
5.62171578e-01 -5.71929291e-02 -6.77341282e-01 1.41394883e-01
-3.25431764e-01 4.60676640e-01 6.68351948e-01 -7.12350607e-01
-4.31485623e-01 -4.47850049e-01 1.50564276e-02 -9.83122438e-02
-6.91402972e-01 6.58772588e-02 -3.70169312e-01 -5.48839688e-01
1.85803726e-01 -6.00904644e-01 -2.94435713e-02 1.12924978e-01
-4.24867004e-01 6.95162592e-03 1.02919543e+00 -7.11674988e-01
1.53576899e+00 -2.52964163e+00 -3.11418045e-02 7.30219185e-02
1.99860796e-01 7.17910886e-01 -1.45757407e-01 -2.01176316e-01
-1.35932550e-01 8.23414233e-03 -1.68199837e-01 -1.78423092e-01
-3.64350140e-01 3.93181294e-02 -1.13963217e-01 6.13815963e-01
1.91995025e-01 7.96104968e-01 -6.70170367e-01 -6.23137534e-01
2.96905249e-01 5.83960712e-01 -4.47770715e-01 2.70117193e-01
7.82078728e-02 7.70302773e-01 -5.63107252e-01 5.14540970e-01
9.69586313e-01 -3.40220660e-01 -1.64013579e-02 -4.44463432e-01
-1.26051242e-02 -4.35443558e-02 -1.32234192e+00 1.61186779e+00
-5.12949586e-01 6.09469473e-01 4.99053150e-02 -1.35331523e+00
1.09993184e+00 1.62350371e-01 6.76285326e-01 -1.01290798e+00
5.07039309e-01 3.54035825e-01 2.61464685e-01 -8.52134049e-01
5.71507812e-02 -1.10921793e-01 3.06674302e-01 3.86895806e-01
-2.79155821e-01 3.93652409e-01 -1.15832463e-02 -6.22525476e-02
6.53100848e-01 -6.83736280e-02 2.65969094e-02 1.56119943e-01
1.03180718e+00 -4.82185036e-01 1.05192089e+00 9.79955643e-02
-4.67993826e-01 4.63433504e-01 6.91786110e-01 -5.89193463e-01
-6.45594299e-01 -6.01029754e-01 -1.07104622e-01 5.39542437e-01
3.54955345e-01 -2.09244162e-01 -7.38612354e-01 -5.11528313e-01
-2.69341469e-01 3.28718461e-02 -5.36964059e-01 -3.80927980e-01
-6.76916361e-01 -1.04657745e+00 5.40537357e-01 5.15987158e-01
1.13138425e+00 -1.23410070e+00 -5.77738822e-01 3.75250906e-01
-3.25845599e-01 -1.11134338e+00 -4.47716236e-01 -5.63906908e-01
-8.09723556e-01 -1.17864096e+00 -8.10139716e-01 -7.54713476e-01
5.50780714e-01 1.76848903e-01 5.71600139e-01 3.62428486e-01
-4.45636690e-01 -4.36726749e-01 -1.12390228e-01 -1.05828196e-01
-1.31068155e-01 1.90879226e-01 -6.72502816e-02 5.13526320e-01
5.77517748e-01 -6.56537652e-01 -9.42641020e-01 3.59836280e-01
-1.06595361e+00 1.27088860e-01 6.09994292e-01 9.15304482e-01
3.24620128e-01 1.12099499e-01 6.44749284e-01 -6.16391242e-01
5.97196341e-01 -2.90954202e-01 -5.77490985e-01 1.09397806e-01
-3.09412003e-01 -2.32776970e-01 6.75212741e-01 -6.81686521e-01
-1.03589296e+00 -3.94646637e-02 -4.09492165e-01 -4.51554626e-01
-2.66169421e-02 4.08701301e-01 -3.07515860e-01 9.16840583e-02
3.61582637e-01 1.77753717e-01 2.65151918e-01 -4.54099894e-01
-1.87760860e-01 9.96037722e-01 4.74310189e-01 -2.22999185e-01
4.21292067e-01 4.67865795e-01 4.87462878e-02 -7.39479125e-01
-8.16670179e-01 -8.90073553e-02 -3.07361424e-01 -1.95733890e-01
9.11297560e-01 -6.02080345e-01 -1.07010281e+00 9.68337595e-01
-1.18094170e+00 -8.16941708e-02 2.39274681e-01 6.27268732e-01
-1.79606020e-01 3.66413176e-01 -8.13804746e-01 -7.76370943e-01
-5.12526810e-01 -1.34346223e+00 6.94443822e-01 7.31195569e-01
1.39897600e-01 -6.41741574e-01 -1.42231852e-01 2.56788224e-01
6.81895614e-01 3.45419317e-01 6.57525361e-01 -1.99116752e-01
-4.40735608e-01 -1.43891782e-01 -5.71433604e-01 4.90345806e-01
3.22980970e-01 2.49224246e-01 -1.07691813e+00 -3.49407569e-02
3.19514945e-02 -2.71892667e-01 7.86674857e-01 3.56943697e-01
1.70568097e+00 -1.65291637e-01 -2.72747755e-01 9.45282340e-01
1.10766208e+00 5.25873065e-01 8.79109859e-01 3.26087326e-01
6.24400914e-01 6.71401620e-01 4.20027763e-01 5.22098720e-01
2.09212124e-01 5.87536335e-01 3.25832635e-01 -3.96189034e-01
1.49855882e-01 -9.71304551e-02 1.98593140e-01 8.86886537e-01
1.89323239e-02 -5.42347692e-02 -6.78155541e-01 2.69371271e-01
-1.69639599e+00 -9.98001218e-01 -6.66077882e-02 1.92003429e+00
7.79806852e-01 2.48080909e-01 4.88499627e-02 3.30757529e-01
7.42474675e-01 3.75887483e-01 -6.78363860e-01 -2.74417996e-01
-1.76735595e-01 9.64106768e-02 -1.87750131e-01 1.05377518e-01
-9.99575019e-01 6.37892723e-01 5.24523640e+00 8.57936502e-01
-1.72945178e+00 9.33623612e-02 1.01672387e+00 -7.83873573e-02
1.52221473e-03 -3.30340028e-01 -5.67423820e-01 8.16472590e-01
5.18699646e-01 3.02909791e-01 3.41425985e-01 5.30799448e-01
3.45612377e-01 4.42081094e-02 -6.29872262e-01 1.46820688e+00
-9.03150812e-02 -1.31642199e+00 -2.43656963e-01 -1.63712946e-03
4.56055194e-01 -2.57743239e-01 2.19613370e-02 1.41956568e-01
-3.65517825e-01 -1.17455077e+00 1.25531837e-01 7.12612569e-01
9.05607283e-01 -7.35668123e-01 9.32397962e-01 4.13480580e-01
-1.00538981e+00 -1.01519436e-01 -2.73757428e-01 -1.29915968e-01
7.11304992e-02 8.81845534e-01 2.55570561e-02 3.16173047e-01
6.70925736e-01 8.67544889e-01 -2.09195986e-01 9.43820894e-01
-1.52303174e-01 5.23008287e-01 -3.99314702e-01 -9.97890532e-02
1.75868735e-01 -3.50955039e-01 7.78079107e-02 1.17845845e+00
2.79331654e-01 1.98838606e-01 -3.10962163e-02 8.28977883e-01
-2.60554194e-01 2.60033518e-01 -3.04964781e-01 -6.83317482e-02
2.64985532e-01 1.46988678e+00 -4.23503309e-01 -3.06790829e-01
-4.31962132e-01 1.06203711e+00 1.55901805e-01 2.92039782e-01
-7.95082808e-01 -7.20710516e-01 6.05256617e-01 -4.30595987e-02
-5.28635681e-02 -1.31638631e-01 -6.74225166e-02 -1.55683136e+00
8.97511765e-02 -8.60313892e-01 3.28882039e-01 -5.21802187e-01
-1.10466504e+00 5.82753718e-01 -5.37983239e-01 -1.33194470e+00
-4.27817553e-02 -4.58174646e-01 -8.73506248e-01 8.45914185e-01
-1.62890828e+00 -6.75963938e-01 -7.52119720e-01 6.19516850e-01
2.78205574e-01 -8.24531764e-02 5.90048432e-01 9.19315398e-01
-1.22790790e+00 7.03987360e-01 7.99830817e-03 5.25128126e-01
7.26320922e-01 -6.29632890e-01 3.03263366e-02 7.38267004e-01
-1.38916671e-01 5.24531722e-01 1.95985630e-01 -1.65002048e-01
-1.15146101e+00 -8.33353639e-01 5.63830197e-01 1.61332846e-01
3.69458258e-01 -2.63308704e-01 -1.15463126e+00 3.47572595e-01
-7.53861591e-02 4.05971855e-01 4.79093999e-01 -3.36292386e-01
-6.78905174e-02 -5.93141794e-01 -1.15544140e+00 4.60413367e-01
8.45358729e-01 -3.03287566e-01 -2.27620319e-01 2.17145700e-02
2.71820992e-01 -4.79027063e-01 -8.26812863e-01 4.65232372e-01
7.53156960e-01 -1.19380820e+00 6.72897518e-01 -4.67217624e-01
6.68249547e-01 -3.50442261e-01 1.79692984e-01 -1.18747199e+00
-7.38336593e-02 -5.11539698e-01 4.10970636e-02 1.37728775e+00
-7.25712329e-02 -7.83788204e-01 8.51202190e-01 2.55036980e-01
3.18852454e-01 -9.90840197e-01 -8.45948577e-01 -4.62801993e-01
-1.39753163e-01 -2.29763225e-01 8.76849711e-01 1.12304151e+00
-1.10986575e-01 3.61133963e-01 -4.35664117e-01 -1.40227884e-01
3.15444618e-01 2.93156773e-01 7.90710092e-01 -1.08832121e+00
-1.38098359e-01 -6.42639160e-01 -5.26793838e-01 -1.09012210e+00
8.16653892e-02 -5.60856879e-01 -2.17247874e-01 -1.29013038e+00
1.88981846e-01 -5.40257752e-01 -4.89634275e-01 3.50777686e-01
-2.15074271e-01 3.84892523e-01 6.02753796e-02 2.34515369e-01
-3.55752498e-01 8.03659916e-01 1.58645201e+00 -1.04823634e-01
-2.28852242e-01 -2.07425311e-01 -5.80920577e-01 7.89492309e-01
8.51821542e-01 -1.19404137e-01 -2.83757865e-01 -5.51485360e-01
1.49861090e-02 1.05032556e-01 3.70467007e-01 -9.91640925e-01
2.14691177e-01 -2.48482987e-01 6.25320435e-01 -4.33283210e-01
2.20025644e-01 -6.26009881e-01 -6.87545314e-02 5.76703072e-01
-1.04159020e-01 -2.12948397e-02 2.51132865e-02 1.33556411e-01
-5.42063177e-01 3.87096182e-02 9.83590662e-01 -1.18576856e-02
-5.52751899e-01 7.62725711e-01 -1.45935073e-01 5.50365224e-02
8.30274224e-01 -1.67779729e-01 -4.38267618e-01 -3.34331632e-01
-3.69759232e-01 1.88182861e-01 1.47050858e-01 3.98116767e-01
6.82430983e-01 -1.36074352e+00 -5.00719190e-01 5.55969894e-01
-9.03457180e-02 1.15093239e-01 6.02210581e-01 1.24741316e+00
-5.17584264e-01 7.62753412e-02 -4.12424386e-01 -5.64595282e-01
-9.36744571e-01 2.57921189e-01 7.23117232e-01 -1.68934405e-01
-5.84926009e-01 4.46180314e-01 1.71431422e-01 -1.98842943e-01
2.26450816e-01 -9.66948643e-02 -4.67429906e-01 2.84331795e-02
7.81415462e-01 3.30693722e-01 -1.23970002e-01 -6.89631879e-01
-4.66734499e-01 7.25054562e-01 -4.69242148e-02 1.63853958e-01
1.36279821e+00 -5.50604463e-02 -1.73009068e-01 2.42606848e-01
1.54537952e+00 -9.04536098e-02 -1.14032328e+00 -1.26289740e-01
-3.76409769e-01 -5.94990134e-01 2.12645039e-01 -4.31984603e-01
-1.64574444e+00 1.46912467e+00 8.95914674e-01 -1.07027195e-01
1.40213919e+00 -6.01345122e-01 1.24578309e+00 1.41730323e-01
-6.20128997e-02 -1.02318430e+00 2.35481039e-01 1.36795327e-01
4.11676317e-01 -1.30094731e+00 -1.61763519e-01 -2.63413042e-01
-4.46252912e-01 1.28244162e+00 9.33562458e-01 -5.44062965e-02
6.75672829e-01 2.88870066e-01 2.86985844e-01 -8.11615810e-02
-2.86251932e-01 2.31366947e-01 7.06773112e-03 3.14055324e-01
4.57629263e-01 -3.13202918e-01 -4.96698350e-01 6.28908396e-01
1.21933758e-01 5.22943556e-01 4.51892912e-01 7.16322184e-01
-1.81461602e-01 -8.15056443e-01 -8.95961821e-02 5.36863744e-01
-6.86405003e-01 2.88520336e-01 1.39021397e-01 5.33007443e-01
2.27888167e-01 7.66142845e-01 2.81554192e-01 -5.86759090e-01
3.91968787e-01 -2.52332509e-01 2.33977333e-01 -7.98943639e-02
-3.86630207e-01 2.51000863e-03 -2.45948285e-01 -6.83964908e-01
-6.67299569e-01 -3.39025468e-01 -1.46373200e+00 -5.06494224e-01
-2.94008046e-01 -3.26755494e-02 4.75477457e-01 9.42323625e-01
3.99251044e-01 5.30746400e-01 8.81977797e-01 -4.64130729e-01
-2.67583668e-01 -9.94469881e-01 -6.28832281e-01 7.38220811e-01
3.54430765e-01 -6.26645148e-01 -2.98501104e-01 -2.18584359e-01] | [13.571454048156738, 1.7451860904693604] |
34f4a50f-6f8d-418a-a9d0-fcaf2a7d81b1 | deep-learning-based-mitosis-detection-in | 2109.00816 | null | https://arxiv.org/abs/2109.00816v1 | https://arxiv.org/pdf/2109.00816v1.pdf | Deep Learning-based mitosis detection in breast cancer histologic samples | This is the submission for mitosis detection in the context of the MIDOG 2021 challenge. It is based on the two-stage objection model Faster RCNN as well as DenseNet as a backbone for the neural network architecture. It achieves a F1-score of 0.6645 on the Preliminary Test Phase Leaderboard. | ['Sylvain Berlemont', 'Hippolyte Heuberger', 'Michel Halmes'] | 2021-09-02 | null | null | null | null | ['mitosis-detection'] | ['medical'] | [ 4.12651487e-02 7.59433389e-01 -9.17766690e-01 -1.96098328e-01
-8.58907938e-01 -2.70918667e-01 6.98831320e-01 2.19033927e-01
-8.19748580e-01 1.13830411e+00 4.87862319e-01 -4.28895772e-01
1.19450025e-01 -4.12397355e-01 -5.62121451e-01 -7.29261994e-01
-1.33953661e-01 7.28905380e-01 2.46688843e-01 -7.26234391e-02
-9.24277827e-02 1.93655014e-01 -1.02680302e+00 4.30564076e-01
2.08665758e-01 6.25697792e-01 -3.43051583e-01 1.26386881e+00
6.78713262e-01 7.71745801e-01 -8.25768352e-01 -4.26579386e-01
-2.91339099e-01 -1.96285948e-01 -1.01488280e+00 -5.60948074e-01
7.55998433e-01 -6.53237775e-02 -7.97029614e-01 7.38483429e-01
9.85454559e-01 -2.15234563e-01 3.47607642e-01 -1.01128256e+00
-2.29847967e-03 1.00756145e+00 -4.71625268e-01 8.93505991e-01
-2.05452576e-01 5.40718138e-01 1.08020437e+00 -6.21349990e-01
1.17331791e+00 1.04929733e+00 9.16328669e-01 9.68663275e-01
-1.14452410e+00 -5.48523962e-01 -1.04446828e-01 1.06421649e-01
-1.35896432e+00 -5.68295181e-01 -3.02213013e-01 7.07329810e-02
1.45653784e+00 1.07966743e-01 9.36313450e-01 1.45863426e+00
6.54663265e-01 1.36038685e+00 7.28690624e-01 -1.77739430e-02
2.52967834e-01 -4.80300128e-01 3.81029069e-01 6.90651774e-01
4.56707507e-01 2.22639605e-01 -8.86091769e-01 5.44571318e-02
5.50309479e-01 -5.97506344e-01 -4.08273160e-01 5.17697811e-01
-1.43303728e+00 6.40689135e-01 7.07943320e-01 4.47144955e-01
1.24068275e-01 8.51682007e-01 6.42274618e-01 -4.98701222e-02
5.41828990e-01 6.16348505e-01 -5.64493597e-01 -4.57479417e-01
-1.12772429e+00 3.29859346e-01 6.62106335e-01 5.40782630e-01
-1.03191353e-01 -7.39488229e-02 -6.20933652e-01 1.66955158e-01
3.55479807e-01 -8.20499752e-03 4.02412474e-01 -8.66401196e-01
5.41599691e-02 5.03131568e-01 -6.36285424e-01 -2.27434829e-01
-8.23338151e-01 -1.18860710e+00 -1.27285433e+00 1.84335746e-02
6.62545502e-01 -9.37662125e-02 -1.33019459e+00 1.49184978e+00
-9.81731266e-02 6.20656788e-01 8.35217256e-03 7.12677538e-01
1.40919673e+00 3.55972379e-01 2.07545936e-01 1.97826639e-01
1.21311545e+00 -1.26099885e+00 -7.32471347e-01 -3.79914194e-02
1.10203993e+00 -3.18551064e-01 2.14281440e-01 6.87059402e-01
-1.25894618e+00 -3.27196300e-01 -1.35327077e+00 -2.12663770e-01
-7.04513848e-01 8.57759416e-02 9.22118723e-01 5.44887900e-01
-1.63142169e+00 4.98084843e-01 -8.83239865e-01 -6.51405334e-01
6.51294231e-01 8.04220200e-01 -2.96334624e-01 -2.27302071e-02
-9.43367898e-01 8.61173987e-01 6.92758083e-01 3.25152755e-01
-1.46536708e+00 -1.13897562e+00 -4.62591410e-01 -9.11782607e-02
1.60470866e-02 -9.28656220e-01 1.50138140e+00 -1.36377901e-01
-1.13079441e+00 1.30523741e+00 7.87025839e-02 -9.59253311e-01
4.97623831e-01 1.20372854e-01 -2.15955794e-01 -1.18262962e-01
-2.59598106e-01 1.60095239e+00 -2.08932772e-01 -3.34862649e-01
-1.13492310e+00 -2.77436107e-01 -3.21985066e-01 -5.03075197e-02
1.40509754e-01 -2.52739727e-01 -8.44864786e-01 -4.50194925e-01
-9.99992490e-02 -8.25218081e-01 -4.98381883e-01 -6.64379448e-02
-6.91961765e-01 -4.99736667e-01 5.58360934e-01 -6.07019663e-01
7.74779499e-01 -1.94764423e+00 1.68738812e-01 1.20702885e-01
7.98052490e-01 1.44146621e-01 -1.77947178e-01 -2.93703794e-01
-2.51546681e-01 2.59704649e-01 2.23550886e-01 -5.04912376e-01
-5.65370470e-02 -1.48782907e-02 2.58242309e-01 8.55082095e-01
2.24589452e-01 1.36586666e+00 -1.00227332e+00 -2.85578430e-01
-3.10961455e-01 4.58288133e-01 -3.37318867e-01 -2.46972844e-01
-2.45864734e-01 -1.02601826e-01 1.08524531e-01 1.07305813e+00
3.75010639e-01 -2.63350666e-01 2.79136896e-01 -9.41356048e-02
5.52545227e-02 1.29802883e-01 -4.08240944e-01 1.95252120e+00
5.42031884e-01 1.24040496e+00 1.93899572e-01 -6.31856918e-01
4.79240090e-01 4.78860021e-01 2.58558363e-01 -4.70892012e-01
3.37551802e-01 2.27614075e-01 4.38777983e-01 4.38871652e-01
4.05556679e-01 5.25687516e-01 -1.63591877e-01 1.73157975e-02
6.41714275e-01 4.58323322e-02 5.70004821e-01 4.60624337e-01
1.88824749e+00 -1.51955381e-01 2.18809441e-01 -6.76899552e-01
1.40960634e-01 -2.11107135e-01 9.72148776e-01 6.59776330e-01
-5.73812008e-01 6.51731431e-01 7.33634174e-01 -7.21813798e-01
-8.60078871e-01 -9.27053213e-01 5.49883172e-02 6.43626273e-01
-4.75015640e-01 -5.91787934e-01 -4.42674190e-01 -1.00836885e+00
-1.60375819e-01 2.64406294e-01 -1.20226765e+00 -1.95036128e-01
-5.40795565e-01 -1.30958402e+00 1.42392778e+00 6.63365364e-01
4.90750074e-01 -9.98143613e-01 -8.56979340e-02 5.10406643e-02
3.65074798e-02 -8.73869956e-01 -1.98844314e-01 8.67881000e-01
-9.33479965e-01 -1.29583073e+00 -8.70795965e-01 -9.60096240e-01
4.59937721e-01 -5.62351108e-01 1.56455684e+00 2.92323083e-01
-6.93882048e-01 -3.64851415e-01 1.63941175e-01 -4.77199316e-01
-1.75565645e-01 7.51778603e-01 -2.73975700e-01 -7.54532933e-01
5.20820081e-01 -2.55199168e-02 -7.17649817e-01 -4.69773971e-02
-6.44293249e-01 2.10898340e-01 6.75136209e-01 9.30041611e-01
7.17570603e-01 -1.04713142e-01 4.91037250e-01 -7.92500854e-01
2.47230694e-01 -2.85257220e-01 -6.01830781e-01 1.30739570e-01
-5.98307252e-01 -4.48724419e-01 -3.88376303e-02 -1.00403288e-02
-4.39501554e-01 1.22956499e-01 -2.38512635e-01 2.24952787e-01
-1.00771245e-02 4.18799967e-01 -1.01393079e-02 -9.53002349e-02
5.41297376e-01 4.45812121e-02 -2.39103198e-01 -1.38406873e-01
5.13794720e-02 1.06103122e-01 1.09843576e+00 -2.05473781e-01
3.72308344e-01 2.70138979e-01 3.03740114e-01 -3.88265669e-01
-8.40832114e-01 -4.47776228e-01 -2.68843830e-01 -2.97403395e-01
9.63128150e-01 -1.19654739e+00 -8.96965802e-01 7.73938775e-01
-1.11269128e+00 -7.14503527e-01 -3.74896884e-01 3.45088899e-01
-3.00971836e-01 -4.60220098e-01 -1.22027051e+00 -5.98085336e-02
-6.60554647e-01 -8.06047916e-01 8.70541215e-01 7.80927777e-01
-3.40574771e-01 -1.01475644e+00 4.53219861e-01 6.73912540e-02
3.92849207e-01 3.41374516e-01 6.50556803e-01 -7.44704068e-01
-6.52093351e-01 -2.21768767e-01 -2.62365460e-01 -1.75082490e-01
-5.48013330e-01 4.52036738e-01 -1.20607042e+00 -5.96479833e-01
-8.79521310e-01 -6.45060837e-01 1.57877374e+00 7.76681304e-01
1.26527178e+00 3.03672969e-01 -9.04620528e-01 7.78096676e-01
1.23331213e+00 -1.83556199e-01 1.02199626e+00 4.07807946e-01
1.28358215e-01 7.98421651e-02 1.82733968e-01 -8.04079399e-02
3.19993317e-01 2.64068037e-01 7.46789932e-01 -5.30771911e-01
-5.21081686e-01 -1.83502898e-01 1.42668948e-01 6.93617463e-01
3.32041234e-01 -6.59824371e-01 -1.57388914e+00 6.22015357e-01
-1.84511852e+00 -5.67932189e-01 -2.40078196e-01 1.52754354e+00
8.94947946e-01 6.60755634e-01 4.86684367e-02 4.34287265e-02
5.04155338e-01 -7.45730698e-02 -5.45454144e-01 -2.29251206e-01
-5.97267330e-01 3.53270739e-01 6.76974773e-01 3.97493303e-01
-9.95214999e-01 9.08221543e-01 8.19158363e+00 1.30848408e+00
-6.12785280e-01 2.06233218e-01 1.48808396e+00 -2.62695014e-01
1.55611038e-01 -3.26027632e-01 -1.50564134e+00 1.51784778e-01
1.53419185e+00 -9.96386707e-02 -9.19974819e-02 2.22697988e-01
-1.81588203e-01 -3.56715977e-01 -1.15507662e+00 5.23413181e-01
-1.32446706e-01 -2.06265259e+00 -3.54976147e-01 3.70347857e-01
8.90707493e-01 8.38121116e-01 1.77518249e-01 7.87316144e-01
7.53507972e-01 -1.65967667e+00 1.09158278e-01 5.91139913e-01
8.38856220e-01 -8.04153979e-01 1.52130926e+00 3.36854815e-01
-7.95980096e-01 3.29943419e-01 -2.07899153e-01 2.60711491e-01
-3.97251397e-01 7.56879210e-01 -1.44907975e+00 1.37958437e-01
4.98113126e-01 7.57687211e-01 -9.10979629e-01 1.74179733e+00
-1.32641062e-01 1.03922176e+00 -6.54259264e-01 -1.14753619e-01
2.75649786e-01 9.42433178e-01 4.26409453e-01 1.54823244e+00
-2.27067858e-01 -2.67814249e-01 -1.21327259e-01 5.15305221e-01
-7.34013796e-01 -5.40516853e-01 -2.13834673e-01 -1.34490743e-01
1.82618201e-01 1.52395535e+00 -1.17685854e+00 -2.34219447e-01
1.85489312e-01 2.39332452e-01 2.63652474e-01 7.22527280e-02
-6.92959189e-01 -3.86936575e-01 3.39360625e-01 -2.41467595e-01
2.97503509e-02 3.03354144e-01 -1.83900148e-01 -5.30001223e-01
-8.31497729e-01 -1.00755787e+00 7.24280298e-01 -5.48451602e-01
-1.03693032e+00 3.33935022e-01 -5.52609265e-01 -6.42960727e-01
3.47040854e-02 -6.72449768e-01 -8.28418672e-01 5.18890619e-01
-1.33910823e+00 -1.13488054e+00 -1.78978801e-01 1.08552158e-01
4.90691751e-01 -1.86890259e-01 1.03635454e+00 2.21080884e-01
-8.89520705e-01 1.07958579e+00 4.39965166e-02 1.08175769e-01
6.09043062e-01 -1.61061060e+00 9.95605707e-01 5.48865795e-01
-1.42985418e-01 1.63607478e-01 4.32489634e-01 -6.97166622e-01
-1.09348774e+00 -1.12608850e+00 1.20230639e+00 -3.90518516e-01
5.60167789e-01 -4.09299940e-01 -2.43320972e-01 6.68063641e-01
4.62383002e-01 2.34688416e-01 7.32480407e-01 5.25462389e-01
9.34833437e-02 1.52734980e-01 -1.09103668e+00 4.31884319e-01
6.69878602e-01 -1.24550931e-01 -1.06785148e-02 4.66942102e-01
8.80053937e-01 -7.76203692e-01 -1.05914462e+00 7.07030773e-01
4.22918379e-01 -4.29532945e-01 5.10884404e-01 -6.27308846e-01
4.39181685e-01 -2.95837760e-01 9.85949337e-02 -9.70106483e-01
-5.18617094e-01 -7.99578726e-01 -6.83453143e-01 8.79859030e-01
1.02484822e+00 9.86606181e-02 1.87011933e+00 -3.05571288e-01
-3.08646351e-01 -1.23281932e+00 -1.44610882e+00 -4.29650873e-01
2.09229648e-01 -8.04039836e-02 6.10178784e-02 5.15923202e-01
-1.38255402e-01 5.15121877e-01 1.30960032e-01 -2.19314083e-01
6.18616343e-01 -8.40953469e-01 6.22953534e-01 -1.12585974e+00
-4.31918859e-01 -8.00867856e-01 -7.90465474e-01 -8.37442160e-01
-2.05216408e-01 -1.09420216e+00 2.15021551e-01 -1.28105700e+00
6.46896482e-01 1.31730363e-01 -8.26707959e-01 5.03956914e-01
2.37631202e-02 7.57149696e-01 -4.00785580e-02 -2.18145147e-01
-1.30426693e+00 1.64533198e-01 8.26988995e-01 -5.37732363e-01
3.18464041e-01 2.03424003e-02 -7.02202380e-01 7.26486683e-01
9.52351987e-01 -4.02096123e-01 1.09510161e-02 -3.02266359e-01
4.43597734e-01 -1.82033733e-01 2.35847250e-01 -1.37016904e+00
4.62517321e-01 3.71055841e-01 9.97081101e-01 -1.32099044e+00
2.63472795e-01 -4.19752114e-03 1.53814312e-02 7.69833148e-01
-6.81567609e-01 9.34337005e-02 6.18596673e-01 4.61472511e-01
-8.66702350e-04 2.05955923e-01 6.35104656e-01 -5.36002405e-02
-4.14758354e-01 3.89303297e-01 -5.37627161e-01 1.66806191e-01
6.44225419e-01 -2.76576698e-01 -1.19456065e+00 -4.55096699e-02
-8.07922781e-01 8.56905818e-01 1.28673837e-01 1.64389893e-01
3.26239765e-01 -1.12649786e+00 -9.95110452e-01 -6.48250356e-02
4.70450670e-02 6.15988113e-02 6.01921463e-03 9.64511216e-01
-5.93119681e-01 9.33675945e-01 -1.22667171e-01 -7.23321378e-01
-1.31163454e+00 -2.26299405e-01 8.34592402e-01 -1.26797569e+00
-3.57603073e-01 1.75576711e+00 -2.26258319e-02 -5.77609777e-01
8.91804039e-01 -2.10016802e-01 -3.19363415e-01 -1.88620180e-01
7.57736206e-01 5.02415955e-01 2.92774320e-01 1.01656735e-01
-3.79051477e-01 -2.00803339e-01 -5.46364963e-01 -1.70345128e-01
1.23590195e+00 5.36401987e-01 -2.30512068e-01 3.01591456e-01
1.03006995e+00 -6.71795905e-01 -8.98953915e-01 2.64254659e-02
2.41523176e-01 3.94790471e-01 7.02044666e-01 -1.55384088e+00
-1.09118199e+00 5.44506073e-01 9.11463261e-01 -4.80280310e-01
8.45084012e-01 5.52913249e-02 5.82595229e-01 5.23671627e-01
7.42182359e-02 -1.07293069e+00 -3.41804996e-02 7.92592227e-01
3.40905666e-01 -7.57158041e-01 2.96683520e-01 -2.50899523e-01
3.71026427e-01 1.19348741e+00 1.06344771e+00 -2.62207221e-02
4.20573533e-01 7.75421679e-01 -1.73968330e-01 -5.64148903e-01
-1.76260602e+00 3.59998550e-03 9.73541364e-02 5.91000140e-01
6.67149961e-01 1.03118822e-01 -5.10487854e-02 6.75420284e-01
-1.69519663e-01 4.31115925e-01 4.38303232e-01 8.89346302e-01
-2.92274505e-01 -7.14661419e-01 2.74228096e-01 5.83533287e-01
-7.94892192e-01 -1.71847284e-01 -7.21617222e-01 9.88116086e-01
2.35579044e-01 3.23891014e-01 2.31343493e-01 -5.27952611e-01
1.52291730e-01 -3.07063878e-01 5.52908719e-01 -4.36605573e-01
-1.07273090e+00 -6.93120286e-02 3.51604968e-01 -8.10523629e-01
-1.09778911e-01 -3.94087106e-01 -1.21222150e+00 -8.77008796e-01
-2.64835984e-01 1.11558154e-01 5.07779837e-01 5.43235302e-01
1.33160666e-01 9.44745660e-01 -1.48576513e-01 -6.31161928e-01
-8.08349699e-02 -1.13538289e+00 -5.56767941e-01 -7.48045743e-01
4.27931845e-01 4.75333296e-02 -2.19028234e-01 -3.49758863e-01] | [15.086214065551758, -3.0942044258117676] |
12b05019-fafc-40ad-80ce-4e9ef394d051 | capacity-and-bias-of-learned-geometric | null | null | http://proceedings.neurips.cc/paper/2021/hash/88d25099b103efd638163ecb40a55589-Abstract.html | http://proceedings.neurips.cc/paper/2021/file/88d25099b103efd638163ecb40a55589-Paper.pdf | Capacity and Bias of Learned Geometric Embeddings for Directed Graphs | A wide variety of machine learning tasks such as knowledge base completion, ontology alignment, and multi-label classification can benefit from incorporating into learning differentiable representations of graphs or taxonomies. While vectors in Euclidean space can theoretically represent any graph, much recent work shows that alternatives such as complex, hyperbolic, order, or box embeddings have geometric properties better suited to modeling real-world graphs. Experimentally these gains are seen only in lower dimensions, however, with performance benefits diminishing in higher dimensions. In this work, we introduce a novel variant of box embeddings that uses a learned smoothing parameter to achieve better representational capacity than vector models in low dimensions, while also avoiding performance saturation common to other geometric models in high dimensions. Further, we present theoretical results that prove box embeddings can represent any DAG. We perform rigorous empirical evaluations of vector, hyperbolic, and region-based geometric representations on several families of synthetic and real-world directed graphs. Analysis of these results exposes correlations between different families of graphs, graph characteristics, model size, and embedding geometry, providing useful insights into the inductive biases of various differentiable graph representations. | ['Andrew McCallum', 'Kenneth Clarkson', 'Luke Vilnis', 'Nicholas Monath', 'Dongxu Zhang', 'Michael Boratko'] | 2021-12-01 | null | https://openreview.net/forum?id=0IqTX6FcZWv | https://openreview.net/pdf?id=0IqTX6FcZWv | neurips-2021-12 | ['knowledge-base-completion', 'knowledge-base-completion'] | ['graphs', 'knowledge-base'] | [ 6.67542173e-03 7.35857725e-01 -3.12493414e-01 -2.80878246e-01
-1.58603653e-01 -7.42506027e-01 7.43535399e-01 7.48588264e-01
-9.26499069e-02 3.35454375e-01 3.96279544e-01 -7.49900997e-01
-6.64201081e-01 -1.11903441e+00 -3.99823815e-01 -4.03624624e-01
-9.61026430e-01 6.06744111e-01 1.13069721e-01 -3.54452789e-01
2.73504198e-01 9.50301409e-01 -1.13970649e+00 -2.65756011e-01
6.19066060e-01 5.64374745e-01 -4.35224682e-01 7.32983351e-01
-1.41594604e-01 3.28855544e-01 -3.96128267e-01 -4.88568097e-01
2.30200171e-01 5.61209843e-02 -7.87426651e-01 1.29501019e-02
6.12842441e-01 5.83931096e-02 -7.83631980e-01 8.97836745e-01
3.17658842e-01 2.25296035e-01 1.08768845e+00 -1.49744546e+00
-1.23201144e+00 6.53714359e-01 -4.04869109e-01 9.12363008e-02
3.11128974e-01 -1.66629612e-01 1.29868007e+00 -5.65615416e-01
6.83895230e-01 1.50702047e+00 9.81443346e-01 4.32579845e-01
-1.51166427e+00 -2.38577023e-01 1.49715558e-01 -1.47898361e-01
-1.31830585e+00 2.01013917e-03 7.72935629e-01 -4.96846586e-01
7.94605851e-01 2.32789114e-01 5.07379591e-01 8.88104975e-01
1.39154971e-01 2.43775964e-01 7.81119943e-01 -5.49944103e-01
1.75469704e-02 1.33590370e-01 5.90684831e-01 1.10632515e+00
8.62921059e-01 3.71238077e-03 6.28515286e-03 -4.49378103e-01
8.73252988e-01 1.16242535e-01 -2.67760843e-01 -1.05420971e+00
-1.19948518e+00 1.13859975e+00 7.77559280e-01 3.10863525e-01
-1.27442181e-01 3.70673001e-01 3.52170825e-01 4.33923185e-01
6.23686969e-01 8.68394196e-01 -7.63194188e-02 3.65054637e-01
-2.65550077e-01 1.88519314e-01 8.85985374e-01 1.17776108e+00
6.23586178e-01 8.88394415e-02 1.38500974e-01 6.45177066e-01
2.12869212e-01 2.23047554e-01 2.28869528e-01 -5.22224367e-01
4.97567803e-01 8.96312833e-01 -1.64680496e-01 -1.51073778e+00
-1.04135835e+00 -4.26694363e-01 -6.85041010e-01 1.73163309e-03
6.82312846e-01 1.32185087e-01 -7.06824720e-01 1.58167112e+00
9.34289321e-02 -1.30028173e-01 5.11666127e-02 6.27493083e-01
6.51839674e-01 3.33345294e-01 -7.36316890e-02 3.09779882e-01
1.29285932e+00 -5.29719651e-01 -3.79464179e-01 -2.76620965e-02
1.20860922e+00 -2.27751970e-01 1.09025002e+00 -8.11322629e-02
-8.33588064e-01 -1.85716391e-01 -1.10251248e+00 -2.02865392e-01
-7.41220653e-01 -2.85740167e-01 1.11106980e+00 9.82573748e-01
-1.21236646e+00 8.40089619e-01 -5.52469492e-01 -6.83021724e-01
4.44195002e-01 3.70948195e-01 -6.20836258e-01 -3.09095889e-01
-1.01108253e+00 9.51810420e-01 3.82056296e-01 -3.85118544e-01
-2.63761699e-01 -7.33204067e-01 -1.03555620e+00 3.22202593e-01
8.39118958e-02 -4.99524146e-01 6.01552606e-01 -4.64622289e-01
-8.52062166e-01 7.61483967e-01 2.58001208e-01 -6.71145380e-01
1.28024518e-01 2.75690675e-01 -5.70694804e-01 7.74840117e-02
-2.82348096e-01 4.84045297e-01 5.38091481e-01 -8.55472922e-01
5.38650714e-02 -6.71004295e-01 5.68156898e-01 1.40139371e-01
-7.87062228e-01 -4.46886480e-01 9.14632976e-02 -4.41135108e-01
1.94947660e-01 -9.83322084e-01 -3.52112234e-01 1.79313555e-01
-3.24488282e-01 -4.71708268e-01 5.22353649e-01 -2.89545178e-01
1.19503748e+00 -2.20755601e+00 2.64967710e-01 5.72743595e-01
7.28341043e-01 -9.93219167e-02 -3.91225755e-01 8.24734807e-01
-1.97630331e-01 4.37814981e-01 2.98796147e-02 1.66355148e-01
2.45200396e-01 2.08484679e-01 -1.11758806e-01 8.74434173e-01
2.12025404e-01 8.62819493e-01 -1.08363593e+00 -3.01859528e-01
1.76510483e-01 5.42984486e-01 -8.00738335e-01 -4.04858351e-01
-1.34684980e-01 -2.65987575e-01 -2.72459596e-01 3.33297312e-01
3.90330285e-01 -5.38418829e-01 5.39446652e-01 -9.24163312e-02
3.59371394e-01 1.93318442e-01 -1.03338289e+00 1.39484382e+00
-3.50667924e-01 8.59673798e-01 -3.18166137e-01 -1.13284564e+00
1.04453194e+00 -8.04750249e-02 2.46394441e-01 -4.90182757e-01
-4.73721279e-03 -1.60005484e-02 1.10566244e-01 -1.36764646e-01
7.22732663e-01 -3.40670085e-04 -5.17184548e-02 4.64377970e-01
2.34408397e-02 -3.43389586e-02 1.06534325e-01 5.09619653e-01
1.25992739e+00 -4.48053390e-01 1.73428714e-01 -4.23600167e-01
8.49709585e-02 -2.35981997e-02 3.25279459e-02 5.40434361e-01
-6.61294982e-02 3.03859472e-01 1.05647135e+00 -5.61471224e-01
-1.26407504e+00 -1.24847305e+00 -3.01890165e-01 1.05232143e+00
3.19282919e-01 -6.82333171e-01 -4.47953641e-01 -7.37817526e-01
6.23532951e-01 7.65641868e-01 -9.03487086e-01 -4.38292742e-01
-4.31156009e-01 -6.80316269e-01 7.74949610e-01 5.88392854e-01
-2.95346200e-01 -3.89732093e-01 -1.10029325e-01 -5.36384284e-02
5.30254602e-01 -1.03143406e+00 -4.29622203e-01 -1.34173427e-02
-1.15154123e+00 -1.45569420e+00 -5.32866418e-01 -8.61018836e-01
8.27136874e-01 3.75542045e-01 1.06582499e+00 4.90010567e-02
-3.90192181e-01 7.83034027e-01 -2.29619265e-01 -1.73643962e-01
-4.06406671e-01 2.08943963e-01 1.72284588e-01 -3.29317153e-01
3.59092653e-01 -5.76618493e-01 -4.11979824e-01 1.94388717e-01
-9.17302191e-01 -3.42657506e-01 4.08923030e-01 7.88088441e-01
1.40504092e-01 -1.10958651e-01 5.60092986e-01 -1.04723966e+00
1.09506905e+00 -7.61836290e-01 -4.22380805e-01 1.71518147e-01
-8.33373725e-01 5.11518300e-01 7.69949257e-01 -4.33068484e-01
-2.56114393e-01 -5.73427081e-01 3.84577096e-01 -3.60588491e-01
1.91542029e-01 5.72785139e-01 2.33773813e-01 -2.64118105e-01
1.10815811e+00 -1.48152947e-01 2.82488465e-01 -3.08596224e-01
9.95313466e-01 3.45343947e-01 6.62491769e-02 -5.04024148e-01
9.06462669e-01 4.12101954e-01 4.68135834e-01 -1.22409225e+00
-3.70697200e-01 -2.80185670e-01 -6.16846323e-01 1.62317380e-01
5.71435452e-01 -5.21401763e-01 -6.42014027e-01 -3.31552446e-01
-8.55178297e-01 -4.94839363e-02 -3.48586559e-01 4.69940841e-01
-4.80905354e-01 4.39252228e-01 -3.56801599e-01 -5.90592861e-01
9.29630622e-02 -6.88225865e-01 8.26823056e-01 -4.49653305e-02
-3.55035603e-01 -1.67633772e+00 4.14898247e-02 -2.28054225e-01
4.29649591e-01 5.84849656e-01 1.69268858e+00 -1.06494999e+00
-5.26512086e-01 -3.65762204e-01 -4.27266866e-01 4.56787497e-02
-9.52407438e-03 -6.86525553e-02 -5.20276785e-01 -5.33736765e-01
-7.59951234e-01 -5.97661734e-02 6.46429658e-01 1.61166489e-01
9.65363801e-01 -4.39417660e-01 -5.65315664e-01 8.16884279e-01
1.39410841e+00 -1.30560145e-01 4.25407022e-01 1.62201136e-01
8.09711516e-01 5.86941957e-01 7.67652690e-02 1.26218945e-01
4.35440719e-01 4.96613175e-01 5.05027294e-01 -2.50351541e-02
4.32489738e-02 -3.46753538e-01 -1.56270955e-02 6.34616077e-01
2.39320751e-02 -2.15339765e-01 -1.08902943e+00 5.40722966e-01
-1.41817689e+00 -8.33293498e-01 -8.71214345e-02 2.16377687e+00
2.54628867e-01 2.20808968e-01 4.76248175e-01 1.83712602e-01
7.96170950e-01 4.20590937e-01 -4.58566278e-01 -6.30192459e-01
-2.32817128e-01 2.12283850e-01 9.63244617e-01 4.36651081e-01
-8.94088864e-01 7.17216909e-01 6.95023108e+00 2.43778750e-01
-8.94486547e-01 -2.17580199e-01 1.93558261e-01 4.39454727e-02
-7.68556356e-01 -3.97735015e-02 -4.09339368e-01 -3.41299027e-02
1.02575874e+00 -5.18692255e-01 5.05251408e-01 1.00640476e+00
-2.81795442e-01 6.36653721e-01 -1.47608709e+00 8.87151062e-01
9.14525315e-02 -1.65790880e+00 1.64199457e-01 4.04393852e-01
5.76573074e-01 1.76031254e-02 1.57682732e-01 3.54141295e-01
4.95333552e-01 -1.43837011e+00 1.27357557e-01 3.65794420e-01
9.47227299e-01 -9.06899810e-01 3.08903456e-01 5.91644086e-02
-1.07440543e+00 -2.53784597e-01 -5.90469658e-01 -1.00255102e-01
-3.76296520e-01 4.10126686e-01 -1.15171707e+00 6.98491693e-01
1.86958835e-02 7.40860283e-01 -9.29682553e-01 8.54878485e-01
2.71242350e-01 3.79231632e-01 -2.48412222e-01 -2.99570918e-01
3.69368374e-01 -2.87581027e-01 5.51811755e-01 1.14057577e+00
1.96948469e-01 -1.12968469e-02 2.46499460e-02 7.33529449e-01
-1.97302952e-01 1.76086217e-01 -1.39776695e+00 -6.11450195e-01
7.11346328e-01 9.68331575e-01 -7.24729836e-01 -2.34974828e-03
-4.60890293e-01 4.52458411e-01 6.00199103e-01 4.52416509e-01
-6.31405652e-01 -8.36609185e-01 9.17906463e-01 5.18922806e-01
6.74102530e-02 -6.62623405e-01 -1.87694922e-01 -1.00213659e+00
-1.97533891e-01 -5.67166507e-01 4.58813161e-01 -4.70731795e-01
-1.31042373e+00 4.31819528e-01 7.25522488e-02 -8.36827159e-01
-1.62042797e-01 -9.05372441e-01 -4.85406965e-01 7.30462432e-01
-1.11867726e+00 -9.39057887e-01 -1.51959032e-01 4.36926007e-01
-1.99884191e-01 -2.18011394e-01 1.02002144e+00 -3.75239886e-02
-2.60252863e-01 7.65580297e-01 5.20829558e-01 3.04225028e-01
3.30368042e-01 -1.51136541e+00 7.54210472e-01 2.89334834e-01
4.40551966e-01 6.88131809e-01 5.64429045e-01 -2.73442656e-01
-1.78609240e+00 -1.09701383e+00 6.31371558e-01 -4.65855837e-01
9.08732057e-01 -4.34601933e-01 -9.05102313e-01 1.01377225e+00
-3.51442188e-01 2.17639267e-01 6.20018601e-01 7.07740486e-01
-8.14831436e-01 1.64546520e-02 -1.19330394e+00 8.28469515e-01
1.43796468e+00 -6.75199628e-01 -4.13227975e-01 6.81298077e-01
8.84341955e-01 -1.28467381e-01 -1.39091849e+00 2.10141361e-01
5.37688434e-01 -6.93966568e-01 1.28901160e+00 -1.27760577e+00
1.45304427e-01 8.85047391e-02 -2.43732452e-01 -1.55134428e+00
-6.90909743e-01 -5.47921896e-01 -1.89056963e-01 7.45098472e-01
3.24541658e-01 -1.09779346e+00 8.73291433e-01 4.01871413e-01
7.47226831e-03 -9.27591980e-01 -7.05641866e-01 -1.08366585e+00
4.68233824e-01 -1.59076259e-01 8.18252981e-01 1.22434068e+00
4.85048026e-01 4.48761195e-01 1.08565658e-01 2.25549549e-01
6.92629039e-01 -6.88177496e-02 8.55418444e-01 -1.67525744e+00
7.69417062e-02 -7.02130318e-01 -1.38824320e+00 -8.69058430e-01
3.17778051e-01 -1.60662210e+00 -9.32663500e-01 -1.72765732e+00
-3.07470590e-01 -7.20366597e-01 -7.06427172e-02 1.49259925e-01
1.99558452e-01 -1.78929150e-01 1.22855306e-01 -8.47870931e-02
-2.67105401e-01 4.34104294e-01 1.18597567e+00 -1.40844777e-01
3.10662296e-02 -3.48806500e-01 -9.25935745e-01 7.05439508e-01
7.46882737e-01 -2.46570438e-01 -6.88687980e-01 -4.28489745e-01
3.56637985e-01 2.31728330e-02 3.58774930e-01 -8.07463884e-01
1.78516284e-02 -7.42538348e-02 2.62399226e-01 -1.37414187e-01
2.63815641e-01 -6.67228997e-01 -1.48957148e-01 3.79344344e-01
-6.31479084e-01 3.72404844e-01 9.21676531e-02 9.56259966e-01
2.11226106e-01 -8.15825164e-02 7.33596683e-01 1.64155692e-01
-4.60551143e-01 4.37342525e-01 1.03176229e-01 4.55341756e-01
1.17053950e+00 -4.64061022e-01 -6.17249489e-01 -4.30527776e-01
-7.79766858e-01 1.55379102e-01 7.06205487e-01 5.81129313e-01
5.35396874e-01 -1.45232499e+00 -5.51339149e-01 2.06966922e-01
3.84070367e-01 -2.21471906e-01 -1.80126786e-01 5.71508229e-01
-7.42370486e-01 5.09760082e-01 -1.22377217e-01 -5.20724416e-01
-1.04703486e+00 7.98509061e-01 2.65596181e-01 -1.85621053e-01
-8.37568223e-01 6.54123008e-01 2.74793595e-01 -6.43533647e-01
3.39059412e-01 -4.17298347e-01 -2.11154278e-02 4.06874456e-02
1.50075555e-01 5.40951848e-01 -1.73320502e-01 -3.71724099e-01
-3.94866973e-01 4.52592105e-01 -1.20132931e-01 3.12336504e-01
1.27263224e+00 1.47646099e-01 9.73122939e-02 3.95221800e-01
1.46286726e+00 -1.38629034e-01 -7.55196214e-01 -3.13227624e-01
2.81031102e-01 -4.63506907e-01 -2.42685586e-01 -1.56858265e-01
-6.61492884e-01 8.84411812e-01 2.66682178e-01 8.76918614e-01
5.21944225e-01 1.62582546e-01 3.37771654e-01 5.09660721e-01
3.50878328e-01 -6.94261849e-01 1.23242885e-01 5.29761195e-01
8.14471960e-01 -8.09425414e-01 8.43443125e-02 -4.07377034e-01
-3.85218620e-01 1.38575637e+00 3.35523993e-01 -5.09213984e-01
7.38606215e-01 -1.88173622e-01 -5.26472509e-01 -5.17955244e-01
-6.80296063e-01 -1.27292782e-01 2.96877980e-01 1.00099254e+00
4.44673479e-01 3.81375998e-01 -7.24892272e-03 1.65612146e-01
-4.28723454e-01 -6.63128674e-01 7.71984637e-01 5.81688046e-01
-4.97071415e-01 -8.22248220e-01 -2.42947623e-01 7.68226802e-01
-1.25195011e-01 -1.05268911e-01 -5.12762010e-01 1.27585912e+00
-4.69228208e-01 6.10743821e-01 3.84497255e-01 -3.34318340e-01
4.36425626e-01 1.87217787e-01 8.19616139e-01 -6.29718125e-01
-1.56307042e-01 -6.66869700e-01 3.60168815e-01 -3.80542278e-01
1.60066813e-01 -3.31774920e-01 -1.20049548e+00 -7.27185786e-01
-3.76873314e-01 1.63029090e-01 7.41836488e-01 4.78246808e-01
5.28589427e-01 5.20313025e-01 4.36672926e-01 -6.43993735e-01
-8.66069913e-01 -7.41938353e-01 -9.37125683e-01 6.28238380e-01
2.81727046e-01 -8.49619985e-01 -5.24085402e-01 -5.50924003e-01] | [7.134638786315918, 6.076377868652344] |
3647965f-5403-427f-947a-d208fe3bd2f3 | beyond-triplet-leveraging-the-most-data-for | 2212.10313 | null | https://arxiv.org/abs/2212.10313v1 | https://arxiv.org/pdf/2212.10313v1.pdf | Beyond Triplet: Leveraging the Most Data for Multimodal Machine Translation | Multimodal machine translation (MMT) aims to improve translation quality by incorporating information from other modalities, such as vision. Previous MMT systems mainly focus on better access and use of visual information and tend to validate their methods on image-related datasets. These studies face two challenges. First, they can only utilize triple data (bilingual texts with images), which is scarce; second, current benchmarks are relatively restricted and do not correspond to realistic scenarios. Therefore, this paper correspondingly establishes new methods and new datasets for MMT. First, we propose a framework 2/3-Triplet with two new approaches to enhance MMT by utilizing large-scale non-triple data: monolingual image-text data and parallel text-only data. Second, we construct an English-Chinese {e}-commercial {m}ulti{m}odal {t}ranslation dataset (including training and testing), named EMMT, where its test set is carefully selected as some words are ambiguous and shall be translated mistakenly without the help of images. Experiments show that our method is more suitable for real-world scenarios and can significantly improve translation performance by using more non-triple data. In addition, our model also rivals various SOTA models in conventional multimodal translation benchmarks. | ['Mingxuan Wang', 'Liwei Wu', 'YuYang Huang', 'Shanbo Cheng', 'Zewei Sun', 'Yaoming Zhu'] | 2022-12-20 | null | null | null | null | ['multimodal-machine-translation'] | ['natural-language-processing'] | [ 3.31803560e-01 -4.15739894e-01 -5.61624169e-01 -2.21649259e-01
-1.01483727e+00 -7.19590664e-01 9.10879731e-01 -6.05598152e-01
-5.67538023e-01 7.84913778e-01 1.59717903e-01 -6.14128888e-01
5.65342963e-01 -4.37417865e-01 -6.71414018e-01 -4.81470972e-01
9.21648502e-01 6.51644945e-01 -6.22490719e-02 -5.42322636e-01
8.12924132e-02 1.68304563e-01 -1.01279593e+00 6.53473020e-01
1.15064383e+00 6.54292345e-01 3.56472641e-01 1.56266123e-01
-8.33751932e-02 2.49993905e-01 -4.66209024e-01 -9.68297422e-01
4.70430017e-01 -8.42415035e-01 -7.31429219e-01 3.03536892e-01
6.89397037e-01 -4.74148661e-01 -2.74452209e-01 1.22375536e+00
8.65855396e-01 -2.44924903e-01 5.60676277e-01 -1.36438453e+00
-1.35749757e+00 4.29215878e-01 -8.62990022e-01 1.95329767e-02
5.13435841e-01 2.43853748e-01 7.37355292e-01 -1.52656782e+00
1.02127528e+00 1.33001113e+00 4.08857048e-01 5.73844552e-01
-1.01780009e+00 -6.91255450e-01 -1.46790639e-01 4.27229047e-01
-1.35702181e+00 -5.95483601e-01 6.03328705e-01 -1.54172555e-01
6.17409766e-01 6.08461261e-01 4.70430702e-01 1.55516815e+00
5.86575121e-02 1.09701014e+00 1.82462513e+00 -6.71613455e-01
-4.28835899e-01 4.22939986e-01 -4.41842973e-01 5.87119520e-01
-2.57647503e-02 1.99137300e-01 -5.52615285e-01 2.62741446e-01
6.64612055e-01 -8.45233630e-03 -5.95495939e-01 -2.48555616e-01
-2.07818222e+00 5.31628549e-01 2.93646574e-01 5.03393650e-01
-4.61560562e-02 -5.02229810e-01 2.60599524e-01 6.00391805e-01
2.55817801e-01 9.32096690e-02 -2.06371248e-01 -5.38158640e-02
-9.39118445e-01 -1.32457763e-01 2.86721289e-01 1.36658239e+00
8.22767735e-01 -2.82298829e-02 -3.31961095e-01 1.06250048e+00
1.87396660e-01 1.29822147e+00 7.02110350e-01 -5.92134774e-01
1.17569160e+00 4.83555168e-01 3.20583582e-02 -9.84650910e-01
-5.08868694e-02 -2.26463050e-01 -1.01390612e+00 -1.74145162e-01
2.94974953e-01 -1.17304809e-01 -9.85523462e-01 1.53736079e+00
5.44679910e-02 -3.59674513e-01 2.55341291e-01 1.36189306e+00
1.11637199e+00 6.37466073e-01 -3.83109391e-01 -4.14418340e-01
1.31227362e+00 -1.28087687e+00 -9.40245390e-01 -2.32978418e-01
5.45700431e-01 -1.62686563e+00 1.36081040e+00 1.36939332e-01
-9.84623432e-01 -5.96619129e-01 -7.45374680e-01 -1.68776870e-01
-5.44447601e-01 6.33263826e-01 2.95285434e-01 6.27408981e-01
-1.14334106e+00 -7.97246546e-02 -3.01184535e-01 -7.51456976e-01
1.28526762e-01 1.68476015e-01 -6.90766096e-01 -5.22278488e-01
-1.27209353e+00 1.27706826e+00 2.41938949e-01 4.58452314e-01
-6.66421592e-01 -1.21249324e-02 -8.52761447e-01 -5.72347343e-01
3.38477552e-01 -8.29499364e-01 1.03646088e+00 -1.27788341e+00
-1.48452854e+00 1.12235773e+00 -3.86960745e-01 9.86348912e-02
8.24905872e-01 9.04988572e-02 -6.61579311e-01 1.72828585e-01
3.35686922e-01 9.77283895e-01 7.48220861e-01 -1.60893083e+00
-4.41410363e-01 -4.89734203e-01 3.20730358e-02 6.08355045e-01
-4.56118077e-01 2.26225048e-01 -1.00066590e+00 -9.09161389e-01
2.34553471e-01 -1.23458958e+00 1.52650639e-01 -1.56585351e-01
-5.82175910e-01 2.72177339e-01 8.86097312e-01 -8.70097578e-01
9.87907767e-01 -1.79047108e+00 3.79321367e-01 -1.08841963e-01
4.36302982e-02 3.76862377e-01 -4.79572535e-01 5.21891475e-01
9.29848403e-02 8.01976994e-02 -1.71753824e-01 -3.31564248e-01
9.61248130e-02 3.75001222e-01 -1.97405979e-01 3.13830435e-01
-2.29539983e-02 1.38374925e+00 -7.08177090e-01 -9.75002289e-01
2.76757330e-01 2.50305057e-01 -1.05186678e-01 -7.21722282e-03
1.98381320e-01 7.24913716e-01 -2.17136472e-01 1.10594308e+00
8.08836460e-01 -8.78743380e-02 9.99915525e-02 -4.99265850e-01
-1.48449227e-01 -2.81233668e-01 -6.44611061e-01 1.85894072e+00
-2.93195277e-01 8.67105305e-01 -2.04720676e-01 -7.76334226e-01
6.69758737e-01 3.40643376e-01 2.64098108e-01 -1.23961031e+00
2.83920348e-01 5.05793512e-01 -1.42665878e-01 -7.20355868e-01
6.08706176e-01 -1.23074315e-01 8.64058882e-02 3.86646420e-01
-5.27340136e-02 -1.59972116e-01 3.05498064e-01 -4.52366984e-03
4.20569032e-01 3.49830359e-01 -3.95933278e-02 6.55719936e-02
4.93649691e-01 4.16949153e-01 6.13408387e-01 6.25801206e-01
-3.81731838e-01 8.40555489e-01 3.68688852e-02 -1.81337267e-01
-1.23607075e+00 -9.74845350e-01 -1.71904713e-01 9.50292766e-01
5.49585104e-01 -1.90567255e-01 -7.68660247e-01 -8.21846664e-01
-5.14232099e-01 4.88470137e-01 -4.78077501e-01 9.13880765e-02
-6.76168144e-01 -1.03583848e+00 5.57179332e-01 3.08882177e-01
8.99339616e-01 -8.11728656e-01 -1.27431471e-02 -2.28247255e-01
-1.06106067e+00 -1.54780471e+00 -9.49366212e-01 -5.07572949e-01
-8.38443398e-01 -8.88021052e-01 -1.30701709e+00 -1.01956558e+00
9.17824864e-01 7.82894671e-01 1.10460913e+00 -1.62340537e-01
1.65136740e-01 3.71194005e-01 -5.42534649e-01 -1.06522091e-01
-5.03358603e-01 -1.38236433e-01 4.57997993e-02 1.72587276e-01
4.39788759e-01 -8.55449960e-02 -5.08492649e-01 9.21438634e-01
-1.01118696e+00 6.39862299e-01 1.13375974e+00 1.04131138e+00
6.02259338e-01 -5.90488613e-01 1.70991793e-01 -5.27372658e-01
5.90507567e-01 -1.46346584e-01 -2.21675843e-01 9.07047391e-01
-6.88073218e-01 -3.18189442e-01 3.23651671e-01 -6.74133360e-01
-1.11509907e+00 -3.13194871e-01 2.50848234e-01 -5.97178936e-01
1.38565823e-02 5.29110193e-01 -2.82469213e-01 -2.73090333e-01
4.58498716e-01 6.61505044e-01 -6.21629842e-02 -3.62523615e-01
3.80607784e-01 9.37961340e-01 5.74190974e-01 -7.05293119e-01
9.89395022e-01 3.54551971e-01 -2.17926383e-01 -4.26079512e-01
-4.01195645e-01 -1.59405977e-01 -8.60786498e-01 -3.20505589e-01
6.74565613e-01 -1.01147485e+00 -3.06937456e-01 4.95425195e-01
-1.22007549e+00 3.18881497e-02 3.38704795e-01 9.07973528e-01
-4.56642628e-01 6.58003986e-01 -7.75310993e-01 -2.79599488e-01
-3.60729337e-01 -1.61216450e+00 1.30010676e+00 -4.30195965e-02
3.02008092e-01 -7.24820018e-01 -6.87600970e-02 1.05192912e+00
3.97474408e-01 -4.74853665e-02 7.30062664e-01 -2.40275726e-01
-6.10343874e-01 3.94307151e-02 -5.90537250e-01 3.08294713e-01
1.78986326e-01 -1.07200488e-01 -5.95582008e-01 -3.55492353e-01
-1.12499282e-01 -4.09783185e-01 6.76613629e-01 -1.39483169e-01
6.34999156e-01 -1.54089078e-01 -1.70717314e-01 4.69346255e-01
1.17067790e+00 7.69941509e-02 6.90180302e-01 3.60772252e-01
9.08834577e-01 3.98234099e-01 9.41968203e-01 -9.75766331e-02
8.55187118e-01 1.05590558e+00 3.49800080e-01 -5.73054731e-01
-4.29223686e-01 -2.24100068e-01 7.43808091e-01 1.46670747e+00
-5.28664231e-01 -3.49534184e-01 -9.88449156e-01 5.27571321e-01
-2.03010273e+00 -8.20898592e-01 -2.79336989e-01 2.01063681e+00
1.02353501e+00 -4.04024601e-01 -1.31562248e-01 -2.81120092e-01
9.26119804e-01 -1.45410761e-01 -2.45585218e-01 -1.38150752e-01
-7.58716464e-01 -1.26607269e-01 4.13603544e-01 2.33827770e-01
-8.77817452e-01 1.19754672e+00 5.79519081e+00 1.03635609e+00
-1.20017397e+00 4.87897843e-01 5.93985915e-01 1.33231774e-01
-5.13989449e-01 -1.51631376e-02 -6.03871763e-01 4.39345062e-01
4.35248464e-01 1.06758989e-01 4.60926265e-01 1.59825444e-01
2.19055086e-01 3.63787636e-02 -9.87380385e-01 1.40298080e+00
5.43442011e-01 -1.13427162e+00 5.45769453e-01 1.46336347e-01
1.09029210e+00 8.22285488e-02 4.16506559e-01 4.77404684e-01
-8.32408387e-03 -9.62041676e-01 8.00931454e-01 4.49136615e-01
1.10928488e+00 -3.46260250e-01 1.00557292e+00 3.29872102e-01
-8.19851935e-01 4.28139627e-01 -2.64315665e-01 3.94080013e-01
1.52793050e-01 1.87030762e-01 -5.73531985e-01 1.06097257e+00
6.67829156e-01 7.84981191e-01 -8.12616289e-01 6.95554733e-01
-2.33208477e-01 2.22149134e-01 -9.69510302e-02 1.22767292e-01
3.72776717e-01 -5.19851863e-01 4.19930577e-01 1.13751650e+00
7.01726496e-01 -1.70520395e-01 2.71094620e-01 6.75294101e-01
-2.45614231e-01 5.66982150e-01 -8.36201310e-01 3.87794003e-02
2.21753672e-01 1.20798099e+00 -4.18656886e-01 -4.08255130e-01
-9.83177364e-01 1.33231425e+00 4.01519202e-02 7.36171782e-01
-9.80623007e-01 1.52838275e-01 1.41872421e-01 -1.94242284e-01
2.21128622e-03 -1.86323762e-01 -1.20305493e-01 -1.89046228e+00
3.15362334e-01 -1.45533109e+00 2.21671104e-01 -1.26758718e+00
-1.28285837e+00 8.09662104e-01 -7.26591125e-02 -1.71660507e+00
-1.17933273e-01 -7.40110636e-01 -6.50863498e-02 8.52004945e-01
-1.65375447e+00 -1.78028274e+00 -2.71773815e-01 1.06390572e+00
6.32368982e-01 -3.75413775e-01 6.10164642e-01 6.65408254e-01
-6.98838353e-01 8.14460874e-01 1.90865517e-01 3.74939799e-01
1.40928161e+00 -7.89525449e-01 -2.68079974e-02 9.84214365e-01
4.05309647e-01 6.26635253e-01 4.27487999e-01 -6.06611609e-01
-1.78835130e+00 -9.49640095e-01 1.02931750e+00 -6.65527046e-01
6.21040285e-01 -1.69199452e-01 -3.84671926e-01 7.91144073e-01
8.25534225e-01 -1.18097968e-01 5.94903886e-01 -3.57466400e-01
-2.80361384e-01 -4.03246470e-02 -1.02758980e+00 9.67432678e-01
1.10232270e+00 -5.74448109e-01 -6.35403514e-01 3.88754368e-01
4.20406491e-01 -6.79224312e-01 -8.93333316e-01 7.87138879e-01
4.20409769e-01 -8.79126966e-01 8.98046613e-01 -4.69027162e-01
6.42978072e-01 -5.29931247e-01 -5.11685371e-01 -1.32140350e+00
1.91437915e-01 -5.96349657e-01 2.62081295e-01 1.18832874e+00
5.87357640e-01 -5.78162611e-01 2.74810225e-01 1.79346070e-01
-1.94146380e-01 -4.98810828e-01 -1.00671434e+00 -6.97474897e-01
1.44682154e-01 -1.73390448e-01 6.66585624e-01 1.50731063e+00
-1.28393263e-01 4.64877278e-01 -8.51438403e-01 -5.59401251e-02
4.88899827e-01 5.73312938e-01 9.40954745e-01 -5.15785635e-01
2.67460737e-02 -5.53544402e-01 -1.40507475e-01 -1.21681273e+00
-6.22684956e-02 -9.71881628e-01 -1.14292897e-01 -1.41284931e+00
6.99616432e-01 -1.25229999e-01 -6.57668412e-02 5.19220173e-01
-1.56300619e-01 8.82701695e-01 3.97347987e-01 6.89716339e-01
-5.89565039e-01 7.61820495e-01 2.03397393e+00 -4.40804124e-01
2.85531789e-01 -3.12879324e-01 -4.58016932e-01 5.05435228e-01
6.71368718e-01 -8.82307366e-02 -2.51354367e-01 -9.82704103e-01
5.26624434e-02 2.28170931e-01 4.55518693e-01 -4.34152424e-01
1.37617037e-01 -3.89707714e-01 5.21131635e-01 -8.53735268e-01
2.45954156e-01 -9.36383426e-01 1.90624058e-01 6.61083460e-02
-1.47464886e-01 6.81380033e-01 1.90676153e-02 2.48361394e-01
-5.40934324e-01 -4.12484109e-02 4.46564913e-01 -1.49746448e-01
-7.08612919e-01 3.50990415e-01 -7.85205662e-02 -4.22698967e-02
9.00600314e-01 -3.11450511e-01 -6.87326312e-01 -3.75961274e-01
-5.37666738e-01 3.01968843e-01 6.96712017e-01 8.09889555e-01
7.08255172e-01 -1.97484732e+00 -9.75548506e-01 3.38654825e-03
5.92479706e-01 -5.56701899e-01 9.92475078e-03 1.43337071e+00
-5.19809723e-01 5.49049437e-01 -4.16424513e-01 -8.50039423e-01
-1.43149781e+00 6.28517151e-01 2.15329304e-01 8.30984302e-03
-2.99558818e-01 2.90666789e-01 2.52938151e-01 -9.25808609e-01
-1.16848171e-01 -1.38881849e-02 3.89425382e-02 -3.16068274e-03
1.91622883e-01 1.11132689e-01 -8.31507146e-03 -1.29468596e+00
-2.64710486e-01 8.05680871e-01 -1.42839486e-02 -5.13658881e-01
8.68115366e-01 -6.21191263e-01 -4.09107357e-01 3.09118509e-01
1.07122660e+00 4.27362230e-03 -6.63373470e-01 -7.93989897e-01
-2.95023113e-01 -7.64909327e-01 -2.19378665e-01 -1.06241894e+00
-1.32596660e+00 1.01521242e+00 7.02546895e-01 -4.71108854e-01
1.26473641e+00 -1.43214524e-01 9.88707662e-01 4.36932713e-01
5.79497278e-01 -1.22113538e+00 1.53896078e-01 3.04429471e-01
1.06619143e+00 -1.79891109e+00 -1.53997734e-01 -2.66118050e-01
-9.67753828e-01 1.18136549e+00 6.89608872e-01 7.82424271e-01
-4.89461496e-02 -1.39442831e-01 5.78611970e-01 1.32819742e-01
-4.02371228e-01 -4.24749553e-01 6.20137393e-01 5.79328775e-01
3.64752293e-01 1.42514661e-01 -5.71034729e-01 1.89222500e-01
-9.09408480e-02 -8.64480063e-02 2.52342165e-01 7.70850360e-01
-1.01180613e-01 -1.47437298e+00 -7.74550617e-01 -3.09776291e-02
-2.91485637e-01 -4.06224996e-01 -6.83771849e-01 9.76591408e-01
2.69297659e-01 1.11561620e+00 -4.36039358e-01 -4.55313563e-01
2.74637610e-01 -1.90227211e-01 7.98347950e-01 -1.63063571e-01
-3.41796100e-01 4.12551761e-01 -1.23517436e-03 -4.11898226e-01
-8.58060598e-01 -6.54597402e-01 -6.45694554e-01 -6.48156285e-01
-2.58214921e-01 -9.82160494e-02 6.36947095e-01 9.85540330e-01
2.62499720e-01 4.93866466e-02 5.97475529e-01 -7.37638533e-01
-2.91157037e-01 -1.01677465e+00 -6.60166070e-02 6.08579814e-01
5.74424909e-03 -4.87089157e-01 1.17308691e-01 2.72892684e-01] | [11.483672142028809, 1.5571210384368896] |
b72a7645-99c0-42c1-9bb2-f962343d2006 | graph-transformer-gans-for-graph-constrained | 2303.08225 | null | https://arxiv.org/abs/2303.08225v1 | https://arxiv.org/pdf/2303.08225v1.pdf | Graph Transformer GANs for Graph-Constrained House Generation | We present a novel graph Transformer generative adversarial network (GTGAN) to learn effective graph node relations in an end-to-end fashion for the challenging graph-constrained house generation task. The proposed graph-Transformer-based generator includes a novel graph Transformer encoder that combines graph convolutions and self-attentions in a Transformer to model both local and global interactions across connected and non-connected graph nodes. Specifically, the proposed connected node attention (CNA) and non-connected node attention (NNA) aim to capture the global relations across connected nodes and non-connected nodes in the input graph, respectively. The proposed graph modeling block (GMB) aims to exploit local vertex interactions based on a house layout topology. Moreover, we propose a new node classification-based discriminator to preserve the high-level semantic and discriminative node features for different house components. Finally, we propose a novel graph-based cycle-consistency loss that aims at maintaining the relative spatial relationships between ground truth and predicted graphs. Experiments on two challenging graph-constrained house generation tasks (i.e., house layout and roof generation) with two public datasets demonstrate the effectiveness of GTGAN in terms of objective quantitative scores and subjective visual realism. New state-of-the-art results are established by large margins on both tasks. | ['Luc van Gool', 'Radu Timofte', 'Nicu Sebe', 'Ling Shao', 'Bo Li', 'Humphrey Shi', 'Zhenyu Zhang', 'Hao Tang'] | 2023-03-14 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Tang_Graph_Transformer_GANs_for_Graph-Constrained_House_Generation_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Tang_Graph_Transformer_GANs_for_Graph-Constrained_House_Generation_CVPR_2023_paper.pdf | cvpr-2023-1 | ['house-generation'] | ['computer-vision'] | [ 4.82720695e-02 4.85069692e-01 1.89582482e-01 -1.70768157e-01
-4.19418335e-01 -4.26499516e-01 5.85616827e-01 -1.19655736e-01
5.86724043e-01 5.93706787e-01 8.63709897e-02 3.65605764e-03
-3.66598889e-02 -1.70648909e+00 -1.00260806e+00 -5.96238673e-01
-2.38434449e-01 2.44706064e-01 1.14589646e-01 -5.77981055e-01
-5.79885364e-01 4.58567560e-01 -1.06567430e+00 -1.68458268e-01
1.05971849e+00 7.85589635e-01 1.56236395e-01 5.76773047e-01
5.79897583e-01 9.24573243e-01 -3.47727746e-01 -8.17451358e-01
3.97528797e-01 -6.36711240e-01 -5.05535603e-01 5.78672469e-01
6.01220250e-01 -7.33864829e-02 -1.01269758e+00 9.04386222e-01
7.32310772e-01 1.35650754e-01 5.70408821e-01 -1.57665002e+00
-1.15012705e+00 5.47025979e-01 -5.51506639e-01 -2.38337636e-01
4.66691405e-01 5.51846266e-01 1.39855504e+00 -4.64175344e-01
7.35735357e-01 1.32188547e+00 7.03484833e-01 6.18575998e-02
-1.30365813e+00 -6.07549250e-01 3.23993444e-01 7.84067065e-02
-1.78491950e+00 3.13965864e-02 1.35035479e+00 -4.19641435e-01
7.75947094e-01 3.90098810e-01 1.11823368e+00 9.94864285e-01
3.89086634e-01 4.01004791e-01 6.05312586e-01 -1.96681693e-01
-2.16905866e-03 -2.84494519e-01 -6.49105728e-01 1.37525475e+00
2.69875497e-01 1.65677413e-01 -3.54049444e-01 2.85933107e-01
9.57713187e-01 -2.24099904e-01 -5.25479078e-01 -5.78826010e-01
-9.62456763e-01 9.58885908e-01 1.41942978e+00 1.19963795e-01
-3.79874319e-01 3.02536726e-01 6.52162880e-02 -7.89783075e-02
5.26232123e-01 3.23845536e-01 1.06272213e-01 8.40844750e-01
-7.57852256e-01 2.44912088e-01 5.49525380e-01 1.49924660e+00
8.46083760e-01 4.69652891e-01 -7.99560070e-01 4.53834057e-01
4.46620882e-01 6.40510321e-01 6.28233608e-03 -3.66839856e-01
5.55309534e-01 9.32026744e-01 -3.85646343e-01 -1.79459369e+00
-2.20442608e-01 -7.52694547e-01 -1.47285819e+00 -1.40250817e-01
-2.97762215e-01 7.71000907e-02 -1.10596442e+00 2.01616812e+00
3.79245907e-01 4.63744551e-01 -2.15639144e-01 6.89062953e-01
1.15234172e+00 6.01300240e-01 1.09086655e-01 1.87329099e-01
1.30216563e+00 -1.28502727e+00 -6.49113834e-01 -5.29491842e-01
2.15029076e-01 -4.93819147e-01 1.05809498e+00 -3.87613356e-01
-1.20984197e+00 -7.80188799e-01 -1.27217746e+00 -1.91681370e-01
-4.77003366e-01 7.03501627e-02 4.89815921e-01 3.61959070e-01
-1.19155455e+00 5.13693511e-01 -5.79040945e-01 -3.77198398e-01
5.32665074e-01 2.58996159e-01 -2.93323100e-01 -1.58126280e-01
-1.18666148e+00 4.51499134e-01 3.04935873e-01 4.13310438e-01
-9.88068759e-01 -6.63470566e-01 -1.53871083e+00 3.76590639e-01
1.74707428e-01 -1.41368365e+00 5.42971194e-01 -6.96665525e-01
-1.18280232e+00 9.13467944e-01 1.86898947e-01 -1.87698528e-01
5.75202525e-01 4.77042794e-01 -4.29767698e-01 6.71551377e-02
3.43395352e-01 6.91032887e-01 8.22691202e-01 -1.41361117e+00
-1.53995723e-01 -3.76120806e-01 3.53353210e-02 2.83246517e-01
-1.42284915e-01 -7.28962183e-01 -5.85002422e-01 -1.14942861e+00
1.73392639e-01 -9.92070735e-01 -7.47537464e-02 2.95736827e-02
-1.11801243e+00 4.83971164e-02 8.46991360e-01 -1.00055397e+00
1.32333386e+00 -1.90492284e+00 4.22210872e-01 5.14046550e-01
6.37969732e-01 -5.99389970e-02 -3.15630674e-01 4.93651599e-01
-2.55892485e-01 1.61996588e-01 -4.10740882e-01 -4.33738023e-01
1.57497659e-01 9.70510021e-02 -5.79904579e-02 4.54110891e-01
3.51717740e-01 1.61548710e+00 -1.09099162e+00 -3.00188810e-01
5.68922222e-01 7.68801928e-01 -5.51837385e-01 5.21372914e-01
-1.57112822e-01 3.20522994e-01 -2.82690972e-01 6.37313306e-01
8.40411246e-01 -3.68289709e-01 4.00272787e-01 -4.86572832e-01
6.28724277e-01 5.03366515e-02 -9.92003679e-01 1.69199657e+00
-6.06323838e-01 3.72142792e-01 -1.94045722e-01 -6.51787519e-01
1.01661825e+00 8.34612250e-02 9.04839635e-02 -6.50140464e-01
3.39858010e-02 -1.45516306e-01 -7.06080943e-02 -5.31916926e-03
2.70521730e-01 1.78028181e-01 -2.94588447e-01 -1.09146245e-01
1.96854934e-01 -3.15215260e-01 5.40175661e-02 5.21523356e-01
1.21360242e+00 8.84485319e-02 3.38246286e-01 -3.75077903e-01
4.14963961e-01 -4.58437830e-01 3.13343525e-01 1.37579545e-01
2.22144485e-01 8.81854951e-01 4.30195540e-01 -3.51229012e-01
-1.03076673e+00 -1.17891324e+00 6.47113740e-01 6.38948143e-01
3.45405281e-01 -5.86921692e-01 -8.26017618e-01 -6.73191309e-01
2.80861128e-02 5.94008029e-01 -8.65046322e-01 -6.49733603e-01
-4.50297952e-01 -4.55833495e-01 2.29228511e-01 7.63172626e-01
8.34280610e-01 -9.55426753e-01 -1.61629185e-01 1.31630316e-01
-1.13574177e-01 -1.39390147e+00 -9.74489152e-01 -1.58540830e-01
-3.01911265e-01 -1.18827415e+00 -5.32782614e-01 -1.06731141e+00
1.13496518e+00 1.59750015e-01 1.35493052e+00 3.91473651e-01
-2.47476086e-01 1.91023976e-01 -2.75523275e-01 1.48666292e-01
-1.05523780e-01 3.81553918e-01 -4.69788879e-01 1.97123095e-01
-4.37294722e-01 -9.72400308e-01 -7.18579590e-01 2.30741665e-01
-6.63256824e-01 5.47356308e-01 4.85025704e-01 9.81153786e-01
7.02377677e-01 4.05220062e-01 1.45602226e-01 -9.89767373e-01
5.57264507e-01 -4.02619570e-01 -4.62948412e-01 4.81026918e-01
-5.64700127e-01 2.69110315e-02 8.17413747e-01 -2.73102894e-02
-7.14452267e-01 3.87825840e-03 1.71342362e-02 -7.27080882e-01
2.73872256e-01 2.84347892e-01 -9.32168245e-01 -1.71524942e-01
3.15826774e-01 2.70265222e-01 -4.99738753e-01 3.63215804e-02
6.17185116e-01 -3.15435231e-01 6.66672707e-01 -4.02452499e-01
1.58329451e+00 2.54830807e-01 3.88003767e-01 -5.59760571e-01
-4.78477925e-01 6.19393252e-02 -5.26051342e-01 -2.21030086e-01
1.10879147e+00 -1.13518941e+00 -4.98705715e-01 6.81641400e-01
-1.12547255e+00 -5.96483171e-01 -4.30985898e-01 -3.01121324e-01
-4.62487131e-01 2.08581775e-01 -4.80689198e-01 -3.40136409e-01
-6.49408042e-01 -1.08522165e+00 1.47357011e+00 1.61531061e-01
1.35466844e-01 -1.19734192e+00 -1.00422181e-01 8.96938145e-02
1.75772294e-01 1.19603109e+00 1.05475235e+00 -2.06012167e-02
-1.08053660e+00 -1.97301388e-01 -3.56910884e-01 1.69919997e-01
3.00286502e-01 -5.04842587e-02 -6.46005929e-01 -5.31722009e-01
-8.26539814e-01 -1.48103395e-02 6.60234213e-01 3.01084548e-01
9.52322960e-01 -6.11009657e-01 -5.08581877e-01 1.12553012e+00
1.64302826e+00 -1.71525851e-01 9.38141882e-01 -1.62885010e-01
1.57402480e+00 4.26758856e-01 1.02176048e-01 2.86248684e-01
7.25860953e-01 8.06810677e-01 6.29905820e-01 -5.60384691e-01
-7.21041381e-01 -1.09885037e+00 -3.21052782e-03 6.69456720e-01
-1.55280516e-01 -8.22821736e-01 -6.36741281e-01 5.18259168e-01
-1.86206543e+00 -6.37057900e-01 -2.86737561e-01 1.96475339e+00
1.30626440e-01 4.47716229e-02 -1.48798423e-02 -2.18531415e-02
9.03179884e-01 5.16645730e-01 -4.84347522e-01 1.19002484e-01
-3.50045532e-01 5.29224157e-01 4.21006560e-01 5.84256172e-01
-1.03914392e+00 1.10494292e+00 4.51373768e+00 8.82816553e-01
-7.59201765e-01 1.02346331e-01 8.97955537e-01 3.43848825e-01
-7.25179732e-01 -5.86539060e-02 -2.19933078e-01 5.67769468e-01
2.97294348e-01 -4.10923302e-01 6.37554884e-01 8.98901999e-01
1.80063117e-02 4.34466392e-01 -8.86026859e-01 9.09622669e-01
1.32637948e-01 -1.33734822e+00 4.45018947e-01 2.15535283e-01
1.05140650e+00 -5.16355157e-01 9.58054736e-02 3.09724450e-01
5.73847830e-01 -1.17320442e+00 9.08162117e-01 3.77020836e-01
1.13903821e+00 -9.72934961e-01 4.59247351e-01 -1.54947519e-01
-2.13695335e+00 1.31665617e-01 -1.00467049e-01 2.74159402e-01
2.02479705e-01 4.00134742e-01 -5.90276480e-01 1.12888789e+00
4.31188941e-01 6.87138915e-01 -7.55349278e-01 5.96246958e-01
-8.90377879e-01 2.13403851e-01 -4.18534130e-02 4.15683717e-01
2.54347444e-01 -3.47288579e-01 5.91564775e-01 7.75291204e-01
4.44069088e-01 4.60363440e-02 3.34769309e-01 1.38420796e+00
-4.58514243e-01 2.15228070e-02 -8.91896784e-01 1.22112595e-01
5.18717289e-01 1.48138714e+00 -8.77380371e-01 2.72559980e-03
-8.92755315e-02 1.37816179e+00 6.11353159e-01 4.26802963e-01
-1.02652764e+00 -4.21293169e-01 5.69174290e-01 5.24417698e-01
5.34021795e-01 -5.59666567e-02 1.01002723e-01 -1.02370596e+00
2.08854392e-01 -6.52917862e-01 2.72890091e-01 -1.02093267e+00
-1.28483927e+00 8.54444683e-01 -1.50697917e-01 -9.77416992e-01
-7.15816095e-02 -1.88477144e-01 -1.04220068e+00 9.13456559e-01
-1.33382475e+00 -2.22794127e+00 -9.88242984e-01 7.61338294e-01
1.46198958e-01 1.39891785e-02 6.79716051e-01 2.28997111e-01
-6.65664852e-01 8.68280828e-01 -5.18702984e-01 4.38338220e-01
2.06724659e-01 -1.31085587e+00 8.48492503e-01 1.16280174e+00
7.27032721e-02 2.75558650e-01 2.94223964e-01 -8.51099014e-01
-1.35906112e+00 -1.90467334e+00 6.47135973e-01 -5.85003234e-02
2.36547783e-01 -7.61216640e-01 -4.72995907e-01 9.96020019e-01
3.25347334e-01 4.03931409e-01 1.92574978e-01 -2.12050572e-01
-4.25656110e-01 -2.04092398e-01 -1.24139702e+00 5.68681717e-01
1.46981406e+00 -5.26965559e-01 2.55438060e-01 5.93716621e-01
1.08846116e+00 -7.10534513e-01 -8.23072255e-01 6.05996311e-01
3.00376415e-01 -8.17730188e-01 1.06918955e+00 -2.63827294e-01
6.26259089e-01 -4.36775625e-01 -1.81640044e-01 -1.62817240e+00
-9.04764831e-01 -8.39662552e-01 -1.62183687e-01 1.32389748e+00
8.96924511e-02 -4.80310678e-01 6.75638378e-01 1.39136821e-01
-2.49352857e-01 -8.48093331e-01 -6.75832808e-01 -6.04466081e-01
-3.38226140e-01 1.01115078e-01 1.00179553e+00 9.01067913e-01
-5.79992890e-01 7.84197450e-01 -4.64505106e-01 5.99579751e-01
7.75860429e-01 1.70942470e-01 7.83456743e-01 -8.86057913e-01
-3.52206498e-01 -2.62892604e-01 -9.79388595e-01 -7.33707309e-01
3.96475375e-01 -1.14262199e+00 -2.19291508e-01 -1.89188981e+00
1.55861333e-01 -2.01142684e-01 8.17017406e-02 3.90718699e-01
-4.66135651e-01 4.64284897e-01 2.44886771e-01 -4.40768272e-01
-2.37998128e-01 9.82970476e-01 1.51806521e+00 -6.73688233e-01
-7.29571655e-02 -2.97355115e-01 -7.47581840e-01 3.62975478e-01
4.59060967e-01 -1.05558448e-01 -8.28496456e-01 -3.56708229e-01
8.77667516e-02 -1.25992760e-01 8.87425423e-01 -1.21226728e+00
2.73962989e-02 1.87143266e-01 4.76555794e-01 -3.46159935e-01
2.88558602e-01 -7.11575031e-01 6.69795275e-01 4.04753536e-01
-4.94872369e-02 1.18002638e-01 9.41404700e-02 8.32653403e-01
-1.67109743e-02 6.87612951e-01 8.79418910e-01 -1.77203998e-01
-4.93040383e-01 8.43415260e-01 5.79218328e-01 1.63644731e-01
1.47453856e+00 -7.60952905e-02 -3.09770018e-01 -6.98471189e-01
-7.84647465e-01 3.36356133e-01 5.22611678e-01 4.11664546e-01
8.27806652e-01 -1.87194228e+00 -9.55010056e-01 3.91450405e-01
2.41081059e-01 3.60935837e-01 5.39935529e-01 3.86660367e-01
-6.65142119e-01 8.60799998e-02 -5.22366464e-02 -2.93548465e-01
-1.19408929e+00 6.08310759e-01 4.93077606e-01 -6.90938413e-01
-7.20055342e-01 1.14140666e+00 6.78773582e-01 -5.20610511e-01
-7.75605217e-02 -3.40568751e-01 2.60164559e-01 -3.96095157e-01
-1.25449419e-01 2.22919643e-01 -2.87972558e-02 -1.00175548e+00
-2.20013872e-01 4.96039301e-01 3.14278454e-01 4.35113549e-01
1.24047363e+00 6.01907372e-02 -8.53909850e-02 -1.79822519e-01
1.13552904e+00 -1.26471683e-01 -1.04710793e+00 -3.99286747e-02
-7.21666932e-01 -5.41849971e-01 1.34239480e-01 -6.26707971e-01
-1.74524689e+00 6.49934232e-01 5.13030708e-01 1.34344682e-01
1.30178297e+00 3.48983216e-03 1.04540741e+00 -2.34502867e-01
4.29329664e-01 -4.33033675e-01 2.33791113e-01 -8.81303027e-02
1.32406569e+00 -9.40790355e-01 7.14894757e-02 -1.15438175e+00
-4.44452792e-01 5.75172961e-01 8.57756317e-01 -4.33799595e-01
6.05292797e-01 -5.40399142e-02 -6.77702069e-01 -4.98129874e-01
-4.00907040e-01 -3.87935281e-01 6.90686285e-01 9.35910821e-01
8.63408446e-02 5.46334565e-01 2.09344029e-01 4.88108039e-01
-5.39121985e-01 -3.96980703e-01 2.61402485e-04 4.59302425e-01
2.33417913e-01 -7.89381683e-01 1.84761044e-02 2.81789094e-01
3.05794418e-01 -3.07832807e-01 -5.17189026e-01 9.65650320e-01
4.25621808e-01 8.37495267e-01 6.62172213e-02 -8.92133772e-01
6.33094490e-01 -5.96376240e-01 6.20779395e-01 -6.31282330e-01
-5.39747119e-01 -7.76194269e-03 3.93487662e-02 -5.78418016e-01
-9.15576294e-02 -9.99694094e-02 -8.17575872e-01 -7.12167501e-01
-2.92715579e-01 -2.01527879e-01 -4.09430452e-02 4.14030939e-01
5.84230065e-01 1.18689537e+00 8.12284648e-01 -8.61518502e-01
4.96163890e-02 -9.13243175e-01 -8.91033232e-01 6.67577744e-01
5.59654050e-02 -6.73740089e-01 -1.99928582e-01 6.37816191e-02] | [11.647628784179688, -0.5151149034500122] |
daa54eef-25d7-4609-baa8-afda1e4a8c54 | free-lunch-robust-cross-lingual-transfer-via | 2305.16834 | null | https://arxiv.org/abs/2305.16834v1 | https://arxiv.org/pdf/2305.16834v1.pdf | Free Lunch: Robust Cross-Lingual Transfer via Model Checkpoint Averaging | Massively multilingual language models have displayed strong performance in zero-shot (ZS-XLT) and few-shot (FS-XLT) cross-lingual transfer setups, where models fine-tuned on task data in a source language are transferred without any or with only a few annotated instances to the target language(s). However, current work typically overestimates model performance as fine-tuned models are frequently evaluated at model checkpoints that generalize best to validation instances in the target languages. This effectively violates the main assumptions of "true" ZS-XLT and FS-XLT. Such XLT setups require robust methods that do not depend on labeled target language data for validation and model selection. In this work, aiming to improve the robustness of "true" ZS-XLT and FS-XLT, we propose a simple and effective method that averages different checkpoints (i.e., model snapshots) during task fine-tuning. We conduct exhaustive ZS-XLT and FS-XLT experiments across higher-level semantic tasks (NLI, extractive QA) and lower-level token classification tasks (NER, POS). The results indicate that averaging model checkpoints yields systematic and consistent performance gains across diverse target languages in all tasks. Importantly, it simultaneously substantially desensitizes XLT to varying hyperparameter choices in the absence of target language validation. We also show that checkpoint averaging benefits performance when further combined with run averaging (i.e., averaging the parameters of models fine-tuned over independent runs). | ['Goran Glavaš', 'Ivan Vulić', 'Fabian David Schmidt'] | 2023-05-26 | null | null | null | null | ['cross-lingual-transfer'] | ['natural-language-processing'] | [ 2.31650434e-02 -3.93868506e-01 -2.03852862e-01 -4.03935760e-01
-1.62313414e+00 -9.20722008e-01 6.85262501e-01 7.73652792e-02
-7.35055804e-01 1.08340693e+00 -2.49422103e-01 -5.41246831e-01
-1.17600068e-01 -3.26480210e-01 -8.39057088e-01 -4.87673074e-01
2.55322665e-01 8.68582606e-01 1.83507174e-01 -4.06491131e-01
-1.51170790e-01 1.25138655e-01 -1.10758078e+00 4.11741227e-01
1.13538837e+00 4.57667381e-01 3.90911192e-01 5.27313828e-01
-2.46800661e-01 4.18612540e-01 -7.31062412e-01 -6.99345171e-01
1.58949643e-01 -8.17219839e-02 -8.87781143e-01 -5.34136951e-01
4.49526072e-01 2.88003117e-01 2.62322932e-01 1.02694988e+00
6.20480001e-01 1.35090515e-01 5.15181065e-01 -1.33016121e+00
-4.92021054e-01 8.93239260e-01 -4.30906057e-01 2.37383470e-02
1.41691536e-01 4.77081686e-01 7.88908422e-01 -8.09650064e-01
7.00377524e-01 1.42779970e+00 9.53113198e-01 5.73321939e-01
-1.43314660e+00 -9.31225300e-01 1.53196841e-01 8.04459397e-03
-1.42946029e+00 -7.95874536e-01 2.00887516e-01 -3.99615198e-01
1.50161791e+00 1.90334454e-01 3.11854128e-02 1.47519493e+00
3.64927977e-01 5.22492170e-01 1.64247429e+00 -6.46996796e-01
2.15471059e-01 4.75518316e-01 3.72998327e-01 3.36248189e-01
2.73996443e-01 1.31673813e-01 -7.45882571e-01 -2.61269301e-01
6.99189901e-02 -7.18876541e-01 -2.70959157e-02 -4.23771329e-02
-1.46149385e+00 6.20703697e-01 -9.44944322e-02 6.59492791e-01
-3.47335696e-01 -2.88209319e-03 9.40904915e-01 6.33523822e-01
6.08719349e-01 6.55440569e-01 -1.12900019e+00 -4.47432369e-01
-9.56328571e-01 3.54269594e-02 6.39985204e-01 1.16084862e+00
8.75161529e-01 1.69759780e-01 -5.32433808e-01 1.16456258e+00
-2.72347599e-01 8.11051548e-01 7.58074939e-01 -4.91335958e-01
7.04911411e-01 2.67407894e-01 6.95893764e-02 2.25373972e-02
-3.03841501e-01 -4.93528515e-01 -4.79146868e-01 -1.96361884e-01
4.40786749e-01 -4.42210019e-01 -9.88991797e-01 2.11256123e+00
1.94785774e-01 -1.66575238e-01 4.69682008e-01 4.40408081e-01
4.67174917e-01 5.39556980e-01 5.79595387e-01 -3.44433308e-01
1.46262538e+00 -8.17153275e-01 -6.36984229e-01 -3.75910878e-01
1.33182216e+00 -8.13295603e-01 1.92542827e+00 2.44956166e-01
-7.66964436e-01 -5.31503081e-01 -6.69850826e-01 7.79208019e-02
-5.94718158e-01 6.49395436e-02 4.99279678e-01 7.14436173e-01
-1.12255859e+00 3.27930152e-01 -7.14464068e-01 -6.32312059e-01
-2.77649201e-02 2.91754872e-01 -5.58765173e-01 -8.76784623e-02
-1.67451990e+00 1.21684468e+00 7.66100109e-01 -2.06254482e-01
-9.39383149e-01 -9.56179261e-01 -7.78530598e-01 5.50833205e-03
4.95151103e-01 -5.42219996e-01 1.55902374e+00 -9.37563539e-01
-1.51150262e+00 8.34119320e-01 -3.64864498e-01 -4.95013863e-01
5.40162206e-01 -2.47714549e-01 -4.35719520e-01 -4.90165651e-01
3.02715182e-01 6.38185143e-01 4.74464625e-01 -1.24778354e+00
-5.97720206e-01 -1.74910992e-01 -5.39824702e-02 2.55445004e-01
-4.02022928e-01 4.33386773e-01 -3.47061664e-01 -3.55322689e-01
-6.05913103e-01 -1.04397094e+00 1.22208476e-01 -8.63657176e-01
-4.26244259e-01 -4.67119783e-01 5.33197105e-01 -7.69786894e-01
1.16027641e+00 -2.01064110e+00 -6.22405224e-02 -1.64437979e-01
-3.93520504e-01 5.33636868e-01 -3.82689238e-01 5.86179674e-01
8.74894261e-02 3.02691847e-01 -2.40495786e-01 -4.49028522e-01
2.47396082e-01 3.53525758e-01 -7.85783678e-02 -2.13613547e-02
3.38485353e-02 1.12866783e+00 -8.59839857e-01 -6.06741250e-01
1.00514755e-01 2.35758856e-01 -2.09672719e-01 4.53451909e-02
-4.14319962e-01 4.74638134e-01 -2.10150152e-01 3.29157323e-01
2.94160426e-01 -1.61160588e-01 2.36648858e-01 -1.47398293e-01
-2.26356342e-01 4.74488169e-01 -7.53380239e-01 1.73353219e+00
-1.06041443e+00 2.36562669e-01 -1.95854649e-01 -6.13357425e-01
6.49266899e-01 5.13518691e-01 1.02906585e-01 -9.87619579e-01
-1.55198559e-01 6.02567554e-01 1.38108924e-01 -3.02821130e-01
4.78273481e-01 -3.70459586e-01 -5.34762025e-01 4.66446072e-01
3.89308870e-01 -4.70444784e-02 3.13970566e-01 1.77666411e-01
8.30281854e-01 1.66689634e-01 3.98032695e-01 -5.11781096e-01
3.31291974e-01 3.14816177e-01 5.16684592e-01 8.90295029e-01
-1.77635342e-01 -1.16563328e-01 2.52400428e-01 5.73651493e-02
-1.06959510e+00 -9.64299083e-01 -2.84596473e-01 1.65514362e+00
-2.78456092e-01 -3.95854175e-01 -1.12282932e+00 -8.82108152e-01
-6.74906522e-02 1.41890562e+00 -4.30921137e-01 -2.97436267e-01
-5.11433244e-01 -7.58735776e-01 1.00125825e+00 2.51371980e-01
4.82786536e-01 -1.17496789e+00 -2.53486842e-01 2.28163600e-01
-3.60050440e-01 -1.13408184e+00 -5.46028554e-01 5.35739481e-01
-5.72026908e-01 -7.16464102e-01 -5.45741081e-01 -5.43082952e-01
2.18562603e-01 -1.15376376e-01 1.21271217e+00 -4.41656440e-01
1.69477716e-01 3.08381379e-01 -2.76569575e-01 -3.59338343e-01
-8.17406833e-01 5.83132386e-01 3.17927808e-01 -2.11874679e-01
5.28335989e-01 -4.18181717e-02 2.43531793e-01 2.28753462e-01
-5.38603485e-01 7.83264861e-02 6.27468228e-01 9.18298066e-01
6.00642860e-01 -1.15256742e-01 9.03162420e-01 -1.22050631e+00
9.09874141e-01 -3.41332078e-01 -4.61017907e-01 9.56037223e-01
-7.86563277e-01 2.20719010e-01 8.27375352e-01 -5.83267093e-01
-1.30898225e+00 -4.29588139e-01 -6.05778657e-02 -5.39467096e-01
-3.22265476e-01 6.76902175e-01 -2.26391837e-01 5.07204868e-02
7.70413280e-01 1.86279327e-01 -3.61912519e-01 -6.36845112e-01
3.75742346e-01 8.10900331e-01 2.67850906e-01 -9.64543104e-01
5.66928387e-01 -2.06773669e-01 -6.41151488e-01 -6.59377754e-01
-8.94243300e-01 -2.50664413e-01 -6.79338098e-01 5.64081706e-02
7.16636658e-01 -9.47422981e-01 -3.91962022e-01 6.12093449e-01
-1.01772332e+00 -8.69651973e-01 -1.91779047e-01 5.14611840e-01
-4.64417368e-01 -3.09312511e-02 -6.26787186e-01 -7.88549423e-01
-5.29784977e-01 -1.26718938e+00 1.28108442e+00 -9.10491571e-02
-4.40451860e-01 -1.31508040e+00 1.61492094e-01 3.30998629e-01
5.25833428e-01 -1.86403245e-01 1.12109804e+00 -9.14177954e-01
-7.86377788e-02 -2.77264602e-02 1.34848170e-02 4.68025237e-01
1.17052592e-01 -1.33115977e-01 -1.20703065e+00 -6.55341089e-01
-1.86318517e-01 -6.42301917e-01 5.15348673e-01 2.86177635e-01
7.29351342e-01 -2.34988302e-01 -2.52108186e-01 4.21688497e-01
1.32497966e+00 1.27797589e-01 2.36023650e-01 4.85970646e-01
5.78163862e-01 4.98752564e-01 8.27610970e-01 -2.12654084e-01
3.67038369e-01 8.88190687e-01 -3.96811604e-01 -7.91702792e-02
-2.38769755e-01 -2.58138418e-01 8.30476284e-01 1.13500631e+00
2.29751751e-01 -2.44253874e-01 -1.22512090e+00 6.58917010e-01
-1.55136859e+00 -5.82234383e-01 4.72791865e-02 2.48581219e+00
1.29785550e+00 1.69682428e-01 -1.55438334e-01 -2.43736029e-01
7.25839376e-01 -2.04620123e-01 -6.16909444e-01 -6.49037540e-01
-2.51511306e-01 4.04553473e-01 4.77534205e-01 6.48418725e-01
-8.23267400e-01 1.71250808e+00 5.56612253e+00 1.29293430e+00
-1.35553491e+00 8.05895209e-01 3.20256621e-01 -4.35135476e-02
-2.09972993e-01 7.01385364e-02 -1.10391629e+00 4.89283085e-01
1.50329638e+00 -6.14108801e-01 4.80744034e-01 5.99038363e-01
1.34283975e-01 -3.66215035e-02 -1.11000109e+00 5.98432541e-01
-2.82035321e-01 -8.88725340e-01 1.07486568e-01 -1.35026038e-01
7.93778300e-01 5.38303077e-01 -1.69947390e-02 9.36078966e-01
6.31885886e-01 -8.87610614e-01 8.72352719e-01 2.13578343e-01
1.34747958e+00 -6.92785740e-01 7.42334366e-01 6.05722964e-01
-9.98187184e-01 1.76576570e-01 -2.40507826e-01 3.59860152e-01
1.87673777e-01 3.90660703e-01 -1.04767299e+00 1.00995648e+00
6.78325832e-01 3.96696121e-01 -7.14342892e-01 5.05244374e-01
-1.39831305e-01 9.23175752e-01 -2.50294000e-01 1.48643032e-01
3.23410869e-01 8.42117518e-02 4.17511195e-01 1.56504524e+00
3.26526999e-01 -3.89979273e-01 1.75285235e-01 6.51185453e-01
-2.05168426e-02 4.11488175e-01 -5.94561040e-01 -5.89168184e-02
8.20254385e-01 1.15580690e+00 -3.29970360e-01 -5.80507815e-01
-2.23907575e-01 7.40769863e-01 5.69827855e-01 5.55728257e-01
-7.70607054e-01 -2.35688686e-01 6.06520414e-01 -1.36390761e-01
-8.61485228e-02 -1.70516670e-01 -1.67332053e-01 -1.20480466e+00
3.67004983e-02 -1.15918338e+00 4.51791137e-01 -6.35308146e-01
-1.48888755e+00 8.74330640e-01 3.23726118e-01 -8.36166322e-01
-3.97975087e-01 -4.42395926e-01 -2.08008155e-01 1.17174053e+00
-1.58685124e+00 -1.33755505e+00 1.19015887e-01 7.63580561e-01
6.48119569e-01 -1.27124175e-01 1.03149176e+00 3.01174313e-01
-6.59145653e-01 1.04648745e+00 3.84886056e-01 -1.05797742e-02
1.21458483e+00 -1.07664859e+00 5.33995450e-01 6.97043777e-01
1.02756053e-01 8.95435810e-01 5.42863250e-01 -8.10440481e-01
-1.15799499e+00 -1.34977829e+00 1.30378747e+00 -5.72769225e-01
7.92567551e-01 -5.95601559e-01 -1.07599795e+00 9.41765308e-01
2.62422651e-01 -3.50581318e-01 3.93550277e-01 5.20033598e-01
-3.93858016e-01 -1.17757618e-01 -1.00053096e+00 5.20168126e-01
7.54107058e-01 -8.26019287e-01 -4.83760774e-01 6.23335183e-01
8.77832830e-01 -2.96717942e-01 -1.11511731e+00 3.51948559e-01
2.42432460e-01 -6.33974910e-01 6.20718718e-01 -8.37858081e-01
-2.37908408e-01 2.10657641e-02 -2.23912001e-01 -1.70104277e+00
-5.67081273e-02 -5.63618183e-01 4.97471213e-01 1.41234303e+00
9.17163670e-01 -1.08097637e+00 -1.35117784e-01 3.78782541e-01
-3.59870702e-01 -3.47439766e-01 -1.22561502e+00 -1.30408657e+00
5.20756543e-01 -5.44704974e-01 5.60415804e-01 1.41851366e+00
-3.03346604e-01 4.80303138e-01 -2.19685018e-01 3.61263640e-02
7.29830861e-01 -2.74373114e-01 8.10871542e-01 -1.04930604e+00
-1.37170658e-01 -2.65919954e-01 2.01080367e-01 -3.45839381e-01
5.66300631e-01 -1.22692275e+00 1.84965342e-01 -1.29166412e+00
2.19023928e-01 -8.96388352e-01 -4.29330200e-01 8.99012208e-01
-4.26960349e-01 -5.67997107e-03 2.25907639e-01 2.91615367e-01
-4.66773540e-01 3.77832860e-01 9.94597733e-01 8.89063552e-02
-1.78401336e-01 -2.75571227e-01 -4.85440016e-01 3.88224483e-01
7.66774535e-01 -6.98706806e-01 -3.80337358e-01 -6.51932657e-01
4.67118807e-02 -2.56195404e-02 2.86346018e-01 -8.29465568e-01
1.90782454e-02 -1.72857150e-01 -9.74910632e-02 -8.43180567e-02
1.81465566e-01 -3.95298690e-01 3.32335830e-01 3.38523805e-01
-5.18979609e-01 9.99916643e-02 5.60049474e-01 1.91833451e-01
-8.81972611e-02 -1.91461593e-01 9.06844676e-01 -1.03147998e-01
-7.64111400e-01 6.54529855e-02 -2.81103104e-02 3.77419621e-01
9.76033509e-01 -1.09047882e-01 -4.64060843e-01 4.30946425e-02
-6.12337708e-01 3.62264782e-01 4.94889915e-01 6.60349548e-01
-9.14994031e-02 -1.11788321e+00 -9.23159480e-01 1.24008432e-01
4.48811561e-01 -2.16913611e-01 3.11934799e-01 1.17682374e+00
5.68969361e-02 8.98224354e-01 -1.39697725e-02 -7.45687246e-01
-1.20967209e+00 4.36262339e-01 4.39633608e-01 -7.19852090e-01
-3.52621943e-01 7.40620315e-01 3.26463491e-01 -1.00030696e+00
-9.90892574e-02 -1.33689329e-01 2.56084114e-01 -6.24650382e-02
1.20331101e-01 3.26300077e-02 4.54302192e-01 -6.32072926e-01
-4.19264197e-01 3.15533638e-01 -3.97593409e-01 -3.06652963e-01
9.72678363e-01 -1.10524349e-01 -2.00228952e-02 9.72313881e-01
9.70897079e-01 4.95916978e-02 -9.54617918e-01 -4.34190333e-01
3.62768322e-01 2.03430057e-02 -2.18096599e-02 -1.31845570e+00
-5.81079006e-01 9.86268938e-01 4.36454177e-01 -1.48069710e-01
7.95828462e-01 6.64813258e-03 7.18765616e-01 3.89092326e-01
9.65621233e-01 -1.17576540e+00 -4.59846914e-01 7.89705396e-01
6.34253323e-01 -1.13574994e+00 -6.02708042e-01 -1.63830048e-03
-9.50109839e-01 6.27216280e-01 7.20357955e-01 4.69240129e-01
1.45528689e-01 3.50995958e-01 3.06539923e-01 -2.60406062e-02
-1.16922748e+00 -1.66672692e-01 1.82138160e-01 4.97523427e-01
5.92891455e-01 4.28808361e-01 -1.80602476e-01 6.74741805e-01
-3.81283909e-01 -5.87002449e-02 -3.62877846e-02 7.61611879e-01
-2.02821866e-01 -1.28497708e+00 -3.67704332e-01 3.34184587e-01
-2.48953298e-01 -6.28135920e-01 -3.72775137e-01 1.13601017e+00
3.61196548e-02 8.11336994e-01 -1.94600254e-01 -1.85709968e-01
4.68513370e-01 7.80172288e-01 5.27950406e-01 -7.30471969e-01
-1.19301605e+00 3.33222710e-02 3.88837248e-01 -3.76735985e-01
-1.27918795e-01 -7.21207500e-01 -1.04590833e+00 -2.95201480e-01
-4.98217672e-01 4.71897900e-01 7.17582166e-01 1.09254444e+00
4.36454564e-01 4.80867952e-01 2.31726751e-01 -3.99978042e-01
-9.32024479e-01 -1.44042873e+00 -3.99062932e-01 3.60761762e-01
-5.54102585e-02 -6.37620926e-01 -2.69765913e-01 4.73827235e-02] | [11.230829238891602, 9.942513465881348] |
a95222d4-69b4-417f-b701-248bdafd850e | guided-patch-wise-nonlocal-sar-despeckling | 1811.11872 | null | http://arxiv.org/abs/1811.11872v1 | http://arxiv.org/pdf/1811.11872v1.pdf | Guided patch-wise nonlocal SAR despeckling | We propose a new method for SAR image despeckling which leverages information
drawn from co-registered optical imagery. Filtering is performed by plain
patch-wise nonlocal means, operating exclusively on SAR data. However, the
filtering weights are computed by taking into account also the optical guide,
which is much cleaner than the SAR data, and hence more discriminative. To
avoid injecting optical-domain information into the filtered image, a
SAR-domain statistical test is preliminarily performed to reject right away any
risky predictor. Experiments on two SAR-optical datasets prove the proposed
method to suppress very effectively the speckle, preserving structural details,
and without introducing visible filtering artifacts. Overall, the proposed
method compares favourably with all state-of-the-art despeckling filters, and
also with our own previous optical-guided filter. | ['Sergio Vitale', 'Luisa Verdoliva', 'Giuseppe Scarpa', 'Davide Cozzolino', 'Giovanni Poggi'] | 2018-11-28 | null | null | null | null | ['sar-image-despeckling'] | ['computer-vision'] | [ 7.45272994e-01 -8.30428079e-02 3.31713289e-01 -2.12928727e-01
-6.77105486e-01 -4.96940941e-01 7.20409989e-01 -2.88650781e-01
-5.81453681e-01 8.91620874e-01 4.98624057e-01 -6.23991117e-02
-5.51417291e-01 -8.19298804e-01 -2.45304704e-01 -1.26965845e+00
1.00852393e-01 -2.86267810e-02 1.83583692e-01 -2.83731550e-01
2.45476991e-01 8.08548987e-01 -1.53433490e+00 1.20409563e-01
1.27858853e+00 1.15757096e+00 3.03835809e-01 3.92287523e-01
5.60562134e-01 6.07783794e-01 -2.74446428e-01 -1.40527904e-01
7.82481074e-01 -4.22555804e-01 -3.56340259e-01 5.72912097e-01
1.01183689e+00 -1.84894517e-01 -2.29964793e-01 1.34888577e+00
2.26661265e-01 2.26995721e-01 4.86274064e-01 -1.50771486e-02
-7.56027102e-01 5.58195226e-02 -5.48524201e-01 -4.42732079e-03
9.99233052e-02 4.19735879e-01 8.77938867e-01 -9.49281454e-01
6.67105317e-01 7.37336993e-01 6.86438382e-01 4.66202982e-02
-1.64752543e+00 -1.60445958e-01 -1.23216368e-01 -1.18295616e-02
-1.25299859e+00 -6.77401364e-01 8.88783813e-01 -4.31315005e-01
3.45480382e-01 5.90163410e-01 5.96820235e-01 7.64826655e-01
4.01021391e-01 2.81962246e-01 1.84951198e+00 -5.47757924e-01
1.86159566e-01 -2.74498835e-02 1.56370163e-01 4.26094413e-01
3.20217371e-01 7.00991213e-01 -3.30089808e-01 -1.67397037e-01
5.09552538e-01 -2.44242139e-02 -7.80457556e-01 -4.04462785e-01
-1.11307991e+00 6.28905952e-01 5.54382145e-01 4.08436060e-01
-6.42418325e-01 -4.17034566e-01 -2.59464711e-01 3.81741464e-01
8.63900721e-01 5.88969290e-01 -2.26500884e-01 7.64666557e-01
-1.57064617e+00 6.47233203e-02 4.34974104e-01 3.07360172e-01
1.01756704e+00 3.42006326e-01 -3.90639067e-01 6.89663172e-01
2.76364863e-01 9.10876155e-01 -5.03113773e-03 -7.04042375e-01
-8.44843090e-02 2.76700944e-01 3.29678029e-01 -1.03193164e+00
-2.66538382e-01 -9.36710060e-01 -1.16790164e+00 7.24599183e-01
3.01839292e-01 5.34516945e-03 -1.14373124e+00 1.16475391e+00
6.39544576e-02 2.09314048e-01 2.05622762e-02 1.24063957e+00
3.66106004e-01 4.04716730e-01 -2.80266374e-01 -5.56941867e-01
1.14423478e+00 -5.99441350e-01 -6.68518603e-01 -4.22686964e-01
-8.84657949e-02 -1.05545139e+00 5.61012626e-01 6.58127010e-01
-7.21204340e-01 -6.37229800e-01 -1.08245134e+00 1.79236531e-01
4.48042676e-02 4.60412174e-01 3.50460798e-01 7.10872710e-01
-1.08802056e+00 7.02077985e-01 -5.20851612e-01 -3.20935994e-01
3.55647475e-01 7.72520294e-03 -3.81647259e-01 -1.79301798e-01
-7.78240979e-01 1.08615339e+00 2.45792732e-01 5.00471711e-01
-7.62052119e-01 -6.29242301e-01 -6.61479712e-01 -1.73818082e-01
4.27613080e-01 -5.99259913e-01 3.29184920e-01 -1.01065373e+00
-1.61170352e+00 8.30717146e-01 -3.00422758e-01 -7.17782378e-01
6.29417002e-01 -5.18145621e-01 -7.76031852e-01 2.39156097e-01
-1.89453557e-01 1.00342460e-01 1.59844053e+00 -1.51870823e+00
-2.09595099e-01 -3.37007761e-01 -4.00436133e-01 -1.28186509e-01
3.91672878e-03 -2.30674699e-01 6.68337569e-02 -9.22341585e-01
3.10186148e-01 -7.45460391e-01 -4.76358980e-01 -8.90261903e-02
-5.08976579e-01 7.80888319e-01 6.67001724e-01 -1.00647271e+00
1.04772449e+00 -2.54518247e+00 -9.04115289e-03 5.66507280e-01
2.36728147e-01 4.20705408e-01 -4.52790648e-01 4.50432330e-01
-1.60292968e-01 -5.00896573e-01 -7.55493820e-01 -4.50153574e-02
-5.27366996e-01 -2.05909312e-01 -5.76638401e-01 9.31937873e-01
2.13271320e-01 5.32405555e-01 -5.97719014e-01 -8.16398114e-02
4.19708341e-01 5.37048459e-01 -3.79681408e-01 -7.55809131e-04
-3.95893082e-02 8.43106568e-01 -3.37425202e-01 6.56940579e-01
1.33905518e+00 2.32219651e-01 1.45050928e-01 -6.20867848e-01
-5.16576171e-01 -2.22395584e-01 -1.08992338e+00 1.30362070e+00
-2.86400616e-01 5.57946324e-01 3.46879900e-01 -1.06762207e+00
1.28760755e+00 -5.84341288e-02 3.07769179e-01 -6.83483720e-01
9.51983221e-03 2.79482514e-01 -2.04278186e-01 -1.27722189e-01
4.54914033e-01 -1.90487072e-01 4.14953172e-01 8.05944353e-02
-1.86034590e-02 -2.80483961e-01 -6.46884665e-02 -1.91119879e-01
9.79972541e-01 1.20966345e-01 3.87662858e-01 -8.56671095e-01
9.42964315e-01 1.12138577e-01 5.05804121e-01 9.36429799e-01
5.44573776e-02 7.90699422e-01 -3.05703372e-01 -5.84451556e-01
-7.89248466e-01 -1.27698886e+00 -3.71008724e-01 3.19933444e-01
2.66247451e-01 -1.23072259e-01 -6.28877878e-01 -5.30852795e-01
-6.79380149e-02 6.57656848e-01 -5.26084185e-01 5.07924072e-02
-4.02661830e-01 -8.87642920e-01 8.43229741e-02 -2.29143441e-01
8.68198633e-01 -6.51709318e-01 -5.43779790e-01 2.75781184e-01
5.29811345e-03 -1.09922922e+00 -1.94404259e-01 -4.52457666e-02
-1.14511609e+00 -1.07829785e+00 -6.83728755e-01 -2.89284199e-01
7.42709637e-01 7.04146802e-01 1.06501031e+00 2.80734641e-03
-5.17697811e-01 1.58079579e-01 -3.41338605e-01 9.11906362e-02
-2.29130074e-01 -4.49225187e-01 -1.51881292e-01 7.87802815e-01
1.38407260e-01 -6.90248013e-01 -6.33307695e-01 3.09915423e-01
-9.99444604e-01 -2.75146812e-02 1.01325655e+00 1.21016788e+00
5.75727463e-01 4.63820845e-01 -1.09325446e-01 -9.38757360e-01
3.44838440e-01 2.25428849e-01 -8.42131019e-01 1.78348675e-01
-6.33991838e-01 1.66005239e-01 6.58087373e-01 -1.25992134e-01
-1.45998681e+00 3.16658735e-01 1.45682395e-01 -8.73663574e-02
-4.86847758e-01 5.21885872e-01 -9.25509110e-02 -5.40625632e-01
8.07006478e-01 4.50991839e-01 1.58547223e-01 -8.37537587e-01
2.82423675e-01 3.95761043e-01 7.70619154e-01 -1.32995844e-02
1.52065229e+00 1.02323651e+00 2.31582776e-01 -1.50321150e+00
-8.86231482e-01 -5.29887676e-01 -7.12841332e-01 -1.84719682e-01
7.95972526e-01 -9.46632564e-01 -3.15853626e-01 6.59830153e-01
-8.60513151e-01 -1.43662885e-01 -4.47297901e-01 6.60944223e-01
-3.04369718e-01 4.80922639e-01 -4.02697563e-01 -8.75613689e-01
-1.84528932e-01 -7.88788676e-01 9.37177896e-01 8.50850642e-02
1.93045139e-01 -7.88781881e-01 7.18050450e-02 4.35166001e-01
7.39721477e-01 1.79559261e-01 4.95727122e-01 -1.37817144e-01
-9.26520586e-01 -1.43306404e-01 -3.56888115e-01 7.46955216e-01
1.60277858e-01 -1.90148592e-01 -1.17996144e+00 -4.22056675e-01
4.85961825e-01 1.48183659e-01 1.51702130e+00 5.27840734e-01
6.29734218e-01 -2.50267982e-01 -7.74632245e-02 8.23049724e-01
1.84633040e+00 -2.08412260e-01 1.10469103e+00 4.31289107e-01
2.88032532e-01 6.51530445e-01 6.99001849e-01 3.90711904e-01
-4.25175309e-01 6.56214416e-01 5.39054394e-01 -5.95593631e-01
-2.18893692e-01 1.18799798e-01 4.77818638e-01 2.94082582e-01
-5.04228771e-01 -1.53485239e-01 -3.09231758e-01 3.34825486e-01
-1.67452502e+00 -1.11390448e+00 -5.04123569e-01 2.36577535e+00
4.84603882e-01 -1.22088030e-01 -3.64107788e-01 1.12609603e-01
3.86138856e-01 7.28513122e-01 -1.28686056e-01 1.59677729e-01
-7.99726188e-01 6.94803178e-01 9.95830059e-01 8.96555543e-01
-1.46473527e+00 8.88956487e-01 6.31230879e+00 8.49362314e-01
-1.15300608e+00 1.18725561e-02 2.51762062e-01 3.19961309e-01
-2.54311532e-01 2.95984328e-01 -4.87934798e-01 1.61695987e-01
4.72931266e-01 2.14214027e-01 5.09789288e-01 4.64828044e-01
4.76484060e-01 -5.07636726e-01 -5.12265742e-01 6.68635666e-01
2.39443541e-01 -1.28384233e+00 4.38119806e-02 1.89170852e-01
7.36313462e-01 2.61134822e-02 9.06375498e-02 -4.89966512e-01
1.41376957e-01 -8.42557251e-01 6.59058332e-01 1.09068871e+00
5.00751376e-01 -5.56023121e-01 8.14174414e-01 2.53043652e-01
-9.20994759e-01 -2.68877931e-02 -3.76752734e-01 -1.02547556e-01
1.87441900e-01 1.53195643e+00 -1.66092321e-01 1.19216418e+00
6.68351948e-01 9.06145751e-01 -7.86065161e-01 1.14689231e+00
-3.11876416e-01 5.46111226e-01 -1.67279899e-01 6.27302766e-01
1.00514263e-01 -8.64462078e-01 1.00707781e+00 1.22533226e+00
5.74555218e-01 1.91129953e-01 2.83901602e-01 8.87012005e-01
5.87581992e-01 -1.52951166e-01 -6.57888770e-01 1.98094606e-01
-1.63230434e-01 1.40685034e+00 -5.85165024e-01 -7.14653656e-02
-2.30041280e-01 1.22693574e+00 -4.21534151e-01 5.69087148e-01
-2.19172835e-01 -1.68162808e-01 7.56471217e-01 1.33332953e-01
5.37262678e-01 -4.48253363e-01 -3.09161663e-01 -1.30093408e+00
-2.26036776e-02 -8.98319006e-01 4.35144082e-02 -7.76554525e-01
-1.52476001e+00 8.27861071e-01 -2.28888109e-01 -1.74387896e+00
2.86323786e-01 -7.54803002e-01 -5.79490781e-01 1.02357149e+00
-1.92145658e+00 -1.20454729e+00 -2.66306967e-01 6.14538431e-01
1.83690548e-01 -9.31297988e-02 6.28212810e-01 3.82778198e-02
-2.10946295e-02 -1.23746939e-01 2.62390971e-01 -1.54503942e-01
8.48263383e-01 -7.54677713e-01 -3.23244222e-02 1.47446859e+00
1.26866952e-01 6.26104951e-01 1.04899466e+00 -7.08935261e-01
-1.36773694e+00 -9.96570289e-01 7.03996778e-01 -5.64856827e-02
6.60572171e-01 -1.79004982e-01 -9.18167830e-01 2.49190554e-01
4.58630472e-01 1.40270874e-01 2.82900304e-01 -1.76324040e-01
-2.94493705e-01 -4.75272804e-01 -1.10469365e+00 3.54995131e-01
9.40044880e-01 -4.40236807e-01 -7.24020541e-01 3.45151961e-01
9.95048881e-02 4.55003045e-02 -4.21079427e-01 7.25612998e-01
3.64720345e-01 -1.52987945e+00 1.28325272e+00 1.02843799e-01
1.06939927e-01 -7.78461516e-01 -2.19212770e-01 -1.48056936e+00
-7.65855134e-01 -6.88776195e-01 4.43635494e-01 1.04795194e+00
2.99075365e-01 -8.43717635e-01 6.04261816e-01 -2.19457194e-01
-2.12045491e-01 1.19285218e-01 -7.93565035e-01 -1.13276947e+00
-5.55769682e-01 -1.83761809e-02 1.57927141e-01 9.16873991e-01
-7.86638737e-01 6.40108511e-02 -7.79004395e-01 7.26111233e-01
1.31198788e+00 3.59454066e-01 5.93362510e-01 -1.55332124e+00
-3.89415979e-01 -1.93361118e-01 -3.38688344e-01 -8.88914526e-01
-1.63154341e-02 -5.49546003e-01 2.03336805e-01 -1.11789680e+00
-1.67605966e-01 -5.65913022e-02 -1.39413863e-01 1.09285794e-01
3.09807248e-02 8.49149406e-01 1.61961958e-01 3.28734428e-01
8.35609287e-02 5.29884875e-01 1.28248978e+00 -2.75841504e-01
-1.44945621e-01 -1.18979841e-01 -5.11417925e-01 8.04143727e-01
5.80635309e-01 -1.55664220e-01 -7.77807683e-02 -3.38827670e-01
-1.04851812e-01 -2.11040616e-01 8.20444286e-01 -1.32054472e+00
2.99300194e-01 -3.28766435e-01 4.42793936e-01 -4.95737225e-01
3.17213356e-01 -1.03748536e+00 5.25270462e-01 4.33031201e-01
5.75985052e-02 -6.87517464e-01 -1.00590691e-01 6.53773367e-01
-5.18344164e-01 5.63917980e-02 1.25377798e+00 -5.83931198e-03
-8.25629175e-01 4.26941598e-03 -5.05689502e-01 -3.56874704e-01
6.87016666e-01 -3.60881239e-01 -3.71648967e-01 -1.90102905e-01
-7.52208173e-01 -4.27777201e-01 6.72773182e-01 -2.51066148e-01
5.89263737e-01 -8.33014309e-01 -1.06408930e+00 7.48599887e-01
9.46397930e-02 -6.01434529e-01 5.47734737e-01 1.13194692e+00
-5.31453073e-01 1.61422089e-01 -2.72098303e-01 -4.71912980e-01
-1.15172398e+00 5.01013219e-01 1.32348835e-01 -3.74007851e-01
-9.02415335e-01 5.40989399e-01 1.55843735e-01 -5.68819121e-02
-4.25240576e-01 -1.33847401e-01 -1.97897032e-01 6.99029565e-02
7.32653558e-01 2.82181174e-01 4.13574725e-01 -6.41330481e-01
-3.73399973e-01 9.11892235e-01 1.29817739e-01 -9.37897041e-02
1.65964413e+00 -2.81607628e-01 -4.51960355e-01 -1.01411156e-01
5.66847682e-01 7.67064452e-01 -1.28461432e+00 -4.41834509e-01
1.10693254e-01 -9.78534579e-01 5.43093681e-01 -8.91261816e-01
-1.14557362e+00 5.42467177e-01 6.64010108e-01 3.17590475e-01
1.60227942e+00 -4.69039589e-01 3.38744968e-01 2.80318975e-01
4.26493347e-01 -9.00079727e-01 -3.12747866e-01 4.95860010e-01
9.53026652e-01 -1.08931792e+00 4.79994565e-01 -6.67151093e-01
-3.96893650e-01 1.17244434e+00 -1.91236675e-01 -5.82009852e-01
6.34662628e-01 1.21770203e-01 2.71189302e-01 -1.33966804e-01
-1.40848443e-01 -6.67378187e-01 4.86872762e-01 7.80551434e-01
1.11599311e-01 -1.33296121e-02 -4.18988287e-01 -3.19215842e-02
1.39987752e-01 1.35200739e-01 4.13535058e-01 6.27422631e-01
-6.48151398e-01 -1.25263774e+00 -7.64342964e-01 3.04709196e-01
-2.49526635e-01 -4.84622717e-01 -3.37140977e-01 5.91307163e-01
-3.78311891e-03 1.10008371e+00 -1.89726964e-01 -2.65933245e-01
2.89431483e-01 -2.26624310e-01 3.19079399e-01 -2.96039701e-01
-4.32948142e-01 3.44163150e-01 1.73103631e-01 -7.93579280e-01
-8.70325863e-01 -5.10174096e-01 -3.51867497e-01 -1.53819844e-01
-4.83881652e-01 5.99516258e-02 2.65425771e-01 9.14040148e-01
3.40809375e-01 1.29773870e-01 8.44278157e-01 -1.18949711e+00
-4.23732907e-01 -7.61500180e-01 -1.05950463e+00 2.54478544e-01
8.19758415e-01 -5.53072691e-01 -8.46001506e-01 1.86867654e-01] | [10.503205299377441, -2.1574974060058594] |
3c0d0372-6acf-419b-a428-53bab17d9baf | multi-agent-reinforcement-learning-with-graph | 2008.08808 | null | https://arxiv.org/abs/2008.08808v4 | https://arxiv.org/pdf/2008.08808v4.pdf | BGC: Multi-Agent Group Belief with Graph Clustering | Recent advances have witnessed that value decomposed-based multi-agent reinforcement learning methods make an efficient performance in coordination tasks. Most current methods assume that agents can make communication to assist decisions, which is impractical in some situations. In this paper, we propose a semi-communication method to enable agents can exchange information without communication. Specifically, we introduce a group concept to help agents learning a belief which is a type of consensus. With this consensus, adjacent agents tend to accomplish similar sub-tasks to achieve cooperation. We design a novel agent structure named Belief in Graph Clustering(BGC), composed of an agent characteristic module, a belief module, and a fusion module. To represent each agent characteristic, we use an MLP-based characteristic module to generate agent unique features. Inspired by the neighborhood cognitive consistency, we propose a group-based module to divide adjacent agents into a small group and minimize in-group agents' beliefs to accomplish similar sub-tasks. Finally, we use a hyper-network to merge these features and produce agent actions. To overcome the agent consistent problem brought by GAT, a split loss is introduced to distinguish different agents. Results reveal that the proposed method achieves a significant improvement in the SMAC benchmark. Because of the group concept, our approach maintains excellent performance with an increase in the number of agents. | ['Tianze Zhou', 'Chenfei Wang', 'Pan Tang', 'Fubiao Zhang'] | 2020-08-20 | null | null | null | null | ['smac-1', 'smac'] | ['playing-games', 'playing-games'] | [-3.15861225e-01 1.38261616e-01 -6.08274154e-02 -3.30959052e-01
-2.18135864e-01 -9.42987725e-02 6.76333368e-01 6.39727294e-01
-3.95747930e-01 8.36072505e-01 1.09074071e-01 3.61262709e-01
-5.01606941e-01 -1.07171071e+00 -3.56904298e-01 -1.12083733e+00
-2.05866188e-01 6.01116478e-01 4.17954117e-01 -4.40625429e-01
4.96940047e-01 -7.06940070e-02 -1.30760837e+00 1.14986941e-01
1.31819081e+00 6.58715785e-01 5.70165455e-01 9.00275484e-02
-2.07872406e-01 1.31015551e+00 -9.54174519e-01 -1.99005809e-02
1.33732364e-01 -6.96508467e-01 -8.05636883e-01 5.83332300e-01
-6.40130460e-01 -2.14792743e-01 1.51629016e-01 1.26600301e+00
5.13710380e-01 3.99680018e-01 6.52513385e-01 -1.68566883e+00
-5.26270866e-01 1.26259339e+00 -7.38968909e-01 -1.75205141e-01
4.67911363e-01 1.73319682e-01 7.08792150e-01 3.19645554e-02
3.35894793e-01 1.51942050e+00 4.06004936e-01 5.13823509e-01
-9.47544813e-01 -5.28822005e-01 6.82384133e-01 5.86275160e-01
-1.25852346e+00 -6.55309930e-02 1.05733132e+00 -9.08152759e-03
6.53511643e-01 4.67317179e-02 8.63059878e-01 5.77348769e-01
3.62887591e-01 5.86163342e-01 1.28222036e+00 -2.85170197e-01
6.86794460e-01 1.78133443e-01 2.37189867e-02 8.40078890e-01
2.54782379e-01 -1.30801767e-01 -2.71770626e-01 -1.65236384e-01
5.31492949e-01 1.01092406e-01 -2.27967158e-01 -2.64055669e-01
-1.20295882e+00 1.00906813e+00 8.03427458e-01 2.97003031e-01
-7.60161400e-01 1.47511706e-01 1.20190896e-01 6.43685997e-01
1.38150454e-01 2.28128180e-01 1.13882767e-02 2.67799973e-01
-5.73960394e-02 1.05079420e-01 8.47966194e-01 5.47303379e-01
1.03550208e+00 -5.56308553e-02 -4.15291339e-02 8.54916036e-01
6.69285059e-01 3.50359589e-01 7.07872570e-01 -1.24869764e+00
2.26797387e-01 1.00586498e+00 -6.90159276e-02 -1.28954864e+00
-5.81437051e-01 -4.94153231e-01 -1.18853915e+00 5.48379481e-01
-9.55621004e-02 -2.72207052e-01 -4.31711316e-01 1.81281042e+00
5.78989029e-01 3.10216963e-01 6.53188288e-01 8.68717670e-01
5.59105039e-01 6.12670720e-01 -1.14251107e-01 -5.96412241e-01
1.05268931e+00 -1.18300235e+00 -6.12900615e-01 1.61612570e-01
5.55284679e-01 -2.87079513e-01 3.09880644e-01 2.92018592e-01
-9.65930462e-01 -4.96081501e-01 -1.06543529e+00 9.30592835e-01
-2.40890011e-01 -6.40093148e-01 5.08799911e-01 4.12479192e-01
-1.08753526e+00 4.81936723e-01 -7.37954140e-01 -3.20492595e-01
7.66701251e-02 5.49320459e-01 -9.31448787e-02 1.51584312e-01
-1.13771701e+00 8.01225245e-01 7.89064586e-01 -2.09373072e-01
-9.88080442e-01 -8.17127377e-02 -7.47440100e-01 3.29940543e-02
7.60438800e-01 -8.06249678e-01 8.99819374e-01 -1.13115466e+00
-1.67005575e+00 -9.37446952e-03 2.16833234e-01 -5.30793130e-01
3.60168308e-01 5.49978018e-01 -3.23451936e-01 1.68842748e-01
1.73936263e-01 7.51810074e-01 8.31244290e-01 -1.77188694e+00
-1.26825523e+00 -1.92439288e-01 3.41458857e-01 8.60050023e-01
-4.85015750e-01 -3.28945220e-01 -2.45113805e-01 -4.29997772e-01
7.87512884e-02 -7.36852586e-01 -5.28313220e-01 -7.45477796e-01
-2.37073734e-01 -6.98420346e-01 7.67571688e-01 -1.04756124e-01
1.02626979e+00 -1.94184160e+00 4.82030123e-01 6.80546403e-01
5.49430668e-01 -2.09824950e-01 -3.67239803e-01 5.03910363e-01
4.70213503e-01 -8.89798403e-02 -1.79236740e-01 -3.73856097e-01
8.44426751e-02 4.88128483e-01 3.93693238e-01 2.79053420e-01
-1.94865808e-01 4.15514171e-01 -1.03370202e+00 -6.48877084e-01
2.84170836e-01 1.51309267e-01 -5.08122504e-01 1.67711362e-01
-3.03181410e-01 3.58069032e-01 -8.53630006e-01 3.82042408e-01
6.52247906e-01 -3.18822652e-01 5.65185785e-01 2.29729652e-01
-7.46991634e-02 -1.75992876e-01 -1.49438953e+00 1.43113005e+00
-1.11232281e-01 -1.06142111e-01 4.51163352e-01 -1.34537697e+00
1.18646801e+00 3.40571731e-01 7.06463337e-01 -5.76094210e-01
2.47271687e-01 2.00946676e-03 3.77934992e-01 -1.30189463e-01
1.15879416e-01 2.89835006e-01 1.12011097e-01 6.22845531e-01
-3.55884820e-01 -1.15441956e-01 4.48898971e-01 3.61607075e-01
1.15571344e+00 -4.69805151e-01 1.42490432e-01 -2.43340001e-01
8.75722885e-01 1.33100361e-01 9.71102417e-01 7.83968508e-01
-3.09697062e-01 3.91183197e-02 3.38944525e-01 -4.93608981e-01
-4.45060760e-01 -7.35544860e-01 6.33894086e-01 8.46731007e-01
8.47359300e-01 -4.40106660e-01 -7.86628842e-01 -8.44659090e-01
1.45511866e-01 4.84160095e-01 -4.60520655e-01 -2.77645618e-01
-4.60679352e-01 -9.38805223e-01 -2.95422338e-02 2.05736473e-01
1.18571508e+00 -1.31093431e+00 -5.64406037e-01 5.83668292e-01
-1.28777131e-01 -6.17404342e-01 -3.48360360e-01 2.40455959e-02
-4.51156378e-01 -1.14913964e+00 -5.57895780e-01 -1.14999163e+00
8.56310070e-01 4.50279891e-01 7.18540788e-01 6.60268247e-01
4.44447219e-01 3.76261264e-01 -7.91611433e-01 -2.81369179e-01
-7.34287858e-01 4.79497835e-02 3.04675907e-01 1.78092405e-01
1.39138564e-01 -7.41673768e-01 -5.05949914e-01 5.43716073e-01
-7.00796723e-01 2.33278394e-01 7.33587682e-01 7.80964375e-01
1.82085007e-01 9.61636305e-01 9.79386628e-01 -2.42517039e-01
1.11187363e+00 -5.20849288e-01 -4.88711268e-01 3.80494565e-01
-9.14780796e-01 8.45558867e-02 8.90021861e-01 -3.81599247e-01
-1.03042066e+00 -1.60628468e-01 3.42291802e-01 -7.48625249e-02
1.75766069e-02 6.99849010e-01 -1.27975687e-01 -8.76733065e-02
1.66861996e-01 3.79784673e-01 6.23053372e-01 -9.34523717e-02
2.12446600e-02 7.95999706e-01 1.76660806e-01 -5.78957200e-01
6.51837647e-01 3.27145785e-01 -4.23904918e-02 -4.37754869e-01
-2.63701349e-01 -1.95207387e-01 -4.70018014e-02 -5.63668430e-01
8.32508087e-01 -9.01629567e-01 -1.30401361e+00 6.26123250e-01
-1.05284405e+00 -4.04383391e-01 5.30868694e-02 5.88953197e-01
-4.83684033e-01 4.34994549e-01 -6.44213855e-01 -7.42927313e-01
-2.68126279e-01 -1.26150560e+00 2.21630931e-01 7.17000365e-01
1.93205982e-01 -9.30863678e-01 6.03410862e-02 3.30682278e-01
4.43773270e-01 5.07250428e-02 6.93202496e-01 -7.72604346e-01
-6.03000939e-01 5.49001992e-01 7.98618570e-02 2.18003437e-01
5.14044881e-01 -3.26437771e-01 -1.29373640e-01 -5.93461633e-01
-9.94441658e-03 -3.47424716e-01 6.64844155e-01 3.88955563e-01
5.97742736e-01 -3.24706733e-01 -4.58741665e-01 9.02479142e-02
1.08313560e+00 7.68462300e-01 3.38903129e-01 6.74621165e-01
3.66529763e-01 7.36144304e-01 5.60883403e-01 7.23462999e-01
9.21697795e-01 3.99741948e-01 6.92403078e-01 1.51255608e-01
-3.50011811e-02 1.05034269e-01 5.19098997e-01 1.10186052e+00
-3.64015341e-01 -4.29830849e-01 -6.24854267e-01 2.29560316e-01
-2.53496885e+00 -1.01301277e+00 1.76488817e-01 1.72554612e+00
7.71492004e-01 2.58163095e-01 1.59142375e-01 1.20665021e-02
1.14227343e+00 2.26038825e-02 -5.05475819e-01 -3.39372121e-02
-2.52236634e-01 -7.26587534e-01 7.41312727e-02 5.79190850e-01
-7.92787254e-01 7.50431538e-01 4.81386518e+00 9.21707749e-01
-7.44717777e-01 8.03297311e-02 4.86260146e-01 3.21688622e-01
-3.51820916e-01 -5.54940924e-02 -4.89475816e-01 7.52207994e-01
3.50635111e-01 -1.66285634e-01 7.71359861e-01 5.22936821e-01
3.26657176e-01 -3.42399359e-01 -7.61384428e-01 9.22003746e-01
1.29363164e-01 -1.36436486e+00 1.58292189e-01 6.10116608e-02
8.50548506e-01 -3.07099938e-01 -2.85897523e-01 3.10364187e-01
9.73563552e-01 -7.10838020e-01 5.66112220e-01 4.60028023e-01
-2.45722517e-01 -1.06899834e+00 9.55063105e-01 6.01289213e-01
-1.45153081e+00 -4.27367389e-01 -4.16949570e-01 -2.88031310e-01
6.88790306e-02 2.45833740e-01 -6.37225270e-01 1.06502080e+00
5.90625286e-01 7.52731800e-01 -3.96626621e-01 9.96045887e-01
-1.68446362e-01 7.57182837e-02 -1.76156417e-01 -4.09878403e-01
4.18916523e-01 -6.88842416e-01 6.31196320e-01 5.18476605e-01
1.55483425e-01 2.00894415e-01 1.07298625e+00 5.58425665e-01
4.75518852e-02 3.28844935e-02 -1.76883146e-01 3.66062254e-01
1.10456622e+00 1.14770389e+00 -9.48129296e-01 -5.07648945e-01
-3.10865670e-01 9.35732841e-01 5.92001140e-01 2.02883378e-01
-7.53983796e-01 -3.44866782e-01 3.19939375e-01 -3.68564308e-01
2.25207247e-02 -1.21714652e-01 1.44854024e-01 -6.70481801e-01
-1.68566495e-01 -1.07593000e+00 5.29454887e-01 -4.02693331e-01
-1.27645290e+00 6.14720762e-01 -4.46204059e-02 -1.10443509e+00
-3.54351193e-01 5.19850738e-02 -9.70263839e-01 3.68047088e-01
-1.43263888e+00 -8.94855082e-01 -4.96487141e-01 9.10268545e-01
5.67893744e-01 -8.09454024e-01 6.19029760e-01 -9.40947384e-02
-7.63227642e-01 1.19005322e-01 1.86599463e-01 7.47754648e-02
5.79210579e-01 -1.16411328e+00 -5.36516070e-01 3.97786826e-01
-1.81150094e-01 3.76554430e-01 4.81009752e-01 -8.22296143e-01
-1.23377860e+00 -9.94649470e-01 2.25104064e-01 3.13530445e-01
3.76398742e-01 2.58965105e-01 -6.72928214e-01 5.22673130e-01
6.99348569e-01 -5.27306855e-01 3.79274875e-01 -1.65652540e-02
6.55601844e-02 -4.91244853e-01 -1.22772181e+00 5.81528068e-01
7.81117439e-01 1.88913196e-01 -9.04385328e-01 2.18692675e-01
6.81619942e-01 1.49918914e-01 -7.14963436e-01 2.59428352e-01
7.66652375e-02 -1.06779754e+00 5.99553227e-01 -6.68349415e-02
-9.90621466e-03 -8.88169944e-01 2.07885969e-02 -2.10683084e+00
-7.23890245e-01 -5.88642657e-01 2.81649917e-01 1.30970883e+00
2.32000500e-01 -1.12132061e+00 8.12119365e-01 2.83199042e-01
-2.76599258e-01 -4.30974633e-01 -8.13643515e-01 -9.15762246e-01
-2.06927612e-01 3.17940742e-01 8.64663899e-01 1.14786470e+00
4.36715245e-01 3.78404558e-01 -1.46665335e-01 2.64842927e-01
9.40445602e-01 1.31023526e-01 6.51348233e-01 -1.36674631e+00
-4.20341611e-01 -6.23272777e-01 -2.08906054e-01 -7.66687572e-01
3.34607840e-01 -7.01036692e-01 2.77775489e-02 -1.91148126e+00
4.46755260e-01 -8.48000526e-01 -5.25279701e-01 4.56548810e-01
-1.19124815e-01 -2.19758362e-01 4.18819636e-01 4.38673645e-01
-1.11086392e+00 8.20295990e-01 1.23095632e+00 -5.38305581e-01
-6.09667778e-01 -1.51525378e-01 -6.80333018e-01 7.85134435e-01
1.23630452e+00 -4.34726238e-01 -5.86927712e-01 -2.63971746e-01
-1.09616496e-01 1.43622339e-01 1.43252373e-01 -1.19723701e+00
8.04671109e-01 -4.76120979e-01 1.76083162e-01 -3.49300534e-01
2.67721355e-01 -8.90141368e-01 2.53121912e-01 1.13603258e+00
-2.79999495e-01 2.65881330e-01 -4.44412857e-01 6.00673318e-01
-3.18053961e-01 -2.74677843e-01 5.95041871e-01 -2.81697541e-01
-7.67954707e-01 -9.79699194e-02 -5.79587877e-01 -3.69379342e-01
1.49031115e+00 -8.47539008e-02 -5.72399616e-01 -7.47014701e-01
-4.81021583e-01 1.16913497e+00 3.93590361e-01 1.00644715e-01
6.90035641e-01 -1.34981346e+00 -1.00767839e+00 -4.39440310e-02
-2.48208448e-01 3.59250121e-02 2.71241665e-01 8.12739849e-01
-1.97932675e-01 -1.35740608e-01 -5.05786419e-01 -5.02755165e-01
-1.31034184e+00 5.63733101e-01 3.04848403e-01 -3.32959145e-01
-4.46236700e-01 4.31018412e-01 -5.83879165e-02 -4.38844323e-01
3.73018771e-01 -5.14018908e-02 -6.44154489e-01 1.20732434e-01
4.84975398e-01 4.68008727e-01 -3.44053686e-01 -3.88622940e-01
-3.64995122e-01 4.22705173e-01 -2.31332228e-01 -9.99521017e-02
1.25582218e+00 -4.06293750e-01 -3.73919457e-01 -6.88150451e-02
5.83467782e-01 -1.21600628e-01 -1.25891602e+00 -1.78325415e-01
-1.99809194e-01 -1.68986116e-02 3.13668177e-02 -7.55054176e-01
-1.25445628e+00 -1.40632261e-02 3.81190062e-01 8.00170183e-01
1.18596554e+00 1.11177869e-01 4.52464670e-01 5.13290942e-01
6.57000422e-01 -1.49092519e+00 3.76350313e-01 5.29474199e-01
8.49638164e-01 -1.37144053e+00 -9.96685773e-02 -4.21439111e-01
-8.79116774e-01 9.05586660e-01 9.24357176e-01 -9.58572701e-02
5.19588649e-01 5.81221581e-02 7.26409853e-02 -1.77943468e-01
-9.05057847e-01 -3.88526410e-01 -2.74455905e-01 1.03405976e+00
-2.70817459e-01 1.83262348e-01 -4.93871003e-01 4.26742047e-01
-5.03795519e-02 -3.67979169e-01 6.85595870e-01 9.91350949e-01
-9.84966993e-01 -1.20740318e+00 -5.33884764e-01 2.45796293e-01
1.74928322e-01 2.75599957e-01 -2.25678936e-01 7.09297597e-01
2.15458661e-01 1.69871294e+00 2.39913791e-01 -7.46728361e-01
1.04541279e-01 -4.54390168e-01 2.42368266e-01 -3.05336624e-01
-7.02540696e-01 1.19671069e-01 -2.96169482e-02 -3.59338641e-01
-9.47185636e-01 -3.73965919e-01 -1.72842777e+00 -6.13150954e-01
-1.72622204e-01 7.93247044e-01 2.23368004e-01 8.49347234e-01
2.70280004e-01 7.90813029e-01 9.99238074e-01 -5.77488065e-01
-6.77094996e-01 -9.51454520e-01 -6.84023857e-01 4.73149866e-01
-5.29814549e-02 -7.78765142e-01 -3.98512125e-01 -2.95238972e-01] | [3.7770769596099854, 1.9880543947219849] |
2e213923-b2b0-424f-8cb0-66c12309b565 | one-stage-3d-whole-body-mesh-recovery-with | 2303.16160 | null | https://arxiv.org/abs/2303.16160v1 | https://arxiv.org/pdf/2303.16160v1.pdf | One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer | Whole-body mesh recovery aims to estimate the 3D human body, face, and hands parameters from a single image. It is challenging to perform this task with a single network due to resolution issues, i.e., the face and hands are usually located in extremely small regions. Existing works usually detect hands and faces, enlarge their resolution to feed in a specific network to predict the parameter, and finally fuse the results. While this copy-paste pipeline can capture the fine-grained details of the face and hands, the connections between different parts cannot be easily recovered in late fusion, leading to implausible 3D rotation and unnatural pose. In this work, we propose a one-stage pipeline for expressive whole-body mesh recovery, named OSX, without separate networks for each part. Specifically, we design a Component Aware Transformer (CAT) composed of a global body encoder and a local face/hand decoder. The encoder predicts the body parameters and provides a high-quality feature map for the decoder, which performs a feature-level upsample-crop scheme to extract high-resolution part-specific features and adopt keypoint-guided deformable attention to estimate hand and face precisely. The whole pipeline is simple yet effective without any manual post-processing and naturally avoids implausible prediction. Comprehensive experiments demonstrate the effectiveness of OSX. Lastly, we build a large-scale Upper-Body dataset (UBody) with high-quality 2D and 3D whole-body annotations. It contains persons with partially visible bodies in diverse real-life scenarios to bridge the gap between the basic task and downstream applications. | ['Yu Li', 'Lei Zhang', 'Haoqian Wang', 'Ailing Zeng', 'Jing Lin'] | 2023-03-28 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Lin_One-Stage_3D_Whole-Body_Mesh_Recovery_With_Component_Aware_Transformer_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Lin_One-Stage_3D_Whole-Body_Mesh_Recovery_With_Component_Aware_Transformer_CVPR_2023_paper.pdf | cvpr-2023-1 | ['3d-human-pose-estimation', '3d-human-reconstruction', '3d-multi-person-mesh-recovery'] | ['computer-vision', 'computer-vision', 'computer-vision'] | [ 6.07680827e-02 2.00473085e-01 -9.94450673e-02 -4.12387192e-01
-7.50951111e-01 -2.20364869e-01 1.88864127e-01 -5.26021242e-01
7.15763047e-02 3.87841702e-01 4.80299503e-01 5.93528450e-01
2.55470365e-01 -6.36499822e-01 -7.46082008e-01 -4.39703792e-01
2.70747542e-01 8.45090091e-01 2.43161038e-01 -1.89882651e-01
-4.97361332e-01 3.89868408e-01 -1.56668019e+00 1.22036517e-01
6.43145859e-01 1.09499192e+00 -1.14518747e-01 4.25178856e-01
2.98539639e-01 3.04925531e-01 -3.76012772e-01 -7.50001311e-01
3.79170150e-01 -3.16578656e-01 -5.74369848e-01 3.40028703e-01
8.60470355e-01 -8.39023113e-01 -3.53502005e-01 7.93342888e-01
8.71662259e-01 -1.31270006e-01 4.42100435e-01 -1.07634628e+00
-6.96886480e-02 3.07124943e-01 -1.07713974e+00 -4.23801661e-01
6.41979694e-01 3.65224779e-01 5.82292438e-01 -9.18235958e-01
7.40893006e-01 1.65686524e+00 1.01521873e+00 7.93541431e-01
-1.02937889e+00 -9.08407509e-01 2.27709562e-01 -2.20249504e-01
-1.53715956e+00 -7.91387618e-01 9.05897677e-01 -3.98668855e-01
4.35084283e-01 1.49955168e-01 1.19297004e+00 1.19342279e+00
1.80305261e-02 6.99891269e-01 6.14029050e-01 -9.30815861e-02
-3.71597975e-01 -5.16335309e-01 -3.07430863e-01 1.15080786e+00
1.73476502e-01 3.70927788e-02 -6.81087196e-01 3.03983856e-02
1.19043469e+00 1.83867007e-01 -4.38280344e-01 -4.53014791e-01
-1.29523933e+00 2.03600973e-01 4.08367336e-01 -2.75442749e-01
-4.87490296e-01 3.43630552e-01 3.53600025e-01 -1.62143573e-01
4.02085900e-01 -3.20278585e-01 -5.39253771e-01 1.06159024e-01
-1.05662894e+00 4.98679459e-01 6.11420214e-01 1.13731122e+00
6.33796394e-01 -1.77336231e-01 -2.98576027e-01 7.72503018e-01
6.04600787e-01 6.57794535e-01 3.66704576e-02 -9.58177507e-01
5.69766462e-01 5.96753478e-01 -1.10508464e-02 -1.01751208e+00
-4.82823223e-01 -2.30843663e-01 -1.03081048e+00 1.49470583e-01
6.22754335e-01 -1.42269015e-01 -1.07512879e+00 1.66857743e+00
1.08051932e+00 1.33188009e-01 -5.02295971e-01 1.57522988e+00
1.04305387e+00 2.42495611e-01 1.33896600e-02 7.64551759e-02
1.85780501e+00 -1.19614506e+00 -6.19262874e-01 -4.20213282e-01
-8.81367736e-03 -6.43392503e-01 1.01946354e+00 2.37516269e-01
-1.34888458e+00 -7.56263077e-01 -8.82194221e-01 -5.25032997e-01
2.63512552e-01 4.12819237e-01 5.07333636e-01 1.95157975e-01
-6.71308577e-01 6.10857308e-01 -9.96879280e-01 -1.80305332e-01
4.27039266e-01 6.72850192e-01 -7.30058432e-01 -1.40055284e-01
-9.05430138e-01 5.94777346e-01 8.04150999e-02 5.34525454e-01
-7.56588995e-01 -7.03570426e-01 -1.19712651e+00 -1.69117898e-01
6.81514621e-01 -1.27573454e+00 1.10936797e+00 -8.89872313e-01
-1.64633214e+00 9.73323524e-01 -2.05604047e-01 1.71046436e-01
8.02396476e-01 -6.31877422e-01 -1.93371996e-01 1.31424978e-01
7.76013136e-02 7.30232418e-01 1.34611619e+00 -9.83205914e-01
-3.32301587e-01 -7.70824313e-01 -2.18064308e-01 3.34363490e-01
2.74056159e-02 3.04665100e-02 -1.22969031e+00 -8.93974841e-01
2.60248393e-01 -8.62243652e-01 1.53356627e-01 5.93348920e-01
-6.25275612e-01 -3.80278379e-02 6.50162876e-01 -1.31928623e+00
9.27393258e-01 -2.06131697e+00 4.46786463e-01 1.22595035e-01
4.76462573e-01 -3.60921808e-02 4.90600765e-02 -4.91274744e-02
1.71862096e-02 -4.34391767e-01 -1.44287705e-01 -7.24809945e-01
4.67883535e-02 1.23889700e-01 8.48163739e-02 7.31070757e-01
1.14680126e-01 1.10165262e+00 -5.87834358e-01 -9.04667616e-01
2.56305605e-01 8.52688849e-01 -7.56719649e-01 2.70822853e-01
-1.31821454e-01 5.77677071e-01 -5.45455456e-01 1.12260437e+00
8.36800754e-01 -2.08321601e-01 1.98344514e-01 -7.55794525e-01
3.05352986e-01 3.94306891e-02 -1.45436287e+00 2.09899616e+00
-1.51360691e-01 -2.67580841e-02 6.71951473e-01 -4.28665251e-01
5.32975614e-01 3.83886784e-01 5.67914188e-01 -3.07239234e-01
3.30707490e-01 2.88654603e-02 -3.16993445e-01 -4.04278725e-01
6.95943981e-02 -2.58283257e-01 -6.61165565e-02 1.19496137e-01
2.14722961e-01 1.22982468e-02 -2.73660123e-01 -1.81821167e-01
7.32469916e-01 7.31700361e-01 2.78069228e-01 5.02445772e-02
4.50147808e-01 -4.66199219e-01 8.80372405e-01 -1.82226896e-01
-1.09927654e-01 1.10459495e+00 2.32259467e-01 -3.82883847e-01
-8.14396203e-01 -9.82191503e-01 1.96098000e-01 1.13123310e+00
2.75011957e-01 -7.42917955e-01 -9.68606830e-01 -6.61033750e-01
1.72239810e-01 -2.97555506e-01 -6.15974963e-01 -9.04974565e-02
-8.40270460e-01 -2.63552666e-01 4.28284258e-01 7.54608810e-01
6.02965355e-01 -9.12651241e-01 -4.82103497e-01 7.39843696e-02
-5.17589569e-01 -1.11609757e+00 -1.13351250e+00 -4.01074469e-01
-6.90826237e-01 -1.27048290e+00 -9.71436679e-01 -5.64624906e-01
7.80717611e-01 -2.35219240e-01 1.12049353e+00 2.59058446e-01
-3.63789022e-01 3.93983833e-02 3.38705853e-02 -4.07929718e-02
-2.53678057e-02 -4.79273982e-02 2.11453885e-01 1.15914993e-01
-1.40409857e-01 -6.99857473e-01 -9.48313296e-01 4.41421509e-01
-2.79633969e-01 2.45159313e-01 5.18730938e-01 6.77871168e-01
8.88512015e-01 -1.28991574e-01 9.36059132e-02 -4.30125356e-01
3.71590517e-02 -1.30268084e-02 -3.99390101e-01 2.64636010e-01
-6.14708588e-02 -1.57750934e-01 4.44719046e-01 -5.38336694e-01
-1.09649837e+00 5.70981383e-01 -4.20296788e-01 -7.15013564e-01
-4.16460037e-02 -1.64319828e-01 -9.10806596e-01 6.80106059e-02
1.79532960e-01 -7.27547007e-03 1.34502545e-01 -8.39433908e-01
3.40487331e-01 4.79443431e-01 1.07602870e+00 -7.17078924e-01
9.29863155e-01 4.91586626e-01 -7.57597163e-02 -4.36345816e-01
-9.08948362e-01 -2.23454446e-01 -1.03000200e+00 -4.04373825e-01
9.63867366e-01 -1.30049872e+00 -9.00086939e-01 6.95913255e-01
-1.12451911e+00 -2.85889983e-01 -3.28403622e-01 3.09400499e-01
-4.98326361e-01 3.56907636e-01 -8.52488279e-01 -4.46917504e-01
-8.51358294e-01 -1.09684420e+00 1.88930941e+00 1.52594194e-01
-4.58353609e-01 -3.84362429e-01 -1.17006369e-01 6.62689090e-01
-1.55679524e-01 4.64492559e-01 3.73575956e-01 1.18511692e-01
-3.82202208e-01 -1.45284325e-01 -1.59466505e-01 1.60540417e-01
8.14705938e-02 -4.26978944e-03 -9.43681121e-01 -3.58382583e-01
-3.15261483e-01 -3.62705737e-01 6.00376189e-01 4.03503060e-01
1.06638360e+00 -3.04007262e-01 -4.06676352e-01 1.10629642e+00
8.84180009e-01 -6.20196044e-01 4.93734539e-01 -3.49890977e-01
1.24064076e+00 7.58480906e-01 5.79162478e-01 5.43586910e-01
6.31940782e-01 9.00511742e-01 3.41900259e-01 -1.86946422e-01
-6.77208960e-01 -6.91028118e-01 4.16952789e-01 8.04568231e-01
-6.03696167e-01 1.71535656e-01 -6.70753300e-01 1.48024738e-01
-1.60257423e+00 -5.65298021e-01 1.11429960e-01 2.09931040e+00
1.03533280e+00 -1.54723346e-01 4.82686400e-01 2.34057661e-02
7.30988681e-01 5.59148267e-02 -7.06201971e-01 5.25933921e-01
2.06063345e-01 2.34131202e-01 1.21347778e-01 3.20060909e-01
-1.12899780e+00 9.61825490e-01 5.43622160e+00 7.79718876e-01
-1.03375554e+00 1.84272990e-01 2.26522684e-01 -4.69739586e-01
8.01490694e-02 -2.17338279e-01 -8.26687157e-01 5.17197609e-01
3.59643251e-01 4.51852858e-01 2.95405746e-01 8.01013649e-01
-3.85594890e-02 1.64102286e-01 -1.12630045e+00 1.39016151e+00
4.44044694e-02 -8.02514493e-01 -7.27886260e-02 8.88756439e-02
2.03880101e-01 -3.04192424e-01 -4.04884160e-01 4.52783927e-02
-1.38437614e-01 -9.48948026e-01 1.16133428e+00 7.72381008e-01
1.31181610e+00 -7.52059221e-01 3.46923053e-01 4.18843806e-01
-1.57527459e+00 1.39576375e-01 -2.75773853e-01 8.27251747e-02
3.71782988e-01 5.75333357e-01 -2.56541312e-01 4.88163054e-01
9.25587177e-01 7.19330192e-01 -3.05834919e-01 6.11409843e-01
-2.85811901e-01 1.71806738e-01 -6.08562350e-01 7.06900835e-01
-6.31247282e-01 -9.20315459e-02 4.20452356e-01 9.01758730e-01
3.02418232e-01 3.29388469e-01 2.48804793e-01 7.27315485e-01
-2.72524536e-01 7.42276758e-02 -6.37621954e-02 3.08316171e-01
3.58211607e-01 1.41706455e+00 -6.70437753e-01 -4.26883698e-01
-2.64929414e-01 1.43795121e+00 2.02930540e-01 4.11014855e-02
-1.03694975e+00 -8.73076497e-04 8.17290902e-01 7.69517004e-01
2.73137301e-01 2.33147312e-02 3.75057049e-02 -1.45471931e+00
4.11497802e-01 -1.07257128e+00 3.25294644e-01 -7.81982422e-01
-1.09495354e+00 3.34064722e-01 -1.06071100e-01 -1.10451114e+00
-2.55867362e-01 -2.50224173e-01 -2.46351853e-01 8.36378694e-01
-8.92688870e-01 -1.74052501e+00 -7.63442874e-01 9.32094455e-01
4.64217305e-01 3.16040307e-01 6.58601403e-01 5.99607050e-01
-8.32086444e-01 8.45089436e-01 -6.94760203e-01 5.21715999e-01
1.01463294e+00 -8.80214572e-01 4.36385632e-01 6.36232555e-01
-1.62856236e-01 5.52598000e-01 4.08191949e-01 -1.03663599e+00
-1.68246019e+00 -1.10850203e+00 4.33830440e-01 -4.91864920e-01
-5.94838820e-02 -6.52045667e-01 -6.27872586e-01 7.84821510e-01
-3.78370553e-01 5.13721764e-01 2.70138115e-01 -4.34270733e-05
-3.46027702e-01 -2.53031880e-01 -1.17687476e+00 4.78836387e-01
1.60882795e+00 -4.44321990e-01 -5.39933145e-01 1.24963507e-01
5.40676415e-01 -9.97867882e-01 -1.11643219e+00 6.11267567e-01
1.14251733e+00 -9.18489397e-01 1.32302558e+00 -2.18165368e-01
4.85215485e-01 -4.04445499e-01 5.89034148e-02 -8.98416758e-01
-1.94356248e-01 -6.92511857e-01 -7.22080708e-01 1.44375086e+00
-2.71774858e-01 -2.09186599e-01 8.78980398e-01 7.44609714e-01
1.54979518e-02 -8.66253734e-01 -8.28275383e-01 -2.65981168e-01
-3.76960903e-01 -3.45291555e-01 9.64035392e-01 6.12014413e-01
-2.80333042e-01 4.27789509e-01 -7.62070179e-01 2.36108735e-01
7.97205508e-01 2.92720050e-01 1.16315532e+00 -1.18202841e+00
-3.76561165e-01 -1.24122947e-02 -3.79290521e-01 -1.37802911e+00
1.28119305e-01 -5.15049338e-01 1.66136757e-01 -1.29775703e+00
2.46540606e-01 -2.55166411e-01 3.11201364e-01 7.44048119e-01
-1.97818339e-01 5.36769331e-01 1.48822442e-01 2.36810595e-01
-4.19589847e-01 6.52240753e-01 1.69959581e+00 -3.11222691e-02
-4.32618596e-02 1.10669389e-01 -5.83866656e-01 1.22783911e+00
1.89468563e-01 -2.00319618e-01 -2.68704504e-01 -4.42855150e-01
9.30682477e-03 3.58338863e-01 8.66968691e-01 -9.98803854e-01
9.17554870e-02 6.32490739e-02 1.00560200e+00 -7.38891304e-01
6.54233634e-01 -8.67855906e-01 5.07905662e-01 2.14376315e-01
2.17580423e-01 -1.59466133e-01 -9.72280353e-02 4.89796668e-01
3.33478861e-02 4.43977684e-01 7.75183797e-01 -1.67491302e-01
-3.90856773e-01 8.79619777e-01 4.48860973e-01 1.77630186e-02
8.85911167e-01 -2.84057051e-01 2.14014709e-01 -2.48843536e-01
-9.38565016e-01 2.14368999e-01 7.76613891e-01 4.39985424e-01
7.10931540e-01 -1.37073255e+00 -7.51158059e-01 5.65086186e-01
-1.85058892e-01 7.06422865e-01 5.61908007e-01 1.02869642e+00
-4.89974052e-01 -2.52773553e-01 -1.33831576e-01 -6.02576256e-01
-1.60875678e+00 4.41857487e-01 6.54122114e-01 -7.50055909e-02
-1.22975707e+00 9.05503809e-01 3.94477904e-01 -4.88338143e-01
2.50370055e-01 -3.87891620e-01 1.72484353e-01 1.18128523e-01
6.58823669e-01 4.03212100e-01 -1.03033744e-01 -1.11988902e+00
-5.60868323e-01 1.21908700e+00 2.57728428e-01 1.41496360e-01
1.14908028e+00 -2.05025584e-01 -2.31400520e-01 -7.39059299e-02
1.08391917e+00 2.28318095e-01 -1.68203366e+00 -2.38461271e-02
-8.08973432e-01 -4.48498130e-01 -1.28942251e-01 -6.05904341e-01
-1.55383825e+00 9.41362262e-01 4.33916658e-01 -6.65142953e-01
1.25163627e+00 2.14652881e-01 1.26918566e+00 -1.48455694e-01
5.07799387e-01 -1.06848717e+00 -1.54563561e-01 1.37191221e-01
1.13932061e+00 -8.90826166e-01 2.90384203e-01 -9.32199240e-01
-3.42364877e-01 9.93493795e-01 8.68040144e-01 -2.05286741e-02
6.95742726e-01 4.92500037e-01 -1.23722017e-01 -3.15802425e-01
-3.24456662e-01 -1.00058593e-01 7.28441179e-01 6.99654639e-01
2.78413266e-01 7.64860436e-02 1.09644614e-01 1.05095577e+00
-5.47175407e-01 1.78311482e-01 -3.03567410e-01 6.68329358e-01
7.02892663e-03 -9.58892345e-01 -7.30684459e-01 3.89170885e-01
-4.74679053e-01 1.71692029e-01 -3.18101317e-01 7.25640535e-01
5.69858372e-01 3.64778072e-01 -9.43820998e-02 -4.85654235e-01
5.19668341e-01 9.93504748e-03 8.31150889e-01 -4.82746542e-01
-4.97806907e-01 4.82071429e-01 4.54986207e-02 -1.08243966e+00
-3.30530137e-01 -5.54446638e-01 -1.44023693e+00 -4.80378747e-01
-2.89860040e-01 -4.82297242e-01 1.50945574e-01 9.31166291e-01
4.30989325e-01 5.60011506e-01 -1.17553078e-04 -1.41820300e+00
-4.30378556e-01 -9.77692127e-01 -6.27737761e-01 5.02373993e-01
3.28474820e-01 -9.94416654e-01 1.05015315e-01 2.65012175e-01] | [7.174017906188965, -1.0479793548583984] |
c3e8c237-86b1-41c0-b890-a9159be6c0c3 | multi-view-orthonormalized-partial-least | 2007.05028 | null | https://arxiv.org/abs/2007.05028v1 | https://arxiv.org/pdf/2007.05028v1.pdf | Multi-view Orthonormalized Partial Least Squares: Regularizations and Deep Extensions | We establish a family of subspace-based learning method for multi-view learning using the least squares as the fundamental basis. Specifically, we investigate orthonormalized partial least squares (OPLS) and study its important properties for both multivariate regression and classification. Building on the least squares reformulation of OPLS, we propose a unified multi-view learning framework to learn a classifier over a common latent space shared by all views. The regularization technique is further leveraged to unleash the power of the proposed framework by providing three generic types of regularizers on its inherent ingredients including model parameters, decision values and latent projected points. We instantiate a set of regularizers in terms of various priors. The proposed framework with proper choices of regularizers not only can recast existing methods, but also inspire new models. To further improve the performance of the proposed framework on complex real problems, we propose to learn nonlinear transformations parameterized by deep networks. Extensive experiments are conducted to compare various methods on nine data sets with different numbers of views in terms of both feature extraction and cross-modal retrieval. | ['Wen-Wei', 'Ren-cang Li', 'Li Wang'] | 2020-07-09 | null | null | null | null | ['multi-view-learning'] | ['computer-vision'] | [ 6.51901513e-02 -5.28983414e-01 -4.10603315e-01 -4.73895341e-01
-9.26111341e-01 -6.83845222e-01 7.70739436e-01 -5.74505210e-01
-1.10007025e-01 4.71799284e-01 4.83623266e-01 8.85418281e-02
-4.66786921e-01 -5.13713360e-01 -6.49571717e-01 -9.25080061e-01
2.78923273e-01 -1.07264135e-03 -2.27290228e-01 -1.11717418e-01
1.97568268e-01 5.55765271e-01 -1.23980510e+00 2.88869530e-01
6.89346969e-01 8.09736550e-01 -1.38228089e-01 2.30979636e-01
3.55209082e-01 5.26450753e-01 9.09346864e-02 -4.84116562e-02
4.16805029e-01 1.90285798e-02 -4.68464345e-01 4.77470607e-01
5.79537332e-01 -2.34698892e-01 -3.20681959e-01 9.31491911e-01
5.54749966e-01 1.84781894e-01 9.86401141e-01 -1.32068038e+00
-8.68510604e-01 1.19826674e-01 -8.58167946e-01 5.62733561e-02
2.49774605e-01 -1.47446692e-01 1.23515153e+00 -1.43138218e+00
3.78305793e-01 1.36450768e+00 4.94849801e-01 2.69625813e-01
-1.29045868e+00 -5.58712065e-01 3.29034448e-01 2.04505727e-01
-1.37574899e+00 -8.09203207e-01 1.15380812e+00 -5.33462822e-01
5.43022871e-01 2.06743181e-01 2.74147123e-01 1.22595692e+00
9.59924757e-02 8.80334973e-01 1.37294376e+00 -4.50060248e-01
-9.40113515e-02 3.39727938e-01 2.68940836e-01 8.01308632e-01
1.14706181e-01 -1.05262913e-01 -5.80900490e-01 -3.81399453e-01
7.28349745e-01 2.82217145e-01 -5.21172404e-01 -1.16675413e+00
-1.36183584e+00 9.81141984e-01 1.03777461e-01 6.11219322e-03
-2.69962579e-01 -1.38928980e-01 2.70695090e-01 6.47336170e-02
4.36859101e-01 -9.41530392e-02 -3.55620414e-01 5.22480965e-01
-7.89900422e-01 -1.28022239e-01 6.72824025e-01 9.53124106e-01
8.60309303e-01 2.04572365e-01 -1.05106095e-02 1.24133635e+00
6.47864819e-01 6.18645430e-01 4.24894273e-01 -9.02149796e-01
5.06186604e-01 5.00960886e-01 1.56798631e-01 -1.34797108e+00
-3.55450898e-01 -5.65823555e-01 -1.12943041e+00 -6.44600345e-03
-5.18285856e-02 -1.56389460e-01 -5.39534688e-01 1.81260753e+00
2.70613223e-01 2.02021345e-01 1.45314232e-01 8.75108242e-01
6.24163628e-01 6.76653326e-01 -4.37093079e-01 -5.03293037e-01
1.17118466e+00 -1.26502240e+00 -5.75878918e-01 -7.73699209e-02
3.12669545e-01 -6.37862802e-01 9.53771234e-01 6.13061309e-01
-7.93390393e-01 -6.14814699e-01 -1.25864172e+00 2.41816207e-03
-9.10445675e-02 5.05989790e-01 6.44026160e-01 4.06897277e-01
-9.61107790e-01 3.30023706e-01 -9.24360991e-01 -3.71575177e-01
6.21822476e-02 3.03979486e-01 -6.72386646e-01 -1.08548760e-01
-9.27201927e-01 6.18386686e-01 7.33219534e-02 5.55483460e-01
-8.22005510e-01 -3.64785761e-01 -9.62572813e-01 -1.36409253e-01
2.73188531e-01 -9.28387463e-01 5.39848328e-01 -6.64847791e-01
-1.42154300e+00 8.92041326e-01 -2.11203918e-01 2.06696913e-01
3.13615531e-01 -5.27468860e-01 -3.94084245e-01 8.03559273e-02
1.31086022e-01 4.26006615e-02 1.18006277e+00 -1.36089778e+00
-2.61888146e-01 -5.96917570e-01 3.00050043e-02 4.92688924e-01
-6.50431752e-01 -7.09547698e-02 -5.71466148e-01 -5.22278905e-01
5.08551240e-01 -9.38982546e-01 -1.10764302e-01 -1.96973369e-01
-4.37718540e-01 -5.51446378e-02 6.49025321e-01 -5.36425173e-01
1.09643066e+00 -1.99489522e+00 7.74093390e-01 1.74950123e-01
1.36146605e-01 -1.44933194e-01 -9.05067176e-02 6.38824821e-01
-5.04868567e-01 -2.84294426e-01 -9.63641778e-02 -3.36225271e-01
2.78763529e-02 1.29912168e-01 -3.90097618e-01 9.04925883e-01
-6.81001320e-02 6.47091210e-01 -4.75550979e-01 -2.83364087e-01
3.10638249e-01 5.88815808e-01 -5.63023031e-01 3.27133417e-01
3.26821238e-01 4.84928221e-01 -6.09930813e-01 5.71399093e-01
7.78184474e-01 -3.48968774e-01 -3.65264602e-02 -7.74993598e-01
-1.24353282e-01 -2.84829944e-01 -1.81474793e+00 1.94939959e+00
-4.26160246e-01 -1.83621858e-04 3.25446695e-01 -1.37484503e+00
8.31234157e-01 3.38069767e-01 6.10985279e-01 7.90522993e-02
-7.91388303e-02 3.28839608e-02 -5.34912527e-01 -7.58974016e-01
-4.67523336e-02 -3.37432414e-01 2.09784713e-02 4.43682671e-01
4.25065219e-01 3.32389504e-01 -6.14685565e-02 -7.31740966e-02
5.20063639e-01 3.87362629e-01 6.76914752e-01 -4.44454849e-01
1.34012055e+00 -5.53950012e-01 6.87741339e-01 4.66899753e-01
9.40441526e-03 5.38707733e-01 2.51480371e-01 -5.71283758e-01
-8.89063001e-01 -9.42258060e-01 -3.22039336e-01 1.30442476e+00
-1.17803356e-02 -1.35410368e-01 -2.52744317e-01 -6.82188392e-01
-1.87851891e-01 3.41354609e-01 -3.03662270e-01 -1.19557986e-02
-3.59345734e-01 -1.09226179e+00 2.06958547e-01 3.53250593e-01
4.30260628e-01 -6.45100057e-01 3.69711407e-02 -1.78356633e-01
-1.33624732e-01 -1.17353821e+00 -6.25396192e-01 1.71012521e-01
-8.92328262e-01 -1.06142068e+00 -8.58250618e-01 -8.50144982e-01
6.84613764e-01 6.08816683e-01 8.13387275e-01 -3.89346421e-01
2.60987908e-01 9.14893925e-01 -1.36044309e-01 3.29329260e-02
-1.18867485e-02 -2.53416244e-02 6.20404899e-01 5.72576523e-01
2.72148639e-01 -1.09102404e+00 -5.21543443e-01 3.16636741e-01
-9.92790103e-01 8.03031102e-02 7.08419144e-01 1.08385432e+00
6.24641359e-01 -1.88123941e-01 4.49828237e-01 -9.06791985e-01
5.75049877e-01 -4.78790104e-01 -6.55175865e-01 5.98040521e-01
-6.55104518e-01 3.98636013e-01 6.38865829e-01 -1.67533904e-01
-1.10365915e+00 3.39224376e-02 1.46606117e-01 -6.35105252e-01
-2.26610139e-01 6.00565910e-01 -4.62925524e-01 -2.28997678e-01
3.76122892e-01 4.53083307e-01 -2.27279142e-01 -6.85909986e-01
7.61170685e-01 5.38290083e-01 3.73996228e-01 -7.77395487e-01
9.71203089e-01 7.38523722e-01 6.55256957e-02 -6.99089229e-01
-1.02842760e+00 -6.31580412e-01 -9.78738546e-01 5.48440637e-03
6.87037051e-01 -1.29688573e+00 -7.02457964e-01 4.04549867e-01
-9.49424446e-01 4.70902979e-01 3.04060131e-01 6.28227532e-01
-7.57841468e-01 7.34449387e-01 -4.43204671e-01 -6.24621987e-01
-3.22318614e-01 -1.22959769e+00 1.17189765e+00 -1.30071431e-01
4.34203178e-01 -1.22251821e+00 3.35135549e-01 4.38980520e-01
-3.06884595e-03 1.66351780e-01 9.36302781e-01 -7.23006904e-01
-4.07728553e-01 -1.75718218e-02 -1.19572707e-01 6.52220666e-01
2.69922525e-01 -8.77173990e-02 -1.11746967e+00 -7.51139998e-01
5.95835030e-01 -3.76925349e-01 9.26935434e-01 3.19456667e-01
9.55801964e-01 -3.17753911e-01 -2.72054106e-01 1.12170708e+00
1.65644097e+00 -7.89693519e-02 7.53003210e-02 3.08352470e-01
9.34196234e-01 6.80609763e-01 1.33494377e-01 5.14017224e-01
3.28701109e-01 5.42793095e-01 2.84586996e-01 7.40015954e-02
4.42638755e-01 -1.60053357e-01 4.52976912e-01 1.55579877e+00
-1.71851635e-01 -5.61924232e-03 -6.72269523e-01 2.77702570e-01
-1.93327820e+00 -9.07606721e-01 2.19575211e-01 2.13828444e+00
4.52576280e-01 -2.41684243e-01 -1.10272586e-01 -1.89751342e-01
7.25260317e-01 7.71342337e-01 -6.52615905e-01 2.05115788e-02
-2.10757434e-01 -2.05480099e-01 1.71870381e-01 5.26297987e-01
-1.50398672e+00 6.35087550e-01 6.08335447e+00 6.72063947e-01
-1.02876461e+00 -6.54851273e-02 3.77208173e-01 7.90058821e-02
-3.84925455e-01 1.47457235e-02 -9.56538200e-01 -1.57724433e-02
4.56223518e-01 -1.14264600e-02 6.65071189e-01 9.12288725e-01
3.06559414e-01 4.50717688e-01 -1.33600664e+00 1.27515125e+00
5.47975481e-01 -1.00849497e+00 3.49662662e-01 -1.06042288e-01
8.76170218e-01 -8.83388072e-02 2.58970678e-01 2.79885888e-01
-3.10589354e-02 -8.49899650e-01 3.35858613e-01 8.23622882e-01
5.56957781e-01 -5.78073442e-01 4.34420407e-01 6.83642983e-01
-1.09604263e+00 -1.18567772e-01 -4.78066087e-01 1.60719067e-01
1.40776196e-02 2.28397042e-01 -1.81505188e-01 9.33935046e-01
3.48119825e-01 1.26552510e+00 -5.56006014e-01 6.51097298e-01
-1.72848061e-01 2.01209322e-01 -2.94063658e-01 5.11401534e-01
8.34732577e-02 -6.85908794e-01 6.17215931e-01 9.09018934e-01
2.67250657e-01 2.41117496e-02 2.75567889e-01 8.15447390e-01
1.55809417e-01 3.61108184e-01 -8.18146169e-01 2.68780380e-01
2.41267473e-01 1.60161626e+00 -2.77950317e-01 -3.34936008e-02
-9.35700297e-01 8.11451852e-01 4.80792075e-01 8.45334470e-01
-6.33083761e-01 1.60708919e-01 3.27852517e-01 -2.37203911e-01
3.58019173e-01 -3.57277274e-01 1.38572022e-01 -1.91819119e+00
1.87851965e-01 -1.15542710e+00 3.71943593e-01 -6.70063496e-01
-1.62879717e+00 4.20243800e-01 3.20701152e-01 -1.55438149e+00
-1.90590382e-01 -8.39098334e-01 -5.48151970e-01 9.31313872e-01
-1.70680201e+00 -1.63990295e+00 -2.39040479e-01 8.93864691e-01
5.30634701e-01 -5.34665167e-01 9.36397016e-01 3.09566855e-01
-8.42835724e-01 4.20831084e-01 4.31131601e-01 -4.49078530e-02
1.00000405e+00 -1.10485578e+00 -2.77640641e-01 8.38761151e-01
3.82870138e-01 1.04536188e+00 3.64604414e-01 -9.88961235e-02
-1.77836013e+00 -8.18467498e-01 2.44916022e-01 -4.29924130e-01
8.03381443e-01 -2.24249288e-01 -6.61119878e-01 1.03037214e+00
2.46576637e-01 1.97007388e-01 9.07374620e-01 3.01638037e-01
-4.37685728e-01 -4.06323224e-01 -5.58352768e-01 3.24991584e-01
6.38571858e-01 -8.24894786e-01 -6.77351236e-01 4.95523125e-01
5.09684563e-01 -1.15788914e-01 -9.71183836e-01 6.82028353e-01
7.79607415e-01 -1.16669703e+00 1.30759943e+00 -9.43138421e-01
2.25252524e-01 -1.71326071e-01 -6.05632782e-01 -1.18193388e+00
-6.78021133e-01 -5.44660211e-01 -2.24081323e-01 1.31334043e+00
1.29201710e-01 -6.26334429e-01 6.65073395e-01 4.07368749e-01
4.29550605e-03 -9.22233880e-01 -7.55449831e-01 -4.49257553e-01
1.70005098e-01 -3.26387107e-01 6.24563061e-02 1.04379177e+00
-2.18761608e-01 5.90140343e-01 -9.08839643e-01 6.21249974e-01
9.50719595e-01 3.30210686e-01 7.76664197e-01 -1.04565120e+00
-4.84300196e-01 -4.12707962e-02 -2.08964631e-01 -1.20861590e+00
4.53170836e-01 -9.04819250e-01 -3.21915507e-01 -1.20334017e+00
6.03022993e-01 -7.42404163e-02 -6.76032424e-01 1.54158860e-01
-1.14550523e-01 -1.52403172e-02 4.67790775e-02 5.91059089e-01
-5.76468050e-01 7.61971593e-01 1.07731605e+00 -4.33158726e-02
-9.09995139e-02 1.53850883e-01 -6.71114147e-01 1.22851813e+00
3.04004937e-01 -1.49963960e-01 -5.94283998e-01 -5.24510980e-01
2.85115540e-01 3.21391612e-01 4.30824041e-01 -8.01828563e-01
3.76314163e-01 -3.09996605e-01 3.46887171e-01 -6.38632476e-01
5.13856649e-01 -9.29137528e-01 1.62063807e-01 -8.04828331e-02
-4.21101809e-01 1.15775689e-01 -1.67404592e-01 9.20252621e-01
-3.44546348e-01 -1.94705948e-01 6.78693652e-01 -1.81450486e-01
-7.09317029e-01 3.22970539e-01 1.46318913e-01 -6.41169101e-02
7.86466837e-01 3.09366155e-02 -4.21810858e-02 -4.31159109e-01
-1.04980159e+00 2.72761822e-01 2.37806380e-01 4.06395346e-01
6.49546385e-01 -1.77737296e+00 -4.92911875e-01 6.53692365e-01
3.33288223e-01 -3.02920282e-01 3.30203295e-01 1.05524409e+00
-2.27362901e-01 6.96746945e-01 -1.86380059e-01 -6.34684086e-01
-1.03210616e+00 8.39722574e-01 2.87415862e-01 -2.87437856e-01
-3.55986774e-01 6.99614227e-01 6.53082967e-01 -7.26706207e-01
2.93748498e-01 -1.44654969e-02 -5.71075916e-01 1.49582282e-01
2.10539892e-01 3.67823720e-01 -2.93340713e-01 -9.66405213e-01
-2.74241894e-01 1.04558396e+00 -2.75876746e-02 -1.15059711e-01
1.68108666e+00 -4.30705488e-01 -3.96610707e-01 7.97262430e-01
1.56758392e+00 2.02253565e-01 -1.12762392e+00 -6.70015812e-01
-1.30598187e-01 -2.07879797e-01 9.02821273e-02 -1.91243067e-01
-9.65766370e-01 9.69692945e-01 5.40665150e-01 -7.85022676e-02
1.11980796e+00 -2.99413502e-01 3.87304991e-01 6.22162282e-01
3.46139133e-01 -7.06751168e-01 2.26614829e-02 3.43341380e-01
1.08207834e+00 -1.51674843e+00 3.82958591e-01 -2.64378697e-01
-4.82524753e-01 1.38584721e+00 4.70866472e-01 -4.94349182e-01
9.01394963e-01 -1.88419223e-01 -6.86240867e-02 -3.22734416e-01
-7.40357578e-01 1.87238529e-01 8.15424860e-01 2.60350019e-01
4.95030552e-01 -2.95469582e-01 -2.97178030e-01 7.47742057e-01
2.33710468e-01 -1.72989950e-01 2.35536322e-01 4.59818393e-01
-2.33041793e-01 -1.05665314e+00 -5.51211715e-01 1.05556533e-01
-3.29808235e-01 8.98020249e-03 -2.77458411e-02 8.08766186e-01
5.52607141e-02 6.96369350e-01 -5.27660370e-01 -2.24638313e-01
3.11942250e-01 2.07641482e-01 3.54305387e-01 -6.05500102e-01
7.33059049e-02 6.58425450e-01 -2.29436561e-01 -4.92573529e-01
-1.03810000e+00 -7.56987214e-01 -3.01615059e-01 1.57537028e-01
-4.17731702e-01 2.39121486e-02 2.03162760e-01 1.01596832e+00
8.36203173e-02 1.83094531e-01 9.78679478e-01 -8.45688641e-01
-1.17723846e+00 -9.30041075e-01 -7.50121534e-01 3.24782372e-01
4.33688760e-01 -7.83447981e-01 -5.47663093e-01 1.72251612e-01] | [8.38999080657959, 4.556726932525635] |
b6554c84-fd82-40b7-8586-f959fbf3f668 | meta-learning-for-low-resource-neural-machine | 1808.08437 | null | http://arxiv.org/abs/1808.08437v1 | http://arxiv.org/pdf/1808.08437v1.pdf | Meta-Learning for Low-Resource Neural Machine Translation | In this paper, we propose to extend the recently introduced model-agnostic
meta-learning algorithm (MAML) for low-resource neural machine translation
(NMT). We frame low-resource translation as a meta-learning problem, and we
learn to adapt to low-resource languages based on multilingual high-resource
language tasks. We use the universal lexical
representation~\citep{gu2018universal} to overcome the input-output mismatch
across different languages. We evaluate the proposed meta-learning strategy
using eighteen European languages (Bg, Cs, Da, De, El, Es, Et, Fr, Hu, It, Lt,
Nl, Pl, Pt, Sk, Sl, Sv and Ru) as source tasks and five diverse languages (Ro,
Lv, Fi, Tr and Ko) as target tasks. We show that the proposed approach
significantly outperforms the multilingual, transfer learning based
approach~\citep{zoph2016transfer} and enables us to train a competitive NMT
system with only a fraction of training examples. For instance, the proposed
approach can achieve as high as 22.04 BLEU on Romanian-English WMT'16 by seeing
only 16,000 translated words (~600 parallel sentences). | ['Jiatao Gu', 'Yun Chen', 'Kyunghyun Cho', 'Yong Wang', 'Victor O. K. Li'] | 2018-08-25 | meta-learning-for-low-resource-neural-machine-1 | https://aclanthology.org/D18-1398 | https://aclanthology.org/D18-1398.pdf | emnlp-2018-10 | ['low-resource-neural-machine-translation'] | ['natural-language-processing'] | [ 3.42180692e-02 -1.35215253e-01 -5.07955015e-01 7.48940883e-03
-1.53069198e+00 -5.97775280e-01 1.06358922e+00 -1.15345992e-01
-9.62626517e-01 1.47300148e+00 -6.39167940e-03 -9.06023026e-01
2.56718367e-01 -3.88362259e-01 -1.05124056e+00 -1.56093314e-01
4.37334239e-01 8.42108905e-01 -1.82791784e-01 -6.57376409e-01
-2.85021437e-04 1.27477169e-01 -9.03451025e-01 7.33076274e-01
1.11517966e+00 4.24350172e-01 5.83301663e-01 6.10615313e-01
-2.85144120e-01 5.39093614e-01 -5.45194030e-01 -7.85670698e-01
7.57476091e-02 -7.77846575e-01 -1.09555292e+00 -4.80628163e-01
2.50725687e-01 2.55715877e-01 -7.53002390e-02 9.90737200e-01
7.06654489e-01 -7.58097917e-02 8.54233623e-01 -7.70398378e-01
-8.01346660e-01 1.15134048e+00 -6.99664652e-01 3.58177185e-01
1.15780801e-01 -7.33331516e-02 7.84264147e-01 -1.43768704e+00
1.07858348e+00 1.28513944e+00 5.64314008e-01 7.60370612e-01
-9.42038596e-01 -8.90970886e-01 -8.84254649e-02 2.83410668e-01
-1.42429388e+00 -6.66564882e-01 2.92084992e-01 -1.20480485e-01
1.51463187e+00 1.19637229e-01 2.86010206e-01 1.57763100e+00
5.65850675e-01 7.98382998e-01 1.61398709e+00 -9.94838834e-01
2.41653668e-03 5.07893085e-01 -3.42575401e-01 6.42237008e-01
2.34914087e-02 -7.79525712e-02 -6.68548346e-01 -1.20503947e-01
4.59553450e-01 -6.09751225e-01 2.48261094e-02 1.23852178e-01
-1.80277956e+00 7.27031112e-01 4.45319433e-03 6.14628017e-01
-2.44393289e-01 -1.31443202e-01 5.34434259e-01 1.05369782e+00
9.04434502e-01 1.91075981e-01 -1.06818032e+00 -1.99789807e-01
-7.62073159e-01 -1.51362076e-01 6.65583253e-01 1.45204699e+00
8.15000951e-01 2.97061980e-01 -6.37311637e-02 1.23597288e+00
8.75675455e-02 8.75689507e-01 1.02239013e+00 -4.40200210e-01
1.17483449e+00 8.15507919e-02 1.16049699e-01 -2.07121551e-01
-3.09450865e-01 -5.25183618e-01 -1.02605987e+00 -4.38021064e-01
-6.81956857e-02 -4.08702224e-01 -8.34968865e-01 1.84498692e+00
-4.56625270e-03 -1.81083560e-01 6.26416087e-01 3.29011083e-01
7.12923706e-01 9.43624854e-01 3.79641540e-02 -6.45570755e-01
1.04313731e+00 -1.44486010e+00 -5.67091882e-01 -3.89846921e-01
1.00952220e+00 -1.23714161e+00 1.12294281e+00 2.94695616e-01
-1.27820241e+00 -7.15949714e-01 -8.86743367e-01 3.63492966e-02
-5.97297668e-01 5.34705341e-01 2.22640693e-01 4.30738747e-01
-1.13880098e+00 4.90469038e-01 -6.31279767e-01 -8.00047517e-01
2.87834555e-02 3.97979289e-01 -4.34718281e-01 -1.72582626e-01
-1.48202801e+00 1.38960958e+00 9.76884007e-01 -8.52911025e-02
-7.92994082e-01 -3.43170166e-01 -5.23979902e-01 -5.88084280e-01
4.54153195e-02 -7.86457479e-01 1.18925357e+00 -1.25639701e+00
-1.92198229e+00 1.06311226e+00 -8.60499889e-02 -3.94821376e-01
6.40188754e-01 -1.63762465e-01 -8.70269060e-01 -2.15929762e-01
9.07286108e-02 6.91572249e-01 4.97212023e-01 -1.05993807e+00
-9.41072106e-01 -1.09747723e-02 -3.95430326e-01 3.13768536e-01
-3.30866188e-01 4.66277361e-01 -1.36895880e-01 -8.14146101e-01
-2.03436226e-01 -1.04398263e+00 -5.81142791e-02 -8.83396208e-01
-1.65317446e-01 -9.48080048e-02 3.00179571e-01 -1.01817191e+00
1.11474872e+00 -1.61275542e+00 6.54189944e-01 -1.50208339e-01
-3.98955524e-01 3.50344837e-01 -4.63226020e-01 9.07825410e-01
9.34579819e-02 1.44892812e-01 -2.38904610e-01 -3.09320211e-01
-7.04759732e-02 3.96978855e-01 -6.72434643e-02 2.91157097e-01
-4.31510210e-02 1.19906878e+00 -9.66170669e-01 -4.37755674e-01
-3.06689441e-02 1.56891301e-01 -1.25257760e-01 -2.34800624e-03
-2.49028727e-01 6.88415170e-01 -1.35637730e-01 6.34151816e-01
2.83194602e-01 7.93943107e-02 3.37102860e-01 -7.12488603e-04
-3.57806325e-01 3.38139862e-01 -5.97898602e-01 2.09761214e+00
-1.06365705e+00 5.08644700e-01 -1.53150901e-01 -7.77860761e-01
9.45971251e-01 6.77199364e-01 1.90467507e-01 -9.23856139e-01
1.58231884e-01 1.10453153e+00 5.36882132e-02 -3.53253514e-01
5.50867677e-01 -1.43778816e-01 -3.13699543e-01 6.82259083e-01
6.57716990e-01 1.06183328e-01 1.59675971e-01 -2.90342808e-01
6.23587728e-01 4.70978528e-01 5.48264742e-01 -4.18657750e-01
6.80799425e-01 1.03160821e-01 4.08296973e-01 5.41619718e-01
-6.67614350e-03 1.64438292e-01 -2.22666651e-01 -3.00521225e-01
-1.44006133e+00 -9.41002548e-01 -2.50584027e-03 1.47159290e+00
-3.47300678e-01 -3.16474825e-01 -8.01417708e-01 -5.86825907e-01
-4.55975175e-01 8.37587535e-01 -1.90322638e-01 -1.53070226e-01
-1.02922642e+00 -9.24807787e-01 7.87676930e-01 8.46447498e-02
6.34466231e-01 -1.34418750e+00 -3.83577235e-02 4.71601605e-01
-6.17329061e-01 -1.17303491e+00 -4.46696639e-01 2.56132364e-01
-8.93711269e-01 -2.53375411e-01 -1.02244389e+00 -1.08012235e+00
3.43499184e-01 -1.83748215e-01 1.29379404e+00 -4.91982281e-01
1.71095595e-01 -1.61895901e-02 -4.10587996e-01 -2.84285814e-01
-1.06147921e+00 7.86146998e-01 4.93024528e-01 -2.51854539e-01
3.22155416e-01 -4.39382970e-01 7.59036839e-02 2.13069141e-01
-5.73589504e-01 3.89702886e-01 1.09338892e+00 1.04517710e+00
6.75389946e-01 -5.53596616e-01 9.34576333e-01 -1.01719975e+00
6.48891687e-01 -5.95309973e-01 -2.42840782e-01 7.05043435e-01
-6.80747330e-01 5.29972464e-02 8.38697791e-01 -7.10387349e-01
-1.04171789e+00 -2.35350266e-01 -1.37482166e-01 -2.49847561e-01
3.39529924e-02 7.26528466e-01 -2.05057904e-01 -1.92712303e-02
7.50438154e-01 5.79036653e-01 -6.60576463e-01 -6.87446773e-01
6.22067690e-01 1.10070205e+00 4.99241501e-01 -8.84446025e-01
7.98516929e-01 -1.79869950e-01 -4.50483918e-01 -5.62563658e-01
-5.24455845e-01 -5.73221110e-02 -1.11608636e+00 7.61154070e-02
5.73352218e-01 -1.19414508e+00 4.71597128e-02 3.28972310e-01
-1.34899747e+00 -5.82508564e-01 -5.41963652e-02 8.05505455e-01
-8.00402164e-01 -6.68862194e-04 -1.01038218e+00 -4.35001284e-01
-8.70550811e-01 -1.03197932e+00 8.75588953e-01 -2.55982339e-01
-2.32392065e-02 -1.30225539e+00 2.43356615e-01 2.37973005e-01
6.51603639e-01 -1.10371737e-02 1.18416953e+00 -7.27475643e-01
-4.97440733e-02 2.23724037e-01 -9.98536944e-02 3.72899264e-01
2.45828941e-01 -3.24728668e-01 -6.04013026e-01 -7.82471478e-01
-2.92969614e-01 -6.12332165e-01 6.34144127e-01 -1.09254345e-01
3.42902571e-01 -4.86494035e-01 -1.21340618e-01 6.12928748e-01
1.50387239e+00 1.69372797e-01 3.20643902e-01 6.12230062e-01
6.13384068e-01 2.39560425e-01 6.56697452e-01 -5.26166521e-02
4.10699725e-01 6.96775138e-01 -3.48189294e-01 -8.19707811e-02
-2.38496214e-01 -3.40921551e-01 9.86005962e-01 1.93184900e+00
-3.34327698e-01 -2.63701260e-01 -1.05047262e+00 4.73341048e-01
-1.75855267e+00 -5.44532776e-01 1.24896534e-01 2.34279227e+00
1.13902080e+00 9.52795818e-02 -4.38281819e-02 -4.59443331e-01
6.07548594e-01 -1.86182529e-01 -1.68360084e-01 -9.42339182e-01
-4.87121642e-01 5.21730542e-01 7.10802197e-01 5.69889665e-01
-8.16522837e-01 1.67905056e+00 5.61007547e+00 1.19675958e+00
-1.22904003e+00 7.88552463e-01 5.05552292e-01 1.19138561e-01
-2.97599435e-01 -1.64639235e-01 -7.85630226e-01 2.77636379e-01
1.73837352e+00 -5.20663083e-01 6.43933058e-01 3.99351656e-01
-1.76224913e-02 5.56647897e-01 -9.91657734e-01 8.02197874e-01
2.67238587e-01 -1.12005997e+00 3.90059501e-01 -1.48132771e-01
1.07801342e+00 7.22137332e-01 1.58589378e-01 8.12894821e-01
4.02294785e-01 -9.10419106e-01 7.34595239e-01 2.46428624e-01
1.28279734e+00 -1.01467001e+00 6.76617265e-01 6.73332036e-01
-1.02149940e+00 1.75237402e-01 -8.41631293e-01 2.58942246e-01
-2.52817404e-02 1.77824143e-02 -8.81719351e-01 1.30474937e+00
4.48373616e-01 5.41806042e-01 -5.76196849e-01 2.87044793e-01
-1.67500347e-01 7.16465175e-01 5.57003841e-02 1.69569515e-02
4.14031684e-01 -2.15158433e-01 4.93054807e-01 1.59771907e+00
6.40954256e-01 -3.94157737e-01 2.70382553e-01 3.21826309e-01
-5.09623826e-01 8.33915055e-01 -6.03587210e-01 -1.30878137e-02
2.56696016e-01 1.06974375e+00 -4.66599911e-01 -5.13448060e-01
-4.23823714e-01 1.40042818e+00 6.90047085e-01 4.27361578e-01
-5.84313691e-01 -1.84484795e-01 1.57116845e-01 -4.15361971e-01
3.41418162e-02 -2.47960210e-01 1.45237565e-01 -1.48887503e+00
-9.50618088e-02 -1.30759597e+00 2.84196943e-01 -5.84955633e-01
-1.29070365e+00 1.12153399e+00 4.86019626e-02 -1.42265463e+00
-6.40205204e-01 -5.98765433e-01 -5.00354245e-02 1.33254135e+00
-1.60812616e+00 -1.70594835e+00 5.37551761e-01 6.32746100e-01
9.63133335e-01 -8.76120210e-01 1.03285491e+00 5.87557554e-01
-5.09974897e-01 9.77025926e-01 6.96437776e-01 7.97690302e-02
1.07051754e+00 -9.88825798e-01 6.56985879e-01 5.52211344e-01
3.90873700e-01 4.97530490e-01 4.28582579e-01 -6.24524891e-01
-1.45529354e+00 -1.40922582e+00 1.47348845e+00 -5.29086947e-01
8.28938186e-01 -4.17209715e-01 -5.71765423e-01 8.96823227e-01
6.51255369e-01 -2.16440335e-01 5.25252223e-01 -1.28747761e-01
-3.82880986e-01 7.08217919e-02 -1.04194474e+00 7.50511706e-01
1.06222165e+00 -6.33447707e-01 -6.87055707e-01 6.81945324e-01
8.30986142e-01 -4.67731863e-01 -1.11148310e+00 3.79763633e-01
5.27648568e-01 -3.08966666e-01 8.33167732e-01 -1.04260588e+00
5.00175774e-01 1.52592674e-01 -3.87291968e-01 -1.79238427e+00
-2.85361856e-01 -6.36949956e-01 7.90885836e-02 1.31491280e+00
1.04404020e+00 -7.21547186e-01 1.52565747e-01 -4.49375540e-01
-3.42127979e-01 -5.53523719e-01 -1.40189147e+00 -1.05958164e+00
9.57646191e-01 -1.54823646e-01 4.64165032e-01 1.29054189e+00
1.45756314e-02 6.85521483e-01 -7.93316603e-01 -1.29368857e-01
4.60808903e-01 1.31132994e-02 5.07122517e-01 -9.43584561e-01
-5.56283116e-01 -4.72010016e-01 1.80709913e-01 -6.44229949e-01
5.13550520e-01 -1.45958674e+00 -2.65895873e-01 -1.40354741e+00
2.65388906e-01 -3.13047111e-01 -7.05940187e-01 5.05033731e-01
-6.94756135e-02 4.86349136e-01 1.56223342e-01 5.06945789e-01
-4.80658680e-01 3.02449554e-01 1.18760240e+00 -2.31432065e-01
-3.65500636e-02 7.65967881e-03 -2.35503376e-01 4.59822863e-01
8.07232857e-01 -5.38501203e-01 7.66373519e-03 -9.64250803e-01
3.34345609e-01 1.23060092e-01 -4.10504192e-01 -5.65841973e-01
1.84504658e-01 -1.98408335e-01 3.58237356e-01 -3.44530612e-01
5.95952310e-02 -5.71994543e-01 2.96320826e-01 6.33062899e-01
-4.36323702e-01 7.51429498e-01 3.82501990e-01 1.03782095e-01
-1.60312697e-01 -1.03227876e-01 7.31730700e-01 -4.83853430e-01
-5.25200188e-01 1.39602080e-01 -4.41209763e-01 5.56602217e-02
4.90120262e-01 3.10872853e-01 -4.00416225e-01 -4.14132588e-02
-4.44548428e-01 -3.00573763e-02 2.73516685e-01 7.60025024e-01
3.80817503e-01 -1.51518142e+00 -1.33937860e+00 -4.91280062e-03
3.90636712e-01 -6.41406178e-01 1.15289837e-02 9.49453294e-01
-5.19563556e-01 6.53642654e-01 -4.69455808e-01 -3.26239735e-01
-8.44611347e-01 4.74238783e-01 2.82150596e-01 -6.37318909e-01
-3.93782109e-01 5.28124213e-01 -3.74186844e-01 -1.11447763e+00
-2.21842915e-01 2.08199341e-02 -3.20309252e-02 -4.95290980e-02
9.88285840e-02 3.72877359e-01 3.81095648e-01 -1.03757071e+00
-1.10306822e-01 4.93412346e-01 -2.37857744e-01 -7.00000107e-01
1.08588850e+00 -2.98341572e-01 -2.54266262e-01 8.84398103e-01
1.26823843e+00 7.69063383e-02 -3.25410992e-01 -6.20125115e-01
3.97988141e-01 7.89262876e-02 -3.73636782e-01 -1.15650284e+00
-5.94693542e-01 8.75359952e-01 6.89309955e-01 -6.56116009e-01
9.65178251e-01 -7.01940805e-02 9.24228966e-01 6.03405118e-01
9.61343110e-01 -1.31554139e+00 -3.15110087e-01 8.29698443e-01
8.05819511e-01 -1.12694204e+00 -2.00590998e-01 2.33724728e-01
-5.76615810e-01 1.11813390e+00 3.04558814e-01 3.06600988e-01
1.07419744e-01 1.17284954e-01 3.53327721e-01 4.29125249e-01
-1.02098894e+00 -1.42201856e-02 3.24635595e-01 3.32445234e-01
7.27935851e-01 2.74151236e-01 -6.96852565e-01 3.09950471e-01
-4.16548669e-01 -1.66357651e-01 3.79886150e-01 8.87030542e-01
-3.56142670e-01 -1.60147274e+00 -1.85594738e-01 2.18304098e-01
-6.61809683e-01 -5.10986924e-01 -3.96072775e-01 1.06210494e+00
3.93668786e-02 8.20048034e-01 -2.95935035e-01 -4.47517157e-01
2.42768615e-01 4.81591761e-01 6.56478643e-01 -6.30235970e-01
-9.86473858e-01 3.28280747e-01 2.53835142e-01 9.54197571e-02
-4.53414530e-01 -5.37175834e-01 -7.23444879e-01 -1.67364597e-01
-9.43061560e-02 3.97360653e-01 7.62492061e-01 1.14508951e+00
4.62345257e-02 2.57130116e-01 8.04846287e-01 -5.85395157e-01
-6.34727478e-01 -1.54989958e+00 -1.17398448e-01 3.04070506e-02
-2.17839442e-02 -2.37481177e-01 -9.95543152e-02 -5.37621230e-02] | [11.642589569091797, 10.342035293579102] |
db79e814-97ca-41cf-a5ba-75386346698b | docile-benchmark-for-document-information | 2302.05658 | null | https://arxiv.org/abs/2302.05658v2 | https://arxiv.org/pdf/2302.05658v2.pdf | DocILE Benchmark for Document Information Localization and Extraction | This paper introduces the DocILE benchmark with the largest dataset of business documents for the tasks of Key Information Localization and Extraction and Line Item Recognition. It contains 6.7k annotated business documents, 100k synthetically generated documents, and nearly~1M unlabeled documents for unsupervised pre-training. The dataset has been built with knowledge of domain- and task-specific aspects, resulting in the following key features: (i) annotations in 55 classes, which surpasses the granularity of previously published key information extraction datasets by a large margin; (ii) Line Item Recognition represents a highly practical information extraction task, where key information has to be assigned to items in a table; (iii) documents come from numerous layouts and the test set includes zero- and few-shot cases as well as layouts commonly seen in the training set. The benchmark comes with several baselines, including RoBERTa, LayoutLMv3 and DETR-based Table Transformer; applied to both tasks of the DocILE benchmark, with results shared in this paper, offering a quick starting point for future work. The dataset, baselines and supplementary material are available at https://github.com/rossumai/docile. | ['Dimosthenis Karatzas', 'Mickaël Coustaty', 'Antoine Doucet', 'Jiří Matas', 'Matyáš Skalický', 'Matěj Kocián', 'Ahmed Hamdi', 'Yash Patel', 'Michal Uřičář', 'Milan Šulc', 'Štěpán Šimsa'] | 2023-02-11 | null | null | null | null | ['unsupervised-pre-training', 'key-information-extraction'] | ['methodology', 'natural-language-processing'] | [ 2.59937216e-02 -5.12244068e-02 -4.65785384e-01 -9.40867960e-02
-1.21084380e+00 -9.78354692e-01 8.81743848e-01 5.66178381e-01
-1.44379482e-01 8.71078074e-01 4.10400748e-01 -1.65427163e-01
-2.72196442e-01 -4.96255934e-01 -9.01382208e-01 -4.58726406e-01
-2.49676526e-01 9.87411261e-01 2.91966230e-01 -2.02186406e-01
6.71888769e-01 5.18926203e-01 -1.40153646e+00 8.12524021e-01
5.34244299e-01 1.44243217e+00 2.56240591e-02 7.92652428e-01
-4.35013473e-01 1.03963745e+00 -9.78533268e-01 -4.66446042e-01
3.62553000e-01 -1.16598025e-01 -9.27971959e-01 1.38656512e-01
9.03663456e-01 -2.10260183e-01 -4.03804660e-01 5.15607774e-01
5.43208301e-01 -7.23161697e-02 9.73375320e-01 -1.41364253e+00
-5.28294921e-01 9.73681331e-01 -5.19818604e-01 2.84968704e-01
3.89310002e-01 -1.73504770e-01 1.28011096e+00 -1.13665831e+00
1.04941213e+00 8.97714853e-01 4.78330135e-01 -3.78928930e-02
-8.97712648e-01 -3.11250329e-01 -2.98989508e-02 3.66677493e-01
-1.53116858e+00 -6.14863455e-01 3.84234220e-01 -3.78407538e-01
1.24402320e+00 3.28879416e-01 4.48804915e-01 1.20973122e+00
1.66832626e-01 1.30930412e+00 6.31906211e-01 -6.84495986e-01
2.46109664e-01 3.81412834e-01 3.47658843e-01 3.87669444e-01
5.33222914e-01 -5.28778195e-01 -7.40993977e-01 -2.41645668e-02
2.83428371e-01 -1.67246401e-01 -1.59741178e-01 -5.43801963e-01
-1.46898472e+00 2.23713428e-01 1.88551277e-01 2.52002448e-01
-3.73070277e-02 -1.70483306e-01 8.43921483e-01 3.24681044e-01
8.21989849e-02 7.33793557e-01 -6.57194912e-01 -3.91648263e-01
-8.77327144e-01 4.60188389e-01 1.14185977e+00 1.86146188e+00
4.21564460e-01 -2.46257037e-01 -5.95069468e-01 7.94931293e-01
-1.47702008e-01 7.12695897e-01 3.13286275e-01 -5.58500707e-01
1.22932696e+00 7.89513767e-01 3.01464438e-01 -8.07856858e-01
-4.25866842e-01 -4.70564246e-01 -6.85018301e-01 -3.66305411e-01
5.54510593e-01 2.38058209e-01 -8.60307693e-01 8.81697953e-01
2.41402928e-02 -4.01400983e-01 2.86032036e-02 2.34789744e-01
1.03509760e+00 7.40633607e-01 -6.97175443e-01 2.06410307e-02
1.57896459e+00 -1.25239515e+00 -8.89270842e-01 -1.76458687e-01
7.58937180e-01 -9.51769412e-01 1.14514041e+00 8.16863775e-01
-9.72943246e-01 -4.20319825e-01 -1.08356452e+00 -3.24960619e-01
-9.69021559e-01 4.84571248e-01 4.46695656e-01 3.96709770e-01
-6.85724795e-01 6.72590062e-02 -2.26527333e-01 -4.81706023e-01
4.07048553e-01 -2.00075172e-02 -3.50204468e-01 -3.49500775e-01
-9.21964347e-01 6.46712124e-01 5.90149283e-01 -2.85315420e-02
-7.09297061e-01 -8.50641012e-01 -7.31601477e-01 1.30555004e-01
1.02265525e+00 -2.69005507e-01 1.16206682e+00 7.80618042e-02
-8.60812426e-01 6.99542522e-01 7.15744421e-02 -5.02656639e-01
6.01029456e-01 -5.00884891e-01 -5.58603168e-01 1.89933866e-01
2.44658872e-01 4.58710164e-01 4.77815986e-01 -1.20946765e+00
-8.57088625e-01 -1.91574395e-01 -2.71038711e-01 1.87283546e-01
-2.95852363e-01 -1.15756534e-01 -1.20684242e+00 -7.88996279e-01
-1.98552817e-01 -8.06497395e-01 3.21054965e-01 -5.08661509e-01
-1.27220559e+00 7.59542510e-02 7.06271291e-01 -6.29260182e-01
1.56639743e+00 -2.16933942e+00 -2.60751426e-01 2.72329688e-01
5.95862232e-02 -9.05410759e-03 -1.07363969e-01 1.15492320e+00
1.10655949e-01 1.16326876e-01 5.52527979e-02 -3.16283494e-01
3.72091174e-01 -2.25513130e-01 -6.98490441e-01 7.58748278e-02
-2.04971973e-02 1.15105164e+00 -5.61485529e-01 -6.08797789e-01
1.31908685e-01 1.30124111e-02 -1.37321025e-01 -3.46001759e-02
-2.06524640e-01 -1.14109688e-01 -1.71698302e-01 1.08511078e+00
5.47076106e-01 -2.72290170e-01 2.58368030e-02 -4.10357356e-01
2.45074909e-02 5.08888066e-01 -1.57428789e+00 1.47478867e+00
-2.21758187e-01 7.69287229e-01 -3.93818349e-01 -5.36674559e-01
9.42073345e-01 1.90122779e-02 3.34090710e-01 -7.78890371e-01
-1.30339697e-01 1.38022631e-01 -3.88451308e-01 -2.98623681e-01
9.85657454e-01 9.54810917e-01 -5.72110534e-01 3.08077574e-01
6.28087297e-02 -3.56558084e-01 9.36975658e-01 7.13838160e-01
1.44736958e+00 -1.02740608e-01 3.42794240e-01 -2.57891506e-01
3.07362199e-01 1.97294280e-01 2.19570026e-01 1.03482413e+00
2.49176651e-01 7.10755944e-01 8.24937165e-01 -2.30791897e-01
-1.20332658e+00 -1.06991231e+00 -2.59433419e-01 9.01034355e-01
-2.78622229e-02 -9.56774235e-01 -5.32554626e-01 -7.94048965e-01
2.55294532e-01 7.84763515e-01 -6.78090513e-01 2.39009827e-01
-5.40064394e-01 -3.66329998e-01 6.13434434e-01 9.18900430e-01
4.01460528e-01 -1.05257630e+00 -2.31361449e-01 3.42851467e-02
-1.68601215e-01 -1.37938285e+00 -5.69065511e-01 6.26585722e-01
-4.21188414e-01 -1.24330819e+00 -4.08996761e-01 -7.08045006e-01
7.06640482e-01 1.79882735e-01 1.57541454e+00 -1.05835877e-01
-5.39091051e-01 3.86583865e-01 -5.31154692e-01 -6.28554940e-01
-5.93933798e-02 4.97280598e-01 -1.05637975e-01 -4.03518558e-01
3.46175164e-01 -6.55254861e-03 -2.76776642e-01 4.25891608e-01
-7.17456102e-01 6.18905481e-03 8.68998230e-01 8.66313517e-01
7.38902271e-01 2.13707343e-01 2.70873427e-01 -1.22453701e+00
4.93305683e-01 -2.67424703e-01 -6.76217556e-01 5.67276180e-01
-5.79159617e-01 -5.62014803e-02 7.66735911e-01 -4.31616344e-02
-8.39668036e-01 -2.28124857e-01 2.26877525e-01 1.31287977e-01
-2.26064667e-01 3.87339592e-01 -6.12480581e-01 5.26591539e-01
5.53793252e-01 3.66297662e-01 -6.66847646e-01 -7.66883552e-01
4.08008218e-01 7.42770314e-01 7.52498567e-01 -6.57507300e-01
7.80818164e-01 3.58739406e-01 -1.40327945e-01 -8.06518912e-01
-8.87787461e-01 -6.50870442e-01 -1.08369994e+00 1.40435532e-01
2.15740561e-01 -7.19700873e-01 -4.29350138e-01 5.60696602e-01
-6.62669182e-01 -4.10638571e-01 -5.89128435e-01 6.76324591e-02
-5.31855941e-01 1.70894340e-01 -7.60667026e-01 -4.93770570e-01
-3.70972872e-01 -9.67278063e-01 1.23877919e+00 -1.14263721e-01
-2.23295346e-01 -6.88479722e-01 -3.08647841e-01 3.42429370e-01
-7.42859964e-04 2.08961889e-01 1.01381111e+00 -1.02829671e+00
-8.45098615e-01 -6.22378826e-01 -3.18643749e-01 1.49597347e-01
1.53707013e-01 3.39865834e-01 -7.47612655e-01 -2.26979181e-01
-6.40641510e-01 -6.20178342e-01 1.00234461e+00 6.94766790e-02
1.10467088e+00 -2.67401725e-01 -5.84912658e-01 5.10009468e-01
1.34103644e+00 3.21613520e-01 6.87306464e-01 6.74161017e-01
7.83058107e-01 5.55893600e-01 9.53223526e-01 7.71984041e-01
4.79904801e-01 7.88271666e-01 1.92310736e-01 1.46429464e-01
-1.55461013e-01 -3.04816157e-01 6.97550699e-02 8.78532469e-01
4.26221132e-01 -8.25095177e-01 -1.24573100e+00 6.54141068e-01
-1.77381229e+00 -8.73871326e-01 -1.80985853e-01 2.13881946e+00
7.16642618e-01 7.15356767e-01 1.19245529e-01 6.28749132e-01
3.13256413e-01 8.28176960e-02 -4.51815337e-01 -1.08372554e-01
-3.32774192e-01 -1.86603516e-01 8.03295732e-01 -3.08796410e-02
-1.34395373e+00 8.19981515e-01 6.18361759e+00 1.07852399e+00
-5.77389419e-01 -4.68275398e-01 6.47566140e-01 -2.34085634e-01
-1.02523878e-01 -2.99482316e-01 -1.58811700e+00 5.52518606e-01
8.80069792e-01 -8.22237656e-02 6.29563928e-02 7.73162723e-01
-2.96462327e-01 -2.99704194e-01 -1.32840979e+00 8.43456447e-01
2.72200614e-01 -1.53214896e+00 1.92781277e-02 1.22077875e-01
6.23200715e-01 -8.73187184e-02 2.17001289e-01 5.04376769e-01
2.47527212e-01 -8.42831612e-01 9.65519369e-01 4.90257710e-01
8.94082606e-01 -9.19341028e-01 8.62085104e-01 3.25943261e-01
-1.30128694e+00 -5.20465290e-03 -2.87529349e-01 4.66354787e-01
-7.73855075e-02 6.17309928e-01 -9.83675659e-01 6.06104374e-01
9.38637197e-01 6.81674540e-01 -1.14500046e+00 1.06038857e+00
-2.28682607e-01 6.09313369e-01 -4.49101210e-01 -1.74776956e-01
1.92910299e-01 1.06835522e-01 2.10830227e-01 1.52257717e+00
1.31625921e-01 -5.18951774e-01 -5.45592839e-03 3.13092560e-01
-2.76427269e-01 3.41360509e-01 -5.76627433e-01 -2.30538160e-01
9.55309093e-01 1.34339166e+00 -1.14260745e+00 -4.89347816e-01
-3.58333409e-01 8.06707203e-01 2.22885713e-01 1.81910545e-01
-6.32116199e-01 -9.33185995e-01 1.81818515e-01 1.91006422e-01
8.09377193e-01 -8.30726027e-02 -3.60093653e-01 -1.07267570e+00
3.33165169e-01 -9.62334335e-01 4.90336895e-01 -5.80889225e-01
-1.08840692e+00 4.35251504e-01 1.58668563e-01 -1.44463980e+00
-3.71233374e-01 -8.08626354e-01 -2.80518442e-01 4.25471365e-01
-1.12760329e+00 -1.17669499e+00 -3.85275990e-01 1.52000740e-01
5.93501985e-01 -4.66398299e-01 6.69856489e-01 3.82807672e-01
-6.93861246e-01 9.17024434e-01 7.56179571e-01 4.49670196e-01
1.11147273e+00 -1.75629890e+00 9.32349861e-01 6.99238420e-01
4.16081458e-01 5.81809163e-01 4.83593732e-01 -5.93581676e-01
-1.73360217e+00 -1.16783690e+00 8.65871012e-01 -1.09855163e+00
6.99327052e-01 -1.10428739e+00 -7.81933904e-01 8.69741023e-01
1.32439315e-01 5.82553409e-02 6.70411527e-01 1.70420140e-01
-4.49693710e-01 -3.32760334e-01 -8.95308912e-01 4.05065805e-01
1.04893434e+00 -3.50239307e-01 -3.00533086e-01 6.54589117e-01
4.94502246e-01 -7.63444543e-01 -9.73346114e-01 1.25415236e-01
5.85377276e-01 -8.16053569e-01 1.02059078e+00 -3.30450922e-01
4.74721074e-01 -2.21020639e-01 -2.36021027e-01 -1.04246855e+00
-2.04101190e-01 -3.32823217e-01 -7.27338731e-01 1.77628136e+00
7.63841450e-01 -1.80777609e-01 7.64166772e-01 1.38189867e-01
-3.20181131e-01 -8.82508397e-01 -5.53502977e-01 -1.07859278e+00
-2.41024330e-01 -3.45413148e-01 8.24934959e-01 6.71747029e-01
-7.61163458e-02 4.85144079e-01 -4.53002810e-01 -1.78406388e-01
3.90264869e-01 2.46273160e-01 1.18377161e+00 -8.70758176e-01
-2.36552566e-01 -3.24232578e-01 -1.86088726e-01 -1.26289964e+00
-3.27503413e-01 -8.75884354e-01 -4.82523553e-02 -1.80517399e+00
1.23816311e-01 -3.04243058e-01 -2.05253229e-01 5.36017179e-01
1.38178542e-01 2.55481601e-01 2.57939041e-01 2.12321296e-01
-9.59848046e-01 1.59422249e-01 9.57616150e-01 -5.08347809e-01
-1.84680615e-02 -9.71159339e-02 -7.85365701e-01 3.50229651e-01
5.66427946e-01 -1.11346453e-01 -4.21819359e-01 -1.67021558e-01
5.29181898e-01 -8.35444108e-02 -1.94662973e-01 -1.10899675e+00
2.97932416e-01 7.68579170e-02 8.16856265e-01 -1.46059632e+00
2.75636762e-01 -7.73789823e-01 -1.99195787e-01 1.85310230e-01
-3.90522420e-01 1.88668758e-01 4.15802211e-01 4.24167365e-01
-2.63782442e-01 -3.95758301e-01 2.96704829e-01 7.30017498e-02
-1.16396773e+00 1.61171794e-01 -2.56160617e-01 5.08911669e-01
8.95495772e-01 -2.81834543e-01 -8.28236639e-01 -1.81670278e-01
-2.17659116e-01 3.67306203e-01 4.64374959e-01 5.32838225e-01
4.13979113e-01 -1.26470423e+00 -6.60149097e-01 1.06104903e-01
8.42513323e-01 1.99943766e-01 3.74252349e-02 5.52786589e-01
-7.48817325e-01 7.72226512e-01 -1.12530909e-01 -4.91739362e-01
-1.01600122e+00 7.92162955e-01 -2.88912922e-01 -5.94529748e-01
-7.38512874e-01 8.42927694e-01 -1.49277791e-01 -3.77083808e-01
5.01021445e-01 -5.61420739e-01 -1.72946468e-01 5.61568320e-01
8.02406669e-01 4.59829867e-01 6.26744390e-01 -2.22231299e-01
-4.34235603e-01 2.31446683e-01 -6.39435887e-01 1.97797701e-01
1.24767566e+00 -4.80736420e-02 1.48375317e-01 6.27764702e-01
1.09249353e+00 4.36706454e-01 -8.62864733e-01 -3.71943355e-01
4.99506593e-01 -4.71219063e-01 -3.83319050e-01 -1.14444447e+00
-5.91205299e-01 6.23076797e-01 1.90951973e-01 2.94103265e-01
9.73345578e-01 6.84191138e-02 7.22923100e-01 8.60655427e-01
4.22478467e-01 -1.37734568e+00 2.02895120e-01 6.59800351e-01
1.02208531e+00 -1.15580666e+00 3.59318316e-01 -4.09490138e-01
-6.85677707e-01 1.01953709e+00 6.79462194e-01 2.66695291e-01
3.11380863e-01 9.15671825e-01 -7.68180937e-02 -1.10712811e-01
-1.15111947e+00 -1.65832564e-02 5.13388932e-01 4.84381229e-01
3.68833303e-01 -8.95234644e-02 1.86282948e-01 6.61960125e-01
-4.95780349e-01 -3.88442963e-01 4.83443469e-01 1.27204239e+00
-3.60769242e-01 -9.91187453e-01 -2.84246504e-01 9.15153325e-01
-1.68744102e-01 -2.58374721e-01 -6.87166035e-01 1.08490515e+00
-1.29542455e-01 4.26182002e-01 1.48802713e-01 -1.00512356e-01
6.30789161e-01 -4.57378514e-02 3.94648105e-01 -6.27830982e-01
-4.55598325e-01 -7.15593982e-04 3.72925609e-01 -5.23367047e-01
3.16609800e-01 -7.09063232e-01 -1.06062341e+00 -2.40762979e-01
-2.35653520e-01 2.53437638e-01 5.32077670e-01 5.68030775e-01
4.42350030e-01 7.46880293e-01 2.70958304e-01 -5.69030046e-01
-4.95747209e-01 -1.22288442e+00 -8.31408858e-01 3.18344355e-01
1.20007865e-01 -4.84427631e-01 -1.34191096e-01 1.74583554e-01] | [11.696913719177246, 2.7929861545562744] |
ccacdca9-19e3-498b-815f-47899fe29848 | graph-based-methods-coupled-with-specific | 2306.00042 | null | https://arxiv.org/abs/2306.00042v1 | https://arxiv.org/pdf/2306.00042v1.pdf | Graph-based methods coupled with specific distributional distances for adversarial attack detection | Artificial neural networks are prone to being fooled by carefully perturbed inputs which cause an egregious misclassification. These \textit{adversarial} attacks have been the focus of extensive research. Likewise, there has been an abundance of research in ways to detect and defend against them. We introduce a novel approach of detection and interpretation of adversarial attacks from a graph perspective. For an image, benign or adversarial, we study how a neural network's architecture can induce an associated graph. We study this graph and introduce specific measures used to predict and interpret adversarial attacks. We show that graphs-based approaches help to investigate the inner workings of adversarial attacks. | ['Michel Dojat', 'Sophie Achard', 'Martial Mermillod', 'Lucrezia Carboni', 'Dwight Nwaigwe'] | 2023-05-31 | null | null | null | null | ['adversarial-attack', 'adversarial-attack-detection', 'adversarial-attack-detection'] | ['adversarial', 'computer-vision', 'knowledge-base'] | [ 7.30739474e-01 6.23119712e-01 -3.25936154e-02 -2.89151520e-01
-5.22663593e-02 -1.10022140e+00 8.96243870e-01 2.69951195e-01
1.26312941e-01 4.99107927e-01 -8.07962567e-02 -7.10337102e-01
-2.85563059e-02 -1.04758120e+00 -1.06727660e+00 -6.40248179e-01
-3.37268829e-01 8.57825484e-03 1.94694832e-01 -2.94230521e-01
2.33348295e-01 8.48137319e-01 -9.85084176e-01 2.64082760e-01
4.68134552e-01 5.74470878e-01 -6.74302042e-01 9.85276461e-01
2.34686002e-01 1.16476512e+00 -1.22265184e+00 -1.11985111e+00
4.82162088e-01 -5.48398912e-01 -8.47498715e-01 1.97329354e-02
9.26832795e-01 -2.54785810e-02 -8.01465392e-01 1.76933265e+00
2.71457165e-01 -1.05050623e-01 6.20647669e-01 -1.65489161e+00
-7.71636426e-01 1.03385651e+00 -2.23024338e-01 4.80297804e-01
2.10413828e-01 2.03311652e-01 7.98920155e-01 -2.48153135e-01
5.71839392e-01 1.48688471e+00 6.11835659e-01 8.42979789e-01
-1.14067829e+00 -6.28910184e-01 1.43277466e-01 1.27044484e-01
-9.74254906e-01 -4.28421617e-01 1.00900841e+00 -3.10121477e-01
3.62084895e-01 7.48492479e-01 1.95196569e-01 1.54558837e+00
5.35124958e-01 4.64747548e-01 1.02614510e+00 -6.52358890e-01
9.00437459e-02 2.29037598e-01 2.28952497e-01 9.77015972e-01
7.45561779e-01 6.37367606e-01 9.55122896e-03 -2.36506537e-01
5.09263992e-01 -1.90704986e-01 -4.88398403e-01 -2.80065358e-01
-6.04218662e-01 1.02482212e+00 7.08115399e-01 2.22686097e-01
6.00650981e-02 5.19852042e-01 4.95302171e-01 6.31828666e-01
3.95299107e-01 9.94685292e-01 -7.39053115e-02 4.90293533e-01
-2.14584902e-01 -3.35422046e-02 9.96198356e-01 6.85094833e-01
2.74529487e-01 5.71462989e-01 1.61530554e-01 3.27927738e-01
3.88258919e-02 3.97865653e-01 8.52843821e-02 -5.59185088e-01
4.49195087e-01 4.46803629e-01 -4.91122812e-01 -1.66632974e+00
-1.60581693e-01 -4.43354785e-01 -9.32721794e-01 6.91300511e-01
6.27441466e-01 -2.76641965e-01 -9.22108829e-01 1.67861986e+00
1.29643222e-02 1.51268736e-01 8.21259394e-02 5.62182248e-01
3.78582954e-01 2.31354281e-01 6.28430843e-02 1.02508038e-01
8.02049577e-01 -7.36115694e-01 -4.74822104e-01 -3.42099488e-01
5.96042991e-01 -3.86117697e-01 7.07197309e-01 2.76461959e-01
-1.00086737e+00 -3.19099352e-02 -1.34388685e+00 5.44152141e-01
-7.59649396e-01 -5.99467874e-01 4.24565285e-01 1.47769582e+00
-8.41240466e-01 1.09499145e+00 -6.02609754e-01 1.87520206e-01
6.97904587e-01 3.88325304e-01 -3.92380476e-01 -6.17616388e-05
-1.40375781e+00 1.04891610e+00 4.66431260e-01 -1.27983123e-01
-1.16929650e+00 -3.09813023e-01 -7.18840957e-01 -1.50479019e-01
3.95704806e-01 -3.55599046e-01 8.64606798e-01 -1.57664013e+00
-6.27514601e-01 9.90717769e-01 5.21680951e-01 -8.93636703e-01
8.64434600e-01 3.45368385e-01 -8.43039334e-01 2.07709491e-01
-4.53198642e-01 -1.63164049e-01 1.36620986e+00 -1.48769152e+00
3.34442630e-02 -6.30304396e-01 4.73283350e-01 -1.29089758e-01
-6.45996451e-01 1.54467031e-01 3.21618676e-01 -1.16034639e+00
-3.05563241e-01 -9.61767554e-01 -3.52633566e-01 -1.67011082e-01
-1.06214464e+00 3.27986330e-01 9.61894631e-01 -2.02753350e-01
1.23960006e+00 -2.08300614e+00 -1.43321380e-01 4.79412019e-01
8.13128293e-01 5.75770974e-01 4.37957831e-02 4.11540866e-01
-6.11339927e-01 8.37689519e-01 -2.84626842e-01 -1.31933969e-02
8.63238871e-02 3.55082810e-01 -6.42382860e-01 9.41207230e-01
1.98786035e-01 7.69301951e-01 -8.58852744e-01 -1.34522393e-01
1.21101737e-01 3.88974577e-01 -1.37835354e-01 1.40323490e-01
-9.65292677e-02 1.30900532e-01 -4.54414994e-01 6.82954788e-01
5.89563012e-01 3.56176049e-02 9.49042812e-02 -5.93732391e-03
6.06830418e-01 -9.40597355e-02 -8.32390189e-01 4.36966896e-01
-6.13102084e-03 1.03104019e+00 -6.38583526e-02 -1.23345745e+00
7.52290726e-01 1.93473116e-01 -3.01888883e-01 -2.45943949e-01
6.43848062e-01 8.47777631e-03 2.77650267e-01 -3.43618691e-01
1.55690059e-01 -1.81372598e-01 -1.54967651e-01 6.08094394e-01
-1.47637371e-02 2.83141136e-01 -1.48767561e-01 3.48316580e-01
1.64396095e+00 -6.95610166e-01 3.57479095e-01 -1.90362319e-01
5.10384381e-01 -6.76547736e-02 1.22956522e-01 1.24046242e+00
-3.12059820e-01 4.48905200e-01 7.75479138e-01 -7.59226441e-01
-1.13643897e+00 -1.12572753e+00 1.84469044e-01 1.01922596e+00
1.92669079e-01 -1.14425287e-01 -1.14667165e+00 -1.38790202e+00
8.64165351e-02 7.06383228e-01 -1.02336729e+00 -8.83662343e-01
-5.09961247e-01 -6.27946913e-01 1.28667378e+00 4.04915422e-01
3.62289995e-01 -1.13438439e+00 -1.44119918e-01 -2.15309605e-01
4.14944470e-01 -1.11158454e+00 -4.96803939e-01 2.67228007e-01
-6.83776498e-01 -1.44227624e+00 -1.09954156e-01 -4.35299128e-01
1.20620716e+00 4.24946100e-02 1.33969688e+00 5.92757463e-01
-3.98052782e-01 5.10965407e-01 -4.41159457e-01 -9.53384757e-01
-1.31778193e+00 -2.30978295e-01 1.49478063e-01 1.63143069e-01
1.07960351e-01 -5.30727684e-01 -1.61323696e-01 4.06260550e-01
-1.30240250e+00 -6.64636254e-01 3.69133651e-01 4.99010235e-01
8.53437930e-02 5.34620225e-01 2.80608952e-01 -1.64209783e+00
1.09157538e+00 -5.96401095e-01 -5.13773799e-01 3.18791747e-01
-7.69912302e-01 8.87281075e-02 1.09821999e+00 -8.13102007e-01
-5.26327610e-01 -1.14045598e-01 -2.04500891e-02 -7.74510026e-01
-3.36240262e-01 1.07847482e-01 -4.76151288e-01 -8.90315771e-01
1.22537780e+00 -5.36217690e-02 -4.68275184e-03 2.91008782e-02
3.00555617e-01 1.31992355e-01 5.18377304e-01 -2.98958480e-01
1.42429709e+00 3.29247504e-01 4.31003124e-01 -7.93396890e-01
-8.55720997e-01 3.01654488e-01 -4.37676460e-01 -5.00436664e-01
4.35804933e-01 -2.43455917e-01 -5.91534138e-01 5.75637460e-01
-9.89907324e-01 -1.58834681e-01 -3.02787155e-01 -5.17297275e-02
-3.05555761e-01 5.36914349e-01 -3.79438847e-01 -9.17962790e-01
-1.65688396e-01 -9.62465167e-01 2.27995232e-01 -5.93047291e-02
-1.56031847e-01 -1.44598937e+00 -1.50229797e-01 1.05377361e-01
2.57134438e-01 8.91767263e-01 9.36458111e-01 -1.39700520e+00
-4.66212273e-01 -8.14521670e-01 -3.59397493e-02 7.11156011e-01
-9.75309983e-02 4.59665284e-02 -1.09023964e+00 -2.48587236e-01
2.15465724e-01 -1.77853227e-01 6.50902033e-01 -5.72701581e-02
1.20889878e+00 -1.06181419e+00 -2.93238878e-01 6.57940149e-01
1.47889972e+00 3.13698709e-01 7.16552198e-01 1.87597424e-01
9.72923398e-01 5.29027224e-01 -1.57231577e-02 -1.73015874e-02
-4.43271697e-01 2.96031147e-01 1.19957924e+00 -1.27304241e-01
7.49614686e-02 -2.68787622e-01 3.06458175e-01 1.33379266e-01
-1.00544401e-01 -8.56540442e-01 -9.54385817e-01 2.11052626e-01
-1.51788735e+00 -1.21731186e+00 -2.69672722e-01 1.92455304e+00
4.16613996e-01 7.35754788e-01 9.83270258e-02 7.01935828e-01
1.03700852e+00 5.21451056e-01 -4.33210939e-01 -8.28510225e-01
-3.34192812e-01 3.36501360e-01 9.60215926e-01 4.42072600e-01
-1.37006211e+00 8.74027669e-01 7.17566204e+00 7.06011653e-01
-8.21639240e-01 -2.45008379e-01 8.42455566e-01 3.63978893e-01
-3.01810682e-01 -2.16495231e-01 -4.29748416e-01 3.26840878e-01
9.52069044e-01 -2.24447086e-01 4.18376148e-01 1.03796208e+00
-3.08350325e-01 4.86888498e-01 -1.14431405e+00 2.93764800e-01
3.54461819e-01 -1.35463309e+00 3.68268400e-01 2.38593176e-01
5.81038952e-01 -2.74793714e-01 3.76899898e-01 -3.40524353e-02
8.74941230e-01 -1.39352334e+00 4.65052724e-01 3.57193291e-01
4.63243455e-01 -9.86413956e-01 6.96861267e-01 2.96867311e-01
-7.36261785e-01 -6.59558624e-02 -2.88422614e-01 -8.23528469e-02
-3.76397610e-01 4.18586463e-01 -8.69028926e-01 2.49743640e-01
2.18063235e-01 2.81536937e-01 -7.79198468e-01 5.68591475e-01
-3.69159818e-01 7.09904671e-01 1.94799617e-01 -1.21448807e-01
2.22707778e-01 -2.28394698e-02 9.72844005e-01 1.01262283e+00
-1.43018961e-01 -7.48173818e-02 7.75022507e-02 7.97012031e-01
-4.75745112e-01 -2.54078418e-01 -1.37357116e+00 -5.58371484e-01
2.68330812e-01 9.38460648e-01 -7.90440083e-01 -8.37294012e-02
-1.70934629e-02 1.01664960e+00 2.31330663e-01 1.91908956e-01
-8.43315899e-01 -4.92872804e-01 8.14736962e-01 8.93255994e-02
-1.28039777e-01 7.02023283e-02 -3.41622353e-01 -8.76888871e-01
-6.20119274e-02 -1.05134189e+00 5.00003695e-01 -3.67564261e-01
-1.58498585e+00 8.40063035e-01 -2.80659169e-01 -9.19379711e-01
-1.51307257e-02 -7.33131409e-01 -1.10963261e+00 5.51434517e-01
-8.38798761e-01 -8.91589642e-01 -6.97000623e-02 8.06556821e-01
1.87012941e-01 -5.72593391e-01 8.72742891e-01 -1.33156657e-01
-6.67121887e-01 1.01767075e+00 -1.76682159e-01 7.44761944e-01
1.30371943e-01 -1.47960448e+00 7.80281961e-01 1.21721506e+00
5.09151340e-01 4.16296273e-01 9.93476093e-01 -6.39695406e-01
-1.22160423e+00 -1.48411477e+00 5.27061939e-01 -9.86504734e-01
1.03779995e+00 -2.69414723e-01 -8.13987970e-01 9.23263192e-01
4.14385982e-02 1.87959865e-01 5.50022602e-01 -3.00575018e-01
-7.76117504e-01 1.39108106e-01 -1.41590345e+00 9.11035717e-01
1.23950946e+00 -5.80222368e-01 -4.79362547e-01 5.00148594e-01
8.16693306e-01 -2.16977715e-01 -5.14505982e-01 3.19604248e-01
1.66781902e-01 -1.22845232e+00 1.18807590e+00 -1.00961101e+00
4.90205199e-01 1.43673688e-01 1.15387321e-01 -1.44397807e+00
-2.06399485e-01 -8.54523659e-01 -2.69899458e-01 9.23727810e-01
5.04279315e-01 -7.97079802e-01 8.97149622e-01 3.50265056e-01
-3.86882164e-02 -4.89648908e-01 -5.44928491e-01 -9.57748830e-01
2.01081708e-02 -4.37297642e-01 4.34468478e-01 1.35295749e+00
-1.64483771e-01 8.08074400e-02 -3.25441211e-01 4.61442262e-01
8.15035522e-01 -5.27209044e-01 6.84316635e-01 -1.13348210e+00
-2.08171755e-01 -7.41418123e-01 -1.00471413e+00 -1.22399569e-01
3.17280859e-01 -9.78833616e-01 -2.94790447e-01 -7.00508118e-01
-3.66335154e-01 -2.53525555e-01 -2.68008620e-01 3.51158410e-01
-1.48982972e-01 6.01777554e-01 1.80241495e-01 -2.89571378e-02
-2.44375065e-01 -1.70772985e-01 9.90074158e-01 -3.70712012e-01
4.53733742e-01 4.00011420e-01 -8.64373446e-01 1.00628865e+00
1.03308821e+00 -8.10296535e-01 -4.79826897e-01 -2.40605831e-01
3.93149167e-01 -2.84563810e-01 5.83673358e-01 -1.05369925e+00
-4.69281897e-02 -8.34667534e-02 2.97086805e-01 2.56182909e-01
5.97930588e-02 -9.52105999e-01 1.47623003e-01 7.21972764e-01
-5.74010789e-01 3.44441980e-01 -4.79707457e-02 9.37099278e-01
-2.88458224e-02 -4.66602921e-01 1.03456891e+00 -3.67768943e-01
-1.42519251e-01 4.92758930e-01 -3.74644905e-01 2.97613323e-01
1.36344159e+00 -2.05085918e-01 -6.00121439e-01 -5.78284979e-01
-9.42727149e-01 -2.07603842e-01 4.99791473e-01 3.55255455e-01
6.37914717e-01 -1.08153439e+00 -4.23061430e-01 2.25044355e-01
-5.57754077e-02 -5.94670177e-01 -1.18899010e-01 1.89549789e-01
-7.04422474e-01 -1.04908936e-01 -3.08279276e-01 -6.05003312e-02
-1.62638187e+00 1.06008494e+00 6.11130893e-01 -2.68397689e-01
-4.51790988e-01 1.01563108e+00 1.05466604e-01 -1.40129654e-02
4.41397280e-01 2.58610368e-01 -1.89571798e-01 -2.07875788e-01
4.42558050e-01 3.49561274e-01 -8.47381428e-02 -7.24179745e-01
-1.28539488e-01 -1.01180084e-01 -1.35512173e-01 3.57309043e-01
9.01767135e-01 3.04908961e-01 8.09105579e-03 1.44643843e-01
1.22140920e+00 5.85869215e-02 -7.93999135e-01 2.24395730e-02
1.23896763e-01 -5.93509734e-01 -1.71651348e-01 -7.80992866e-01
-1.29812026e+00 8.69683266e-01 2.78286159e-01 1.26890790e+00
1.10484564e+00 -1.53168514e-01 3.11417729e-01 3.91956180e-01
8.17290321e-02 -5.92451811e-01 1.72659501e-01 2.95276850e-01
7.73644507e-01 -1.01530993e+00 -1.27180293e-01 -6.60542011e-01
-4.81804669e-01 1.19518030e+00 4.60132837e-01 -5.64212620e-01
6.38709009e-01 3.92214835e-01 6.76681325e-02 -3.39269340e-01
-4.04785991e-01 2.17392877e-01 3.12378198e-01 9.48277593e-01
-1.11983880e-01 2.06326798e-01 1.20438077e-01 1.01425983e-01
-4.36618954e-01 -7.57919312e-01 9.18177247e-01 8.88356864e-01
-3.13722908e-01 -1.04545522e+00 -5.46457469e-01 4.94396031e-01
-9.23617363e-01 -1.67362154e-01 -1.33681452e+00 8.44107211e-01
-6.58018738e-02 8.05816710e-01 -2.97606379e-01 -8.76437783e-01
2.88120985e-01 -6.15402646e-02 5.01461148e-01 -4.67390090e-01
-9.42920387e-01 -7.46494353e-01 2.39309862e-01 -4.63425457e-01
-1.50614619e-01 -3.23276520e-01 -6.86954796e-01 -5.88974118e-01
-4.36928004e-01 -4.72417101e-02 5.93546689e-01 8.43253255e-01
6.82911649e-02 6.52039707e-01 1.02009964e+00 -3.59580547e-01
-6.97351754e-01 -5.68871319e-01 -5.51510155e-01 7.76485741e-01
4.66525197e-01 -4.75543708e-01 -1.03217816e+00 -6.08270951e-02] | [5.834445953369141, 7.740427494049072] |
ac12f707-1f90-489d-85bc-799626a9acd5 | universal-litmus-patterns-revealing-backdoor | 1906.10842 | null | https://arxiv.org/abs/1906.10842v2 | https://arxiv.org/pdf/1906.10842v2.pdf | Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs | The unprecedented success of deep neural networks in many applications has made these networks a prime target for adversarial exploitation. In this paper, we introduce a benchmark technique for detecting backdoor attacks (aka Trojan attacks) on deep convolutional neural networks (CNNs). We introduce the concept of Universal Litmus Patterns (ULPs), which enable one to reveal backdoor attacks by feeding these universal patterns to the network and analyzing the output (i.e., classifying the network as `clean' or `corrupted'). This detection is fast because it requires only a few forward passes through a CNN. We demonstrate the effectiveness of ULPs for detecting backdoor attacks on thousands of networks with different architectures trained on four benchmark datasets, namely the German Traffic Sign Recognition Benchmark (GTSRB), MNIST, CIFAR10, and Tiny-ImageNet. The codes and train/test models for this paper can be found here https://umbcvision.github.io/Universal-Litmus-Patterns/. | ['Hamed Pirsiavash', 'Soheil Kolouri', 'Heiko Hoffmann', 'Aniruddha Saha'] | 2019-06-26 | universal-litmus-patterns-revealing-backdoor-1 | http://openaccess.thecvf.com/content_CVPR_2020/html/Kolouri_Universal_Litmus_Patterns_Revealing_Backdoor_Attacks_in_CNNs_CVPR_2020_paper.html | http://openaccess.thecvf.com/content_CVPR_2020/papers/Kolouri_Universal_Litmus_Patterns_Revealing_Backdoor_Attacks_in_CNNs_CVPR_2020_paper.pdf | cvpr-2020-6 | ['traffic-sign-recognition'] | ['computer-vision'] | [ 2.40420312e-01 -2.55766571e-01 -1.30649418e-01 -3.53599973e-02
-2.74050891e-01 -1.25453210e+00 6.22267306e-01 -4.27453339e-01
-5.07661045e-01 4.69633192e-01 -4.72488701e-01 -1.23794365e+00
3.30058336e-01 -8.37247610e-01 -1.12737954e+00 -7.69858003e-01
-2.34735250e-01 -5.07683754e-01 5.22763848e-01 -1.67769611e-01
6.86341301e-02 7.96330154e-01 -1.13044679e+00 5.03933132e-01
6.47390261e-02 1.18369401e+00 -3.96640062e-01 1.02680647e+00
3.59846503e-01 9.23474371e-01 -8.37629497e-01 -9.21469152e-01
5.76522887e-01 -2.22615361e-01 -6.03670835e-01 -8.50417316e-01
7.99267113e-01 -4.99362826e-01 -1.09630442e+00 1.60584569e+00
2.76115805e-01 -3.32016796e-01 6.91301450e-02 -1.42976558e+00
-5.21308124e-01 6.30395830e-01 -1.89448103e-01 6.05226398e-01
-1.79714262e-01 4.75478619e-01 8.53211462e-01 -5.71078241e-01
4.61585045e-01 1.14794278e+00 7.11659789e-01 9.30233181e-01
-7.85970867e-01 -1.44866812e+00 -2.23036274e-01 4.11673754e-01
-1.06150532e+00 -6.58712506e-01 5.58851540e-01 -2.12252364e-01
7.38413870e-01 5.36750078e-01 2.20259503e-01 1.88342059e+00
3.81782889e-01 7.09142864e-01 8.23617578e-01 -2.93199360e-01
1.66549668e-01 -2.92552747e-02 4.36064869e-01 9.29764569e-01
6.75052822e-01 8.02232623e-01 -4.29152489e-01 -3.75867218e-01
5.80520928e-01 5.47878891e-02 -3.56328905e-01 1.47755757e-01
-8.59754860e-01 7.89181054e-01 7.28067338e-01 7.58478940e-02
7.88549632e-02 6.81504369e-01 7.74033308e-01 9.10761654e-01
-1.97725788e-01 2.34046608e-01 -4.44926113e-01 1.77671283e-01
-2.98823446e-01 1.86618865e-01 9.01743531e-01 5.80543041e-01
5.75752437e-01 3.18198353e-01 1.07573994e-01 3.13440830e-01
2.40165591e-01 5.39328218e-01 4.57076460e-01 -4.58459198e-01
5.79561353e-01 1.88592836e-01 -3.73817950e-01 -1.10985363e+00
-1.31288469e-01 -3.31421018e-01 -1.01343727e+00 5.25524974e-01
6.35347128e-01 -4.33625162e-01 -1.18626666e+00 1.70165420e+00
7.13257417e-02 5.34942091e-01 2.31269941e-01 7.01206207e-01
8.76200736e-01 4.72351581e-01 -1.31288812e-01 5.30754864e-01
1.49612844e+00 -8.47347319e-01 -2.79575944e-01 -3.63313466e-01
8.86699796e-01 -5.76500654e-01 6.62592351e-01 4.25149858e-01
-3.09275627e-01 -3.50332171e-01 -1.38302541e+00 1.95179313e-01
-9.25063610e-01 4.83699627e-02 5.39125264e-01 1.31888163e+00
-7.09036171e-01 7.07121193e-01 -9.41943467e-01 7.27645382e-02
9.26823914e-01 3.80702436e-01 -6.11078084e-01 -5.96521944e-02
-1.35029948e+00 4.17601079e-01 7.08717108e-01 1.42701775e-01
-1.51344240e+00 -4.38303053e-01 -6.25580966e-01 -1.21402880e-02
2.19868273e-01 -6.90358039e-03 1.18365419e+00 -1.00553572e+00
-1.11703694e+00 9.75026727e-01 5.00881612e-01 -1.08357012e+00
4.79797810e-01 -2.54305840e-01 -6.73484206e-01 1.45791575e-01
-3.63797218e-01 4.72599924e-01 1.04295301e+00 -7.42426991e-01
-4.69137013e-01 -1.79877207e-01 2.25110605e-01 -9.17676091e-01
-5.68274200e-01 5.09978831e-01 -1.68256052e-02 -7.71917522e-01
-1.37908265e-01 -1.09460783e+00 -6.05701320e-02 1.30628213e-01
-9.87294972e-01 7.85478652e-02 1.46465397e+00 -5.44083595e-01
8.46029699e-01 -2.52710009e+00 -5.24187744e-01 4.03907567e-01
3.17327648e-01 1.00749624e+00 -4.01793063e-01 9.02214050e-02
-5.39109945e-01 3.17396343e-01 -1.02566034e-01 -2.68369496e-01
2.66880654e-02 3.64825815e-01 -1.06806147e+00 7.84013987e-01
1.65063798e-01 1.09226322e+00 -7.44901776e-01 1.87048420e-01
5.20189852e-02 3.06977630e-01 -3.01473349e-01 -1.47155166e-01
-1.91615790e-01 1.27715662e-01 -3.56763214e-01 8.62483859e-01
7.49691784e-01 -6.77002314e-03 -4.46100459e-02 2.58134510e-02
1.50154233e-01 3.90872657e-01 -7.68723905e-01 8.85874689e-01
5.94894998e-02 1.31552243e+00 -1.80848077e-01 -7.04500079e-01
9.07025933e-01 4.46082562e-01 -4.20035571e-01 -6.39478624e-01
5.94166517e-01 4.58992183e-01 2.54027128e-01 -1.14176616e-01
1.21854752e-01 4.26486552e-01 -5.00853211e-02 3.87011200e-01
2.37587079e-01 7.87498653e-01 1.20199755e-01 1.84232235e-01
1.58023489e+00 -5.10830760e-01 -5.75380996e-02 -2.59140618e-02
5.25664628e-01 -2.80364186e-01 5.71185648e-01 1.06735992e+00
-3.68728876e-01 1.20190986e-01 8.34711850e-01 -9.29191411e-01
-7.09694207e-01 -1.06737995e+00 9.04288292e-02 8.35673392e-01
-1.82669610e-01 -4.45356429e-01 -6.11486375e-01 -9.68042910e-01
9.70961228e-02 3.23114038e-01 -7.53230810e-01 -5.66969335e-01
-6.31131053e-01 -3.90593261e-01 1.72040689e+00 4.85572517e-01
9.03210700e-01 -1.27739167e+00 -7.06589043e-01 -2.05051154e-01
3.10704708e-01 -1.41007900e+00 -2.04788819e-01 3.30442876e-01
-7.49970496e-01 -1.51917291e+00 -4.22866672e-01 -6.73906922e-01
5.54515719e-01 1.70088455e-01 6.71668172e-01 2.59171277e-01
-6.21976435e-01 -2.21448019e-01 -3.05778325e-01 -5.68625450e-01
-6.90715611e-01 -4.36656289e-02 2.59813428e-01 1.54836506e-01
2.74330944e-01 -6.15246892e-01 -4.07412320e-01 2.84202874e-01
-1.04532111e+00 -3.96064997e-01 5.57797909e-01 5.63568413e-01
1.50069207e-01 -9.29699019e-02 1.46590680e-01 -9.60603297e-01
4.34349239e-01 -3.84612143e-01 -1.07797718e+00 6.88291341e-02
1.09469473e-01 -1.35559767e-01 8.69471252e-01 -6.27097785e-01
-2.37326950e-01 -1.43850043e-01 -3.26645583e-01 -1.07837951e+00
-4.55494732e-01 1.18983999e-01 -9.62810963e-02 -7.86158621e-01
9.83049929e-01 1.82539776e-01 -4.58361715e-01 -3.83661509e-01
1.58840358e-01 3.36170077e-01 1.00405025e+00 -2.40008742e-01
1.35401487e+00 4.75236654e-01 1.94008872e-01 -7.95561731e-01
-3.82149905e-01 -1.24347359e-02 -8.51590186e-02 -1.52943850e-01
5.08909762e-01 -6.03100538e-01 -9.82828557e-01 1.05986261e+00
-1.28261590e+00 -3.83662462e-01 4.30121571e-02 2.41712630e-01
1.65614262e-01 4.36405838e-01 -7.55117416e-01 -6.23220205e-01
-5.20786405e-01 -1.10467935e+00 3.68936270e-01 3.44653875e-01
1.45191848e-01 -8.66753459e-01 -1.55923486e-01 -7.89273679e-02
3.25658858e-01 7.23748207e-01 8.28613281e-01 -1.00837350e+00
-8.52940261e-01 -8.04734886e-01 -3.49518478e-01 8.13876271e-01
9.54640191e-03 8.87396932e-02 -1.43960190e+00 -4.28467631e-01
-2.26176947e-01 -5.40586054e-01 1.32658124e+00 -1.12184279e-01
1.30762005e+00 -7.03128040e-01 -2.33067051e-01 1.21201360e+00
1.37848079e+00 2.02034578e-01 8.57657909e-01 6.30438507e-01
7.75782943e-01 6.45942166e-02 -1.57675266e-01 8.07901323e-02
-4.04479831e-01 1.87446624e-01 1.00737286e+00 5.28057925e-02
9.38424915e-02 -2.44569883e-01 6.98423505e-01 1.45147055e-01
1.06813096e-01 -4.12308693e-01 -9.36811984e-01 3.74238968e-01
-1.48114955e+00 -8.77887011e-01 -3.84809002e-02 1.91394591e+00
4.41010326e-01 4.39517111e-01 -1.27649888e-01 4.13579106e-01
4.76709723e-01 4.61997777e-01 -3.91725451e-01 -6.61539376e-01
-2.89336592e-01 5.48870265e-01 1.05912971e+00 1.57210618e-01
-1.39772069e+00 1.04710615e+00 4.77738714e+00 7.84412086e-01
-1.41059160e+00 1.14168540e-01 7.32755542e-01 7.27110654e-02
2.40539074e-01 -1.84931576e-01 -7.88968265e-01 4.58905309e-01
1.09639418e+00 2.52839535e-01 3.49945217e-01 8.92841637e-01
-4.51557189e-01 5.03144562e-01 -8.95763278e-01 8.49276006e-01
-3.55670363e-01 -1.66960537e+00 4.09949422e-02 2.55949169e-01
5.98662078e-01 6.88293576e-01 4.91258949e-01 1.13472976e-01
5.92613578e-01 -8.97004604e-01 6.82816029e-01 -3.88777889e-02
1.03645551e+00 -8.75089645e-01 6.38169050e-01 1.61600918e-01
-9.46968973e-01 -3.94484967e-01 -5.82431614e-01 3.63707781e-01
-4.26413447e-01 2.81425625e-01 -5.28756380e-01 3.69793296e-01
1.00011301e+00 4.63595003e-01 -5.17053723e-01 9.18159664e-01
-6.51435792e-01 1.00546706e+00 -4.33486968e-01 -2.57083382e-02
6.91856086e-01 3.01391929e-01 7.94160008e-01 1.31345868e+00
1.56516299e-01 -2.92831868e-01 -3.60191733e-01 9.22825396e-01
-6.93489969e-01 -4.83797997e-01 -8.53771329e-01 -4.95275855e-01
3.21652740e-01 1.21277857e+00 -6.77175522e-01 -1.56138269e-02
-4.40205745e-02 8.92349303e-01 4.99419402e-03 3.12154323e-01
-7.92998135e-01 -7.02121198e-01 1.24994802e+00 -4.20181632e-01
4.09826279e-01 -2.24500760e-01 3.11804060e-02 -1.08233809e+00
1.32167652e-01 -1.13256669e+00 5.36412477e-01 -2.18425184e-01
-9.26437497e-01 7.38854587e-01 -4.83150601e-01 -1.15885770e+00
1.33310705e-01 -1.38189065e+00 -1.13980317e+00 6.61002636e-01
-1.55937588e+00 -8.76251519e-01 -8.09260309e-02 9.12542403e-01
-5.73375262e-02 -6.52569234e-01 8.61488104e-01 3.56469035e-01
-8.40809464e-01 1.27778399e+00 1.53672218e-01 1.14816844e+00
3.83359104e-01 -7.07186759e-01 1.30740201e+00 1.31942153e+00
4.75175977e-01 6.83116734e-01 4.79756653e-01 -3.07993531e-01
-1.41556382e+00 -1.26890457e+00 5.86039662e-01 -2.88619041e-01
9.75782037e-01 -5.97259164e-01 -8.56448650e-01 8.53727162e-01
-4.90625836e-02 4.22811598e-01 6.62775576e-01 -3.64825666e-01
-1.26524580e+00 -1.03667527e-01 -1.05196857e+00 7.22511530e-01
8.76393855e-01 -7.44577587e-01 -3.23391594e-02 3.84838969e-01
7.53892243e-01 -5.74415803e-01 -1.51051462e-01 2.64898062e-01
7.49516904e-01 -9.06698227e-01 1.05932808e+00 -1.04168499e+00
2.96533465e-01 -7.32773617e-02 -2.97340989e-01 -8.07591319e-01
4.30300878e-03 -9.99306619e-01 -4.69343215e-01 7.19966769e-01
3.87871861e-01 -1.32859218e+00 9.53004956e-01 -1.07083835e-01
-2.66113877e-02 -5.04418492e-01 -1.25201333e+00 -1.08915854e+00
-1.97301209e-02 -6.44983292e-01 6.03951573e-01 1.03272998e+00
-5.17761409e-01 -4.77256417e-01 -4.73451883e-01 7.07668364e-01
8.25032413e-01 -4.18306977e-01 8.27397943e-01 -8.87929559e-01
-3.69032651e-01 -4.96825993e-01 -8.88400137e-01 -5.86118519e-01
1.50666878e-01 -9.09430325e-01 -3.01927805e-01 -2.47163311e-01
-4.67398226e-01 -1.55281857e-01 -7.57882297e-01 1.00957727e+00
2.89207220e-01 7.71843076e-01 3.33495855e-01 9.99964327e-02
-1.58369362e-01 1.75722055e-02 5.62138915e-01 -3.12366635e-01
2.10933447e-01 2.91404188e-01 -4.99797285e-01 6.92966700e-01
1.28860593e+00 -8.97579491e-01 -4.67116646e-02 -5.20728469e-01
1.48200035e-01 -4.77301747e-01 1.08038867e+00 -1.27080595e+00
3.82087052e-01 2.98383623e-01 2.72071987e-01 -2.79509783e-01
1.88605487e-01 -6.24297500e-01 -2.11656708e-02 1.14649904e+00
-1.64189935e-01 9.82601941e-02 7.82998204e-01 5.14042079e-01
-8.40068683e-02 -1.03790484e-01 8.94727528e-01 2.91818753e-02
-8.26112568e-01 5.65922678e-01 -1.34450793e-01 -2.39153892e-01
7.47045279e-01 -2.03615755e-01 -1.00051868e+00 4.47742641e-03
-3.63798499e-01 -8.86300430e-02 5.00478297e-02 5.98727643e-01
8.73816013e-01 -1.24876654e+00 -5.24514318e-01 5.73104858e-01
1.21450722e-01 -5.18514037e-01 5.34851924e-02 5.12176037e-01
-9.95505810e-01 6.85342371e-01 -4.35506195e-01 -2.26290837e-01
-1.72625411e+00 4.21731889e-01 7.09787667e-01 -8.05459693e-02
-7.40919054e-01 1.27856529e+00 1.51602760e-01 -3.23485315e-01
4.71456200e-01 -3.18419755e-01 2.79212147e-01 -4.48803306e-01
7.77053356e-01 6.46741912e-02 4.51265760e-02 -4.75017190e-01
-4.85421985e-01 -5.25711104e-02 -3.35474074e-01 2.07789972e-01
1.05482423e+00 8.92444909e-01 -1.77169070e-01 -2.42218956e-01
1.57171607e+00 -3.20348054e-01 -9.19209540e-01 -4.51742053e-01
-2.10037902e-02 -4.65399206e-01 -4.14076261e-02 -4.80955362e-01
-1.46961319e+00 1.00100553e+00 7.25939989e-01 2.10213438e-01
9.72368717e-01 -1.92517310e-01 1.00582981e+00 1.12105989e+00
1.63053587e-01 -4.07214880e-01 2.47018989e-02 6.88019216e-01
5.78622758e-01 -7.48370290e-01 -6.13724828e-01 -6.88712373e-02
2.75053643e-02 1.29635978e+00 4.66625661e-01 -4.23645079e-01
7.84344733e-01 3.55946392e-01 3.35154146e-01 -1.26723036e-01
-7.76414990e-01 1.49138168e-01 -9.04990640e-03 3.75814140e-01
-2.92214662e-01 1.01238392e-01 4.30968225e-01 1.88303277e-01
-3.35715234e-01 -1.75433859e-01 4.11741972e-01 9.48928058e-01
-3.33934247e-01 -1.01678264e+00 -4.82386947e-01 2.95213789e-01
-9.92794514e-01 -1.36105835e-01 -7.14946449e-01 6.31080151e-01
5.42829856e-02 6.65083885e-01 -1.98371306e-01 -9.72295821e-01
1.50477543e-01 -9.58924666e-02 1.44306615e-01 -2.09334135e-01
-7.09855258e-01 -6.99295998e-01 2.61005852e-03 -8.80156040e-01
2.09455699e-01 -2.35048667e-01 -7.26702869e-01 -6.69319391e-01
-3.37908924e-01 -1.51914835e-01 7.82362878e-01 7.25654364e-01
9.40563530e-02 4.56967682e-01 7.79615223e-01 -4.62522835e-01
-6.02997839e-01 -6.70760095e-01 -3.05171371e-01 5.75405397e-02
7.79643536e-01 -2.22180948e-01 -6.48124814e-01 -2.26607159e-01] | [5.6721649169921875, 7.773167133331299] |
c9dde8ca-2221-40f2-9c2b-c6f04ba22b44 | a-deep-convolutional-neural-network-for-2 | 2110.15956 | null | https://arxiv.org/abs/2110.15956v1 | https://arxiv.org/pdf/2110.15956v1.pdf | A deep convolutional neural network for classification of Aedes albopictus mosquitoes | Monitoring the spread of disease-carrying mosquitoes is a first and necessary step to control severe diseases such as dengue, chikungunya, Zika or yellow fever. Previous citizen science projects have been able to obtain large image datasets with linked geo-tracking information. As the number of international collaborators grows, the manual annotation by expert entomologists of the large amount of data gathered by these users becomes too time demanding and unscalable, posing a strong need for automated classification of mosquito species from images. We introduce the application of two Deep Convolutional Neural Networks in a comparative study to automate this classification task. We use the transfer learning principle to train two state-of-the-art architectures on the data provided by the Mosquito Alert project, obtaining testing accuracy of 94%. In addition, we applied explainable models based on the Grad-CAM algorithm to visualise the most discriminant regions of the classified images, which coincide with the white band stripes located at the legs, abdomen, and thorax of mosquitoes of the Aedes albopictus species. The model allows us to further analyse the classification errors. Visual Grad-CAM models show that they are linked to poor acquisition conditions and strong image occlusions. | ['David Masip', 'Mohammad Mahdi Dehshibi', 'Gereziher Adhane'] | 2021-10-29 | null | null | null | null | ['explainable-models'] | ['computer-vision'] | [ 3.04452851e-02 -1.28062069e-01 3.46348941e-01 -4.81537253e-01
9.05979145e-03 -6.56774580e-01 7.05289006e-01 2.24051118e-01
-8.12461257e-01 6.32372379e-01 -1.29209206e-01 -4.92823690e-01
-6.90342188e-02 -8.43400240e-01 -4.85508978e-01 -7.40390062e-01
-6.35863245e-01 5.87984979e-01 4.22505802e-03 -2.42474347e-01
-3.88067737e-02 7.00495422e-01 -1.62262154e+00 3.51942718e-01
6.79022849e-01 8.65208745e-01 1.58651441e-01 7.63427734e-01
2.73515396e-02 4.19046320e-02 -7.91176081e-01 -5.09438097e-01
1.68339387e-01 -7.54253641e-02 -3.87215972e-01 -3.10918093e-01
5.90909421e-01 -5.58202982e-01 2.28300601e-01 1.03260756e+00
4.58262324e-01 -5.69981337e-01 7.07560420e-01 -1.17520368e+00
-3.70942980e-01 -7.04478770e-02 -6.43070459e-01 5.68086207e-01
4.52528089e-01 1.80751950e-01 3.12179416e-01 -4.68311995e-01
8.00336957e-01 1.09838259e+00 1.07816613e+00 4.28586602e-01
-1.22331560e+00 -5.24274409e-01 -2.64426619e-01 1.88888580e-01
-1.67974317e+00 -3.75771731e-01 1.74907953e-01 -8.04816306e-01
1.04066658e+00 3.67849499e-01 7.92895317e-01 9.90698636e-01
7.01755807e-02 2.39391819e-01 1.03077590e+00 -2.34056756e-01
2.39934713e-01 2.37324864e-01 -1.93039477e-01 6.71232522e-01
4.57198590e-01 2.27516204e-01 -1.26441970e-01 -2.19949007e-01
6.97259247e-01 5.08165598e-01 -3.95098448e-01 -2.87260890e-01
-8.59886765e-01 9.74343598e-01 7.65131712e-01 5.02918541e-01
-4.29513991e-01 -4.25313473e-01 6.99091554e-02 2.58015692e-01
8.43472719e-01 2.92711705e-01 -6.59686863e-01 8.36367235e-02
-1.28457868e+00 1.58165544e-01 6.18209481e-01 2.02190593e-01
7.69711554e-01 -2.00005919e-01 2.92775333e-01 4.80864108e-01
5.61589897e-01 8.27859461e-01 1.10498257e-01 -3.59217972e-01
2.08196744e-01 1.02346659e+00 1.48157388e-01 -1.08109176e+00
-7.89208293e-01 -8.91596079e-02 -9.60504889e-01 4.56082642e-01
6.19391084e-01 -4.84551638e-01 -1.06704557e+00 1.47218096e+00
4.24264967e-01 -1.45208865e-01 -1.44743189e-01 8.83758545e-01
6.46053016e-01 6.86117411e-01 3.16135168e-01 7.05557540e-02
1.44503736e+00 -1.20981678e-01 -5.14196157e-01 9.21027884e-02
5.61349571e-01 -4.89422917e-01 6.39514446e-01 1.48195148e-01
-5.22746563e-01 -4.52880293e-01 -9.09065127e-01 4.55138773e-01
-1.19456398e+00 2.54711002e-01 5.64013064e-01 7.32263386e-01
-1.24925113e+00 5.50516725e-01 -1.10577738e+00 -8.93053174e-01
8.67214441e-01 4.82640952e-01 -7.53459096e-01 8.02250877e-02
-8.88718009e-01 1.05291986e+00 2.29757413e-01 5.50127149e-01
-6.74760938e-01 -6.30367815e-01 -8.64656925e-01 -1.02448560e-01
-2.72801340e-01 -9.35641080e-02 5.23957193e-01 -9.11136925e-01
-8.99093926e-01 1.16391873e+00 7.01319948e-02 -3.66050780e-01
5.89144528e-01 -1.15092263e-01 -5.85703969e-01 2.31520832e-01
9.19859186e-02 1.01161361e+00 5.53105116e-01 -8.94761503e-01
-8.59669924e-01 -8.44384372e-01 -1.63881108e-01 -3.49248588e-01
-3.40106845e-01 2.00898692e-01 -1.15878426e-01 -5.05476356e-01
-5.49582362e-01 -6.58789337e-01 -3.22154313e-02 2.39368260e-01
1.83776598e-02 -7.26601183e-02 9.34167445e-01 -8.55700195e-01
9.42157567e-01 -2.04450154e+00 1.53515086e-01 5.30640967e-02
1.11255489e-01 8.16506803e-01 -1.65336609e-01 3.93427104e-01
1.58506036e-02 1.74046531e-01 -4.12549108e-01 -6.04355708e-03
-1.51739880e-01 1.39097095e-01 -1.77057073e-01 6.72610283e-01
4.74845648e-01 6.10247970e-01 -8.85882139e-01 -2.56520003e-01
4.62296277e-01 1.28226590e+00 -2.34470248e-01 4.77835804e-01
-1.11841559e-01 4.61524457e-01 -1.81434512e-01 7.20653534e-01
8.21213305e-01 -1.13087751e-01 -1.72033161e-02 -1.05259381e-01
-3.13269883e-01 -1.07987888e-01 -6.42216563e-01 1.31197107e+00
-1.46695286e-01 9.11329031e-01 2.85720229e-01 -7.37959683e-01
7.54805923e-01 3.28482866e-01 2.95522958e-01 -7.07198501e-01
-1.08465990e-02 5.55445328e-02 -2.24971771e-03 -7.03125119e-01
-7.57545233e-03 1.76372826e-01 4.07448888e-01 3.20522875e-01
2.46719673e-01 2.18981147e-01 3.69842708e-01 -6.44463003e-02
6.21466517e-01 3.17109436e-01 8.98744315e-02 -6.08930349e-01
4.65206265e-01 1.73585624e-01 1.64076537e-01 2.21992090e-01
-2.63525993e-01 4.91159290e-01 4.33422238e-01 -1.38961887e+00
-9.48179305e-01 -7.07101166e-01 -4.61837560e-01 1.03004920e+00
-3.92516077e-01 -1.83389693e-01 -1.20388341e+00 -6.06390834e-01
-1.61246598e-01 1.83487236e-01 -1.07666385e+00 2.51260579e-01
-2.41854101e-01 -1.25098348e+00 5.48061490e-01 7.46161193e-02
5.49257934e-01 -1.20865166e+00 -1.40549517e+00 -9.02420133e-02
1.84778929e-01 -6.46512091e-01 3.33453685e-01 2.01749831e-01
-3.98457348e-01 -1.44927824e+00 -9.93329525e-01 -3.95306498e-01
8.33651662e-01 -1.01480363e-02 9.98196959e-01 2.23263785e-01
-7.18852460e-01 -8.59935358e-02 -1.90917045e-01 -3.64200056e-01
-4.27680165e-02 6.19212016e-02 -2.91035138e-02 4.79729958e-02
1.03876448e+00 -1.91441342e-01 -6.38982177e-01 3.36828262e-01
-1.09631920e+00 -1.41616389e-01 2.76461750e-01 3.45282346e-01
1.43280730e-01 -1.09941937e-01 6.53419942e-02 -4.47914243e-01
3.61820638e-01 -5.20183802e-01 -1.10739017e+00 4.85584259e-01
-5.32711409e-02 -8.10444802e-02 3.92169505e-01 -1.08341366e-01
-5.83347023e-01 4.02559817e-01 -1.83400452e-01 2.48076729e-02
-7.78177381e-01 3.16252530e-01 -2.04811920e-03 -1.76662505e-01
6.74795568e-01 -2.26992652e-01 -2.46840529e-02 -4.44385767e-01
2.22298317e-02 9.06777680e-01 4.59010392e-01 1.86989933e-01
5.30115366e-01 6.03228211e-01 5.73538393e-02 -1.28391659e+00
-4.96651769e-01 -3.00448179e-01 -7.57127225e-01 -1.63742840e-01
1.25670731e+00 -7.80340493e-01 -7.68839121e-01 5.59874237e-01
-1.25613475e+00 -3.24295849e-01 3.13982904e-01 2.70066231e-01
1.44495577e-01 1.79357812e-01 -2.25994036e-01 -7.02323437e-01
-4.36721504e-01 -1.25832522e+00 1.30875111e+00 3.56084377e-01
-2.90978879e-01 -1.21579087e+00 4.56318527e-01 -2.45884135e-02
8.34430695e-01 7.58607805e-01 5.39478719e-01 -7.38873422e-01
-5.99811710e-02 -3.82054478e-01 -4.54690695e-01 -1.38866857e-01
2.81196594e-01 3.26411456e-01 -1.11447358e+00 -3.55392873e-01
-2.47060731e-01 -2.40646049e-01 8.05685103e-01 4.52300161e-01
6.38434589e-01 -3.18123043e-01 -4.41242307e-01 8.40685129e-01
1.32893574e+00 1.73462883e-01 5.40013790e-01 3.32767844e-01
3.70522380e-01 1.03785765e+00 1.21868618e-01 3.04566890e-01
1.75611615e-01 9.01761413e-01 5.25938809e-01 -4.57296014e-01
2.56321132e-01 1.53360695e-01 9.90801975e-02 -2.97558516e-01
-4.43368703e-01 -2.78924048e-01 -1.18079114e+00 4.16526765e-01
-1.58526003e+00 -8.24849069e-01 -1.60481632e-01 2.38069725e+00
3.90228331e-01 -3.65639895e-01 1.30266458e-01 -1.45662397e-01
6.08043134e-01 -2.01184407e-01 -5.48080280e-02 -2.28287354e-01
-1.59912765e-01 2.87988454e-01 6.43465400e-01 6.10913634e-01
-1.54230189e+00 8.14333916e-01 6.44544601e+00 2.72129655e-01
-1.36244369e+00 -1.81463704e-01 7.67086089e-01 -1.51948892e-02
3.25176775e-01 -5.60479045e-01 -8.52319896e-01 8.03713560e-01
1.14039910e+00 5.03802717e-01 5.22624016e-01 5.56500435e-01
9.24568847e-02 -3.04050356e-01 -9.29817080e-01 9.06355679e-01
1.00502804e-01 -1.24303615e+00 -2.75247097e-02 3.08391184e-01
4.54970151e-01 3.29751343e-01 -1.14487290e-01 -1.93961561e-01
2.58242607e-01 -1.33098435e+00 7.83800557e-02 5.01344383e-01
8.72098744e-01 -6.09960258e-01 1.06492114e+00 3.46726067e-02
-9.64189947e-01 2.11667880e-01 -4.75536466e-01 -2.88662594e-02
5.21808676e-03 7.93144330e-02 -7.98482180e-01 -5.39980158e-02
1.21008229e+00 5.44869900e-01 -9.63365138e-01 1.09675598e+00
-3.30551714e-01 2.08416671e-01 -7.31683314e-01 1.24541773e-02
3.19496781e-01 -1.40410841e-01 8.37339014e-02 1.33988416e+00
3.58513623e-01 -1.53865099e-01 -3.30385298e-01 7.90999889e-01
3.26541096e-01 -3.73736888e-01 -7.97799528e-01 -4.77437824e-02
-4.04016785e-02 1.45661402e+00 -8.13344002e-01 -3.23372126e-01
-2.02677950e-01 8.87314081e-01 2.26974025e-01 2.78872877e-01
-4.06714410e-01 -4.44797277e-01 6.42851055e-01 2.29489177e-01
4.56771553e-01 3.03969402e-02 3.31446528e-01 -9.92164135e-01
-1.19827740e-01 -5.63825190e-01 4.39641416e-01 -5.45654297e-01
-9.71417785e-01 1.03763843e+00 2.11198524e-01 -8.35050464e-01
-5.74537873e-01 -9.23034191e-01 -5.96789896e-01 9.57244158e-01
-1.54496217e+00 -1.34327805e+00 -5.27058542e-01 4.91817921e-01
-1.10531755e-01 -3.77569497e-01 1.24167073e+00 4.32368785e-01
-4.75063503e-01 1.13591716e-01 5.76774124e-03 2.08121747e-01
3.06765944e-01 -9.56508338e-01 4.63150144e-01 7.01159537e-01
1.86412960e-01 5.59815347e-01 5.81199050e-01 -4.93676305e-01
-1.06016088e+00 -1.03521192e+00 1.08691859e+00 -5.39959311e-01
5.45892417e-01 -5.34235954e-01 -8.24776471e-01 4.75633234e-01
4.08205479e-01 1.05314732e-01 8.29421639e-01 -2.54549801e-01
-2.44336754e-01 -1.27321854e-01 -1.32806063e+00 1.04190357e-01
3.24527353e-01 -3.04498374e-01 -5.35519481e-01 5.31374574e-01
-3.95980664e-02 1.79106727e-01 -4.85516757e-01 2.27622837e-01
5.68453193e-01 -1.08221912e+00 8.82456183e-01 -6.08386636e-01
2.46921897e-01 -4.31985199e-01 4.18398641e-02 -1.22036564e+00
7.52692372e-02 -3.35822701e-01 3.97341222e-01 1.02685523e+00
3.07744324e-01 -4.36082304e-01 6.69314146e-01 2.76429236e-01
3.29571068e-01 -5.79623021e-02 -1.06901729e+00 -3.96733671e-01
-2.48423636e-01 1.49289414e-01 5.82538128e-01 8.16526830e-01
-1.91529512e-01 1.47428498e-01 -3.42289031e-01 3.35508734e-01
5.67761242e-01 -2.05939189e-01 6.87577188e-01 -1.48848772e+00
1.28404841e-01 -3.91046226e-01 -7.07482994e-01 -1.51833981e-01
-2.82270908e-01 -3.41656387e-01 -3.04610342e-01 -1.42273879e+00
-1.32316560e-01 -2.04781711e-01 -8.89807940e-02 8.63221228e-01
8.12543854e-02 8.08479488e-01 -3.35854813e-02 5.24408817e-02
-4.29858088e-01 -2.12836824e-02 2.94721216e-01 -1.85852870e-01
-2.89982647e-01 -9.93722528e-02 -8.27361196e-02 7.81643927e-01
7.75300860e-01 -3.01572800e-01 9.38525870e-02 -9.18940187e-01
3.95158708e-01 -4.01116103e-01 6.56351447e-01 -1.06963968e+00
-4.76825424e-03 1.97226301e-01 8.91696215e-01 -5.66670299e-01
2.90255189e-01 -1.42121160e+00 5.33662617e-01 9.61911201e-01
6.48708791e-02 1.06518976e-01 6.10303402e-01 2.78347749e-02
-1.11850537e-01 8.72242078e-02 7.09196985e-01 -1.91049337e-01
-5.47380805e-01 2.92307526e-01 -4.50021952e-01 -4.45045531e-01
1.08078289e+00 -8.04994330e-02 -4.72389787e-01 3.63547914e-02
-4.37475711e-01 1.43454760e-01 5.40470183e-01 3.62856120e-01
3.89128506e-01 -8.38638544e-01 -8.35890830e-01 6.86107695e-01
2.21419111e-01 -1.63808227e-01 5.19615375e-02 6.52978241e-01
-1.18288577e+00 6.86616957e-01 -9.30602133e-01 -7.82990992e-01
-1.40483308e+00 5.80611110e-01 3.46399784e-01 -6.39791833e-04
-1.40511468e-01 7.41037965e-01 8.30969587e-02 -3.37503940e-01
2.02607393e-01 -2.26463288e-01 -6.36850715e-01 3.30711842e-01
1.10184169e+00 2.06340879e-01 1.42306224e-01 -8.81612420e-01
-7.00478733e-01 7.36005306e-01 1.24501728e-01 1.50838524e-01
1.80882215e+00 3.57752234e-01 -3.22651714e-01 -2.87837893e-01
1.12220085e+00 -4.41582620e-01 -1.37621164e+00 4.86697942e-01
3.34126912e-02 -4.59639758e-01 1.14579029e-01 -9.35309768e-01
-1.15678430e+00 1.41159964e+00 1.36537719e+00 5.58498085e-01
9.24823463e-01 -1.72322452e-01 1.08007804e-01 2.61243850e-01
2.42033541e-01 -6.51394010e-01 -7.33914316e-01 2.93367077e-02
7.71592021e-01 -1.56270409e+00 -2.44831331e-02 1.04414873e-01
-2.41954044e-01 1.20337403e+00 2.05028221e-01 1.79390609e-01
5.05909801e-01 2.09479138e-01 3.17759216e-01 -5.08199871e-01
-3.17053884e-01 -2.65046269e-01 2.77658731e-01 1.15378785e+00
5.03862917e-01 1.76014930e-01 -1.02322593e-01 -7.18179643e-02
9.36872233e-03 4.85335067e-02 -6.24890765e-03 8.04675341e-01
-3.75371158e-01 -8.89522016e-01 -5.49196482e-01 1.82024255e-01
-5.91584325e-01 -8.51285830e-02 -7.77481616e-01 8.37673247e-01
4.48244542e-01 9.12302375e-01 5.73401630e-01 -1.92474931e-01
3.00708245e-02 -1.50886282e-01 3.46276075e-01 -1.96227953e-01
-8.01539063e-01 -2.58520432e-02 -2.27275386e-01 -3.52764368e-01
-8.45686734e-01 -3.38760376e-01 -5.07471621e-01 -3.27310741e-01
2.59202942e-02 1.66450307e-01 1.13191497e+00 6.95005476e-01
3.55411947e-01 -1.36313155e-01 2.65020519e-01 -1.02609026e+00
1.62117109e-01 -1.17570317e+00 -2.84151018e-01 4.81408477e-01
5.84826708e-01 -4.66807485e-01 -2.87489772e-01 2.68964887e-01] | [9.118902206420898, -1.1104358434677124] |
0eb9f318-0636-48fe-99be-f6301447ae22 | learning-a-depth-covariance-function | 2303.12157 | null | https://arxiv.org/abs/2303.12157v1 | https://arxiv.org/pdf/2303.12157v1.pdf | Learning a Depth Covariance Function | We propose learning a depth covariance function with applications to geometric vision tasks. Given RGB images as input, the covariance function can be flexibly used to define priors over depth functions, predictive distributions given observations, and methods for active point selection. We leverage these techniques for a selection of downstream tasks: depth completion, bundle adjustment, and monocular dense visual odometry. | ['Andrew J. Davison', 'Eric Dexheimer'] | 2023-03-21 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Dexheimer_Learning_a_Depth_Covariance_Function_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Dexheimer_Learning_a_Depth_Covariance_Function_CVPR_2023_paper.pdf | cvpr-2023-1 | ['depth-completion', 'visual-odometry'] | ['computer-vision', 'robots'] | [ 1.52859524e-01 4.23393816e-01 -4.15306389e-01 -7.70674527e-01
-9.24258649e-01 -8.19061875e-01 8.02604258e-01 1.37239501e-01
-7.00959444e-01 4.51206714e-01 3.72773468e-01 -2.31707215e-01
4.19899113e-02 -6.32134676e-01 -5.99100173e-01 -5.20642281e-01
1.58519268e-01 8.18329573e-01 2.16543868e-01 1.81251988e-01
6.89897716e-01 9.96882856e-01 -1.36652517e+00 -2.84727961e-01
6.31064117e-01 8.17592025e-01 3.37380975e-01 8.61438870e-01
-1.06275775e-01 4.32427824e-01 -1.89195469e-01 -9.89425033e-02
4.40720528e-01 2.40217596e-01 -6.88922763e-01 3.80904496e-01
4.42768723e-01 -4.82450902e-01 -4.90179777e-01 8.22271585e-01
3.17862749e-01 4.62536782e-01 8.84005547e-01 -1.10579252e+00
-2.39995033e-01 -3.45411897e-02 -5.15501976e-01 -1.02519989e-05
5.95854759e-01 4.22889680e-01 1.07589543e+00 -9.68149126e-01
8.43670905e-01 1.38436091e+00 5.33386350e-01 4.78675753e-01
-1.53744161e+00 -1.70491040e-01 1.64938375e-01 -1.27729461e-01
-1.08042407e+00 -5.85760832e-01 6.48496330e-01 -8.36942554e-01
1.05886793e+00 -8.32690895e-02 8.19958448e-01 9.32315946e-01
6.17182143e-02 7.67322361e-01 6.19735718e-01 -2.76786447e-01
5.50770044e-01 -2.95071006e-01 -3.64420339e-02 7.72637963e-01
2.08874885e-02 3.00677061e-01 -7.47284591e-01 -4.05641884e-01
1.11845160e+00 1.22652158e-01 -4.04354990e-01 -8.91214132e-01
-1.10491073e+00 1.04444945e+00 5.94826043e-01 -9.00664270e-01
-1.10208616e-01 5.12427032e-01 -3.09684463e-02 1.36931971e-01
4.31452096e-01 6.05351746e-01 -5.05783558e-01 -1.07180618e-01
-3.69364470e-01 3.44368756e-01 6.62102938e-01 1.13014090e+00
1.45137560e+00 -3.09246719e-01 1.54377431e-01 5.44741631e-01
9.78748143e-01 8.42664480e-01 2.54866406e-02 -1.66944158e+00
5.80650449e-01 5.69116414e-01 1.37593627e-01 -3.44742179e-01
-4.05524641e-01 4.32392269e-01 -3.11640710e-01 9.13326144e-01
2.53161997e-01 -1.01118237e-02 -1.45745027e+00 1.29546046e+00
4.77710247e-01 -9.35295001e-02 -1.58088952e-02 8.47612739e-01
7.22381949e-01 2.36033306e-01 -3.11150670e-01 2.18198448e-01
6.71556950e-01 -4.69481707e-01 -1.07228875e-01 -7.42366433e-01
3.28722417e-01 -7.25960791e-01 8.97951722e-01 4.40076739e-01
-1.00913441e+00 -6.03152886e-02 -1.07268333e+00 -7.26031303e-01
4.72105183e-02 -2.31508926e-01 8.65377665e-01 1.80725574e-01
-1.31195462e+00 6.12897277e-01 -1.36529362e+00 -2.28425592e-01
4.94318783e-01 6.84512973e-01 -3.50222290e-01 -7.48848692e-02
-3.66571635e-01 6.62793517e-01 6.81891665e-02 -1.22626200e-02
-1.08357668e+00 -5.64734817e-01 -1.31451201e+00 -3.69091362e-01
-1.06721610e-01 -1.29013407e+00 1.31622088e+00 -2.22803369e-01
-1.67360508e+00 1.21833122e+00 -2.72844791e-01 -3.31403732e-01
4.62202638e-01 -3.89676601e-01 6.98871434e-01 2.90102094e-01
1.28324285e-01 9.73689020e-01 1.00107205e+00 -1.07270527e+00
-4.23208505e-01 -8.10803890e-01 1.80627987e-01 7.03066528e-01
5.69598138e-01 -6.21028900e-01 -7.47404993e-01 -1.81312323e-01
1.00942791e+00 -9.99907017e-01 -6.99148834e-01 7.41280735e-01
-6.49964571e-01 1.88063875e-01 5.09266198e-01 -1.39788449e-01
1.19555138e-01 -2.10336018e+00 6.84790611e-01 4.17360067e-01
4.74436790e-01 -7.27386534e-01 7.14203566e-02 -3.22687924e-02
5.09588540e-01 -2.09265888e-01 -3.32197577e-01 -1.08206785e+00
9.79538709e-02 5.49184978e-01 -4.35009271e-01 7.54225373e-01
2.72139162e-01 8.36625755e-01 -9.07860518e-01 -3.01998824e-01
6.54501915e-01 6.58836007e-01 -6.44048870e-01 5.87097287e-01
-3.99661303e-01 8.62564206e-01 -2.79217243e-01 6.72698140e-01
4.79748756e-01 -1.78361684e-01 -3.58147860e-01 -1.00177363e-03
-7.64672309e-02 5.81005216e-01 -1.14752853e+00 2.26740026e+00
-3.69439691e-01 8.69192719e-01 2.01940745e-01 -2.70844698e-01
1.01547050e+00 -1.95819572e-01 6.26061797e-01 1.39609640e-02
1.08919321e-02 -8.45021382e-02 -6.04711175e-01 -4.45660770e-01
6.51149809e-01 6.46813065e-02 2.02819824e-01 3.74785513e-01
1.45773068e-01 -1.12316525e+00 -4.33228880e-01 3.11791748e-01
1.15437150e+00 5.09429634e-01 3.34744066e-01 -6.61057560e-03
-2.87882406e-02 8.46174434e-02 2.74287671e-01 5.25163054e-01
-3.93449999e-02 1.15351140e+00 3.16914648e-01 -1.68087110e-01
-1.13320851e+00 -1.70575953e+00 -2.52288401e-01 6.24431312e-01
3.68349731e-01 -1.78407058e-01 1.99585892e-02 -3.67136657e-01
4.97274250e-01 3.50356810e-02 -5.65054536e-01 2.44969539e-02
-3.62502426e-01 -1.63516432e-01 3.08524281e-01 6.69291735e-01
2.62537226e-02 -7.83632100e-01 -7.42079020e-01 -1.81144968e-01
2.82535642e-01 -9.90204871e-01 -2.84590244e-01 5.83805144e-01
-1.32451344e+00 -1.35649669e+00 -4.95040983e-01 -4.53323007e-01
7.12509692e-01 1.36282936e-01 1.20219588e+00 -2.13124380e-01
-3.40955794e-01 9.22856927e-01 5.57178669e-02 -3.67773443e-01
3.28551442e-03 4.22971770e-02 -2.14914218e-01 -5.70016205e-01
1.46006823e-01 -7.09829569e-01 -7.84949005e-01 -7.53051490e-02
-6.48631513e-01 -1.03863940e-01 2.83994645e-01 4.49699134e-01
9.36226428e-01 -1.00200200e+00 -4.32581782e-01 -9.00796950e-01
1.99553505e-01 -2.56777883e-01 -9.65992272e-01 -1.81502253e-01
-3.57892931e-01 4.90642965e-01 -1.38602614e-01 -1.26284808e-01
-8.38857532e-01 7.02035308e-01 -2.89698660e-01 -6.62639201e-01
-1.38002962e-01 2.01112241e-01 -2.99912155e-01 -2.85530746e-01
8.22860539e-01 -2.03647763e-01 1.98025882e-01 -3.15292627e-01
7.50602961e-01 2.03938872e-01 6.87193573e-01 -4.88355994e-01
8.29826474e-01 1.08983219e+00 2.86479086e-01 -7.82174408e-01
-7.02557921e-01 -7.58303642e-01 -1.20317841e+00 3.19503665e-01
9.30905521e-01 -1.18703735e+00 -8.75990391e-01 3.93642992e-01
-1.35869753e+00 -7.55677819e-01 -4.20901209e-01 5.18656373e-01
-1.04359126e+00 3.73727530e-01 -4.88158882e-01 -6.58165336e-01
-2.07020342e-01 -1.38456309e+00 1.68812990e+00 1.23726048e-01
-2.02662051e-01 -1.43582726e+00 2.50613242e-01 -6.42518923e-02
-2.48033315e-01 2.83561647e-01 6.33679032e-01 1.36996627e-01
-1.20812249e+00 2.53453702e-01 1.45512205e-02 -1.03610838e-02
5.18710986e-02 2.78927058e-01 -1.11155784e+00 -2.28574723e-01
-2.56602224e-02 -4.76645291e-01 1.07960248e+00 6.78757131e-01
1.03605032e+00 8.28422084e-02 -4.54229146e-01 1.68746734e+00
1.45973575e+00 -3.26634608e-02 6.81553364e-01 4.59585041e-01
1.01354730e+00 4.44288909e-01 4.47533727e-01 6.27508521e-01
6.21331632e-01 5.52445889e-01 7.25610375e-01 -1.02066070e-01
1.90689832e-01 -2.26207986e-01 7.64417797e-02 1.75647408e-01
1.65099844e-01 1.98363930e-01 -1.17523026e+00 2.29041234e-01
-1.68357205e+00 -5.61426222e-01 1.16995849e-01 2.18869233e+00
5.43403029e-01 2.71606177e-01 -1.74523860e-01 -1.69400394e-01
2.12252080e-01 2.59122550e-01 -1.16321230e+00 4.90859188e-02
-2.10911229e-01 2.80646145e-01 9.03350413e-01 1.14299262e+00
-1.12693012e+00 8.49147379e-01 7.65234709e+00 -1.85812280e-01
-9.85543728e-01 -8.94494802e-02 1.89817145e-01 -2.08841786e-02
-8.04189324e-01 4.72522020e-01 -9.25333798e-01 -1.31958634e-01
2.24742651e-01 -1.99122410e-02 4.34538662e-01 8.06667924e-01
1.29484430e-01 -3.49335015e-01 -1.41450262e+00 1.49391568e+00
-1.71839893e-01 -1.31151843e+00 -1.38730139e-01 2.37500474e-01
6.58055365e-01 7.21887231e-01 5.79607598e-02 -3.22435886e-01
8.80093157e-01 -8.56815755e-01 5.00472069e-01 5.45994580e-01
7.10438311e-01 -4.57714438e-01 -1.09367175e-02 6.75544366e-02
-9.48941410e-01 4.58410047e-02 -5.68933010e-01 -1.23221710e-01
4.04762626e-01 5.25710106e-01 -1.09009290e+00 -1.70876086e-02
4.96203750e-01 1.15975761e+00 -3.32023472e-01 1.17939281e+00
-8.00388157e-01 1.00820087e-01 -6.55371785e-01 3.22762251e-01
3.66519280e-02 -4.33284253e-01 6.45224988e-01 7.23069191e-01
1.32609941e-02 8.46217200e-02 1.55267343e-01 9.25962090e-01
7.55627379e-02 -3.34398210e-01 -9.69640911e-01 4.87456650e-01
6.86515808e-01 8.69788289e-01 -6.72581971e-01 -2.23712325e-02
-2.06433818e-01 1.12228966e+00 5.16335845e-01 7.07874894e-01
-2.97898829e-01 -2.15819463e-01 1.44839537e+00 -2.49222685e-02
1.17132306e-01 -9.31627035e-01 -9.05663252e-01 -1.48848546e+00
-2.00171679e-01 -4.91199493e-02 2.18421623e-01 -1.09578073e+00
-1.10304511e+00 2.20578894e-01 2.17774287e-01 -1.03163111e+00
-4.76220161e-01 -1.00291896e+00 -6.04261816e-01 9.93377268e-01
-1.50012517e+00 -6.61839724e-01 -6.21317148e-01 8.15710127e-01
4.69257414e-01 2.56053023e-02 4.81918246e-01 -2.65442014e-01
-5.74733876e-02 -3.03189978e-02 9.19849724e-02 1.29094481e-01
4.59126949e-01 -1.62933099e+00 9.87338066e-01 6.91933811e-01
3.24377716e-01 5.38951993e-01 6.49238288e-01 -5.57947755e-01
-1.62365854e+00 -9.17841017e-01 2.87193228e-02 -8.41969371e-01
4.88161445e-01 -4.62746173e-01 -5.11370242e-01 1.04387319e+00
-3.27264369e-01 8.35062861e-02 4.05771196e-01 1.94256365e-01
-3.61276120e-01 1.57047600e-01 -1.17953289e+00 4.33379352e-01
1.22607076e+00 -8.52409065e-01 -3.75537634e-01 3.63803953e-01
8.10877442e-01 -1.03184044e+00 -7.59702444e-01 2.05682606e-01
3.68835419e-01 -9.60185885e-01 1.37854803e+00 -4.15353864e-01
1.79535523e-01 -1.19277000e-01 -4.08207059e-01 -1.30354369e+00
-8.76937956e-02 -7.27431059e-01 -2.38612354e-01 7.03318000e-01
3.38544250e-01 -5.21972656e-01 1.17878556e+00 9.00586009e-01
-4.10668284e-01 -6.38683677e-01 -9.08008039e-01 -1.56385779e-01
-6.91910088e-02 -6.25120938e-01 3.93328905e-01 4.90323097e-01
-3.04995000e-01 3.96502435e-01 1.50252983e-01 3.56612056e-01
9.38475311e-01 8.24774951e-02 1.15362823e+00 -1.32025254e+00
-4.87175971e-01 -4.04525667e-01 -7.42371202e-01 -1.90629208e+00
2.10792691e-01 -7.70878673e-01 4.04231280e-01 -1.72903872e+00
-1.82530209e-01 -6.41243160e-01 4.86589909e-01 4.39388067e-01
-8.51592496e-02 1.04710013e-01 5.13392314e-02 5.85908055e-01
-2.17280984e-01 7.18257546e-01 1.05337214e+00 -6.30884916e-02
-5.59082866e-01 1.33816078e-01 -1.54956743e-01 8.07801425e-01
4.78306115e-01 -1.84771970e-01 -6.64895535e-01 -9.59985673e-01
3.69487762e-01 1.44157514e-01 4.22487885e-01 -7.17481375e-01
3.43044758e-01 -5.85777044e-01 3.75508547e-01 -6.96260810e-01
8.52307141e-01 -4.79144633e-01 -7.85338655e-02 1.47531658e-01
-2.43927315e-01 2.43382171e-01 -6.28790632e-02 5.75956762e-01
3.50309834e-02 -1.20321184e-01 7.76054263e-01 -3.12978685e-01
-1.06136072e+00 7.55437255e-01 -1.32615060e-01 2.64731109e-01
6.77501500e-01 -5.38343132e-01 -2.05590099e-01 -3.39077950e-01
-1.04950774e+00 3.10475886e-01 1.07612872e+00 2.69174278e-01
1.27111256e+00 -1.22979677e+00 -3.70531499e-01 5.55047750e-01
2.24214971e-01 9.62090969e-01 -4.11776841e-01 4.64205205e-01
-9.78276432e-01 3.81134003e-02 -2.92019825e-03 -1.36569953e+00
-9.43923771e-01 1.51575968e-01 5.04340708e-01 4.20410782e-01
-8.35126638e-01 1.08415473e+00 3.72334182e-01 -6.31130397e-01
4.24573839e-01 -6.18551075e-01 1.20783165e-01 -2.73747504e-01
2.12383062e-01 1.86931968e-01 -7.04232678e-02 -4.16469961e-01
-2.36603037e-01 9.15660977e-01 3.33700806e-01 -6.79623604e-01
1.31349301e+00 -6.25707686e-01 6.57148808e-02 7.92455494e-01
1.36040998e+00 -1.34096935e-01 -2.02498245e+00 -2.31141686e-01
5.00346012e-02 -8.58884215e-01 6.80554565e-03 -1.45053700e-01
-8.28288436e-01 1.03004038e+00 3.92857760e-01 -4.15935606e-01
6.89766765e-01 2.88914979e-01 1.23841338e-01 5.52444577e-01
6.94529057e-01 -4.63120431e-01 3.34466547e-01 8.32128763e-01
7.06025124e-01 -1.45046496e+00 2.32567817e-01 -5.03480673e-01
-4.73050505e-01 1.30305398e+00 4.42792624e-01 -3.72077554e-01
1.02426124e+00 5.36279857e-01 3.94237518e-01 -3.53708923e-01
-6.55256510e-01 -4.25201595e-01 3.09106380e-01 9.49602902e-01
1.04451619e-01 -2.48192817e-01 5.42186081e-01 -5.89164436e-01
-3.92469704e-01 -4.18445855e-01 5.92453897e-01 9.59192216e-01
-7.09506750e-01 -9.96295512e-01 -3.90320927e-01 3.11430395e-01
1.05840705e-01 -5.88790793e-03 -4.09121990e-01 4.45311457e-01
-1.95089966e-01 5.73877752e-01 4.88197535e-01 -2.32560486e-01
2.40478724e-01 -2.40153238e-01 9.12705898e-01 -1.20069158e+00
-4.32792306e-02 -7.52689764e-02 -2.74128139e-01 -7.97818065e-01
-3.96231055e-01 -9.26441610e-01 -1.44781613e+00 -4.78759706e-02
-1.60877667e-02 -2.54991442e-01 7.92097449e-01 9.53988135e-01
2.15376541e-01 -2.54313380e-01 4.37795341e-01 -1.29020429e+00
-3.42951536e-01 -7.09017932e-01 -4.23040986e-01 5.25795698e-01
7.82880485e-01 -7.93294430e-01 -5.93958795e-01 8.64446163e-02] | [8.498863220214844, -2.6918468475341797] |
47ac896b-0ef5-4a1b-8f85-8eccb16f137f | learning-sparse-nonlinear-dynamics-via-mixed | 2206.00176 | null | https://arxiv.org/abs/2206.00176v1 | https://arxiv.org/pdf/2206.00176v1.pdf | Learning Sparse Nonlinear Dynamics via Mixed-Integer Optimization | Discovering governing equations of complex dynamical systems directly from data is a central problem in scientific machine learning. In recent years, the sparse identification of nonlinear dynamics (SINDy) framework, powered by heuristic sparse regression methods, has become a dominant tool for learning parsimonious models. We propose an exact formulation of the SINDy problem using mixed-integer optimization (MIO) to solve the sparsity constrained regression problem to provable optimality in seconds. On a large number of canonical ordinary and partial differential equations, we illustrate the dramatic improvement of our approach in accurate model discovery while being more sample efficient, robust to noise, and flexible in accommodating physical constraints. | ['Wes Gurnee', 'Dimitris Bertsimas'] | 2022-06-01 | null | null | null | null | ['model-discovery'] | ['miscellaneous'] | [ 4.34941612e-02 -4.01336163e-01 -2.57623881e-01 1.66719660e-01
-6.48400784e-01 -6.53024018e-01 4.94189262e-01 -2.34918967e-01
-1.93645563e-02 1.20057762e+00 -2.03570560e-01 -2.45363891e-01
-7.26849139e-01 3.80465612e-02 -5.16794205e-01 -8.95695806e-01
-3.18124563e-01 8.55912209e-01 -3.13611180e-01 -7.32563362e-02
3.67219180e-01 1.01368356e+00 -1.14487660e+00 -5.33560336e-01
9.18761849e-01 7.67930210e-01 1.53531477e-01 6.85327232e-01
2.35196114e-01 6.90364897e-01 2.88320743e-02 2.96045542e-01
2.95737058e-01 -3.41841370e-01 -5.52621663e-01 1.51656985e-01
3.03240657e-01 2.29412749e-01 -6.34053290e-01 8.58680069e-01
3.84553224e-01 3.05385619e-01 9.41144645e-01 -1.20021927e+00
-2.96826988e-01 2.01733008e-01 -4.68077958e-01 5.07939219e-01
3.66236940e-02 1.59449369e-01 8.55778217e-01 -1.03438056e+00
7.07643270e-01 1.31841588e+00 6.40152693e-01 3.70724976e-01
-1.73223889e+00 -4.71704602e-01 1.30581021e-01 1.45127669e-01
-1.60360813e+00 -7.43123114e-01 8.92352104e-01 -7.13051319e-01
8.38473976e-01 4.78164583e-01 5.26742697e-01 8.94046128e-01
2.36529961e-01 4.27286506e-01 1.07278478e+00 -1.40261233e-01
5.09446144e-01 3.52072716e-03 1.41980961e-01 8.27656746e-01
6.62335515e-01 4.34259057e-01 -4.13058043e-01 -7.16482759e-01
1.12995338e+00 -1.85004994e-02 -2.67980218e-01 -5.65738976e-01
-1.08988726e+00 9.79421258e-01 -1.66530669e-01 -3.05870865e-02
-4.16602045e-01 1.99951634e-01 5.37461303e-02 2.51202404e-01
4.40221071e-01 1.03160250e+00 -6.73925519e-01 -3.51885349e-01
-1.08060455e+00 6.79116666e-01 1.27417922e+00 8.52574348e-01
4.47603196e-01 7.31177747e-01 6.30815983e-01 6.81113780e-01
2.07148537e-01 7.00664043e-01 2.35288143e-01 -1.33811867e+00
-8.23994875e-02 3.36155385e-01 2.33636335e-01 -1.03735638e+00
-4.21482861e-01 -5.26400328e-01 -1.30927753e+00 1.44983321e-01
2.14590743e-01 -4.45272356e-01 -6.03799164e-01 1.44882238e+00
5.68511605e-01 5.76192498e-01 -8.43779296e-02 9.15237546e-01
5.69599330e-01 9.85555649e-01 -2.80437440e-01 -8.91118288e-01
7.85451055e-01 -4.97671455e-01 -6.64080203e-01 5.44636548e-02
4.39568698e-01 -5.53238273e-01 2.82356650e-01 4.81784344e-01
-1.12115753e+00 -1.87629700e-01 -6.09890759e-01 1.50442168e-01
1.24633878e-01 -3.29801179e-02 9.05786037e-01 -4.48787846e-02
-8.15233052e-01 9.38117504e-01 -1.21020269e+00 -6.04889765e-02
1.32836014e-01 7.01904774e-01 -4.18017715e-01 6.35000244e-02
-6.93134785e-01 8.65324318e-01 -6.27814385e-04 1.43782541e-01
-1.10682499e+00 -1.20407271e+00 -7.62243986e-01 7.41849467e-02
6.93283796e-01 -7.52002299e-01 8.43404293e-01 -3.73626620e-01
-1.76244414e+00 5.14632106e-01 -6.57871664e-01 -4.51400995e-01
2.91158497e-01 -6.67103082e-02 -1.91074580e-01 5.87560050e-02
-2.56617755e-01 5.37229255e-02 1.08504128e+00 -1.09271300e+00
2.96840370e-02 -5.67450710e-02 -4.57806498e-01 -1.77034214e-01
1.48940921e-01 7.77403563e-02 -1.44773141e-01 -7.71126091e-01
3.33549023e-01 -1.33434832e+00 -8.53150845e-01 2.15015598e-02
-3.56989861e-01 -1.92208856e-01 9.38914835e-01 -7.07147479e-01
1.22159564e+00 -1.66657615e+00 9.92917836e-01 3.30221325e-01
4.99138623e-01 1.38488516e-01 1.02719322e-01 5.96525848e-01
-2.28992671e-01 -4.09359820e-02 -5.47518253e-01 -2.73343772e-01
-2.77717948e-01 4.22255486e-01 -5.19173205e-01 7.47136474e-01
2.36398831e-01 6.02929831e-01 -6.55237556e-01 -4.18024153e-01
1.60773933e-01 3.26432973e-01 -6.40828490e-01 3.30887049e-01
-1.41676083e-01 9.13049102e-01 -6.91205919e-01 7.33525336e-01
3.63806516e-01 -6.24506056e-01 1.35831773e-01 -4.84727845e-02
-4.20080960e-01 -1.93207070e-01 -1.75456822e+00 1.28685486e+00
-3.11906070e-01 5.64772904e-01 6.29878998e-01 -1.55749965e+00
8.62359345e-01 4.14448410e-01 1.08088994e+00 -3.95150222e-02
-2.76034456e-02 3.45669866e-01 -2.70831101e-02 -5.37795305e-01
2.01908454e-01 -1.16468064e-01 -8.77095759e-02 2.91760147e-01
1.15286790e-01 -5.12692451e-01 2.89697319e-01 1.56165779e-01
9.27324235e-01 -3.02047655e-02 6.18002832e-01 -8.11780632e-01
5.91516197e-01 3.27432573e-01 8.62688839e-01 5.56599140e-01
1.13025688e-01 2.71979183e-01 4.55387920e-01 -6.47382915e-01
-1.34128952e+00 -5.93995869e-01 -3.24637920e-01 2.52718866e-01
-7.51431137e-02 -3.19955498e-01 -2.14419216e-01 1.53778985e-01
4.42046076e-01 7.60988072e-02 -4.24270988e-01 -3.62982713e-02
-9.74258959e-01 -7.38595486e-01 1.23395965e-01 9.08477902e-02
-1.52636930e-01 -5.18260837e-01 -2.37498209e-01 3.89308304e-01
3.24178696e-01 -1.26763058e+00 -4.62512791e-01 2.61753112e-01
-1.15262890e+00 -1.10881889e+00 -7.37631261e-01 -6.24211907e-01
7.23197699e-01 1.56153634e-01 9.38281119e-01 -1.06919847e-01
-9.93930638e-01 3.02187324e-01 1.61213145e-01 -6.08922495e-03
-3.28449309e-01 -1.58211472e-03 7.51522720e-01 -1.80218592e-01
-3.89215738e-01 -9.10370409e-01 -8.75701532e-02 1.94278196e-01
-6.13256216e-01 1.06716581e-01 2.80994564e-01 9.47612226e-01
9.30656135e-01 9.24401879e-02 3.26491624e-01 -8.12553644e-01
5.07187486e-01 -7.83345461e-01 -1.16022515e+00 -5.62505855e-04
-7.79110849e-01 3.94823074e-01 1.03099382e+00 -7.68327832e-01
-5.90109110e-01 4.11198735e-01 2.24962980e-01 -9.84374642e-01
6.33663982e-02 8.16606939e-01 2.05769494e-01 -6.60861433e-01
4.42856938e-01 5.86157560e-01 2.00771824e-01 -7.65929222e-01
1.17642820e-01 1.50126070e-01 5.26183546e-01 -8.23809683e-01
1.14628541e+00 3.43505919e-01 8.55031848e-01 -1.36931014e+00
-5.81522465e-01 -3.96416068e-01 -7.00941503e-01 3.98841873e-02
3.72999579e-01 -8.99360001e-01 -9.41020429e-01 1.97886720e-01
-8.05582821e-01 -1.22320309e-01 -1.10389575e-01 5.96823573e-01
-4.87851977e-01 5.20089746e-01 -4.56006348e-01 -1.03975439e+00
-2.60835499e-01 -9.69846606e-01 9.48554337e-01 9.19567049e-02
-3.92234117e-01 -1.20467162e+00 4.81402278e-01 -1.46316916e-01
4.90091234e-01 6.27122462e-01 9.02370214e-01 -2.68992960e-01
-4.84312087e-01 -2.34160587e-01 1.30281240e-01 -5.29855974e-02
1.34521797e-01 4.81651753e-01 -3.55506927e-01 -5.26949167e-01
1.61730126e-01 -9.79020223e-02 6.41812384e-01 7.95025170e-01
1.06543922e+00 -6.77085161e-01 -5.35739601e-01 9.99373913e-01
1.53564644e+00 4.99555208e-02 -1.80062249e-01 -3.57213140e-01
9.53245521e-01 2.64311224e-01 9.24193412e-02 8.77883673e-01
5.13226800e-02 6.86035633e-01 6.33082390e-02 3.83162946e-02
3.11668962e-01 1.74404070e-01 2.23310053e-01 1.18291116e+00
-1.23986237e-01 2.11356983e-01 -9.04625952e-01 3.01669359e-01
-1.89350438e+00 -1.07029343e+00 -1.18949465e-01 1.97638357e+00
9.36389029e-01 -2.10966632e-01 2.58969814e-01 -1.00645863e-01
5.30639529e-01 -3.37707996e-02 -1.07220650e+00 -3.05081666e-01
-3.38908494e-01 1.46250740e-01 5.22570610e-01 8.34043801e-01
-9.20341492e-01 8.30443621e-01 7.83790159e+00 5.54402292e-01
-1.25783420e+00 -3.54458928e-01 4.09865797e-01 -3.02115798e-01
-1.40463904e-01 1.94395468e-01 -1.02667284e+00 4.46646482e-01
1.08269691e+00 -6.59036517e-01 9.78935063e-01 7.64561832e-01
8.80490363e-01 1.69654831e-01 -9.54763889e-01 1.29038560e+00
-2.90192813e-01 -1.70880711e+00 -1.14713356e-01 2.04694197e-01
1.11506724e+00 -6.17429130e-02 -4.28339057e-02 -5.14387563e-02
3.96187454e-01 -1.20525265e+00 2.84295946e-01 8.15050304e-01
7.97031522e-01 -4.25681144e-01 1.33320555e-01 4.77590561e-01
-1.17798734e+00 4.17485274e-02 -5.29600799e-01 -3.60386223e-01
3.33566993e-01 9.26368237e-01 -2.78259814e-01 1.94100454e-01
3.80542755e-01 1.20891142e+00 9.31867361e-02 1.13165700e+00
2.88616329e-01 9.14481580e-01 -6.99988842e-01 1.08977906e-01
8.22045580e-02 -6.95293486e-01 1.13161397e+00 7.16535926e-01
3.19740593e-01 5.60236931e-01 4.29967523e-01 9.78734136e-01
2.05637842e-01 -1.57692716e-01 -6.99464023e-01 -4.93537605e-01
5.76150715e-01 1.14616871e+00 -4.19068724e-01 -1.32579535e-01
-1.24182887e-02 4.55145270e-01 2.59762764e-01 5.00946224e-01
-5.59985042e-01 1.84052646e-01 1.00694013e+00 -1.92224622e-01
3.96797866e-01 -8.83134127e-01 -1.80012450e-01 -1.46139431e+00
-2.30727285e-01 -1.00676239e+00 2.65062630e-01 -3.61336797e-01
-1.31429243e+00 3.60327452e-01 1.73984766e-01 -1.15021455e+00
-4.04439390e-01 -5.91747582e-01 -5.89012682e-01 9.57865953e-01
-1.29845190e+00 -5.12548983e-01 1.01532349e-02 5.51853538e-01
6.06217384e-01 -2.91418880e-01 9.64869499e-01 2.89345365e-02
-1.15659583e+00 7.76169449e-02 7.62426019e-01 -5.63078284e-01
2.12192610e-01 -1.20823109e+00 5.39810136e-02 7.54899561e-01
-7.09340125e-02 7.22148061e-01 1.26876414e+00 -7.37620592e-01
-2.25492144e+00 -7.77535677e-01 6.79243624e-01 -2.24334285e-01
9.30381656e-01 -1.63033441e-01 -1.03414881e+00 4.08223540e-01
-4.05532092e-01 1.74107149e-01 5.55125594e-01 -5.42350039e-02
-2.34056618e-02 1.63168460e-01 -8.60638738e-01 4.43262517e-01
8.56361270e-01 -3.09489429e-01 -3.77366304e-01 6.29523218e-01
4.62808698e-01 -6.13101959e-01 -1.22670698e+00 3.06610227e-01
3.52143317e-01 3.66439372e-02 1.09731042e+00 -1.09148705e+00
4.20528442e-01 -2.72772878e-01 7.25106522e-02 -1.12417459e+00
-5.97869754e-01 -1.46732271e+00 -9.82522488e-01 5.55371344e-01
2.02007651e-01 -5.35254121e-01 7.57624567e-01 8.23037326e-01
-9.74359885e-02 -9.78844941e-01 -1.15615499e+00 -9.71030831e-01
6.69627264e-02 -3.38620357e-02 6.83738291e-02 1.20305908e+00
-1.14956535e-02 1.80941805e-01 -1.02937376e+00 3.53843659e-01
8.81510258e-01 3.83908868e-01 7.41079986e-01 -1.63933396e+00
-5.19862831e-01 -4.25995171e-01 -1.47963315e-01 -1.01651752e+00
4.75334823e-01 -7.89534688e-01 -1.62800744e-01 -9.60802615e-01
1.29700616e-01 -3.99981767e-01 -3.11729219e-03 8.15294385e-02
-2.10829914e-01 -7.16552883e-02 7.33009502e-02 8.01641762e-01
-3.95492762e-01 7.06991196e-01 1.07428312e+00 -6.59519108e-03
-3.23206156e-01 1.59063116e-01 -6.05849564e-01 6.10813498e-01
4.31069762e-01 -7.58801877e-01 -9.54483449e-02 -1.26154870e-01
1.70267910e-01 4.78637666e-01 2.36935720e-01 -8.29303324e-01
3.46112996e-01 -6.53162837e-01 8.58950838e-02 -2.91494370e-01
4.03570324e-01 -8.62800539e-01 4.67589736e-01 7.44605899e-01
-2.14604661e-01 3.80839169e-01 2.80362844e-01 6.39951408e-01
-1.67413175e-01 2.44877134e-02 8.67524445e-01 -1.17438227e-01
-5.56862414e-01 6.76945031e-01 -4.92111266e-01 1.68361545e-01
8.17006946e-01 3.19114886e-02 6.26477823e-02 -3.40846390e-01
-8.90477300e-01 5.22848725e-01 2.60388196e-01 -7.53608868e-02
5.20464718e-01 -9.95883167e-01 -9.02639508e-01 9.81260464e-02
-4.33075935e-01 -3.52318846e-02 2.14945525e-01 1.03652191e+00
-5.10562837e-01 8.37928474e-01 2.90969145e-02 -5.45815289e-01
-1.15155375e+00 5.29114485e-01 4.03166860e-01 -3.79247338e-01
-7.43001103e-01 5.96909821e-01 -2.75132775e-01 -1.45533159e-01
-4.56217937e-02 -5.19848801e-02 -1.20296404e-02 -4.18002307e-01
3.81724894e-01 7.79452384e-01 -3.99346203e-01 -6.14657104e-01
-3.27960521e-01 6.75676882e-01 1.35421008e-01 2.28113174e-01
1.73672211e+00 -2.83385869e-02 -3.57642502e-01 5.00289917e-01
1.12568235e+00 -1.74377456e-01 -1.50424850e+00 -4.82590914e-01
-4.26924676e-02 -1.42001808e-01 1.70431301e-01 -3.36253971e-01
-9.12072122e-01 4.04507607e-01 1.16394134e-02 2.54507214e-01
6.91270590e-01 -1.07364699e-01 6.37755752e-01 8.33091676e-01
1.58626348e-01 -7.00213373e-01 -3.03751171e-01 7.36066520e-01
9.96954560e-01 -1.22786474e+00 4.60842609e-01 -5.52430212e-01
-2.54704595e-01 1.29995561e+00 3.02083284e-01 -6.33161068e-01
1.00611222e+00 2.98143566e-01 -3.67008299e-01 -1.77395135e-01
-1.02916694e+00 3.10139596e-01 5.22806883e-01 1.99083656e-01
1.33213192e-01 -1.20970696e-01 -2.17369139e-01 3.99001092e-01
-3.38938609e-02 -1.45939663e-01 5.39168954e-01 8.36091638e-01
-3.35669905e-01 -8.72893512e-01 -4.02978539e-01 6.57727659e-01
-2.34383479e-01 -1.21697329e-01 -3.02303612e-01 6.89458549e-01
-5.66166997e-01 5.90681672e-01 -3.78158092e-01 1.19710550e-01
1.47636672e-02 -1.52997822e-01 2.44090647e-01 -5.50328672e-01
-8.82664770e-02 1.53767467e-01 -2.06078649e-01 -5.39196908e-01
-3.27921212e-01 -9.88225579e-01 -1.01778913e+00 -5.18784642e-01
-3.06044281e-01 4.98680651e-01 5.14867246e-01 1.31345165e+00
6.56247914e-01 2.33753055e-01 9.57012832e-01 -1.11250985e+00
-8.95806909e-01 -6.92621231e-01 -7.60864019e-01 -1.77127100e-03
7.09325075e-01 -9.09589231e-01 -6.79143250e-01 4.19772565e-02] | [6.544191360473633, 3.5302634239196777] |
ec359be5-26c4-4762-bc7c-1c19c939b769 | analysis-and-utilization-of-entrainment-on | 2212.03398 | null | https://arxiv.org/abs/2212.03398v1 | https://arxiv.org/pdf/2212.03398v1.pdf | Analysis and Utilization of Entrainment on Acoustic and Emotion Features in User-agent Dialogue | Entrainment is the phenomenon by which an interlocutor adapts their speaking style to align with their partner in conversations. It has been found in different dimensions as acoustic, prosodic, lexical or syntactic. In this work, we explore and utilize the entrainment phenomenon to improve spoken dialogue systems for voice assistants. We first examine the existence of the entrainment phenomenon in human-to-human dialogues in respect to acoustic feature and then extend the analysis to emotion features. The analysis results show strong evidence of entrainment in terms of both acoustic and emotion features. Based on this findings, we implement two entrainment policies and assess if the integration of entrainment principle into a Text-to-Speech (TTS) system improves the synthesis performance and the user experience. It is found that the integration of the entrainment principle into a TTS system brings performance improvement when considering acoustic features, while no obvious improvement is observed when considering emotion features. | ['Trevor Wood', 'Agis Oikonomou Filandras', 'Jonas Rohnke', 'Marek Strelec', 'Antonio Bonafonte', 'Constantinos Papayiannis', 'David McHardy', 'Nikos Kargas', 'Daxin Tan'] | 2022-12-07 | null | null | null | null | ['spoken-dialogue-systems'] | ['speech'] | [-3.40320349e-01 3.99097055e-01 1.89242765e-01 -4.80948150e-01
-3.77337784e-01 -6.18811071e-01 7.60166764e-01 -1.11769296e-01
-1.31474286e-01 7.19879925e-01 7.37393260e-01 -2.39652246e-01
-1.57534033e-02 -2.30453417e-01 -2.06191242e-01 -5.93649626e-01
1.18445560e-01 3.00697803e-01 -4.98263352e-02 -6.21281087e-01
2.01600820e-01 5.72656035e-01 -1.63946426e+00 1.81286871e-01
7.29108512e-01 5.65444469e-01 2.26287350e-01 1.06105340e+00
-3.13226789e-01 5.20084977e-01 -1.13175702e+00 1.54950663e-01
-2.89684031e-02 -6.48773015e-01 -9.18063641e-01 -8.70819762e-02
-1.60321385e-01 7.81527609e-02 5.49661480e-02 7.53923833e-01
9.37011778e-01 4.67247874e-01 5.38814962e-01 -1.19288874e+00
-2.05956444e-01 6.72964036e-01 3.12868925e-03 3.17472368e-01
9.16620851e-01 6.95728883e-02 8.74503136e-01 -6.14395082e-01
5.13520479e-01 1.45533288e+00 4.90406901e-01 5.22326469e-01
-1.17650509e+00 -3.78799438e-01 -2.89615870e-01 -4.02213261e-03
-1.08092201e+00 -8.04092884e-01 7.43295312e-01 -3.31361890e-01
1.19324541e+00 7.16813982e-01 5.33355772e-01 8.54276955e-01
2.02380627e-01 6.56858385e-01 1.11337185e+00 -8.67751479e-01
1.24143116e-01 9.00616109e-01 2.05437973e-01 1.54648602e-01
-6.14863753e-01 -5.22771031e-02 -7.23137498e-01 -2.39692330e-01
1.84715018e-01 -8.40010524e-01 -4.32432681e-01 2.60865033e-01
-6.40150726e-01 7.96955407e-01 -7.19066411e-02 9.70648706e-01
-4.13078159e-01 -5.16350329e-01 6.42350614e-01 5.72069764e-01
3.82534385e-01 9.98729467e-01 -3.30920458e-01 -9.98475552e-01
-7.43157685e-01 6.86371624e-02 1.31735039e+00 7.94665217e-01
6.19747579e-01 1.63950160e-01 -3.23301286e-01 1.40202451e+00
2.81619608e-01 4.48590815e-01 9.35356140e-01 -9.02636886e-01
3.99015322e-02 4.00093466e-01 -5.86776882e-02 -8.65465045e-01
-7.40569830e-01 1.78716555e-01 -2.21544147e-01 -8.41339380e-02
2.56844431e-01 -5.64009607e-01 -2.52034783e-01 1.71818018e+00
4.38407809e-01 -4.54536915e-01 4.24875915e-01 8.17554533e-01
9.89778936e-01 9.95307505e-01 -2.10214749e-01 -6.31239891e-01
1.39851749e+00 -9.37610388e-01 -1.40166581e+00 1.31385252e-01
6.47444904e-01 -1.15624344e+00 1.38616824e+00 3.68210256e-01
-9.08865809e-01 -6.77947581e-01 -8.77046883e-01 1.04270034e-01
-4.03453350e-01 6.15253933e-02 1.06319927e-01 1.20778155e+00
-1.09146440e+00 4.28094059e-01 -2.66969264e-01 -6.75190508e-01
-8.88127089e-01 4.20453668e-01 -3.33711922e-01 8.27351034e-01
-1.24197686e+00 1.01886332e+00 1.05848894e-01 -3.94699275e-02
7.93291181e-02 -3.03553313e-01 -6.72702789e-01 -3.45247164e-02
-2.57125292e-02 -1.26127779e-01 1.59472704e+00 -9.31249022e-01
-2.44800854e+00 5.50445020e-01 -3.50069195e-01 -1.86290190e-01
2.91060477e-01 -2.15743586e-01 -6.66258514e-01 1.31221293e-02
-2.00419679e-01 2.20489830e-01 6.46573603e-01 -1.30664098e+00
-5.13203442e-01 -1.31957874e-01 -3.46083790e-01 3.94384503e-01
-2.83458829e-01 3.30521286e-01 2.67747715e-02 -3.23712349e-01
-2.05556870e-01 -1.01397717e+00 3.47125918e-01 -8.35826576e-01
-5.57218969e-01 -3.82060081e-01 1.07302833e+00 -6.76497340e-01
1.58780408e+00 -2.29612947e+00 8.92246142e-02 3.36869270e-01
-1.60082519e-01 4.38556373e-01 1.56482235e-01 7.01357961e-01
7.74118491e-03 2.93029677e-02 1.10237442e-01 -4.31425512e-01
3.16988468e-01 4.15245354e-01 -9.10265595e-02 1.63224235e-01
-2.10066974e-01 4.41559315e-01 -5.19811988e-01 -3.11124682e-01
2.57642150e-01 3.44482005e-01 -5.99017501e-01 7.39882946e-01
1.98711038e-01 5.67688406e-01 -1.46789402e-01 2.58646578e-01
4.19731945e-01 6.21260405e-01 1.62834525e-01 -1.02085814e-01
-6.29791200e-01 6.36487544e-01 -7.96969116e-01 9.94812191e-01
-7.09346175e-01 8.49940717e-01 3.74511242e-01 -6.10449731e-01
1.26075971e+00 8.79788995e-01 4.04674292e-01 -5.75230062e-01
1.73484609e-01 5.12242436e-01 5.92372060e-01 -9.47590292e-01
1.04667330e+00 -3.66856396e-01 -9.99563560e-02 3.42824697e-01
1.38293788e-01 -4.80310857e-01 5.19087864e-03 -1.63993642e-01
6.59280062e-01 -3.49474818e-01 4.39200342e-01 -5.52999079e-01
7.99646974e-01 -4.90926623e-01 1.85612947e-01 5.03526866e-01
-4.06404763e-01 2.90334255e-01 5.05297363e-01 2.25592300e-01
-8.40672314e-01 -6.20969951e-01 -2.63316482e-01 1.41814423e+00
-2.53153443e-01 -4.17032272e-01 -1.04118848e+00 -2.04766527e-01
-2.04277113e-01 8.97697926e-01 -2.76381254e-01 -1.38527021e-01
-3.81223977e-01 -5.08841515e-01 7.43116021e-01 2.20528051e-01
3.21635395e-01 -1.43986309e+00 -5.91319740e-01 3.57691109e-01
-3.18748593e-01 -9.88706946e-01 -6.57674074e-01 4.01995361e-01
-4.22254652e-01 -3.41620088e-01 -5.89101672e-01 -5.33188760e-01
-4.51854914e-02 -1.07157454e-01 6.53310359e-01 -1.51522085e-01
-9.62600335e-02 6.88203394e-01 -7.95446754e-01 -4.94201750e-01
-1.09093642e+00 2.70112336e-01 3.70445251e-01 -5.70367947e-02
3.82946253e-01 -5.73339403e-01 -2.40919173e-01 4.59344119e-01
-6.56693518e-01 -5.30810773e-01 1.33742228e-01 6.34320021e-01
-2.10993379e-01 -1.74917772e-01 9.25593078e-01 -6.13817573e-01
1.21271908e+00 -1.42786846e-01 9.68393907e-02 -3.98310311e-02
-5.78293145e-01 1.19192779e-01 5.23789525e-01 -3.65432978e-01
-1.25520110e+00 -2.48021185e-01 -6.45627916e-01 7.68190920e-02
-4.76933241e-01 4.02557284e-01 -4.23337728e-01 6.94624335e-03
6.02329195e-01 5.85042015e-02 2.94453859e-01 -3.45470399e-01
1.63432479e-01 1.43460643e+00 3.57433677e-01 -6.13159597e-01
3.21691722e-01 -8.85055885e-02 -5.93020380e-01 -1.65266502e+00
-2.68109411e-01 -8.15664649e-01 -5.09461462e-01 -4.99411136e-01
8.82927537e-01 -2.62811959e-01 -1.00442827e+00 3.53545636e-01
-1.18161452e+00 -3.53973001e-01 -2.42119893e-01 6.43064201e-01
-7.07146943e-01 4.00197327e-01 -4.75359201e-01 -1.29834068e+00
-3.11360598e-01 -1.30205679e+00 8.87658119e-01 5.91825783e-01
-9.22210872e-01 -1.06721079e+00 2.20214918e-01 4.62830216e-01
4.73682702e-01 -3.51121783e-01 7.65395641e-01 -1.06150258e+00
4.52695340e-01 6.91836923e-02 3.19215864e-01 3.75815570e-01
5.20639062e-01 1.38184175e-01 -1.30360627e+00 -3.74830142e-02
3.50526690e-01 -9.61698443e-02 1.25793949e-01 3.28137457e-01
2.96776742e-01 -5.38755655e-01 2.27711424e-01 -3.71603221e-02
6.04208708e-01 8.56269896e-01 6.77638292e-01 2.39930928e-01
2.75318027e-01 1.15205371e+00 6.36307061e-01 6.65502608e-01
7.11321086e-02 1.01659811e+00 -8.20132047e-02 -1.01763763e-01
1.48559824e-01 4.37709354e-02 6.42213881e-01 1.22247541e+00
4.09799209e-03 -3.33622336e-01 -7.69684911e-01 3.72210413e-01
-1.60113418e+00 -8.03467095e-01 -1.73176244e-01 2.08150434e+00
9.66568708e-01 -7.05960318e-02 4.80283469e-01 2.23421097e-01
7.05080152e-01 1.61452800e-01 1.30243063e-01 -1.57785690e+00
-4.85838614e-02 -1.58013701e-01 1.07063472e-01 1.05707431e+00
-5.96666694e-01 8.30267787e-01 6.43670082e+00 6.29497826e-01
-1.39931881e+00 -1.49400637e-01 4.17733848e-01 1.74000889e-01
-1.39073700e-01 -2.72149056e-01 -6.55020058e-01 2.80729294e-01
1.03310549e+00 -4.26686257e-01 4.14211184e-01 6.58863246e-01
6.63593829e-01 -3.31248850e-01 -1.12623680e+00 7.08957255e-01
1.36930704e-01 -4.86294419e-01 -3.51809680e-01 1.55660242e-01
1.58201337e-01 -3.83386075e-01 -4.32748049e-02 3.53545368e-01
-3.34906042e-01 -9.66949522e-01 5.56997657e-01 4.06412631e-01
9.61845964e-02 -7.50581086e-01 8.83007884e-01 2.89687097e-01
-1.04504097e+00 1.70574114e-01 3.12223062e-02 -6.79844022e-02
4.27320987e-01 4.74988110e-02 -1.57120812e+00 5.10469377e-01
4.11822885e-01 -8.08052942e-02 -1.36174768e-01 7.91344881e-01
1.49364173e-01 8.34655166e-01 -3.45663339e-01 -2.45520070e-01
2.01946065e-01 -2.63614655e-01 1.06032193e+00 1.56052232e+00
3.85467768e-01 6.41374514e-02 -3.06509566e-02 6.63067162e-01
5.06876945e-01 6.33772194e-01 -5.97639143e-01 -2.20545515e-01
5.55161238e-01 1.01462698e+00 -3.37004691e-01 -2.13453561e-01
-5.37546501e-02 9.46695268e-01 -4.12283748e-01 3.05594802e-01
-5.31260252e-01 -6.12234533e-01 5.13370931e-01 -3.54796350e-02
-4.55244668e-02 -5.17470064e-03 -2.22592413e-01 -4.60794181e-01
-1.69072021e-02 -1.13233137e+00 -2.09218904e-01 -6.37398124e-01
-9.37112510e-01 8.56553197e-01 -9.02632065e-03 -8.67412984e-01
-8.60930920e-01 -4.42956120e-01 -7.98110962e-01 9.82087493e-01
-9.35520589e-01 -6.67839348e-01 -9.17877257e-03 2.61920452e-01
5.64185381e-01 -3.67671579e-01 9.32025969e-01 2.04895467e-01
-3.97050858e-01 7.83207178e-01 9.62724723e-03 -2.24188432e-01
1.01843154e+00 -1.47652912e+00 -1.88858971e-01 3.53073120e-01
-8.34422633e-02 6.42638743e-01 1.40412664e+00 -1.14588968e-01
-1.02600074e+00 -3.69991302e-01 1.20364237e+00 -9.29151773e-02
5.79869092e-01 -2.98534989e-01 -1.04398239e+00 2.27628335e-01
7.91260839e-01 -7.14385509e-01 9.70124483e-01 4.26082909e-01
6.83817938e-02 1.66225955e-02 -1.11581039e+00 5.07157564e-01
3.16506743e-01 -7.70136237e-01 -8.41904461e-01 -7.39601701e-02
7.99357355e-01 -3.49642515e-01 -1.17673707e+00 2.25305751e-01
6.48356616e-01 -1.23398626e+00 4.27623212e-01 -2.24835888e-01
6.88705519e-02 1.11911669e-01 -2.83261359e-01 -1.60128069e+00
1.41806258e-02 -1.40720415e+00 3.67491663e-01 1.67590809e+00
8.01619768e-01 -1.00888383e+00 1.13553837e-01 8.16204786e-01
-4.81061578e-01 -2.34364122e-01 -1.08822560e+00 -8.39894950e-01
1.59587815e-01 -8.43309462e-02 5.24117708e-01 6.90781415e-01
1.05201113e+00 6.67232752e-01 -5.29110432e-01 -3.67913134e-02
-3.66525650e-01 -1.56155884e-01 1.01373589e+00 -9.51472819e-01
-4.63987231e-01 -5.10419846e-01 -2.46349260e-01 -9.46852386e-01
1.28989115e-01 -3.27054620e-01 7.12599277e-01 -1.00344622e+00
-3.29244107e-01 -1.70675904e-01 1.51383549e-01 7.73089528e-02
-1.61242887e-01 -3.21569592e-01 4.99972373e-01 -6.25322610e-02
-2.18962561e-02 7.56986320e-01 9.21776056e-01 2.04501048e-01
-9.62040365e-01 2.43584931e-01 -3.84224564e-01 5.62545300e-01
9.21489418e-01 -8.29243138e-02 -2.65219599e-01 3.20482016e-01
-2.91595340e-01 3.50104779e-01 -2.01844275e-01 -8.75182927e-01
1.04884520e-01 9.85117555e-02 -4.62125808e-01 -1.43873990e-01
6.13293409e-01 -6.16992474e-01 -1.45016536e-01 2.02594802e-01
-3.27528268e-01 4.69972603e-02 5.82884371e-01 1.36208057e-01
-4.89870191e-01 -4.09613788e-01 7.01442182e-01 3.13763082e-01
-3.27348053e-01 -7.07360506e-01 -1.24311590e+00 -2.28408217e-01
6.06261075e-01 -3.51306379e-01 -1.23156860e-01 -8.10718834e-01
-7.44844019e-01 -7.52776638e-02 1.39982626e-01 5.86970210e-01
9.56022516e-02 -1.05455780e+00 -3.57441306e-01 2.28872374e-01
-1.00718617e-01 -6.73777997e-01 2.01302826e-01 1.13577437e+00
-2.76908100e-01 8.30795467e-01 -1.70766562e-01 -6.56244099e-01
-1.90388989e+00 7.36409798e-02 5.03529787e-01 -7.84173906e-02
-2.24410191e-01 6.16835952e-01 1.18091017e-01 -8.22987437e-01
4.31385428e-01 -2.53130972e-01 -4.66058463e-01 3.30751270e-01
1.46589935e-01 5.14328957e-01 5.37234582e-02 -9.26602483e-01
-3.41170341e-01 2.58074701e-01 8.10296014e-02 -7.41740704e-01
8.31148565e-01 -6.47034407e-01 -1.33720800e-01 1.03356767e+00
1.22240400e+00 5.21460414e-01 -5.41804552e-01 1.74710020e-01
1.33391708e-01 -2.59945065e-01 -1.03546798e-01 -6.97743952e-01
-3.47330213e-01 6.70188308e-01 5.07278264e-01 9.26821470e-01
8.99327636e-01 -9.51084215e-03 7.15384483e-01 4.59529787e-01
-6.96190745e-02 -1.52876949e+00 2.60576028e-02 9.07631755e-01
1.14512897e+00 -1.00652766e+00 -5.24518132e-01 -3.70293677e-01
-1.11870611e+00 1.01859903e+00 5.37090540e-01 3.81427735e-01
8.15552294e-01 3.43795478e-01 4.13008153e-01 7.91969150e-03
-6.41234934e-01 -1.03049219e-01 2.88451344e-01 6.51137650e-01
1.00239468e+00 3.34986717e-01 -6.96491182e-01 6.00822389e-01
-9.01416540e-01 -3.86933118e-01 6.97565913e-01 6.19162321e-01
-6.30534708e-01 -1.26787460e+00 -6.17215276e-01 -1.04849609e-02
-2.96523452e-01 1.00848511e-01 -9.10020947e-01 6.68890059e-01
-3.58014889e-02 1.57711041e+00 5.54082058e-02 -5.30593157e-01
6.93958998e-01 4.81360406e-01 -5.84332331e-04 -6.48035705e-01
-1.12141764e+00 5.29366970e-01 7.22090125e-01 -1.82169110e-01
-4.69431430e-01 -6.76936567e-01 -1.37960911e+00 -2.82552063e-01
-4.95091647e-01 7.88142860e-01 7.64273047e-01 1.11428642e+00
2.79777557e-01 6.36614323e-01 9.53698695e-01 -6.20149314e-01
-4.20785099e-01 -1.48361778e+00 -9.06368852e-01 3.61581258e-02
4.15943503e-01 -3.59162271e-01 -5.67348421e-01 -1.31784350e-01] | [14.569896697998047, 6.642016410827637] |
486d83ba-df29-4dab-a4b8-9375a7397584 | deep-reinforcement-learning-for-multi-agent-2 | 2208.01769 | null | https://arxiv.org/abs/2208.01769v1 | https://arxiv.org/pdf/2208.01769v1.pdf | Deep Reinforcement Learning for Multi-Agent Interaction | The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning. Towards this goal, the Autonomous Agents Research Group develops novel machine learning algorithms for autonomous systems control, with a specific focus on deep reinforcement learning and multi-agent reinforcement learning. Research problems include scalable learning of coordinated agent policies and inter-agent communication; reasoning about the behaviours, goals, and composition of other agents from limited observations; and sample-efficient learning based on intrinsic motivation, curriculum learning, causal inference, and representation learning. This article provides a broad overview of the ongoing research portfolio of the group and discusses open problems for future directions. | ['Stefano V. Albrecht', 'Cheng Wang', 'Giuseppe Vecchio', 'Massimiliano Tamborski', 'Lukas Schäfer', 'Arrasy Rahman', 'Georgios Papoudakis', 'Trevor McInroe', 'Balint Gyevnar', 'Shangmin Guo', 'Samuel Garcin', 'Elliot Fosong', 'Mhairi Dunion', 'Filippos Christianos', 'Ignacio Carlucho', 'Cillian Brewitt', 'Ibrahim H. Ahmed'] | 2022-08-02 | null | null | null | null | ['machine-learning', 'machine-learning'] | ['methodology', 'miscellaneous'] | [-1.87475264e-01 3.18643332e-01 -5.02241552e-01 -2.70126790e-01
-1.29460424e-01 -2.06365824e-01 1.07033157e+00 2.66110063e-01
-3.34392190e-01 1.01033974e+00 1.57670453e-01 -1.29182532e-01
-3.83345217e-01 -8.03752303e-01 -4.69053298e-01 -8.34821165e-01
-5.70289493e-01 9.27639067e-01 6.53962493e-02 -1.53574511e-01
1.54019415e-01 3.72856975e-01 -1.37341070e+00 -5.87917678e-02
4.37103540e-01 5.62438011e-01 8.86646286e-03 1.02775753e+00
2.45175824e-01 1.53907049e+00 -7.19889998e-01 5.00959516e-01
-3.40566486e-02 -5.92243254e-01 -5.10859728e-01 1.81931034e-01
-1.47967458e-01 -4.86952305e-01 -4.55865383e-01 7.53152788e-01
2.45674193e-01 3.82046402e-01 7.96772361e-01 -1.59233510e+00
-2.62083501e-01 8.17565560e-01 -1.10792994e-01 1.54665664e-01
9.43924338e-02 5.46566606e-01 9.04283404e-01 1.04009230e-02
2.11620778e-01 1.61059797e+00 2.78136525e-02 7.41073489e-01
-1.07700694e+00 -7.47244954e-01 6.39402628e-01 5.42395532e-01
-5.77808678e-01 -1.93139344e-01 3.32563102e-01 -4.05465305e-01
1.20431411e+00 -2.51735002e-01 7.96717048e-01 1.27328646e+00
6.31358624e-01 8.36677194e-01 1.03486097e+00 -3.82065356e-01
7.32953072e-01 -2.04916894e-01 -7.76968077e-02 8.67735803e-01
4.79888096e-02 1.08279967e+00 -3.41614544e-01 -3.68232548e-01
8.05784047e-01 -1.98740974e-01 4.63728666e-01 -5.68731904e-01
-1.09358883e+00 1.36311078e+00 1.49083242e-01 -9.89534780e-02
-6.63511634e-01 6.87082112e-01 3.80283177e-01 6.46007597e-01
-2.48963118e-01 6.65671527e-01 -8.55790734e-01 -3.74376103e-02
6.10075966e-02 7.47326910e-01 1.00681555e+00 6.42587841e-01
7.26471066e-01 7.51245797e-01 8.09588358e-02 5.18798709e-01
7.65066266e-01 6.79176807e-01 5.76806724e-01 -1.41064405e+00
-1.61355004e-01 5.02483666e-01 9.94077027e-02 -3.84223729e-01
-8.28689337e-01 -3.90596054e-02 -3.93592179e-01 9.55893457e-01
9.18895304e-02 -8.92001748e-01 -4.83992100e-01 1.56513441e+00
4.61761922e-01 3.48274946e-01 6.87562704e-01 4.72244471e-01
4.66727227e-01 7.79081583e-01 4.32938278e-01 -4.48716968e-01
8.72117102e-01 -9.80641484e-01 -6.59684598e-01 -5.60331047e-01
4.43702549e-01 -1.97470725e-01 9.27860960e-02 2.66222119e-01
-8.80415559e-01 -3.11455905e-01 -9.45888877e-01 5.84001005e-01
-1.55701205e-01 -4.23650920e-01 9.38766479e-01 1.47962138e-01
-8.54152918e-01 3.16639125e-01 -1.10777664e+00 -1.81006968e-01
2.97054231e-01 6.05886281e-01 2.36927554e-01 2.41705552e-01
-1.03300643e+00 1.26392245e+00 5.49950778e-01 -7.38422573e-01
-1.82999182e+00 -5.15518069e-01 -9.12335336e-01 -1.05843984e-01
6.66589797e-01 -7.32398093e-01 1.87150109e+00 -1.04368162e+00
-2.13874125e+00 6.97912881e-03 2.98598528e-01 -8.93680990e-01
2.52629668e-02 -1.80247898e-05 -4.24143165e-01 -5.63649088e-02
-2.58172005e-02 5.31635225e-01 7.83908248e-01 -1.11535788e+00
-1.40791726e+00 -3.51978540e-01 1.16940625e-01 6.11292362e-01
-9.52974483e-02 3.07605416e-03 3.11063915e-01 -1.71931535e-01
-8.73272002e-01 -9.61212158e-01 -7.39489019e-01 -4.73692954e-01
2.13755935e-01 -9.11040127e-01 1.06655288e+00 2.81103272e-02
4.40285772e-01 -1.66392124e+00 3.03507209e-01 1.79952502e-01
7.59442672e-02 1.05329148e-01 -4.67414349e-01 6.36859834e-01
1.91549212e-01 -4.73555148e-01 3.37091476e-01 3.05885583e-01
8.25635940e-02 5.44126570e-01 -1.52253047e-01 2.45627642e-01
1.57796770e-01 7.17222929e-01 -1.09903002e+00 -1.46847159e-01
6.81797385e-01 -4.37560007e-02 -3.13364029e-01 6.36274457e-01
-9.04191613e-01 5.60131252e-01 -8.14371705e-01 2.51191139e-01
-3.16628963e-01 -8.06969106e-02 5.70401073e-01 4.59607393e-01
-3.55396926e-01 3.28802794e-01 -1.09981370e+00 8.90520930e-01
-4.32654321e-01 5.27268350e-01 3.01454574e-01 -1.34502196e+00
8.87010872e-01 6.73689902e-01 9.14936662e-01 -7.96006620e-01
1.60654292e-01 -4.58281301e-02 4.47903037e-01 -7.12628186e-01
-1.59826964e-01 7.10464567e-02 -9.62660164e-02 7.25138545e-01
1.13686092e-01 -2.65699804e-01 4.47000593e-01 -1.57457858e-01
1.49989986e+00 -4.87455316e-02 7.13689387e-01 1.49792731e-02
3.29741061e-01 2.89112657e-01 5.37213206e-01 9.36184406e-01
-4.90679145e-01 -7.28376746e-01 2.81721860e-01 -7.97559917e-01
-9.68632102e-01 -8.81227553e-01 3.67092699e-01 1.59429443e+00
1.56613916e-01 -1.46918699e-01 -3.67725909e-01 -5.61641991e-01
1.55687690e-01 7.30193436e-01 -6.13334656e-01 -2.33392745e-01
-6.55394733e-01 -7.50193000e-01 7.90845696e-03 5.48930168e-01
2.84143150e-01 -1.61624563e+00 -1.03245878e+00 5.50285876e-01
5.58065951e-01 -9.06044781e-01 1.97316185e-01 3.60086501e-01
-5.54703772e-01 -1.47808170e+00 -1.69573054e-02 -7.97382951e-01
2.63818860e-01 1.82415952e-03 8.17008078e-01 -5.66549785e-02
-1.20011650e-01 8.21610689e-01 -1.92169935e-01 -8.71118307e-01
-8.70061815e-01 -1.07800148e-01 3.31183374e-01 -4.02342975e-01
3.50520134e-01 -3.09359163e-01 -2.96159595e-01 4.74900395e-01
-4.88701850e-01 -1.84698045e-01 6.59388125e-01 1.00124335e+00
2.16346383e-02 3.07796150e-01 8.96368265e-01 -3.45878780e-01
9.35755730e-01 -6.96632266e-01 -1.16389251e+00 1.05659470e-01
-7.21738040e-01 2.50702471e-01 6.91561162e-01 -5.35379410e-01
-1.14617896e+00 1.75923854e-02 2.41693974e-01 1.14851603e-02
-5.38925290e-01 3.22799623e-01 1.40597433e-01 7.35291466e-02
5.25976300e-01 4.86711264e-02 5.79583168e-01 2.10649207e-01
5.49107552e-01 4.97171253e-01 1.33617312e-01 -6.10841393e-01
4.06268567e-01 2.35565469e-01 6.69643879e-02 -7.35237658e-01
-5.35571754e-01 -1.06085464e-01 -1.06027745e-01 -3.63521606e-01
7.73023307e-01 -1.04324818e+00 -1.23472333e+00 3.36269110e-01
-8.08532894e-01 -1.28704846e+00 -2.52029240e-01 8.05352390e-01
-1.07279813e+00 -3.07701945e-01 -4.71345603e-01 -7.27522254e-01
4.06032018e-02 -1.27000463e+00 4.96415287e-01 6.06712937e-01
-4.40570325e-01 -1.33938599e+00 6.92266047e-01 1.64449796e-01
2.44174466e-01 3.79277505e-02 8.94699335e-01 -7.78439164e-01
-6.64456427e-01 2.36668572e-01 3.84021878e-01 3.25251371e-02
1.53785393e-01 1.96009368e-01 -3.34053963e-01 -4.35682327e-01
-3.45409334e-01 -7.43677855e-01 3.71650845e-01 8.84308875e-01
6.06218994e-01 -5.36488712e-01 -4.80218858e-01 -6.40008375e-02
1.19738853e+00 8.89293015e-01 2.42046844e-02 5.37829041e-01
1.93413258e-01 7.41394281e-01 6.78313851e-01 8.12179446e-01
6.86148047e-01 4.61006284e-01 8.31019759e-01 3.43433350e-01
1.00435345e-02 1.59674019e-01 7.27684021e-01 2.93026656e-01
1.54855132e-01 -2.29775622e-01 -9.18738127e-01 4.32447195e-01
-2.45679665e+00 -1.19876647e+00 1.93481430e-01 1.53665853e+00
4.74652231e-01 -1.19253114e-01 3.56839776e-01 -3.49883258e-01
4.99013990e-01 -6.55730143e-02 -1.05639267e+00 -5.96164525e-01
2.05366820e-01 -7.77245089e-02 4.98629153e-01 6.98010623e-01
-1.23966718e+00 1.12662697e+00 7.64453125e+00 3.70881796e-01
-7.54070103e-01 -1.17784835e-01 2.24015802e-01 3.39772254e-02
1.94706157e-01 -2.26756260e-01 -9.67396379e-01 1.42906800e-01
1.38045359e+00 -3.60581040e-01 8.58518600e-01 8.00397456e-01
7.56122410e-01 -2.37607017e-01 -1.09272254e+00 4.74082351e-01
-1.12807430e-01 -1.49968934e+00 -1.84506491e-01 1.10249840e-01
1.09262156e+00 5.16493618e-01 -7.30169937e-02 6.18400574e-01
1.75920320e+00 -1.00145566e+00 4.05565560e-01 2.00499520e-01
-2.10065514e-01 -9.48196411e-01 3.75487566e-01 4.14402574e-01
-8.67261708e-01 -1.07444811e+00 -1.21218652e-01 -6.67655408e-01
-1.14443466e-01 -2.14361742e-01 -9.29090083e-01 8.11517686e-02
4.72764432e-01 8.60027671e-01 5.07221855e-02 8.87987435e-01
-5.64381957e-01 6.43909156e-01 -4.86836694e-02 -6.49338007e-01
5.53527653e-01 -2.17853099e-01 5.42414486e-01 6.27089918e-01
-1.25817642e-01 2.06527263e-01 9.20563102e-01 4.72489119e-01
2.84571767e-01 -3.81736100e-01 -6.45821691e-01 -5.39471172e-02
5.90619266e-01 1.04082215e+00 -2.10995764e-01 -4.36885267e-01
-5.25748849e-01 2.75225118e-02 4.54182327e-01 4.46242422e-01
-4.73987311e-01 1.74215734e-01 1.24587679e+00 -5.83352804e-01
2.55649686e-01 -4.17981386e-01 -2.69438922e-01 -5.05610585e-01
-9.32559669e-01 -1.36731422e+00 5.93247950e-01 -2.49777809e-01
-1.17140853e+00 5.52503951e-02 1.06473707e-01 -6.48132980e-01
-1.05874765e+00 -6.85623348e-01 -7.70787001e-01 2.40610018e-01
-1.46595681e+00 -7.48755515e-01 -4.06071693e-02 6.48843050e-01
8.75391006e-01 -1.15314353e+00 1.17314148e+00 -4.12736595e-01
-7.77629673e-01 -8.64201412e-02 3.81356478e-01 1.27298295e-01
4.46220517e-01 -1.26783550e+00 5.13758361e-02 2.87791073e-01
-5.15919998e-02 -1.66283682e-01 8.24665546e-01 -5.53274274e-01
-1.64287758e+00 -1.26543212e+00 2.48705526e-03 -2.03226820e-01
1.04628885e+00 2.26812869e-01 -3.42225105e-01 8.77411008e-01
7.74164617e-01 -3.39513868e-01 5.93441367e-01 1.69320032e-01
-9.34896059e-03 -1.14141181e-01 -7.40114987e-01 8.14916313e-01
2.96483308e-01 4.35198173e-02 -4.28858936e-01 3.49492520e-01
4.83091503e-01 -1.84669778e-01 -7.99860895e-01 2.71300375e-01
4.43952829e-01 -5.49579263e-01 7.41897225e-01 -1.00469601e+00
1.64099351e-01 -1.59716666e-01 1.60161316e-01 -1.82961595e+00
-4.70326751e-01 -8.72227669e-01 -5.07085502e-01 5.10556340e-01
2.05149874e-01 -6.46755815e-01 6.87770486e-01 5.16905606e-01
-1.72250763e-01 -4.61652577e-01 -5.92087030e-01 -7.10613608e-01
2.46430665e-01 1.11561446e-02 2.30192482e-01 6.90822124e-01
2.19260022e-01 6.83104932e-01 -2.24844426e-01 4.87811595e-01
9.60429072e-01 7.12255761e-02 9.60288346e-01 -1.14459157e+00
-3.68476599e-01 -7.47201800e-01 -2.25513563e-01 -6.86384201e-01
7.02016771e-01 -3.71044099e-01 2.06794485e-01 -1.53390121e+00
1.80481505e-02 -3.90942246e-01 -2.30729301e-02 7.15434730e-01
1.77747503e-01 -5.00168920e-01 9.67680067e-02 -1.14946842e-01
-8.27381968e-01 6.84427321e-01 1.16082990e+00 -4.53551471e-01
-3.28666270e-01 3.52921128e-01 -4.70602721e-01 7.50265837e-01
1.40266669e+00 -3.34694713e-01 -5.26668191e-01 -2.81011552e-01
-6.35484830e-02 2.44198844e-01 3.36835206e-01 -8.84502590e-01
3.87256503e-01 -1.02405953e+00 1.02817535e-01 -3.99916209e-02
2.01807469e-01 -6.92034781e-01 -2.52893806e-01 9.94498014e-01
-8.02212238e-01 1.09996505e-01 1.03909910e-01 7.53457129e-01
5.78891346e-03 -2.83174604e-01 8.15501511e-01 -4.49703485e-01
-1.12394273e+00 3.02715957e-01 -1.37499774e+00 -4.38170694e-03
1.58113325e+00 4.88388389e-01 -3.65165830e-01 -6.26845896e-01
-5.95641255e-01 1.05732405e+00 -1.99073106e-01 7.30374098e-01
6.26835942e-01 -1.00802326e+00 -1.04647362e+00 1.75561768e-03
-2.35117242e-01 -2.44620234e-01 -2.23423198e-01 1.75089598e-01
8.51826221e-02 4.47804779e-01 -5.60924172e-01 -3.51803213e-01
-1.25496817e+00 4.33402568e-01 7.40827501e-01 -3.53249192e-01
-2.89865524e-01 1.96702093e-01 1.65972024e-01 -5.79600155e-01
4.74529535e-01 1.82636350e-01 -5.94870389e-01 -3.09951991e-01
5.93908131e-01 5.60260594e-01 -4.92616504e-01 -7.92760476e-02
1.06918998e-01 -2.87967660e-02 -1.73299998e-01 -3.08688164e-01
1.43308783e+00 -9.81489494e-02 3.98410074e-02 4.88873422e-01
5.62856674e-01 -9.54079092e-01 -1.76283216e+00 -2.98220426e-01
1.67417884e-01 1.07629694e-01 2.44122267e-01 -8.70149136e-01
-7.10374773e-01 4.41294670e-01 5.15223861e-01 4.09967721e-01
4.04639930e-01 5.28136492e-02 1.18894219e-01 7.05520451e-01
3.37367833e-01 -1.46036136e+00 7.99469113e-01 9.86964822e-01
8.62521887e-01 -1.43908167e+00 -2.99862027e-02 3.17989051e-01
-6.53623164e-01 1.28794253e+00 1.04749954e+00 -4.41446602e-01
7.16610551e-01 5.41650772e-01 1.84833914e-01 -3.21561843e-01
-1.59888208e+00 -4.29371625e-01 -2.65711218e-01 1.13712072e+00
-3.17157656e-02 2.16105253e-01 1.82975277e-01 -2.66089320e-01
1.75742611e-01 -2.20245466e-01 6.07176185e-01 8.35938931e-01
-8.03866386e-01 -1.25635493e+00 -3.11266124e-01 4.25319672e-01
7.10516647e-02 4.12361413e-01 -1.92362681e-01 6.20846927e-01
-1.23675138e-01 1.29516423e+00 3.94051641e-01 5.85994385e-02
8.33140388e-02 -2.87191629e-01 6.14790082e-01 -6.65370226e-01
-4.13137257e-01 1.92707859e-03 1.83960825e-01 -5.94234228e-01
-6.92175269e-01 -8.96422327e-01 -1.54782128e+00 -4.63102646e-02
7.73588642e-02 1.02543883e-01 7.13373125e-01 1.12303555e+00
1.92992136e-01 9.38498318e-01 8.14810276e-01 -8.52738678e-01
-9.50738549e-01 -8.08954716e-01 -1.30086422e-01 -1.22657761e-01
5.28568447e-01 -7.54784644e-01 -7.62745813e-02 -7.19879493e-02] | [3.806912660598755, 2.0264902114868164] |
db6d9e82-e4dc-4264-b0e0-06a48d173206 | sapnet-segmentation-aware-progressive-network | 2111.08892 | null | https://arxiv.org/abs/2111.08892v2 | https://arxiv.org/pdf/2111.08892v2.pdf | SAPNet: Segmentation-Aware Progressive Network for Perceptual Contrastive Deraining | Deep learning algorithms have recently achieved promising deraining performances on both the natural and synthetic rainy datasets. As an essential low-level pre-processing stage, a deraining network should clear the rain streaks and preserve the fine semantic details. However, most existing methods only consider low-level image restoration. That limits their performances at high-level tasks requiring precise semantic information. To address this issue, in this paper, we present a segmentation-aware progressive network (SAPNet) based upon contrastive learning for single image deraining. We start our method with a lightweight derain network formed with progressive dilated units (PDU). The PDU can significantly expand the receptive field and characterize multi-scale rain streaks without the heavy computation on multi-scale images. A fundamental aspect of this work is an unsupervised background segmentation (UBS) network initialized with ImageNet and Gaussian weights. The UBS can faithfully preserve an image's semantic information and improve the generalization ability to unseen photos. Furthermore, we introduce a perceptual contrastive loss (PCL) and a learned perceptual image similarity loss (LPISL) to regulate model learning. By exploiting the rainy image and groundtruth as the negative and the positive sample in the VGG-16 latent space, we bridge the fine semantic details between the derained image and the groundtruth in a fully constrained manner. Comprehensive experiments on synthetic and real-world rainy images show our model surpasses top-performing methods and aids object detection and semantic segmentation with considerable efficacy. A Pytorch Implementation is available at https://github.com/ShenZheng2000/SAPNet-for-image-deraining. | ['Gaurav Gupta', 'Yuxiong Wu', 'Changjie Lu', 'Shen Zheng'] | 2021-11-17 | null | null | null | null | ['single-image-deraining'] | ['computer-vision'] | [ 3.19141299e-01 -1.42955288e-01 1.99895397e-01 -5.52947223e-01
-5.04825950e-01 -2.92071730e-01 1.83898166e-01 -4.03602839e-01
-4.42363173e-01 7.88472652e-01 -2.80022055e-01 -1.33384511e-01
3.12402308e-01 -1.10230625e+00 -9.50055301e-01 -1.12099278e+00
1.46295175e-01 1.71208784e-01 5.55533528e-01 -2.43660703e-01
-1.40469909e-01 5.94650149e-01 -1.45267951e+00 7.99301714e-02
1.46107674e+00 8.20710480e-01 7.70523369e-01 5.91225505e-01
-1.33023560e-01 7.66389012e-01 -4.48863506e-01 -9.79220048e-02
4.89162326e-01 -3.73964250e-01 -5.25679588e-01 2.06804425e-01
8.53948355e-01 -4.20914173e-01 -2.98516273e-01 1.43053949e+00
4.98293310e-01 2.50404507e-01 3.15490335e-01 -1.04148853e+00
-6.16337836e-01 1.07622020e-01 -5.61215878e-01 5.57096779e-01
-3.76493514e-01 1.35725141e-01 6.34325206e-01 -9.84116554e-01
3.84880453e-01 1.31471229e+00 7.92776525e-01 4.67548102e-01
-1.16989815e+00 -8.07701766e-01 3.30496877e-01 1.22812003e-01
-1.22981918e+00 -1.15572281e-01 7.54590929e-01 -1.93836287e-01
4.19554859e-01 2.99155116e-01 7.35388756e-01 7.52325892e-01
1.36969969e-01 8.22112858e-01 1.36213577e+00 -1.39423519e-01
2.35760272e-01 3.63897309e-02 1.76322356e-01 7.31333315e-01
4.45743978e-01 1.99947566e-01 5.00394069e-02 3.54584754e-01
9.61485326e-01 3.76365721e-01 -6.99744880e-01 -2.56686777e-01
-5.86807013e-01 8.83145690e-01 8.97628546e-01 1.75117165e-01
-3.37874353e-01 -1.38635235e-02 -2.43271694e-01 1.71992809e-01
7.73622036e-01 1.12613909e-01 -3.80790204e-01 5.71296990e-01
-1.29941177e+00 2.48246297e-01 5.65760553e-01 5.09795725e-01
1.20901942e+00 5.17769217e-01 -9.90322381e-02 8.69041979e-01
2.74817526e-01 1.06461990e+00 1.43109366e-01 -1.03960168e+00
2.52617687e-01 4.11867350e-01 1.08613566e-01 -9.49061096e-01
-3.65034640e-01 -6.58767402e-01 -1.09042084e+00 6.19671285e-01
3.45721632e-01 3.75603996e-02 -1.51564026e+00 1.49056041e+00
4.38299030e-01 4.40271884e-01 1.66649967e-01 1.18169439e+00
9.03995514e-01 8.94106567e-01 1.70593321e-01 -1.85622618e-01
1.09606910e+00 -1.12842941e+00 -6.20983064e-01 -6.67535961e-01
1.22640026e-03 -6.52570128e-01 1.28176975e+00 2.15521201e-01
-1.01393831e+00 -7.65838981e-01 -1.00771940e+00 -1.20109446e-01
-2.89300501e-01 2.41267104e-02 4.81889457e-01 4.88972634e-01
-1.05893433e+00 7.24577487e-01 -8.92992198e-01 -3.66952717e-01
6.66030645e-01 5.00015728e-03 -9.63182300e-02 -4.46134895e-01
-1.30786836e+00 7.34541297e-01 4.88634139e-01 6.07924104e-01
-1.22246075e+00 -7.13581204e-01 -7.73351490e-01 -5.79453558e-02
2.28183299e-01 -7.75819123e-01 7.18108892e-01 -1.28255224e+00
-1.25280261e+00 9.53897953e-01 1.06336996e-01 -6.39802217e-01
4.26480770e-01 -4.18125749e-01 -3.84209365e-01 4.62824732e-01
9.95067731e-02 7.23750710e-01 1.27345252e+00 -1.70660949e+00
-6.33961797e-01 -2.68379241e-01 5.27106971e-02 3.85278046e-01
1.15165181e-01 -2.81069845e-01 -4.61036295e-01 -1.00216150e+00
3.04447919e-01 -7.44645357e-01 -3.12321573e-01 4.09941636e-02
-2.87856400e-01 3.70189667e-01 1.02968490e+00 -1.01999867e+00
8.59361351e-01 -2.09849358e+00 -1.91872916e-03 -8.25677514e-02
2.29707241e-01 7.28314698e-01 -3.01915407e-01 -2.92545527e-01
7.81965256e-02 -2.01053604e-01 -1.01908410e+00 -2.68419623e-01
-2.37436473e-01 6.68724418e-01 -5.36734700e-01 6.38982773e-01
2.20104024e-01 9.96684194e-01 -7.14274406e-01 -3.52495551e-01
3.98138970e-01 7.20234632e-01 -4.06870127e-01 4.93808836e-01
-3.43477279e-01 5.51922143e-01 -3.07389140e-01 8.47851455e-01
1.28182566e+00 2.28029327e-03 -3.04023802e-01 -3.35485697e-01
-4.58509289e-02 -2.90639013e-01 -1.05404055e+00 1.33062625e+00
-4.57922995e-01 4.20199990e-01 5.93188643e-01 -1.05123329e+00
9.59678054e-01 -2.32127309e-01 -1.12517960e-01 -8.71757507e-01
-2.63214670e-02 2.05601215e-01 -4.36613649e-01 -4.95479226e-01
3.85883182e-01 -4.29234684e-01 3.84568989e-01 -1.33796409e-01
-1.30171254e-01 -4.33664262e-01 -9.17213857e-02 5.12901656e-02
5.53337276e-01 1.89274266e-01 -1.08846493e-01 -3.58389705e-01
5.09173334e-01 -8.97993743e-02 9.49576557e-01 8.85423064e-01
-2.57271945e-01 1.01016402e+00 -5.84674217e-02 -4.46979910e-01
-9.05324280e-01 -1.36787271e+00 -2.60941327e-01 1.00802100e+00
5.57174861e-01 3.17293495e-01 -9.24352348e-01 -5.71635246e-01
-1.26445545e-02 7.30368376e-01 -6.02465093e-01 -2.45765457e-03
-6.97992325e-01 -1.27821350e+00 4.53079760e-01 5.01068056e-01
1.12597036e+00 -1.33423078e+00 -3.73335958e-01 8.85916874e-02
-3.65722656e-01 -1.18851411e+00 -3.09670269e-01 2.28211835e-01
-1.02620053e+00 -9.89102483e-01 -7.07920849e-01 -9.39867079e-01
7.69099593e-01 5.38132131e-01 1.22383142e+00 3.08576897e-02
-4.59207773e-01 1.04231991e-01 -3.08014542e-01 -1.86982974e-01
-3.68703417e-02 -3.61781120e-01 -3.16696107e-01 7.42269009e-02
1.14027955e-01 -8.40298772e-01 -8.21118176e-01 1.55998304e-01
-1.18466091e+00 1.00566037e-01 6.90183222e-01 8.31682742e-01
7.62942970e-01 2.21433252e-01 2.00358123e-01 -8.34787130e-01
9.59200636e-02 -2.68005162e-01 -7.78181255e-01 1.04308039e-01
-4.89193767e-01 -2.29975671e-01 4.68841016e-01 -1.23619542e-01
-1.34631634e+00 9.85002331e-03 -2.22095042e-01 -5.49679458e-01
-2.48278990e-01 3.47982496e-02 -5.01695931e-01 -2.81567812e-01
4.48087126e-01 5.83703518e-01 -1.27950266e-01 -5.49058139e-01
4.99455988e-01 3.02011341e-01 7.42444754e-01 -3.81258309e-01
1.20551157e+00 9.94800866e-01 -2.61187822e-01 -9.80388403e-01
-1.25176346e+00 -4.16193336e-01 -5.22680938e-01 -5.89967296e-02
1.05958760e+00 -1.30672991e+00 -3.24300796e-01 7.95776367e-01
-8.13586235e-01 -9.11588907e-01 -4.31632102e-01 2.48507068e-01
-2.84703076e-01 5.56559980e-01 -7.02220619e-01 -7.47442722e-01
-5.63989103e-01 -8.87634277e-01 9.20010090e-01 5.76770842e-01
6.46800399e-01 -9.58291948e-01 -1.18561730e-01 5.73312223e-01
5.98831594e-01 3.58406186e-01 6.28991544e-01 7.25821964e-03
-9.51553941e-01 2.22394735e-01 -5.99543214e-01 9.81132507e-01
-5.77949099e-02 -2.70948023e-01 -1.08186948e+00 -4.84263897e-01
3.91670346e-01 -2.23750547e-01 1.59504318e+00 7.27766156e-01
9.96418893e-01 -1.80053890e-01 -3.27363573e-02 1.22638667e+00
1.62582684e+00 -1.83157735e-02 9.16886568e-01 5.09062707e-01
9.57873344e-01 4.71475720e-01 6.70602262e-01 4.16660793e-02
2.50842333e-01 3.00044060e-01 7.22114980e-01 -7.74897635e-01
-5.84222972e-01 -6.71256986e-03 4.41815883e-01 5.11805952e-01
-1.97544500e-01 -2.18543276e-01 -6.49601400e-01 5.68597138e-01
-1.65685844e+00 -9.07195985e-01 -6.92701116e-02 2.00106525e+00
8.52950811e-01 1.99346505e-02 -4.04887319e-01 -2.72787511e-01
7.83801794e-01 4.91856724e-01 -6.18727684e-01 8.81171450e-02
-6.19382262e-01 3.20012927e-01 6.98950529e-01 9.31678832e-01
-1.46390164e+00 1.33355629e+00 4.89004946e+00 1.02648771e+00
-1.21111929e+00 3.24539185e-01 7.12492883e-01 1.43694267e-01
-1.50633633e-01 -1.85853064e-01 -9.38601613e-01 6.41072810e-01
4.84981537e-01 3.14341754e-01 4.61678445e-01 8.50236177e-01
3.99235815e-01 -1.87382042e-01 -1.61024809e-01 7.76948810e-01
7.42659494e-02 -1.08346939e+00 1.68924108e-01 -4.08626735e-01
8.82938802e-01 3.65961105e-01 1.18720166e-01 3.76659453e-01
3.59999686e-01 -9.93380070e-01 5.24116516e-01 6.96536481e-01
6.48977280e-01 -5.27089417e-01 7.57288396e-01 9.84897763e-02
-1.11566663e+00 -9.70937312e-03 -6.83380067e-01 1.68671489e-01
6.48056418e-02 9.58465159e-01 -3.15097541e-01 5.19873857e-01
1.10018539e+00 7.13835001e-01 -5.35131276e-01 9.45271969e-01
-7.14811683e-01 8.51336777e-01 -3.87418896e-01 7.51073360e-01
3.43539834e-01 -6.54573917e-01 7.06125259e-01 1.42563188e+00
8.88474584e-02 2.56456673e-01 3.83560210e-01 9.08581257e-01
-5.23200608e-04 -2.41667151e-01 -2.34845191e-01 3.20613444e-01
1.29209414e-01 1.33995712e+00 -8.46488416e-01 -3.53213847e-01
-2.24907964e-01 1.28758550e+00 5.81098646e-02 8.71891260e-01
-9.60667968e-01 -3.70720297e-01 7.16929972e-01 2.13935152e-01
5.54839134e-01 -1.53602019e-01 -2.89421946e-01 -1.27594602e+00
-2.25000568e-02 -7.58222401e-01 1.77382246e-01 -8.44027936e-01
-1.26665485e+00 8.21814120e-01 -2.49073699e-01 -1.02599692e+00
5.48675358e-01 -3.95176440e-01 -7.22889245e-01 9.61259305e-01
-2.19792199e+00 -1.36464417e+00 -9.40824926e-01 6.28768444e-01
5.92166007e-01 1.53889298e-01 3.83983314e-01 4.60547328e-01
-6.48316860e-01 1.64755955e-01 3.65285039e-01 8.52101594e-02
7.52356112e-01 -1.35742164e+00 2.24630252e-01 1.38863432e+00
-1.77679792e-01 2.94082463e-01 8.66973460e-01 -7.41935372e-01
-6.48731947e-01 -1.73461413e+00 4.42211956e-01 -1.61461234e-01
4.39905047e-01 -3.32389534e-01 -1.38853967e+00 5.64719379e-01
-7.68257231e-02 4.89022017e-01 2.25971527e-02 -4.24487382e-01
-2.93478251e-01 -4.21487689e-01 -1.17315531e+00 3.90544683e-01
8.78641248e-01 -3.32095832e-01 -7.11609602e-01 3.97734702e-01
8.28871906e-01 -4.28082854e-01 -3.97040159e-01 7.81775713e-01
8.50427523e-02 -1.12550616e+00 1.27460587e+00 -9.67082158e-02
3.35524529e-01 -6.69452727e-01 -3.38845789e-01 -1.20403624e+00
-3.00707698e-01 -2.85941958e-01 -2.52679326e-02 1.13991976e+00
-5.57760708e-03 -5.98064899e-01 8.35393250e-01 1.17219843e-01
-3.73387158e-01 -5.11837840e-01 -6.90761209e-01 -7.84465909e-01
1.66549146e-01 -1.48758680e-01 1.97208703e-01 9.73430157e-01
-1.09601569e+00 5.03221154e-02 -5.07173777e-01 7.31790125e-01
1.05238426e+00 5.36111236e-01 4.99994218e-01 -1.10166860e+00
-1.42720342e-01 -1.43335789e-01 -1.14885300e-01 -1.06373787e+00
1.24189846e-01 -8.50769222e-01 3.74447852e-01 -1.72716296e+00
2.31540889e-01 -3.56197357e-01 -3.79747570e-01 5.81040800e-01
-4.92169499e-01 6.86022580e-01 2.79428095e-01 3.35867971e-01
-6.43360317e-01 9.63388264e-01 1.44555843e+00 -2.48504594e-01
-2.29422048e-01 5.72350658e-02 -4.15319175e-01 1.06769824e+00
9.75006521e-01 -5.60220718e-01 -1.80041790e-01 -3.80108505e-01
-3.61225784e-01 -3.62965673e-01 7.97788918e-01 -1.08914995e+00
-1.29700927e-02 -8.45623612e-02 5.12088418e-01 -5.27733564e-01
3.31997454e-01 -6.43626630e-01 -1.40235117e-02 5.55971980e-01
1.38445631e-01 -5.93722463e-01 3.02370012e-01 7.33577371e-01
-4.24378335e-01 7.95219764e-02 1.41285193e+00 -2.08403572e-01
-1.02447248e+00 4.51823324e-01 -1.76068634e-01 1.51269093e-01
7.40157306e-01 -3.36501271e-01 -4.45641071e-01 -7.96867460e-02
-9.54460502e-01 2.41366223e-01 5.51481843e-01 1.91600814e-01
7.43364155e-01 -7.61473656e-01 -7.82515645e-01 3.21981639e-01
-3.14596295e-01 2.66707331e-01 6.78013206e-01 8.20764542e-01
-9.24895108e-01 8.33083317e-03 -4.27964270e-01 -4.36020643e-01
-1.22435832e+00 3.42267573e-01 6.53665781e-01 -1.37606561e-01
-1.05567586e+00 1.00226092e+00 9.53877330e-01 -4.51676339e-01
2.14794174e-01 -3.78340036e-01 -1.50372639e-01 2.88946391e-03
5.26560903e-01 1.96759790e-01 -7.52356201e-02 -5.25515795e-01
-1.73310190e-01 5.56571245e-01 -9.60929096e-02 3.88605356e-01
1.47037816e+00 -4.12059873e-01 -3.76609683e-01 2.20950589e-01
8.72765064e-01 -1.67555496e-01 -1.89216805e+00 -3.75898510e-01
-4.47697252e-01 -5.40954053e-01 4.49684083e-01 -7.85018623e-01
-1.57197022e+00 9.77616370e-01 1.02694178e+00 -7.70031363e-02
1.42971277e+00 -2.16506854e-01 9.52652812e-01 2.91460663e-01
9.37222391e-02 -8.69896233e-01 1.09530166e-01 6.02707624e-01
7.91176021e-01 -1.34873652e+00 -6.58016130e-02 -5.29804289e-01
-6.43358290e-01 8.38310361e-01 6.70419335e-01 -4.40664262e-01
5.61657012e-01 2.11228833e-01 4.53152686e-01 -1.60996020e-01
4.71266806e-02 -6.02746069e-01 3.23701054e-02 6.60854459e-01
-8.61984044e-02 4.48963903e-02 -9.66249630e-02 5.64007103e-01
1.35852545e-01 -2.20828891e-01 4.92882073e-01 7.05185533e-01
-1.01209509e+00 -6.26213193e-01 -6.42462790e-01 1.82737604e-01
-4.06029612e-01 -4.92619246e-01 1.27743155e-01 7.37772286e-01
4.82714742e-01 8.18767250e-01 -3.60106031e-04 1.78998765e-02
2.48620644e-01 -3.32045496e-01 3.73973638e-01 -4.94803071e-01
-2.14616328e-01 1.16116285e-01 -3.98816228e-01 -6.86480224e-01
-6.55149043e-01 -3.20875853e-01 -1.28795695e+00 -9.82723832e-02
-1.07404783e-01 2.00498492e-01 3.41126263e-01 7.52496541e-01
6.41111061e-02 5.94694495e-01 5.07304072e-01 -1.13957930e+00
-1.60008624e-01 -7.14997113e-01 -1.14628494e+00 3.52777988e-01
5.47208726e-01 -5.69066048e-01 -7.21368432e-01 2.91191041e-01] | [10.903042793273926, -3.191300392150879] |
59beb649-2a34-4acf-884e-ab48442ef0ef | diversifying-joint-vision-language | 2306.03421 | null | https://arxiv.org/abs/2306.03421v2 | https://arxiv.org/pdf/2306.03421v2.pdf | Diversifying Joint Vision-Language Tokenization Learning | Building joint representations across images and text is an essential step for tasks such as Visual Question Answering and Video Question Answering. In this work, we find that the representations must not only jointly capture features from both modalities but should also be diverse for better generalization performance. To this end, we propose joint vision-language representation learning by diversifying the tokenization learning process, enabling tokens that are sufficiently disentangled from each other to be learned from both modalities. We observe that our approach outperforms the baseline models in a majority of settings and is competitive with state-of-the-art methods. | ['Anelia Angelova', 'AJ Piergiovanni', 'Vardaan Pahuja'] | 2023-06-06 | null | null | null | null | ['visual-question-answering-1', 'video-question-answering'] | ['computer-vision', 'computer-vision'] | [-1.87055543e-02 -1.36809379e-01 -4.76799071e-01 -4.80296612e-01
-1.00698662e+00 -6.44861400e-01 8.69994164e-01 5.36644049e-02
-5.83928287e-01 5.52666008e-01 4.84344959e-01 -2.54477024e-01
2.18293414e-01 -4.71675366e-01 -8.11084569e-01 -3.94254029e-01
2.49358460e-01 2.24699602e-01 1.20499462e-01 1.84775233e-01
-1.41422272e-01 1.93211183e-01 -1.44000959e+00 5.81442952e-01
4.50604618e-01 9.05723035e-01 1.62423328e-01 5.95990300e-01
-2.00589016e-01 1.17254126e+00 -2.29220957e-01 -3.47082108e-01
-1.25556931e-01 -1.38637170e-01 -9.72983420e-01 1.94796041e-01
8.68063807e-01 -5.26545763e-01 -8.44950736e-01 8.05849612e-01
2.17827961e-01 3.62523884e-01 8.64606380e-01 -1.22184658e+00
-1.19880581e+00 3.20153713e-01 -7.64346361e-01 1.33277565e-01
3.00580204e-01 1.85512155e-01 1.54793394e+00 -9.65507686e-01
6.04793012e-01 1.41179347e+00 6.50397316e-02 6.54562712e-01
-1.23503792e+00 -7.30222166e-01 6.27018213e-01 4.37566042e-01
-1.19673121e+00 -4.49098885e-01 6.74073279e-01 -5.37190139e-01
8.15971851e-01 5.64272776e-02 2.48251632e-01 1.19107878e+00
-3.48167062e-01 1.29726684e+00 8.81970048e-01 -3.57151479e-01
-7.65487552e-02 1.05498619e-01 1.21822767e-02 8.87554526e-01
2.65506774e-01 -2.37682372e-01 -7.69331574e-01 -1.19329952e-01
6.84595525e-01 3.83893937e-01 -3.52885455e-01 -5.45243680e-01
-1.34610295e+00 1.00302410e+00 5.97878337e-01 2.83371150e-01
-4.64954555e-01 8.44768345e-01 3.66710663e-01 8.61222371e-02
3.25478047e-01 3.38698328e-01 -3.54298741e-01 -8.15089121e-02
-6.85398519e-01 1.89522758e-01 4.41554993e-01 8.66396070e-01
8.58952761e-01 2.81444769e-02 -6.21769369e-01 7.43026733e-01
5.43456495e-01 5.56259453e-01 1.90748841e-01 -1.02693546e+00
5.48169076e-01 5.19508481e-01 1.19406812e-01 -4.47412968e-01
6.51176423e-02 -7.92575069e-03 -6.90658569e-01 7.34798759e-02
4.94701296e-01 -3.33285704e-02 -1.36606944e+00 2.02229857e+00
1.24667145e-01 2.23315150e-01 2.57235821e-02 8.55616331e-01
1.21480501e+00 6.99740767e-01 4.08383936e-01 3.03414345e-01
1.68638659e+00 -1.03410053e+00 -7.26918817e-01 -3.80248696e-01
3.43889713e-01 -6.13868177e-01 1.00167167e+00 -3.67116742e-02
-9.31049168e-01 -4.88367230e-01 -8.53110969e-01 -6.12647414e-01
-2.44217694e-01 2.39618391e-01 5.91891110e-01 3.12787294e-01
-7.16823816e-01 -2.32114438e-02 -8.36160123e-01 -3.46248120e-01
7.27806926e-01 1.68963876e-02 -6.48925543e-01 -5.83856165e-01
-1.05746400e+00 8.03408980e-01 1.07646056e-01 1.94163676e-02
-1.20398140e+00 -5.29764891e-01 -1.10449684e+00 7.07711279e-02
4.32354271e-01 -1.09886920e+00 1.27856040e+00 -7.91024864e-01
-1.12777829e+00 9.63157415e-01 -5.14214694e-01 -3.89554203e-01
2.86364555e-01 -4.80469108e-01 6.92466497e-02 4.62750912e-01
1.87418889e-02 8.00464511e-01 1.08059251e+00 -1.40385997e+00
-3.89488190e-01 -3.63972694e-01 4.74353641e-01 2.40813628e-01
-3.53700846e-01 -8.59133229e-02 -8.49596322e-01 -2.92497009e-01
-1.50405914e-01 -7.27299452e-01 -1.16460994e-01 4.29701030e-01
-4.14089888e-01 -4.25117344e-01 8.31499934e-01 -6.97170079e-01
5.25496900e-01 -2.00808382e+00 3.77442181e-01 -3.83231044e-02
5.56272447e-01 2.10714772e-01 -3.67626786e-01 3.69318038e-01
1.18475169e-01 2.06962109e-01 1.50649130e-01 -7.86148429e-01
1.00031637e-01 4.80687439e-01 -4.90670860e-01 6.72303736e-01
3.48605126e-01 1.30920792e+00 -9.26306009e-01 -5.69266796e-01
1.59820199e-01 5.89789808e-01 -4.26108658e-01 4.21131730e-01
-5.09191632e-01 4.26998198e-01 -6.78608418e-01 7.25231111e-01
4.80872720e-01 -6.71326339e-01 1.04152329e-01 -3.02436948e-01
2.69593686e-01 2.41832867e-01 -7.77094066e-01 1.87344539e+00
-4.92188692e-01 9.23119307e-01 3.77230458e-02 -1.19896591e+00
6.34451032e-01 5.14699757e-01 3.65621179e-01 -6.91502869e-01
-9.91098508e-02 -2.08714172e-01 -2.20118880e-01 -8.12242985e-01
5.22286832e-01 -2.72293121e-01 2.77507827e-02 4.58233535e-01
3.54749799e-01 3.15314531e-02 -2.78911777e-02 5.26756763e-01
7.63159752e-01 2.64903437e-02 2.57981420e-01 3.06503236e-01
1.96328685e-01 -2.93498069e-01 3.94837528e-01 8.51733923e-01
-3.26196313e-01 6.74617648e-01 5.70875704e-01 -3.11690457e-02
-8.79485011e-01 -1.35861242e+00 1.57608002e-01 1.29596853e+00
8.83676261e-02 -4.35535461e-01 -1.58767655e-01 -9.38948691e-01
3.00771385e-01 4.40313250e-01 -9.49984252e-01 -2.79105995e-02
-2.79725909e-01 -4.36958037e-02 6.64839149e-01 9.34300780e-01
3.32573891e-01 -8.32120478e-01 -3.03439170e-01 -2.97465861e-01
-2.59304166e-01 -1.59778917e+00 -3.89817506e-01 -7.32025877e-02
-5.60591638e-01 -1.19930673e+00 -1.03542769e+00 -7.88867056e-01
6.44376755e-01 6.49311543e-01 1.26145279e+00 2.68166095e-01
-1.59525737e-01 9.75646913e-01 -4.97958601e-01 -3.53454530e-01
3.41666257e-03 1.71924178e-02 -3.40765327e-01 1.50279298e-01
3.81974608e-01 -3.92523170e-01 -7.00011432e-01 -1.34673879e-01
-1.11772811e+00 -6.87497556e-02 6.29880846e-01 9.70917881e-01
6.37604296e-01 -6.68496132e-01 4.26372230e-01 -8.09745193e-01
4.59865004e-01 -5.99162400e-01 -2.29300946e-01 7.21359491e-01
-1.84471514e-02 2.17113629e-01 4.07299548e-01 -6.14785433e-01
-8.92100811e-01 -5.38886040e-02 7.47671723e-02 -8.93906951e-01
-1.84998691e-01 5.40147662e-01 -1.52357817e-01 1.90510526e-01
3.78394037e-01 2.34839976e-01 -8.79589692e-02 -5.98996222e-01
9.62154150e-01 4.32193011e-01 4.57737535e-01 -7.13768840e-01
9.12517607e-01 8.47558677e-01 -2.48328120e-01 -8.77224743e-01
-9.79040504e-01 -7.62905717e-01 -4.16933537e-01 -4.90557728e-03
1.17355573e+00 -1.20857215e+00 -8.34303319e-01 1.57103673e-01
-1.50813770e+00 -5.43669239e-02 -2.54089594e-01 6.23153210e-01
-2.92128175e-01 5.20562232e-01 -4.89817530e-01 -8.25486839e-01
-1.16753593e-01 -1.02497947e+00 1.19490266e+00 4.56394345e-01
4.70476821e-02 -1.03430283e+00 1.03207909e-01 5.91123104e-01
2.96041280e-01 3.92661281e-02 7.76290655e-01 -7.44183481e-01
-8.12613070e-01 -1.27345413e-01 -7.75925219e-01 4.33769614e-01
1.50741860e-01 2.15804279e-02 -1.17163777e+00 -3.59807640e-01
-3.51654112e-01 -9.08225954e-01 1.59785783e+00 2.87661821e-01
1.19873500e+00 -3.92065495e-02 -1.89974591e-01 4.99656409e-01
1.26003385e+00 -3.97347480e-01 5.83955407e-01 1.15711629e-01
1.06517172e+00 6.02544904e-01 2.24583566e-01 2.43884340e-01
8.50152016e-01 4.94019687e-01 6.29131854e-01 -2.81021804e-01
-3.56020719e-01 -3.66865814e-01 3.22383910e-01 4.51816469e-01
1.50576690e-02 -1.68296754e-01 -8.38248253e-01 9.79532599e-01
-2.07124329e+00 -1.03539801e+00 7.18760937e-02 1.78285897e+00
6.66878223e-01 -3.55563134e-01 4.85494360e-02 -4.80754316e-01
5.41099072e-01 6.30258501e-01 -6.25625372e-01 -1.68578595e-01
-2.99784988e-02 2.06957430e-01 3.10751259e-01 3.16553235e-01
-1.09287989e+00 1.05193150e+00 6.66385031e+00 4.31519717e-01
-9.78250802e-01 2.68470913e-01 3.82795155e-01 -6.50105700e-02
-6.72168195e-01 2.27670103e-01 -4.55197752e-01 1.32106589e-02
3.62024605e-01 -2.75653265e-02 1.42660469e-01 6.58299923e-01
-1.82700723e-01 -7.34057054e-02 -1.24556184e+00 1.07696176e+00
3.79474163e-01 -1.38516712e+00 2.95221925e-01 -1.09553583e-01
7.95788169e-01 2.03561291e-01 2.93288022e-01 4.13241297e-01
4.73296702e-01 -1.39256048e+00 6.47494137e-01 5.80560505e-01
7.62183547e-01 -3.32238257e-01 4.68272805e-01 1.99579582e-01
-1.29464984e+00 2.09396452e-01 -3.48491192e-01 1.40080139e-01
2.52255797e-01 4.10622448e-01 -5.33644080e-01 6.88847899e-01
5.81280112e-01 8.12855661e-01 -5.02693892e-01 1.03275597e+00
-5.25060236e-01 6.73438728e-01 -1.61068097e-01 5.76175973e-02
1.91424266e-01 2.71558523e-01 2.25753978e-01 1.23754478e+00
1.18115814e-02 -1.25966787e-01 2.83378601e-01 1.07053816e+00
-6.53017998e-01 -7.46531710e-02 -6.97190344e-01 -3.53985310e-01
4.22945201e-01 1.06844342e+00 -1.34751424e-01 -5.20579934e-01
-8.58644903e-01 9.05317545e-01 6.11264884e-01 9.10199165e-01
-6.82360888e-01 -1.59476146e-01 8.66880655e-01 -3.28583091e-01
7.33082771e-01 -6.01208448e-01 -1.12695560e-01 -1.64629567e+00
8.32632110e-02 -5.43645799e-01 5.23776472e-01 -8.23853970e-01
-1.69111073e+00 3.31448466e-01 -4.86547612e-02 -1.03763556e+00
-3.23499143e-01 -8.12787890e-01 -5.90600610e-01 9.92156684e-01
-2.10667372e+00 -1.75247538e+00 -2.80668199e-01 9.34821546e-01
3.66744041e-01 2.69908011e-02 7.01110005e-01 7.55977854e-02
-4.70453233e-01 5.64617574e-01 3.19065377e-02 4.81494486e-01
8.01472127e-01 -1.08658123e+00 2.38336787e-01 8.14342856e-01
7.87885606e-01 6.11574650e-01 4.66017395e-01 -3.77928793e-01
-1.63960457e+00 -8.63125324e-01 6.06949568e-01 -4.67408001e-01
7.47249901e-01 -4.62828487e-01 -1.01617801e+00 9.04999077e-01
4.40363884e-01 4.09743518e-01 9.04710829e-01 5.70598423e-01
-1.24279392e+00 9.28795040e-02 -6.93673790e-01 5.55921674e-01
6.17546260e-01 -1.24837279e+00 -7.19965935e-01 2.11363748e-01
6.32685661e-01 -1.66530773e-01 -6.11948192e-01 1.60327554e-01
6.07251585e-01 -6.61590219e-01 1.10629678e+00 -1.09797990e+00
5.56417167e-01 -1.55577198e-01 -4.60057944e-01 -9.83617425e-01
-8.48062336e-02 -2.84658164e-01 -5.50948858e-01 1.24381137e+00
3.56667399e-01 -4.37103093e-01 6.14817023e-01 6.37621105e-01
3.47685814e-01 -6.38044059e-01 -1.05999815e+00 -6.65816605e-01
3.14947754e-01 -5.55179894e-01 3.13347727e-01 8.73770297e-01
-1.75179362e-01 7.15415418e-01 -7.29404688e-01 1.36747822e-01
5.53136885e-01 3.70373011e-01 8.78068030e-01 -9.14574683e-01
-4.63980973e-01 -3.31112951e-01 -3.75469685e-01 -1.58113003e+00
4.93306637e-01 -8.55548561e-01 3.78888063e-02 -2.07156610e+00
6.80450976e-01 -2.10317969e-02 -5.00572741e-01 7.39456356e-01
-4.08639520e-01 3.36163759e-01 4.65713769e-01 2.30631530e-01
-9.90258157e-01 8.56280804e-01 1.43778205e+00 -3.33806783e-01
3.34164411e-01 -4.19227093e-01 -1.00493646e+00 5.43452501e-01
5.18570185e-01 -3.60780478e-01 -3.51867020e-01 -7.88891196e-01
1.41718790e-01 -7.98305795e-02 6.96256876e-01 -3.34446222e-01
1.37986168e-01 -4.08661902e-01 3.82403642e-01 -4.04311389e-01
7.24460721e-01 -5.61206877e-01 -7.89524734e-01 1.24039672e-01
-6.08673692e-01 -9.56565589e-02 6.13293573e-02 8.63118708e-01
-3.93173039e-01 -2.28506755e-02 4.70491439e-01 3.77213024e-02
-7.65522420e-01 5.20254731e-01 -2.61752456e-01 3.02851170e-01
8.35940540e-01 1.03694387e-01 -6.43142700e-01 -8.34977686e-01
-3.83971006e-01 5.26350200e-01 3.51074696e-01 6.09434605e-01
8.71609807e-01 -1.44626987e+00 -8.29681695e-01 -2.43237540e-01
5.01486421e-01 -4.67687882e-02 4.44926232e-01 7.38089681e-01
-9.58420634e-02 4.10435200e-01 3.15202139e-02 -5.61225712e-01
-1.20805192e+00 5.79581380e-01 6.02216423e-02 -3.61294657e-01
-4.42076743e-01 9.06204343e-01 5.16835988e-01 -3.13798100e-01
3.75932187e-01 -2.49168828e-01 -3.42198253e-01 1.08811613e-02
6.32944167e-01 -1.36807829e-01 -4.99053299e-01 -6.86862350e-01
-4.62330520e-01 4.46535498e-01 -3.68247032e-01 -2.51237810e-01
1.15201545e+00 -1.31777152e-01 2.03982383e-01 5.47948837e-01
1.59379995e+00 -4.93712313e-02 -1.36554122e+00 -6.45005763e-01
-3.13500464e-01 -6.45615995e-01 -4.18263599e-02 -5.69704592e-01
-1.18454468e+00 1.25836051e+00 3.07106793e-01 1.15891337e-01
7.88127363e-01 7.07111299e-01 6.38036728e-01 4.85521495e-01
-1.23482540e-01 -7.84883142e-01 5.89940548e-01 5.06207764e-01
8.12469482e-01 -1.49187398e+00 1.19434103e-01 -1.49278626e-01
-9.48525846e-01 1.00422585e+00 5.38341880e-01 -2.97735989e-01
5.70321858e-01 -1.81832328e-01 1.05953356e-02 -3.06958884e-01
-1.02737117e+00 -6.95045531e-01 8.82484913e-01 7.70527065e-01
6.29991531e-01 3.59414034e-02 1.34916514e-01 4.27453041e-01
4.89997745e-01 -1.47171304e-01 1.41058490e-01 1.01468134e+00
-3.01289976e-01 -1.17749834e+00 -2.08849028e-01 3.57184470e-01
-4.06844974e-01 -3.78332958e-02 -3.95649135e-01 7.48815835e-01
-1.61153719e-01 8.99492025e-01 4.95680124e-02 -2.58802146e-01
1.49963513e-01 4.58401442e-02 6.99058294e-01 -6.73163712e-01
-1.47156909e-01 -2.34867379e-01 1.31073922e-01 -4.69507307e-01
-6.55494571e-01 -5.72475553e-01 -1.05575359e+00 8.35406706e-02
-2.50274301e-01 -9.32463855e-02 6.45682096e-01 1.23243642e+00
3.45160723e-01 4.93765444e-01 2.81261295e-01 -6.86076701e-01
-5.39820850e-01 -7.74320543e-01 -4.41501647e-01 5.73755205e-01
6.43297672e-01 -7.52909243e-01 -2.18354315e-01 1.30850554e-01] | [10.71689224243164, 1.4633948802947998] |
2511059c-81e7-4bee-bbc0-f449bef9549e | road-damages-detection-and-classification | 2211.00091 | null | https://arxiv.org/abs/2211.00091v1 | https://arxiv.org/pdf/2211.00091v1.pdf | Road Damages Detection and Classification with YOLOv7 | Maintaining the roadway infrastructure is one of the essential factors in enabling a safe, economic, and sustainable transportation system. Manual roadway damage data collection is laborious and unsafe for humans to perform. This area is poised to benefit from the rapid advance and diffusion of artificial intelligence technologies. Specifically, deep learning advancements enable the detection of road damages automatically from the collected road images. This work proposes to collect and label road damage data using Google Street View and use YOLOv7 (You Only Look Once version 7) together with coordinate attention and related accuracy fine-tuning techniques such as label smoothing and ensemble method to train deep learning models for automatic road damage detection and classification. The proposed approaches are applied to the Crowdsensing-based Road Damage Detection Challenge (CRDDC2022), IEEE BigData 2022. The results show that the data collection from Google Street View is efficient, and the proposed deep learning approach results in F1 scores of 81.7% on the road damage data collected from the United States using Google Street View and 74.1% on all test images of this dataset. | ['Christopher Donan', 'Du Nguyen', 'Vung Pham'] | 2022-10-31 | null | null | null | null | ['road-damage-detection'] | ['computer-vision'] | [ 8.03187303e-03 -1.01965681e-01 -2.39395387e-02 -3.35287780e-01
-8.74218345e-01 -3.66782337e-01 5.59312761e-01 7.10160881e-02
-3.33122015e-01 6.12370133e-01 3.02627325e-01 -2.69862384e-01
-4.39762957e-02 -1.37744522e+00 -6.32571638e-01 -7.72070050e-01
1.69715434e-01 5.18580005e-02 2.77630985e-01 -2.06056550e-01
2.70668328e-01 6.79546356e-01 -1.91989291e+00 -1.85133815e-01
1.19951820e+00 1.07435489e+00 -4.59396206e-02 7.56721199e-01
1.77461561e-02 5.90304792e-01 -3.82183492e-01 -2.64752924e-01
2.32607886e-01 5.08135557e-01 -6.64516807e-01 -2.07499474e-01
6.09565735e-01 -7.25695729e-01 -2.96401650e-01 7.47636318e-01
8.80823910e-01 2.18959793e-01 8.54911923e-01 -1.21371365e+00
-7.19667375e-01 -3.30969274e-01 -6.58985674e-01 4.56304133e-01
-9.58743095e-02 2.76101381e-01 5.43959916e-01 -7.54829526e-01
5.74422553e-02 1.04039407e+00 6.22875631e-01 2.93451101e-01
-5.33126295e-01 -6.52939677e-01 -1.50125906e-01 5.32163680e-01
-1.43785071e+00 -4.47035164e-01 5.66768885e-01 -8.54319990e-01
1.11922002e+00 9.30886269e-02 1.88481465e-01 8.03014457e-01
1.68964729e-01 6.31669044e-01 8.59298408e-01 -1.46867886e-01
2.68983185e-01 -1.24303453e-01 2.30067119e-01 7.37395227e-01
3.84651244e-01 3.64702761e-01 -6.89608827e-02 2.05670565e-01
2.17208527e-02 2.27531701e-01 2.68568546e-01 1.28144115e-01
-5.04123151e-01 8.93971562e-01 8.20474982e-01 -4.05655578e-02
-6.78308845e-01 3.36897075e-01 5.96866906e-01 -1.32574206e-02
8.27557147e-01 -2.62773633e-01 -3.14389989e-02 -1.76446408e-01
-5.68581402e-01 2.03636169e-01 3.31097953e-02 5.95164716e-01
8.36357236e-01 1.84347153e-01 -6.45040721e-02 1.05599940e+00
2.12049723e-01 1.16192174e+00 -8.43869969e-02 -1.01711953e+00
7.42017627e-01 7.61246681e-01 4.24753457e-01 -1.36665022e+00
-5.84182203e-01 -7.00583635e-03 -9.18193221e-01 4.97139782e-01
1.01829834e-01 -2.91391313e-01 -1.12484586e+00 1.17709160e+00
5.31579137e-01 3.27079631e-02 -2.38141060e-01 6.70858324e-01
8.06083858e-01 6.40142739e-01 5.51421106e-01 4.07151371e-01
1.06915033e+00 -7.21958339e-01 -6.12675250e-01 -5.29812947e-02
9.57854807e-01 -3.05475980e-01 1.30592179e+00 3.65949422e-01
-5.64981341e-01 -5.93245029e-01 -9.25153852e-01 -3.46468955e-01
-1.10872066e+00 3.01399410e-01 1.82211131e-01 1.00940967e+00
-7.84042776e-01 2.59271204e-01 -3.95155162e-01 -4.41340059e-01
1.17602003e+00 1.36144295e-01 -2.26914853e-01 -5.39057195e-01
-1.38228357e+00 1.06594324e+00 -4.65906002e-02 1.63592741e-01
-1.20110357e+00 -6.01398468e-01 -5.97016931e-01 -1.20177031e-01
1.52257994e-01 -2.69885182e-01 8.51130009e-01 -1.08632326e-01
-9.57994759e-01 9.81806099e-01 -5.73589019e-02 -5.81103325e-01
4.60045755e-01 -7.03548789e-01 -6.18366361e-01 7.40521699e-02
3.91053617e-01 5.69085956e-01 7.17189133e-01 -1.17785990e+00
-1.19928086e+00 -4.55216646e-01 1.28193730e-02 4.74963784e-02
-3.36003691e-01 -1.11140437e-01 1.87859505e-01 -9.76884887e-02
-6.32932365e-01 -9.03146863e-01 8.71318057e-02 -1.54672891e-01
-3.88958991e-01 -6.07533157e-01 1.29191434e+00 -1.04644191e+00
1.25430191e+00 -1.79336059e+00 -7.10996926e-01 2.47698680e-01
2.48875618e-01 8.48848403e-01 1.31435484e-01 3.40068489e-01
1.30686387e-01 3.48408014e-01 -2.35337451e-01 -9.63772014e-02
-4.07503434e-02 1.34948626e-01 -2.13622853e-01 5.59399128e-01
1.01479627e-01 7.55608201e-01 -8.53823364e-01 -1.39079615e-01
6.44995749e-01 5.48254728e-01 -7.00702658e-03 1.42027274e-01
1.40237838e-01 1.89394310e-01 -4.20864999e-01 7.49908566e-01
7.99844742e-01 2.25587264e-01 -9.73637700e-01 -1.20660625e-01
-4.62162971e-01 1.53076693e-01 -7.90114939e-01 1.03018463e+00
-7.66936183e-01 7.91388869e-01 -3.13770831e-01 -8.45722854e-01
9.35244143e-01 2.65419215e-01 3.63733798e-01 -1.15257227e+00
1.85955554e-01 2.47533992e-03 -5.84427714e-01 -1.23999918e+00
3.81938785e-01 1.77861184e-01 -1.20047867e-01 4.43912238e-01
-5.84391773e-01 6.16333401e-03 -5.55837387e-03 2.17458438e-02
1.14884567e+00 -3.39321673e-01 -8.67142305e-02 4.27358877e-03
5.96579254e-01 1.05865464e-01 1.78076252e-01 5.20667136e-01
-4.77547497e-01 4.18346465e-01 -9.08891112e-02 -9.44156110e-01
-1.17633629e+00 -1.01067233e+00 3.48986574e-02 1.18983686e+00
-4.62710857e-02 4.04844105e-01 -9.98325884e-01 -7.55059898e-01
1.72810316e-01 9.26353872e-01 -6.18624330e-01 -3.20942611e-01
-4.51184928e-01 -7.50490665e-01 7.80137181e-01 6.76065385e-01
1.09915364e+00 -9.86019969e-01 -5.67839801e-01 -2.70951800e-02
-4.24860716e-01 -9.26201463e-01 -5.28757088e-02 -5.19811928e-01
-3.00416082e-01 -1.24643683e+00 -5.66748142e-01 -4.15707648e-01
3.82415444e-01 8.18849266e-01 7.44419515e-01 7.80141205e-02
-4.69814360e-01 4.61737305e-01 -1.72315940e-01 -9.62175429e-01
-4.27041911e-02 3.90691698e-01 -1.03053816e-01 1.24180995e-01
7.10116684e-01 -4.21799630e-01 -8.47202122e-01 4.48535591e-01
-6.90624356e-01 -3.53036195e-01 2.69314319e-01 1.60433531e-01
4.34773713e-01 4.92598087e-01 1.18666160e+00 -5.72683036e-01
6.11624181e-01 -9.40945268e-01 -7.36646652e-01 1.70250647e-02
-7.56904244e-01 -4.42815632e-01 2.30920047e-01 2.73666322e-01
-1.14268720e+00 3.44120376e-02 -4.34685230e-01 1.07441492e-01
-8.16604555e-01 1.16669364e-01 -3.29340458e-01 -5.44757620e-02
8.64052594e-01 -2.26969332e-01 -3.07710707e-01 -3.83739799e-01
4.95559484e-01 1.26846206e+00 4.46163714e-01 -1.06026776e-01
6.76368058e-01 9.18193460e-01 2.69839466e-02 -1.09564161e+00
-8.22095752e-01 -7.51935065e-01 -6.35250092e-01 -7.27956891e-01
1.26648736e+00 -1.11502874e+00 -7.97730029e-01 9.54413056e-01
-1.04812121e+00 -2.52296954e-01 1.87528990e-02 3.06994151e-02
-2.50230789e-01 1.08431473e-01 5.70109412e-02 -1.03454673e+00
-5.85299134e-01 -7.68071175e-01 1.28367937e+00 3.25556070e-01
1.55496284e-01 -8.26156259e-01 1.86979517e-01 7.09479272e-01
7.24616647e-01 6.33733809e-01 8.03150713e-01 -9.72840115e-02
-5.21576881e-01 -6.97141588e-01 -6.97083831e-01 6.35474503e-01
3.41956437e-01 -3.74361947e-02 -1.47049749e+00 2.05579489e-01
-4.22966689e-01 -2.61824071e-01 1.08022785e+00 5.01620233e-01
1.25611627e+00 -1.86011091e-01 -3.36337239e-01 -1.04441844e-01
1.38739908e+00 2.20819026e-01 1.11891854e+00 3.26214522e-01
1.20393288e+00 8.64514291e-01 5.56309342e-01 1.52800277e-01
9.39023972e-01 3.90457362e-01 9.81464505e-01 -2.07552388e-01
-2.86504000e-01 -1.81723148e-01 2.08570525e-01 2.79702961e-01
-9.03697610e-02 -3.34155798e-01 -1.34370422e+00 1.28392923e+00
-1.63675046e+00 -1.21804023e+00 -7.09385276e-01 2.22265482e+00
2.41904587e-01 -1.65838853e-01 4.12181139e-01 4.47976321e-01
9.76854205e-01 1.50562391e-01 -5.40823340e-01 -4.19094265e-01
8.19156393e-02 -1.39529929e-01 9.27218437e-01 6.11970246e-01
-1.53227234e+00 9.18507457e-01 5.52725458e+00 9.49363589e-01
-9.74797368e-01 3.62635195e-01 6.04463160e-01 2.36346126e-02
-1.35050535e-01 -6.54380500e-01 -8.17266881e-01 6.11572385e-01
1.24250340e+00 1.97732180e-01 3.86921823e-01 7.43935466e-01
9.33824956e-01 -4.66440856e-01 -2.52922535e-01 7.57231295e-01
-1.93364412e-01 -1.20278227e+00 -1.78919822e-01 2.49362022e-01
1.00075066e+00 5.47874928e-01 2.05830440e-01 1.21649742e-01
3.35591376e-01 -1.15145707e+00 1.41315371e-01 8.99286866e-01
7.35924602e-01 -9.92318273e-01 7.97874749e-01 4.33395594e-01
-1.04545844e+00 -4.59131390e-01 -3.93326759e-01 4.27526645e-02
3.78569394e-01 9.05946314e-01 -9.51667726e-01 2.22886473e-01
1.09958529e+00 8.21467400e-01 -4.42202508e-01 1.06232107e+00
-3.42197269e-01 8.11799347e-01 -2.71247894e-01 3.31995711e-02
2.73216218e-01 7.13618323e-02 3.71915340e-01 1.02823365e+00
3.54915679e-01 2.62054373e-02 -1.77749440e-01 3.10856253e-01
-1.57949090e-01 -2.07242161e-01 -1.22522819e+00 4.13485795e-01
3.53561163e-01 1.15437424e+00 -1.37969702e-01 -2.86945730e-01
-3.98907870e-01 3.69631499e-01 8.73047113e-02 2.06000328e-01
-9.10167694e-01 -5.42181194e-01 7.38549769e-01 5.65425277e-01
2.27280110e-01 -2.26607457e-01 -6.28193378e-01 -4.33091313e-01
-1.36409029e-01 -2.19483271e-01 1.78329483e-01 -9.61746871e-01
-1.31563568e+00 1.34517059e-01 2.63611674e-02 -1.12460852e+00
2.45990917e-01 -4.41353530e-01 -7.47722268e-01 9.00447726e-01
-2.05510449e+00 -1.23926926e+00 -9.30929840e-01 6.45137191e-01
5.76241493e-01 -1.22979581e-02 5.50592124e-01 9.04177368e-01
-6.51162028e-01 3.09444636e-01 1.19325057e-01 7.21926093e-02
5.18812835e-01 -1.03797972e+00 7.65775204e-01 8.60547066e-01
-4.36399132e-01 -1.78899691e-01 2.60753065e-01 -7.89767444e-01
-5.83816409e-01 -1.95937407e+00 9.92555618e-01 -6.38246000e-01
2.15753555e-01 3.04472186e-02 -8.33560348e-01 1.95638940e-01
1.60478488e-01 -1.25815585e-01 5.39419055e-01 -2.54166931e-01
-1.52528629e-01 -4.35865730e-01 -1.53289974e+00 2.79932708e-01
1.01972926e+00 -5.99384427e-01 -1.61887005e-01 5.33790231e-01
4.75517482e-01 -5.98582393e-03 -5.59131265e-01 2.59945810e-01
3.91484112e-01 -8.61204684e-01 9.50336397e-01 -4.55790669e-01
3.25619966e-01 -4.83548582e-01 -1.67619914e-01 -1.21367180e+00
-1.77669391e-01 -8.10282230e-02 4.96512577e-02 1.31765962e+00
2.81140566e-01 -6.38852775e-01 7.13193774e-01 8.11149180e-01
-4.63384420e-01 -3.18692356e-01 -1.00330746e+00 -6.39779866e-01
2.38368616e-01 -6.92200065e-01 7.34137416e-01 5.37300706e-01
-8.02228749e-01 1.39201254e-01 -5.19298434e-01 6.88919723e-01
6.75653636e-01 -4.88930911e-01 8.80397499e-01 -1.50190461e+00
1.01230037e+00 -1.87743768e-01 -3.60548645e-01 -5.49410641e-01
1.43468170e-03 -5.24231255e-01 5.01519442e-02 -1.93714070e+00
-3.07847708e-01 -5.97039402e-01 -1.54127806e-01 5.69965661e-01
-1.20101534e-01 2.06469223e-01 -3.76128525e-01 1.08018750e-02
-5.01466453e-01 6.63355529e-01 7.74160266e-01 -4.92183357e-01
-4.35078779e-04 2.82026857e-01 -6.66338503e-01 6.81001723e-01
1.27788723e+00 -6.60391152e-01 -4.29283708e-01 -6.67728543e-01
3.38966697e-01 -5.81989706e-01 7.16064572e-01 -1.24014306e+00
6.27756864e-02 -1.22443862e-01 -3.41363735e-02 -9.61450279e-01
4.49896939e-02 -9.05870438e-01 -2.29371548e-01 3.03418607e-01
-1.14419565e-01 -1.41867086e-01 1.91439301e-01 7.56860852e-01
9.96730998e-02 3.45389582e-02 7.44653165e-01 1.90175503e-01
-9.57296371e-01 3.98579538e-01 -6.30737185e-01 -1.75083075e-02
1.20983183e+00 -3.09290260e-01 -7.41143763e-01 -3.92882288e-01
-3.78627032e-01 4.92589086e-01 -9.24471766e-03 6.70015514e-01
5.79413831e-01 -1.48228300e+00 -7.25525200e-01 -1.04828533e-02
3.94106060e-01 1.08319141e-01 7.09107697e-01 5.59712112e-01
-3.90912592e-01 5.01688898e-01 -2.25889549e-01 -4.84685898e-01
-1.04972303e+00 4.97950137e-01 2.87500858e-01 3.52779366e-02
-4.27519530e-01 5.05568087e-01 -1.04705952e-01 -4.57030982e-01
9.56471190e-02 -2.83920318e-01 -6.50785983e-01 1.44857973e-01
7.65030801e-01 1.31002843e+00 4.79764372e-01 -8.83524060e-01
-3.45216125e-01 8.53796601e-01 2.30029836e-01 2.38804936e-01
1.24736917e+00 -6.03760064e-01 3.68202955e-01 7.47698620e-02
1.25464904e+00 -2.23055020e-01 -1.19062614e+00 1.60143792e-03
-5.39630763e-02 -4.36515749e-01 4.86546248e-01 -1.04970276e+00
-1.08459473e+00 1.46887231e+00 1.24539399e+00 4.93741482e-01
9.72307324e-01 -2.90055007e-01 1.37034118e+00 4.42360818e-01
2.64577389e-01 -1.50837779e+00 -1.17535628e-01 3.21934849e-01
9.45130706e-01 -1.66266668e+00 -2.97847658e-01 -1.73227400e-01
-6.46875560e-01 5.01783252e-01 5.26877701e-01 -1.99499637e-01
7.43636966e-01 -1.89429894e-01 8.09810087e-02 -5.29323161e-01
-2.01674864e-01 -7.52198219e-01 1.19679429e-01 1.14268994e+00
-1.85787708e-01 3.15982431e-01 1.30419731e-01 6.44035488e-02
2.87674904e-01 4.17807214e-02 3.40361625e-01 6.09968543e-01
-1.15809083e+00 -6.12161934e-01 -3.86134177e-01 6.98283970e-01
-2.95611054e-01 1.74366876e-01 -2.46547803e-01 6.45632088e-01
5.97008586e-01 1.50666642e+00 -1.30825251e-01 -4.55375582e-01
7.47303545e-01 -6.52196482e-02 -2.90894419e-01 -2.81104773e-01
-1.90551996e-01 -6.41964257e-01 3.64550680e-01 -5.60060143e-01
-5.22077620e-01 -5.11002004e-01 -1.13681734e+00 -6.33384049e-01
-1.37871966e-01 -4.57088500e-01 9.69423950e-01 1.06966627e+00
7.46625781e-01 2.92065769e-01 1.05240703e+00 -7.66046405e-01
3.85365672e-02 -7.76139200e-01 -1.97008446e-01 1.83417290e-01
5.92490971e-01 -1.14972770e+00 -2.38007203e-01 1.40660658e-01] | [7.407608509063721, 1.1035584211349487] |
fe93fb61-4fd5-4c10-8b2b-1b5eba342852 | modelling-neuronal-behaviour-with-time-series | 2107.06762 | null | https://arxiv.org/abs/2107.06762v1 | https://arxiv.org/pdf/2107.06762v1.pdf | Modelling Neuronal Behaviour with Time Series Regression: Recurrent Neural Networks on C. Elegans Data | Given the inner complexity of the human nervous system, insight into the dynamics of brain activity can be gained from understanding smaller and simpler organisms, such as the nematode C. Elegans. The behavioural and structural biology of these organisms is well-known, making them prime candidates for benchmarking modelling and simulation techniques. In these complex neuronal collections, classical, white-box modelling techniques based on intrinsic structural or behavioural information are either unable to capture the profound nonlinearities of the neuronal response to different stimuli or generate extremely complex models, which are computationally intractable. In this paper we show how the nervous system of C. Elegans can be modelled and simulated with data-driven models using different neural network architectures. Specifically, we target the use of state of the art recurrent neural networks architectures such as LSTMs and GRUs and compare these architectures in terms of their properties and their accuracy as well as the complexity of the resulting models. We show that GRU models with a hidden layer size of 4 units are able to accurately reproduce with high accuracy the system's response to very different stimuli. | ['L. Miguel Silveira', 'Arlindo L. Oliveira', 'Ruxandra Barbulescu', 'Gonçalo Mestre'] | 2021-07-01 | null | null | null | null | ['time-series-regression'] | ['time-series'] | [ 3.78449202e-01 -2.00201556e-01 5.55790246e-01 -4.94204648e-02
3.73123825e-01 -4.17354614e-01 8.55943859e-01 9.80884768e-03
-6.92209840e-01 6.87311888e-01 -2.84763813e-01 -2.54077584e-01
-4.24114019e-02 -4.87114161e-01 -7.13488519e-01 -8.75051618e-01
-4.12430137e-01 3.77670318e-01 5.15080094e-01 -4.63639647e-01
2.65427623e-02 4.60933864e-01 -1.83845532e+00 2.18438089e-01
4.11507994e-01 6.94863021e-01 4.91768181e-01 1.09147799e+00
2.72908002e-01 7.38968611e-01 -5.63570023e-01 1.03253372e-01
-2.75486141e-01 -7.04424858e-01 -5.88640988e-01 -4.36913043e-01
-8.06087777e-02 5.77054881e-02 -1.16064392e-01 7.30250418e-01
6.19742036e-01 3.87556218e-02 5.87611377e-01 -6.09934032e-01
5.17188199e-02 4.51480836e-01 2.08267212e-01 2.24517897e-01
1.00018360e-01 2.41148934e-01 3.87743741e-01 -2.80717075e-01
5.85760295e-01 1.31358278e+00 8.24847162e-01 9.94983852e-01
-1.87405980e+00 -4.44412172e-01 -1.08738728e-01 -2.90854704e-02
-9.47241962e-01 -5.83495855e-01 3.72487783e-01 -5.49839556e-01
1.21835756e+00 9.19759795e-02 9.75667059e-01 1.43400812e+00
6.17710412e-01 3.88872534e-01 1.23990059e+00 -2.67987996e-01
6.25587821e-01 -2.06397742e-01 -2.29562214e-03 3.39278877e-01
6.04763664e-02 3.16303074e-01 -2.80569673e-01 4.11552154e-02
9.56588447e-01 -7.97523335e-02 -3.58481817e-02 -2.13870853e-01
-1.28702712e+00 4.81834352e-01 5.09216070e-01 6.61359489e-01
-2.83230513e-01 7.65648365e-01 6.18730605e-01 3.70714575e-01
1.33095026e-01 5.48757195e-01 -5.28242648e-01 -1.48710251e-01
-7.48565793e-01 5.06455779e-01 8.92038226e-01 3.60800028e-01
3.95146668e-01 4.51913714e-01 4.80135977e-01 7.99830496e-01
1.28318593e-01 2.25210488e-01 9.11728740e-01 -1.03508162e+00
-2.04300538e-01 6.22883439e-01 -1.62988827e-01 -7.15875387e-01
-7.10347056e-01 -4.60648924e-01 -1.19212556e+00 4.97337699e-01
4.30020362e-01 -2.23581120e-01 -9.34301376e-01 1.94564390e+00
1.95047781e-02 1.45316929e-01 1.26947060e-01 5.08956432e-01
4.65062022e-01 5.93203306e-01 1.55433044e-01 -1.08975604e-01
8.92590046e-01 -1.72435850e-01 -2.92986065e-01 -4.13048327e-01
8.72561872e-01 -1.75066620e-01 4.80407059e-01 1.85753897e-01
-1.33431995e+00 -4.12387311e-01 -9.72047746e-01 1.83950439e-01
-7.09543228e-01 -3.50443900e-01 4.74098623e-01 3.49485964e-01
-1.30827749e+00 1.10069227e+00 -1.41049623e+00 -5.70488036e-01
1.77257936e-02 7.33862340e-01 -3.02142054e-01 4.55900222e-01
-1.19965112e+00 1.20188344e+00 5.99143207e-01 2.96647578e-01
-1.03383803e+00 -5.74161291e-01 -5.88204145e-01 2.29977548e-01
-1.89817548e-01 -7.47931600e-01 1.43337989e+00 -7.88016319e-01
-1.49520791e+00 6.31591439e-01 -5.88379614e-02 -8.50413024e-01
3.28260005e-01 4.49311644e-01 1.94452852e-01 -2.24688768e-01
-6.39627874e-01 8.36833537e-01 4.95545924e-01 -9.88374770e-01
-2.19095182e-02 -3.63609672e-01 -2.75897235e-01 -2.03123540e-02
2.11796641e-01 2.17799574e-01 2.56959736e-01 -4.78336364e-01
-8.45365003e-02 -9.98910129e-01 -6.00840747e-01 -7.79171437e-02
-5.97630888e-02 3.01673174e-01 5.55531144e-01 -3.77946615e-01
9.59125817e-01 -1.87234557e+00 5.56386590e-01 8.21285509e-03
2.15233654e-01 5.05745649e-01 -5.94604611e-02 6.55422330e-01
-1.66454241e-01 1.44008845e-01 -3.29735786e-01 -1.15280688e-01
-3.71438044e-04 5.75854838e-01 -9.03869048e-02 1.88789904e-01
1.54664934e-01 9.85613286e-01 -6.86985552e-01 -5.88357076e-02
2.73710579e-01 9.15792465e-01 -5.10031700e-01 1.39255419e-01
-4.44259137e-01 5.27049482e-01 -3.71158540e-01 1.47667095e-01
-1.72195405e-01 5.57132438e-02 2.68281460e-01 4.04362410e-01
-2.94591755e-01 4.39853698e-01 -6.33626938e-01 1.19249475e+00
-5.82035959e-01 8.15631747e-01 1.62593812e-01 -1.16108429e+00
8.46872509e-01 4.75089371e-01 1.01241507e-01 -8.71686757e-01
4.80795026e-01 3.85228306e-01 8.86371553e-01 6.74613714e-02
-3.43587220e-01 -2.11277828e-01 -2.25189142e-03 4.67930049e-01
3.35493743e-01 -2.09660754e-01 3.40094179e-01 -2.58152753e-01
1.17947018e+00 1.19621724e-01 2.55554169e-01 -4.91747320e-01
3.78891975e-01 -3.63513619e-01 2.33220503e-01 5.83082318e-01
2.25123212e-01 3.24393094e-01 7.08693504e-01 -5.97213149e-01
-1.38996696e+00 -5.68495870e-01 -2.81321257e-01 8.33941579e-01
-5.49070060e-01 -3.47717963e-02 -1.39167345e+00 5.32488585e-01
-2.91691810e-01 3.97459269e-01 -1.02986813e+00 -5.91054678e-01
-6.65181696e-01 -1.03495491e+00 7.70860910e-01 2.84321338e-01
3.03557396e-01 -1.60580647e+00 -1.47607791e+00 7.17063308e-01
4.73444790e-01 -7.99024284e-01 5.37424147e-01 7.62620568e-01
-1.11287916e+00 -9.77880716e-01 -7.42710352e-01 -5.53128958e-01
4.08941865e-01 -3.82284045e-01 8.46441031e-01 1.45104796e-01
-5.17013311e-01 -2.25951388e-01 1.02645569e-01 -5.83378851e-01
-7.84573436e-01 4.24901918e-02 2.26464108e-01 -3.13433439e-01
-1.46344444e-02 -1.05847502e+00 -3.63819718e-01 3.22827488e-01
-1.26946294e+00 2.66503632e-01 4.10652816e-01 9.69254136e-01
3.38467777e-01 -1.18910514e-01 3.95888567e-01 -6.75363302e-01
8.45707536e-01 -3.81410182e-01 -5.71826577e-01 4.69248369e-03
-1.76543012e-01 3.34406555e-01 8.83118808e-01 -7.37458408e-01
-7.53374279e-01 5.97879775e-02 -2.49146715e-01 6.55088201e-02
-3.93239498e-01 5.33163786e-01 2.07601279e-01 -4.14367139e-01
6.02648377e-01 6.27342582e-01 -2.47428399e-02 -5.56262493e-01
-2.46787354e-01 2.24116534e-01 4.88460749e-01 -4.49687272e-01
2.26073653e-01 9.32632685e-02 3.45706761e-01 -9.83559847e-01
-9.49886888e-02 2.32710406e-01 -7.34233320e-01 -2.75188744e-01
4.61826712e-01 -4.00641471e-01 -1.08713317e+00 1.13142133e+00
-1.15991557e+00 -9.08393383e-01 -2.21737381e-02 3.24097455e-01
-9.29951370e-01 -1.85152754e-01 -8.26798856e-01 -9.96940196e-01
-2.05272913e-01 -1.20289874e+00 8.11390936e-01 1.40319452e-01
-4.17879909e-01 -1.26337492e+00 5.85816264e-01 -4.87614214e-01
7.17234015e-01 5.61209261e-01 1.30414379e+00 -5.87624252e-01
-1.86757725e-02 -2.78713733e-01 2.31663719e-01 1.45133436e-01
-3.07762504e-01 2.96284437e-01 -1.10517693e+00 -2.35471740e-01
2.64165729e-01 -3.61283928e-01 8.46245050e-01 5.12577653e-01
7.93298304e-01 -3.05784702e-01 -3.19334358e-01 4.71275538e-01
1.27482879e+00 3.70748490e-01 6.80757165e-01 2.62444675e-01
2.66947925e-01 8.82343709e-01 -3.94608498e-01 -4.73304000e-03
-9.56983641e-02 7.28525043e-01 5.25285959e-01 6.98643103e-02
1.82932377e-01 -7.72587508e-02 4.19598788e-01 9.54714894e-01
-3.19701076e-01 -1.06678173e-01 -1.18893516e+00 4.11522418e-01
-1.90662849e+00 -1.07968044e+00 2.06855945e-02 2.26264453e+00
8.36854339e-01 3.89265686e-01 2.12318227e-01 4.55924332e-01
5.51207900e-01 -2.20871210e-01 -7.23399103e-01 -9.12464619e-01
-1.79931358e-01 2.22503960e-01 2.42224187e-01 2.23193631e-01
-5.83137751e-01 6.91228688e-01 7.52917147e+00 2.76586354e-01
-1.21387577e+00 -2.55585790e-01 6.78386271e-01 -2.79149920e-01
3.77936035e-01 -2.68795878e-01 -7.23699749e-01 7.52887070e-01
1.88394535e+00 -1.57886997e-01 8.46171021e-01 3.36352378e-01
3.96568805e-01 -2.01178685e-01 -1.22276843e+00 6.48140788e-01
-3.37225646e-01 -1.26992023e+00 -1.92614436e-01 2.88294792e-01
5.48250377e-01 4.36117142e-01 7.67736882e-02 2.94928610e-01
5.18018484e-01 -1.43096864e+00 4.66124713e-01 8.34694386e-01
2.60837793e-01 -6.25859499e-01 7.38686621e-01 9.06135619e-01
-7.44125783e-01 -4.76547852e-02 -6.14808977e-01 -4.98189539e-01
-9.50761810e-02 6.59119710e-02 -4.69521731e-01 -2.99758255e-01
6.34879231e-01 5.40702820e-01 -6.50326610e-01 1.14827526e+00
2.27364168e-01 5.80004692e-01 -7.58145630e-01 -4.73118931e-01
4.39678222e-01 -6.99804500e-02 2.29172751e-01 1.19807792e+00
3.38185102e-01 -8.17369446e-02 -6.26485288e-01 1.05203569e+00
1.54325366e-01 -3.58960420e-01 -7.95134723e-01 -2.38118783e-01
5.21180704e-02 9.49217379e-01 -6.24781311e-01 -2.05454603e-01
6.19603060e-02 3.58655065e-01 4.88807797e-01 4.05536890e-01
-3.25558841e-01 -1.82056099e-01 7.90576398e-01 9.19812620e-02
2.16229916e-01 -3.71317714e-01 -1.39550781e-02 -9.24871027e-01
-2.36800045e-01 -8.25756609e-01 -3.69168788e-01 -8.49952698e-01
-5.80213964e-01 6.63107157e-01 -4.88125253e-03 -6.67588472e-01
-8.99593890e-01 -9.35810149e-01 -8.91964495e-01 7.92039096e-01
-9.09569502e-01 -6.86331511e-01 2.54072636e-01 3.07132304e-01
1.93210632e-01 2.18276814e-01 1.27272928e+00 -9.87142920e-02
-7.02113450e-01 5.09285443e-02 4.61540729e-01 -8.51329044e-02
-4.15210426e-02 -1.15202177e+00 8.44601154e-01 3.96661550e-01
-6.35638386e-02 7.71126747e-01 1.15547788e+00 -1.99320391e-01
-1.15689540e+00 -8.77698660e-01 7.94767499e-01 -2.72470921e-01
8.11057687e-01 -8.46902847e-01 -1.21721196e+00 5.92349589e-01
-6.93373606e-02 1.70899630e-02 4.61859703e-01 -2.91024566e-01
-1.26029402e-01 2.41590708e-01 -8.69760096e-01 9.16827857e-01
7.85832107e-01 -4.00235176e-01 -5.51855087e-01 -2.09494475e-02
1.82697684e-01 1.26648392e-03 -7.75860727e-01 3.91227782e-01
9.23312724e-01 -1.15211260e+00 8.79426479e-01 -7.63036668e-01
3.14851344e-01 7.48947188e-02 1.03553846e-01 -1.59437799e+00
-1.90134630e-01 -5.20544529e-01 -2.43452564e-01 8.22134256e-01
3.60283434e-01 -8.12418401e-01 4.39469725e-01 7.29266286e-01
2.24203184e-01 -8.43842745e-01 -9.73728597e-01 -6.05273247e-01
4.23118651e-01 -1.46438599e-01 1.99127585e-01 4.30623710e-01
2.92723268e-01 2.88989246e-01 -9.06322971e-02 -4.29919094e-01
3.56702417e-01 -3.37511271e-01 3.51980984e-01 -1.53043175e+00
-3.01982403e-01 -7.36124396e-01 -8.95003259e-01 -4.38094527e-01
2.32271820e-01 -3.85956794e-01 4.82270531e-02 -1.23417473e+00
1.79916024e-02 -1.10986203e-01 -3.48986924e-01 3.18779290e-01
3.70821863e-01 1.93443328e-01 4.82782722e-02 8.97613987e-02
-1.57418907e-01 3.03999215e-01 8.60839248e-01 1.77325815e-01
5.75458771e-03 -8.44848678e-02 -4.31034714e-02 9.59268093e-01
1.03831875e+00 -4.74177629e-01 -2.23094195e-01 -4.61257875e-01
5.44970810e-01 3.37834880e-02 6.33389890e-01 -1.37305140e+00
3.28594208e-01 1.56194672e-01 6.81521714e-01 4.26469883e-03
5.61758757e-01 -6.30156279e-01 4.84439671e-01 9.54053819e-01
-7.10961819e-01 8.32935572e-02 4.21961218e-01 3.13993663e-01
-1.96812466e-01 -2.61925817e-01 8.86430800e-01 -5.93936086e-01
-2.49809921e-01 -8.90101865e-02 -1.09189844e+00 -2.61385083e-01
8.13448489e-01 -3.50180447e-01 -2.22820610e-01 -2.20940307e-01
-8.29403162e-01 1.76298041e-02 6.44864500e-01 4.18447778e-02
3.13414395e-01 -8.80407333e-01 -4.74291444e-01 3.02490443e-01
-3.10433388e-01 -1.94647446e-01 2.04260990e-01 7.10501134e-01
-6.67485476e-01 8.68988037e-01 -7.93293297e-01 -3.81774217e-01
-1.16531825e+00 3.94961715e-01 9.05910075e-01 -2.07567513e-01
-1.55421063e-01 5.55286586e-01 4.50751901e-01 -6.96665406e-01
-1.24572180e-02 -5.87925553e-01 -3.11357409e-01 -1.03326350e-01
4.67472911e-01 7.15605319e-02 2.50722580e-02 -6.90503716e-01
-1.80450335e-01 5.67483485e-01 8.67877305e-02 -4.44885939e-02
1.44084907e+00 2.72176713e-01 -9.15243179e-02 8.11465442e-01
9.31804836e-01 -9.65726495e-01 -1.22851217e+00 5.32045998e-02
6.77470788e-02 2.98712641e-01 8.81700590e-02 -6.51764214e-01
-6.40882134e-01 1.49290180e+00 3.48118573e-01 4.64397579e-01
1.00954485e+00 -4.91726100e-01 4.70325083e-01 7.73212373e-01
4.65845406e-01 -8.22539568e-01 -4.57537681e-01 6.90484285e-01
7.04081595e-01 -6.33480489e-01 -2.88972080e-01 2.16085881e-01
-2.82268263e-02 1.09160054e+00 2.86122411e-01 -6.47599697e-01
3.42941493e-01 5.70840299e-01 -1.44307628e-01 6.81440681e-02
-1.65225208e+00 4.03465107e-02 -1.21492207e-01 6.08078718e-01
5.83121181e-01 -1.57141000e-01 -8.93561915e-03 1.37148529e-01
-2.92878181e-01 3.57807577e-02 6.61544383e-01 8.95146906e-01
-5.82404077e-01 -9.66878891e-01 2.05373764e-02 3.20634782e-01
-6.44340992e-01 -5.46869487e-02 -7.40742505e-01 7.30247140e-01
-2.85211742e-01 3.40178311e-01 8.52599333e-04 -2.25274980e-01
9.37037393e-02 3.50335926e-01 6.27346456e-01 -5.97549856e-01
-9.61354315e-01 -2.54205726e-02 -1.12894572e-01 -4.88933682e-01
-3.65456790e-01 -6.02726400e-01 -1.09733498e+00 -3.65610778e-01
-5.41910008e-02 -9.88588035e-02 1.04950941e+00 9.86895502e-01
2.53900439e-01 6.97621703e-01 1.56993419e-01 -1.45866668e+00
-3.97791922e-01 -1.08296335e+00 -4.59105790e-01 6.64246455e-02
4.44041848e-01 -5.27808011e-01 -3.20045769e-01 1.74060568e-01] | [8.065876960754395, 2.924891948699951] |
66ba059b-7fa2-45bc-ad4d-fc32581f496e | self-supervised-eeg-representation-learning | 2110.15278 | null | https://arxiv.org/abs/2110.15278v3 | https://arxiv.org/pdf/2110.15278v3.pdf | Self-supervised EEG Representation Learning for Automatic Sleep Staging | Background: Deep learning models have shown great success in automating tasks in sleep medicine by learning from carefully annotated Electroencephalogram (EEG) data. However, effectively utilizing a large amount of raw EEG remains a challenge. Objective: In this paper, we aim to learn robust vector representations from massive unlabeled EEG signals, such that the learned vectorized features (1) are expressive enough to replace the raw signals in the sleep staging task; and (2) provide better predictive performance than supervised models in scenarios of fewer labels and noisy samples. Methods: We propose a self-supervised model, named Contrast with the World Representation (ContraWR), for EEG signal representation learning, which uses global statistics from the dataset to distinguish signals associated with different sleep stages. The ContraWR model is evaluated on three real-world EEG datasets that include both at-home and in-lab EEG recording settings. Results: ContraWR outperforms 4 recent self-supervised learning methods on the sleep staging task across 3 large EEG datasets. ContraWR also beats supervised learning when fewer training labels are available (e.g., 4% accuracy improvement when less than 2% data is labeled). Moreover, the model provides informative representative feature structures in 2D projection. Conclusions: We show that ContraWR is robust to noise and can provide high-quality EEG representations for downstream prediction tasks. The proposed model can be generalized to other unsupervised physiological signal learning tasks. Future directions include exploring task-specific data augmentations and combining self-supervised with supervised methods, building upon the initial success of self-supervised learning in this paper. | ['Jimeng Sun', 'M. Brandon Westover', 'Danica Xiao', 'Chaoqi Yang'] | 2021-10-27 | null | null | null | null | ['sleep-staging'] | ['medical'] | [ 4.26672429e-01 -4.84718150e-03 -1.51913956e-01 -8.13527107e-01
-8.27296734e-01 -1.97699904e-01 1.43034816e-01 1.04703344e-02
-4.95765030e-01 1.06063044e+00 4.59409952e-01 6.47351593e-02
-2.78154850e-01 -2.27314472e-01 -4.34125155e-01 -7.68925965e-01
-3.02103311e-01 2.55339414e-01 -3.10443908e-01 -1.09020598e-01
-6.38421252e-02 3.38971823e-01 -1.42633700e+00 2.59067535e-01
8.63572955e-01 1.19358611e+00 2.74505585e-01 1.81818813e-01
2.92502046e-01 6.30275726e-01 -7.89855182e-01 3.44141334e-01
1.12754926e-01 -5.33036709e-01 -6.12293959e-01 1.78577974e-02
2.71220058e-02 8.80746990e-02 -1.55221358e-01 8.87173474e-01
9.25525188e-01 1.24805547e-01 5.68242967e-01 -1.16086113e+00
-4.39509332e-01 6.09279275e-01 -4.02366012e-01 8.21639240e-01
1.81569561e-01 1.95977107e-01 8.55031252e-01 -7.69721389e-01
8.48136917e-02 4.10301149e-01 7.11310983e-01 8.53364050e-01
-1.57693481e+00 -1.16843200e+00 6.45789057e-02 3.08010936e-01
-1.47611856e+00 -6.86681271e-01 8.60943556e-01 -3.91371727e-01
1.12613904e+00 2.67977506e-01 9.00880396e-01 1.61990058e+00
3.66143554e-01 6.60449028e-01 1.51333976e+00 -4.57169600e-02
5.99195242e-01 8.87926221e-02 6.01935148e-01 3.11177015e-01
1.19608000e-01 -1.24569483e-01 -1.03485990e+00 -8.10999796e-02
5.56017399e-01 3.21618617e-01 -5.27174115e-01 -4.90840189e-02
-1.28237557e+00 6.21106088e-01 3.01876247e-01 5.63033581e-01
-6.45581663e-01 -4.10178415e-02 3.71407896e-01 3.75718296e-01
7.89842784e-01 9.07297075e-01 -7.53276527e-01 -3.60590577e-01
-1.50589609e+00 -2.17113703e-01 4.76342350e-01 7.52781749e-01
7.39872694e-01 3.95664394e-01 -2.66433686e-01 1.03430581e+00
-5.29748015e-02 3.03694665e-01 1.28615272e+00 -6.14021420e-01
1.99990973e-01 6.25626624e-01 -1.55735642e-01 -4.62133646e-01
-1.09572923e+00 -7.56915689e-01 -1.00830209e+00 -1.21898547e-01
-1.38739243e-01 -3.02281976e-01 -8.09384763e-01 1.73431933e+00
-5.23805976e-01 5.10254502e-01 1.08102456e-01 8.06327224e-01
1.09567797e+00 4.02787149e-01 -2.01612785e-02 -4.89387095e-01
1.18336999e+00 -6.93353593e-01 -1.01073265e+00 -6.11874759e-01
4.76596236e-01 -9.06585902e-02 1.11836123e+00 6.88048482e-01
-9.02439356e-01 -6.25379026e-01 -1.14224541e+00 2.18675837e-01
-2.42734596e-01 3.30487132e-01 7.02558339e-01 6.77188635e-01
-1.16933346e+00 5.11519492e-01 -1.23960662e+00 -2.89679050e-01
8.75514269e-01 1.01825249e+00 -5.53732276e-01 1.53499246e-01
-9.56052005e-01 8.42874169e-01 2.75576293e-01 9.68809798e-02
-1.05863202e+00 -8.37017477e-01 -7.54081011e-01 2.68075347e-01
-3.52047272e-02 -4.29185808e-01 8.74011517e-01 -1.05791056e+00
-1.32935119e+00 7.26963401e-01 -3.30478162e-01 -6.66483879e-01
-1.36435732e-01 -3.46627682e-01 -5.22455275e-01 1.08061634e-01
1.12286277e-01 5.97386658e-01 9.05883312e-01 -9.16087151e-01
-1.08507901e-01 -6.14892423e-01 -4.40641791e-01 7.28798186e-05
-6.44698083e-01 -1.16825551e-01 9.24328491e-02 -7.45410979e-01
-5.94797321e-02 -7.24252045e-01 -2.24290833e-01 -3.85200828e-01
-2.80481100e-01 -1.70442328e-01 4.70481873e-01 -3.72774780e-01
1.03863764e+00 -2.22268176e+00 1.56715676e-01 1.31668493e-01
6.41302407e-01 1.74761474e-01 -2.21298993e-01 -2.86702868e-02
-5.08903384e-01 -2.87016451e-01 -4.33055252e-01 -4.54286188e-01
-2.68245995e-01 2.19185442e-01 -3.01771641e-01 6.52159631e-01
2.38905579e-01 1.09759521e+00 -8.90913904e-01 -4.92884666e-02
1.58418998e-01 3.70010197e-01 -3.75685036e-01 3.54034275e-01
4.22178507e-01 7.16439426e-01 -1.13110334e-01 5.08754492e-01
2.77838945e-01 -3.18917185e-01 -8.40183720e-02 -2.51207352e-01
1.15902431e-01 4.28888738e-01 -8.26740742e-01 1.93944025e+00
-5.88203371e-01 8.65726233e-01 -2.47889191e-01 -1.32207716e+00
1.11217844e+00 3.69037777e-01 7.30903447e-01 -7.36217737e-01
2.85950005e-01 -3.03135812e-02 1.94765106e-01 -4.65842634e-01
-1.63157925e-01 -4.07223433e-01 1.35778055e-01 5.41199386e-01
7.56035507e-01 2.73122434e-02 -8.39986801e-02 -3.90321836e-02
1.39605975e+00 -1.63118094e-01 4.95458573e-01 -5.55074275e-01
2.21601978e-01 -4.49152321e-01 8.11028719e-01 7.26587355e-01
-2.15578690e-01 5.89221060e-01 3.36300433e-01 -3.92457813e-01
-2.88228154e-01 -9.47489560e-01 -4.15511996e-01 9.48752642e-01
-1.15109578e-01 -7.24667370e-01 -5.35397887e-01 -5.83240807e-01
-3.10847849e-01 6.97782218e-01 -7.92487025e-01 -6.95744514e-01
-1.94965690e-01 -1.38000882e+00 4.60527211e-01 1.04607272e+00
2.08824202e-01 -1.21526146e+00 -7.40326464e-01 2.47744322e-01
-2.77961027e-02 -1.09069800e+00 -7.94990659e-02 1.08832192e+00
-1.02168429e+00 -9.44862127e-01 -5.90804815e-01 -6.85076833e-01
7.05106437e-01 6.01718724e-02 9.28326368e-01 -1.84252053e-01
-4.41379011e-01 4.70592052e-01 -3.85075718e-01 -5.96896529e-01
2.63482869e-01 -7.56075084e-02 7.44114101e-01 2.76443571e-01
7.25712657e-01 -1.13546586e+00 -6.43920302e-01 2.89715111e-01
-5.80783665e-01 -1.00817263e-01 5.88650048e-01 1.18458807e+00
7.09488392e-01 -5.41140288e-02 1.27851236e+00 -7.67213047e-01
8.65694404e-01 -5.81838489e-01 -7.58066103e-02 -1.07273057e-01
-6.82137370e-01 1.89912040e-02 8.71353924e-01 -5.69962144e-01
-7.18101263e-01 -9.76910908e-03 -3.47956449e-01 -4.66007411e-01
-4.01775628e-01 2.62392789e-01 -5.63821867e-02 -6.97732251e-03
8.41410398e-01 5.16076982e-01 -2.36897752e-01 -4.14501607e-01
-8.11970830e-02 8.34221900e-01 4.47924823e-01 -3.19719821e-01
3.82947892e-01 3.53168160e-01 -2.00550333e-01 -9.36554790e-01
-9.26444650e-01 -7.18629360e-01 -7.89330006e-01 1.13134563e-01
7.85559833e-01 -1.09982550e+00 -4.16662663e-01 1.59731641e-01
-5.90574980e-01 -5.69532216e-01 -6.26503646e-01 9.78966177e-01
-7.30266094e-01 1.33719211e-02 -3.08128029e-01 -8.22208583e-01
-7.24810660e-01 -1.13413477e+00 1.10218740e+00 6.97582737e-02
-6.00806415e-01 -8.50891232e-01 2.45171547e-01 1.19755335e-01
3.90188694e-01 -1.12442404e-01 7.14313269e-01 -1.18290961e+00
2.23500341e-01 -8.15151930e-02 1.35753006e-01 6.20776236e-01
5.83452284e-01 -7.36852467e-01 -1.48298001e+00 -4.07924950e-01
4.26428288e-01 -7.75311291e-01 9.25298870e-01 4.83489424e-01
1.47259688e+00 -3.20282578e-02 -1.56859979e-01 9.02660489e-01
1.01716435e+00 2.04360291e-01 4.50256258e-01 7.44210035e-02
3.27748179e-01 2.69313037e-01 1.12891700e-02 4.16122675e-01
1.04510382e-01 3.60551625e-01 9.62558687e-02 -2.42331266e-01
-4.95500565e-02 1.45130605e-01 3.58496398e-01 1.08452797e+00
-1.80078059e-01 3.19304258e-01 -7.96314895e-01 3.61808717e-01
-1.67319274e+00 -6.58787012e-01 2.59871721e-01 2.05930686e+00
7.80323982e-01 1.47443101e-01 1.29875362e-01 5.02180755e-01
1.99184060e-01 -3.50998305e-02 -9.18944836e-01 -5.04465476e-02
-2.07364216e-01 1.01042104e+00 8.48162994e-02 -1.79528534e-01
-9.14346516e-01 6.23885810e-01 6.46946335e+00 5.06427407e-01
-1.21849024e+00 5.80325007e-01 5.57376444e-01 -5.99018037e-01
2.32490450e-01 -5.54478168e-01 -5.41293859e-01 6.77886844e-01
1.33138549e+00 -9.17239785e-02 6.08445466e-01 6.53731346e-01
5.05618274e-01 9.69947353e-02 -1.40998280e+00 1.63589990e+00
3.25526357e-01 -1.21866608e+00 -4.25308228e-01 -1.66627303e-01
5.96992433e-01 3.67765158e-01 -4.52003330e-02 5.99648356e-01
-1.32050127e-01 -1.24929523e+00 2.61777192e-01 5.02855361e-01
9.55032170e-01 -5.20772040e-01 9.19316709e-01 4.49698120e-01
-9.16393280e-01 -4.28083658e-01 -4.25322443e-01 -1.09662548e-01
-9.96904895e-02 5.66642284e-01 -5.79287112e-01 3.56655538e-01
9.22255039e-01 1.36071932e+00 -9.60102141e-01 1.07834721e+00
-3.05911422e-01 1.18554854e+00 -1.47149831e-01 9.45216045e-02
-2.82000680e-03 -2.68077906e-02 1.75911039e-01 1.21163690e+00
2.23881736e-01 2.37177446e-01 -1.47108987e-01 9.79263902e-01
-3.04380149e-01 6.49455190e-02 -4.69147295e-01 4.09852974e-02
2.62397259e-01 1.41430724e+00 -6.99383557e-01 -1.87898427e-01
-3.68694067e-01 9.92908001e-01 4.65259761e-01 4.33295786e-01
-3.99724841e-01 -2.25886375e-01 5.73033750e-01 -1.05451666e-01
-1.79124519e-01 5.11326157e-02 -5.69966078e-01 -1.47074080e+00
-1.23158306e-01 -7.38870144e-01 1.57168254e-01 -9.11769807e-01
-1.52971828e+00 9.85717595e-01 -7.49071985e-02 -1.16590905e+00
-4.44948785e-02 -6.46634758e-01 -8.45160604e-01 6.13792777e-01
-1.45928144e+00 -7.34011233e-01 -3.54730040e-01 1.00066221e+00
7.54559457e-01 -4.60932612e-01 1.23589897e+00 3.18581939e-01
-8.57318759e-01 5.71860552e-01 1.54724836e-01 -3.06234173e-02
8.21012676e-01 -1.28155875e+00 -7.65017718e-02 4.86464888e-01
6.24393344e-01 8.42780352e-01 2.33447060e-01 -2.77462423e-01
-1.30213165e+00 -1.17182481e+00 4.07805830e-01 -4.02390569e-01
5.61127067e-01 -7.53475547e-01 -9.53609884e-01 7.51388371e-01
1.09299846e-01 3.55616212e-01 1.45642960e+00 3.72970819e-01
-5.80059877e-03 -5.27894080e-01 -1.05248892e+00 1.20600134e-01
1.00100684e+00 -5.37535608e-01 -1.01423633e+00 4.56669450e-01
1.73291385e-01 -1.96404345e-02 -8.19401443e-01 3.40206444e-01
3.85698438e-01 -6.65700376e-01 7.07687497e-01 -7.64384031e-01
-7.02985525e-02 1.12180330e-01 -9.59215015e-02 -1.78685498e+00
-3.96398306e-01 -7.18749046e-01 -3.65806639e-01 8.56877089e-01
3.09198946e-01 -6.01199210e-01 6.07270718e-01 5.03478348e-01
-4.01971996e-01 -1.12506866e+00 -1.09771883e+00 -7.90019035e-01
-1.77034691e-01 -6.66995406e-01 4.54726875e-01 7.75207996e-01
5.32048404e-01 7.01322854e-01 -4.06136930e-01 -2.65967324e-02
3.77659023e-01 -9.97982025e-02 2.79008627e-01 -1.52707326e+00
-1.12159602e-01 -1.66102216e-01 -7.96083152e-01 -7.86821663e-01
6.16453767e-01 -1.27101529e+00 6.12758249e-02 -1.51168644e+00
3.70833635e-01 -2.42077723e-01 -1.01024270e+00 9.24809337e-01
-1.47113517e-01 5.51660120e-01 -9.22352150e-02 2.06460446e-01
-6.29559100e-01 7.98003793e-01 6.77841246e-01 -2.23391965e-01
-4.50228781e-01 1.51786610e-01 -9.66985881e-01 7.69792557e-01
1.06552505e+00 -5.45503199e-01 -6.06854022e-01 -1.21840850e-01
-1.48358390e-01 -1.81815654e-01 1.95905596e-01 -1.30877614e+00
1.21799611e-01 3.68403673e-01 9.22468841e-01 -1.46497816e-01
6.68459475e-01 -7.47594655e-01 -2.65084743e-01 1.40947893e-01
-5.07507980e-01 -5.37895523e-02 1.85988992e-01 5.86774468e-01
-3.31438035e-02 -4.24450450e-02 7.54789948e-01 -2.01463029e-02
-5.72282791e-01 2.09317014e-01 -6.56336069e-01 1.50952667e-01
8.44083011e-01 -2.72518635e-01 -7.73089975e-02 -3.42978567e-01
-1.10053253e+00 1.19542971e-01 -1.50900006e-01 3.39698702e-01
9.63320434e-01 -1.14585137e+00 -5.10464132e-01 8.11372757e-01
2.46459082e-01 -2.81571329e-01 4.36811149e-02 1.15623963e+00
2.80215800e-01 3.87829363e-01 -5.21799266e-01 -7.10981607e-01
-9.96907592e-01 3.75290245e-01 2.42132336e-01 -9.63198859e-03
-8.69796395e-01 8.51607978e-01 2.58114398e-01 -1.86887950e-01
3.89479667e-01 -5.66600561e-01 -4.70808744e-01 1.83707878e-01
8.11836004e-01 2.12414339e-01 6.53499246e-01 -5.54662406e-01
-4.63959128e-01 1.81054816e-01 1.86318858e-03 2.20296159e-01
1.93238211e+00 1.46099284e-01 1.41512472e-02 8.31626952e-01
1.15690827e+00 -3.10628146e-01 -1.20935667e+00 -9.79174450e-02
-3.17067169e-02 -4.92002964e-02 3.30994129e-01 -9.41180110e-01
-1.25901985e+00 1.10215867e+00 1.08032382e+00 -2.65102208e-01
1.37970567e+00 4.57441136e-02 5.10820687e-01 7.00250924e-01
5.96756756e-01 -8.64756167e-01 1.99215621e-01 2.09164117e-02
7.55514562e-01 -1.11750829e+00 5.32161482e-02 2.93776810e-01
-8.48711848e-01 1.12917483e+00 7.04953492e-01 -2.87938178e-01
7.67207503e-01 4.29347128e-01 -5.48569299e-02 -4.34650958e-01
-7.40015626e-01 -1.20830297e-01 3.79570425e-01 7.85774589e-01
3.72885764e-01 2.08525918e-02 -5.45534864e-02 1.63535857e+00
-3.10012996e-01 2.33868718e-01 3.89924228e-01 8.75293791e-01
-2.18066692e-01 -7.84396470e-01 -7.67151341e-02 1.29607058e+00
-4.85664189e-01 -3.60572010e-01 -2.48324424e-01 4.31968212e-01
2.05441818e-01 1.16112268e+00 1.89788956e-02 -5.93542278e-01
3.25871140e-01 3.97709340e-01 5.17833352e-01 -1.07492852e+00
-6.97724164e-01 1.25412107e-01 -2.53963351e-01 -6.99777842e-01
-6.50909722e-01 -4.37675297e-01 -1.24759901e+00 6.36738539e-01
-4.01696146e-01 2.92495072e-01 2.73613393e-01 1.04579782e+00
5.05990505e-01 8.47697973e-01 5.10581195e-01 -1.14769793e+00
-3.00245881e-01 -1.29705942e+00 -1.03015625e+00 2.28976160e-01
5.96876562e-01 -9.50193584e-01 -4.66608465e-01 1.50064573e-01] | [13.34559440612793, 3.520479202270508] |
a1bccc15-fa1f-46cc-8016-b565556dcd3e | over-the-air-gaussian-process-regression | 2210.02204 | null | https://arxiv.org/abs/2210.02204v2 | https://arxiv.org/pdf/2210.02204v2.pdf | Over-the-Air Gaussian Process Regression Based on Product of Experts | This paper proposes a distributed Gaussian process regression (GPR) with over-the-air computation, termed AirComp GPR, for communication- and computation-efficient data analysis over wireless networks. GPR is a non-parametric regression method that can model the target flexibly. However, its computational complexity and communication efficiency tend to be significant as the number of data increases. AirComp GPR focuses on that product-of-experts-based GPR approximates the exact GPR by a sum of values reported from distributed nodes. We introduce AirComp for the training and prediction steps to allow the nodes to transmit their local computation results simultaneously; the communication strategies are presented, including distributed training based on perfect and statistical channel state information cases. Applying to a radio map construction task, we demonstrate that AirComp GPR speeds up the computation time while maintaining the communication cost in training constant regardless of the numbers of data and nodes. | ['Koya Sato'] | 2022-10-05 | null | null | null | null | ['gpr', 'gpr'] | ['computer-vision', 'miscellaneous'] | [ 4.09882367e-02 2.64288992e-01 3.23407799e-01 -2.00894699e-01
-1.37241066e+00 4.55605499e-02 9.52341184e-02 2.64818668e-01
-3.87833148e-01 8.62913668e-01 -4.40102100e-01 -4.71150309e-01
-3.74851346e-01 -1.19398916e+00 -7.26543486e-01 -1.11191499e+00
-8.86769533e-01 1.02807784e+00 1.51671935e-02 2.41530418e-01
-1.98080719e-01 3.55492443e-01 -7.13377774e-01 -3.83203954e-01
6.30957603e-01 1.33814275e+00 5.26090145e-01 1.01380706e+00
1.79314151e-01 5.15704334e-01 -7.91298449e-01 -2.69047529e-01
4.92392592e-02 1.78026289e-01 -5.35234995e-02 -4.95728731e-01
-8.09106410e-01 -1.00466296e-01 -2.86091626e-01 6.43339515e-01
1.17467344e+00 9.96424407e-02 8.08011889e-01 -1.26066899e+00
-1.21875061e-02 7.74822712e-01 -8.86687398e-01 -2.24675775e-01
8.62985253e-02 -6.50477767e-01 4.22441572e-01 -9.63880479e-01
-1.64227650e-01 1.25408328e+00 1.38479698e+00 6.75142556e-02
-1.25595617e+00 -1.04218924e+00 -6.52977154e-02 -4.19239968e-01
-2.04403329e+00 -3.84415776e-01 3.92383933e-01 -1.49104640e-01
4.16593969e-01 1.74341634e-01 2.79673368e-01 8.72756362e-01
5.48555017e-01 3.65565538e-01 6.84350848e-01 -2.84307629e-01
8.34957898e-01 -1.40948057e-01 -2.48574093e-01 3.73129040e-01
2.44890690e-01 1.94229290e-01 -6.25387192e-01 -9.30203736e-01
8.63269985e-01 -1.12922862e-01 -1.81484833e-01 9.04125869e-02
-5.52209914e-01 7.21113145e-01 -2.30234712e-02 -1.92034587e-01
-1.12172472e+00 7.79695034e-01 5.82311936e-02 2.96283156e-01
8.93090129e-01 -1.26506329e-01 -9.26431298e-01 -3.19278389e-01
-1.19600642e+00 1.70284927e-01 1.27459037e+00 1.47013915e+00
8.15182805e-01 1.35988623e-01 -3.84499818e-01 5.75944364e-01
7.07696438e-01 1.19312763e+00 -2.11521551e-01 -7.39674509e-01
7.00692296e-01 -4.02917624e-01 3.81131291e-01 -1.11542177e+00
-5.92500627e-01 -6.96469545e-01 -1.32158303e+00 -2.84097314e-01
-1.13567606e-01 -1.10952687e+00 -4.45811570e-01 1.47517610e+00
2.59927660e-01 5.95390558e-01 3.27661932e-01 3.47649872e-01
1.28058702e-01 9.98988569e-01 1.96365222e-01 -3.99247676e-01
9.03801441e-01 -4.29532766e-01 -5.85260987e-01 -4.87919245e-03
6.68509662e-01 -4.19817269e-01 1.49307400e-01 6.53174043e-01
-1.28753912e+00 -5.04355848e-01 -8.10967445e-01 7.29598761e-01
1.46999523e-01 1.07666897e-02 5.89174151e-01 1.16780138e+00
-1.40640199e+00 5.86461425e-01 -1.14422965e+00 4.36895639e-02
4.19809610e-01 7.64583111e-01 1.67371839e-01 -3.56443495e-01
-1.09527755e+00 5.20360410e-01 -2.60923114e-02 5.02435327e-01
-1.09324896e+00 -9.14557934e-01 -5.60580552e-01 1.97281167e-01
-4.81681824e-02 -6.54466987e-01 1.27571118e+00 -1.99644208e-01
-1.59512293e+00 -1.66740581e-01 -4.85117137e-01 -5.70659757e-01
5.49487889e-01 -5.46160452e-02 -4.94384736e-01 -9.14792940e-02
-4.94523831e-02 1.73417538e-01 8.35232675e-01 -1.33356929e+00
-7.04962254e-01 -2.14921236e-01 -8.89219999e-01 1.58590347e-01
8.69407579e-02 -3.15672643e-02 -7.91610360e-01 -3.34475845e-01
3.79039317e-01 -8.24179053e-01 -1.07750487e+00 8.60741287e-02
-2.83036739e-01 1.58634689e-02 7.03971744e-01 -8.42843831e-01
9.81834352e-01 -1.97944570e+00 -3.93344641e-01 1.18986714e+00
1.65174112e-01 -5.43594956e-01 2.91114002e-01 6.84385955e-01
5.46032727e-01 1.33717254e-01 5.26001267e-02 -9.54990327e-01
-2.06656128e-01 3.65057528e-01 -1.10840462e-01 7.74728775e-01
-2.55069166e-01 4.10633266e-01 -8.16708803e-01 -6.14915073e-01
-2.52568245e-01 7.71930516e-01 -3.41576248e-01 2.99533576e-01
1.41219944e-01 7.20564365e-01 -8.97102594e-01 4.14964646e-01
1.11515439e+00 -1.93608850e-01 3.10474068e-01 6.31645918e-02
2.31164455e-01 -3.23553920e-01 -1.20824802e+00 1.43047214e+00
-1.08304453e+00 3.54080260e-01 6.87657893e-01 -9.89623964e-01
1.25288141e+00 7.48004675e-01 7.80538738e-01 -2.52153963e-01
1.43201068e-01 3.35500926e-01 -4.84532773e-01 1.83553360e-02
4.52491045e-01 -3.18954773e-02 -2.80647248e-01 2.76186079e-01
-2.29623720e-01 -8.09748545e-02 -3.71843040e-01 -7.20200092e-02
1.27921247e+00 -1.65038824e-01 1.99721888e-01 -2.78806597e-01
1.95832085e-02 -3.83504421e-01 4.79798287e-01 1.21034873e+00
3.67155015e-01 1.85888618e-01 1.78812385e-01 3.00649196e-01
-6.57078981e-01 -1.30359650e+00 -8.16356763e-02 1.19441271e+00
2.60966808e-01 -2.32591301e-01 -2.75695920e-01 1.01763122e-01
-6.16727571e-04 6.67752385e-01 -4.27810252e-01 2.58169621e-01
-8.57499912e-02 -1.08321595e+00 6.90856636e-01 4.50547427e-01
4.93082494e-01 -3.70041311e-01 -1.69430524e-01 6.09493852e-01
-4.05933931e-02 -1.27898586e+00 -2.47332156e-02 6.89473689e-01
-6.74424112e-01 -3.14608604e-01 -8.10592711e-01 -3.97938639e-01
8.42224121e-01 9.70480368e-02 7.37294376e-01 -3.31563950e-01
3.85885388e-01 4.67253536e-01 -2.05239326e-01 -7.78852403e-01
-2.86216289e-01 -3.98083963e-02 -9.65309963e-02 -8.85173306e-02
-2.58519441e-01 -1.06075132e+00 -3.65941852e-01 4.58992511e-01
-3.38738933e-02 1.85505487e-02 6.13316774e-01 4.88513172e-01
6.65413201e-01 7.40007639e-01 4.06158566e-01 -8.58916283e-01
7.97588944e-01 -1.05260324e+00 -5.61447144e-01 9.51512158e-02
-4.59564209e-01 -4.57147583e-02 5.59690356e-01 -4.35401320e-01
-1.01706219e+00 -9.70631838e-02 -6.38185143e-02 -1.89616799e-01
4.03122336e-01 7.65355825e-01 -7.72786736e-02 -4.57408041e-01
5.97703040e-01 1.31498098e-01 -2.89363384e-01 -1.85534179e-01
1.34245798e-01 6.80289984e-01 4.43854511e-01 -9.24742818e-01
8.65936339e-01 3.54984760e-01 5.66371381e-01 -9.95678604e-01
-3.77975941e-01 -5.03271520e-01 -6.45592213e-02 -1.87456250e-01
4.41535652e-01 -1.24346924e+00 -9.72735345e-01 1.34712830e-01
-1.29184163e+00 -5.13854027e-01 -5.41826934e-02 5.67826331e-01
-6.57702148e-01 1.67829305e-01 -5.26649594e-01 -1.47736549e+00
-6.04972303e-01 -6.08839929e-01 1.10737383e+00 -1.50983945e-01
6.12071157e-02 -1.20282423e+00 -1.45818844e-01 -4.94818181e-01
8.04450512e-01 2.15146795e-01 3.59077722e-01 -6.24394655e-01
-4.99673247e-01 -6.16943955e-01 -2.91707814e-01 -1.61755428e-01
-3.18832666e-01 -2.04571575e-01 -9.71505642e-01 -3.82750005e-01
8.28846882e-04 2.49721125e-01 1.18658483e-01 8.83867979e-01
1.59870017e+00 -2.29641810e-01 -9.18393612e-01 6.07809782e-01
1.48641181e+00 -7.41771907e-02 5.78588367e-01 -4.91894007e-01
2.82044798e-01 2.32987091e-01 6.59102499e-01 1.05769050e+00
4.34977531e-01 4.93066579e-01 3.81008267e-01 -4.27551776e-01
6.33023381e-01 -2.98623294e-01 2.89808810e-01 6.47963703e-01
-2.71773219e-01 -6.18817449e-01 -8.59048963e-01 6.66639656e-02
-1.89978111e+00 -6.24221206e-01 -3.40758204e-01 2.35132122e+00
5.22313058e-01 4.87034395e-02 -2.16609821e-01 2.57360488e-01
7.95937121e-01 -3.44332397e-01 -8.21965411e-02 -6.13934062e-02
3.71596783e-01 4.31075782e-01 1.49233484e+00 4.39609796e-01
-7.27310956e-01 2.52830118e-01 6.73726797e+00 1.24382603e+00
-7.60993838e-01 5.79612195e-01 6.32717788e-01 5.89997470e-01
-2.22449098e-02 -2.03286842e-01 -8.85528803e-01 5.42932510e-01
1.71593571e+00 -2.39010811e-01 1.99708030e-01 1.06830466e+00
7.07358599e-01 -3.06114018e-01 -8.91836822e-01 1.13989496e+00
-3.59482229e-01 -9.67109919e-01 -5.08817315e-01 2.27175087e-01
5.34257293e-01 4.23338234e-01 -7.10127950e-02 4.30937529e-01
9.18365300e-01 -1.12671971e+00 4.97119844e-01 7.11659193e-01
7.44351208e-01 -8.00612152e-01 1.07007015e+00 5.33460319e-01
-1.54665303e+00 -1.79507166e-01 -4.99453545e-01 1.18431345e-01
5.51542282e-01 9.36531126e-01 -1.14843345e+00 9.88470435e-01
6.30673707e-01 1.52189478e-01 1.85981132e-02 1.31317675e+00
1.91495970e-01 8.76573801e-01 -8.99347246e-01 -1.67834640e-01
-2.10609864e-02 -2.62402017e-02 2.48857170e-01 1.20260978e+00
1.10864425e+00 -5.42518571e-02 5.14202416e-01 4.34273869e-01
1.84997246e-01 -6.35343492e-02 -1.40690207e-01 6.90261066e-01
1.10944510e+00 1.13806820e+00 -4.26605195e-01 1.40887238e-02
-2.03915939e-01 6.16555572e-01 -7.10944384e-02 7.54917741e-01
-8.27697694e-01 -5.71375489e-02 1.89272836e-01 2.26633507e-04
3.57803077e-01 -6.50050938e-01 -3.65428805e-01 -3.62331979e-02
-3.22901577e-01 1.20089308e-03 -8.91452562e-03 -7.18048513e-01
-1.25886703e+00 3.59418631e-01 1.22436106e-01 -9.92018282e-01
-2.47185394e-01 -1.60855681e-01 -5.77978611e-01 1.18207896e+00
-1.39837122e+00 -1.22833180e+00 -5.40019274e-01 6.58039629e-01
9.96055678e-02 3.22200768e-02 1.18756843e+00 3.38292241e-01
-3.22555423e-01 6.13598108e-01 6.84257090e-01 -2.11992741e-01
1.50137037e-01 -8.92734706e-01 3.71436596e-01 3.38600397e-01
-4.16393101e-01 1.24748461e-01 1.13262033e+00 -5.82609713e-01
-1.19760573e+00 -1.31745720e+00 4.38049734e-01 -1.03969023e-01
5.44208646e-01 -4.28633779e-01 -4.83505160e-01 4.14816320e-01
-4.61840957e-01 2.14341879e-01 8.03681374e-01 4.06594008e-01
3.67768317e-01 -3.01385313e-01 -1.33326542e+00 3.90162379e-01
5.21284699e-01 -8.65596086e-02 5.47008812e-01 4.48987722e-01
5.22732496e-01 -3.81694674e-01 -1.18541718e+00 2.43615866e-01
3.42462212e-01 -1.06155716e-01 7.84020722e-01 4.07545507e-01
-5.27744889e-01 -1.00367956e-01 -5.02391577e-01 -1.20734406e+00
-9.32800472e-02 -1.18143809e+00 -2.88858712e-01 9.79259491e-01
7.93797135e-01 -7.09797978e-01 1.05724669e+00 5.92699289e-01
-2.31164936e-02 -6.06239200e-01 -1.20836306e+00 -6.30816519e-01
-3.00041676e-01 -1.16445673e+00 4.49478835e-01 2.01477036e-01
-2.14005768e-01 2.01488920e-02 -5.22676706e-01 9.35453117e-01
9.45960939e-01 -6.37448251e-01 1.07585311e+00 -1.51797140e+00
-6.47977173e-01 4.38287646e-01 -1.84793860e-01 -1.58439183e+00
-1.63860232e-01 -2.86964267e-01 4.47438836e-01 -1.45987940e+00
-2.29335427e-01 -1.37811530e+00 1.44243419e-01 9.83445719e-02
2.36418873e-01 -3.34550768e-01 -2.62371778e-01 3.07626218e-01
-6.72157824e-01 6.93043828e-01 8.06829870e-01 4.29681838e-01
-3.60926747e-01 1.08324230e+00 -5.12128115e-01 5.43292880e-01
9.74292576e-01 -8.60404730e-01 -5.82012415e-01 -2.05949843e-01
4.11529213e-01 7.57753491e-01 2.36909747e-01 -1.31847084e+00
6.28882945e-01 8.98644999e-02 4.79312152e-01 -9.47576106e-01
8.16972256e-01 -1.32724249e+00 6.00409031e-01 3.41256380e-01
-4.89041097e-02 1.49578946e-02 -5.77138960e-02 1.39504755e+00
2.06810743e-01 -6.63197925e-03 3.81509274e-01 3.94308507e-01
-2.28981823e-01 5.96361399e-01 -8.38108182e-01 -4.37014103e-01
1.04494429e+00 -1.60350367e-01 2.00536013e-01 -1.10366452e+00
-8.47827435e-01 5.94548941e-01 -2.66322464e-01 -5.39584875e-01
5.35390615e-01 -8.14772427e-01 -7.39955783e-01 -3.30730192e-02
-3.63174051e-01 4.68159258e-01 2.88429707e-01 1.03503573e+00
-3.28908116e-01 6.38441294e-02 5.76980948e-01 -7.12266266e-01
-9.85966325e-01 1.01258028e-02 4.84065294e-01 -6.90066576e-01
-4.14641917e-01 7.92867839e-01 -2.04031572e-01 -3.69816065e-01
4.84766364e-01 -2.60142416e-01 1.38053939e-01 -5.56880355e-01
2.43584186e-01 6.47120237e-01 -5.80798909e-02 1.29607499e-01
6.95767552e-02 3.27243626e-01 4.42490995e-01 -4.35003370e-01
1.13847160e+00 -6.19335175e-01 1.24010310e-01 3.63678455e-01
8.24699342e-01 -5.81388101e-02 -1.34796143e+00 -4.51797664e-01
-8.94404575e-03 -6.66373235e-05 2.08970308e-01 -3.98444921e-01
-9.14318681e-01 6.62352085e-01 4.84781414e-01 9.59003568e-02
1.03979766e+00 -7.29745105e-02 4.33577925e-01 5.04107356e-01
1.05434251e+00 -9.97534871e-01 -4.14981604e-01 3.27917844e-01
4.75920439e-01 -7.29378998e-01 8.66842717e-02 -7.67335176e-01
-3.24772328e-01 8.74824643e-01 7.40638748e-02 -6.30887516e-04
1.46695268e+00 9.31916475e-01 -5.96326768e-01 6.08235151e-02
-7.48324335e-01 2.47202784e-01 -4.24602836e-01 1.25268185e+00
6.13448806e-02 2.90267676e-01 5.03949635e-02 1.13084173e+00
-3.61025304e-01 -1.69984568e-02 2.53590524e-01 8.84963393e-01
-5.55332065e-01 -7.65587807e-01 -6.59800887e-01 6.92995965e-01
-5.51806211e-01 -2.85314381e-01 7.15086699e-01 5.57525635e-01
-2.32580498e-01 1.34704638e+00 2.28492782e-01 -2.18419209e-01
3.71142328e-02 -6.17170990e-01 7.35829324e-02 -4.16788697e-01
-1.77199781e-01 1.02519736e-01 5.19406796e-01 -2.36721739e-01
-1.94729596e-01 -3.93149406e-01 -1.32576358e+00 -7.58339584e-01
-4.26847488e-01 7.06460297e-01 1.14530873e+00 8.17730367e-01
2.56513000e-01 5.11619091e-01 9.46132064e-01 -1.15206754e+00
-8.13091874e-01 -1.05398667e+00 -1.02750146e+00 -8.19391072e-01
-2.38244142e-02 -4.91032690e-01 -3.30625623e-01 -3.77736777e-01] | [6.332211494445801, 1.2526854276657104] |
25493510-a0d1-44a9-9718-66738102ad53 | bootstrapping-meaning-through-listening | 2210.12857 | null | https://arxiv.org/abs/2210.12857v1 | https://arxiv.org/pdf/2210.12857v1.pdf | Bootstrapping meaning through listening: Unsupervised learning of spoken sentence embeddings | Inducing semantic representations directly from speech signals is a highly challenging task but has many useful applications in speech mining and spoken language understanding. This study tackles the unsupervised learning of semantic representations for spoken utterances. Through converting speech signals into hidden units generated from acoustic unit discovery, we propose WavEmbed, a multimodal sequential autoencoder that predicts hidden units from a dense representation of speech. Secondly, we also propose S-HuBERT to induce meaning through knowledge distillation, in which a sentence embedding model is first trained on hidden units and passes its knowledge to a speech encoder through contrastive learning. The best performing model achieves a moderate correlation (0.5~0.6) with human judgments, without relying on any labels or transcriptions. Furthermore, these models can also be easily extended to leverage textual transcriptions of speech to learn much better speech embeddings that are strongly correlated with human annotations. Our proposed methods are applicable to the development of purely data-driven systems for speech mining, indexing and search. | ['Chia-wen Lo', 'Cong Zhang', 'Yadong Liu', 'Zuoyu Tian', 'Jian Zhu'] | 2022-10-23 | null | null | null | null | ['sentence-embeddings', 'sentence-embeddings', 'spoken-language-understanding', 'spoken-language-understanding', 'acoustic-unit-discovery'] | ['methodology', 'natural-language-processing', 'natural-language-processing', 'speech', 'speech'] | [ 3.73332381e-01 8.84180248e-01 -1.44497871e-01 -9.15815175e-01
-6.15473509e-01 -2.69143015e-01 7.64237404e-01 4.05266732e-02
-4.09188449e-01 4.81463224e-01 6.79171264e-01 -2.86513060e-01
2.31364682e-01 -6.03265345e-01 -6.69077039e-01 -5.45272768e-01
6.23483993e-02 6.06105208e-01 -9.58915353e-02 -1.83874562e-01
-1.44604594e-01 2.16718670e-02 -1.67625821e+00 5.10237515e-01
3.78720284e-01 9.34925497e-01 3.90632033e-01 9.38116670e-01
-4.89520907e-01 9.48114574e-01 -6.58443213e-01 -6.20442145e-02
-3.55867893e-01 -5.35697699e-01 -1.14623463e+00 2.26948425e-01
-1.01455837e-01 -7.67721534e-02 -3.60124081e-01 9.29486096e-01
4.25335228e-01 3.72921675e-01 7.39909887e-01 -1.06645310e+00
-8.99283886e-01 9.44173992e-01 1.48208141e-01 5.68864904e-02
4.41057086e-01 -2.54308224e-01 1.31083691e+00 -1.01956642e+00
2.30100006e-01 1.49126112e+00 9.52265412e-02 7.99565077e-01
-1.03766704e+00 -3.96875292e-01 4.26567756e-02 3.20202976e-01
-1.25424719e+00 -9.65553641e-01 7.15608418e-01 -2.61390835e-01
1.37583423e+00 3.28986824e-01 1.20390899e-01 1.31390500e+00
-5.68158269e-01 9.93948936e-01 6.93067372e-01 -7.19599962e-01
5.35576522e-01 5.54812610e-01 9.00064036e-02 6.23553216e-01
-5.82415223e-01 -2.75274310e-02 -7.23387301e-01 -4.00503129e-02
3.03002536e-01 4.52389382e-02 -2.91616857e-01 8.80129784e-02
-1.19730043e+00 1.21108210e+00 5.13511002e-01 4.17970061e-01
-4.73489702e-01 3.66728604e-02 2.72730321e-01 4.68982220e-01
6.01851463e-01 4.60550010e-01 -5.45374453e-01 -2.43180811e-01
-9.97566819e-01 -1.78844377e-01 1.05035412e+00 8.71317923e-01
7.69853175e-01 3.25088024e-01 -3.34661305e-02 1.14637792e+00
5.68004131e-01 5.34053326e-01 9.17321384e-01 -7.86431193e-01
2.41737857e-01 4.20347840e-01 -3.06534469e-01 -6.31918371e-01
-2.66671479e-01 -3.24126147e-02 -5.72199225e-01 -2.68580079e-01
-2.03858703e-01 -2.11899579e-01 -9.14454818e-01 1.63716257e+00
1.37747779e-01 3.02341044e-01 7.08443820e-01 9.37399387e-01
1.13023150e+00 1.02134061e+00 3.54962200e-02 -9.43875238e-02
1.51088369e+00 -1.06346262e+00 -8.09359133e-01 -3.57380867e-01
6.11901999e-01 -4.58384931e-01 1.10038686e+00 1.60000369e-01
-8.66151273e-01 -5.23272097e-01 -8.56779337e-01 -1.14371419e-01
-6.82716608e-01 1.39674529e-01 3.39640319e-01 4.89268839e-01
-1.11326921e+00 1.58380166e-01 -7.58369803e-01 -5.91609061e-01
3.05347532e-01 3.05131525e-01 -3.24815542e-01 2.63843775e-01
-1.34567356e+00 8.01092923e-01 6.89319193e-01 -1.26380190e-01
-1.06390536e+00 -2.05971062e-01 -1.20279944e+00 2.50389546e-01
3.02697062e-01 -5.73106825e-01 1.46356726e+00 -1.02918625e+00
-1.96775019e+00 7.59818971e-01 -5.41585624e-01 -8.52925241e-01
-4.30950195e-01 -3.40774510e-04 -5.28684199e-01 1.79110259e-01
-6.09396473e-02 8.48854601e-01 1.11009264e+00 -9.78671551e-01
-3.79574835e-01 -1.96604922e-01 -6.16981871e-02 2.06811666e-01
-7.54544377e-01 9.13810043e-04 -2.29560360e-01 -5.77089250e-01
-4.88011464e-02 -7.70921111e-01 -1.87214330e-01 -4.96991575e-01
-5.50198078e-01 -6.78365529e-01 7.61828661e-01 -5.53203046e-01
9.75566924e-01 -2.12399220e+00 3.95661652e-01 2.15556517e-01
1.31326661e-01 2.11221859e-01 -3.35419863e-01 4.78932559e-01
7.79572502e-02 -7.09847957e-02 -2.13818893e-01 -6.25958979e-01
2.70110607e-01 7.20618546e-01 -7.66061485e-01 -9.13663059e-02
4.77558106e-01 9.90250587e-01 -8.77829671e-01 -1.51647404e-01
2.03193173e-01 5.81916571e-01 -5.61346173e-01 5.70789099e-01
-3.36780697e-01 3.25866044e-01 -2.31369019e-01 2.43869647e-01
-4.64597158e-03 -2.92409241e-01 1.92893535e-01 9.41932052e-02
9.49715357e-03 7.62643516e-01 -7.01646566e-01 1.83657777e+00
-7.65506089e-01 7.09673464e-01 -3.72691974e-02 -1.53429651e+00
1.19060588e+00 7.54971623e-01 2.28953641e-02 -5.05257845e-01
1.04449771e-01 -9.08523053e-03 -2.89814860e-01 -6.93237603e-01
4.08698887e-01 -4.07094330e-01 -1.64279282e-01 5.82782507e-01
6.33960962e-01 -1.86135769e-01 -2.89462745e-01 1.04611650e-01
1.07478988e+00 -4.71506894e-01 1.14372276e-01 2.83676069e-02
6.47015870e-01 -2.23301500e-01 1.88044146e-01 5.31512976e-01
1.25545934e-01 4.98522311e-01 2.77453512e-01 -2.75656551e-01
-8.77476990e-01 -1.14009726e+00 1.14517212e-02 1.56891930e+00
-3.39327097e-01 -5.01999378e-01 -8.56076837e-01 -6.09850049e-01
-1.47243991e-01 9.63750243e-01 -5.79092026e-01 -3.76116753e-01
-4.20091823e-02 -2.59006530e-01 8.54018867e-01 6.77045763e-01
-4.24742699e-03 -1.41681075e+00 -1.97737470e-01 1.56276539e-01
-1.75365821e-01 -1.45215619e+00 -1.75373942e-01 4.41776752e-01
-5.54129839e-01 -5.47425508e-01 -7.24007487e-01 -1.05254900e+00
5.65298021e-01 -9.28063169e-02 9.59905624e-01 -1.22936063e-01
-4.96079773e-02 5.61487436e-01 -7.63082683e-01 -6.33834243e-01
-7.65797675e-01 2.24713728e-01 4.60969448e-01 3.63310188e-01
8.68514478e-01 -4.10291016e-01 -2.13315472e-01 1.28464922e-01
-8.53897393e-01 -1.08854696e-01 6.69464350e-01 9.29654479e-01
3.53274047e-01 -1.92127571e-01 9.02518690e-01 -6.50009453e-01
7.03331351e-01 -5.83925545e-01 -1.47057712e-01 1.62221659e-02
-3.62720877e-01 4.66008633e-01 5.03808677e-01 -2.54482180e-01
-1.01221144e+00 3.94795500e-02 -3.88632149e-01 -5.10854900e-01
-7.42191374e-01 4.88010377e-01 -2.91532818e-02 5.76051474e-01
4.19712037e-01 4.56221491e-01 2.42410928e-01 -6.27931952e-01
8.87147784e-01 1.23754430e+00 5.17956793e-01 -2.57735252e-01
4.33082134e-01 3.40030253e-01 -7.73044407e-01 -1.55317307e+00
-9.44287896e-01 -6.34335756e-01 -5.99839270e-01 3.07693899e-01
1.32509124e+00 -8.57096076e-01 -5.57745576e-01 -2.14904830e-01
-1.37362611e+00 -1.53397754e-01 -3.70345265e-01 7.38457382e-01
-6.56548083e-01 1.50270954e-01 -5.96373320e-01 -9.69214439e-01
-4.34196383e-01 -8.53667915e-01 1.28435564e+00 4.35223021e-02
-5.81129730e-01 -1.08337772e+00 2.36739621e-01 6.41700804e-01
4.27940041e-01 -5.17380655e-01 8.08628798e-01 -1.34640992e+00
-9.78059471e-02 -6.22742018e-03 2.53281964e-04 7.68087566e-01
2.60729700e-01 -4.57080811e-01 -1.61460209e+00 -1.72233865e-01
-4.94896062e-02 -8.17337811e-01 9.47789490e-01 1.91756755e-01
1.10881937e+00 -6.75442457e-01 -1.62901208e-01 1.98802799e-01
6.01144016e-01 3.02011609e-01 3.51068616e-01 -3.88548858e-02
5.14395773e-01 1.03883958e+00 1.73548535e-02 3.06827873e-01
4.09533232e-01 5.26873231e-01 1.26335368e-01 -3.11968736e-02
-1.23942615e-02 -3.39969039e-01 7.18490779e-01 1.60527527e+00
2.00893030e-01 -1.21342368e-01 -8.30790818e-01 6.79641247e-01
-1.61732388e+00 -8.75347793e-01 4.07927811e-01 1.86600018e+00
9.95771050e-01 -8.84407200e-03 -1.00624748e-01 1.55672282e-01
4.35018867e-01 2.46447265e-01 -2.33158946e-01 -6.21854246e-01
1.09909333e-01 5.74225008e-01 -1.31799087e-01 6.85838580e-01
-1.02667940e+00 1.24297690e+00 6.16974831e+00 5.47198653e-01
-9.84844983e-01 3.85339260e-01 3.86182487e-01 -2.98840459e-02
-3.76628846e-01 -8.43506530e-02 -6.83031917e-01 3.80237401e-01
1.58730626e+00 -1.37144998e-02 3.41448039e-01 8.93507183e-01
2.61739403e-01 4.25907880e-01 -1.28305507e+00 1.01723957e+00
3.59154642e-01 -1.20103157e+00 2.34987691e-01 -8.41095075e-02
4.95409191e-01 2.00827777e-01 1.65368374e-02 6.56277597e-01
3.51407707e-01 -1.29508901e+00 3.10142696e-01 4.17027324e-01
5.73052704e-01 -6.83798611e-01 7.14006782e-01 5.73540688e-01
-9.09786999e-01 1.33502394e-01 -5.75106382e-01 -1.90341175e-01
2.93376476e-01 4.10301507e-01 -1.66335535e+00 2.27642670e-01
5.37458956e-01 5.69950581e-01 -9.77629125e-02 1.87626079e-01
-4.61053461e-01 1.03201795e+00 -1.85543299e-01 -3.79268765e-01
3.95705879e-01 1.88888833e-01 3.38116497e-01 1.50474775e+00
1.89742461e-01 -3.78074050e-02 2.81608254e-01 1.05932546e+00
-2.11961672e-01 2.19469994e-01 -9.62874174e-01 -5.89429677e-01
4.89720047e-01 1.00414670e+00 -2.94594049e-01 -7.25251436e-01
-5.84985971e-01 1.17388594e+00 2.53795922e-01 5.43538153e-01
-4.26388383e-01 -5.00742018e-01 8.12380493e-01 -1.73846185e-01
4.00991082e-01 -1.73232555e-01 1.64945766e-01 -1.19477475e+00
-2.22871825e-01 -6.32974684e-01 1.09665796e-01 -8.01120698e-01
-1.37314987e+00 1.01684546e+00 -1.95845053e-01 -9.14928198e-01
-9.47295070e-01 -6.80364907e-01 -7.01261699e-01 7.82467067e-01
-1.51046145e+00 -9.06450868e-01 4.13733758e-02 6.32462800e-01
1.06976628e+00 -7.07536101e-01 1.46510053e+00 3.55686583e-02
-3.39236110e-01 4.38650221e-01 -1.93862513e-01 4.30483907e-01
4.46975112e-01 -1.27266395e+00 4.86337870e-01 3.24833393e-01
9.44549084e-01 5.62715948e-01 5.01175761e-01 -1.28492221e-01
-1.15621400e+00 -1.09047651e+00 1.30304193e+00 -4.97670084e-01
8.32194924e-01 -6.35442019e-01 -1.12573004e+00 6.87745035e-01
4.79878426e-01 -1.96616635e-01 1.16957498e+00 3.85985196e-01
-3.88874918e-01 7.67714605e-02 -5.23260534e-01 2.59509504e-01
6.62886739e-01 -1.24282002e+00 -1.24659765e+00 2.84540206e-01
1.20773637e+00 1.03168771e-01 -8.41735244e-01 8.89397413e-02
1.84565932e-01 -4.38636184e-01 8.80328774e-01 -9.22966480e-01
2.26030275e-01 -6.29564151e-02 -4.50156569e-01 -1.43962097e+00
9.57318321e-02 -4.02840912e-01 -2.14552164e-01 1.22714496e+00
8.02831531e-01 -4.87743199e-01 6.85869277e-01 2.68323809e-01
-2.54383922e-01 -4.96896446e-01 -9.81660128e-01 -6.79643691e-01
-9.53807756e-02 -7.49938428e-01 4.62357700e-01 1.15618122e+00
3.87324810e-01 9.21411037e-01 -2.83686906e-01 3.12971443e-01
3.26479405e-01 -2.91679446e-02 7.20541120e-01 -1.12841725e+00
-5.08240223e-01 -1.57390207e-01 -5.85671782e-01 -1.47562706e+00
7.53169119e-01 -1.28956866e+00 3.94350559e-01 -1.33644235e+00
-1.11300573e-01 4.36485372e-02 -4.06988770e-01 7.71329880e-01
1.58138379e-01 1.66981872e-02 -3.35520171e-02 5.64924367e-02
-6.22633219e-01 1.15263462e+00 6.50865734e-01 -3.64768833e-01
-2.20427290e-01 -5.50942197e-02 -5.14904141e-01 8.23932588e-01
7.93329000e-01 -3.96810353e-01 -6.51550233e-01 -4.45711315e-01
-1.32568598e-01 2.82939170e-02 3.02236378e-01 -6.95477486e-01
4.27795559e-01 1.94849417e-01 -1.18809037e-01 -2.71851391e-01
6.12339079e-01 -5.90804279e-01 -6.04556322e-01 5.23358062e-02
-7.28643000e-01 -3.03853542e-01 2.60262582e-02 5.53614497e-01
-8.09433877e-01 -3.69460315e-01 2.78859317e-01 -6.45997375e-02
-8.98879111e-01 -3.63661610e-02 -6.79324865e-01 -6.98306113e-02
4.54663575e-01 1.63647830e-01 4.81860004e-02 -7.03782201e-01
-1.25981927e+00 1.08431049e-01 -2.54548997e-01 9.34900343e-01
1.01530778e+00 -1.49092853e+00 -6.72386706e-01 6.06081367e-01
4.02035147e-01 -7.48019814e-02 -1.58095285e-01 5.62091410e-01
1.80305406e-01 7.27810562e-01 3.65253866e-01 -7.69232869e-01
-1.04473364e+00 2.80454546e-01 -5.38604148e-02 3.58761728e-01
-4.39751536e-01 9.77013826e-01 3.91560733e-01 -8.26049984e-01
5.29439867e-01 -5.67006230e-01 -3.03847015e-01 6.98177293e-02
8.20121706e-01 -8.26052856e-03 4.01743725e-02 -7.42121339e-01
-3.73014539e-01 1.36051670e-01 2.95653958e-02 -4.63288188e-01
1.37373614e+00 -1.90998644e-01 5.38384216e-03 7.62958646e-01
1.50905979e+00 -3.74201477e-01 -8.78828883e-01 -4.44962770e-01
4.09372449e-01 2.08113521e-01 2.21219599e-01 -5.14463723e-01
-7.91234672e-01 1.12581885e+00 2.72940636e-01 3.48127753e-01
7.34365702e-01 7.56068587e-01 9.07646477e-01 9.19513345e-01
2.02483851e-02 -1.15566516e+00 3.76442552e-01 8.23369563e-01
8.61865520e-01 -1.48502040e+00 -7.62213826e-01 -8.44846386e-03
-9.44838703e-01 1.10622275e+00 2.26610810e-01 1.87269643e-01
7.18383610e-01 2.58824348e-01 2.39990115e-01 -4.24277216e-01
-1.00367355e+00 -5.79243720e-01 4.93221998e-01 5.23386657e-01
5.80395937e-01 2.79809475e-01 2.68207312e-01 8.70484471e-01
-4.61779684e-01 -2.61027187e-01 1.00278951e-01 6.22389317e-01
-8.09365153e-01 -1.08296275e+00 -1.81335717e-01 1.54126272e-01
-1.65924728e-01 -3.64545435e-01 -6.38267875e-01 1.06536224e-01
-1.93845883e-01 1.17935133e+00 4.09101844e-01 -5.80177665e-01
3.58955204e-01 6.49267316e-01 -6.74218312e-02 -1.19727457e+00
-6.23022653e-02 1.33996502e-01 1.82549715e-01 -3.90428454e-01
-5.34137249e-01 -2.69331157e-01 -1.53183615e+00 3.14558178e-01
-2.03660160e-01 6.88141763e-01 8.53457630e-01 1.07237291e+00
3.56137574e-01 5.27201235e-01 7.05736816e-01 -7.26286173e-01
-6.06139541e-01 -1.33990872e+00 -4.91953552e-01 4.02125001e-01
4.18509901e-01 -4.06737298e-01 -5.27999341e-01 4.24135566e-01] | [14.06570053100586, 6.894286155700684] |
9d69651a-c5db-49a6-ba86-f990e9a60d5b | translation-enhanced-multilingual-text-to | 2305.19216 | null | https://arxiv.org/abs/2305.19216v1 | https://arxiv.org/pdf/2305.19216v1.pdf | Translation-Enhanced Multilingual Text-to-Image Generation | Research on text-to-image generation (TTI) still predominantly focuses on the English language due to the lack of annotated image-caption data in other languages; in the long run, this might widen inequitable access to TTI technology. In this work, we thus investigate multilingual TTI (termed mTTI) and the current potential of neural machine translation (NMT) to bootstrap mTTI systems. We provide two key contributions. 1) Relying on a multilingual multi-modal encoder, we provide a systematic empirical study of standard methods used in cross-lingual NLP when applied to mTTI: Translate Train, Translate Test, and Zero-Shot Transfer. 2) We propose Ensemble Adapter (EnsAd), a novel parameter-efficient approach that learns to weigh and consolidate the multilingual text knowledge within the mTTI framework, mitigating the language gap and thus improving mTTI performance. Our evaluations on standard mTTI datasets COCO-CN, Multi30K Task2, and LAION-5B demonstrate the potential of translation-enhanced mTTI systems and also validate the benefits of the proposed EnsAd which derives consistent gains across all datasets. Further investigations on model variants, ablation studies, and qualitative analyses provide additional insights on the inner workings of the proposed mTTI approaches. | ['Anna Korhonen', 'Ivan Vulić', 'Stephen Rawls', 'Ching-Yun Chang', 'Yaoyiran Li'] | 2023-05-30 | null | null | null | null | ['nmt', 'crosslingual-text-to-image-generation', 'multilingual-text-to-image-generation', 'cross-lingual-text-to-image-generation', 'multi-lingual-text-to-image-generation'] | ['computer-code', 'computer-vision', 'computer-vision', 'natural-language-processing', 'natural-language-processing'] | [ 4.35555369e-01 1.45635903e-01 -1.57769978e-01 -1.37876496e-01
-1.28294671e+00 -6.24562144e-01 1.15849245e+00 -6.87566757e-01
-3.12606901e-01 9.18694258e-01 5.39229214e-01 -5.76056242e-01
1.81806341e-01 -4.69219804e-01 -1.00025356e+00 -4.55504566e-01
4.23925459e-01 6.66532576e-01 -3.06186080e-01 -2.63587266e-01
-1.57435700e-01 -6.91074431e-02 -1.19470060e+00 5.15473723e-01
1.18636775e+00 7.92012393e-01 2.71607608e-01 5.10294795e-01
-9.52852070e-02 8.56359601e-01 -7.53698051e-01 -8.34715426e-01
2.71550685e-01 -6.34112835e-01 -8.24854076e-01 -1.02305442e-01
6.46160126e-01 -3.48228395e-01 -3.47883403e-01 5.84322155e-01
8.22127581e-01 -3.45253795e-01 8.69981945e-01 -1.46088111e+00
-1.25436091e+00 8.74523401e-01 -4.01888341e-01 -8.56602972e-04
1.28695264e-01 4.27970469e-01 8.58354330e-01 -1.10190797e+00
1.00625372e+00 1.22314084e+00 6.15281999e-01 5.36202133e-01
-1.05527222e+00 -7.21974313e-01 -2.49366388e-01 2.69578218e-01
-1.32554543e+00 -6.18653715e-01 2.27680579e-01 -3.69188219e-01
1.13256586e+00 1.49655074e-01 3.73755306e-01 1.59783816e+00
2.91027904e-01 1.28364944e+00 1.56001782e+00 -6.85797393e-01
-3.91413808e-01 2.96777129e-01 -3.61676902e-01 4.27795380e-01
-1.02709725e-01 3.94202143e-01 -8.79345894e-01 4.55869377e-01
3.45143020e-01 -8.28357458e-01 -2.69796312e-01 1.24222375e-01
-1.71293068e+00 7.93524384e-01 2.47339293e-01 3.30271959e-01
-1.53883189e-01 2.17617989e-01 6.09355450e-01 5.15044808e-01
7.43605852e-01 4.86879855e-01 -2.54606366e-01 -2.49420017e-01
-8.61086726e-01 4.21066768e-02 4.64641690e-01 1.23765278e+00
6.41518831e-01 1.67416707e-01 -7.43761003e-01 8.92017961e-01
-1.06660157e-01 1.00091398e+00 5.44543982e-01 -7.60779262e-01
9.41904485e-01 1.80440485e-01 -2.07335487e-01 -3.36594075e-01
-4.13218774e-02 -4.80752707e-01 -8.49483430e-01 -8.38144794e-02
2.14633420e-01 -1.34758681e-01 -9.98577833e-01 1.86526334e+00
-7.30057806e-02 2.81502362e-02 4.02361661e-01 6.71674788e-01
8.12396765e-01 8.99227321e-01 2.10399091e-01 1.66383132e-01
1.16309762e+00 -1.25424218e+00 -6.10754848e-01 -2.98393071e-01
8.82828236e-01 -1.06920028e+00 1.37332010e+00 4.84873482e-04
-1.03418803e+00 -6.33972585e-01 -8.94387662e-01 -1.90609589e-01
-4.68407065e-01 6.07560456e-01 5.05449235e-01 5.42217731e-01
-1.29133058e+00 3.27743217e-02 -3.47014576e-01 -5.38062871e-01
2.76122332e-01 1.20107539e-01 -3.04661572e-01 -4.04152393e-01
-1.42281771e+00 1.27912664e+00 4.74850088e-01 2.49051034e-01
-1.07063162e+00 -7.97723055e-01 -8.05033088e-01 -2.40130588e-01
2.41693944e-01 -9.26731646e-01 1.20607245e+00 -1.24637663e+00
-1.50515449e+00 8.60352337e-01 -1.30318716e-01 -6.59085631e-01
5.69372177e-01 -1.82715371e-01 -2.10003674e-01 -8.40805750e-03
4.26254719e-01 1.33730793e+00 7.16725707e-01 -1.19458246e+00
-4.60529715e-01 -8.73875022e-02 -3.93063165e-02 6.25496686e-01
-3.50076199e-01 2.48733573e-02 -5.34932792e-01 -6.51226044e-01
-6.50895178e-01 -1.30428457e+00 2.16048270e-01 -4.79604989e-01
-4.70059663e-01 -8.56865197e-02 6.70221984e-01 -9.81919348e-01
1.06740618e+00 -2.10290766e+00 2.97900289e-01 -2.74017632e-01
-2.01230839e-01 3.05816531e-01 -6.07650518e-01 5.53853333e-01
7.07915798e-02 1.60966709e-01 -1.20193005e-01 -4.27953094e-01
1.58916172e-02 3.69802028e-01 -3.36536020e-01 -4.74494211e-02
3.02291602e-01 1.67451715e+00 -7.05720782e-01 -6.21952057e-01
2.30501443e-01 3.45821828e-01 -2.65685767e-01 5.87869473e-02
-1.40608147e-01 7.49409974e-01 -8.44185948e-02 5.32591939e-01
2.98236936e-01 -2.15791091e-01 -7.36378357e-02 -6.10881209e-01
-2.89101630e-01 1.81648999e-01 -3.52950126e-01 2.01720047e+00
-9.56121802e-01 8.36693585e-01 -3.84529054e-01 -8.57110381e-01
4.67077225e-01 5.59065461e-01 2.51306623e-01 -1.30908203e+00
-3.96889485e-02 4.35219198e-01 -8.12267512e-02 -3.52343738e-01
5.58515370e-01 -4.80187647e-02 -3.28794390e-01 4.86789554e-01
4.27950025e-01 -8.83230194e-02 3.88985872e-01 3.85359615e-01
6.44892633e-01 5.58131754e-01 -1.46957987e-03 -1.53163254e-01
3.87391120e-01 2.23432243e-01 1.29762843e-01 8.27359617e-01
-6.90675080e-02 5.85130274e-01 3.22270580e-02 -1.52664647e-01
-1.30539513e+00 -1.13016725e+00 5.82820736e-02 1.03752089e+00
-2.27685243e-01 -7.32132047e-02 -9.46590424e-01 -6.91590309e-01
-4.85983014e-01 1.04231262e+00 -6.21478260e-01 -2.25545093e-01
-4.64543283e-01 -9.36635494e-01 9.19802904e-01 4.74609852e-01
7.52441049e-01 -1.18145430e+00 -2.80731648e-01 7.42297471e-02
-1.07934427e+00 -1.38767099e+00 -7.97713399e-01 -1.47196069e-01
-4.33886051e-01 -3.93435150e-01 -1.07755876e+00 -7.31005430e-01
3.51923913e-01 3.55455905e-01 1.46245861e+00 -4.53910768e-01
-2.02107131e-01 5.95562220e-01 -4.41939831e-01 -4.41046923e-01
-1.00062335e+00 5.43197215e-01 -2.77731717e-01 -1.00336693e-01
-5.54603571e-03 -1.69922307e-01 -3.90766948e-01 2.45074227e-01
-7.42186785e-01 7.74287760e-01 1.08383024e+00 9.24871504e-01
4.63999867e-01 -4.64415371e-01 7.94004858e-01 -6.13965452e-01
5.63440442e-01 -3.67378473e-01 -3.12688261e-01 8.14256191e-01
-6.15161657e-01 1.40371352e-01 2.91200697e-01 -4.34718251e-01
-1.51481390e+00 -3.85175079e-01 -5.98965995e-02 -2.28257775e-01
8.73586908e-02 7.63828278e-01 -1.04488961e-01 -1.13225719e-02
5.40561497e-01 5.81316113e-01 -1.23868972e-01 -1.18549459e-01
8.49012077e-01 7.37028003e-01 6.62546158e-01 -7.80277133e-01
6.51302516e-01 2.17876762e-01 -3.55121464e-01 -7.16349721e-01
-9.44367230e-01 -2.06039455e-02 -5.11939347e-01 -4.48653311e-01
1.08383822e+00 -1.27106059e+00 -1.36862487e-01 5.91505647e-01
-1.10827446e+00 -7.50893474e-01 -2.52516448e-01 3.16841930e-01
-7.39730835e-01 1.68422967e-01 -6.67900026e-01 -3.68132055e-01
-8.44525993e-01 -1.37867570e+00 1.36926496e+00 -1.20720170e-01
-7.37273917e-02 -9.68953848e-01 2.01982871e-01 8.88725460e-01
5.96311092e-01 -1.83796491e-02 1.03071535e+00 -3.19854349e-01
-6.41789556e-01 2.50565171e-01 -5.37474215e-01 5.27224064e-01
-1.55327037e-01 -2.30268061e-01 -9.81503725e-01 -3.26905638e-01
-5.41965008e-01 -8.40384126e-01 5.69693089e-01 3.48452508e-01
5.80720842e-01 -3.50190818e-01 -1.09194279e-01 5.11122525e-01
1.35023236e+00 1.73720419e-02 7.97714591e-01 4.42587852e-01
8.13100755e-01 5.43790519e-01 5.50948918e-01 -5.92324995e-02
8.69514585e-01 8.65572393e-01 2.10396163e-02 -3.56006354e-01
-8.89159381e-01 -4.46307838e-01 6.80010796e-01 1.42727339e+00
2.08095182e-03 -5.08484721e-01 -8.52163732e-01 7.92042434e-01
-1.58900714e+00 -7.41633832e-01 -2.93268841e-02 2.09482098e+00
1.04613519e+00 -2.40862027e-01 -2.21410364e-01 -3.81259710e-01
4.03532147e-01 -2.22853974e-01 -2.80967832e-01 -3.82286638e-01
-4.91687804e-01 2.35014662e-01 6.59384370e-01 2.62893677e-01
-8.09387207e-01 1.29660058e+00 6.07177162e+00 1.20792747e+00
-1.18285966e+00 6.01127744e-01 8.69567811e-01 9.24719591e-03
-3.01340848e-01 -4.17693406e-02 -7.32395053e-01 2.85980493e-01
1.31011760e+00 -2.15279326e-01 7.05494523e-01 3.97029996e-01
1.78038552e-01 1.03764713e-01 -1.02815175e+00 7.73530543e-01
3.07877272e-01 -1.41273582e+00 3.91326904e-01 2.45018378e-01
1.13604736e+00 5.69349527e-01 3.94265115e-01 6.73866749e-01
3.20518345e-01 -9.87271190e-01 1.15647078e+00 2.49200806e-01
1.36623669e+00 -4.88982469e-01 6.71763659e-01 9.37071666e-02
-9.10791755e-01 8.74149650e-02 -7.79563412e-02 3.49938303e-01
2.65816063e-01 1.64725482e-01 -1.06009281e+00 1.01650953e+00
4.54997480e-01 6.23008788e-01 -8.15767884e-01 4.74206030e-01
-2.32195348e-01 9.35589373e-01 -2.46816710e-01 3.92239153e-01
5.82500696e-01 -1.21755123e-01 2.49765262e-01 1.29398060e+00
6.09978735e-01 -4.83862638e-01 3.08002643e-02 8.21497321e-01
-1.24489494e-01 2.46468678e-01 -8.11956704e-01 -1.28759071e-01
2.81690776e-01 1.15015888e+00 -4.27234471e-01 -5.27287066e-01
-7.95296490e-01 1.46147621e+00 2.82873183e-01 5.37850320e-01
-1.05696142e+00 1.25995472e-01 1.99545681e-01 -1.70557931e-01
1.17646150e-01 -1.57286778e-01 -2.40235716e-01 -1.28588772e+00
4.21633758e-03 -1.24244678e+00 2.41116405e-01 -1.16752172e+00
-1.14697015e+00 7.56851315e-01 2.36013532e-01 -1.19067538e+00
-5.22851586e-01 -4.46664989e-01 -2.27860838e-01 8.87093604e-01
-1.72617698e+00 -2.03938508e+00 -7.59560466e-02 6.11267209e-01
8.16479206e-01 -1.48825705e-01 7.92495489e-01 5.59317946e-01
-4.63283271e-01 9.76634562e-01 2.83716589e-01 3.84780467e-02
9.63420689e-01 -9.18554366e-01 6.87334895e-01 9.63407159e-01
4.96011883e-01 2.51334041e-01 3.24315399e-01 -5.45594871e-01
-1.29654562e+00 -1.32918751e+00 1.06103361e+00 -5.10414243e-01
6.60901070e-01 -4.59464937e-01 -5.62203765e-01 8.30184639e-01
8.70852172e-01 -6.07095122e-01 4.40548480e-01 -2.02981785e-01
-3.14012408e-01 5.21322107e-03 -6.98385298e-01 8.35023522e-01
1.04047275e+00 -4.58814740e-01 -2.23382980e-01 3.57361227e-01
8.13816071e-01 -1.81407496e-01 -1.00892675e+00 3.31543654e-01
5.37451446e-01 -7.04393566e-01 1.06540155e+00 -1.41187236e-01
7.90707588e-01 -2.68710107e-02 -1.19438618e-01 -1.55269122e+00
-8.24330822e-02 -5.65268040e-01 3.59231889e-01 1.39992416e+00
7.93093920e-01 -5.58898091e-01 2.10373819e-01 1.82884306e-01
-4.22480136e-01 -4.85778570e-01 -1.17261159e+00 -8.54158700e-01
4.07669932e-01 -4.92513090e-01 4.99987602e-01 7.92079926e-01
-3.94825697e-01 7.72184432e-01 -7.84764946e-01 -2.30195627e-01
5.65962374e-01 -1.09620258e-01 9.52389717e-01 -5.12880027e-01
-2.59393811e-01 -3.30938637e-01 7.21979141e-02 -7.75374472e-01
2.66719669e-01 -1.32429492e+00 1.27465278e-01 -1.62488091e+00
4.81562108e-01 -4.56161857e-01 -1.30732253e-04 6.12811029e-01
-2.79889733e-01 6.48838460e-01 4.84138370e-01 3.83705258e-01
-4.31135386e-01 7.73011148e-01 1.48586619e+00 -3.24230224e-01
3.05930287e-01 -6.18556738e-01 -5.91539741e-01 2.05744609e-01
6.16403759e-01 -2.10326821e-01 -7.77605653e-01 -1.05325758e+00
1.59886926e-01 5.01701459e-02 2.59223789e-01 -9.93053138e-01
-1.38883308e-01 1.19438864e-01 7.12082116e-03 -4.25675005e-01
1.23124428e-01 -4.46222991e-01 2.93037981e-01 1.69241205e-01
-4.78981465e-01 9.55130979e-02 3.31999302e-01 2.22900137e-01
-2.16676518e-01 -3.82298678e-02 5.33290327e-01 -1.34774283e-01
-7.32405603e-01 1.77725121e-01 -4.95112151e-01 3.45700264e-01
6.63245380e-01 -8.94330144e-02 -3.40484917e-01 -5.20468473e-01
-1.99849203e-01 7.28987306e-02 3.09340745e-01 8.18501890e-01
2.84061134e-01 -1.54581106e+00 -1.28050148e+00 -7.23413303e-02
5.57745159e-01 -5.53785503e-01 2.21539780e-01 1.03723967e+00
-2.12060571e-01 7.19220579e-01 -2.39466652e-01 -5.85205972e-01
-9.04610097e-01 4.05753404e-01 2.08667636e-01 -6.60889328e-01
-5.10087132e-01 6.63013875e-01 5.67437768e-01 -6.38709724e-01
-1.86899602e-01 -1.29511937e-01 2.66816318e-01 -1.65515676e-01
2.08916128e-01 7.07912222e-02 1.12936378e-01 -9.29059148e-01
9.75861400e-03 2.86603719e-01 -1.37741312e-01 -7.07315087e-01
9.13946033e-01 -5.14641464e-01 2.49682032e-02 3.65193307e-01
1.18554616e+00 -4.59274799e-01 -8.75852346e-01 -2.60918081e-01
-2.04661250e-01 -1.51954025e-01 -1.71533212e-01 -1.47626126e+00
-9.25854027e-01 9.10079479e-01 6.24122500e-01 -5.22459030e-01
1.17286527e+00 7.07209557e-02 1.04517519e+00 1.47507191e-01
4.51681107e-01 -1.05574894e+00 5.46091385e-02 4.35616463e-01
1.02634954e+00 -1.26214051e+00 -4.92925078e-01 -9.89563018e-02
-1.07709181e+00 6.20647252e-01 5.01735270e-01 5.85672796e-01
-1.04373915e-03 2.54879713e-01 3.13488841e-01 1.03361577e-01
-8.35545540e-01 -1.68969154e-01 3.70665103e-01 6.17085040e-01
6.12954378e-01 1.02743573e-01 -3.05431783e-01 1.75193444e-01
-2.98348576e-01 1.98347330e-01 3.41306657e-01 6.26183987e-01
3.41743112e-01 -1.06183183e+00 -2.18068600e-01 2.19584972e-01
-4.24203873e-01 -6.37611091e-01 -2.16982827e-01 8.54780853e-01
1.44538105e-01 9.45803046e-01 -1.82193905e-01 -2.20313266e-01
1.17211424e-01 2.71822929e-01 7.08889842e-01 -2.41663963e-01
-5.72855890e-01 6.94079399e-02 3.40465575e-01 -4.08196688e-01
-5.04999816e-01 -5.44198811e-01 -5.90352476e-01 -6.38513789e-02
-3.39742899e-01 -1.42495945e-01 9.61333573e-01 1.12468815e+00
6.54760957e-01 5.20681143e-01 2.34521821e-01 -6.74265504e-01
-4.21081841e-01 -1.20125008e+00 2.01760292e-01 4.36772555e-01
-2.12780222e-01 -3.89142483e-01 4.47350815e-02 4.56061780e-01] | [11.409706115722656, 1.5168007612228394] |
00ce6b85-0f99-48d1-a8b3-f2ee5ed31583 | bilinear-cnns-for-fine-grained-visual | 1504.07889 | null | http://arxiv.org/abs/1504.07889v6 | http://arxiv.org/pdf/1504.07889v6.pdf | Bilinear CNNs for Fine-grained Visual Recognition | We present a simple and effective architecture for fine-grained visual
recognition called Bilinear Convolutional Neural Networks (B-CNNs). These
networks represent an image as a pooled outer product of features derived from
two CNNs and capture localized feature interactions in a translationally
invariant manner. B-CNNs belong to the class of orderless texture
representations but unlike prior work they can be trained in an end-to-end
manner. Our most accurate model obtains 84.1%, 79.4%, 86.9% and 91.3% per-image
accuracy on the Caltech-UCSD birds [67], NABirds [64], FGVC aircraft [42], and
Stanford cars [33] dataset respectively and runs at 30 frames-per-second on a
NVIDIA Titan X GPU. We then present a systematic analysis of these networks and
show that (1) the bilinear features are highly redundant and can be reduced by
an order of magnitude in size without significant loss in accuracy, (2) are
also effective for other image classification tasks such as texture and scene
recognition, and (3) can be trained from scratch on the ImageNet dataset
offering consistent improvements over the baseline architecture. Finally, we
present visualizations of these models on various datasets using top
activations of neural units and gradient-based inversion techniques. The source
code for the complete system is available at http://vis-www.cs.umass.edu/bcnn. | ['Tsung-Yu Lin', 'Subhransu Maji', 'Aruni RoyChowdhury'] | 2015-04-29 | null | null | null | null | ['fine-grained-visual-recognition'] | ['computer-vision'] | [ 1.02984190e-01 -4.01354402e-01 7.41791278e-02 -4.22071725e-01
-4.60973620e-01 -5.00531793e-01 6.19006097e-01 -2.96616882e-01
-3.68148446e-01 4.81041282e-01 -2.53662735e-01 -3.40220839e-01
-8.93749222e-02 -6.02857471e-01 -1.11500466e+00 -7.18597770e-01
-1.84676245e-01 2.66319245e-01 3.51206422e-01 -3.70717943e-01
1.48463935e-01 7.43455470e-01 -1.65654981e+00 5.87776482e-01
2.05185145e-01 1.74874318e+00 -1.46195129e-01 8.73331070e-01
4.59943175e-01 9.98069584e-01 -1.82508036e-01 8.86395872e-02
5.47638476e-01 5.16826697e-02 -8.32728505e-01 1.95080992e-02
1.08722413e+00 -4.99020815e-01 -4.72094178e-01 6.76300824e-01
2.69903332e-01 1.72206655e-01 3.53760481e-01 -1.07607388e+00
-5.23458362e-01 -7.42652491e-02 -4.92021799e-01 2.04656094e-01
-2.81676739e-01 6.10959791e-02 7.86582351e-01 -9.65124905e-01
5.66408813e-01 1.19644666e+00 8.42920125e-01 3.24077249e-01
-1.30853212e+00 -5.37014425e-01 -2.30778754e-01 8.24793279e-02
-1.20654273e+00 -5.55735886e-01 3.51503223e-01 -4.26208138e-01
1.48967803e+00 3.80350292e-01 7.04735041e-01 8.51308584e-01
4.62780476e-01 3.31605643e-01 1.21578598e+00 -3.33183199e-01
-2.09517971e-01 -4.18577611e-01 1.89883724e-01 1.22679615e+00
1.27295837e-01 5.34247518e-01 -6.77315533e-01 -8.36901143e-02
1.27528906e+00 -7.67234294e-03 6.35240823e-02 -4.51613039e-01
-1.32290626e+00 8.06895256e-01 9.64786649e-01 -3.63104977e-02
-2.63907582e-01 6.91596389e-01 5.55113971e-01 4.41368788e-01
4.38628733e-01 3.26407671e-01 -4.59291101e-01 8.17514956e-03
-6.26525223e-01 4.21765625e-01 5.79103887e-01 7.79515386e-01
9.92299616e-01 5.10894120e-01 9.95765701e-02 7.92775810e-01
5.40061146e-02 5.02616823e-01 3.05249363e-01 -1.08263302e+00
-1.86530892e-02 2.80241340e-01 -6.62784129e-02 -1.13930714e+00
-4.53654647e-01 -4.94119555e-01 -9.48811829e-01 6.74014270e-01
2.93576688e-01 -2.34090704e-02 -1.12653804e+00 1.49014461e+00
2.29092374e-01 1.00488149e-01 -2.28477970e-01 1.04546130e+00
1.00831127e+00 6.04931772e-01 -1.43466175e-01 5.85363626e-01
1.42101467e+00 -1.13409603e+00 -7.32740015e-02 -2.23138541e-01
4.37875062e-01 -9.35549438e-01 7.85047174e-01 3.83163661e-01
-1.00905085e+00 -8.77105296e-01 -1.23106229e+00 -4.52585399e-01
-4.44486678e-01 3.90570790e-01 9.48851526e-01 3.79886925e-01
-1.33598030e+00 8.56436968e-01 -1.16483581e+00 -3.87101561e-01
5.60639977e-01 6.43496871e-01 -4.59089994e-01 8.42075124e-02
-5.14625609e-01 5.62328398e-01 1.11626163e-01 2.98995554e-01
-1.04572392e+00 -6.42559230e-01 -8.20631921e-01 7.52886459e-02
-7.61958137e-02 -7.74320066e-01 1.22947705e+00 -1.26305985e+00
-1.46067286e+00 9.00086462e-01 -9.98848975e-02 -6.72622383e-01
1.23907559e-01 -2.54485607e-01 -9.01214033e-02 2.12749615e-01
-9.26256925e-02 1.05623209e+00 9.29429173e-01 -8.68698359e-01
-5.33277392e-01 -1.90814361e-01 1.65590018e-01 1.90937445e-02
-2.29777116e-02 8.23145509e-02 -2.96187758e-01 -6.68409884e-01
1.73215598e-01 -1.23318207e+00 -2.14377642e-01 3.81039798e-01
-3.20418954e-01 2.60732830e-01 1.24466300e+00 -4.38619703e-01
3.36309761e-01 -2.10584712e+00 7.82759860e-03 2.94928383e-02
3.74708086e-01 3.66309553e-01 -2.98560202e-01 2.20959291e-01
-2.73694187e-01 -5.48201799e-02 -4.93896343e-02 -7.69257396e-02
-1.90228447e-01 1.51946336e-01 -3.09056580e-01 5.59848905e-01
3.33953381e-01 1.12456536e+00 -3.58675361e-01 1.98404603e-02
5.58355570e-01 6.30796671e-01 -6.50729895e-01 1.71605982e-02
-1.95573531e-02 3.88282508e-01 -2.83972502e-01 7.58646131e-01
6.46640658e-01 -2.54052758e-01 4.20291200e-02 -6.65022135e-01
-3.57888430e-01 1.03802353e-01 -7.35706151e-01 1.38876605e+00
-4.61830020e-01 1.17501199e+00 1.36507824e-01 -1.21105170e+00
9.09705877e-01 -9.84641314e-02 1.55813068e-01 -8.71667922e-01
2.84174740e-01 1.84776470e-01 2.03848168e-01 -9.53130722e-02
6.01368904e-01 -1.10865995e-01 -1.15133077e-01 2.05631196e-01
3.09612900e-01 -1.66139424e-01 1.87427253e-01 -2.46296257e-01
9.50157166e-01 2.22599089e-01 2.28688046e-01 -6.42599881e-01
1.82436362e-01 2.36869246e-01 3.18833262e-01 7.93962777e-01
-1.28897727e-01 6.72377050e-01 3.77195776e-01 -1.22938347e+00
-1.14388704e+00 -8.45248044e-01 -2.31413096e-01 1.26988304e+00
-4.21146117e-02 -3.10007751e-01 -5.61373651e-01 -1.11127913e-01
1.11591130e-01 -5.24763167e-02 -9.20318484e-01 5.52805811e-02
-5.97954392e-01 -5.60223699e-01 7.57731199e-01 6.59228683e-01
9.72139120e-01 -1.01014042e+00 -9.08177555e-01 3.38256061e-02
1.61427438e-01 -1.13880897e+00 -5.51208481e-02 5.19404888e-01
-9.26777244e-01 -1.10204005e+00 -2.81262338e-01 -8.18561614e-01
5.30865788e-01 4.74121749e-01 1.17443728e+00 2.77901918e-01
-6.19814277e-01 2.35412523e-01 -1.69699535e-01 -2.52639890e-01
1.86185151e-01 -2.10333969e-02 1.05326191e-01 -3.30374800e-02
5.59974946e-02 -4.95559603e-01 -5.70802689e-01 4.42591310e-01
-7.10091949e-01 2.10157394e-01 4.14951771e-01 1.32505143e+00
7.33583093e-01 -3.84729832e-01 8.32232460e-03 -7.74195671e-01
1.14400975e-01 -3.95881645e-02 -9.73816335e-01 -7.18657076e-02
3.75299938e-02 -9.43031460e-02 7.34088957e-01 -1.82915762e-01
-8.93726707e-01 2.54283339e-01 -2.28926018e-01 -7.04642951e-01
-4.30884808e-01 3.18132818e-01 6.32288337e-01 -9.64099586e-01
8.40162516e-01 1.48388483e-02 -5.76291010e-02 -2.88340598e-01
1.07360795e-01 1.23358667e-01 5.80873728e-01 -7.43965924e-01
6.88161850e-01 7.39207327e-01 2.94687748e-01 -1.03595114e+00
-7.13090599e-01 -1.93732515e-01 -7.18315482e-01 4.68284450e-03
8.03201199e-01 -9.15475130e-01 -1.02341104e+00 7.53090620e-01
-9.79938209e-01 -7.94213057e-01 -9.85358134e-02 3.07968557e-01
-5.99473536e-01 2.43401360e-02 -7.85924196e-01 -2.28537172e-01
-3.87063175e-01 -1.24637890e+00 1.19938827e+00 3.48319530e-01
-3.18719633e-02 -1.01310158e+00 -3.19435596e-01 1.52501971e-01
8.38107407e-01 5.00069022e-01 8.10484707e-01 -8.08233619e-02
-8.17766905e-01 -1.15649007e-01 -5.94986677e-01 3.87205988e-01
-5.03036566e-02 2.39323169e-01 -1.01738250e+00 -4.89990592e-01
-3.23754668e-01 -7.96476781e-01 1.07603359e+00 5.75507879e-01
1.44096732e+00 -1.81151539e-01 -3.65267210e-02 1.15537477e+00
1.56597197e+00 2.03685537e-02 5.94524443e-01 3.10750216e-01
8.30732644e-01 3.71348411e-01 2.46285558e-01 3.01068038e-01
4.72617224e-02 7.45736480e-01 5.74807346e-01 -4.76594865e-01
-2.44445235e-01 1.51610434e-01 1.57264367e-01 5.75813591e-01
-4.17374045e-01 1.11667864e-01 -1.00443375e+00 2.89599717e-01
-1.78563511e+00 -8.55612516e-01 -2.42817938e-01 1.94255626e+00
3.02018344e-01 1.69786997e-02 -5.23455441e-02 -2.95813829e-01
3.19467992e-01 2.75952637e-01 -5.73356628e-01 -7.48734057e-01
-2.69021243e-01 7.78004289e-01 7.59757459e-01 3.62670809e-01
-1.37314045e+00 1.28125763e+00 6.27564716e+00 6.85326576e-01
-1.61496007e+00 3.54658440e-02 1.04687619e+00 -2.06679016e-01
4.00301039e-01 1.60279199e-02 -5.21539271e-01 -7.66821802e-02
9.69210863e-01 2.25734130e-01 6.10875309e-01 9.05540109e-01
-8.78066868e-02 -1.57886177e-01 -8.36771548e-01 9.69201982e-01
-1.38359249e-01 -1.77004373e+00 7.33239052e-04 -4.62834761e-02
7.57170618e-01 6.10613346e-01 3.55358869e-01 2.00297147e-01
3.62155050e-01 -1.35189700e+00 8.16968799e-01 3.88899773e-01
1.14557111e+00 -7.08828390e-01 5.85272193e-01 -1.07073756e-02
-1.28806698e+00 1.06011286e-01 -7.55316794e-01 -4.18410331e-01
-2.02948079e-01 3.15583199e-01 -3.92429978e-01 3.49098176e-01
1.28125429e+00 7.27313757e-01 -6.86437130e-01 6.93925619e-01
4.01657447e-02 6.79988980e-01 -4.80347395e-01 -5.54173663e-02
6.96454942e-01 -2.22567767e-02 1.13176852e-01 1.24434865e+00
2.28511289e-01 4.82817739e-02 7.55960345e-02 7.17977047e-01
-1.61734611e-01 -4.04347956e-01 -6.67911351e-01 2.47551817e-02
-5.11244498e-02 1.64592052e+00 -7.07629859e-01 -4.14880604e-01
-2.62035280e-01 8.25854242e-01 6.09039962e-01 4.12853867e-01
-7.30641246e-01 -5.58957934e-01 9.14445460e-01 -2.07501367e-01
6.84367180e-01 -4.37901706e-01 -2.31825396e-01 -1.00883043e+00
-2.07678363e-01 -9.26448345e-01 -8.00683796e-02 -9.82961416e-01
-1.03629458e+00 8.97996783e-01 -3.57424170e-01 -1.12121785e+00
-2.53259182e-01 -1.28343141e+00 -4.62145001e-01 8.08510244e-01
-1.27720976e+00 -1.33421493e+00 -7.39622355e-01 6.47921264e-01
2.71997005e-01 -1.11609362e-01 1.09187949e+00 2.07641825e-01
-4.57311511e-01 4.02496427e-01 1.07412189e-01 2.59379625e-01
3.81863803e-01 -9.31418061e-01 6.83203816e-01 6.11551583e-01
3.02656479e-02 6.17826223e-01 4.21521634e-01 -3.12526077e-01
-1.53857827e+00 -1.26005983e+00 4.78085697e-01 -1.29779801e-01
5.35302162e-01 -5.45412064e-01 -7.53862679e-01 8.92203510e-01
3.59745950e-01 6.24715507e-01 3.64884257e-01 1.33094653e-01
-6.60562158e-01 -3.23758453e-01 -9.85941887e-01 5.49855351e-01
9.85495806e-01 -5.67467570e-01 -4.89505827e-02 4.65884030e-01
3.28231543e-01 -9.05548096e-01 -7.16337383e-01 4.23625618e-01
1.00471556e+00 -1.39801323e+00 1.03635454e+00 -6.76487923e-01
5.71890473e-01 -2.01102078e-01 -3.81654799e-01 -1.16307294e+00
-6.01211607e-01 -3.90405387e-01 3.11772138e-01 4.16055173e-01
1.10514320e-01 -7.91841984e-01 5.86318314e-01 7.59490281e-02
-2.80607551e-01 -8.27569842e-01 -1.04001188e+00 -6.40624702e-01
7.91975185e-02 -4.28222865e-01 2.91255534e-01 6.99975729e-01
-5.12522042e-01 8.95057246e-02 -4.89578724e-01 7.64329135e-02
6.09070063e-01 2.88337529e-01 8.58936667e-01 -1.00636744e+00
-2.07106754e-01 -3.86523366e-01 -5.42412877e-01 -9.44458604e-01
1.00821860e-01 -6.71757400e-01 7.61761190e-03 -1.04620278e+00
-3.41826305e-02 -5.57144880e-01 -1.45350128e-01 9.33327496e-01
5.17856896e-01 1.05488873e+00 8.78171325e-02 8.29710662e-02
-4.65935290e-01 4.01242822e-01 1.06260729e+00 5.00832200e-02
4.28175688e-01 -3.90182585e-01 -4.15392488e-01 7.45104969e-01
1.02449560e+00 -1.82565570e-01 2.39932798e-02 -6.71411455e-01
-8.08240101e-02 3.09379529e-02 9.99859154e-01 -1.18600905e+00
1.10186838e-01 3.84109505e-02 7.90335834e-01 -3.01546723e-01
6.82195485e-01 -5.18996656e-01 5.55664040e-02 5.29523253e-01
-4.31945510e-02 3.03681552e-01 8.20501089e-01 5.23399860e-02
-3.98426801e-01 2.01210916e-01 1.14461589e+00 -1.10926114e-01
-9.05143142e-01 3.79055351e-01 -4.68443751e-01 -3.11629236e-01
6.64372921e-01 -1.51447952e-01 -6.54741108e-01 -2.16719985e-01
-3.23789746e-01 -2.94539481e-01 3.88232201e-01 2.41064057e-01
5.16235232e-01 -1.49251461e+00 -5.33235610e-01 5.97850740e-01
-9.62624699e-02 -9.17366743e-02 4.45546687e-01 7.94458389e-01
-1.16455126e+00 7.08630145e-01 -9.37651038e-01 -9.50511813e-01
-1.25485957e+00 6.39973879e-02 6.53530657e-01 -1.14638038e-01
-3.30107510e-01 9.56546366e-01 5.34778118e-01 -5.14852226e-01
-1.51406258e-01 -5.31613767e-01 2.06391722e-01 -4.28640127e-01
4.12304282e-01 1.28676981e-01 3.48606467e-01 -8.71795952e-01
-3.65608662e-01 8.06834698e-01 -1.02189213e-01 1.32261902e-01
1.49570942e+00 3.07441056e-01 -2.82072812e-01 1.47140935e-01
1.43519652e+00 -4.17584091e-01 -1.42881083e+00 -1.32927984e-01
-4.18018728e-01 -3.72694522e-01 2.56186604e-01 -6.13913238e-01
-1.35878253e+00 1.11729252e+00 7.47288644e-01 7.65370131e-02
1.22936690e+00 -2.74586290e-01 4.97677952e-01 6.56821549e-01
2.32207507e-01 -6.00573301e-01 5.10051921e-02 1.01050806e+00
1.01967454e+00 -1.12589097e+00 -9.46677569e-03 -3.54571968e-01
-4.16622907e-01 1.39782310e+00 6.94211245e-01 -7.28117466e-01
5.85730553e-01 4.61795956e-01 2.00597644e-01 -3.67672414e-01
-1.01493537e+00 -1.68758810e-01 4.61115569e-01 5.08253038e-01
5.85767269e-01 1.17707767e-01 3.01894546e-01 2.22775210e-02
-2.71083146e-01 -8.54638517e-02 2.83896416e-01 1.02140629e+00
-2.72947013e-01 -6.51003301e-01 -1.61942214e-01 4.67776418e-01
-3.60719264e-01 -2.80093193e-01 -2.03569055e-01 8.58077824e-01
3.75561602e-03 5.55625319e-01 3.28000516e-01 -5.06312311e-01
2.45011151e-01 -1.73554361e-01 6.40513182e-01 -3.16309631e-01
-7.67135084e-01 5.57626784e-02 3.14387202e-01 -9.12850857e-01
-3.60204875e-01 -4.43238705e-01 -9.11634445e-01 -7.72020996e-01
-1.41733503e-02 -3.75701159e-01 6.70467079e-01 7.11902678e-01
6.17857754e-01 6.29239380e-01 2.89390653e-01 -1.57928133e+00
-2.07654089e-01 -9.12711501e-01 -3.79993081e-01 1.35453537e-01
4.94387597e-01 -7.53623068e-01 -1.27087623e-01 6.22451715e-02] | [9.281630516052246, 1.5489684343338013] |
2fe8d3dd-9fbf-4ed7-a087-5e3193565d21 | pair-based-joint-encoding-with-relational | 2212.01844 | null | https://arxiv.org/abs/2212.01844v1 | https://arxiv.org/pdf/2212.01844v1.pdf | Pair-Based Joint Encoding with Relational Graph Convolutional Networks for Emotion-Cause Pair Extraction | Emotion-cause pair extraction (ECPE) aims to extract emotion clauses and corresponding cause clauses, which have recently received growing attention. Previous methods sequentially encode features with a specified order. They first encode the emotion and cause features for clause extraction and then combine them for pair extraction. This lead to an imbalance in inter-task feature interaction where features extracted later have no direct contact with the former. To address this issue, we propose a novel Pair-Based Joint Encoding (PBJE) network, which generates pairs and clauses features simultaneously in a joint feature encoding manner to model the causal relationship in clauses. PBJE can balance the information flow among emotion clauses, cause clauses and pairs. From a multi-relational perspective, we construct a heterogeneous undirected graph and apply the Relational Graph Convolutional Network (RGCN) to capture the various relationship between clauses and the relationship between pairs and clauses. Experimental results show that PBJE achieves state-of-the-art performance on the Chinese benchmark corpus. | ['Qianli Ma', 'Xichen Shang', 'Junlong Liu'] | 2022-12-04 | null | null | null | null | ['emotion-cause-pair-extraction'] | ['natural-language-processing'] | [ 1.41276717e-01 3.88500005e-01 -1.28680348e-01 -7.81251371e-01
-8.40482056e-01 -4.56410468e-01 5.44043422e-01 3.01909596e-01
-3.24223330e-03 5.37222743e-01 4.16090518e-01 2.51172751e-01
-1.41063511e-01 -1.00081527e+00 -5.02985001e-01 -5.34502268e-01
-2.41576105e-01 3.67679387e-01 -2.33211920e-01 -4.48620945e-01
-5.52217327e-02 -8.85162270e-04 -1.42448056e+00 7.67693162e-01
1.03028286e+00 9.46608007e-01 -1.93939611e-01 3.68762165e-01
-5.25771558e-01 1.54501355e+00 -5.55436254e-01 -8.86995137e-01
-1.73741728e-01 -7.24862516e-01 -1.02815342e+00 -3.29057826e-03
-2.63935834e-01 2.93634050e-02 -3.18637103e-01 9.04738247e-01
3.09973001e-01 -1.06727250e-01 6.52121842e-01 -1.59578681e+00
-6.20761871e-01 1.28031206e+00 -6.77109122e-01 -3.41363177e-02
5.82992852e-01 -4.00870621e-01 1.78802061e+00 -7.52696574e-01
7.92627573e-01 1.28257823e+00 4.87403721e-01 4.32313323e-01
-9.05125022e-01 -8.37437034e-01 5.07589400e-01 4.53521639e-01
-1.24710643e+00 5.29155396e-02 1.34502757e+00 -5.03004044e-02
1.32362807e+00 3.46950322e-01 9.25168097e-01 1.14046717e+00
4.11311805e-01 1.18438601e+00 8.30108464e-01 -7.44327232e-02
-1.71560660e-01 -2.11530373e-01 4.65076596e-01 6.03692472e-01
-1.21322842e-02 -1.68895915e-01 -7.89351881e-01 1.47905633e-01
2.31192484e-01 -3.09494019e-01 -3.56433302e-01 7.81750008e-02
-9.78013873e-01 1.07603788e+00 6.94097817e-01 4.29932505e-01
-3.53501618e-01 1.90244913e-01 6.07039869e-01 5.22649944e-01
6.92163587e-01 5.60776293e-01 -7.11753428e-01 -1.33834928e-02
-3.97382468e-01 3.55542541e-01 7.98902810e-01 1.16117442e+00
7.13422358e-01 -4.17981535e-01 -4.98590142e-01 8.37745190e-01
2.69945681e-01 -1.76266059e-02 2.87138045e-01 -2.04024881e-01
7.57669210e-01 1.20849752e+00 -5.10147810e-01 -1.47775769e+00
-5.92020154e-01 -4.00832355e-01 -1.05347240e+00 -7.39708304e-01
-3.80751103e-01 -3.66322488e-01 -5.22204936e-01 1.73107171e+00
5.35112917e-01 8.94922689e-02 3.23155463e-01 8.89232635e-01
1.42201197e+00 8.07630956e-01 2.82424781e-03 -2.56927013e-01
1.54133070e+00 -1.05641162e+00 -1.14013577e+00 -4.41775262e-01
8.58378589e-01 -6.48902297e-01 5.44238389e-01 2.46210560e-01
-8.12780023e-01 -2.54014701e-01 -9.47012365e-01 -4.78981376e-01
-3.02171230e-01 1.83639914e-01 1.11261582e+00 -5.27053736e-02
-6.60339713e-01 4.30942446e-01 -5.73809266e-01 2.70652086e-01
1.91582933e-01 5.23758888e-01 -4.60554332e-01 -1.57592297e-01
-1.74971724e+00 7.62630165e-01 4.46319431e-01 6.42813504e-01
-2.10110188e-01 -5.95185041e-01 -1.22589481e+00 3.72820437e-01
4.93987411e-01 -5.67631066e-01 9.42388058e-01 -1.05813849e+00
-1.13313591e+00 7.47641444e-01 -8.56611952e-02 -1.43947065e-01
-1.74825355e-01 -2.96978951e-01 -5.65157056e-01 -2.70928666e-02
9.96212754e-03 6.29138470e-01 4.96317357e-01 -1.07359326e+00
-6.23582840e-01 -2.85216987e-01 -9.35822502e-02 4.42116916e-01
-9.71498713e-02 1.71808168e-01 -6.75599456e-01 -5.03072143e-01
1.44344404e-01 -6.31070077e-01 -1.48593970e-02 -7.65065312e-01
-9.04128194e-01 -8.96461070e-01 6.82041943e-01 -3.39252055e-01
1.37980163e+00 -2.21741176e+00 6.25474751e-01 1.19620726e-01
6.83553874e-01 -2.08453879e-01 -3.38097423e-01 5.00088871e-01
-4.46263492e-01 2.43475005e-01 -9.98528600e-02 -4.21673954e-01
1.80216014e-01 2.68943667e-01 -1.63704962e-01 9.35628116e-02
1.05586803e+00 1.11919248e+00 -9.53334987e-01 -6.90116942e-01
-3.03968936e-01 7.04635859e-01 -6.91408038e-01 6.66590333e-01
-1.60508841e-01 -1.12857781e-01 -7.32708871e-01 6.46551549e-01
8.32242548e-01 -3.16475034e-01 5.78749239e-01 -6.16076767e-01
2.24082872e-01 6.99173808e-01 -8.43933702e-01 1.25372434e+00
-2.23935574e-01 5.27084112e-01 -2.05145534e-02 -9.23696995e-01
1.21088982e+00 3.21147919e-01 6.34535491e-01 -7.83114612e-01
3.66211802e-01 3.16932201e-02 2.17381358e-01 -6.19989753e-01
4.97509599e-01 -2.02280656e-01 -5.38233697e-01 1.20591834e-01
3.12467158e-01 -3.00917387e-01 3.90357167e-01 5.67855060e-01
1.27372396e+00 -6.70992211e-02 3.94249529e-01 -9.19394940e-02
3.91252518e-01 -1.17862679e-01 8.91005933e-01 8.93174186e-02
3.56436297e-02 4.67008829e-01 1.34169400e+00 -3.58685642e-01
-2.61555076e-01 -6.69229090e-01 2.77531624e-01 7.55413711e-01
2.36565337e-01 -9.01219428e-01 -3.51293653e-01 -1.09000528e+00
-1.50361642e-01 4.49548453e-01 -9.61626410e-01 -4.69963461e-01
-6.27086997e-01 -8.45963359e-01 4.32789207e-01 4.54335093e-01
5.13863802e-01 -1.13615239e+00 -2.53460765e-01 2.37697348e-01
-7.35813677e-01 -1.13187003e+00 -2.60273784e-01 7.52208889e-01
-2.66378224e-01 -1.37861884e+00 3.65659595e-02 -8.25714827e-01
6.21841252e-01 -2.42211401e-01 1.60127223e+00 2.17186362e-01
-1.06720500e-01 6.57873750e-02 -8.18657637e-01 -2.85120189e-01
4.86262664e-02 2.13299111e-01 -6.91016197e-01 3.56776640e-02
6.65107787e-01 -3.63689274e-01 -3.61132085e-01 -2.06131384e-01
-8.17678690e-01 3.80317122e-01 6.75034285e-01 1.05383909e+00
6.31635964e-01 2.40757465e-01 4.23862219e-01 -1.35477877e+00
9.02219534e-01 -6.76273763e-01 -3.17308486e-01 3.14974964e-01
-5.01812637e-01 1.03850566e-01 4.74873215e-01 -1.97487608e-01
-1.12464523e+00 -2.53996924e-02 -1.44880727e-01 -2.79465616e-01
2.03996569e-01 1.08171606e+00 -4.51865524e-01 5.66450000e-01
-6.58452958e-02 -6.26836643e-02 -5.54807782e-01 1.30560072e-02
3.90207022e-01 3.14743727e-01 2.48890579e-01 -5.36141276e-01
5.14528811e-01 -8.18179473e-02 3.22813075e-03 -1.73956096e-01
-1.07546735e+00 -4.17008013e-01 -4.65759426e-01 -1.47600532e-01
9.80048001e-01 -1.08017707e+00 -6.79300845e-01 3.27257693e-01
-1.54243171e+00 -2.77192052e-02 6.42272178e-03 2.65310407e-01
-6.91551194e-02 -1.11099638e-01 -1.01364863e+00 -6.98116839e-01
-4.73900318e-01 -1.03196883e+00 1.50463772e+00 1.03845894e-01
-2.09584787e-01 -8.43507648e-01 1.09503247e-01 1.92913726e-01
-8.64016712e-02 6.19037867e-01 1.07439578e+00 -7.84184635e-01
-5.75054109e-01 -8.86468813e-02 -5.24592757e-01 -1.01493090e-01
2.68114895e-01 2.27338061e-01 -7.31439352e-01 1.11541286e-01
-4.07822654e-02 -4.70755398e-01 9.70722079e-01 3.73235866e-02
8.80462110e-01 -4.36588436e-01 -3.53437692e-01 5.46579599e-01
1.45588541e+00 1.23562306e-01 6.66547596e-01 -1.02318451e-01
1.03736842e+00 8.60765874e-01 8.05773556e-01 4.24070477e-01
8.43589723e-01 4.29770112e-01 5.46710908e-01 -4.08545971e-01
9.31605622e-02 -1.09227628e-01 3.10143858e-01 1.23540103e+00
1.74951181e-01 -5.77029288e-01 -7.22064614e-01 5.14660478e-01
-1.85438502e+00 -7.29029953e-01 -6.58718586e-01 1.26213241e+00
1.18140495e+00 -4.89305742e-02 -3.79545033e-01 1.41071513e-01
5.23151815e-01 1.92833096e-01 -6.26118109e-02 -4.97015446e-01
-1.74263045e-01 2.02326834e-01 -5.98483793e-02 3.22292835e-01
-1.08505344e+00 1.01590466e+00 5.35415745e+00 7.57611096e-01
-1.12662590e+00 -1.72397599e-01 8.68064284e-01 6.15817308e-02
-6.73926950e-01 8.98801759e-02 -6.03158832e-01 1.61865517e-01
5.25651395e-01 -1.21442243e-01 3.72546434e-01 7.05883503e-01
-3.30763638e-01 2.58983448e-02 -1.27471817e+00 8.98714781e-01
4.93774638e-02 -1.07213879e+00 4.30436991e-02 -7.51779079e-02
5.98135173e-01 -9.66254324e-02 -2.85314679e-01 7.86169767e-01
1.64890543e-01 -1.08040082e+00 5.00060797e-01 4.47358131e-01
5.21475315e-01 -1.20667207e+00 1.19433939e+00 -6.69437125e-02
-1.69237447e+00 1.25239819e-01 -2.45608047e-01 -1.00360364e-01
2.28128266e-02 9.70538139e-01 -6.34335697e-01 1.01450253e+00
6.58120930e-01 9.92256284e-01 -5.52477241e-01 3.96348059e-01
-5.27924299e-01 5.20316780e-01 -1.77519768e-02 -3.20516407e-01
2.97910541e-01 -2.19959006e-01 2.25877285e-01 1.45569074e+00
5.31621836e-02 3.97341669e-01 -3.55565213e-02 1.19206560e+00
-3.07016671e-01 2.92697728e-01 -6.12218142e-01 -3.82456809e-01
3.15992177e-01 1.67791903e+00 -8.67013216e-01 -1.91236794e-01
-4.16208982e-01 1.06696069e+00 9.22967911e-01 9.50994343e-02
-1.10293627e+00 -7.09475338e-01 5.50373733e-01 -5.59767962e-01
3.78286839e-01 2.93715328e-01 6.00776970e-02 -1.30713940e+00
6.71416447e-02 -8.11398566e-01 5.01247227e-01 -6.07154906e-01
-1.59765530e+00 8.81400764e-01 -1.92651562e-02 -8.88002336e-01
-3.79738241e-01 -4.40056801e-01 -6.63404286e-01 5.75503409e-01
-1.69792366e+00 -1.37889695e+00 -2.13716999e-01 6.13409102e-01
3.69599164e-01 3.65484029e-01 7.81600654e-01 3.91576856e-01
-8.68441582e-01 6.05483413e-01 -7.68851817e-01 4.83535677e-01
4.04437333e-01 -1.47659600e+00 5.34711927e-02 6.98322833e-01
1.54879481e-01 6.56240761e-01 3.55871379e-01 -7.47091532e-01
-1.53369546e+00 -1.16770089e+00 1.61929846e+00 -1.87893823e-01
4.61455792e-01 -8.18277717e-01 -8.43588412e-01 6.45910800e-01
5.45066178e-01 1.11749887e-01 7.72023916e-01 5.40087342e-01
-4.64291692e-01 -1.82912558e-01 -7.90005982e-01 4.34277534e-01
8.57244194e-01 -5.29469311e-01 -4.60134506e-01 2.11198628e-01
1.17222798e+00 -4.96805847e-01 -8.63653362e-01 6.42516017e-01
2.12105036e-01 -1.10418093e+00 5.51582038e-01 -3.43913823e-01
1.10091531e+00 -6.74103498e-02 -8.33490118e-02 -1.36560273e+00
-4.05638874e-01 -4.86067563e-01 -8.65440145e-02 1.82679665e+00
7.57205427e-01 -2.23630875e-01 2.74118036e-01 5.09815276e-01
-2.03360066e-01 -1.27279627e+00 -6.97821319e-01 -2.11868823e-01
-1.77582368e-01 -4.40270901e-01 9.61298883e-01 1.26967859e+00
4.92648989e-01 1.07345259e+00 -3.20753366e-01 -6.10594079e-02
1.37146534e-02 5.40449679e-01 3.25887233e-01 -1.14408684e+00
-2.90488809e-01 -4.21945572e-01 -7.20363632e-02 -5.95938802e-01
5.18355489e-01 -1.06973302e+00 3.20431948e-01 -1.76450276e+00
5.65311670e-01 -3.02622348e-01 -2.84866303e-01 6.33821070e-01
-7.04643548e-01 -1.51530102e-01 9.20456052e-02 -2.69937456e-01
-7.99940288e-01 1.00184596e+00 1.34811401e+00 -2.36474290e-01
-3.48223299e-02 -4.68537688e-01 -9.85320866e-01 3.88295352e-01
5.11150539e-01 -5.88361800e-01 -5.75207531e-01 -4.17879224e-01
9.02271867e-01 1.00261882e-01 -9.96903032e-02 -4.74734843e-01
1.58781737e-01 -1.10657282e-01 3.37491870e-01 -6.47845984e-01
1.75579935e-01 -9.07227516e-01 -3.97551470e-02 -2.39917487e-02
-3.55625898e-01 2.93622315e-01 5.26618995e-02 4.86390591e-01
-7.84016728e-01 2.26170987e-01 1.34742811e-01 1.21050343e-01
-3.85952204e-01 1.41181529e-01 -9.08086300e-02 5.55909052e-02
8.33460689e-01 3.50189090e-01 -4.35958624e-01 -3.34184289e-01
-4.28424001e-01 5.80694616e-01 -2.68198162e-01 5.23792088e-01
8.48529339e-01 -1.54240811e+00 -8.04603100e-01 7.36294836e-02
2.64397293e-01 3.54538590e-01 2.52327323e-01 9.00979459e-01
-6.64557284e-03 2.32091695e-01 2.10498750e-01 -2.30338201e-01
-1.36380172e+00 5.04187465e-01 2.53448665e-01 -1.03902268e+00
-2.96944857e-01 1.28816640e+00 2.28268966e-01 -6.86872840e-01
-1.34379908e-01 -5.89550138e-01 -6.57089174e-01 3.54249716e-01
1.22111477e-01 -2.00211585e-01 3.85944992e-02 -6.11223042e-01
-5.74844420e-01 3.03991258e-01 -9.26768854e-02 2.59202987e-01
1.47220075e+00 9.95835811e-02 -8.09007347e-01 3.49200666e-01
1.51537657e+00 7.49461204e-02 -7.27136433e-01 7.32606351e-02
1.04140617e-01 -8.72454345e-02 1.02492839e-01 -7.01278627e-01
-1.54431653e+00 5.65398335e-01 -1.20118119e-01 3.33407670e-01
1.46259737e+00 2.50418961e-01 8.20372581e-01 7.65332803e-02
8.55910033e-03 -9.51710820e-01 1.62934303e-01 6.73875988e-01
1.06375170e+00 -1.09221661e+00 -3.94171290e-02 -1.21971297e+00
-8.59369874e-01 1.15026319e+00 1.05333221e+00 -2.59061843e-01
6.22474134e-01 6.40005946e-01 -1.93493411e-01 -8.43287766e-01
-1.38836920e+00 -3.83172482e-01 7.03445196e-01 3.35504830e-01
1.09052742e+00 2.61460751e-01 -6.52970612e-01 1.35122752e+00
-2.84084082e-01 -4.03237522e-01 1.10985927e-01 7.18826115e-01
1.90789282e-01 -1.32185340e+00 1.29987001e-01 5.02243638e-01
-3.75685185e-01 -4.67659116e-01 -1.01743817e+00 9.42690492e-01
3.82063389e-01 1.14838135e+00 2.75615215e-01 -7.91711569e-01
1.46952078e-01 -1.02869131e-01 3.93502951e-01 -6.11347377e-01
-1.03431630e+00 2.79257864e-01 5.26327789e-01 -7.19038129e-01
-6.01545095e-01 -4.42326695e-01 -1.60157430e+00 8.56816918e-02
-6.00929201e-01 3.49314839e-01 2.66177595e-01 1.10344696e+00
4.95369136e-01 1.21524811e+00 7.03043103e-01 -4.06049848e-01
1.03471071e-01 -9.95688558e-01 -6.03303492e-01 5.55257559e-01
2.24084929e-01 -4.47564691e-01 -2.69482613e-01 -3.67609233e-01] | [12.579793930053711, 6.202013969421387] |
b774f63d-b5ba-4027-9264-6d2a3a8f2389 | a-unified-front-end-framework-for-english | 2305.10666 | null | https://arxiv.org/abs/2305.10666v1 | https://arxiv.org/pdf/2305.10666v1.pdf | a unified front-end framework for english text-to-speech synthesis | The front-end is a critical component of English text-to-speech (TTS) systems, responsible for extracting linguistic features that are essential for a text-to-speech model to synthesize speech, such as prosodies and phonemes. The English TTS front-end typically consists of a text normalization (TN) module, a prosody word prosody phrase (PWPP) module, and a grapheme-to-phoneme (G2P) module. However, current research on the English TTS front-end focuses solely on individual modules, neglecting the interdependence between them and resulting in sub-optimal performance for each module. Therefore, this paper proposes a unified front-end framework that captures the dependencies among the English TTS front-end modules. Extensive experiments have demonstrated that the proposed method achieves state-of-the-art (SOTA) performance in all modules. | ['Yuxuan Wang', 'Yuping Wang', 'YuanYuan Huo', 'Qiuqiang Kong', 'Yu Dong', 'Chen Li', 'Zelin Ying'] | 2023-05-18 | null | null | null | null | ['text-to-speech-synthesis', 'speech-synthesis'] | ['speech', 'speech'] | [ 1.50206149e-01 3.77719961e-02 -1.32789597e-01 -4.87337530e-01
-9.53157008e-01 -4.48319823e-01 3.90133619e-01 4.62539755e-02
-3.29924047e-01 3.35073799e-01 4.51859176e-01 -6.38322234e-01
5.30654490e-01 -3.82505953e-01 -2.84253299e-01 -4.84206527e-01
5.06416678e-01 1.30452618e-01 3.13374490e-01 -3.88885409e-01
-8.22642148e-02 2.40537405e-01 -1.37123847e+00 3.97482753e-01
6.68377519e-01 9.49602306e-01 3.82691771e-01 9.03246462e-01
-6.83153510e-01 9.43675876e-01 -5.84038258e-01 -4.17685002e-01
2.59136111e-02 -6.68333530e-01 -3.81780416e-01 -2.10706010e-01
-6.57835975e-02 -6.20639846e-02 -2.59606153e-01 1.21506226e+00
6.30212724e-01 2.65669495e-01 6.19607210e-01 -9.66930926e-01
-1.76003009e-01 1.08995378e+00 -1.01156592e-01 3.78483415e-01
1.67050675e-01 -1.26678020e-01 1.19493258e+00 -1.14769340e+00
2.55545706e-01 1.29978240e+00 3.29194337e-01 5.92736959e-01
-1.05073488e+00 -8.26018929e-01 6.85218796e-02 -1.44723011e-02
-1.19557261e+00 -1.06717825e+00 9.43321347e-01 -3.41535926e-01
1.30924892e+00 4.03347731e-01 4.06016797e-01 8.13762069e-01
3.30321759e-01 9.81260121e-01 7.30556607e-01 -7.68803000e-01
1.39256313e-01 7.72704408e-02 2.72847414e-01 1.07785180e-01
-3.69510889e-01 6.28988147e-02 -9.55381215e-01 2.55178452e-01
4.96871293e-01 -5.19334793e-01 -8.02987441e-02 3.20910335e-01
-8.12010050e-01 6.07861400e-01 -2.12097272e-01 4.90880042e-01
-4.84648168e-01 -1.84096664e-01 8.15831780e-01 3.75398219e-01
3.77311170e-01 -2.62993723e-01 -4.94928926e-01 -4.09391135e-01
-1.17675102e+00 1.91034228e-02 7.96839237e-01 1.26187289e+00
2.58875579e-01 5.11514664e-01 -3.83739829e-01 1.16483784e+00
5.10824740e-01 6.39046490e-01 7.43455231e-01 -2.32613966e-01
8.70744884e-01 3.34015697e-01 -2.47712553e-01 -3.71356368e-01
-2.13412464e-01 -4.82651919e-01 -6.35595620e-01 -1.59422010e-01
1.65952399e-01 -2.49570355e-01 -8.56351674e-01 1.82999039e+00
4.25271302e-01 -3.25471729e-01 1.95847616e-01 6.27206802e-01
8.57042909e-01 1.18105793e+00 4.04184014e-01 -5.37524343e-01
1.46679318e+00 -1.23760331e+00 -1.30625153e+00 -4.04491454e-01
4.43558335e-01 -1.36987984e+00 1.50624156e+00 1.00976899e-01
-1.48761785e+00 -8.82305145e-01 -1.09120667e+00 -4.12329674e-01
-4.24557447e-01 3.42346013e-01 -6.72639906e-02 7.23071098e-01
-8.18381727e-01 2.35755503e-01 -6.57458842e-01 -2.92441528e-02
-4.50418055e-01 1.53466821e-01 1.07781686e-01 4.90609288e-01
-1.38076067e+00 7.15187252e-01 6.04661286e-01 -2.91283559e-02
-4.58923250e-01 -5.54516792e-01 -9.06132936e-01 2.23479226e-01
3.30202758e-01 -3.85919720e-01 1.69793022e+00 -9.10792470e-01
-2.08562207e+00 5.64242303e-01 -5.72665453e-01 -3.32298487e-01
2.43142307e-01 -1.85442984e-01 -7.96854138e-01 -9.34209228e-02
-2.13534698e-01 3.62849474e-01 1.13091171e+00 -7.46780992e-01
-1.04333401e+00 -2.86430657e-01 -6.95086956e-01 5.59730053e-01
-4.54063714e-01 7.01727390e-01 -7.18436480e-01 -1.20567501e+00
1.52763113e-01 -7.63866127e-01 4.07698363e-01 -7.54691780e-01
-5.51600635e-01 -2.72553533e-01 7.57777393e-01 -1.16087198e+00
1.89939356e+00 -2.34962273e+00 1.34276286e-01 -1.88044850e-02
-3.66802037e-01 3.79803419e-01 4.37030196e-03 5.69759130e-01
-1.88798100e-01 -1.82712778e-01 -5.24590090e-02 -8.16730082e-01
2.86455274e-01 1.36150941e-01 -4.34741914e-01 -1.43829901e-02
7.02722445e-02 8.39673817e-01 -6.33143425e-01 -4.99161929e-01
6.22428417e-01 3.69123518e-01 -2.25289702e-01 3.60030174e-01
-6.71910644e-02 2.87987769e-01 -7.98495859e-02 4.69966948e-01
4.58839387e-01 6.85489655e-01 1.16823427e-01 8.89357924e-02
-5.82590997e-01 1.23598611e+00 -1.07744241e+00 1.34515285e+00
-5.56792557e-01 4.85728443e-01 4.18286264e-01 -4.98763859e-01
8.71665895e-01 7.26377130e-01 2.14684486e-01 -5.94354868e-01
4.80992854e-01 4.56758767e-01 2.08224192e-01 -1.53445482e-01
7.40809977e-01 -4.31048214e-01 -1.28571555e-01 -2.28387546e-02
1.43124267e-01 -3.10132533e-01 2.71673530e-01 -5.95232435e-02
7.06641018e-01 -2.06428573e-01 6.88342631e-01 -3.08446497e-01
9.41001832e-01 -2.59436518e-01 5.90998650e-01 2.28277355e-01
-2.22069874e-01 6.14488602e-01 1.85382634e-01 1.40560582e-01
-1.09391809e+00 -1.29907739e+00 1.18095346e-01 1.41668606e+00
-2.25124404e-01 -6.71757281e-01 -1.25511324e+00 -2.68828064e-01
-3.82878214e-01 1.20981908e+00 1.83312669e-02 -1.07841427e-03
-7.74493456e-01 -2.66595721e-01 7.96798229e-01 5.26527166e-01
1.32334575e-01 -1.38633978e+00 9.22667682e-02 7.27671981e-01
-3.89390409e-01 -1.42412460e+00 -1.14032853e+00 4.54705149e-01
-6.69763684e-01 -5.33912838e-01 -5.92740178e-01 -9.87823009e-01
9.89807546e-02 1.23249136e-01 6.89924955e-01 -4.61898804e-01
3.71969372e-01 -2.43426874e-01 -5.06231189e-01 -6.77482188e-01
-1.16545796e+00 2.66611069e-01 7.90906474e-02 2.07473323e-01
4.30400789e-01 -4.03631359e-01 -6.51545823e-02 1.79691106e-01
-8.21937084e-01 3.15922856e-01 4.46654260e-01 4.74284619e-01
8.74279857e-01 1.29061341e-01 5.45947909e-01 -7.74308145e-01
6.97247028e-01 -7.19047859e-02 -6.92772508e-01 9.95085016e-02
-2.48277053e-01 -2.59021372e-01 1.24982238e+00 -4.08922285e-01
-1.26985133e+00 2.67070502e-01 -8.83065283e-01 -1.47396386e-01
-1.32363588e-01 4.34037179e-01 -8.41899693e-01 2.70221740e-01
1.57065034e-01 5.85469425e-01 -3.48588705e-01 -7.14833319e-01
2.72190154e-01 1.27255428e+00 7.92910039e-01 -3.37164670e-01
7.84585476e-01 -1.82143226e-01 -5.08578062e-01 -1.41115379e+00
-7.42037892e-01 -8.06034625e-01 -5.88452220e-01 -1.96507350e-01
7.72738934e-01 -1.09481001e+00 -4.26167667e-01 6.31869256e-01
-1.30239463e+00 -8.05015117e-02 -5.00478923e-01 6.60539329e-01
-5.78628480e-01 2.62579829e-01 -8.63794863e-01 -8.81161034e-01
-6.57777071e-01 -1.17434180e+00 8.75044525e-01 2.89849132e-01
-3.12809438e-01 -6.55953348e-01 2.43640086e-03 5.03051281e-01
4.08583432e-01 -5.10593951e-01 1.03355205e+00 -7.59360731e-01
-4.50734049e-02 6.40293062e-02 8.92851576e-02 9.46969509e-01
2.55403310e-01 3.99763621e-02 -1.32889795e+00 -6.08907640e-02
3.94996673e-01 1.38549343e-01 6.34092391e-01 5.65980554e-01
6.06819570e-01 -3.09709460e-01 2.03479156e-01 5.65296173e-01
8.63848925e-01 7.33001471e-01 6.20629668e-01 -8.99958387e-02
7.15634227e-01 6.56870842e-01 5.36058843e-01 2.57208765e-01
5.40556967e-01 6.51322305e-01 -2.29871948e-03 -1.51069939e-01
-6.04808092e-01 -3.72117013e-01 1.07111502e+00 2.14506316e+00
5.31216383e-01 -6.02646351e-01 -7.80642748e-01 4.70400542e-01
-1.63541281e+00 -5.70487678e-01 -2.06573859e-01 2.13864207e+00
1.03119218e+00 4.44502324e-01 2.27216855e-01 5.99683046e-01
1.01473367e+00 3.64388585e-01 -3.26021135e-01 -8.19657266e-01
-1.27154276e-01 1.81218758e-01 1.81662574e-01 6.67534888e-01
-1.00009608e+00 1.51769388e+00 6.16645384e+00 1.47473490e+00
-1.13717723e+00 4.60308045e-02 1.35631815e-01 1.06934637e-01
-3.39917749e-01 -4.85948287e-02 -1.21003497e+00 3.74926746e-01
1.27188182e+00 -1.54285103e-01 6.69268191e-01 8.10517132e-01
5.84018052e-01 1.98444217e-01 -9.86704826e-01 1.05157423e+00
-1.50469482e-01 -7.84049630e-01 2.21454352e-01 -2.50787735e-01
3.89531940e-01 8.39325711e-02 -1.36525497e-01 4.62638319e-01
-1.01237938e-01 -4.50536758e-01 1.32018256e+00 -1.61681306e-02
8.03786337e-01 -9.95635986e-01 4.17128772e-01 3.51755619e-01
-1.71923208e+00 2.41092831e-01 -6.02684841e-02 7.55045712e-02
4.85040814e-01 5.92956960e-01 -9.73432004e-01 5.44494271e-01
1.83637708e-01 2.61517316e-01 -2.82648690e-02 6.24858499e-01
-4.63894576e-01 1.07724071e+00 -2.88646787e-01 -9.78033021e-02
1.90796420e-01 -2.08742946e-01 8.75494957e-01 1.77568996e+00
2.72440672e-01 3.36773158e-03 -2.16142591e-02 6.12930357e-01
-1.56408623e-01 8.48514020e-01 -6.51546717e-02 -5.03671467e-01
6.82337701e-01 1.06613731e+00 -7.10503399e-01 -3.81085992e-01
-5.94450831e-01 7.80698359e-01 7.38512129e-02 2.75273502e-01
-7.15442777e-01 -7.21463382e-01 9.36183810e-01 1.45363780e-02
3.47132057e-01 -3.93733114e-01 -3.48797619e-01 -1.02810490e+00
1.42050385e-01 -9.51851845e-01 2.44499713e-01 -5.83596706e-01
-1.12792671e+00 7.94306576e-01 -3.02821994e-01 -1.03297520e+00
-4.77477401e-01 -4.79706556e-01 -5.81324100e-01 1.17765689e+00
-1.77332091e+00 -1.14331019e+00 2.55885422e-01 6.22729957e-01
1.11422491e+00 -2.50979960e-01 6.67631388e-01 4.22510833e-01
-7.18245268e-01 6.95547581e-01 1.90668464e-01 2.65177697e-01
5.26537597e-01 -1.18448162e+00 9.03822243e-01 1.29696441e+00
2.80008733e-01 4.69287723e-01 5.14216781e-01 -6.53790772e-01
-1.19829440e+00 -1.15844393e+00 1.46349597e+00 2.73392946e-01
6.23562157e-01 -6.25382781e-01 -7.91404545e-01 5.11407673e-01
2.65159607e-01 -3.90713394e-01 6.18324041e-01 -1.08267769e-01
-3.14916596e-02 -2.28044555e-01 -6.72374845e-01 8.92292559e-01
6.60906851e-01 -9.45915520e-01 -8.22704554e-01 -3.50713015e-01
9.74769533e-01 -5.68395078e-01 -5.99980652e-01 2.06931323e-01
3.96814495e-01 -7.88546801e-01 6.89535201e-01 -2.25653961e-01
-1.49937849e-02 -5.22535801e-01 -4.40319449e-01 -1.32250738e+00
-1.17325455e-01 -1.06851482e+00 -3.14368308e-02 1.72103333e+00
5.03517747e-01 -2.82237142e-01 2.61153370e-01 1.74824193e-01
-7.36598670e-01 -9.74242613e-02 -9.76364076e-01 -9.29662824e-01
-1.75678775e-01 -1.05738485e+00 6.41343415e-01 6.55375361e-01
1.68311983e-01 8.15329373e-01 -2.35899419e-01 1.86726227e-01
3.30538005e-01 -2.20336273e-01 5.88296592e-01 -8.23253512e-01
-2.27866203e-01 -6.23355687e-01 7.73163438e-02 -1.24537575e+00
1.12050585e-01 -9.85390902e-01 4.31107581e-01 -1.14363861e+00
-2.62580782e-01 -6.00343831e-02 -4.42947358e-01 3.22045535e-01
-2.78137952e-01 -2.87526071e-01 4.55114692e-01 -9.19117555e-02
-1.06325172e-01 8.14545035e-01 1.05169189e+00 1.10695221e-01
-7.92306721e-01 1.46288887e-01 -4.16420192e-01 9.54587817e-01
8.61887217e-01 -7.50254154e-01 -3.90283316e-01 -3.86464506e-01
-3.92271310e-01 3.41176569e-01 -4.10852820e-01 -1.03340054e+00
4.86668855e-01 -1.67037711e-01 -4.34121527e-02 -1.06063020e+00
5.07817149e-01 -6.26786649e-01 -1.13317601e-01 2.27436796e-01
-1.90671995e-01 5.60177155e-02 4.69494939e-01 -4.00756933e-02
-7.28250563e-01 -3.05214852e-01 9.86767709e-01 2.58578598e-01
-4.56540436e-01 4.81769703e-02 -7.91462898e-01 4.03315574e-01
6.62861168e-01 -1.51141435e-01 8.97809938e-02 -3.10300052e-01
-4.89025712e-01 -4.58082557e-02 -3.83673497e-02 6.33680165e-01
4.88679469e-01 -1.19903696e+00 -6.73005581e-01 5.46955943e-01
2.26324573e-02 -2.55432397e-01 5.90293966e-02 4.40784186e-01
-3.09556901e-01 6.19909465e-01 6.90037683e-02 -1.93961695e-01
-1.39300442e+00 3.15332830e-01 1.09174885e-01 -1.83225185e-01
-2.96078652e-01 7.96770871e-01 3.08931082e-01 -3.85506809e-01
6.11090839e-01 -6.69818819e-01 -8.00978169e-02 8.48436803e-02
5.82212508e-01 5.19884169e-01 2.99759984e-01 -1.07346749e+00
-4.77129161e-01 3.71279180e-01 -8.64375308e-02 -6.84049785e-01
9.75796223e-01 -4.23957944e-01 9.26650092e-02 6.76384211e-01
9.75570440e-01 4.27597016e-01 -8.54632616e-01 -2.80368567e-01
2.30116501e-01 1.19766153e-01 4.03731287e-01 -6.33568823e-01
-7.40835905e-01 1.14246893e+00 -1.67151004e-01 1.17333025e-01
1.28050661e+00 -4.35181916e-01 1.38802469e+00 1.85132444e-01
-9.75017473e-02 -1.71274340e+00 -3.98143739e-01 1.12851691e+00
9.13648069e-01 -8.14058423e-01 -5.76771736e-01 -7.12877810e-01
-7.57714033e-01 1.21521473e+00 2.92419612e-01 2.87746102e-01
8.61698747e-01 6.70962870e-01 3.34056616e-01 4.13431853e-01
-7.57893860e-01 -2.61809230e-01 5.59716880e-01 1.67658091e-01
7.22509325e-01 2.10004136e-01 -3.71835083e-01 9.86954927e-01
-6.77316964e-01 -2.86588460e-01 1.84067801e-01 6.73608303e-01
-5.82364440e-01 -1.42116523e+00 -4.48798507e-01 -6.36248738e-02
-6.38146639e-01 -6.81446254e-01 -4.49620515e-01 5.62215328e-01
-6.64436668e-02 1.22745502e+00 -1.08274713e-01 -6.21168196e-01
7.01455891e-01 5.56994915e-01 1.36299178e-01 -7.55246997e-01
-1.05398142e+00 9.33791041e-01 1.83923125e-01 -3.18190396e-01
1.24968521e-01 -6.42005563e-01 -1.54950774e+00 -2.28126362e-01
-3.83482933e-01 1.18208162e-01 9.41208124e-01 9.34521019e-01
2.12230836e-03 8.26745033e-01 7.44042873e-01 -5.23321211e-01
-3.75063539e-01 -1.06154430e+00 -8.15847754e-01 1.04180090e-01
3.65005404e-01 -4.85827066e-02 -2.55794257e-01 2.39690110e-01] | [14.734979629516602, 6.722599029541016] |
3fb1234e-747d-4b45-ae2d-c034949859ec | sleeppriorcl-contrastive-representation | 2110.09966 | null | https://arxiv.org/abs/2110.09966v1 | https://arxiv.org/pdf/2110.09966v1.pdf | SleepPriorCL: Contrastive Representation Learning with Prior Knowledge-based Positive Mining and Adaptive Temperature for Sleep Staging | The objective of this paper is to learn semantic representations for sleep stage classification from raw physiological time series. Although supervised methods have gained remarkable performance, they are limited in clinical situations due to the requirement of fully labeled data. Self-supervised learning (SSL) based on contrasting semantically similar (positive) and dissimilar (negative) pairs of samples have achieved promising success. However, existing SSL methods suffer the problem that many semantically similar positives are still uncovered and even treated as negatives. In this paper, we propose a novel SSL approach named SleepPriorCL to alleviate the above problem. Advances of our approach over existing SSL methods are two-fold: 1) by incorporating prior domain knowledge into the training regime of SSL, more semantically similar positives are discovered without accessing ground-truth labels; 2) via investigating the influence of the temperature in contrastive loss, an adaptive temperature mechanism for each sample according to prior domain knowledge is further proposed, leading to better performance. Extensive experiments demonstrate that our method achieves state-of-the-art performance and consistently outperforms baselines. | ['Youfang Lin', 'Jiaoxue Deng', 'Qinfeng Xiao', 'Jing Wang', 'Hongjun Zhang'] | 2021-10-15 | null | null | null | null | ['sleep-staging'] | ['medical'] | [ 4.17847961e-01 -2.69918442e-02 -4.08203274e-01 -7.08272159e-01
-7.31812239e-01 -2.06089944e-01 2.81802654e-01 5.33613265e-01
-4.31101680e-01 1.00496304e+00 2.39107877e-01 2.36050576e-01
-7.16197640e-02 -4.05549198e-01 -4.41600084e-01 -8.40058506e-01
3.14171538e-02 2.55968362e-01 2.13572085e-01 -1.22806676e-01
2.33699098e-01 1.71720877e-01 -1.52364039e+00 2.76203305e-01
9.42757666e-01 1.08938742e+00 1.93187490e-01 -4.35789339e-02
-1.78696141e-01 5.06888807e-01 -5.54599285e-01 1.25141144e-01
1.12104602e-01 -6.81801200e-01 -9.45183516e-01 -2.97621608e-01
-1.89439952e-01 1.12023965e-01 1.34631708e-01 1.10423362e+00
7.67779768e-01 1.89369872e-01 4.49753165e-01 -1.22225118e+00
-4.16353941e-01 2.59014904e-01 -6.55175328e-01 4.76985961e-01
3.47007483e-01 -1.29832238e-01 8.81657064e-01 -6.21900082e-01
3.24103385e-01 8.78610075e-01 6.56734526e-01 1.01558602e+00
-1.40623641e+00 -8.86549711e-01 5.21011576e-02 4.11659598e-01
-1.23466063e+00 -5.97505629e-01 1.02410221e+00 -1.03895776e-01
8.82053673e-01 1.11335650e-01 6.73788190e-01 1.19338906e+00
1.82906240e-01 8.35318089e-01 1.47126830e+00 -3.71094525e-01
6.82206392e-01 3.13149989e-01 3.09319884e-01 5.58960855e-01
1.08136430e-01 1.28512559e-02 -7.61777401e-01 -2.87960857e-01
2.28876963e-01 1.94687009e-01 -4.45492357e-01 -4.78223920e-01
-9.99555528e-01 6.28604412e-01 7.07299769e-01 5.38728416e-01
-3.00743937e-01 -2.66941249e-01 6.17842972e-01 7.99867436e-02
7.75812149e-01 6.45513415e-01 -4.35937881e-01 -7.35103860e-02
-1.21074200e+00 2.25599273e-03 4.52475101e-01 4.53456700e-01
6.27796710e-01 -2.19399154e-01 -1.81059897e-01 9.16521311e-01
-5.55600272e-04 1.88595876e-01 1.11314523e+00 -4.68440950e-01
1.96891859e-01 8.60215783e-01 -4.06243745e-03 -7.76215732e-01
-7.61743486e-01 -6.32796109e-01 -7.31339931e-01 -1.39868572e-01
3.03732064e-02 2.29059860e-01 -9.41569269e-01 1.75223517e+00
7.77366832e-02 3.49181563e-01 3.23077023e-01 9.87793386e-01
9.62306559e-01 3.64153057e-01 3.29324573e-01 -4.51998085e-01
1.25393093e+00 -8.34446847e-01 -8.61982882e-01 -4.57393527e-01
5.56599855e-01 -2.89416999e-01 1.13432992e+00 3.05260628e-01
-9.99450922e-01 -3.01130563e-01 -1.08581269e+00 7.21977577e-02
-2.99831241e-01 6.43869489e-02 5.02993941e-01 5.88953018e-01
-1.04225290e+00 7.87923753e-01 -1.07354391e+00 -5.89201450e-01
7.83062100e-01 6.11191332e-01 -1.64128840e-01 1.36320651e-01
-1.12457597e+00 7.25783467e-01 1.57721594e-01 3.91885974e-02
-6.42953813e-01 -6.91902697e-01 -8.09455454e-01 3.41100059e-02
2.28113439e-02 -4.92401063e-01 8.87480199e-01 -1.07719266e+00
-1.24216998e+00 1.15481567e+00 -6.16951406e-01 -5.04841328e-01
1.35578319e-01 -1.09960526e-01 -4.18090403e-01 4.05831367e-01
2.55783409e-01 8.29172075e-01 7.46218145e-01 -1.18330467e+00
-1.81000262e-01 -6.68237627e-01 -2.21897259e-01 2.75839686e-01
-6.55479670e-01 -1.24793440e-01 -8.52050167e-03 -5.95840514e-01
3.34231704e-01 -7.61712551e-01 -2.88125515e-01 1.40524313e-01
-2.32882991e-01 -3.64330143e-01 6.01947546e-01 -2.52083004e-01
9.34238732e-01 -2.32215667e+00 -8.55148956e-02 -2.93624997e-02
3.09409678e-01 4.13253099e-01 1.33005027e-02 1.52492216e-02
-2.23885745e-01 -1.58102494e-02 -4.06545907e-01 -4.88324374e-01
-4.83739167e-01 1.64452583e-01 -2.86654264e-01 4.91542786e-01
3.77241135e-01 7.87117302e-01 -1.21147025e+00 -6.52071118e-01
1.34135708e-01 2.64257580e-01 -3.75179827e-01 2.09886327e-01
8.65682513e-02 6.27155066e-01 -4.38928008e-01 6.20215118e-01
5.26752949e-01 -4.20933932e-01 7.02607334e-02 -2.57037550e-01
2.22453684e-01 5.94540715e-01 -4.75239992e-01 2.03195977e+00
-2.22136304e-01 1.53123036e-01 -2.66897172e-01 -1.50117922e+00
1.08786690e+00 2.70046622e-01 7.14099050e-01 -9.99488533e-01
6.35981038e-02 1.43653214e-01 -1.80078238e-01 -4.61122304e-01
1.80299625e-01 -7.28621423e-01 1.12894334e-01 3.26133847e-01
-5.59617020e-02 1.27152786e-01 -2.90802181e-01 -2.36702766e-02
1.04900122e+00 2.35915959e-01 4.68457252e-01 -5.72049856e-01
3.72564673e-01 3.25650536e-02 9.57260430e-01 4.48105425e-01
-8.03506911e-01 5.34506500e-01 2.94836164e-01 -3.48616660e-01
-4.36150342e-01 -1.22261333e+00 -2.98011392e-01 5.44802427e-01
5.17395198e-01 -3.68439287e-01 -6.72977567e-01 -7.31684089e-01
-3.79701465e-01 5.40992081e-01 -7.07995653e-01 -7.29534566e-01
-3.04305583e-01 -1.16020906e+00 3.88157994e-01 7.99714565e-01
5.10188937e-01 -1.21929598e+00 -8.06302249e-01 9.58830714e-02
-4.76550907e-01 -9.63046014e-01 -1.15574092e-01 4.81621951e-01
-1.37237298e+00 -8.62660706e-01 -5.56269825e-01 -7.24315166e-01
7.87497759e-01 4.05099660e-01 8.59870970e-01 -6.41620951e-03
-5.76188624e-01 8.69087651e-02 -4.66693044e-01 -5.41004658e-01
2.14748289e-02 -8.29045326e-02 2.90349841e-01 -1.47215975e-02
7.52692521e-01 -6.83960676e-01 -1.05642796e+00 2.03280717e-01
-6.69463813e-01 -1.06509298e-01 5.14707923e-01 8.05426478e-01
8.27784717e-01 -8.21845233e-02 1.08286834e+00 -8.27248812e-01
3.77690643e-01 -5.53620160e-01 -3.67858884e-04 8.40456411e-02
-9.94639218e-01 2.20187724e-01 7.07093775e-01 -3.57316971e-01
-9.15416002e-01 -3.56426984e-02 -5.92447743e-02 -5.03586233e-01
-2.88920611e-01 1.58066615e-01 5.98832220e-02 1.04065247e-01
7.61591196e-01 4.33713496e-01 1.68188229e-01 -3.83537710e-01
-1.67368427e-01 6.12445533e-01 4.18834448e-01 -4.13860261e-01
3.44018161e-01 9.07240987e-01 -1.32008016e-01 -6.63971186e-01
-1.24003899e+00 -8.12231302e-01 -4.05383348e-01 -1.46032928e-03
8.47623885e-01 -1.00246441e+00 -4.96598214e-01 2.34235734e-01
-4.11349893e-01 -2.45009735e-01 -5.05240262e-01 6.40655756e-01
-5.00592768e-01 3.79442841e-01 -3.79006773e-01 -7.79902697e-01
-6.67777717e-01 -1.00738072e+00 1.12613463e+00 2.95600444e-01
-4.87090319e-01 -9.74641860e-01 3.84698696e-02 5.30547619e-01
3.60260904e-01 4.51521538e-02 9.21253562e-01 -8.47117960e-01
-2.40790076e-03 -6.28588349e-02 -9.79924053e-02 3.77774775e-01
5.68942904e-01 -7.43094981e-01 -1.17782390e+00 -4.35536414e-01
3.97424847e-01 -6.02397442e-01 8.67148340e-01 2.87910819e-01
1.49276829e+00 8.31492990e-02 -6.36099160e-01 4.72569317e-01
1.26641870e+00 6.27369387e-03 6.25646532e-01 3.21059555e-01
3.00567985e-01 6.01505160e-01 6.49412870e-01 3.99937510e-01
3.84069055e-01 4.04218793e-01 3.53825152e-01 -2.71627128e-01
-2.84768548e-02 -3.78714986e-02 3.22456419e-01 7.20532835e-01
1.91648379e-01 8.56184587e-02 -5.73562920e-01 7.22940862e-01
-1.65644622e+00 -7.48990536e-01 7.70216137e-02 2.39083982e+00
8.80613267e-01 2.30457246e-01 1.73497096e-01 4.52853590e-01
5.17150044e-01 1.08014077e-01 -8.54724228e-01 -9.54406857e-02
6.32983074e-02 5.80252945e-01 8.67556036e-02 -9.69036669e-02
-8.83916855e-01 6.77801192e-01 6.08162498e+00 7.09583998e-01
-1.37415993e+00 2.34516814e-01 6.68186069e-01 -4.17746693e-01
-2.00882912e-01 -2.06263468e-01 -6.40473247e-01 5.44752181e-01
8.27031612e-01 3.54667497e-03 3.90041500e-01 6.56331480e-01
4.16499645e-01 -2.01360956e-01 -1.01501942e+00 1.22234094e+00
2.65469283e-01 -9.19642746e-01 -3.11132848e-01 -2.94331431e-01
3.96969765e-01 5.01815639e-02 -1.16565317e-01 2.70605862e-01
-2.18673736e-01 -7.59487867e-01 4.34827089e-01 4.23431844e-01
6.69994056e-01 -4.49321538e-01 6.62167311e-01 1.70288220e-01
-9.07666266e-01 -8.94928426e-02 -3.98920417e-01 -5.83618097e-02
-2.83906490e-01 7.64136136e-01 -7.31529355e-01 6.05756521e-01
1.09427202e+00 1.06005013e+00 -5.73743284e-01 9.97660041e-01
-1.41737759e-01 9.67374146e-01 -2.23670542e-01 -7.26315454e-02
-2.40637213e-02 7.50207603e-02 2.83103615e-01 8.36046219e-01
-6.13282919e-02 1.01725638e-01 1.40171900e-01 1.05823886e+00
-4.85676378e-02 1.40025750e-01 -3.42813075e-01 -9.23211919e-04
3.07557791e-01 1.14540970e+00 -9.91112292e-01 -2.32106313e-01
-2.71935344e-01 1.13872123e+00 4.26604241e-01 1.03756770e-01
-4.81596977e-01 -1.64406285e-01 5.33673584e-01 1.69696063e-01
-4.70250882e-02 3.09743673e-01 -5.12883484e-01 -1.15676272e+00
2.11273760e-01 -3.62929314e-01 5.52315474e-01 -6.87776268e-01
-1.60568857e+00 4.70648050e-01 -1.29633799e-01 -1.33788931e+00
2.37512231e-01 -2.08957568e-01 -5.97338796e-01 5.44445932e-01
-1.84130919e+00 -7.03832150e-01 -3.56547743e-01 6.59624755e-01
5.06228209e-01 1.11500911e-01 1.01129174e+00 3.44503343e-01
-5.28197825e-01 6.64300799e-01 -2.20501199e-02 -1.92667395e-01
8.70865166e-01 -1.27423692e+00 -3.17377076e-02 4.25192386e-01
-1.37452036e-01 6.19782627e-01 4.61907506e-01 -5.26646554e-01
-8.89911115e-01 -1.05076241e+00 9.63816464e-01 -1.59322739e-01
3.68091613e-01 -3.66110116e-01 -1.09892321e+00 2.38686144e-01
-2.08539426e-01 2.15983421e-01 1.04789424e+00 1.91963285e-01
-1.93648413e-01 -4.53233778e-01 -1.35862112e+00 2.64112025e-01
1.00791907e+00 -5.27092576e-01 -7.64459908e-01 4.89473343e-01
4.22058105e-01 -1.80468380e-01 -5.83853781e-01 5.15081882e-01
2.62746900e-01 -9.40422356e-01 8.01913381e-01 -4.65791941e-01
2.83743739e-01 -3.30479085e-01 1.40570447e-01 -1.28505421e+00
-4.05454822e-02 -2.38259852e-01 4.54169922e-02 1.00693834e+00
1.11679249e-01 -6.13698184e-01 9.15607512e-01 4.28530455e-01
-2.76374221e-01 -1.03451002e+00 -8.99499416e-01 -9.13200855e-01
-3.12872827e-02 -1.23457871e-01 3.96630853e-01 1.00590181e+00
4.36443895e-01 3.79625678e-01 -1.49107352e-01 3.03468332e-02
5.54665148e-01 3.77723634e-01 4.51773629e-02 -1.30960774e+00
-5.21521047e-02 -9.95047688e-02 -5.11841834e-01 -6.16726995e-01
2.78118670e-01 -1.12565064e+00 3.04667294e-01 -1.52383339e+00
6.83985651e-01 -5.97256422e-01 -8.96273911e-01 7.87651181e-01
-4.58044201e-01 4.80120063e-01 -1.78988948e-01 3.71254742e-01
-9.11750793e-01 7.19699204e-01 8.96752238e-01 9.36858356e-02
-3.34239602e-01 -1.12606101e-02 -8.32061768e-01 5.38381875e-01
9.38348830e-01 -7.38586426e-01 -6.37603045e-01 -6.42661229e-02
-8.25113580e-02 -8.29744488e-02 4.25099611e-01 -1.14251912e+00
-7.81716704e-02 2.13230446e-01 3.88579339e-01 -3.07644278e-01
4.15768385e-01 -5.04739165e-01 -4.25982088e-01 5.74846685e-01
-4.30868864e-01 -2.62050658e-01 1.47500411e-01 6.65820658e-01
-1.41317934e-01 -1.50964350e-01 1.03079665e+00 -1.19610302e-01
-5.91018617e-01 6.39639348e-02 -2.44235769e-01 2.35653520e-01
9.46777344e-01 -2.62635171e-01 -1.80791125e-01 -1.43344775e-01
-7.62361765e-01 1.76457748e-01 4.51626092e-01 4.18050557e-01
7.20889211e-01 -1.01067567e+00 -2.13675410e-01 2.59038746e-01
4.15634990e-01 -3.80816683e-02 1.78273112e-01 1.08136880e+00
6.19013309e-02 2.35353649e-01 -1.76581874e-01 -7.42932737e-01
-1.15348792e+00 6.19840920e-01 2.39181355e-01 -3.11784953e-01
-7.11744070e-01 8.43274415e-01 3.52859825e-01 -3.06625783e-01
2.14842036e-01 -1.87849790e-01 -1.47235423e-01 -9.95733216e-02
5.35622180e-01 1.26763791e-01 4.41283166e-01 -2.99968868e-01
-7.27717936e-01 4.08554643e-01 -1.97683305e-01 4.11105394e-01
1.52567852e+00 -5.35647422e-02 -2.05937978e-02 5.82300305e-01
1.17797792e+00 -3.94743532e-01 -9.42110956e-01 -1.95773989e-01
-3.92028652e-02 -1.60924345e-01 4.63652462e-02 -8.84080887e-01
-1.07094479e+00 1.03279352e+00 1.12118030e+00 -2.66033649e-01
1.50370085e+00 1.33085802e-01 1.05699241e+00 2.19906807e-01
3.98883551e-01 -9.97586131e-01 3.87032121e-01 -1.82288900e-01
2.10144147e-01 -1.35564363e+00 6.31293654e-02 -2.83836126e-01
-6.63962901e-01 7.24161267e-01 5.20099699e-01 -1.04204386e-01
4.68061805e-01 2.08786502e-02 1.01714931e-01 -4.29884166e-01
-5.43821633e-01 -1.92653090e-01 8.21613595e-02 5.63663542e-01
3.75844926e-01 -7.46475160e-02 -4.97366458e-01 8.09623361e-01
-1.87595338e-02 2.84713954e-01 2.61452049e-01 1.14607942e+00
-2.29451194e-01 -1.04342067e+00 4.03380394e-02 7.84938276e-01
-6.98610365e-01 -1.70712203e-01 -3.48453462e-01 2.83426553e-01
2.08872557e-02 1.07948208e+00 -4.72745625e-03 -2.95070976e-01
1.67419851e-01 1.43013999e-01 5.15829623e-01 -7.40861654e-01
-5.98227620e-01 -3.62262428e-02 -2.68857926e-01 -6.39905155e-01
-7.59272099e-01 -6.36633694e-01 -1.65850782e+00 3.70695889e-01
-4.16213632e-01 3.76403689e-01 5.87677360e-01 1.12648189e+00
5.57946920e-01 5.15788317e-01 6.20476484e-01 -6.46353960e-01
-4.33681905e-01 -6.45723999e-01 -6.27415478e-01 7.42176056e-01
4.34898794e-01 -8.71739984e-01 -3.48707139e-01 2.11194400e-02] | [13.374597549438477, 3.4759485721588135] |
c4358b79-c20b-43ce-9bc7-3d7f8650c409 | segment-anything-in-non-euclidean-domains | 2304.11595 | null | https://arxiv.org/abs/2304.11595v1 | https://arxiv.org/pdf/2304.11595v1.pdf | Segment Anything in Non-Euclidean Domains: Challenges and Opportunities | The recent work known as Segment Anything (SA) has made significant strides in pushing the boundaries of semantic segmentation into the era of foundation models. The impact of SA has sparked extremely active discussions and ushered in an encouraging new wave of developing foundation models for the diverse tasks in the Euclidean domain, such as object detection and image inpainting. Despite the promising advances led by SA, the concept has yet to be extended to the non-Euclidean graph domain. In this paper, we explore a novel Segment Non-Euclidean Anything (SNA) paradigm that strives to develop foundation models that can handle the diverse range of graph data within the non-Euclidean domain, seeking to expand the scope of SA and lay the groundwork for future research in this direction. To achieve this goal, we begin by discussing the recent achievements in foundation models associated with SA. We then shed light on the unique challenges that arise when applying the SA concept to graph analysis, which involves understanding the differences between the Euclidean and non-Euclidean domains from both the data and task perspectives. Motivated by these observations, we present several preliminary solutions to tackle the challenges of SNA and detail their corresponding limitations, along with several potential directions to pave the way for future SNA research. Experiments on five Open Graph Benchmark (OGB) datasets across various tasks, including graph property classification and regression, as well as multi-label prediction, demonstrate that the performance of the naive SNA solutions has considerable room for improvement, pointing towards a promising avenue for future exploration of Graph General Intelligence. | ['DaCheng Tao', 'Xinchao Wang', 'Yongcheng Jing'] | 2023-04-23 | null | null | null | null | ['image-inpainting'] | ['computer-vision'] | [ 7.41923690e-01 2.98638552e-01 -2.78297096e-01 -4.63694990e-01
-3.67642343e-01 -5.42262137e-01 5.09788036e-01 1.96153671e-01
9.66698602e-02 2.28986621e-01 2.45134272e-02 -4.66916829e-01
-6.11254394e-01 -9.33210611e-01 -5.20303369e-01 -6.99353516e-01
-2.22190320e-01 4.68541503e-01 9.16629732e-02 -2.81954825e-01
2.79059470e-01 6.50528550e-01 -1.41375768e+00 1.81353793e-01
5.97574294e-01 8.94189000e-01 -1.04084410e-01 4.63721067e-01
-1.12359887e-02 6.60034657e-01 -2.94670939e-01 -6.82041943e-01
2.64625847e-01 -4.37222749e-01 -1.04653943e+00 5.42538524e-01
7.07860708e-01 2.37622574e-01 -4.11892861e-01 1.02869105e+00
2.64641017e-01 3.03458273e-01 5.13911605e-01 -1.65737832e+00
-9.88790274e-01 4.50676441e-01 -6.36416614e-01 8.27863738e-02
3.14836740e-01 -1.15242921e-01 1.36282945e+00 -5.61244488e-01
7.82365084e-01 1.14294863e+00 1.03926086e+00 4.77885216e-01
-1.19468403e+00 -1.04476914e-01 4.24125075e-01 3.26849312e-01
-1.31608152e+00 -9.49065834e-02 1.00149238e+00 -2.35674441e-01
1.03108978e+00 3.72059733e-01 5.86263239e-01 1.03945708e+00
6.96222037e-02 9.37527359e-01 1.31594372e+00 -5.24442554e-01
-1.09066721e-02 -2.66873837e-01 3.81352425e-01 1.06308699e+00
2.82030582e-01 -1.02135524e-01 -5.47122657e-01 6.98893741e-02
5.89828491e-01 -3.03593069e-01 -2.17667505e-01 -7.84473062e-01
-1.20761490e+00 9.57175016e-01 5.12902737e-01 2.83632368e-01
-1.28606020e-03 -1.64673217e-02 3.69408965e-01 3.68977755e-01
7.18423665e-01 6.50542438e-01 -1.45727947e-01 1.23381995e-01
-8.33466351e-01 3.86523187e-01 8.03623855e-01 1.15070426e+00
6.26612127e-01 -1.04229905e-01 1.02419220e-01 7.87673533e-01
1.44418657e-01 1.28463572e-02 -2.13623539e-01 -8.80232871e-01
4.30073470e-01 6.85560584e-01 -3.30000937e-01 -1.39549649e+00
-7.61777222e-01 -5.58701694e-01 -6.36534154e-01 1.56464294e-01
7.11287498e-01 2.99234629e-01 -8.37359607e-01 1.64436531e+00
3.55628729e-01 1.18244186e-01 -1.90626353e-01 7.19745517e-01
7.92566299e-01 3.64157677e-01 -1.34245083e-01 -1.48060815e-02
1.23991203e+00 -1.20654917e+00 -4.18095708e-01 -1.78277999e-01
8.58062744e-01 -6.47405505e-01 1.09874046e+00 5.31146646e-01
-1.01209342e+00 -4.44186866e-01 -1.19076943e+00 -3.68344247e-01
-6.20300412e-01 -4.42110956e-01 1.16591656e+00 7.85295606e-01
-1.28059340e+00 6.60008132e-01 -6.86236918e-01 -7.89430976e-01
5.62523425e-01 3.36694270e-01 -4.11066681e-01 -5.17052114e-01
-9.74899471e-01 9.28883255e-01 2.12701216e-01 1.41741425e-01
-4.14066166e-01 -4.95900899e-01 -9.15882766e-01 -9.71172303e-02
8.26240361e-01 -9.24154520e-01 7.21815765e-01 -8.99344504e-01
-9.77211654e-01 1.14452183e+00 2.01131240e-01 -4.84773695e-01
3.76400352e-01 2.94201612e-01 -4.17341560e-01 -5.75749669e-03
4.42166179e-02 5.86862504e-01 5.04989684e-01 -1.09431982e+00
-3.77394050e-01 -6.91557944e-01 3.26852143e-01 2.73710638e-01
-2.96823978e-01 8.43931362e-02 -4.17642921e-01 -9.12106633e-01
1.52955100e-01 -1.29233825e+00 -8.87459591e-02 -1.00147292e-01
-4.55553442e-01 -4.99172658e-01 6.77139759e-01 -2.03544170e-01
1.12399864e+00 -2.10358405e+00 4.73591238e-01 2.49388188e-01
5.35329461e-01 1.21962965e-01 -2.91104883e-01 7.41366386e-01
-2.33986899e-01 1.42802730e-01 -3.74653757e-01 -3.43358099e-01
-5.76720908e-02 2.73760051e-01 -1.69451758e-01 5.17475724e-01
1.96928248e-01 9.99218762e-01 -1.05735254e+00 -3.61582726e-01
8.04084763e-02 4.49621499e-01 -2.97861993e-01 -2.33126000e-01
-4.02076542e-01 2.47016221e-01 -5.62915146e-01 8.04837704e-01
6.73543513e-01 -5.01968265e-01 9.10325050e-02 -1.25243261e-01
2.08822358e-03 2.02966273e-01 -1.03566206e+00 1.86811304e+00
-1.09234173e-02 6.34721339e-01 2.27671087e-01 -1.41184354e+00
9.50911820e-01 -1.72324315e-01 7.48670280e-01 -5.37666678e-01
7.86020458e-02 2.61523537e-02 8.49560946e-02 -4.52179641e-01
5.91880798e-01 -1.93621233e-01 8.56091604e-02 3.56238157e-01
-5.27288802e-02 -3.27768713e-01 3.90864581e-01 3.36862624e-01
1.46791208e+00 2.71008700e-01 1.45505607e-01 -2.86025256e-01
3.77620876e-01 4.83229131e-01 2.26181448e-01 7.17725396e-01
-3.25113058e-01 5.44685900e-01 4.99429703e-01 -5.89106262e-01
-7.37950921e-01 -1.10924435e+00 -2.43358195e-01 1.01046312e+00
2.62986422e-01 -8.00862432e-01 -7.53923118e-01 -1.01056218e+00
2.50316799e-01 5.53241372e-01 -7.32336104e-01 -1.34389430e-01
-4.49688852e-01 -1.00715375e+00 4.86560911e-01 5.76727271e-01
5.11658907e-01 -8.60388041e-01 4.06608582e-02 1.27435014e-01
-4.65213843e-02 -1.37640226e+00 -2.35363424e-01 -2.55327132e-02
-9.45342124e-01 -1.18298304e+00 -4.78598624e-01 -9.39648092e-01
6.08473182e-01 7.73019850e-01 1.21837175e+00 2.51223445e-01
-4.34414893e-01 8.67448092e-01 -5.84253073e-01 -4.35341477e-01
-2.73529589e-01 1.34401456e-01 -3.49227160e-01 -4.32708003e-02
4.74364936e-01 -5.13525248e-01 -4.03118283e-01 4.34037924e-01
-9.56538856e-01 2.82520354e-01 2.87154764e-01 4.58592534e-01
6.64219499e-01 3.29020828e-01 6.19775116e-01 -1.18015230e+00
6.78761899e-01 -6.65636480e-01 -4.37906325e-01 3.30043703e-01
-9.84823167e-01 -9.05689895e-02 3.57740700e-01 -1.43515849e-02
-6.16927683e-01 -2.56991535e-01 2.57198904e-02 -6.54141381e-02
8.56567249e-02 7.63002276e-01 3.00722066e-02 -4.75360185e-01
5.78299105e-01 -1.64693370e-01 7.85373673e-02 -4.31465238e-01
6.05591536e-01 4.12011653e-01 4.27165508e-01 -6.82599306e-01
6.81636631e-01 6.24307811e-01 7.19946027e-01 -9.17072952e-01
-1.00901949e+00 -5.43966949e-01 -5.28556466e-01 -2.26793364e-01
9.81811941e-01 -4.85578090e-01 -3.33795100e-01 4.52864319e-01
-8.32383990e-01 -3.41173112e-01 -3.20109576e-01 9.51452404e-02
-7.88893342e-01 7.02625453e-01 -5.10710120e-01 -4.68562186e-01
3.48777138e-02 -1.13476336e+00 9.71828163e-01 1.10622859e-02
-2.20417216e-01 -1.36114514e+00 -5.07136285e-02 9.32853699e-01
1.00619942e-01 5.35156667e-01 1.24812281e+00 -5.91862082e-01
-8.29871953e-01 -2.10819468e-01 -3.79946291e-01 3.99766713e-01
-3.25698568e-03 -1.12975709e-01 -6.49002850e-01 -3.19361359e-01
8.77243932e-03 -3.92311752e-01 9.70517695e-01 1.87355831e-01
1.20239389e+00 3.07887584e-01 -3.58229458e-01 8.39379847e-01
1.42906868e+00 -1.68538362e-01 5.17771900e-01 4.23530340e-01
1.02499366e+00 8.16597819e-01 7.72093236e-01 1.10706240e-02
7.16606796e-01 7.09433913e-01 6.99748218e-01 -1.26490325e-01
-6.83729351e-01 -2.33209193e-01 -7.06381947e-02 7.75143087e-01
-3.68327409e-01 -5.87371290e-01 -9.64084327e-01 4.93479103e-01
-1.92751288e+00 -8.52456927e-01 -5.72497368e-01 2.03827667e+00
3.34199905e-01 6.00742437e-02 2.93013245e-01 2.40774989e-01
7.20485032e-01 4.89145756e-01 -4.84667569e-01 -6.69538379e-01
-2.92263895e-01 3.09660435e-01 4.37211990e-01 3.33456129e-01
-1.12874687e+00 1.03061593e+00 6.32020903e+00 6.73041880e-01
-8.38905215e-01 -2.09266022e-01 4.45902318e-01 2.24405780e-01
-3.51634204e-01 1.84279561e-01 -6.11668110e-01 3.00252736e-02
6.93406999e-01 2.66236439e-03 9.47772980e-01 8.57501507e-01
-8.73582885e-02 3.06806695e-02 -1.22566211e+00 9.37318087e-01
4.38230842e-01 -1.39556122e+00 -3.92222144e-02 2.59748399e-01
8.77391636e-01 3.23747009e-01 1.51999742e-01 2.36851081e-01
1.94086045e-01 -1.03492010e+00 3.79060596e-01 2.27651626e-01
5.97624362e-01 -4.40605849e-01 3.08423907e-01 1.89313635e-01
-1.16564691e+00 1.49685889e-01 -4.49012130e-01 -3.29053581e-01
-8.31592232e-02 4.42097098e-01 -9.63067174e-01 9.80953991e-01
4.01495665e-01 1.14183843e+00 -6.77030444e-01 9.86577630e-01
-9.01831090e-02 3.77681255e-01 -3.31185162e-02 1.47834837e-01
4.15405363e-01 -4.77782965e-01 6.27346694e-01 1.06863189e+00
3.94554362e-02 -3.64118479e-02 3.90803397e-01 8.36570144e-01
-2.54037291e-01 2.71393955e-01 -9.21564817e-01 -3.33215564e-01
9.64775905e-02 1.22640443e+00 -1.32317591e+00 2.33517680e-02
-9.18161273e-01 9.20744658e-01 5.77480853e-01 3.41198206e-01
-9.09197569e-01 -2.50173479e-01 3.61748368e-01 1.97902307e-01
2.62277156e-01 -5.80629528e-01 -5.32712698e-01 -1.12623394e+00
3.11869327e-02 -9.30424631e-01 7.01493561e-01 -8.04898381e-01
-1.53350198e+00 4.05198842e-01 1.59958422e-01 -7.32184589e-01
2.26827085e-01 -9.31319237e-01 -4.37170178e-01 5.50556898e-01
-1.62717974e+00 -1.42258918e+00 -4.54938650e-01 6.20628774e-01
4.28254932e-01 2.30639338e-01 7.84194052e-01 1.08573794e-01
-5.38635075e-01 4.16085362e-01 6.23913296e-02 2.83009280e-02
6.74908578e-01 -1.31793451e+00 7.70116568e-01 7.49395013e-01
7.48527288e-01 4.56964582e-01 5.13853788e-01 -6.59791529e-01
-1.64965081e+00 -9.42082703e-01 8.16376805e-01 -6.77952468e-01
8.53113532e-01 -4.21003491e-01 -8.36718917e-01 9.32544410e-01
-1.97732478e-01 1.89793840e-01 6.79504454e-01 4.93268639e-01
-5.27902663e-01 8.40624571e-02 -1.11541021e+00 4.86356974e-01
1.63675845e+00 -5.35397232e-01 -3.86472940e-01 5.82372904e-01
4.78406578e-01 -2.25105524e-01 -1.03737020e+00 6.05086207e-01
3.22388768e-01 -1.20894158e+00 1.02040339e+00 -7.04570293e-01
1.14253938e-01 -3.64591293e-02 -2.39357308e-01 -1.15641391e+00
-4.45434779e-01 -7.71323979e-01 9.12548974e-02 1.10662735e+00
2.04416037e-01 -6.38936639e-01 1.08680415e+00 6.24320328e-01
-5.66223025e-01 -1.19669461e+00 -7.41178930e-01 -9.74707186e-01
1.03629306e-01 -6.81618750e-01 5.63855946e-01 1.14682794e+00
-1.73278041e-02 4.67844546e-01 -1.49652898e-01 -3.89431082e-02
5.97518563e-01 2.75472313e-01 7.82844722e-01 -1.44504094e+00
-2.73275286e-01 -4.66822058e-01 -8.07258725e-01 -1.05374885e+00
3.02809387e-01 -1.48899925e+00 -4.77925658e-01 -1.83625638e+00
1.08586289e-01 -5.25693774e-01 -3.18546593e-01 4.64193970e-01
-6.75948188e-02 4.76608276e-01 3.40836167e-01 5.45177348e-02
-7.61377692e-01 1.92357376e-01 1.51482475e+00 -1.68150946e-01
1.07653670e-01 1.51495084e-01 -1.07035255e+00 7.79463768e-01
6.63952827e-01 -1.96246833e-01 -8.01775396e-01 -5.08786798e-01
4.63542610e-01 -1.68855131e-01 4.11157668e-01 -7.74329662e-01
7.34231919e-02 -1.53948009e-01 -2.88735777e-02 -2.70073473e-01
2.21553192e-01 -7.71299601e-01 -1.44278497e-01 -1.42470673e-01
-2.37240940e-01 2.10565269e-01 -5.60283102e-02 7.51221836e-01
2.66735554e-02 -8.77423286e-02 7.11065531e-01 -1.99156225e-01
-8.87261093e-01 4.57834035e-01 2.16335341e-01 4.05369937e-01
1.27510726e+00 -5.75126886e-01 -4.30365831e-01 -1.98556527e-01
-1.07973087e+00 1.20760076e-01 7.01621771e-01 6.17247880e-01
4.25171971e-01 -1.02045393e+00 -5.96631289e-01 1.80582121e-01
2.76138753e-01 -1.97169840e-01 1.38482735e-01 9.61310387e-01
-3.08742851e-01 4.30216283e-01 -5.80603145e-02 -4.63474065e-01
-1.30901527e+00 1.02931523e+00 6.26418069e-02 -4.05376136e-01
-7.88248181e-01 9.69642937e-01 5.82954027e-02 -1.00471161e-01
2.59166449e-01 -2.52964407e-01 5.32537252e-02 -1.27460852e-01
1.57810748e-01 7.42400587e-01 3.54143351e-01 -6.98789358e-01
-4.29670244e-01 6.97056592e-01 -7.77806491e-02 4.28523958e-01
1.48864818e+00 -1.23056911e-01 -3.23089391e-01 3.68469030e-01
1.15342140e+00 3.38641554e-02 -1.05929637e+00 -1.54867485e-01
2.08289519e-01 -4.62266386e-01 1.25142395e-01 -8.28567505e-01
-9.93172467e-01 8.09095263e-01 4.87806983e-02 7.18810141e-01
1.08030915e+00 3.54770213e-01 7.90710270e-01 4.01796326e-02
6.55805171e-01 -9.48500693e-01 8.99129137e-02 3.57277662e-01
8.25122535e-01 -1.22880685e+00 2.37596706e-01 -9.17219400e-01
-5.81180513e-01 1.20927978e+00 3.30691010e-01 -2.10864171e-01
5.93977690e-01 -1.67581644e-02 -2.96823710e-01 -7.10427403e-01
-4.31439817e-01 -5.19453287e-01 4.35694277e-01 9.49247301e-01
4.40814286e-01 9.73030254e-02 -2.59693891e-01 1.13962732e-01
-1.52504563e-01 -2.04289675e-01 4.88909781e-01 7.88221478e-01
-3.07430595e-01 -1.48736966e+00 -1.82536587e-01 4.86480027e-01
-2.45123222e-01 -2.40556300e-02 -7.64250576e-01 1.11122429e+00
2.28285104e-01 1.14773130e+00 -2.53295124e-01 -4.19906914e-01
4.51229155e-01 1.00489065e-01 9.45944369e-01 -8.17998528e-01
-4.31825012e-01 -2.64140457e-01 4.16635841e-01 -6.09080613e-01
-4.47163016e-01 -7.48519480e-01 -1.15119815e+00 -4.54153746e-01
-4.04463887e-01 -4.43227007e-04 7.65476346e-01 7.67991900e-01
2.89706409e-01 4.49010849e-01 3.23769599e-01 -5.92648149e-01
-5.46012044e-01 -5.12517691e-01 -6.72749519e-01 5.08067429e-01
8.80494267e-02 -8.32357943e-01 -3.71092290e-01 -3.39525223e-01] | [7.07454252243042, 6.200143814086914] |
245887b1-b800-46ec-a10c-5308f272a5dc | open-source-fpga-ml-codesign-for-the-mlperf | 2206.11791 | null | https://arxiv.org/abs/2206.11791v1 | https://arxiv.org/pdf/2206.11791v1.pdf | Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark | We present our development experience and recent results for the MLPerf Tiny Inference Benchmark on field-programmable gate array (FPGA) platforms. We use the open-source hls4ml and FINN workflows, which aim to democratize AI-hardware codesign of optimized neural networks on FPGAs. We present the design and implementation process for the keyword spotting, anomaly detection, and image classification benchmark tasks. The resulting hardware implementations are quantized, configurable, spatial dataflow architectures tailored for speed and efficiency and introduce new generic optimizations and common workflows developed as a part of this work. The full workflow is presented from quantization-aware training to FPGA implementation. The solutions are deployed on system-on-chip (Pynq-Z2) and pure FPGA (Arty A7-100T) platforms. The resulting submissions achieve latencies as low as 20 $\mu$s and energy consumption as low as 30 $\mu$J per inference. We demonstrate how emerging ML benchmarks on heterogeneous hardware platforms can catalyze collaboration and the development of new techniques and more accessible tools. | ['Michaela Blott', 'Aidan Yokuda', 'Olivia Weng', 'Yaman Umuroglu', 'Nhan Tran', 'Rushil Roy', 'Tai Nguyen', 'Jules Muhizi', 'Andres Meza', 'Jason Liang', 'Ryan Kastner', 'Shih-Chieh Hsu', 'Scott Hauck', 'Ben Hawks', 'Nicolò Ghielmetti', 'Javier Duarte', 'Giuseppe Di Guglielmo', 'Hendrik Borras'] | 2022-06-23 | null | null | null | null | ['keyword-spotting'] | ['speech'] | [ 1.99497536e-01 -1.72123685e-01 -1.07986346e-01 -8.76302242e-01
-1.54931039e-01 -4.45523530e-01 2.46441975e-01 2.80397952e-01
-6.89994276e-01 5.86196840e-01 -3.78237039e-01 -6.19646549e-01
-2.84182400e-01 -8.03814352e-01 -8.55270028e-01 -3.18367422e-01
-2.68256843e-01 3.76984864e-01 6.50049597e-02 -9.37639177e-02
2.08387062e-01 8.47967744e-01 -2.02422023e+00 4.95261550e-01
1.17796279e-01 1.42129779e+00 8.10971577e-03 1.14837992e+00
1.71207756e-01 9.45757866e-01 -7.08440483e-01 -2.81511158e-01
6.38484240e-01 3.64998102e-01 -4.92413074e-01 -7.45130181e-01
1.13448083e+00 -2.31648445e-01 -3.86680216e-01 1.20626843e+00
8.25923264e-01 -2.14791641e-01 -9.56010520e-02 -1.28125453e+00
2.72707622e-02 9.27702606e-01 2.04540968e-01 5.72549164e-01
-2.14038014e-01 5.49468398e-01 9.36078191e-01 -6.43523097e-01
4.85224217e-01 1.24067008e+00 9.56726491e-01 3.31610560e-01
-1.07607627e+00 -8.30822647e-01 -1.68456376e-01 4.64099228e-01
-1.53649545e+00 -9.49456155e-01 1.31546065e-01 -1.43301055e-01
1.93991697e+00 5.73826909e-01 9.02792454e-01 1.08706653e+00
4.42682117e-01 7.47298241e-01 6.34519577e-01 -4.04595643e-01
5.32099962e-01 -7.30316266e-02 2.78043896e-01 1.06870806e+00
5.38232446e-01 1.19615085e-01 -7.01104879e-01 9.74218920e-02
5.67308843e-01 -2.34148383e-01 3.17832500e-01 2.14199692e-01
-1.45463729e+00 4.51255023e-01 4.60409135e-01 2.64896691e-01
-2.83701152e-01 9.13684666e-01 9.46571946e-01 3.87737930e-01
-6.17960170e-02 5.54705679e-01 -7.74810433e-01 -3.18357795e-01
-1.20432758e+00 5.69633663e-01 8.86674404e-01 1.15606856e+00
5.84721446e-01 6.78599954e-01 -4.10723209e-01 3.68412763e-01
4.32165593e-01 4.48843330e-01 4.25430626e-01 -1.03308570e+00
3.36204797e-01 5.18682361e-01 -3.99461597e-01 -7.43295431e-01
-7.51384437e-01 -6.57689512e-01 -9.58173513e-01 3.51896346e-01
1.16958223e-01 -1.84881806e-01 -8.19213569e-01 1.21591806e+00
1.09800929e-02 2.93166161e-01 -9.70220119e-02 5.95645368e-01
8.18756580e-01 4.67175782e-01 2.76032556e-02 2.36599296e-01
1.46696305e+00 -1.00178099e+00 -7.51319349e-01 -4.25151050e-01
8.84437203e-01 -6.05513632e-01 8.91344845e-01 5.42726755e-01
-1.28974783e+00 -8.68962586e-01 -1.94359517e+00 -3.44789118e-01
-7.51978278e-01 5.16890824e-01 7.31680512e-01 9.59297955e-01
-1.23469710e+00 1.10159159e+00 -1.24088800e+00 -6.03352711e-02
6.66882098e-01 1.07331729e+00 7.15358555e-02 3.83412451e-01
-9.51978326e-01 6.25417233e-01 8.36443484e-01 1.22062035e-01
-7.41034269e-01 -1.20378292e+00 -6.19889736e-01 1.81444213e-01
2.53968816e-02 -7.68347621e-01 1.34233105e+00 -6.48424625e-01
-1.62151194e+00 6.53597176e-01 4.65483606e-01 -1.29452884e+00
3.85979153e-02 -2.91575938e-02 -8.32290947e-01 -2.72511572e-01
-1.82319611e-01 1.01922548e+00 6.28118217e-01 1.78626016e-01
-9.65067446e-01 -2.85781264e-01 -4.46770817e-01 -3.07724148e-01
-4.62944031e-01 -7.69085288e-02 -1.63243070e-01 -6.16804659e-01
-6.33214295e-01 -7.81728446e-01 -1.52012199e-01 1.22725507e-02
-3.99008930e-01 2.31402535e-02 8.39389265e-01 -3.00922990e-01
1.30832541e+00 -2.09388328e+00 -3.15598041e-01 5.39178133e-01
2.90516410e-02 6.64650738e-01 8.63348469e-02 -1.07973211e-01
-2.18787533e-03 -1.69977799e-01 9.25417915e-02 -1.63339719e-01
5.59695959e-01 3.23382795e-01 -2.67540127e-01 4.47161078e-01
2.31313154e-01 8.80821824e-01 -7.64318109e-01 -2.16977686e-01
6.21135831e-01 4.20960695e-01 -6.46689355e-01 -2.87855148e-01
-4.14076447e-01 -1.92776665e-01 -1.73266366e-01 1.02341866e+00
5.05715489e-01 -1.20487452e-01 1.84640154e-01 -6.51270032e-01
-5.82643270e-01 4.56137419e-01 -1.31453121e+00 2.09782863e+00
-3.29456717e-01 9.85846162e-01 1.50006130e-01 -7.78076291e-01
8.39730799e-01 1.10281214e-01 3.98062505e-02 -7.85219193e-01
4.83579963e-01 5.49080968e-01 1.36098012e-01 -1.19421907e-01
5.98130584e-01 5.44207871e-01 -1.63070977e-01 1.07814051e-01
6.14981771e-01 3.63499336e-02 7.35150754e-01 -2.79685944e-01
1.49096227e+00 1.04161471e-01 4.40039277e-01 -7.55747378e-01
5.38512826e-01 -2.52950639e-02 3.87121350e-01 8.85269344e-01
-2.53220767e-01 -2.38532633e-01 3.12474489e-01 -8.19213450e-01
-1.19310570e+00 -8.39322627e-01 -5.45171499e-01 1.37952769e+00
-6.96878731e-01 -1.05354738e+00 -8.06567848e-01 -2.67537475e-01
-8.68454203e-03 6.67044401e-01 -1.83020845e-01 5.84081328e-03
-5.44808567e-01 -7.37798154e-01 1.29674828e+00 6.52640939e-01
9.17013884e-01 -1.10429323e+00 -1.42737556e+00 4.98120576e-01
9.55106199e-01 -1.20903909e+00 2.26137921e-01 6.44315720e-01
-6.28650963e-01 -4.10481483e-01 1.92451179e-01 -5.50421894e-01
2.04720944e-01 -8.27917457e-01 1.29589975e+00 -1.81045532e-01
-1.16037202e+00 -7.29242014e-03 3.72765929e-01 -7.36608207e-01
-2.21869290e-01 2.96765864e-01 3.21547508e-01 -4.44518983e-01
4.07996178e-01 -8.13103914e-01 -7.10275531e-01 -8.21408704e-02
-6.46091998e-01 -6.69324547e-02 7.37367153e-01 6.30884171e-01
8.68882477e-01 -2.12462604e-01 1.67350322e-01 -7.07878172e-01
2.34598115e-01 -9.11563337e-02 -1.41634321e+00 1.24724641e-01
-7.90083408e-01 3.94639432e-01 1.02267814e+00 3.26144546e-02
-4.52951610e-01 5.87528467e-01 -7.26789832e-01 -5.84033072e-01
-1.52380988e-01 1.99816674e-02 -1.22330584e-01 -5.49626529e-01
9.72353876e-01 -1.66197196e-01 -2.15272367e-01 -1.60235077e-01
1.37415424e-01 5.90900302e-01 9.12231565e-01 -4.12484556e-01
2.84887671e-01 1.94783092e-01 4.10547018e-01 -8.90413165e-01
-3.42604965e-01 1.02233954e-01 -3.38272840e-01 6.96461648e-02
7.15925634e-01 -1.14127564e+00 -1.09965956e+00 1.30559266e-01
-8.01448524e-01 -6.04496717e-01 -4.56924230e-01 2.58327454e-01
-2.56615818e-01 -2.98262089e-01 -4.19458926e-01 -2.25959614e-01
-9.81835902e-01 -1.57352853e+00 1.05118275e+00 2.67212003e-01
-3.00221294e-01 -8.19045007e-01 -9.37933996e-02 -2.55550474e-01
6.49653614e-01 2.71815002e-01 5.68821609e-01 -8.22902977e-01
-9.46629941e-01 -2.13142738e-01 -8.10712278e-02 6.43538952e-01
-5.24267197e-01 2.28115201e-01 -1.24243915e+00 -2.66913623e-01
-4.28127944e-01 -2.35837460e-01 6.30319893e-01 3.79347384e-01
1.65830910e+00 -2.77846754e-01 -4.87304896e-01 1.12141895e+00
1.53625882e+00 -7.38129243e-02 5.73679566e-01 2.34442994e-01
6.60222471e-01 -2.04993859e-01 4.44060117e-01 4.58240122e-01
-8.88005793e-02 7.41632700e-01 5.60176432e-01 3.22944134e-01
-3.53020728e-02 2.13984907e-01 4.48049098e-01 6.16660357e-01
1.92968771e-01 -1.08911492e-01 -9.75652993e-01 2.29721233e-01
-1.66060960e+00 -7.59421289e-01 -1.91596031e-01 2.06687355e+00
4.93448913e-01 4.07816112e-01 -1.56502590e-01 5.94377995e-01
2.59196550e-01 2.11000238e-02 -5.46592891e-01 -9.95363951e-01
1.50945008e-01 1.00836027e+00 1.01051378e+00 2.90640265e-01
-1.27429259e+00 7.32982099e-01 6.23484325e+00 1.15756047e+00
-1.31738758e+00 1.95887033e-02 5.29813647e-01 -5.81205547e-01
4.39925551e-01 -4.57002640e-01 -1.45598006e+00 4.59685504e-01
2.00222158e+00 -2.51344666e-02 5.31019151e-01 1.11345172e+00
-3.67637038e-01 3.63853276e-01 -1.41181910e+00 1.07104015e+00
-4.22183037e-01 -2.08172274e+00 -1.13729209e-01 -1.61430895e-01
2.49448627e-01 6.48241818e-01 2.58387804e-01 4.15542781e-01
1.21203862e-01 -1.22262704e+00 8.99429202e-01 2.87529588e-01
1.03443968e+00 -1.07694674e+00 6.76992893e-01 -9.76286605e-02
-1.20200145e+00 -3.26784164e-01 -4.80822861e-01 -2.40878105e-01
-2.97001868e-01 7.20127404e-01 -1.20345461e+00 2.68203676e-01
9.93938744e-01 8.85097325e-01 -8.70454788e-01 5.70821166e-01
6.11774623e-02 4.18887347e-01 -7.01787591e-01 -2.75594741e-01
1.47409618e-01 3.73716921e-01 3.76195371e-01 1.66112804e+00
3.42844248e-01 -3.94570351e-01 -3.19057852e-01 6.67592525e-01
-1.92429960e-01 -1.40570775e-01 -3.02792400e-01 -1.40437543e-01
6.88604116e-01 1.75099576e+00 -6.93277717e-01 -4.74875808e-01
-1.79029569e-01 5.36271334e-01 6.73370734e-02 -5.63191831e-01
-1.03165233e+00 -8.44293177e-01 9.66574609e-01 -1.94390938e-01
4.18700635e-01 1.39627159e-01 -4.99097586e-01 -7.43444085e-01
-1.19292498e-01 -9.05866981e-01 2.25077122e-01 -4.65132922e-01
-7.13455856e-01 4.55159009e-01 -1.34092152e-01 -8.29790592e-01
-4.37968940e-01 -1.09471095e+00 -9.40463543e-02 4.25449908e-01
-1.11317587e+00 -6.93972349e-01 -3.21024269e-01 4.37353700e-01
1.97829768e-01 -7.11283445e-01 1.17230797e+00 8.45708847e-01
-9.58633244e-01 9.91490960e-01 3.19442481e-01 -1.01097271e-01
4.00030404e-01 -1.25435686e+00 9.84263897e-01 8.65201890e-01
1.75900757e-01 6.02984071e-01 5.84937990e-01 -2.02311516e-01
-1.92005956e+00 -1.66170180e+00 4.17528570e-01 -1.94605649e-01
7.17147648e-01 -7.39468515e-01 -4.00788188e-01 9.63294744e-01
1.46753818e-01 7.39241064e-01 5.28432488e-01 -2.52373725e-01
-7.37288734e-03 -7.15180814e-01 -1.35952890e+00 5.01333058e-01
1.10233355e+00 -2.26445407e-01 4.44024913e-02 6.06357932e-01
4.01460499e-01 -9.17320788e-01 -1.16276026e+00 4.71375912e-01
5.41387439e-01 -1.03438163e+00 1.24085081e+00 -9.28906649e-02
1.34188324e-01 -3.75967115e-01 -3.00716013e-01 -6.93414271e-01
-4.89214435e-02 -8.64702046e-01 -4.42664325e-01 8.29109251e-01
3.31394970e-01 -5.73389113e-01 6.35311604e-01 -1.81477427e-01
-6.26421690e-01 -4.76964563e-01 -1.31354117e+00 -4.44881767e-01
-4.82112080e-01 -7.68772840e-01 7.65963972e-01 4.35829610e-01
-1.66137800e-01 4.60163474e-01 1.36227101e-01 1.32278323e-01
6.21320784e-01 -4.65421021e-01 4.58835423e-01 -1.04045761e+00
-4.21866596e-01 -4.54250246e-01 -1.07427311e+00 -3.70926172e-01
2.81751342e-02 -1.15440524e+00 -2.14948595e-01 -7.23862469e-01
-6.53665066e-01 -3.43858331e-01 -4.00740206e-01 7.83776939e-01
6.47651315e-01 4.80529696e-01 -1.46280244e-01 -4.63864684e-01
-8.88241887e-01 -1.35085270e-01 3.94398302e-01 -7.76920989e-02
1.31550893e-01 -3.44352871e-01 -1.96695074e-01 6.90298021e-01
9.20091569e-01 -2.79620588e-01 -2.32676789e-01 -5.95225751e-01
5.39547503e-01 -5.33364952e-01 6.08187079e-01 -2.14350796e+00
5.76950133e-01 5.87685466e-01 7.22528517e-01 -6.67627871e-01
3.79510731e-01 -7.29484260e-01 2.45363206e-01 8.83551061e-01
-1.93192214e-01 4.43636864e-01 9.13672268e-01 1.51514918e-01
1.49140820e-01 6.16476778e-03 8.76968682e-01 5.44627756e-02
-9.81325746e-01 1.23449095e-01 -3.47894788e-01 -2.23933145e-01
1.00323772e+00 1.12210631e-01 -4.79797125e-01 4.99366999e-01
-6.01622641e-01 9.54812244e-02 4.13839146e-02 6.84049129e-02
3.56181741e-01 -1.18782103e+00 -4.87699300e-01 8.21751058e-01
-1.31445080e-01 -3.64282019e-02 1.48181662e-01 6.32936478e-01
-1.15840173e+00 1.16575503e+00 -8.73889744e-01 -8.97651315e-01
-1.33986187e+00 1.37517557e-01 5.47991335e-01 -2.39223570e-01
-4.88028288e-01 1.13688838e+00 -7.07494378e-01 -3.77804160e-01
4.12514925e-01 -9.66986120e-01 2.98766136e-01 -3.63507837e-01
7.51607418e-01 6.55867159e-01 8.40604067e-01 1.43630370e-01
-7.42288768e-01 1.41024262e-01 -1.22388646e-01 1.90449834e-01
1.25492227e+00 6.27859831e-01 -1.24074921e-01 1.88247100e-01
1.12913811e+00 -4.32285517e-01 -9.86535192e-01 2.59484768e-01
1.53915405e-01 1.02795698e-01 6.15906298e-01 -7.41845489e-01
-1.06334078e+00 8.67050946e-01 1.29141128e+00 -2.84940749e-01
1.12170553e+00 -6.31070852e-01 6.44809067e-01 1.05232859e+00
2.26868525e-01 -1.22492898e+00 -5.67787945e-01 7.52071083e-01
3.16816062e-01 -6.26313090e-01 3.39154243e-01 6.18878007e-02
1.79519042e-01 1.44639516e+00 5.21090984e-01 -2.75562227e-01
5.38078129e-01 1.10328901e+00 -4.88983989e-01 -1.67175531e-01
-1.01392782e+00 1.87593728e-01 1.14195906e-01 3.85046154e-01
4.06160265e-01 1.00569963e-01 1.14085346e-01 5.92872739e-01
-6.41557455e-01 3.19921464e-01 1.89226463e-01 1.13769567e+00
-1.48069128e-01 -9.47482646e-01 -1.60183281e-01 7.61531651e-01
-6.96089149e-01 -3.00938547e-01 1.04567960e-01 8.18618417e-01
5.57301879e-01 2.39620119e-01 5.95825851e-01 -7.23296285e-01
3.51155639e-01 8.31875578e-02 7.38098264e-01 -4.40264523e-01
-1.25321937e+00 -3.74777406e-01 1.98454201e-01 -1.04436898e+00
1.28670409e-01 -3.34533989e-01 -1.32563066e+00 -4.84778345e-01
2.90059805e-01 -2.68270254e-01 1.23680377e+00 6.34367526e-01
8.50856841e-01 1.11988807e+00 -1.12478234e-01 -1.05196464e+00
-3.70833725e-01 -7.30111599e-01 -3.55003804e-01 -7.76621699e-01
2.79963583e-01 -2.93767065e-01 -9.50322449e-02 -9.14044306e-02] | [8.392123222351074, 2.900789737701416] |
13dfe6c0-e204-4add-98fb-c17ff39ee8b5 | dense-retrieval-adaptation-using-target | 2307.02740 | null | https://arxiv.org/abs/2307.02740v1 | https://arxiv.org/pdf/2307.02740v1.pdf | Dense Retrieval Adaptation using Target Domain Description | In information retrieval (IR), domain adaptation is the process of adapting a retrieval model to a new domain whose data distribution is different from the source domain. Existing methods in this area focus on unsupervised domain adaptation where they have access to the target document collection or supervised (often few-shot) domain adaptation where they additionally have access to (limited) labeled data in the target domain. There also exists research on improving zero-shot performance of retrieval models with no adaptation. This paper introduces a new category of domain adaptation in IR that is as-yet unexplored. Here, similar to the zero-shot setting, we assume the retrieval model does not have access to the target document collection. In contrast, it does have access to a brief textual description that explains the target domain. We define a taxonomy of domain attributes in retrieval tasks to understand different properties of a source domain that can be adapted to a target domain. We introduce a novel automatic data construction pipeline that produces a synthetic document collection, query set, and pseudo relevance labels, given a textual domain description. Extensive experiments on five diverse target domains show that adapting dense retrieval models using the constructed synthetic data leads to effective retrieval performance on the target domain. | ['W. Bruce Croft', 'Edgar Meij', 'Srivas Prasad', 'Sachith Sri Ram Kothur', 'Yong Zhuang', 'Helia Hashemi'] | 2023-07-06 | null | null | null | null | ['domain-adaptation', 'unsupervised-domain-adaptation', 'retrieval', 'information-retrieval'] | ['methodology', 'methodology', 'methodology', 'natural-language-processing'] | [ 4.33647066e-01 6.14279322e-03 -5.73674083e-01 -5.04370809e-01
-1.31026733e+00 -8.93390238e-01 9.93255258e-01 2.89391428e-01
-3.99171501e-01 7.51814604e-01 2.76663065e-01 2.01040640e-01
-3.74113023e-01 -6.42813921e-01 -3.45620155e-01 -3.86666447e-01
3.03867608e-01 1.34403682e+00 4.41831142e-01 -6.18763030e-01
4.40613896e-01 1.59635931e-01 -1.57414532e+00 3.93117189e-01
6.56414330e-01 7.00199604e-01 3.02368104e-01 6.37250602e-01
-4.46322501e-01 3.02252650e-01 -9.75627840e-01 1.66215822e-02
3.10250908e-01 -5.43772995e-01 -1.12523377e+00 7.37860128e-02
2.65738845e-01 -3.91057253e-01 -2.25777850e-01 7.33879983e-01
5.19543290e-01 5.30303121e-01 1.21143997e+00 -9.65344191e-01
-1.09388912e+00 4.68293160e-01 -1.62558407e-01 3.39372545e-01
4.62003589e-01 -4.19577390e-01 8.67908299e-01 -1.02400994e+00
1.18305326e+00 1.22335672e+00 -2.31210589e-02 7.13535190e-01
-1.36450398e+00 -5.25161326e-01 2.05810126e-02 2.82529771e-01
-1.42027402e+00 -4.02753711e-01 6.89111948e-01 -3.73177439e-01
8.41365099e-01 -2.16714740e-01 4.31345329e-02 1.29585564e+00
-3.22573245e-01 6.08114600e-01 4.00067717e-01 -9.97689664e-01
6.27034307e-01 5.69651604e-01 6.81044221e-01 -3.56907874e-01
1.26888528e-01 -4.48837690e-02 -3.07588726e-01 -5.69636047e-01
3.00790280e-01 -1.14982761e-01 -4.27700691e-02 -7.57039070e-01
-8.91984463e-01 9.68145669e-01 4.53339964e-02 5.12084305e-01
-3.03349614e-01 -4.06842202e-01 5.53000569e-01 7.33980417e-01
4.89181578e-01 7.87759364e-01 -4.40908611e-01 2.60802656e-01
-7.46693611e-01 4.21369314e-01 1.10167718e+00 1.65489233e+00
1.06903148e+00 -3.41039985e-01 -5.27645409e-01 1.20556712e+00
4.07165550e-02 5.83389997e-01 9.54709411e-01 -7.01841593e-01
1.97140053e-01 5.18031359e-01 5.88388681e-01 -3.80954802e-01
-6.97930902e-03 -3.68187316e-02 -2.21920386e-01 -2.58276939e-01
1.42665267e-01 1.98631167e-01 -1.15739202e+00 1.64563954e+00
2.97206193e-01 -2.80739725e-01 6.32435143e-01 7.36656547e-01
9.18570817e-01 7.36407876e-01 1.47097066e-01 -3.56173635e-01
1.13510537e+00 -7.80503333e-01 -7.19106615e-01 -4.69509274e-01
7.83399284e-01 -8.38474810e-01 1.37470853e+00 8.55064392e-02
-6.94175363e-01 -5.81028879e-01 -9.78725791e-01 -1.94624797e-01
-7.82610893e-01 -2.08707348e-01 1.04249537e-01 4.03394878e-01
-7.29082167e-01 1.09181382e-01 -1.35332555e-01 -1.07875121e+00
-1.25918120e-01 1.17482297e-01 -1.86606437e-01 -7.25121498e-01
-1.70332515e+00 9.54722703e-01 8.44723284e-01 -9.10329044e-01
-9.52283025e-01 -6.95280254e-01 -7.10694730e-01 2.19773263e-01
5.34114361e-01 -6.82307363e-01 1.77146852e+00 -1.14183831e+00
-1.13578022e+00 8.67682934e-01 -1.29920632e-01 -2.39640221e-01
-1.66806296e-01 -2.16824844e-01 -6.03602529e-01 4.00720119e-01
3.35193276e-01 5.46723723e-01 1.11484408e+00 -1.39783859e+00
-5.83119392e-01 -4.18359786e-01 -1.11251265e-01 4.64731932e-01
-5.61308324e-01 2.13790402e-01 -7.38956571e-01 -6.80983186e-01
-2.60981113e-01 -8.28374982e-01 1.59569114e-01 -3.04667324e-01
2.67550834e-02 -3.87960613e-01 9.41937685e-01 -2.02246159e-01
1.41967273e+00 -2.10926628e+00 2.73686778e-02 2.76653379e-01
-2.52157748e-01 4.36754137e-01 -4.96144205e-01 9.28674579e-01
-5.14986962e-02 8.79895017e-02 -7.88191408e-02 8.17695186e-02
3.68396565e-03 2.34202579e-01 -6.91175640e-01 -8.31447095e-02
9.30003077e-03 6.69372618e-01 -1.17172432e+00 -5.68892062e-01
-1.63031697e-01 1.93038344e-01 -4.21106488e-01 4.30206299e-01
-4.82507408e-01 2.03552783e-01 -8.15117538e-01 5.43531120e-01
4.59684312e-01 -4.01718110e-01 1.90226525e-01 1.27227485e-01
4.61543381e-01 1.01177745e-01 -1.10663724e+00 2.00341845e+00
-3.18977028e-01 4.14892107e-01 -3.51404607e-01 -9.62672234e-01
1.16137850e+00 4.95516330e-01 4.07435685e-01 -8.72123063e-01
-2.06964672e-01 3.42754066e-01 -2.79934168e-01 -5.49631000e-01
7.84038365e-01 -3.67096394e-01 -4.86217618e-01 9.06569481e-01
4.18962747e-01 -2.02969849e-01 4.56975728e-01 5.33878267e-01
1.25739908e+00 -3.26354131e-02 6.86276913e-01 -8.56581405e-02
3.04729193e-01 7.19663560e-01 2.51038313e-01 1.22691810e+00
1.63286794e-02 7.02861071e-01 -1.64011315e-01 -1.66104332e-01
-1.33419442e+00 -1.11491632e+00 -2.26729304e-01 1.81428099e+00
3.54045689e-01 -3.05444896e-01 -3.10309231e-01 -5.93760133e-01
-1.12961881e-01 9.84391451e-01 -6.45913601e-01 -6.11796319e-01
-3.16447973e-01 -1.48893461e-01 3.48850667e-01 2.88072288e-01
1.24616422e-01 -1.12723804e+00 -2.99098730e-01 4.03275341e-01
-3.00525218e-01 -8.35637212e-01 -5.71871698e-01 1.13955967e-01
-6.99688792e-01 -9.84222591e-01 -1.02322245e+00 -1.11725140e+00
5.55710673e-01 6.23653412e-01 1.44006360e+00 -1.99488238e-01
-2.18828484e-01 1.04931176e+00 -9.36463773e-01 -6.10418916e-01
-6.11788809e-01 3.68404597e-01 1.13754965e-01 -3.70557338e-01
1.26555991e+00 -4.12430018e-02 -3.67341429e-01 5.00880837e-01
-1.50317609e+00 -6.58370197e-01 5.31025648e-01 9.64610517e-01
6.07634902e-01 -1.03421032e-01 8.49213660e-01 -1.17368329e+00
1.13072836e+00 -9.19550002e-01 -1.24835998e-01 8.83621037e-01
-7.44627595e-01 3.26498717e-01 3.56660247e-01 -9.18602884e-01
-1.39065933e+00 -9.60239992e-02 6.99028730e-01 -4.97801900e-01
-2.84903586e-01 6.76535845e-01 -4.41315211e-02 4.11495328e-01
1.44230413e+00 1.07282951e-01 -1.35928333e-01 -7.01074958e-01
4.41234350e-01 1.05686557e+00 2.50774294e-01 -8.19351614e-01
7.65359104e-01 2.47771904e-01 -4.73927110e-01 -7.04549313e-01
-9.71692502e-01 -1.16203487e+00 -9.79694307e-01 1.56026408e-01
3.57677341e-01 -7.90311456e-01 3.15728337e-01 -7.71862864e-02
-1.00182557e+00 -2.35150427e-01 -7.34538913e-01 3.63953888e-01
-5.69013596e-01 1.54641315e-01 -3.32874767e-02 -5.32560468e-01
-4.46256578e-01 -6.03545427e-01 1.22809529e+00 1.47525892e-01
-4.82709646e-01 -1.10333169e+00 6.18093908e-01 -7.67757297e-02
4.98783886e-01 -4.31580186e-01 1.27796042e+00 -1.55305767e+00
-1.84535980e-02 -4.55142766e-01 -6.79248869e-02 1.79388180e-01
3.07519317e-01 -2.94045806e-01 -9.00881052e-01 -5.72267890e-01
3.28919739e-02 -7.06214607e-01 5.71885049e-01 1.28777474e-01
6.33007407e-01 -2.56371826e-01 -5.92319489e-01 1.17152799e-02
1.34924901e+00 4.62253481e-01 5.48901081e-01 6.03760123e-01
-6.86804578e-02 8.55549037e-01 1.34182775e+00 4.89356130e-01
1.94378415e-04 9.31254506e-01 -2.90890664e-01 1.69456422e-01
-1.33419365e-01 -3.44807088e-01 1.16219707e-01 3.45408320e-01
5.44089079e-01 -4.27623183e-01 -1.12308168e+00 8.01314592e-01
-1.83932626e+00 -1.03165448e+00 6.36335492e-01 2.48416281e+00
1.03210866e+00 -1.93901524e-01 -1.03090459e-03 -3.57621223e-01
8.41473103e-01 -3.37687105e-01 -9.44802046e-01 -2.00970486e-01
-4.09453623e-02 2.41400853e-01 1.95838392e-01 5.09697795e-01
-9.46462929e-01 1.24092972e+00 6.81061554e+00 8.21738839e-01
-7.53135264e-01 -5.08820601e-02 -3.97792198e-02 -2.55235404e-01
-3.70397359e-01 2.37050161e-01 -1.14967656e+00 9.95076373e-02
1.07194448e+00 -1.02930951e+00 2.77138650e-01 1.02321601e+00
-2.48040721e-01 1.29120722e-01 -1.55163479e+00 7.57195175e-01
4.79023755e-01 -8.39466095e-01 6.55794024e-01 -6.25786781e-02
6.32881820e-01 -2.20209315e-01 -2.67194919e-02 9.23687816e-01
5.74430525e-01 -7.12470591e-01 6.16502650e-02 5.65176189e-01
1.05943394e+00 -5.26255012e-01 5.89922786e-01 5.64882517e-01
-7.75105059e-01 -1.41965672e-01 -7.96849191e-01 3.69402438e-01
-7.35403970e-02 1.81537569e-02 -1.44263256e+00 4.15386796e-01
7.68760085e-01 7.11369514e-01 -7.11973190e-01 9.60899830e-01
1.78324506e-02 2.39614666e-01 -1.09850831e-01 9.66370851e-02
1.31117916e-02 9.75321531e-02 6.42018676e-01 1.18817544e+00
3.40152979e-01 3.07390988e-01 2.78768718e-01 4.79250133e-01
-1.10560834e-01 3.21669102e-01 -1.07435298e+00 -1.46523193e-01
1.02884090e+00 8.81878436e-01 -1.94522589e-01 -7.90295839e-01
-3.94331038e-01 8.32994521e-01 8.93634036e-02 8.86153102e-01
-6.64852858e-02 -7.74480879e-01 4.58811849e-01 1.46152422e-01
1.91896155e-01 1.50979355e-01 2.58379102e-01 -1.19668150e+00
-1.53662249e-01 -1.06024599e+00 9.54927802e-01 -9.47067559e-01
-1.66085994e+00 3.85632724e-01 6.64476395e-01 -1.65416491e+00
-9.25996542e-01 -2.01960176e-01 -6.78118244e-02 9.36980724e-01
-1.59357142e+00 -7.85764396e-01 -2.69825906e-01 9.23922718e-01
9.74742353e-01 -6.45726144e-01 1.33542740e+00 1.49468586e-01
7.08882511e-02 5.80658853e-01 7.34604061e-01 1.13843799e-01
1.64351392e+00 -1.03044748e+00 2.41260920e-02 3.88321280e-01
1.22533934e-02 1.07884526e+00 7.90914893e-01 -7.17941999e-01
-1.05421925e+00 -9.91729259e-01 7.86523283e-01 -6.70634627e-01
6.08000815e-01 -2.71240354e-01 -1.48244441e+00 8.02056432e-01
2.27495596e-01 -2.55959213e-01 1.12718868e+00 1.54533967e-01
-5.69707572e-01 -7.95623288e-02 -1.28810632e+00 3.24507982e-01
6.09497428e-01 -5.53316593e-01 -1.36090672e+00 5.71865201e-01
7.57179081e-01 5.40502109e-02 -8.19927812e-01 2.03277901e-01
3.82256359e-01 -1.65943518e-01 1.13489115e+00 -1.10664690e+00
9.59093869e-02 -1.07407294e-01 -2.59512454e-01 -1.46569693e+00
-4.30308878e-01 -1.31517559e-01 -2.51757443e-01 1.22373199e+00
2.47422442e-01 -2.51243174e-01 4.49944258e-01 1.04841328e+00
1.09788947e-01 1.38024390e-01 -5.58016419e-01 -1.13414943e+00
4.02185708e-01 3.57240140e-02 4.97400880e-01 1.03054154e+00
2.07454920e-01 8.97452056e-01 -3.96005064e-02 -1.29270867e-01
4.68081653e-01 2.63092607e-01 1.05583405e+00 -1.65369213e+00
-1.41455829e-01 -7.46661201e-02 -2.29897443e-02 -1.19485521e+00
2.00867072e-01 -8.94224942e-01 1.51786149e-01 -1.59138119e+00
4.52962190e-01 -3.31676573e-01 -4.37014580e-01 3.62105638e-01
-4.22290191e-02 -1.39305353e-01 -1.83904231e-01 8.78663540e-01
-8.25088739e-01 4.41796064e-01 9.29451585e-01 -3.88482362e-01
-6.66469991e-01 -1.59631327e-01 -7.82617092e-01 3.11399728e-01
6.45769596e-01 -8.05328846e-01 -8.61127436e-01 -4.72027689e-01
9.12527367e-02 -1.16466489e-02 -1.10798135e-01 -6.61315978e-01
5.67947626e-01 -3.12547863e-01 3.19270521e-01 -4.32214558e-01
3.12800407e-01 -8.98462057e-01 -1.33748621e-01 -3.59739102e-02
-8.63972008e-01 -2.62751341e-01 2.03122780e-01 8.39607596e-01
-5.12866616e-01 -8.15085292e-01 7.39040971e-01 -3.45817089e-01
-1.35278535e+00 1.31946042e-01 -3.61910313e-01 4.22203183e-01
1.04153585e+00 -2.51122415e-01 -4.51518774e-01 -6.32838309e-01
-8.50182176e-01 3.10110003e-01 6.65661752e-01 7.69215882e-01
6.11740410e-01 -1.41238260e+00 -7.71434605e-01 5.60349971e-02
1.16527414e+00 -1.58497036e-01 -8.12247321e-02 -1.29800141e-01
1.62230179e-01 7.78599739e-01 -1.60529241e-01 -5.09837389e-01
-1.14847577e+00 1.08116412e+00 -1.15989521e-03 -3.50564063e-01
-4.63785172e-01 4.25742745e-01 3.64482164e-01 -4.84973371e-01
2.75450736e-01 4.33965564e-01 -5.51237881e-01 3.38816047e-01
8.65221083e-01 2.27783490e-02 1.63672984e-01 -4.62907135e-01
-9.49155316e-02 4.39509988e-01 -7.90018678e-01 -4.45190877e-01
1.09598875e+00 -4.77548927e-01 2.74242669e-01 7.56305218e-01
1.18735695e+00 -5.03162384e-01 -7.17404783e-01 -1.19678497e+00
4.54619944e-01 -6.23961627e-01 -1.89507768e-01 -9.53813672e-01
-1.98867753e-01 7.29699373e-01 6.95024371e-01 1.19919918e-01
1.23735607e+00 4.07254815e-01 4.27306294e-01 1.15524435e+00
5.39986253e-01 -1.72056460e+00 4.32516992e-01 9.04783964e-01
9.98520255e-01 -1.46972120e+00 2.32207179e-02 8.31490681e-02
-8.59696269e-01 9.68816876e-01 6.16132379e-01 6.12086765e-02
7.54509270e-01 -4.40077275e-01 1.63408637e-01 -2.47238427e-01
-9.40245390e-01 -4.26472843e-01 4.90767419e-01 9.81248796e-01
3.16202372e-01 -4.83979613e-01 -1.73209295e-01 4.83054310e-01
1.46935716e-01 7.51625896e-02 3.42816234e-01 1.33107722e+00
-7.73337841e-01 -1.44951308e+00 -3.64947617e-01 4.91806120e-01
-1.60339385e-01 -2.38085106e-01 -8.98861885e-01 9.25752223e-01
-6.79548442e-01 1.04910231e+00 1.44610286e-01 4.90342230e-02
4.72213686e-01 6.76941812e-01 1.03921235e-01 -1.67859221e+00
-2.27924302e-01 1.94651112e-01 -1.03025734e-01 -6.94822669e-02
-3.88085604e-01 -4.14168477e-01 -9.92801368e-01 2.84359515e-01
-2.83771873e-01 7.21635342e-01 4.78229821e-01 8.34386945e-01
4.81261015e-01 -8.43455177e-03 4.91059035e-01 -5.13196707e-01
-7.30516613e-01 -1.31413805e+00 -7.58746207e-01 8.92922044e-01
2.63274759e-01 -7.69620001e-01 -2.74373055e-01 3.28130752e-01] | [11.186606407165527, 7.840414524078369] |
ee4942cd-53f1-48ed-9dc5-a74f34745580 | the-skill-task-matching-model-mechanism-model | 2306.12176 | null | https://arxiv.org/abs/2306.12176v1 | https://arxiv.org/pdf/2306.12176v1.pdf | The Skill-Task Matching Model: Mechanism, Model Form and implications | We propose the iteration mechanism as a supplement to the price mechanism in microeconomics. We hold that firms set expected profits in the beginning of each producing period, then try to achieve them. The ability to achieve target number is not born. Firms continuously trial and error, let their actual profits increasingly approach expected profits. We propose the Skill-Task Matching Model to describe this iteration process. The model vectorizes occupations into a task vector space, vectorizes employees into a skill vector space, regards production technology as the matching level of skills and tasks, and regards corporate strategy as the value vector of tasks. Firms turn these producing parameters by iteration, to make actual profit get closer to expected profit. We build a neural network algorithm to simulated how the Skill-Task Matching Model works. Being a new model to illustrate firm's decision making, the Skill-Task Matching Model offers another perspective to discuss firm's short-run and long-run decision making, routine tasks, and perfect competition markets. | ['WeiGuo Yang', 'Da Xie'] | 2023-06-21 | null | null | null | null | ['decision-making'] | ['reasoning'] | [-1.12502865e-01 4.04030651e-01 -6.19256616e-01 1.34297505e-01
9.89064574e-02 -4.05047208e-01 5.61955929e-01 -5.13653517e-01
-6.00560486e-01 7.70573854e-01 -1.33915022e-01 -5.39887011e-01
-6.70173407e-01 -8.23136687e-01 -3.19225967e-01 -4.89104658e-01
2.87051499e-01 5.92967212e-01 -4.38076347e-01 -2.57749707e-01
7.23992646e-01 1.76911324e-01 -1.27934575e+00 -3.10083389e-01
7.54572332e-01 9.79482710e-01 8.06690931e-01 5.15482068e-01
-3.28737050e-01 9.99052286e-01 -4.98162121e-01 -6.46278143e-01
7.50523806e-01 -1.00144543e-01 -7.60741711e-01 3.76140147e-01
-6.51222885e-01 -5.16997091e-02 1.61237568e-02 1.08107400e+00
-1.06272772e-01 9.05932263e-02 1.13432145e+00 -1.38451993e+00
-1.32939470e+00 8.07056189e-01 -4.79499310e-01 6.60639405e-02
2.35749714e-04 3.75575393e-01 9.52118993e-01 -5.23304880e-01
4.20256495e-01 1.04809189e+00 4.18775976e-01 1.74552277e-01
-1.15794873e+00 -4.32690442e-01 2.68851936e-01 -3.19548905e-01
-9.09676194e-01 -1.67122409e-02 6.23114049e-01 -9.33032036e-01
1.02783132e+00 -9.96856857e-03 1.11095893e+00 6.95405722e-01
1.06308544e+00 3.27401459e-01 1.09264481e+00 -5.29206932e-01
1.12166241e-01 3.08552325e-01 -2.52615404e-03 2.06097394e-01
6.85653448e-01 6.63453519e-01 -2.07579434e-01 2.20296279e-01
1.54976344e+00 5.05818069e-01 2.51561224e-01 -2.73509026e-01
-1.27324700e+00 7.46493340e-01 2.58658946e-01 6.95843577e-01
-9.26984727e-01 4.33103412e-01 -1.87822431e-01 1.02282321e+00
4.44143005e-02 1.09346557e+00 -2.98165619e-01 -1.63737088e-01
-6.73490524e-01 3.88401061e-01 7.52246320e-01 7.89516330e-01
7.28806973e-01 3.10715795e-01 -5.30906618e-01 3.90348524e-01
1.84518620e-01 6.71388984e-01 7.91099429e-01 -1.66353500e+00
3.91406983e-01 4.47852850e-01 7.57017851e-01 -9.96759653e-01
-3.73083472e-01 -1.10463560e+00 -8.12106550e-01 2.16317475e-01
5.62785804e-01 -2.79728562e-01 -5.61345816e-01 1.57278550e+00
-5.96971035e-01 -3.52848992e-02 3.47669065e-01 5.72519660e-01
-2.41198391e-01 6.81664944e-01 9.00218561e-02 -9.24395263e-01
1.30167007e+00 -1.00064480e+00 -1.04493809e+00 -3.09080184e-01
5.81252992e-01 -5.11005700e-01 1.02321243e+00 4.22551394e-01
-1.64001346e+00 -8.80707026e-01 -6.34665966e-01 5.24036109e-01
-2.96831578e-01 2.85181135e-01 1.06399310e+00 4.29909766e-01
-1.09584856e+00 9.32571352e-01 -6.32233500e-01 2.31901750e-01
1.46712437e-01 4.08749640e-01 2.56734937e-01 7.86467373e-01
-1.20352471e+00 9.58516598e-01 4.38915789e-01 -1.35740591e-02
-7.18973994e-01 -5.73683500e-01 -5.06284952e-01 6.52713835e-01
6.43206596e-01 -1.09064353e+00 1.90979064e+00 -1.19532979e+00
-1.48366463e+00 6.88852727e-01 2.47139543e-01 -4.34130490e-01
3.23647082e-01 1.95695609e-01 -2.48198956e-01 -4.83084053e-01
5.13612866e-01 2.66055316e-01 7.47704625e-01 -1.22552776e+00
-9.43863750e-01 -2.73788720e-01 -3.92045155e-02 4.77040678e-01
-4.11613643e-01 -1.24200374e-01 1.37780279e-01 -4.38738078e-01
8.79295915e-02 -6.94054902e-01 -6.93207264e-01 -9.60837901e-01
3.28683294e-02 -5.64809144e-01 -4.03411955e-01 -1.57168835e-01
1.37319887e+00 -1.87224805e+00 5.33692464e-02 3.09219211e-01
4.55108464e-01 -4.75060999e-01 2.79435534e-02 4.06445861e-01
-7.56359175e-02 2.15405673e-01 3.57197464e-01 -9.69417989e-02
4.89762425e-01 1.79755539e-01 5.42493872e-02 -7.84745589e-02
2.01377913e-01 1.20354331e+00 -7.37480879e-01 -1.41732857e-01
-2.64779478e-01 -6.47689283e-01 -3.00725281e-01 5.96133992e-02
1.00386225e-01 -2.01200306e-01 -8.17843676e-01 6.48033917e-01
4.50552493e-01 -4.20604348e-01 2.02369049e-01 5.35697579e-01
-7.20965266e-01 -6.47174865e-02 -1.12925816e+00 1.06086040e+00
-5.91482341e-01 1.85848594e-01 1.57853484e-01 -1.25448763e+00
9.00021374e-01 1.89153075e-01 4.16521192e-01 -8.18988085e-01
4.56956655e-01 3.41398031e-01 4.89610434e-01 -4.55262452e-01
7.81105101e-01 -5.38696229e-01 -4.80978757e-01 5.95605969e-01
1.09512769e-02 -3.87387216e-01 3.13760966e-01 1.10357225e-01
6.39151514e-01 -4.59990054e-02 3.86290371e-01 -5.52753091e-01
4.24078666e-02 1.69390529e-01 7.08984852e-01 8.84979486e-01
-1.46664441e-01 -2.29683563e-01 1.05402017e+00 -2.06993014e-01
-9.57239985e-01 -9.95330036e-01 1.93359643e-01 1.23878634e+00
4.83888388e-02 6.12122655e-01 -5.94090223e-01 -1.67933866e-01
5.63673377e-01 7.97158003e-01 -7.49283969e-01 -1.16142564e-01
-1.12368673e-01 -1.33222356e-01 -1.67440221e-01 5.27245879e-01
5.39998472e-01 -1.27692652e+00 -7.90913761e-01 3.40864807e-01
2.32060790e-01 -2.76942611e-01 -5.84693313e-01 3.55361015e-01
-5.94323218e-01 -7.10764647e-01 -1.01848197e+00 -1.01688194e+00
4.48688447e-01 1.83460325e-01 1.16893077e+00 -2.98295438e-01
1.93965569e-01 2.83028930e-01 1.45268574e-01 -9.85586882e-01
-2.31966525e-01 7.31380433e-02 4.81468469e-01 -1.22132331e-01
3.59187424e-01 -4.51137871e-01 -5.51328003e-01 1.95950300e-01
-2.42733777e-01 -4.27376665e-02 8.34294736e-01 9.32079852e-01
4.90333289e-01 4.89237100e-01 8.25479388e-01 -5.68383217e-01
1.45677829e+00 -5.40602326e-01 -8.25630426e-01 3.38454962e-01
-1.25345838e+00 -5.17472811e-02 3.33373636e-01 -6.66644037e-01
-1.42518294e+00 -2.41367817e-01 4.58329171e-01 -2.54156142e-01
3.58547091e-01 7.62450993e-01 1.84366211e-01 4.57788676e-01
4.52450424e-01 3.48381013e-01 3.25166851e-01 -2.00246632e-01
2.24607721e-01 7.46705413e-01 7.74414062e-01 -6.25911653e-01
8.57989311e-01 -1.89106777e-01 9.74527895e-02 1.24558806e-01
-5.81060767e-01 -1.98978677e-01 -5.05401373e-01 -3.35971355e-01
7.88829148e-01 -7.73316443e-01 -1.43105471e+00 2.45474741e-01
-7.56789982e-01 -5.30364752e-01 -8.99062276e-01 7.35955834e-01
-1.25443566e+00 -2.15017408e-01 -3.46418709e-01 -1.26009488e+00
7.19509199e-02 -9.04825687e-01 5.69164753e-01 6.59680188e-01
5.57091227e-03 -1.07625568e+00 -2.85944462e-01 2.30714440e-01
4.66783732e-01 -2.01155484e-01 5.83006501e-01 -5.04016459e-01
-5.62955618e-01 -2.24299803e-02 -5.49703538e-02 2.96156168e-01
2.46374011e-01 -3.50284457e-01 -2.98956018e-02 -1.04774557e-01
6.08055830e-01 -1.06758073e-01 5.26491284e-01 8.63179743e-01
9.36086297e-01 -2.67651320e-01 -4.18744206e-01 3.35577339e-01
1.29798794e+00 1.09648287e+00 3.28212261e-01 6.44282877e-01
2.65897475e-02 9.14558053e-01 1.08027291e+00 4.43038374e-01
2.07877770e-01 2.06269294e-01 3.03409338e-01 3.21646817e-02
5.19242346e-01 -2.76808053e-01 -1.82000198e-03 6.09586179e-01
-7.50407934e-01 3.48570794e-02 -8.55708539e-01 6.52569056e-01
-2.05937290e+00 -1.31093013e+00 2.00791255e-01 2.00789642e+00
6.62440658e-01 6.17652237e-01 3.84878278e-01 -9.82557237e-02
3.72034341e-01 -3.92819196e-01 -4.58093286e-01 -8.83498132e-01
2.46366441e-01 -2.59981602e-01 9.30294514e-01 3.89710456e-01
-4.86033738e-01 1.06481969e+00 7.34455395e+00 7.67074347e-01
-7.63794243e-01 3.10945958e-02 1.02682388e+00 -9.64890644e-02
-5.15716791e-01 2.31470983e-03 -9.51112032e-01 4.64434952e-01
7.80185401e-01 -9.91071403e-01 6.25885665e-01 1.14476812e+00
4.51015651e-01 -1.12238303e-01 -1.02165174e+00 9.80666459e-01
-5.94307780e-01 -1.40648746e+00 -4.47755039e-01 6.61893785e-01
1.07055426e+00 -8.54350686e-01 7.19097853e-01 8.40473533e-01
9.63369787e-01 -1.28557456e+00 8.59649658e-01 1.05272865e+00
8.48510683e-01 -8.35073292e-01 8.14505279e-01 7.57510185e-01
-1.03880095e+00 -9.44241881e-01 -6.20157063e-01 -1.05095398e+00
1.23960204e-01 1.18792213e-01 -6.55399442e-01 4.54087883e-01
2.15703562e-01 1.61059231e-01 1.08610295e-01 3.49919707e-01
3.21097344e-01 9.75001901e-02 2.29207590e-01 -2.94929355e-01
6.42612994e-01 -7.55217910e-01 -7.51459897e-02 6.38934016e-01
8.55364740e-01 7.44714290e-02 1.96228862e-01 1.23984563e+00
-3.06375492e-02 6.31643832e-02 -8.02734733e-01 -3.83646876e-01
5.85787773e-01 8.77758265e-01 -6.56435966e-01 -3.06636065e-01
-2.72788435e-01 7.65960097e-01 -9.80499852e-03 4.15310234e-01
-3.83370996e-01 -7.11651564e-01 7.37253845e-01 3.28629971e-01
-1.61988333e-01 -2.91128069e-01 -6.99771702e-01 -6.09894872e-01
-3.08516920e-01 -5.21009207e-01 -8.39869529e-02 -7.04912186e-01
-1.00432026e+00 -9.08261165e-02 2.37600617e-02 -8.42854500e-01
-5.79956830e-01 -8.41394067e-01 -7.09994614e-01 1.22468555e+00
-1.33623767e+00 -5.73761344e-01 3.27748060e-01 2.27215573e-01
6.99145555e-01 -7.28999674e-01 2.25597247e-01 -5.69709718e-01
-4.06238019e-01 4.51482654e-01 4.30278987e-01 -1.37954950e-01
6.65109232e-02 -1.44883323e+00 2.14668959e-01 3.37831408e-01
-4.10553485e-01 7.53877580e-01 3.60586315e-01 -8.87768209e-01
-1.18994379e+00 -5.43544888e-01 1.17274761e+00 -5.00956059e-01
1.07041419e+00 1.98526457e-02 -2.42746875e-01 7.86610246e-01
4.64984864e-01 -9.11962330e-01 3.00774336e-01 1.14801638e-01
5.71748495e-01 -2.18790099e-01 -8.54988992e-01 8.24981987e-01
1.29335546e+00 -1.29693925e-01 -7.91787505e-01 4.41843092e-01
1.03127289e+00 1.20898291e-01 -1.04757631e+00 -1.04968779e-01
4.39905345e-01 -8.35942209e-01 9.17967558e-01 -6.72010422e-01
5.17761648e-01 3.81064564e-01 1.35666862e-01 -1.68194914e+00
-1.38013148e+00 -9.68498290e-01 3.64156127e-01 9.65057552e-01
4.11379457e-01 -1.03487861e+00 7.39045858e-01 4.74292815e-01
-2.35667095e-01 -8.07387650e-01 -8.91914010e-01 -1.30651677e+00
4.19307113e-01 -5.20336116e-03 1.10216546e+00 1.01317704e+00
4.22076106e-01 3.21895778e-01 -3.46770018e-01 -4.36816126e-01
6.85483098e-01 2.78203815e-01 4.60831761e-01 -1.66635454e+00
-5.80286264e-01 -1.11778188e+00 2.92020917e-01 -9.24259007e-01
1.20756485e-01 -8.27238321e-01 -3.44524026e-01 -1.64443505e+00
2.62312412e-01 -4.25190032e-01 -5.69700122e-01 2.39946425e-01
2.18522757e-01 -4.16899651e-01 5.07745385e-01 4.18353170e-01
-8.64920318e-02 -2.78012678e-02 1.98565054e+00 1.02290668e-01
-6.61036730e-01 3.65296632e-01 -1.67276263e+00 6.71706498e-01
1.03722858e+00 -6.15628362e-02 -6.31316543e-01 -1.85220599e-01
6.02409601e-01 7.50377297e-01 -1.31824136e-01 -5.20900130e-01
7.79864341e-02 -1.21400940e+00 3.34030479e-01 -1.90498650e-01
1.69611588e-01 -9.02330458e-01 4.62226570e-01 9.99088585e-01
-4.04425502e-01 3.14736605e-01 -4.37500983e-01 2.99188763e-01
4.45701256e-02 -5.14771938e-01 2.99346447e-01 -5.10649145e-01
-2.78433830e-01 5.44856824e-02 -8.46183658e-01 -5.05568445e-01
1.36545515e+00 -7.43890405e-01 -5.81737049e-02 -3.42116356e-01
-1.14000058e+00 5.68174422e-01 3.30710709e-01 1.78606480e-01
1.15597129e-01 -1.45741141e+00 -5.33142388e-01 1.29021868e-01
-2.55104095e-01 -5.18435061e-01 1.07348785e-01 5.57959855e-01
-2.31787950e-01 8.88849676e-01 -5.41598320e-01 -7.15302899e-02
-5.90144873e-01 8.73781204e-01 4.43594813e-01 -8.94926786e-01
2.91014344e-01 9.75870669e-01 4.35691237e-01 -1.09038604e-02
-1.00928649e-01 -4.34529930e-01 -7.27239609e-01 2.62541592e-01
9.20796394e-02 4.49571341e-01 -5.54809093e-01 -2.29159117e-01
1.75172687e-01 6.32509887e-01 1.58029959e-01 -3.89697701e-01
9.77527380e-01 -3.02804142e-01 -4.71935384e-02 4.34737563e-01
3.98423821e-01 -3.49513471e-01 -1.19977915e+00 -2.04959184e-01
8.34953710e-02 -6.99298620e-01 -5.88149345e-03 -7.59010732e-01
-7.79692948e-01 4.96777892e-01 4.13811684e-01 9.41229999e-01
1.07861316e+00 -1.82585612e-01 7.45303631e-02 3.89308125e-01
3.22104245e-01 -1.73201811e+00 7.20739663e-01 5.28043926e-01
8.26814950e-01 -7.94817746e-01 -5.99753141e-01 -2.61668533e-01
-1.00990558e+00 5.95066667e-01 5.42323947e-01 -1.68161616e-01
8.30651283e-01 1.87193096e-01 -9.84575003e-02 -1.54903993e-01
-9.10417914e-01 -3.08754832e-01 -1.22328937e-01 8.02323461e-01
3.37750256e-01 6.62955046e-01 -8.66363823e-01 1.20114076e+00
-8.56226504e-01 1.72402859e-01 5.49988687e-01 6.24327540e-01
-9.25275028e-01 -1.15219796e+00 -6.42666638e-01 8.90746474e-01
-7.00148404e-01 6.08889163e-02 -8.32979847e-03 7.39826560e-01
3.83172572e-01 8.25556576e-01 8.11333895e-01 -2.50112504e-01
6.26817763e-01 2.10394710e-01 3.85097384e-01 -6.35557711e-01
-5.84521830e-01 3.73880923e-01 -1.50123551e-01 -1.56330571e-01
6.22252226e-02 -8.93619001e-01 -1.04652107e+00 -5.20909190e-01
-1.34583816e-01 5.03943682e-01 4.96872485e-01 6.51027977e-01
1.04051657e-01 9.47943032e-01 1.16775656e+00 -7.53801763e-01
-1.40334082e+00 -8.55419040e-01 -1.24125457e+00 2.90699899e-01
-2.76882380e-01 -7.85221994e-01 -3.19449633e-01 4.85752076e-02] | [4.383849143981934, 3.1656956672668457] |
dc400202-97b0-44ed-b855-a248e8e56b35 | is-kalman-filter-optimal-for-fault-detection | 2301.11573 | null | https://arxiv.org/abs/2301.11573v2 | https://arxiv.org/pdf/2301.11573v2.pdf | On the optimality of Kalman Filter for Fault Detection | Kalman filter is widely used for residual generation in fault detection. It leads to optimality in fault detection using some performance indices and also leads to statistically sound residual evaluation and threshold setting. This paper shows that these nice features do not necessarily imply an optimal fault detection performance. Based on a performance index related to fault detection rate and false alarm rate, several occasions where Kalman filter should not be used are pointed out; further the residual evaluation and threshold setting are discussed, in which it is pointed out that in stochastic setting an optimal statistical test of Kamlan filter is not related to optimality of commonly used detection performance indicators. The theoretical analysis is verified through Monte Carlo simulations. | ['Yucai Zhu', 'Jinming Zhou'] | 2023-01-27 | null | null | null | null | ['fault-detection'] | ['miscellaneous'] | [-2.19171584e-01 -1.97757140e-01 3.30601871e-01 2.02504243e-03
-4.19082642e-01 -7.07161203e-02 4.22175735e-01 1.37311816e-01
-2.55367339e-01 1.13527167e+00 -2.28289917e-01 -5.23806036e-01
-8.00391316e-01 -6.28525853e-01 -1.21363625e-01 -9.28333163e-01
-3.98294777e-01 1.68255568e-01 4.94063973e-01 -5.23036607e-02
4.59836304e-01 7.41324127e-01 -1.68047059e+00 -4.38385814e-01
6.89551353e-01 8.92145514e-01 1.08859278e-01 8.83257449e-01
4.80222642e-01 6.14009261e-01 -1.27169096e+00 2.34945118e-01
2.30673462e-01 -7.64618456e-01 -8.09053361e-01 1.54759079e-01
-4.10932720e-01 -3.13524932e-01 -1.36607140e-01 1.00711238e+00
5.05406141e-01 9.57878530e-02 8.46450686e-01 -1.10591185e+00
-5.51343560e-02 5.03671944e-01 2.04003215e-01 6.55854940e-01
5.13992548e-01 -1.17846631e-01 4.98634040e-01 -7.48813093e-01
-7.70133734e-02 8.82747293e-01 5.70807815e-01 2.59431228e-02
-7.40440249e-01 -2.26523399e-01 -3.41020554e-01 1.83861271e-01
-1.59035397e+00 -9.97150093e-02 3.64931107e-01 -3.33570689e-01
8.76037836e-01 5.35456121e-01 6.78113163e-01 5.72070479e-01
9.24202085e-01 2.16549739e-01 1.24611521e+00 -6.72080994e-01
4.66214210e-01 -1.63783923e-01 4.62845117e-01 5.95075786e-01
9.05946791e-01 5.20281255e-01 1.00610591e-01 -8.06326345e-02
1.05053961e+00 -2.39323527e-01 -6.58478737e-01 2.32758835e-01
-9.89052653e-01 5.66131949e-01 -1.23639442e-01 7.66025662e-01
-5.08469880e-01 2.05150217e-01 5.65255165e-01 7.76504755e-01
8.84252191e-02 3.10208410e-01 -3.33609253e-01 -2.22889319e-01
-8.02566826e-01 1.99625909e-01 9.90531683e-01 4.36955988e-01
4.87791359e-01 6.42798901e-01 -1.53239161e-01 4.66873646e-01
3.63536209e-01 8.86845469e-01 3.99220109e-01 -7.25162029e-01
-3.37677211e-01 4.14063781e-01 2.70906448e-01 -5.45898557e-01
-6.47145033e-01 -8.07061434e-01 -7.39919126e-01 6.39751554e-01
3.78105640e-01 -3.99875462e-01 -7.68613875e-01 1.07337534e+00
-1.50713533e-01 3.02636802e-01 3.27249944e-01 6.57316387e-01
1.65431604e-01 3.86100262e-01 -4.58391160e-01 -8.78577173e-01
1.18424809e+00 3.88543829e-02 -1.11904740e+00 3.49535167e-01
7.17355371e-01 -1.03497219e+00 4.08808321e-01 9.53996360e-01
-8.27959836e-01 -3.85971814e-01 -1.21602929e+00 1.09490323e+00
-1.30489364e-01 7.22617656e-02 4.26843792e-01 1.19028425e+00
-9.14187789e-01 7.72059917e-01 -7.81703353e-01 -3.73283207e-01
-4.00255919e-01 3.16924483e-01 -2.76599526e-01 1.03001036e-01
-1.33204544e+00 1.25387478e+00 5.36238372e-01 5.20219445e-01
-9.47480202e-01 -1.11484669e-01 -5.57110190e-01 -1.55611202e-01
2.16092288e-01 -5.83139241e-01 1.15064800e+00 -3.64126295e-01
-1.46462107e+00 2.15682492e-01 -2.05068551e-02 -7.70546317e-01
5.66900671e-01 -4.83506799e-01 -9.67783391e-01 2.34437361e-01
1.86727978e-02 -6.07571125e-01 7.69884646e-01 -9.57745194e-01
-6.95419788e-01 5.89911863e-02 -9.48400125e-02 -7.38153905e-02
3.08678657e-01 1.69583350e-01 1.34303004e-01 -6.64206266e-01
5.56976259e-01 -5.29915214e-01 -1.98720217e-01 -1.03740644e+00
-4.23212528e-01 -4.49207306e-01 8.47575009e-01 -4.42924112e-01
1.42788184e+00 -1.68646407e+00 -4.73524660e-01 7.18335867e-01
-4.47251737e-01 1.30361304e-01 5.41228116e-01 7.13150144e-01
-3.26086462e-01 -2.05095738e-01 -1.43922538e-01 5.33676505e-01
1.07426466e-02 2.47944221e-01 -2.35311881e-01 1.03551161e+00
6.25707805e-02 3.02570045e-01 -7.13869274e-01 -1.98526263e-01
7.65591919e-01 2.48910129e-01 -1.88894480e-01 1.53954282e-01
4.71246034e-01 2.27473617e-01 -3.42454106e-01 6.20215893e-01
4.81519848e-01 5.65108806e-02 -2.51652479e-01 -1.13531247e-01
-3.46592404e-02 1.42332599e-01 -1.71877587e+00 6.32568240e-01
-2.17730895e-01 4.37168360e-01 -2.82108724e-01 -1.35489380e+00
1.20334888e+00 9.17369843e-01 4.29893374e-01 -5.59636891e-01
3.47450018e-01 5.28545618e-01 9.81890187e-02 -4.83376652e-01
2.42765680e-01 -2.33603477e-01 -1.57226309e-01 2.86577404e-01
-3.75286676e-02 -2.27942228e-01 3.18255723e-01 -8.90456438e-02
1.42332137e+00 -2.84650892e-01 3.65755230e-01 -8.89492750e-01
8.69578660e-01 -3.46812040e-01 5.23565590e-01 1.06058359e+00
5.56116179e-02 2.29533225e-01 2.91548640e-01 -1.10094689e-01
-5.66074014e-01 -1.09555376e+00 -6.15512908e-01 9.14525986e-02
1.24526545e-01 -3.09711456e-01 -6.00295305e-01 -5.51900208e-01
-1.19400769e-01 5.87614238e-01 -5.13852596e-01 -3.06573153e-01
-3.53018671e-01 -1.05771613e+00 5.21438122e-01 2.31716126e-01
3.93981129e-01 -8.13913405e-01 -9.52198625e-01 4.30074632e-01
4.00750011e-01 -6.06760800e-01 4.52855587e-01 6.38361633e-01
-1.04815900e+00 -1.51033974e+00 -6.86526000e-01 -2.82712132e-01
7.78360128e-01 1.35552585e-01 8.78017068e-01 6.11291647e-01
-3.41017991e-01 5.56348860e-01 -6.94022119e-01 -2.80845881e-01
-8.14256310e-01 -6.18576288e-01 4.11292553e-01 -4.00812626e-01
1.86276153e-01 -3.53026658e-01 -5.16750455e-01 6.84210122e-01
-1.00455916e+00 -9.85690594e-01 6.20878339e-01 9.42762971e-01
5.79930507e-02 8.23048353e-01 8.34729075e-01 -7.03158319e-01
7.13618517e-01 -1.50178730e-01 -7.45765030e-01 1.43817037e-01
-1.11848545e+00 8.12093690e-02 3.29153121e-01 2.35822752e-01
-7.96467066e-01 -4.42325443e-01 -4.19662774e-01 -2.51984224e-02
-5.03119946e-01 5.45652509e-01 -9.42310244e-02 -1.16024926e-01
8.67724061e-01 8.97502974e-02 -1.25755398e-02 -3.41931731e-01
-1.94953308e-01 4.98596668e-01 5.10056376e-01 -1.85526863e-01
8.97322476e-01 2.18070924e-01 3.62032741e-01 -1.08375895e+00
-5.83119392e-01 -5.33427954e-01 -3.91768008e-01 -4.33945179e-01
3.10348779e-01 -6.64358199e-01 -7.42562234e-01 6.41133726e-01
-7.60761917e-01 -1.05282567e-01 -1.64875045e-01 9.56145704e-01
-5.85796595e-01 6.77967668e-01 -6.92061543e-01 -1.46350062e+00
-2.86773052e-02 -1.11426950e+00 7.17723846e-01 -4.33510356e-02
-1.81506589e-01 -1.17611480e+00 -1.99773237e-01 -4.24941719e-01
2.85159558e-01 1.54780030e-01 3.79133701e-01 -4.01332557e-01
-2.54881591e-01 -8.19518685e-01 9.00785252e-02 7.23668098e-01
3.98986459e-01 2.17996597e-01 -6.26378059e-01 -4.47372019e-01
4.09313142e-01 3.15295607e-01 7.14832127e-01 7.21090555e-01
5.40786028e-01 3.87387984e-02 -2.50672221e-01 6.49345517e-02
1.72150767e+00 5.36999106e-01 1.07315755e+00 3.53996247e-01
1.64429575e-01 4.02796507e-01 1.04331458e+00 6.57200813e-01
-5.28143644e-01 4.60654587e-01 4.29415315e-01 1.52806520e-01
1.94170788e-01 4.61275637e-01 5.67153692e-01 7.68537700e-01
-8.24781135e-02 -4.42168921e-01 -6.97257578e-01 4.17511970e-01
-1.61448967e+00 -1.14727449e+00 -7.76701689e-01 2.54764366e+00
1.99362129e-01 6.00957453e-01 5.43073565e-02 1.05277395e+00
8.38705719e-01 -4.57472652e-01 9.36579853e-02 -2.49098167e-01
-3.66480052e-01 2.49735951e-01 8.76415372e-01 7.14527905e-01
-9.50529277e-01 2.83159584e-01 7.76305580e+00 7.18962073e-01
-6.81022406e-01 -1.34634506e-02 8.10418725e-02 4.31865871e-01
9.54136699e-02 2.24296093e-01 -6.54501498e-01 5.71400940e-01
1.19516826e+00 -4.03603226e-01 -3.17412198e-01 3.62060785e-01
5.03934503e-01 -8.21669936e-01 -6.93988323e-01 9.58816051e-01
-1.21000983e-01 -8.37666273e-01 -3.95551443e-01 2.48198450e-01
4.66588259e-01 -5.16449988e-01 -3.76013696e-01 1.43237272e-02
3.29523236e-01 -8.77888083e-01 5.50171733e-01 7.46420324e-01
1.43653587e-01 -1.13551414e+00 1.50197399e+00 3.53216403e-03
-8.84706914e-01 -2.81418443e-01 -3.90521646e-01 -3.84248108e-01
5.74780881e-01 1.28643084e+00 -7.53340125e-01 1.08345377e+00
4.71769273e-01 2.95738339e-01 -3.49453479e-01 1.68513453e+00
-5.34917176e-01 9.86897528e-01 -3.43788326e-01 7.98430294e-02
-5.94568327e-02 -5.31571992e-02 7.12370098e-01 1.11770856e+00
6.79308951e-01 -4.30879295e-02 -6.90141097e-02 3.84528309e-01
9.95679915e-01 1.13601554e-02 -5.58207452e-01 5.68563640e-01
5.14588594e-01 6.80202901e-01 -1.14740455e+00 -2.16524616e-01
-2.86053181e-01 9.12018657e-01 -7.72978127e-01 1.63681388e-01
-7.45028496e-01 -5.50136328e-01 5.07666588e-01 -5.92003241e-02
1.30718306e-01 -9.52563286e-02 2.53588855e-02 -7.48479187e-01
-1.68093562e-01 -5.51204622e-01 4.23327118e-01 -2.85195321e-01
-1.08308685e+00 4.95434284e-01 4.54516143e-01 -1.48778844e+00
-4.65551704e-01 -7.81469166e-01 -7.77683139e-01 9.35369968e-01
-7.50524580e-01 -1.82072520e-01 4.92718369e-02 4.50111568e-01
2.96141028e-01 -2.64588416e-01 7.41339147e-01 1.73679292e-01
-8.10508847e-01 3.28152806e-01 1.40891775e-01 -8.23468864e-02
4.89694834e-01 -1.39959002e+00 -3.14292982e-02 1.43369448e+00
-2.34921500e-01 5.00688255e-01 1.62328100e+00 -8.53636205e-01
-1.13838518e+00 -5.87885857e-01 6.41562223e-01 -3.06641638e-01
6.30485058e-01 3.41144174e-01 -1.00035024e+00 1.59164533e-01
3.85925584e-02 -3.04428756e-01 3.15903276e-01 -1.37273371e-01
4.79682863e-01 -7.43578970e-02 -1.04667306e+00 1.35303959e-01
4.66958553e-01 -3.75716269e-01 -9.43986952e-01 5.14372289e-01
2.24577263e-01 -8.52586329e-02 -1.03061104e+00 6.15739524e-01
2.19615281e-01 -1.26660013e+00 6.23122096e-01 7.87284821e-02
-4.98178184e-01 -6.14423633e-01 -2.72790678e-02 -1.17061734e+00
-2.41711363e-01 -4.98967439e-01 1.82248309e-01 1.08772039e+00
2.49271974e-01 -1.11568248e+00 4.69032347e-01 2.87154429e-02
-2.78019637e-01 -3.10059935e-01 -1.20353281e+00 -1.31408226e+00
-1.89573795e-01 -7.52322853e-01 2.58906335e-01 5.61183631e-01
1.31905908e-02 5.13436310e-02 -2.73896426e-01 5.23544729e-01
6.30014300e-01 -2.94000447e-01 4.07267302e-01 -1.56420827e+00
-2.69326597e-01 -3.26486140e-01 -9.55653906e-01 -5.56098163e-01
-6.56511933e-02 -1.65353939e-01 1.83901981e-01 -1.63749349e+00
-5.14233649e-01 -3.67655724e-01 -7.40287423e-01 1.00413151e-01
-2.45006010e-02 2.12677896e-01 -4.28976029e-01 8.11153501e-02
-1.78344354e-01 1.91545025e-01 5.57524145e-01 3.76481950e-01
6.27566576e-02 4.89797413e-01 -4.32317816e-02 5.92582703e-01
7.68985152e-01 -3.77891421e-01 -4.00444776e-01 3.31251681e-01
3.30604136e-01 4.24088210e-01 5.71849346e-01 -1.64919579e+00
-5.23281805e-02 5.19036613e-02 3.08085710e-01 -7.68431127e-01
-1.98980402e-02 -1.09632897e+00 4.27403033e-01 1.09155464e+00
3.72133791e-01 5.04475355e-01 -9.41335484e-02 6.20665014e-01
-2.55854696e-01 -9.07362938e-01 6.28226221e-01 -3.44684646e-02
-8.85471165e-01 -3.65898848e-01 -8.57751429e-01 -6.59148633e-01
1.12578809e+00 -6.20850563e-01 -2.09886506e-01 -4.11269277e-01
-9.29670870e-01 4.22635768e-03 5.20291507e-01 3.22259143e-02
5.70673704e-01 -1.10825408e+00 -6.94497287e-01 2.03203455e-01
-8.49238187e-02 -6.77605867e-01 3.32993656e-01 1.28517449e+00
-6.44121647e-01 5.39486408e-01 -4.90504280e-02 -5.64661026e-01
-1.10875356e+00 3.89583409e-01 4.10963982e-01 2.68673431e-02
-7.88137615e-01 6.21093035e-01 -3.44458669e-01 5.32545686e-01
6.11287914e-02 -3.63376647e-01 -1.09573089e-01 -1.31547213e-01
6.63236439e-01 8.54155898e-01 5.90227485e-01 -5.35851657e-01
-4.41696733e-01 3.67025226e-01 4.78246182e-01 -2.33450085e-01
6.95470035e-01 -3.43808621e-01 -2.54354894e-01 7.04337656e-01
7.39826441e-01 -4.42548096e-02 -8.26133311e-01 3.35168421e-01
3.73086929e-01 -3.26839209e-01 2.49074817e-01 -6.52644157e-01
-7.59757638e-01 3.53163868e-01 9.92171109e-01 9.00978327e-01
1.30367506e+00 -3.26212108e-01 1.55846626e-01 4.39774364e-01
8.07230294e-01 -1.10670698e+00 -3.54435086e-01 5.23763835e-01
7.90536523e-01 -6.95179582e-01 1.90452293e-01 -4.95388597e-01
-7.89098516e-02 1.27994192e+00 2.85054594e-01 -5.86148262e-01
8.34547102e-01 6.63368464e-01 1.24527842e-01 -1.59037352e-01
-6.35512888e-01 -4.92716134e-01 -7.91936442e-02 6.34775817e-01
4.01757509e-01 1.25558630e-01 -9.96067762e-01 1.01485707e-01
-7.36526251e-02 -1.07174784e-01 7.43346572e-01 9.57264245e-01
-9.39448476e-01 -1.22710645e+00 -1.06093991e+00 7.08285570e-01
-6.97315037e-01 2.51892507e-01 1.58932164e-01 1.01432478e+00
-2.03586429e-01 1.37059140e+00 4.09828424e-02 -3.89200300e-01
4.43175167e-01 2.02682838e-01 3.62504214e-01 -3.77744526e-01
-4.01846021e-01 1.63612857e-01 2.23869443e-01 -4.77831721e-01
-4.80892718e-01 -5.88296175e-01 -1.30441308e+00 -7.46110678e-02
-9.00534630e-01 9.56087708e-01 4.82040912e-01 1.31392455e+00
-3.18926603e-01 8.43097329e-01 4.90350038e-01 -4.95650321e-01
-5.99986017e-01 -1.23711514e+00 -1.33305776e+00 -1.16330795e-01
2.10662246e-01 -1.00705349e+00 -8.75145912e-01 -2.38724962e-01] | [6.3239336013793945, 2.6717512607574463] |
7224c809-490e-40be-a325-66eb8bba4fa9 | sneaky-spikes-uncovering-stealthy-backdoor | 2302.06279 | null | https://arxiv.org/abs/2302.06279v2 | https://arxiv.org/pdf/2302.06279v2.pdf | Sneaky Spikes: Uncovering Stealthy Backdoor Attacks in Spiking Neural Networks with Neuromorphic Data | Deep neural networks (DNNs) have demonstrated remarkable performance across various tasks, including image and speech recognition. However, maximizing the effectiveness of DNNs requires meticulous optimization of numerous hyperparameters and network parameters through training. Moreover, high-performance DNNs entail many parameters, which consume significant energy during training. In order to overcome these challenges, researchers have turned to spiking neural networks (SNNs), which offer enhanced energy efficiency and biologically plausible data processing capabilities, rendering them highly suitable for sensory data tasks, particularly in neuromorphic data. Despite their advantages, SNNs, like DNNs, are susceptible to various threats, including adversarial examples and backdoor attacks. Yet, the field of SNNs still needs to be explored in terms of understanding and countering these attacks. This paper delves into backdoor attacks in SNNs using neuromorphic datasets and diverse triggers. Specifically, we explore backdoor triggers within neuromorphic data that can manipulate their position and color, providing a broader scope of possibilities than conventional triggers in domains like images. We present various attack strategies, achieving an attack success rate of up to 100\% while maintaining a negligible impact on clean accuracy. Furthermore, we assess these attacks' stealthiness, revealing that our most potent attacks possess significant stealth capabilities. Lastly, we adapt several state-of-the-art defenses from the image domain, evaluating their efficacy on neuromorphic data and uncovering instances where they fall short, leading to compromised performance. | ['Aitor Urbieta', 'Stjepan Picek', 'Oguzhan Ersoy', 'Gorka Abad'] | 2023-02-13 | null | null | null | null | ['event-based-vision'] | ['computer-vision'] | [ 5.89351773e-01 -2.22185954e-01 1.74635842e-01 1.39696762e-01
-2.06249669e-01 -9.62022960e-01 5.92993855e-01 -2.31420055e-01
-7.65138328e-01 6.62216663e-01 -3.41697067e-01 -4.15048122e-01
3.99345793e-02 -7.74161160e-01 -9.56590116e-01 -1.12667000e+00
-4.43910211e-01 -4.09860164e-01 3.45712334e-01 -1.75992340e-01
3.78506273e-01 8.39524508e-01 -1.39356756e+00 -8.29343572e-02
5.51746905e-01 1.05806220e+00 -7.46306106e-02 5.41393042e-01
2.24093124e-01 1.37174785e-01 -1.12123239e+00 -5.11179864e-01
4.56905395e-01 -1.84272632e-01 -1.78335518e-01 -7.22716331e-01
1.40469819e-01 -2.01371580e-01 -7.16560364e-01 1.48601091e+00
7.48474777e-01 -3.81391108e-01 2.51603663e-01 -1.44789124e+00
-5.57098091e-01 6.87488973e-01 -1.30495086e-01 5.09131312e-01
-1.33822247e-01 5.98683953e-01 4.73317474e-01 -3.30285281e-01
3.74401897e-01 1.03166699e+00 4.73262012e-01 1.22145200e+00
-1.39558375e+00 -1.42678154e+00 -1.44767180e-01 7.69480094e-02
-1.15443289e+00 -6.99369013e-01 5.92364848e-01 8.93787853e-03
1.08110046e+00 1.72426030e-01 6.72826111e-01 1.98195314e+00
6.27126455e-01 3.98318887e-01 1.25131118e+00 6.40296265e-02
6.47693336e-01 -4.08500642e-01 -6.09422252e-02 3.30738783e-01
7.28270173e-01 4.85204279e-01 -7.04724967e-01 -4.39408630e-01
7.77932644e-01 -4.25275974e-02 -4.08913910e-01 -4.24152352e-02
-9.55506504e-01 5.17203331e-01 6.27943993e-01 1.57311782e-01
-1.16759934e-01 6.94241345e-01 3.83074760e-01 7.71400034e-02
-3.84625018e-01 6.97682261e-01 -2.03037754e-01 -1.39408991e-01
-4.85186428e-01 1.05349481e-01 7.75595605e-01 6.09779835e-01
3.56094897e-01 4.68434721e-01 1.04840100e-01 3.64835948e-01
5.81956953e-02 7.52176344e-01 3.47605616e-01 -7.50590384e-01
2.60395944e-01 3.61280471e-01 -3.53332341e-01 -8.63934875e-01
-3.79659534e-01 -4.27219570e-01 -9.98338580e-01 5.04388034e-01
2.49270082e-01 -2.51534700e-01 -1.13836849e+00 2.27567363e+00
6.59167022e-02 3.39310884e-01 2.95583904e-01 7.15970218e-01
5.14268458e-01 4.10661131e-01 2.66344517e-01 3.41773819e-04
1.39061010e+00 -2.08668724e-01 -5.44099212e-01 -3.87052238e-01
1.34869581e-02 -2.11627707e-01 7.28089929e-01 5.70159078e-01
-9.17075455e-01 3.34903486e-02 -1.45345306e+00 3.30110431e-01
-6.69278443e-01 -6.61858976e-01 6.91972733e-01 1.24224830e+00
-9.18005466e-01 6.69471025e-01 -1.22660148e+00 -2.29628623e-01
9.99317110e-01 8.82954895e-01 -1.42884493e-01 1.84223831e-01
-1.23087299e+00 7.32669055e-01 2.86766857e-01 -2.30556801e-02
-1.61510694e+00 -5.94001651e-01 -5.40549099e-01 1.64169446e-02
-2.16475688e-02 -4.48305607e-01 6.53697193e-01 -3.26640189e-01
-1.39302325e+00 5.23823738e-01 3.83640975e-01 -9.65184629e-01
2.05453008e-01 8.55760425e-02 -7.02088475e-01 2.60904789e-01
-3.78136009e-01 8.09874177e-01 8.42834771e-01 -1.08590889e+00
-3.39672528e-02 -4.43279862e-01 8.28950405e-02 -4.72773224e-01
-9.47379947e-01 1.62361994e-01 1.96708320e-03 -7.50486970e-01
-1.22726008e-01 -1.10404170e+00 -2.48131439e-01 1.39624730e-01
-6.73869252e-01 2.80576408e-01 1.05951965e+00 6.40416071e-02
8.41278613e-01 -2.25001884e+00 -7.37528875e-02 2.55634099e-01
3.91801178e-01 7.49620736e-01 -3.22800785e-01 2.50970483e-01
2.45044619e-01 5.89365065e-01 -3.04259449e-01 1.19208947e-01
-9.89478752e-02 4.46828783e-01 -6.63880825e-01 5.93017459e-01
3.41110855e-01 1.01390362e+00 -5.86016893e-01 6.93237185e-02
-5.34605011e-02 6.97501421e-01 -5.07993996e-01 -7.89940208e-02
-8.22237730e-02 3.10411841e-01 -4.58516210e-01 9.07813668e-01
6.12578511e-01 9.31837130e-03 6.64856704e-03 -1.35007426e-01
1.22731708e-01 1.62599355e-01 -4.58040178e-01 1.25516009e+00
-2.00076737e-02 7.08526671e-01 6.88766465e-02 -8.79081786e-01
1.00605798e+00 -5.17252227e-03 3.06817919e-01 -9.34394538e-01
4.81525242e-01 3.10865968e-01 3.59720051e-01 -3.00781399e-01
6.78555742e-02 8.16454589e-02 -2.03841671e-01 2.97026336e-01
3.59225273e-02 7.21639320e-02 -2.52309442e-01 1.50106803e-01
1.77773285e+00 -3.69351149e-01 -1.51428834e-01 -3.26558501e-01
-9.19827223e-02 -2.91855961e-01 5.59664905e-01 1.02012694e+00
-4.67220098e-01 2.03019232e-01 4.71774399e-01 -1.97608724e-01
-9.12437618e-01 -1.32236135e+00 -4.27292436e-01 4.72118378e-01
5.31028926e-01 -2.27436304e-01 -9.87962425e-01 -2.78640479e-01
-1.05617411e-01 3.19237024e-01 -6.19793355e-01 -7.48476088e-01
-4.87719774e-01 -1.16951346e+00 1.79788685e+00 3.65492702e-01
8.68569493e-01 -1.02717698e+00 -1.25465548e+00 1.93737060e-01
2.48706415e-01 -1.33461106e+00 8.94941092e-02 7.55829275e-01
-9.13619518e-01 -9.85468447e-01 -3.38835090e-01 -3.86590034e-01
5.83273411e-01 1.04735166e-01 6.18819237e-01 7.78869838e-02
-6.31513536e-01 9.54549685e-02 -1.29416451e-01 -7.19516218e-01
-2.77744293e-01 -1.00308858e-01 5.00605702e-01 -3.67855698e-01
2.75188118e-01 -1.07423890e+00 -7.45047510e-01 3.61389667e-01
-1.27266300e+00 -5.03713548e-01 5.90950608e-01 7.66862631e-01
5.76875925e-01 -4.15973030e-02 6.85006618e-01 -4.90171254e-01
6.77686453e-01 -5.33421576e-01 -6.68338716e-01 1.41226217e-01
-4.25266385e-01 1.40039459e-01 1.02092695e+00 -8.79460037e-01
-3.24511766e-01 -1.55452535e-01 -2.30797172e-01 -4.41880047e-01
-4.66603115e-02 -1.01288617e-01 -3.05297494e-01 -6.94928408e-01
1.00658023e+00 2.88754314e-01 -2.14485470e-02 -2.05595165e-01
-5.74291646e-02 1.83366299e-01 6.72369838e-01 -6.33815527e-01
9.43018496e-01 7.91832268e-01 2.67709970e-01 -7.47788489e-01
-2.18359619e-01 4.45154816e-01 2.09635377e-01 -2.91498527e-02
6.71322525e-01 -4.80067372e-01 -1.05059707e+00 9.03110087e-01
-1.02463531e+00 -2.77895719e-01 6.11420237e-02 1.06831066e-01
-1.87569126e-01 2.07001194e-01 -8.25144470e-01 -8.15793991e-01
-5.14942944e-01 -1.33116674e+00 5.19165874e-01 5.93599677e-01
2.44867764e-02 -5.64934254e-01 -1.73535630e-01 -1.48463026e-02
5.94489872e-01 5.15710533e-01 1.11581874e+00 -9.10366297e-01
-7.69144535e-01 4.07712581e-03 -5.77034317e-02 1.85920104e-01
-4.51246612e-02 -9.00120568e-03 -1.29055285e+00 -5.29333413e-01
3.54592986e-02 -6.11422002e-01 9.17606831e-01 2.18659565e-01
1.46023583e+00 -5.24027884e-01 -4.43333566e-01 1.10957932e+00
1.44186509e+00 4.96971607e-01 9.18343008e-01 5.12712300e-01
3.78735483e-01 3.26156259e-01 -1.92397520e-01 3.42756569e-01
-2.29305610e-01 3.71334016e-01 1.22447646e+00 1.84352577e-01
1.25942543e-01 -1.74784899e-01 5.29367745e-01 3.11749101e-01
2.30241239e-01 -5.56920171e-01 -7.48015046e-01 2.11422458e-01
-1.24656057e+00 -8.05160165e-01 1.74097583e-01 2.06913733e+00
7.72970557e-01 4.97960329e-01 2.94890255e-03 1.97842240e-01
7.25614250e-01 1.43255726e-01 -1.25875068e+00 -4.48193610e-01
-6.26332879e-01 5.78487515e-01 7.95320392e-01 -3.68015975e-01
-9.23485994e-01 8.67768884e-01 6.95285797e+00 7.40781009e-01
-1.40998626e+00 -1.74425930e-01 4.50393736e-01 -4.68232632e-01
-3.64669353e-01 -1.98016718e-01 -8.20540011e-01 6.30274117e-01
1.05447233e+00 2.96296887e-02 7.76760042e-01 6.02724612e-01
-1.82579786e-01 1.24459945e-01 -7.89859235e-01 9.04652238e-01
-1.95593536e-01 -1.55798626e+00 1.25271201e-01 5.30662894e-01
4.77722317e-01 3.74437183e-01 3.87973040e-01 1.48603283e-02
4.56421614e-01 -1.28328216e+00 4.79673266e-01 -9.61800888e-02
6.92624211e-01 -9.55450892e-01 2.85373390e-01 1.53570592e-01
-6.01966143e-01 -3.32260609e-01 -6.81057334e-01 7.48194531e-02
-2.20796943e-01 5.53976297e-01 -2.51791239e-01 -4.43467870e-02
1.03610766e+00 1.66111827e-01 -5.17941177e-01 9.53613698e-01
-7.44039342e-02 5.86617231e-01 -5.40342391e-01 -3.95232022e-01
1.44710183e-01 2.95069724e-01 6.91320717e-01 9.98355925e-01
3.93385410e-01 6.46832064e-02 -3.14820677e-01 1.23447537e+00
-4.96526003e-01 -6.38815463e-01 -9.19317961e-01 -2.93011516e-01
1.09447074e+00 1.15443647e+00 -8.45590353e-01 1.43208817e-01
1.48474708e-01 7.79038787e-01 1.38172016e-01 3.36571544e-01
-9.34378028e-01 -5.89591980e-01 1.32668042e+00 -3.45674843e-01
-1.80973113e-02 -3.45399976e-01 -6.18318796e-01 -8.30440342e-01
-1.19978517e-01 -1.03916252e+00 1.59649290e-02 -2.04871327e-01
-1.15870392e+00 6.78981423e-01 -3.32281917e-01 -9.40551341e-01
1.06330417e-01 -8.60921502e-01 -6.54883325e-01 3.16290110e-01
-1.41299117e+00 -6.48487628e-01 -9.76814702e-02 8.22800159e-01
-3.20431516e-02 -2.26098970e-01 8.28199327e-01 2.07636550e-01
-1.00462317e+00 1.00689518e+00 3.57409716e-02 2.30443642e-01
3.77076119e-01 -6.22560024e-01 7.67521858e-01 1.15980697e+00
2.02417716e-01 9.77024674e-01 7.76621878e-01 -4.68837976e-01
-1.91072214e+00 -1.00522327e+00 -3.77549008e-02 -2.09734350e-01
7.16255724e-01 -7.44345129e-01 -8.64708960e-01 1.50412336e-01
2.31255181e-02 1.46953747e-01 7.18971014e-01 -4.75373447e-01
-7.33832002e-01 -6.33256361e-02 -1.36968875e+00 1.18972301e+00
1.36364615e+00 -5.35166144e-01 -1.41156435e-01 -5.14422283e-02
6.21954560e-01 -1.04153469e-01 -6.50833309e-01 6.34298265e-01
6.71072781e-01 -9.52198267e-01 1.17354512e+00 -5.13587415e-01
3.86935651e-01 -1.19178392e-01 -1.56884491e-01 -1.18697238e+00
1.02352090e-01 -9.79496479e-01 -3.18882674e-01 1.16630387e+00
1.67398512e-01 -9.03380454e-01 8.05202305e-01 5.24835169e-01
-8.47729295e-02 -7.41823852e-01 -1.29761660e+00 -1.17481196e+00
1.39370456e-01 -4.09372836e-01 6.00831389e-01 6.79098785e-01
-2.62242090e-02 -2.87990034e-01 -2.26263344e-01 3.56289446e-01
9.32973206e-01 -4.59145039e-01 5.36598265e-01 -8.94020498e-01
-3.61102563e-03 -6.48632526e-01 -8.02984655e-01 -6.46905065e-01
1.72553182e-01 -7.41397917e-01 6.70806244e-02 -7.63552547e-01
5.94571233e-02 -3.39814812e-01 -5.57458401e-01 6.63833678e-01
1.50793329e-01 6.31553233e-01 1.17263600e-01 1.76962152e-01
-2.46876925e-01 4.16529745e-01 8.36894035e-01 -1.73148319e-01
1.46978110e-01 -3.87661070e-01 -8.28050256e-01 6.18784666e-01
1.07272637e+00 -8.22557151e-01 -3.81794304e-01 -5.94485998e-01
-6.76614121e-02 -3.97293568e-01 8.17917764e-01 -1.32673001e+00
4.73243803e-01 -1.58685073e-01 5.08342505e-01 3.57773937e-02
5.43477893e-01 -7.37144828e-01 1.96054101e-01 9.53458548e-01
-2.25471362e-01 5.48681542e-02 4.58405912e-01 6.48883820e-01
1.71260104e-01 -6.35182336e-02 1.03992510e+00 2.42707822e-02
-5.55380821e-01 4.43536520e-01 -7.51613021e-01 1.62567958e-01
1.11583602e+00 -5.37114024e-01 -9.78284061e-01 7.06754550e-02
-2.20087618e-01 -3.04237548e-02 6.26136184e-01 4.27752078e-01
8.24890852e-01 -1.04662669e+00 -1.14253625e-01 4.81864303e-01
5.88419586e-02 -3.90016079e-01 1.88552350e-01 4.04001504e-01
-3.47468972e-01 2.14734331e-01 -7.86926448e-01 -5.34424305e-01
-1.03537428e+00 5.85564137e-01 4.19534862e-01 1.84970513e-01
-4.72934127e-01 9.17160094e-01 1.87605470e-01 -3.60306688e-02
3.95438999e-01 -4.09351960e-02 1.84525594e-01 -4.12539184e-01
5.10289252e-01 2.13321790e-01 5.38724959e-02 3.73905897e-02
-6.60597503e-01 2.50635326e-01 2.38541085e-02 5.19198366e-02
1.27404690e+00 2.81792730e-01 -1.77237985e-03 -3.54436904e-01
1.04340696e+00 -1.80993527e-01 -1.49196064e+00 1.53715372e-01
8.72562379e-02 -2.29678005e-01 -1.34546950e-01 -8.38284731e-01
-1.17415416e+00 1.01484811e+00 7.38251626e-01 2.32884213e-01
1.27284753e+00 -2.34777093e-01 1.10383403e+00 6.72475100e-01
7.59115279e-01 -8.15984309e-01 3.80897552e-01 3.84451270e-01
3.96776170e-01 -7.30871379e-01 -3.95411223e-01 -5.90243451e-02
-1.63230881e-01 9.66679275e-01 7.21493125e-01 -4.21531588e-01
4.94000286e-01 9.97789264e-01 7.61094689e-03 -1.80853218e-01
-7.90101469e-01 1.77274436e-01 -3.97286355e-01 9.19052303e-01
-3.69296134e-01 -4.23982739e-02 -6.63554808e-03 6.08023524e-01
-2.67584503e-01 -3.37886274e-01 5.55316925e-01 1.02028179e+00
-4.44751650e-01 -1.11095309e+00 -3.47148925e-01 3.80089134e-01
-1.05801308e+00 -2.10493207e-01 -6.36780322e-01 5.61047614e-01
-2.18625814e-02 9.26295280e-01 -2.38283038e-01 -9.20034349e-01
1.67214230e-01 -1.98948666e-01 4.39822704e-01 -1.91930696e-01
-8.38111222e-01 -2.78719544e-01 -1.46986917e-01 -6.33193076e-01
-1.95894074e-02 -2.54311830e-01 -1.37055254e+00 -5.52407563e-01
-2.45064706e-01 -2.51414120e-01 1.09719229e+00 8.08474422e-01
5.52550256e-01 5.09900153e-01 6.36342585e-01 -8.25626433e-01
-7.76560426e-01 -2.56167173e-01 -4.15487498e-01 1.46866843e-01
2.67855793e-01 -5.71973503e-01 -4.65001196e-01 -3.97313416e-01] | [5.605057716369629, 7.774829387664795] |
12ab29ba-0a35-4e56-9719-265958f5fa0a | aakos-aspect-adaptive-knowledge-based-opinion | 2306.05537 | null | https://arxiv.org/abs/2306.05537v1 | https://arxiv.org/pdf/2306.05537v1.pdf | AaKOS: Aspect-adaptive Knowledge-based Opinion Summarization | The rapid growth of information on the Internet has led to an overwhelming amount of opinions and comments on various activities, products, and services. This makes it difficult and time-consuming for users to process all the available information when making decisions. Text summarization, a Natural Language Processing (NLP) task, has been widely explored to help users quickly retrieve relevant information by generating short and salient content from long or multiple documents. Recent advances in pre-trained language models, such as ChatGPT, have demonstrated the potential of Large Language Models (LLMs) in text generation. However, LLMs require massive amounts of data and resources and are challenging to implement as offline applications. Furthermore, existing text summarization approaches often lack the ``adaptive" nature required to capture diverse aspects in opinion summarization, which is particularly detrimental to users with specific requirements or preferences. In this paper, we propose an Aspect-adaptive Knowledge-based Opinion Summarization model for product reviews, which effectively captures the adaptive nature required for opinion summarization. The model generates aspect-oriented summaries given a set of reviews for a particular product, efficiently providing users with useful information on specific aspects they are interested in, ensuring the generated summaries are more personalized and informative. Extensive experiments have been conducted using real-world datasets to evaluate the proposed model. The results demonstrate that our model outperforms state-of-the-art approaches and is adaptive and efficient in generating summaries that focus on particular aspects, enabling users to make well-informed decisions and catering to their diverse interests and preferences. | ['Quan Bai', 'Edmund M-K. Lai', 'Weihua Li', 'Guan Wang'] | 2023-05-26 | null | null | null | null | ['text-summarization'] | ['natural-language-processing'] | [ 3.96662146e-01 2.33863339e-01 -4.06924099e-01 -4.00964111e-01
-8.68927598e-01 -4.97739881e-01 4.58777338e-01 8.10222983e-01
-1.09425345e-02 7.30765104e-01 7.38986552e-01 -1.10799810e-02
1.92894503e-01 -6.42447233e-01 -1.48769855e-01 -3.21362376e-01
2.76926696e-01 5.16962826e-01 6.33893162e-02 -5.21624386e-01
8.07554960e-01 8.17598626e-02 -1.79612565e+00 4.95110363e-01
1.73622191e+00 7.05715477e-01 5.67584753e-01 7.09866047e-01
-7.78397739e-01 3.51943672e-01 -9.99021053e-01 -3.95525217e-01
-1.37058780e-01 -5.48296452e-01 -6.68958783e-01 5.12866259e-01
1.61975101e-01 -1.90971181e-01 3.78698170e-01 1.01583242e+00
7.49389589e-01 3.76461357e-01 5.19500971e-01 -8.19246173e-01
-1.00128663e+00 6.75099432e-01 -6.71974599e-01 2.98636220e-02
7.55638599e-01 -3.62608358e-02 1.24228156e+00 -7.74404526e-01
4.01190341e-01 1.18412685e+00 2.09027693e-01 4.74446684e-01
-8.48669887e-01 -1.82883412e-01 6.29103363e-01 -4.14383188e-02
-8.34561944e-01 -3.99499327e-01 8.74593735e-01 -8.33410248e-02
1.05811763e+00 5.40550232e-01 7.58085668e-01 6.72261298e-01
3.65137815e-01 1.20390487e+00 4.44929987e-01 -3.52483928e-01
5.38106024e-01 4.81549233e-01 3.28015476e-01 -4.40697297e-02
6.25554323e-01 -1.06108570e+00 -6.52287841e-01 -3.72518808e-01
1.30302846e-01 2.63573647e-01 -2.95970738e-01 9.01190266e-02
-8.82886410e-01 8.20114791e-01 -1.01615816e-01 1.93465352e-01
-1.14274156e+00 -5.33264577e-01 6.38892651e-01 1.54112443e-01
8.21856141e-01 7.36691177e-01 -4.66423452e-01 -2.42445618e-01
-8.00083458e-01 4.72079009e-01 1.09870601e+00 1.25338781e+00
6.65074408e-01 -2.08273213e-02 -5.42663991e-01 1.16648531e+00
2.14191794e-01 6.68436348e-01 8.45871091e-01 -6.84482157e-01
6.42692804e-01 1.15998042e+00 3.77048731e-01 -1.27907372e+00
1.90523006e-02 -3.93087238e-01 -9.57745790e-01 -5.44585407e-01
-6.68739855e-01 -3.56557876e-01 -6.08430326e-01 1.19810653e+00
1.72455013e-01 -5.27305365e-01 3.08031857e-01 5.86922586e-01
1.03828216e+00 1.09929061e+00 8.71208757e-02 -7.46218204e-01
1.47877741e+00 -9.83737767e-01 -9.31773484e-01 -5.06781280e-01
4.27739382e-01 -1.04662335e+00 1.23479593e+00 4.26964909e-01
-1.20607543e+00 -5.03273010e-01 -8.70238781e-01 1.11488439e-01
-2.24072024e-01 1.78996429e-01 6.11286640e-01 4.47188437e-01
-9.44719315e-01 2.95573145e-01 -2.55822361e-01 -5.15928984e-01
2.89076090e-01 1.74417689e-01 7.52351061e-02 -1.55023724e-01
-1.10641837e+00 4.57290024e-01 2.39699244e-01 9.31081548e-02
-1.73144847e-01 -5.86137652e-01 -8.99738371e-01 2.35240132e-01
4.65634108e-01 -9.28020716e-01 1.67734814e+00 -1.03215027e+00
-1.52520621e+00 1.42913252e-01 -6.56685591e-01 -1.04041293e-01
4.69848812e-02 -5.04242122e-01 -4.84015107e-01 1.75793260e-01
4.05858189e-01 4.27278191e-01 6.43673360e-01 -1.22458136e+00
-9.12319660e-01 -3.62463176e-01 1.77950814e-01 7.33350992e-01
-6.23046160e-01 1.43559366e-01 -4.58129346e-01 -5.49405575e-01
-2.66082913e-01 -5.52181363e-01 -5.74310184e-01 -6.56255186e-01
-5.88899970e-01 -4.98816550e-01 7.46647716e-01 -6.74312294e-01
1.69387281e+00 -1.60746384e+00 -8.26010481e-02 -7.51410574e-02
-4.48360369e-02 7.23101795e-01 -3.31088632e-01 1.03157151e+00
4.25995946e-01 3.87416482e-01 -6.81038499e-02 -4.39757705e-01
8.53048638e-02 -2.22597271e-02 -3.94064367e-01 -4.22887474e-01
7.70473257e-02 7.82425463e-01 -9.93497193e-01 -4.47748274e-01
-3.32454368e-02 3.46415967e-01 -4.83454973e-01 3.35249424e-01
-6.28933132e-01 2.50739872e-01 -9.26359713e-01 5.52500069e-01
5.64872801e-01 -2.92175382e-01 -1.16441227e-01 2.96563730e-02
-9.41332877e-02 3.56539845e-01 -9.70641017e-01 1.42130435e+00
-7.46589839e-01 2.49961168e-01 -1.15096703e-01 -6.89415812e-01
9.87792552e-01 3.42685819e-01 3.85508507e-01 -7.05853105e-01
6.92935809e-02 1.28087029e-01 -4.70321298e-01 -6.21805251e-01
1.23910773e+00 2.41647363e-01 -3.24995339e-01 7.83532441e-01
-4.51535881e-01 -4.04488385e-01 8.08718681e-01 5.47739327e-01
7.42510319e-01 -3.28920573e-01 6.81069434e-01 -5.27827144e-02
7.90126622e-01 1.35581017e-01 4.57927644e-01 5.67113280e-01
2.73644060e-01 5.28388023e-01 3.06639940e-01 -1.28002837e-01
-6.36081100e-01 -4.29986984e-01 5.76075196e-01 1.02098060e+00
1.77321032e-01 -7.86712170e-01 -7.00778008e-01 -5.56257248e-01
-2.58582175e-01 1.19030774e+00 -1.89054623e-01 -1.90912500e-01
-2.88648844e-01 -5.69315135e-01 -2.65118957e-01 2.84610182e-01
5.04409075e-01 -1.31525850e+00 -5.50580680e-01 4.75334138e-01
-6.04697764e-01 -8.69232059e-01 -8.99678051e-01 -5.21174133e-01
-8.51556838e-01 -7.45728612e-01 -9.00820613e-01 -7.42355883e-01
9.92092311e-01 8.19751322e-01 1.23966110e+00 -1.11153863e-01
4.01606485e-02 4.69159782e-01 -8.88944864e-01 -8.98369491e-01
-4.78944987e-01 4.51667458e-01 -9.10758972e-02 1.50328919e-01
4.15278703e-01 -5.50437987e-01 -7.55780876e-01 1.63690627e-01
-1.27579868e+00 1.66236937e-01 9.11282182e-01 4.31259602e-01
6.19431973e-01 2.33787850e-01 1.21787632e+00 -1.22426987e+00
1.64823925e+00 -5.44273496e-01 -1.24379642e-01 4.99367476e-01
-6.88668966e-01 3.46348099e-02 1.03628349e+00 -3.48566175e-01
-1.39430618e+00 -5.06892502e-01 -1.29098058e-01 4.57389325e-01
3.79566976e-04 1.02817094e+00 -2.30321899e-01 5.22694588e-01
4.91928399e-01 5.19543886e-01 -1.85726479e-01 -3.49664956e-01
4.30383652e-01 1.14771616e+00 5.22857606e-02 -2.72641093e-01
3.97315443e-01 6.35238513e-02 -5.86226165e-01 -1.06166553e+00
-1.00775290e+00 -8.70461226e-01 -2.55776554e-01 -1.33616254e-01
3.82136554e-01 -7.21223474e-01 -4.17998075e-01 2.79611975e-01
-1.20976281e+00 3.77605706e-01 -5.39982438e-01 5.67430072e-02
-2.49370188e-01 7.08167374e-01 -1.87719017e-01 -9.49631989e-01
-1.39216363e+00 -8.49103451e-01 1.07004142e+00 9.14249361e-01
-7.12710142e-01 -8.90626848e-01 1.38677061e-02 5.21030247e-01
8.11186969e-01 -6.75503165e-02 8.44660044e-01 -9.06705499e-01
-3.38692755e-01 -7.38874733e-01 1.17191263e-02 3.96496475e-01
6.82073414e-01 -1.50904981e-02 -4.71353024e-01 -1.13380417e-01
1.66603066e-02 -1.54865786e-01 5.35339177e-01 4.27971929e-01
9.02015388e-01 -8.23333859e-01 -1.73990771e-01 -3.72958899e-01
9.75545883e-01 2.69333184e-01 3.87429327e-01 3.56220715e-02
4.79733080e-01 8.15491676e-01 1.16890192e+00 8.94505739e-01
7.83457398e-01 2.52312541e-01 9.44771692e-02 6.55340105e-02
2.80387163e-01 -2.79450417e-01 4.40442443e-01 1.28035080e+00
1.10315308e-01 -6.27765536e-01 -2.56862074e-01 8.06335568e-01
-2.11929226e+00 -8.23561490e-01 5.11870347e-02 1.98139644e+00
9.90804493e-01 -6.43831193e-02 -9.25452933e-02 -1.41731858e-01
6.17803931e-01 4.43649888e-01 -7.75822043e-01 -8.96750689e-01
7.05410764e-02 9.16233379e-03 -3.40976156e-02 2.20010474e-01
-5.70315242e-01 8.61875057e-01 5.53259325e+00 7.89727211e-01
-9.01386201e-01 -3.67133498e-01 6.21534407e-01 -1.12684928e-01
-9.12685096e-01 -1.26271635e-01 -9.35147285e-01 4.36660379e-01
9.38570976e-01 -1.06126082e+00 1.17381467e-02 9.74743426e-01
7.71410286e-01 -4.23316777e-01 -7.40835130e-01 7.75196552e-01
4.80965555e-01 -1.28679788e+00 7.18446076e-01 -2.42916837e-01
1.17888248e+00 -4.61793363e-01 -9.42734480e-02 2.75386274e-01
3.27967405e-01 -4.64955568e-01 2.94466674e-01 3.77795786e-01
3.49824607e-01 -1.03915298e+00 9.64809120e-01 6.53186202e-01
-1.26733148e+00 3.44942659e-02 -4.60308343e-01 -2.54688039e-02
6.86702788e-01 8.41849685e-01 -9.32013929e-01 8.52829337e-01
3.13715011e-01 8.46603155e-01 -4.25859153e-01 9.16118741e-01
-3.23482662e-01 3.79750073e-01 3.68024446e-02 -4.80203509e-01
2.01388791e-01 -3.52701455e-01 5.56838870e-01 1.09497547e+00
5.50037205e-01 2.05088884e-01 4.45843071e-01 4.38558310e-01
-8.79258737e-02 7.81297743e-01 -4.40610826e-01 -4.57474500e-01
3.09702158e-01 1.45336270e+00 -5.39791465e-01 -5.64999878e-01
-3.06103170e-01 9.06558990e-01 -2.33310521e-01 2.80910790e-01
-2.37907529e-01 -6.75980330e-01 4.65435565e-01 8.78373384e-02
2.48907641e-01 5.25022410e-02 -2.83345789e-01 -1.06066072e+00
3.22497845e-01 -1.13432288e+00 2.62130290e-01 -7.19518363e-01
-1.16782546e+00 7.07255006e-01 -2.97126211e-02 -1.27797651e+00
-5.40584028e-01 1.36666000e-01 -9.65782702e-01 7.85035372e-01
-1.66279590e+00 -9.89066660e-01 -2.62640119e-01 1.25952393e-01
1.36857939e+00 -9.82621983e-02 7.59277761e-01 -2.27849204e-02
-4.55648243e-01 1.91940531e-01 -1.45786524e-01 -6.50010765e-01
6.86149478e-01 -1.11684096e+00 5.55253327e-01 9.27420974e-01
-2.62002677e-01 8.81362081e-01 9.66304302e-01 -8.67561936e-01
-1.42220473e+00 -1.06054199e+00 1.41166794e+00 2.25761794e-02
2.19210044e-01 6.16063811e-02 -9.31025386e-01 2.41749629e-01
6.50823534e-01 -9.64116454e-01 1.13468885e+00 -4.27556783e-02
2.75743186e-01 -2.43938625e-01 -1.01301980e+00 8.15080464e-01
6.60889089e-01 -5.87866679e-02 -6.46338284e-01 4.62048948e-01
9.89463091e-01 -1.48568777e-02 -5.12095928e-01 2.22253382e-01
2.32418656e-01 -7.73535311e-01 4.20300245e-01 -4.05989826e-01
4.18467134e-01 -2.50128090e-01 2.23930314e-01 -1.78940177e+00
-5.18791899e-02 -9.66454327e-01 -1.11785203e-01 1.68399608e+00
5.92449367e-01 -6.64792597e-01 6.45012081e-01 9.78807330e-01
-2.87458718e-01 -8.82261395e-01 -4.72773947e-02 -8.52419212e-02
-5.46130538e-01 -1.76441491e-01 6.85027897e-01 3.66498768e-01
2.58983403e-01 7.15069234e-01 -2.82425195e-01 -5.62241040e-02
1.39873058e-01 5.71358860e-01 9.37427580e-01 -1.20561111e+00
-2.35637240e-02 -5.02876759e-01 1.26587644e-01 -1.41989028e+00
-8.12439397e-02 -4.34761763e-01 7.10405931e-02 -2.39153433e+00
3.83881658e-01 2.83172708e-02 9.28219259e-02 2.14357898e-01
-5.38100481e-01 -3.21519554e-01 -3.86458635e-02 1.94866627e-01
-1.06418717e+00 8.78244102e-01 1.38876760e+00 -1.87974527e-01
-7.04557836e-01 6.62630260e-01 -1.63479817e+00 6.56753242e-01
8.59310627e-01 -1.03336886e-01 -9.43137228e-01 -2.11827070e-01
6.12882435e-01 1.06987329e-02 -5.81809163e-01 -4.83374834e-01
4.54769552e-01 -3.29491198e-01 -2.76310239e-02 -1.07194149e+00
1.00239463e-01 -4.68880266e-01 -2.05470413e-01 3.80826667e-02
-5.58573663e-01 3.39306861e-01 1.85434148e-01 6.04680061e-01
-5.50110221e-01 -2.64593482e-01 1.43553972e-01 -2.95420736e-01
-6.94754422e-01 3.87552083e-01 -6.24316216e-01 9.00340974e-02
8.69365513e-01 -2.60525674e-01 -1.39198571e-01 -1.01793921e+00
-1.96245059e-01 7.45955586e-01 3.87151450e-01 6.44437313e-01
7.73501754e-01 -1.08233404e+00 -8.78515422e-01 4.26255316e-02
4.19220120e-01 3.16394627e-01 6.01076841e-01 4.05335546e-01
-2.40618646e-01 6.46671474e-01 8.76882672e-03 -2.36270621e-01
-1.42799175e+00 2.41265550e-01 -4.27097440e-01 -6.69496179e-01
-3.21951628e-01 5.12586057e-01 4.10824381e-02 -3.07812363e-01
-1.68627743e-02 -4.42721635e-01 -7.74442673e-01 4.79519516e-01
1.02827561e+00 2.26372972e-01 1.11881271e-01 -5.58565378e-01
5.69215529e-02 5.23027420e-01 -6.07695699e-01 3.88903804e-02
1.31646681e+00 -6.39929950e-01 -2.35284835e-01 3.17825347e-01
7.38677502e-01 2.50688255e-01 -7.96768188e-01 -4.28959787e-01
2.13649757e-02 -2.72660375e-01 -1.94929197e-01 -7.56145418e-01
-8.17369103e-01 6.34029865e-01 -2.61024833e-01 5.92755258e-01
1.33686769e+00 -1.47359014e-01 1.28345668e+00 4.87840861e-01
2.88404495e-01 -1.29884899e+00 2.37298995e-01 4.01282012e-01
1.05157149e+00 -1.14780712e+00 1.81359977e-01 -4.59445775e-01
-1.19703507e+00 8.55112255e-01 5.15546203e-01 1.67966202e-01
3.01725358e-01 -2.92337239e-01 1.79672942e-01 -6.92248717e-02
-1.02861416e+00 -2.81065945e-02 5.31775415e-01 5.53597331e-01
4.81045842e-01 -5.79404365e-03 -5.89777768e-01 7.62355447e-01
-2.29456350e-01 -3.26317623e-02 6.60575628e-01 1.12721765e+00
-8.27528119e-01 -1.25292194e+00 -1.03863232e-01 6.75655961e-01
-5.62681198e-01 -9.63108167e-02 -6.60734832e-01 1.51990399e-01
-5.01273453e-01 1.46993983e+00 -3.66145521e-01 3.75320902e-03
6.23668313e-01 -1.05845742e-01 -2.01504350e-01 -1.22841883e+00
-6.07898951e-01 4.93552387e-02 2.85342693e-01 -2.46733144e-01
-3.98884416e-01 -5.47475636e-01 -1.24627876e+00 -2.26468906e-01
-4.61798668e-01 6.19201779e-01 6.84743047e-01 8.09571862e-01
1.07127333e+00 5.60724199e-01 8.52375865e-01 -9.77070093e-01
-6.53810978e-01 -1.12103081e+00 -4.17366445e-01 3.84904027e-01
1.11498311e-01 1.40173780e-02 -1.09519251e-01 1.98302604e-02] | [12.459211349487305, 9.372713088989258] |
53e0ccb2-db8c-4fb3-a912-5d115b201e40 | predictive-modelling-of-football-injuries | 1609.07480 | null | http://arxiv.org/abs/1609.07480v1 | http://arxiv.org/pdf/1609.07480v1.pdf | Predictive modelling of football injuries | The goal of this thesis is to investigate the potential of predictive
modelling for football injuries. This work was conducted in close collaboration
with Tottenham Hotspurs FC (THFC), the PGA European tour and the participation
of Wolverhampton Wanderers (WW).
Three investigations were conducted:
1. Predicting the recovery time of football injuries using the UEFA injury
recordings: The UEFA recordings is a common standard for recording injuries in
professional football. For this investigation, three datasets of UEFA injury
recordings were available. Different machine learning algorithms were used in
order to build a predictive model. The performance of the machine learning
models is then improved by using feature selection conducted through
correlation-based subset feature selection and random forests.
2. Predicting injuries in professional football using exposure records: The
relationship between exposure (in training hours and match hours) in
professional football athletes and injury incidence was studied. A common
problem in football is understanding how the training schedule of an athlete
can affect the chance of him getting injured. The task was to predict the
number of days a player can train before he gets injured.
3. Predicting intrinsic injury incidence using in-training GPS measurements:
A significant percentage of football injuries can be attributed to overtraining
and fatigue. GPS data collected during training sessions might provide
indicators of fatigue, or might be used to detect very intense training
sessions which can lead to overtraining. This research used GPS data gathered
during training sessions of the first team of THFC, in order to predict whether
an injury would take place during a week. | ['Stylianos Kampakis'] | 2016-09-20 | null | null | null | null | ['injury-prediction', 'game-of-football'] | ['playing-games', 'playing-games'] | [ 7.12025259e-03 -4.42930698e-01 -2.13287994e-01 1.74802423e-01
-4.03162688e-01 -1.61924511e-01 -2.62328058e-01 2.15604499e-01
-6.93106413e-01 5.94659865e-01 3.84996921e-01 -1.86527506e-01
-9.22273338e-01 -9.39367771e-01 -6.76288247e-01 -5.65683901e-01
-3.43956828e-01 5.13199091e-01 3.65645289e-01 -3.13307256e-01
4.83865142e-01 8.57611835e-01 -1.76023674e+00 6.39872611e-01
2.36833900e-01 3.91039073e-01 5.90119839e-01 6.82718039e-01
5.38956881e-01 9.26400900e-01 -5.53594828e-01 -4.36893292e-02
3.63642544e-01 -5.19053996e-01 -1.02991962e+00 4.89628278e-02
-2.90094197e-01 -1.60279889e-02 -4.06699359e-01 9.39329062e-03
5.42294443e-01 5.62678039e-01 4.05689478e-01 -1.09027267e+00
2.80447125e-01 3.85075092e-01 -2.56268620e-01 7.27241874e-01
7.52986252e-01 5.47725037e-02 3.43040198e-01 -4.37189937e-01
5.08415937e-01 8.25727403e-01 9.15505111e-01 -9.89369899e-02
-1.11688972e+00 -8.40439856e-01 -4.20132726e-01 9.78449941e-01
-1.34527016e+00 -2.37011723e-02 4.55437392e-01 -8.07032228e-01
1.00418055e+00 4.55768228e-01 1.03088295e+00 8.61922145e-01
4.84418243e-01 2.97684133e-01 1.40810192e+00 -5.30065060e-01
-2.02464294e-02 -1.44423246e-01 1.98391408e-01 8.65129679e-02
2.26989910e-01 6.68117702e-01 -8.55219364e-01 5.57584688e-02
6.26219392e-01 1.07924797e-01 -1.23984247e-01 3.84097785e-01
-5.80492914e-01 8.63258421e-01 2.36150503e-01 3.08099180e-01
-6.86551213e-01 1.95383350e-03 8.00977111e-01 5.75110018e-01
2.75379926e-01 5.30727804e-01 -4.34752464e-01 -8.69338453e-01
-1.01268697e+00 6.03719354e-01 5.22822499e-01 1.59686971e-02
5.62967479e-01 -2.01257065e-01 1.99098997e-02 8.75200212e-01
-5.70980683e-02 9.52136517e-02 2.19453543e-01 -8.28807533e-01
2.99673408e-01 5.27772963e-01 -3.07470292e-01 -1.13597977e+00
-6.09724700e-01 -3.30578446e-01 -9.45636816e-03 2.50078261e-01
5.17589509e-01 -2.91520506e-01 -6.21970892e-01 8.68498921e-01
-4.45694812e-02 1.12414341e-02 -5.14475167e-01 1.27524555e+00
2.30367497e-01 4.04590398e-01 9.23055708e-02 -2.56906480e-01
1.32213724e+00 -1.55786335e-01 -3.89810205e-01 -2.87094444e-01
8.05996597e-01 -8.64451826e-01 8.11659276e-01 8.68119299e-01
-1.05836082e+00 -9.12694752e-01 -4.40187782e-01 5.25018275e-01
3.98539379e-02 -9.76055190e-02 4.74447668e-01 7.85033882e-01
-2.77995110e-01 1.01837695e+00 -9.91775274e-01 -5.68592787e-01
-9.49405283e-02 4.88299489e-01 -6.07233226e-01 -3.19421232e-01
-1.30248010e+00 1.28632379e+00 2.63417453e-01 1.91798121e-01
-5.77023327e-01 -7.76905894e-01 -6.61086202e-01 -3.99799675e-01
4.50489044e-01 -3.01140904e-01 5.93082190e-01 -5.01579523e-01
-6.78006411e-01 8.56748939e-01 5.45905866e-02 -4.28691834e-01
5.03279328e-01 -5.54948747e-01 -2.69822985e-01 -9.40100402e-02
4.98974293e-01 -3.82476807e-01 -7.00062290e-02 -9.27475810e-01
-7.12744713e-01 -6.37145877e-01 -1.95911452e-01 2.48699769e-01
4.21606421e-01 6.50287688e-01 6.76417276e-02 -4.59423780e-01
1.56589150e-01 -1.29887092e+00 -2.52857119e-01 -1.09715366e+00
-1.26219973e-01 -6.95680901e-02 5.89263082e-01 -8.51858377e-01
1.44864118e+00 -1.83478141e+00 2.73573864e-02 5.47862709e-01
-4.48549122e-01 1.92753170e-02 6.28433466e-01 1.25399923e+00
-2.36566126e-01 -1.81342557e-01 1.72364563e-01 5.22555709e-01
-3.12904567e-01 6.79266751e-01 -2.90217530e-02 6.03413343e-01
-1.20722450e-01 2.65427232e-01 -5.18657625e-01 -3.74637812e-01
2.71342516e-01 1.21982440e-01 -3.31937492e-01 1.25852585e-01
8.66875589e-01 5.53040147e-01 -6.48084059e-02 2.94206411e-01
2.05191895e-01 9.73995030e-01 -1.80000097e-01 8.00773874e-02
-6.16694570e-01 2.73114145e-01 -1.26899660e+00 1.18335640e+00
-3.06794584e-01 6.82941258e-01 -2.92181581e-01 -1.28443778e+00
1.11520195e+00 5.37156463e-01 7.26802051e-01 -8.08131814e-01
2.87160009e-01 1.73399553e-01 3.76698703e-01 -1.15149724e+00
4.20550585e-01 -6.05666518e-01 -4.93805893e-02 3.73681813e-01
-3.96975577e-02 3.22799772e-01 6.70783401e-01 -2.95650929e-01
1.18839741e+00 1.80134043e-01 -1.50782451e-01 -3.50757301e-01
-5.75357489e-03 4.00635540e-01 6.77168965e-01 6.00377858e-01
2.76655070e-02 4.89388436e-01 5.71842313e-01 -6.95299566e-01
-6.84315741e-01 -5.79761565e-01 -2.47145802e-01 1.17646277e+00
-1.46341488e-01 -1.12443611e-01 -5.09463727e-01 1.48241684e-01
-6.83208033e-02 6.72598362e-01 -6.96136773e-01 -6.28919005e-01
-6.91490829e-01 -7.79153049e-01 4.15426761e-01 6.41932726e-01
9.90127996e-02 -1.19119549e+00 -9.99945819e-01 4.56598967e-01
-3.75592738e-01 -4.99056250e-01 5.65866008e-02 6.30370021e-01
-9.28865910e-01 -1.26633155e+00 -3.57884496e-01 -6.03646874e-01
1.32138774e-01 1.20364748e-01 7.78363168e-01 4.72003788e-01
-6.86735332e-01 2.91602820e-01 -6.68682694e-01 -7.67851174e-01
-8.66300613e-02 1.60691187e-01 2.38260761e-01 -1.69350863e-01
6.75387561e-01 -6.03000462e-01 -5.36871850e-01 6.84740841e-01
-7.28214681e-01 -3.91697854e-01 7.55800545e-01 5.10219991e-01
4.68115032e-01 3.40247661e-01 4.58629578e-01 -8.40771079e-01
5.09578824e-01 -7.22383976e-01 2.63272822e-01 -2.35802963e-01
-3.73376131e-01 -6.53420687e-01 -1.10014312e-01 -4.22705710e-01
-8.02649558e-01 -1.33153915e-01 -2.93056726e-01 -2.54925966e-01
-6.69204772e-01 8.07353854e-01 1.77286625e-01 8.48997384e-02
1.14637196e+00 -9.04962048e-02 1.14781506e-01 -5.64108908e-01
-6.83034718e-01 6.00386560e-01 6.34297431e-01 -8.12497437e-01
4.37132835e-01 1.49599114e-03 2.63958156e-01 -9.25907016e-01
-6.90347433e-01 -1.13257778e+00 -9.73481536e-01 -1.08331513e+00
8.18309963e-01 -7.25746870e-01 -8.44029009e-01 2.20569223e-01
-4.70062643e-01 -2.93179423e-01 -1.20965384e-01 1.27320421e+00
-5.66448271e-01 -9.87930894e-02 -4.47657079e-01 -1.11335671e+00
2.04745308e-01 -8.37033689e-01 4.80693638e-01 1.82427559e-02
-6.52702749e-01 -7.10291326e-01 5.15757322e-01 9.31486070e-01
-1.62143767e-01 7.53659785e-01 5.30643344e-01 -5.01930118e-01
1.44633979e-01 -6.71272278e-01 4.55564022e-01 2.85434484e-01
-9.08339992e-02 -1.75421149e-01 -4.40300763e-01 -1.91720113e-01
-2.36437880e-02 -1.34919032e-01 5.85613191e-01 5.76127887e-01
7.38890946e-01 2.18980908e-01 -3.40613067e-01 1.55018732e-01
1.38713419e+00 4.14977789e-01 1.03288579e+00 9.59322155e-01
3.48344117e-01 1.01712751e+00 1.21107304e+00 2.45381102e-01
-1.40695095e-01 8.02029133e-01 1.38167385e-02 -1.63481459e-02
3.63862030e-02 -6.24037832e-02 2.11698323e-01 5.33209443e-01
-1.25173509e+00 2.31470406e-01 -1.20970798e+00 9.46035147e-01
-1.58946621e+00 -1.44309771e+00 -1.36023784e+00 2.28157330e+00
3.59742254e-01 3.75444800e-01 7.41401672e-01 1.10767233e+00
4.52927679e-01 -5.87727606e-01 3.20707381e-01 -1.08778918e+00
3.66561115e-01 6.43260658e-01 9.14605439e-01 6.60227314e-02
-5.52206159e-01 1.28396109e-01 5.96477890e+00 5.95166445e-01
-6.74469948e-01 6.34202780e-03 1.94855645e-01 -5.62148452e-01
5.07907391e-01 3.37672353e-01 -5.28276324e-01 5.77612579e-01
1.18681777e+00 8.72602016e-02 -7.06295073e-02 4.63210911e-01
7.69411504e-01 -7.22190619e-01 -5.23722231e-01 3.35376710e-01
-1.57904088e-01 -7.59476960e-01 -7.42198646e-01 4.23017353e-01
4.09057200e-01 -2.73715019e-01 -4.99624133e-01 4.33805853e-01
-1.53567359e-01 -9.10654962e-01 6.64787889e-01 1.01202738e+00
4.16187406e-01 -1.17667449e+00 1.12792742e+00 6.37257755e-01
-7.69674182e-01 -4.47494835e-01 -1.95335031e-01 -1.04806340e+00
5.41232407e-01 3.78694206e-01 -8.83087993e-01 6.32913291e-01
1.17428899e+00 4.92155068e-02 -2.40772992e-01 1.47125363e+00
-5.25093861e-02 1.30500650e+00 -3.29398721e-01 3.19752872e-01
1.30736023e-01 -1.48910582e-01 5.40745974e-01 9.76303637e-01
2.89294153e-01 3.06666791e-01 3.23797971e-01 3.34440023e-01
8.75411153e-01 2.03073621e-01 -5.82850397e-01 5.32773614e-01
8.27619135e-02 7.34509706e-01 -7.88520694e-01 3.42118174e-01
-3.36775571e-01 4.97957021e-01 -1.85379490e-01 -7.68741742e-02
-7.04585075e-01 -4.25025821e-01 5.96598089e-01 1.20704412e+00
-1.97219163e-01 -9.30310041e-02 -2.91677088e-01 -1.02904052e-01
-1.76956326e-01 -6.84616685e-01 4.31072116e-01 -6.70541286e-01
-1.01472223e+00 1.99799776e-01 5.25676668e-01 -1.04973090e+00
-1.64085910e-01 -4.19365227e-01 -8.54204714e-01 1.21832430e+00
-3.60624880e-01 -7.66164482e-01 -1.16587490e-01 4.95398581e-01
5.85516036e-01 8.79987925e-02 6.44578040e-01 4.55823570e-01
-6.47426128e-01 8.84592086e-02 -3.18736911e-01 7.11563602e-02
4.68068242e-01 -9.97790098e-01 -3.10218066e-01 6.55152321e-01
7.98251387e-03 3.45021755e-01 1.04703724e+00 -1.17167652e+00
-9.47084963e-01 -6.49959743e-01 9.44519997e-01 -4.55551624e-01
5.78105628e-01 8.88015926e-02 -9.30843472e-01 4.78934824e-01
-3.46015632e-01 -6.18994236e-01 1.12624538e+00 2.81532884e-01
6.54736698e-01 1.71679836e-02 -6.57320261e-01 1.83760777e-01
8.88969660e-01 -4.73056674e-01 -9.18266118e-01 2.92261750e-01
-3.69298697e-01 -5.06868362e-01 -1.21377730e+00 3.50639075e-01
8.45828354e-01 -9.80773151e-01 8.99158597e-01 -7.65691340e-01
5.09051621e-01 -5.75833917e-02 4.04361486e-01 -1.18520975e+00
-4.56359476e-01 -2.11359084e-01 7.58852720e-01 9.75103736e-01
2.06406444e-01 -4.54158783e-02 7.65841901e-01 8.64139736e-01
-5.10373950e-01 -7.24016964e-01 -9.39045191e-01 -8.17266822e-01
-8.59991312e-02 -9.73632157e-01 -1.30266277e-02 7.22653091e-01
2.32529283e-01 -9.79247019e-02 -6.12542629e-01 -3.96648236e-02
1.76587939e-01 -3.45931709e-01 7.72972703e-01 -1.34999979e+00
-4.28163797e-01 -1.95640344e-02 -1.10633755e+00 7.78475925e-02
-3.34597260e-01 -5.99265993e-01 -2.78788507e-02 -1.73271012e+00
2.40660599e-03 -2.81827301e-01 -7.63982311e-02 3.81441742e-01
-7.71042472e-03 3.48452091e-01 1.77473620e-01 2.09129930e-01
3.51194829e-01 -4.90472227e-01 8.73001814e-01 5.56892991e-01
-3.70449156e-01 8.89078021e-01 -2.29581654e-01 3.02949458e-01
8.40407610e-01 -9.36687708e-01 -3.71456623e-01 -1.47049293e-01
5.39824605e-01 4.75218534e-01 6.47188246e-01 -1.27608383e+00
7.03559443e-02 -4.94004756e-01 3.41889739e-01 -5.63194275e-01
2.61370748e-01 -8.59105587e-01 9.96085763e-01 7.56865740e-01
-1.17584087e-01 6.10224269e-02 3.94296855e-01 2.94188857e-01
-2.82952338e-01 -7.76885331e-01 1.67501077e-01 -2.84324080e-01
-4.35213357e-01 -1.76699474e-01 -1.19818521e+00 -2.65315592e-01
1.27823436e+00 -8.82898986e-01 2.30756953e-01 -3.51993032e-02
-1.25569105e+00 5.66476025e-03 2.07393855e-01 3.68152142e-01
3.08921278e-01 -1.12907720e+00 -8.58497620e-01 -3.96633968e-02
-1.06183372e-01 -4.99282062e-01 7.50871181e-01 1.58343494e+00
-8.21526170e-01 1.98332608e-01 -7.71061599e-01 -3.09888095e-01
-1.46748972e+00 4.05950159e-01 1.51921809e-01 -1.35446712e-01
-6.86048090e-01 8.81938994e-01 -4.70097542e-01 1.63954794e-01
-1.89557374e-01 1.80890486e-01 -4.64441359e-01 3.19801301e-01
2.32596681e-01 1.15249848e+00 4.07003522e-01 -9.57487464e-01
-2.96735346e-01 4.09407467e-01 1.93832159e-01 6.31249277e-03
1.36417568e+00 6.33447319e-02 9.29128379e-02 8.44942570e-01
9.92808700e-01 2.65953057e-02 -7.86995471e-01 3.07726294e-01
1.06688716e-01 -7.43967950e-01 5.53666279e-02 -6.63676918e-01
-8.27896655e-01 7.22358763e-01 6.57177389e-01 3.59878778e-01
1.29561567e+00 -6.03425875e-02 8.11394691e-01 -2.93347873e-02
4.15815204e-01 -1.33169472e+00 -3.97900254e-01 5.39317988e-02
9.51783657e-01 -5.52664876e-01 7.46420547e-02 -2.75300980e-01
-8.94283414e-01 1.10709095e+00 3.01773727e-01 -4.39684153e-01
4.99768317e-01 2.52623290e-01 -4.83387560e-02 -6.36659026e-01
-4.36135441e-01 -4.68867540e-01 3.56212825e-01 6.53458059e-01
5.40182710e-01 2.57302076e-01 -1.08456123e+00 7.89760709e-01
-6.83674335e-01 2.71093458e-01 7.58042693e-01 1.07518947e+00
-4.51638669e-01 -1.14173841e+00 -8.50958228e-01 1.05457509e+00
-8.02956462e-01 5.20335138e-01 -3.97996813e-01 1.20819187e+00
9.05966520e-01 1.10475576e+00 -1.18705481e-02 -7.19992518e-01
1.10845995e+00 2.69560128e-01 2.59101987e-01 -7.38459766e-01
-1.35348153e+00 7.70187657e-03 4.23223585e-01 -4.42307711e-01
-5.19414723e-01 -1.31463230e+00 -1.07059526e+00 -6.08453810e-01
-4.92212802e-01 4.88234341e-01 5.67833543e-01 1.07813287e+00
-3.49491954e-01 7.26973176e-01 3.89835238e-01 -7.99113512e-01
2.86710292e-01 -1.22548568e+00 -1.17137396e+00 3.76267761e-01
-4.23166245e-01 -1.19880199e+00 -1.03098005e-01 1.14524767e-01] | [6.851314067840576, 0.394118994474411] |
958bb299-604d-450f-b03f-33389444b43d | improving-unsupervised-neural-aspect | 2006.09766 | null | https://arxiv.org/abs/2006.09766v1 | https://arxiv.org/pdf/2006.09766v1.pdf | Improving unsupervised neural aspect extraction for online discussions using out-of-domain classification | Deep learning architectures based on self-attention have recently achieved and surpassed state of the art results in the task of unsupervised aspect extraction and topic modeling. While models such as neural attention-based aspect extraction (ABAE) have been successfully applied to user-generated texts, they are less coherent when applied to traditional data sources such as news articles and newsgroup documents. In this work, we introduce a simple approach based on sentence filtering in order to improve topical aspects learned from newsgroups-based content without modifying the basic mechanism of ABAE. We train a probabilistic classifier to distinguish between out-of-domain texts (outer dataset) and in-domain texts (target dataset). Then, during data preparation we filter out sentences that have a low probability of being in-domain and train the neural model on the remaining sentences. The positive effect of sentence filtering on topic coherence is demonstrated in comparison to aspect extraction models trained on unfiltered texts. | ['Anton Alekseev', 'Elena Tutubalina', 'Sergey Nikolenko', 'Valentin Malykh'] | 2020-06-17 | null | null | null | null | ['aspect-extraction'] | ['natural-language-processing'] | [ 2.28634372e-01 7.27081358e-01 -1.38994619e-01 -5.69640815e-01
-9.31570828e-01 -1.82224870e-01 1.09938681e+00 7.79822886e-01
-7.47826755e-01 6.38832629e-01 9.77790833e-01 -7.81343430e-02
-1.16032161e-01 -9.58586514e-01 -5.63984931e-01 -5.00514448e-01
1.24039866e-01 6.71423376e-01 2.36731485e-01 -2.35598564e-01
2.81009346e-01 -1.01225667e-01 -1.65013659e+00 6.85429096e-01
7.24500418e-01 4.78554726e-01 3.10599636e-02 5.15989482e-01
-7.14825332e-01 6.22523248e-01 -1.11940253e+00 -1.82180047e-01
-3.92867893e-01 -4.68783528e-01 -9.64038610e-01 3.33302855e-01
1.87015370e-01 -2.49790889e-03 -1.39338300e-01 9.42951620e-01
4.00590420e-01 1.14165254e-01 8.05093050e-01 -7.41152227e-01
-4.97868538e-01 1.31427896e+00 -3.17685872e-01 2.84897715e-01
3.07289004e-01 -4.62900788e-01 1.16406643e+00 -8.17945302e-01
7.60293782e-01 1.12594461e+00 4.81507778e-01 3.01461369e-01
-1.27133107e+00 -1.16031766e-01 4.96793181e-01 6.15601800e-02
-8.09558392e-01 -3.40655804e-01 9.71700251e-01 -4.53620672e-01
1.38657188e+00 1.73651263e-01 7.50416458e-01 1.23161638e+00
2.06214264e-01 9.85633671e-01 8.00893962e-01 -5.27220786e-01
3.89549762e-01 4.08239156e-01 7.51447439e-01 -1.82529986e-01
2.85951942e-01 -5.47471821e-01 -7.75341332e-01 -1.88292101e-01
-5.67961074e-02 -3.81592959e-01 -1.90547228e-01 5.98516911e-02
-1.14942706e+00 1.14122212e+00 6.53714463e-02 8.39140415e-01
-9.98907387e-01 -3.57741714e-01 5.26830852e-01 2.18311831e-01
1.28674495e+00 6.57361031e-01 -6.25304520e-01 -9.88212153e-02
-1.22648597e+00 3.72959167e-01 1.09034336e+00 7.19712794e-01
5.77388585e-01 -6.72476962e-02 -5.60466707e-01 8.41322660e-01
2.36824870e-01 2.54816473e-01 6.58908248e-01 -1.77378595e-01
4.07405704e-01 8.01829517e-01 -1.55984774e-01 -7.46937931e-01
-5.77978373e-01 -7.30845690e-01 -6.77375495e-01 -1.11044593e-01
-5.25366999e-02 -3.84012133e-01 -1.05458343e+00 1.45829356e+00
3.14086527e-01 -4.75067943e-01 3.53623122e-01 4.27573293e-01
1.20783281e+00 9.53283966e-01 3.33338499e-01 -2.73010433e-01
1.52277887e+00 -8.66481304e-01 -1.08726394e+00 -3.65098953e-01
3.37173223e-01 -8.68708372e-01 7.32453346e-01 3.04896474e-01
-9.33344901e-01 -4.09666896e-01 -9.74580944e-01 -3.29717807e-02
-7.21646786e-01 5.01000546e-02 5.06929100e-01 4.51470852e-01
-9.93433475e-01 4.07517582e-01 -5.83540916e-01 -5.46806991e-01
5.45422018e-01 1.76583961e-01 -3.28767091e-01 3.04505199e-01
-1.30292416e+00 9.19519722e-01 7.01693833e-01 -3.27531040e-01
-7.81434298e-01 -7.34606445e-01 -8.15434933e-01 4.31767195e-01
5.03109872e-01 -7.59132087e-01 1.26023328e+00 -9.25011873e-01
-1.35437810e+00 7.44318724e-01 -2.86541581e-01 -8.34810793e-01
-4.93854769e-02 -6.16812944e-01 -3.33952934e-01 2.71711916e-01
2.78530687e-01 5.33050239e-01 1.04885721e+00 -1.00572991e+00
-7.39460289e-01 -2.82523394e-01 2.55991742e-02 2.67696351e-01
-5.81719816e-01 2.40392923e-01 -3.35356742e-01 -7.57126331e-01
-2.11044047e-02 -5.77730596e-01 -2.48275563e-01 -7.34648526e-01
-7.68012047e-01 -5.60956657e-01 9.66056347e-01 -6.21525407e-01
1.21586442e+00 -1.82697117e+00 1.46023512e-01 -1.55791512e-03
2.65451044e-01 3.24475974e-01 -1.73081592e-01 5.48038840e-01
-5.91967106e-02 6.25670627e-02 -9.05366763e-02 -3.43970209e-01
4.33920436e-02 -2.17159197e-01 -5.27588844e-01 9.84404087e-02
5.34829199e-01 5.46266973e-01 -7.24906921e-01 -4.76657391e-01
6.95548058e-02 5.08652568e-01 -5.65553606e-01 2.21496299e-01
-6.47788584e-01 1.83544591e-01 -4.37492996e-01 1.32388875e-01
4.94337410e-01 -1.39082417e-01 4.58423644e-02 -7.32795075e-02
-1.01569615e-01 1.07402515e+00 -6.73501313e-01 1.39712954e+00
-6.42474174e-01 1.08695495e+00 -1.05442153e-02 -8.85975540e-01
9.07912314e-01 5.84483147e-01 5.28641701e-01 -3.11753541e-01
2.79483587e-01 -3.26506943e-01 1.20351836e-02 -4.19813603e-01
1.02594376e+00 -2.18983248e-01 -1.64400369e-01 8.25708568e-01
6.41761959e-01 -3.27257514e-01 6.22701705e-01 5.15290856e-01
8.91280830e-01 -5.85899979e-04 5.05151570e-01 -5.13175607e-01
5.07083356e-01 9.99580994e-02 1.54679164e-01 7.59135783e-01
1.26809523e-01 6.61181509e-01 8.57443035e-01 -3.16676587e-01
-1.08034074e+00 -6.64461851e-01 -1.99383616e-01 1.25331390e+00
-3.67251247e-01 -9.74156618e-01 -8.29496920e-01 -8.43163669e-01
-4.10088062e-01 1.14878511e+00 -9.05372918e-01 3.28461900e-02
-4.10559386e-01 -1.08410871e+00 1.31301163e-02 1.97901413e-01
3.33536386e-01 -1.22371590e+00 -4.52435344e-01 5.06176174e-01
-3.48580688e-01 -1.11102664e+00 7.29597220e-03 3.94798517e-01
-5.63682377e-01 -6.68280780e-01 -6.98004544e-01 -5.25067151e-01
4.89866644e-01 5.67482226e-02 1.48062360e+00 -3.22262824e-01
1.53177455e-01 3.06600809e-01 -6.75525606e-01 -9.69726861e-01
-6.45965278e-01 6.18151963e-01 -2.79978305e-01 5.00944257e-02
9.51888561e-01 -4.66115832e-01 -3.15686613e-01 -1.59615412e-01
-1.06175625e+00 -2.97914579e-04 6.12978756e-01 7.44957983e-01
3.49298388e-01 1.83421448e-01 6.74938977e-01 -1.25208318e+00
1.03135443e+00 -5.79729736e-01 -1.29345343e-01 -9.68889967e-02
-5.67417681e-01 3.88523228e-02 2.98043519e-01 -3.97382826e-01
-1.33036721e+00 -2.68761516e-01 -4.16471988e-01 2.55390406e-01
-5.10459185e-01 8.34136784e-01 -5.79764880e-03 8.70851517e-01
7.16253579e-01 3.05859059e-01 -2.79326797e-01 -4.66544956e-01
2.27018639e-01 7.65832245e-01 2.25266609e-02 -1.03500247e-01
5.15103877e-01 4.45953488e-01 -5.32567322e-01 -1.34374869e+00
-1.39631999e+00 -5.79220653e-01 -6.01708591e-01 -1.55210629e-01
9.87985909e-01 -8.59279931e-01 1.76115692e-01 3.59748632e-01
-1.44779205e+00 2.30054960e-01 -6.69314206e-01 5.41082442e-01
-2.92569101e-01 1.25356093e-01 -4.09969121e-01 -7.64045894e-01
-7.17986345e-01 -7.04622030e-01 1.21550524e+00 3.20991933e-01
-6.90666199e-01 -1.06712568e+00 2.72473305e-01 1.13979839e-01
6.79199040e-01 -6.15209080e-02 9.60186183e-01 -1.41756248e+00
-1.22848071e-01 -4.28774208e-01 2.35156357e-01 2.71108299e-01
1.70703933e-01 -4.51925136e-02 -1.30599630e+00 7.04317763e-02
2.43890211e-01 1.77843217e-02 1.06267893e+00 6.17053032e-01
5.54706514e-01 -4.09354120e-01 -2.79984772e-01 -1.74628850e-02
9.65638340e-01 -1.10910036e-01 5.17769992e-01 7.00930536e-01
2.75480986e-01 9.18773472e-01 4.35191870e-01 2.71829844e-01
2.64688939e-01 4.67810065e-01 1.06913567e-01 -1.08398527e-01
-1.61080167e-01 -8.21377411e-02 4.73276496e-01 9.89283621e-01
2.45810851e-01 -4.34164137e-01 -6.97368205e-01 9.12887514e-01
-1.61372435e+00 -1.05561674e+00 -2.95893431e-01 1.84097958e+00
8.83053958e-01 6.57848299e-01 1.00822382e-01 9.97078419e-02
6.23548865e-01 6.43288612e-01 3.24968286e-02 -6.21186197e-01
-3.38415265e-01 1.53294891e-01 -2.06846520e-01 4.19790834e-01
-1.68379819e+00 9.05058146e-01 5.89241171e+00 8.11343908e-01
-7.83977211e-01 2.17621446e-01 5.53457677e-01 -1.28443345e-01
-5.91150761e-01 6.44460097e-02 -1.08795178e+00 2.78805405e-01
1.18407762e+00 -4.07452732e-01 -4.26902801e-01 1.13031054e+00
2.16679171e-01 -4.22690183e-01 -9.00856316e-01 2.16337487e-01
4.23823595e-01 -1.24278557e+00 3.41636211e-01 -1.42613173e-01
8.12176526e-01 1.37651607e-01 -3.31720591e-01 6.54760420e-01
1.24018230e-01 -5.86015999e-01 4.56432670e-01 3.29434484e-01
-8.23893547e-02 -6.15328550e-01 1.31624961e+00 4.89470363e-01
-6.78115427e-01 3.16501945e-01 -5.10122776e-01 6.69303834e-02
4.13263172e-01 1.23502004e+00 -1.10072649e+00 5.90874553e-01
7.16953933e-01 6.67180121e-01 -5.97090304e-01 9.26830292e-01
-5.23803771e-01 9.65660393e-01 -2.92295277e-01 -3.43273789e-01
3.77058506e-01 -3.73038538e-02 1.08292425e+00 1.44865119e+00
7.54658505e-02 -3.53923559e-01 -9.92620364e-02 7.76146948e-01
5.58596551e-02 5.51440060e-01 -6.24058902e-01 -2.60404319e-01
-3.40614915e-02 1.31055152e+00 -9.78310525e-01 -8.09546173e-01
-5.07589817e-01 4.98857349e-01 1.25176176e-01 2.75621593e-01
-3.49869162e-01 -5.40221035e-01 4.29056048e-01 1.46264508e-01
6.06724441e-01 4.65003140e-02 -4.65126365e-01 -1.23602438e+00
1.26260368e-03 -7.26582944e-01 2.79110998e-01 -4.78968054e-01
-1.20564771e+00 1.23595107e+00 7.76037127e-02 -1.09256446e+00
-6.24035120e-01 -1.88729718e-01 -9.96238053e-01 7.18131125e-01
-1.24228573e+00 -1.00886261e+00 4.32434194e-02 1.89673379e-01
1.03699100e+00 -2.69041032e-01 9.91504371e-01 -1.99756846e-02
-1.89852953e-01 1.18000852e-02 -8.18966925e-02 2.28511896e-02
4.97424841e-01 -1.35734117e+00 5.36994696e-01 9.01214123e-01
3.52117777e-01 6.89670742e-01 1.21408117e+00 -7.84582675e-01
-7.98418045e-01 -1.07218170e+00 1.57431757e+00 -4.40395206e-01
6.97945118e-01 -5.02239347e-01 -1.01142931e+00 6.36351109e-01
1.00321877e+00 -8.28461826e-01 8.91978085e-01 7.26820707e-01
-2.49678090e-01 1.74890682e-01 -6.53901398e-01 5.72684705e-01
2.55725294e-01 -3.84873241e-01 -1.33265913e+00 4.53828186e-01
9.71278846e-01 3.68991867e-02 -6.99186802e-01 3.11658829e-01
7.81372711e-02 -9.36489046e-01 7.10744083e-01 -6.91701412e-01
6.36787117e-01 -3.99657004e-02 1.48836866e-01 -1.52469766e+00
-1.81233525e-01 -5.64137638e-01 -1.06373668e-01 1.63006389e+00
8.59465361e-01 -3.64886880e-01 7.18708694e-01 2.56135374e-01
-2.32553676e-01 -6.02408230e-01 -8.13572407e-01 -3.06978315e-01
1.61153153e-01 -4.16521400e-01 3.37539047e-01 7.11997211e-01
2.61885017e-01 1.12022221e+00 -2.04733670e-01 -1.66926742e-01
3.30701590e-01 3.32966238e-01 6.67751789e-01 -1.32017994e+00
-2.34862491e-01 -5.43641031e-01 -1.44354388e-01 -6.68529749e-01
2.90119141e-01 -6.51131928e-01 2.34779790e-01 -1.93707025e+00
4.70499903e-01 2.55172938e-01 -6.16560467e-02 2.70657688e-01
-5.23049116e-01 -4.77943830e-02 2.06097332e-03 -6.36504963e-02
-8.06306779e-01 8.80852759e-01 8.44359100e-01 -3.71891171e-01
-2.97334373e-01 3.85137200e-01 -7.82273948e-01 8.33818138e-01
8.92150879e-01 -7.55763233e-01 -2.17957437e-01 -6.71515912e-02
2.91309476e-01 -5.10400951e-01 -2.22819522e-01 -9.59480286e-01
1.17377460e-01 4.18152183e-01 2.80800134e-01 -1.10067308e+00
2.75478154e-01 -5.69836676e-01 -4.12129432e-01 1.60833165e-01
-6.79538548e-01 -3.28822345e-01 2.94080883e-01 5.35909653e-01
-6.47977114e-01 -5.10768712e-01 4.13680166e-01 -7.94210956e-02
-2.73478478e-01 -9.43828449e-02 -1.24752808e+00 5.58547787e-02
5.18750787e-01 2.21457124e-01 -5.14514625e-01 -7.97858655e-01
-8.56554210e-01 -1.08071513e-01 -5.42280972e-02 5.60123205e-01
4.37725186e-01 -8.67511213e-01 -9.93389130e-01 1.45245790e-01
1.45856619e-01 -2.44221836e-03 4.40296888e-01 7.94580460e-01
-2.14892775e-02 7.94719219e-01 1.06173672e-01 -4.93642896e-01
-1.18150043e+00 4.97799128e-01 -3.24763089e-01 -6.90489233e-01
-7.68665254e-01 7.12866008e-01 3.20123345e-01 -4.08537298e-01
1.47119805e-01 -2.31559500e-01 -8.97318602e-01 6.13422811e-01
7.24158823e-01 -1.23458080e-01 3.56139511e-01 -5.83514273e-01
-1.17756329e-01 1.93140149e-01 -5.32973588e-01 -2.90764928e-01
1.82947600e+00 -1.42721131e-01 -2.25303590e-01 5.33627689e-01
1.03703892e+00 8.55701193e-02 -8.12697828e-01 -4.27006096e-01
4.34598118e-01 1.24571688e-01 2.65893549e-01 -4.99804884e-01
-5.71035922e-01 8.40662181e-01 8.53395239e-02 9.65000451e-01
9.32144821e-01 4.47893500e-01 5.20644665e-01 4.45449740e-01
-2.01692283e-01 -1.39901865e+00 -5.44635020e-02 8.99409711e-01
9.86313164e-01 -1.19826794e+00 3.02505344e-01 -4.01737452e-01
-6.73144400e-01 1.03359902e+00 3.52524519e-01 -1.74047589e-01
9.90892231e-01 2.95896739e-01 1.05054259e-01 -5.19728601e-01
-1.13702333e+00 -5.12664378e-01 5.66491187e-01 5.34530044e-01
7.53555715e-01 -1.47853777e-01 -6.21819794e-01 8.52621615e-01
-4.71704632e-01 -3.69023949e-01 7.01298475e-01 9.87316191e-01
-7.08016157e-01 -8.83341134e-01 -2.82026798e-01 7.39332855e-01
-9.82576787e-01 -3.02327156e-01 -6.39796734e-01 7.04943120e-01
-3.46699595e-01 1.04802561e+00 3.21583956e-01 -1.18883334e-01
1.41062081e-01 3.95406485e-01 -1.78481936e-01 -9.94329929e-01
-9.56583023e-01 5.91538727e-01 7.43580997e-01 -1.28865585e-01
-7.12110996e-01 -7.61386871e-01 -6.90882683e-01 3.12276483e-01
-3.48155171e-01 5.45657396e-01 9.95229244e-01 1.23506856e+00
4.95142788e-01 9.54116642e-01 2.70147592e-01 -9.06595290e-01
-1.64502442e-01 -1.60504150e+00 -4.03968692e-01 3.39518785e-01
2.57239819e-01 -2.78380960e-01 -3.07525754e-01 1.54123977e-01] | [11.366394996643066, 6.753102779388428] |
d67ef436-5a26-4667-932a-34d4724799e2 | code-switching-language-modeling-using-syntax | 1805.12070 | null | http://arxiv.org/abs/1805.12070v2 | http://arxiv.org/pdf/1805.12070v2.pdf | Code-Switching Language Modeling using Syntax-Aware Multi-Task Learning | Lack of text data has been the major issue on code-switching language
modeling. In this paper, we introduce multi-task learning based language model
which shares syntax representation of languages to leverage linguistic
information and tackle the low resource data issue. Our model jointly learns
both language modeling and Part-of-Speech tagging on code-switched utterances.
In this way, the model is able to identify the location of code-switching
points and improves the prediction of next word. Our approach outperforms
standard LSTM based language model, with an improvement of 9.7% and 7.4% in
perplexity on SEAME Phase I and Phase II dataset respectively. | ['Chien-Sheng Wu', 'Pascale Fung', 'Genta Indra Winata', 'Andrea Madotto'] | 2018-05-30 | code-switching-language-modeling-using-syntax-1 | https://aclanthology.org/W18-3207 | https://aclanthology.org/W18-3207.pdf | ws-2018-7 | ['syntax-representation'] | ['natural-language-processing'] | [-4.45051134e-01 -1.31878555e-01 -6.74961209e-01 -3.98882270e-01
-1.40303230e+00 -4.14253801e-01 1.86386555e-01 3.30630213e-01
-3.18937391e-01 5.00432074e-01 3.88494998e-01 -7.68211961e-01
1.13738045e-01 -2.62166917e-01 -5.69154799e-01 -1.21147707e-01
-1.66239530e-01 2.50134736e-01 1.26201496e-01 -2.87911773e-01
3.61386418e-01 9.33687761e-03 -6.60717845e-01 7.82268882e-01
7.42746294e-01 4.32819933e-01 6.23288631e-01 5.61539233e-01
-8.73642802e-01 1.30120063e+00 -4.73690510e-01 3.40824910e-02
-1.59866884e-01 5.54045439e-02 -8.47318470e-01 -1.83933482e-01
1.43432051e-01 3.05576563e-01 -2.45726824e-01 8.16353798e-01
2.56338984e-01 9.88863707e-02 3.05207580e-01 -9.34539378e-01
-5.18373549e-01 1.10344279e+00 -8.96800697e-01 4.33137834e-01
2.58558631e-01 -3.77042532e-01 1.11085427e+00 -9.52321947e-01
4.70828861e-01 1.24754083e+00 7.56030679e-01 4.42083240e-01
-9.45382118e-01 -7.58693457e-01 2.57473886e-01 -2.11759582e-01
-1.56182027e+00 -4.89488780e-01 7.44273782e-01 -1.00491858e+00
1.64939737e+00 -4.75776881e-01 6.05203165e-03 1.02917182e+00
9.11787808e-01 9.07441318e-01 8.36357951e-01 -6.16139054e-01
-2.03942895e-01 9.01106372e-02 3.12270075e-01 1.18144846e+00
-1.99037001e-01 -3.63919228e-01 -6.26908481e-01 -1.71181336e-01
3.89284760e-01 2.33984485e-01 3.16504985e-01 -1.44911185e-01
-1.07997167e+00 9.00740862e-01 -8.17397889e-03 7.76105225e-01
-1.84649453e-01 4.16368783e-01 7.33107924e-01 2.81100631e-01
6.53426170e-01 1.36079326e-01 -1.00433159e+00 -5.72259009e-01
-1.13018203e+00 -3.32804650e-01 6.49821937e-01 1.20822549e+00
7.81675518e-01 3.82526904e-01 -1.79862365e-01 1.21665370e+00
8.06876719e-01 4.89100367e-01 9.39960957e-01 -4.38406497e-01
9.21130180e-01 7.45073020e-01 -4.32274073e-01 -5.05648315e-01
-4.49504107e-01 -6.00336730e-01 -4.02752519e-01 -4.67214108e-01
-2.67888546e-01 -6.11349285e-01 -9.58947182e-01 1.57910323e+00
-5.20402789e-01 1.07825294e-01 4.98815514e-02 -7.52174407e-02
5.75344503e-01 9.37980056e-01 3.10416371e-01 1.68839648e-01
1.35518599e+00 -1.31943738e+00 -7.91082323e-01 -8.03025544e-01
1.23793960e+00 -1.12127244e+00 8.73311579e-01 6.05862997e-02
-7.96563327e-01 -5.75210929e-01 -7.60103941e-01 9.33038741e-02
-2.37906799e-01 5.77455580e-01 6.97132587e-01 4.99848813e-01
-1.06186795e+00 -6.51661307e-02 -8.62372339e-01 -3.64376605e-01
2.77907819e-01 5.25507689e-01 -2.21452102e-01 9.62970331e-02
-1.01132572e+00 7.06381917e-01 3.78074557e-01 -4.16679889e-01
-1.05133522e+00 -6.59944832e-01 -1.09416425e+00 1.01258382e-01
2.30698153e-01 8.71407520e-03 1.39896250e+00 -7.48366296e-01
-1.43775916e+00 7.79068172e-01 -5.71162581e-01 -4.30555135e-01
-1.30961269e-01 -2.08684370e-01 -7.89390385e-01 -6.82652771e-01
4.03713137e-01 4.39415395e-01 4.60261196e-01 -8.57741833e-01
-7.20392287e-01 3.92170995e-02 -2.11614028e-01 -2.99829155e-01
-2.87493140e-01 3.71511877e-01 -5.42447746e-01 -6.36892378e-01
-3.24926674e-01 -9.23730612e-01 -2.58764833e-01 -5.80037117e-01
-2.35549077e-01 -4.96142417e-01 6.20654941e-01 -9.39410925e-01
1.73980224e+00 -2.47153640e+00 -1.18574254e-01 -2.62385339e-01
7.34163970e-02 3.13608915e-01 -5.68744779e-01 8.28497112e-01
2.19465625e-02 2.81161934e-01 4.93627340e-02 -6.74717963e-01
-2.52306610e-01 2.11157486e-01 -3.50703955e-01 1.42375603e-01
1.54748052e-01 7.31263220e-01 -7.12979317e-01 -5.21794200e-01
2.03588400e-02 3.53966504e-01 -7.07212925e-01 1.61120445e-01
-2.38767043e-01 2.44852439e-01 -5.85324526e-01 6.69802666e-01
3.21222067e-01 -2.17155680e-01 2.22386122e-01 4.34153378e-01
-4.88849878e-01 6.25857353e-01 -7.02436328e-01 2.40741420e+00
-1.24771833e+00 8.52111697e-01 -1.48097083e-01 -8.28271806e-01
1.04697609e+00 4.68661457e-01 3.62034500e-01 -7.87460566e-01
-1.51174918e-01 2.02818036e-01 2.80121595e-01 -7.01234460e-01
2.68615842e-01 -1.82781313e-02 -5.55209875e-01 2.51391888e-01
4.04536039e-01 5.83039463e-01 -5.26283272e-02 1.16225637e-01
1.14741218e+00 1.78794742e-01 4.75103140e-01 -5.60101807e-01
7.08928525e-01 -1.06146045e-01 8.12330782e-01 5.73351562e-01
-6.41453713e-02 -1.22416236e-01 4.16028410e-01 -3.76585245e-01
-7.38270044e-01 -6.98402703e-01 1.28044650e-01 1.62813938e+00
-4.95049089e-01 -6.10370398e-01 -3.32284480e-01 -7.39587784e-01
-1.19247966e-01 8.55421126e-01 -3.75647932e-01 -1.07601378e-02
-8.30494821e-01 -4.54607606e-01 8.64960909e-01 4.19470459e-01
1.79990917e-01 -8.02302599e-01 -4.38894778e-02 5.13897359e-01
-2.99917459e-01 -1.08753765e+00 -6.31553173e-01 6.30504727e-01
-8.82513762e-01 -7.60904133e-01 -2.63592452e-01 -1.22540724e+00
3.72340679e-01 1.00597583e-01 1.14242804e+00 6.66554645e-02
3.86558436e-02 -1.76280737e-01 -2.79460371e-01 -7.20394999e-02
-6.38620019e-01 5.26438713e-01 -2.65500546e-01 -1.75787777e-01
5.47792792e-01 -3.07370782e-01 3.71480845e-02 -1.35943994e-01
-5.72340906e-01 1.74624696e-02 8.32102478e-01 6.71428025e-01
3.63861173e-02 -3.59921068e-01 5.44281006e-01 -8.68083358e-01
7.84138501e-01 -8.71866226e-01 -6.82038248e-01 5.02605259e-01
-4.51254278e-01 6.78738832e-01 6.74928367e-01 -3.17854673e-01
-1.13415337e+00 2.08231449e-01 -2.98813730e-01 -1.05349727e-01
-3.40832137e-02 9.25051093e-01 4.06541854e-01 -1.69216037e-01
2.18856305e-01 3.26459855e-01 -5.76966524e-01 -9.16371882e-01
1.24859894e-02 9.97513950e-01 -1.52860701e-01 -5.96870303e-01
3.84695113e-01 -9.55814030e-03 -4.42741811e-01 -6.76823914e-01
-7.88051128e-01 -8.18118870e-01 -8.30105186e-01 6.78160042e-02
8.92401814e-01 -1.44662750e+00 -5.00210881e-01 2.58720845e-01
-1.41291845e+00 -4.81240571e-01 5.23985028e-01 4.82634574e-01
-1.62556112e-01 2.60805458e-01 -8.52770925e-01 -7.14203894e-01
-1.49171650e-01 -1.49947155e+00 1.08243096e+00 -2.26949781e-01
-9.57836956e-02 -1.51104856e+00 4.34629858e-01 4.31533307e-01
6.28377140e-01 -2.56769001e-01 1.34531450e+00 -9.43789959e-01
-5.00560403e-01 -3.59345861e-02 8.25960338e-02 3.36413570e-02
1.82471722e-01 6.24382943e-02 -6.23402357e-01 -4.63389993e-01
-2.41902873e-01 -2.26827621e-01 7.77705967e-01 4.19383049e-01
7.97613084e-01 -3.26448157e-02 -6.24123871e-01 3.64143103e-01
1.83825159e+00 5.90987146e-01 8.89552087e-02 2.46733636e-01
6.89162552e-01 2.18021885e-01 3.04172993e-01 5.17121077e-01
6.46413028e-01 7.83409953e-01 -5.97651862e-02 1.85125113e-01
-3.27095211e-01 -3.77419919e-01 7.35409141e-01 1.80848193e+00
7.88563728e-01 -2.63962746e-01 -1.75067842e+00 9.14417684e-01
-1.82485998e+00 -3.84951234e-01 -2.71122038e-01 1.77493763e+00
7.26552069e-01 1.96116939e-01 -2.89511889e-01 -6.35200202e-01
6.35797977e-01 2.52995104e-01 -5.00153266e-02 -6.86956942e-01
3.33801746e-01 1.28355578e-01 7.84407318e-01 1.01804328e+00
-1.05473125e+00 1.47081316e+00 6.39847803e+00 8.82152915e-01
-1.18566799e+00 7.11340725e-01 8.05230290e-02 2.05868572e-01
-2.00146794e-01 3.70924056e-01 -1.07925868e+00 6.30880535e-01
1.32574213e+00 -1.78436205e-01 3.07164907e-01 8.20261955e-01
2.53962636e-01 -3.06138918e-02 -9.55196261e-01 9.15516317e-01
3.39243501e-01 -1.27159214e+00 1.17243379e-02 -3.49120470e-03
7.53360987e-01 7.43646562e-01 -8.79719183e-02 8.66093040e-01
5.90674043e-01 -9.49497402e-01 6.36434436e-01 4.97754067e-01
4.23503876e-01 -7.39052474e-01 7.88517594e-01 5.95724046e-01
-1.53209782e+00 -2.63674349e-01 -1.62726596e-01 -1.95437118e-01
1.52317867e-01 4.54165041e-01 -8.37579787e-01 2.85899460e-01
2.35421732e-01 8.51065099e-01 -7.63150454e-01 9.46029782e-01
-5.11970893e-02 7.22237587e-01 1.34145215e-01 7.39629716e-02
6.76737010e-01 1.60841390e-01 1.86032116e-01 1.61425734e+00
4.56457704e-01 -5.71747422e-01 7.48003185e-01 7.36171722e-01
-2.88749695e-01 9.20032188e-02 -6.80329442e-01 -2.19980642e-01
5.88539839e-01 9.55051064e-01 -4.82046634e-01 -2.57825077e-01
-1.01016271e+00 8.01555932e-01 4.99945551e-01 2.78418362e-01
-7.17285097e-01 -5.18738151e-01 5.97447574e-01 -2.94591516e-01
3.68047506e-01 -6.37455940e-01 2.09971890e-02 -1.24495840e+00
-1.63985282e-01 -7.27952778e-01 1.73504084e-01 -3.08771610e-01
-7.61930287e-01 7.04398572e-01 -2.44058371e-01 -1.06374025e+00
-2.95186251e-01 -5.08327723e-01 -7.56586432e-01 8.07482481e-01
-1.68762481e+00 -1.41189075e+00 3.06133568e-01 2.98199624e-01
1.21680200e+00 -7.17343032e-01 7.79551089e-01 8.62742484e-01
-8.75106335e-01 5.87816775e-01 4.71069604e-01 4.81582731e-01
7.81379402e-01 -1.00348699e+00 7.69968688e-01 9.85415399e-01
2.52382278e-01 9.72877145e-01 3.12233388e-01 -7.60558128e-01
-1.40303969e+00 -1.17237115e+00 1.50015700e+00 -5.10453224e-01
9.96738434e-01 -6.87578380e-01 -7.21412599e-01 1.07389688e+00
3.49657744e-01 -1.87375084e-01 1.07880807e+00 3.88130248e-01
-4.14393216e-01 8.99133980e-02 -5.55743158e-01 1.67261943e-01
5.95227122e-01 -8.95462573e-01 -5.84051788e-01 3.08481336e-01
8.87008309e-01 -1.39920786e-01 -1.03461576e+00 1.08767524e-01
4.60496545e-02 -4.90023762e-01 4.84897375e-01 -6.29188299e-01
3.49808663e-01 -1.27992600e-01 -2.84650922e-01 -1.18146753e+00
-4.16722029e-01 -5.02648413e-01 1.23452850e-01 1.36782146e+00
9.51008081e-01 -3.05677980e-01 2.84843594e-01 -4.24601510e-02
-4.59863484e-01 -7.34881997e-01 -9.67490435e-01 -8.10701132e-01
3.60236645e-01 -5.93664825e-01 1.03060447e-01 1.03503144e+00
4.13959995e-02 5.82810462e-01 -6.48802578e-01 -1.39541589e-02
2.93555230e-01 5.72734922e-02 3.74226093e-01 -1.08409691e+00
-2.32070491e-01 -3.52747083e-01 -2.48087035e-03 -1.27762008e+00
8.33890140e-01 -1.24482965e+00 5.88546470e-02 -1.56771910e+00
4.22834903e-01 -3.29939574e-01 -4.35570836e-01 8.13242257e-01
2.04488963e-01 -5.15108705e-01 1.33591473e-01 9.69154909e-02
-9.30121124e-01 3.56161177e-01 5.00938773e-01 -1.07579939e-01
-1.59803450e-01 -1.26411214e-01 -3.79860967e-01 6.75378144e-01
9.09945905e-01 -1.02174413e+00 -1.82148352e-01 -1.04632294e+00
3.73463184e-01 4.63214189e-01 -3.97361994e-01 -8.85641098e-01
4.39271182e-01 -3.62502933e-02 -1.93067625e-01 -4.71831739e-01
-7.68963769e-02 -6.65611804e-01 -2.26671547e-01 8.24232042e-01
-6.19211674e-01 4.11266685e-01 6.49085641e-01 5.10833085e-01
-2.92591572e-01 -4.38257515e-01 6.38098419e-01 -2.14269876e-01
-1.06316674e+00 1.11150160e-01 -1.08681989e+00 2.64934838e-01
8.38548601e-01 2.62320399e-01 -3.83982547e-02 1.16430856e-01
-3.89762998e-01 3.97448391e-01 1.18193291e-01 1.11992502e+00
3.70944291e-01 -1.24503386e+00 -5.09212732e-01 3.78176033e-01
3.91214848e-01 -6.09115064e-01 6.88034575e-03 7.12253451e-01
-3.23565006e-01 1.04680121e+00 -8.58024135e-02 -4.27625716e-01
-1.19777560e+00 3.65118444e-01 3.53751004e-01 -5.62022328e-01
-2.09574386e-01 8.34730089e-01 -1.45785585e-01 -7.74486244e-01
3.10477525e-01 -6.63062215e-01 -1.91099778e-01 -4.82056625e-02
7.54345506e-02 -3.96149084e-02 1.08911440e-01 -6.97336435e-01
-7.74284005e-01 5.73647797e-01 -3.33595693e-01 1.59866482e-01
1.37728536e+00 -1.17738456e-01 -3.88558656e-01 1.04111803e+00
1.45125020e+00 3.54199618e-01 -8.74602437e-01 -4.71671730e-01
8.16691637e-01 -1.99649885e-01 2.33025357e-01 -7.89031625e-01
-9.06417131e-01 1.12271488e+00 5.73909342e-01 -3.90722036e-01
5.00909388e-01 1.02971599e-01 9.79053855e-01 4.92402524e-01
5.47919631e-01 -1.04196405e+00 1.23559244e-01 1.03406382e+00
3.48936141e-01 -1.28447497e+00 -4.99289900e-01 4.31896858e-02
-5.33528328e-01 1.16951108e+00 7.04894006e-01 1.85116529e-02
7.96482563e-01 6.44916356e-01 1.42238900e-01 -3.05894554e-01
-1.17709100e+00 5.11992350e-02 2.81675041e-01 2.00631648e-01
1.28958941e+00 6.00487180e-02 -1.07233450e-01 4.24095392e-01
3.43218595e-01 -1.32657632e-01 3.49339962e-01 9.71761644e-01
-6.04083300e-01 -1.54979980e+00 9.30163935e-02 3.35705340e-01
-7.76396334e-01 -6.06620550e-01 -4.52845879e-02 5.25114596e-01
1.67944133e-01 9.62355256e-01 1.63014252e-02 -4.03925240e-01
1.29188299e-01 5.08269906e-01 -5.61068766e-02 -1.17196214e+00
-8.10114086e-01 1.70040891e-01 2.62865666e-02 -4.11060780e-01
-2.12323532e-01 -3.21786612e-01 -1.37355947e+00 -5.30715175e-02
-2.36117825e-01 3.17778796e-01 8.29876900e-01 1.09686947e+00
6.12220824e-01 9.60744202e-01 4.90118206e-01 -1.64097697e-01
-2.99952894e-01 -1.03889740e+00 -2.80889273e-01 -5.44836968e-02
6.11885130e-01 -3.17807853e-01 7.26575777e-02 -9.97445825e-03] | [10.498238563537598, 9.72341537475586] |
ebe8410b-88f3-4160-9203-9f55853d5f65 | llm-rm-at-semeval-2023-task-2-multilingual | 2305.03300 | null | https://arxiv.org/abs/2305.03300v1 | https://arxiv.org/pdf/2305.03300v1.pdf | LLM-RM at SemEval-2023 Task 2: Multilingual Complex NER using XLM-RoBERTa | Named Entity Recognition(NER) is a task of recognizing entities at a token level in a sentence. This paper focuses on solving NER tasks in a multilingual setting for complex named entities. Our team, LLM-RM participated in the recently organized SemEval 2023 task, Task 2: MultiCoNER II,Multilingual Complex Named Entity Recognition. We approach the problem by leveraging cross-lingual representation provided by fine-tuning XLM-Roberta base model on datasets of all of the 12 languages provided -- Bangla, Chinese, English, Farsi, French, German, Hindi, Italian, Portuguese, Spanish, Swedish and Ukrainian | ['Vasudeva Varma', 'Rahul Mehta'] | 2023-05-05 | null | null | null | null | ['named-entity-recognition-ner'] | ['natural-language-processing'] | [-7.83563793e-01 -1.24455497e-01 3.07337474e-02 -4.17595088e-01
-1.02785063e+00 -9.63357151e-01 5.28906882e-01 2.35263839e-01
-1.23890233e+00 1.52406406e+00 6.62892282e-01 -2.76947588e-01
2.81580597e-01 -4.65533495e-01 -4.85543132e-01 1.35962099e-01
-2.77135342e-01 5.62194943e-01 -1.48740411e-01 -2.76985884e-01
1.78248733e-01 9.82082605e-01 -4.61164027e-01 3.95170927e-01
7.73035884e-01 2.27721885e-01 -1.27171576e-01 6.37522399e-01
-2.52285838e-01 1.27267325e+00 -6.40027046e-01 -8.09686303e-01
8.28847848e-03 -6.66656122e-02 -1.45051193e+00 -5.15716910e-01
1.88456818e-01 4.73008424e-01 -1.90057397e-01 8.49462628e-01
7.21825480e-01 1.99377075e-01 6.69559062e-01 -7.18173325e-01
-7.34783590e-01 1.13922775e+00 -3.68920892e-01 3.62759709e-01
3.22913080e-01 -2.69741625e-01 1.18636572e+00 -1.34736502e+00
1.44269633e+00 1.05897641e+00 1.08996940e+00 4.57060099e-01
-7.52300799e-01 -4.80191290e-01 -1.43342525e-01 1.19294837e-01
-1.99067998e+00 -5.98923087e-01 -5.36449775e-02 -3.26383226e-02
1.85492730e+00 -3.84679548e-02 -1.42252654e-01 9.17421460e-01
4.04999554e-02 9.00562048e-01 1.25148714e+00 -5.57553470e-01
1.10861935e-01 3.61741781e-01 3.80241960e-01 4.13906157e-01
3.75830948e-01 -1.84350327e-01 -4.57801640e-01 -1.50761113e-01
1.41762540e-01 -6.95945203e-01 -1.07509658e-01 3.09590787e-01
-1.44742203e+00 6.23926044e-01 1.14797972e-01 1.10590458e+00
-6.55932486e-01 -2.62767404e-01 8.13882709e-01 5.01607776e-01
4.36760902e-01 8.26691806e-01 -1.51954436e+00 -3.29082906e-01
-8.58451605e-01 -2.08513290e-01 1.37993276e+00 1.44328523e+00
5.42875051e-01 7.07145482e-02 -1.60301879e-01 9.59973037e-01
2.51549661e-01 5.54506540e-01 5.28989434e-01 -8.16604495e-02
9.12219942e-01 2.30186015e-01 3.43920439e-01 -4.71105337e-01
-8.79516184e-01 -1.83753334e-02 -6.27139032e-01 -3.40782404e-01
9.41373259e-02 -1.00991571e+00 -9.06378031e-01 1.58737850e+00
4.63113904e-01 -1.16784923e-01 8.48033667e-01 3.44683439e-01
1.05075324e+00 6.87408566e-01 7.13066518e-01 -5.74725457e-02
1.69808018e+00 -1.06497085e+00 -7.51667619e-01 1.45275220e-02
8.84131789e-01 -9.37189519e-01 1.66716143e-01 3.82571928e-02
-8.13527286e-01 -2.87554979e-01 -5.81618249e-01 -1.83091193e-01
-1.19664276e+00 7.76815414e-01 2.81679511e-01 6.79880619e-01
-8.98130894e-01 3.82879764e-01 -7.78976500e-01 -7.22283423e-01
-1.65698379e-02 3.08513880e-01 -1.20053840e+00 -3.43288737e-03
-1.63648248e+00 1.27482402e+00 1.25328267e+00 2.77380258e-01
-4.24932688e-01 -7.57560253e-01 -1.19580996e+00 -9.44270641e-02
-1.15302391e-01 -1.47991970e-01 8.58577669e-01 -1.44210711e-01
-1.00446749e+00 1.16253018e+00 -1.11719847e-01 -5.07565796e-01
1.46844298e-01 -4.30338979e-01 -1.28142595e+00 -3.21950853e-01
5.82507372e-01 4.55287874e-01 -3.35266799e-01 -7.84761786e-01
-8.84995162e-01 -4.42108482e-01 -2.29382530e-01 -3.99241894e-02
3.95726040e-02 9.22069252e-01 -5.82222752e-02 -6.88597381e-01
-7.06075191e-01 -8.86675000e-01 -5.83483219e-01 -1.20581591e+00
-8.99090171e-01 -5.17065644e-01 3.57452750e-01 -1.15597332e+00
1.31102598e+00 -2.34658861e+00 -3.23940039e-01 -2.58817319e-02
-2.88374811e-01 4.07669008e-01 -1.89251766e-01 9.61351156e-01
-4.95792717e-01 4.16959882e-01 -9.76795703e-03 -2.87919283e-01
1.51371002e-01 4.65625487e-02 -2.91313678e-02 2.87529826e-01
7.16696024e-01 9.04281855e-01 -7.93185294e-01 -6.92427516e-01
-1.56856164e-01 4.93950784e-01 2.05028486e-02 1.59340322e-01
3.28276783e-01 3.44787776e-01 -4.47474688e-01 4.63703036e-01
6.95846796e-01 3.36469144e-01 3.09054106e-01 -1.80181488e-01
-8.64295781e-01 6.43028796e-01 -1.67850816e+00 1.67986178e+00
-7.63328910e-01 5.33352733e-01 -1.53242769e-02 -5.18405914e-01
7.95838952e-01 9.13519382e-01 1.78841814e-01 -3.51043344e-01
-8.09228271e-02 6.74286425e-01 -5.30872464e-01 -4.64810580e-01
8.01122427e-01 -1.75049394e-01 -7.39891589e-01 4.95956000e-03
6.30240142e-01 4.48516428e-01 7.88084030e-01 2.71154698e-02
1.21437752e+00 5.60511015e-02 1.12068558e+00 -2.77048111e-01
6.69460416e-01 3.06778163e-01 7.63274193e-01 6.75361812e-01
-4.01399553e-01 4.31481749e-01 -9.91153624e-03 -3.30346674e-01
-1.08028054e+00 -9.38120484e-01 -5.03597260e-01 1.26540184e+00
-6.32973373e-01 -4.80759352e-01 -5.00621974e-01 -1.02540624e+00
-2.52831340e-01 8.84796441e-01 -4.34080958e-01 4.96240169e-01
-1.15763342e+00 -7.09649861e-01 1.49221933e+00 3.93983483e-01
5.96839488e-01 -1.76756489e+00 7.07569197e-02 6.52774453e-01
-2.61426598e-01 -1.76109838e+00 -6.62348390e-01 6.39053285e-01
-3.45089138e-01 -8.36945355e-01 -7.65822649e-01 -1.15478814e+00
1.79406762e-01 -6.97795749e-01 1.53984582e+00 -7.04544425e-01
-5.29494464e-01 3.83484930e-01 -4.53640670e-01 -4.05016661e-01
-2.91283935e-01 6.12428486e-01 4.65282500e-02 -2.98510194e-01
6.91528738e-01 -5.88771254e-02 8.94756541e-02 -7.69874603e-02
-4.72561508e-01 -6.38552606e-01 8.31340253e-01 6.21910632e-01
5.28559506e-01 -7.64617994e-02 7.52393425e-01 -1.48403740e+00
2.35748574e-01 -7.07262397e-01 -1.50067359e-01 7.21718490e-01
-3.66681814e-02 1.96951702e-01 8.76268029e-01 1.40402811e-02
-1.55925226e+00 3.04791689e-01 -5.11222422e-01 4.23449636e-01
-7.96681762e-01 6.67688668e-01 -6.60735846e-01 2.97363192e-01
6.64626777e-01 1.55038044e-01 -1.52817571e+00 -7.59976506e-01
6.83460355e-01 1.07235646e+00 6.48063302e-01 -4.97562796e-01
5.92985272e-01 -1.09196439e-01 -4.45292860e-01 -1.05410182e+00
-9.26244080e-01 -9.19234991e-01 -1.26006246e+00 3.41898561e-01
1.30164623e+00 -1.41303921e+00 -2.11171910e-01 4.39971268e-01
-1.56572175e+00 1.70668602e-01 -4.49302554e-01 8.62719715e-01
-1.75788794e-02 5.23532508e-03 -1.26203990e+00 -6.82183444e-01
-7.25748062e-01 -2.71804839e-01 1.06926703e+00 4.66467619e-01
-1.17815927e-01 -1.34799004e+00 6.41912699e-01 7.54785240e-02
2.03547418e-01 2.11079553e-01 6.93676889e-01 -1.62795973e+00
9.06092003e-02 -2.60908604e-01 -1.90570921e-01 3.37300658e-01
-9.80887860e-02 -2.20481813e-01 -5.48387349e-01 -1.14169151e-01
-4.89309043e-01 -4.80018049e-01 5.51124871e-01 -2.97803938e-01
1.90871079e-02 -2.39446700e-01 -2.12157279e-01 2.36732170e-01
1.69001734e+00 1.62588596e-01 5.34730434e-01 5.87239444e-01
7.73425698e-01 2.83922911e-01 4.81322289e-01 5.88090658e-01
8.63222599e-01 1.47340998e-01 -5.79621911e-01 -2.13835627e-01
-1.84168126e-02 -8.71393010e-02 4.34112549e-01 1.15364528e+00
2.90759709e-02 -2.00101748e-01 -1.28003824e+00 9.83994901e-01
-1.30898130e+00 -8.65524292e-01 -4.68195438e-01 1.74968326e+00
1.34688795e+00 -1.69989675e-01 -2.53005385e-01 -5.94239533e-01
8.46987188e-01 -1.57122418e-01 -1.05615631e-02 -5.27402580e-01
-6.01319790e-01 6.83967352e-01 7.36364603e-01 9.24428478e-02
-1.64581048e+00 1.45665634e+00 5.69569016e+00 8.75937521e-01
-7.56209970e-01 3.95307869e-01 9.32639763e-02 7.02954590e-01
2.05048114e-01 6.93605617e-02 -1.53825200e+00 1.10769413e-01
1.71253276e+00 -2.94405490e-01 3.54977045e-03 8.15203965e-01
-1.40251040e-01 3.98533195e-01 -8.47491622e-01 5.74659169e-01
-4.86425459e-02 -1.00073218e+00 -2.93257743e-01 -3.59427273e-01
9.82570887e-01 1.06882894e+00 -8.04132521e-01 8.76446962e-01
8.35505068e-01 -8.28929365e-01 5.00119388e-01 5.07141352e-01
6.77816153e-01 -9.29762065e-01 1.01269174e+00 3.28200907e-01
-1.47628677e+00 4.21298981e-01 -3.88577521e-01 9.00259078e-01
5.45334101e-01 5.02450705e-01 -7.71868467e-01 1.09944284e+00
7.15889454e-01 5.22642374e-01 -6.78105712e-01 1.05157602e+00
-3.88657838e-01 8.78867745e-01 -2.82987773e-01 1.21221401e-01
3.44786704e-01 3.70709747e-01 4.90894079e-01 2.26864910e+00
2.48151105e-02 4.92571592e-02 2.74999231e-01 1.85698390e-01
-5.73859751e-01 8.89228284e-01 -4.84157234e-01 -3.97454500e-01
3.81586343e-01 1.51912403e+00 -6.38656557e-01 -3.94314080e-01
-5.03279865e-01 1.01185822e+00 9.48530734e-01 1.55337125e-01
-4.38553602e-01 -1.11762059e+00 1.44706219e-01 -6.69181168e-01
6.03763402e-01 -4.34751004e-01 2.93816086e-02 -1.59081948e+00
-2.66862154e-01 -8.67536664e-01 7.43699253e-01 -4.55516100e-01
-1.72692323e+00 1.08303356e+00 -4.42598909e-01 -8.41820657e-01
-2.17733264e-01 -8.25995028e-01 -5.14422834e-01 9.76433456e-01
-1.55990779e+00 -1.29943037e+00 4.92197305e-01 6.73270047e-01
2.13158071e-01 -3.71801645e-01 1.10045898e+00 1.01341259e+00
-6.59208298e-01 7.10950613e-01 3.75491709e-01 1.03886509e+00
1.13974440e+00 -1.56053185e+00 9.58359241e-01 6.81693375e-01
6.06274784e-01 7.61472166e-01 2.72747904e-01 -7.17508137e-01
-8.35444391e-01 -1.32370353e+00 2.17516994e+00 -6.89856231e-01
9.96666193e-01 -3.61533582e-01 -5.94948590e-01 9.58116770e-01
5.87398589e-01 1.99811935e-01 9.75269973e-01 3.42384160e-01
-4.30436373e-01 5.36764264e-01 -1.21894252e+00 1.92597076e-01
7.10706174e-01 -7.55889118e-01 -7.82166958e-01 4.92657155e-01
6.11226201e-01 -2.85311580e-01 -1.71853459e+00 9.08730328e-02
1.45822406e-01 -2.29753450e-01 5.68355799e-01 -1.44925642e+00
-3.85739803e-02 -2.57287592e-01 -1.71769008e-01 -1.45258784e+00
-8.15789104e-02 -3.93534392e-01 5.58013916e-01 2.10827994e+00
1.09735513e+00 -4.36853141e-01 2.34995022e-01 3.41296017e-01
-1.75896257e-01 3.77655365e-02 -1.29932296e+00 -8.29755247e-01
3.43520045e-01 -4.41657245e-01 4.29065198e-01 1.44015026e+00
-3.15415300e-02 8.05671275e-01 -3.59576046e-01 3.77140373e-01
2.99371034e-01 -4.06779528e-01 3.30474764e-01 -1.01413453e+00
7.99299479e-02 1.32962108e-01 -5.86672843e-01 -3.95701945e-01
6.47570193e-01 -1.02251816e+00 1.59956113e-01 -1.61683691e+00
7.00924844e-02 -4.69810218e-01 -4.58652258e-01 9.66842413e-01
-2.25133419e-01 9.85370204e-02 3.60383242e-01 5.01698554e-02
-1.10308290e+00 2.53449351e-01 4.91425753e-01 1.39135942e-01
5.53985201e-02 -2.95428604e-01 -3.22731286e-01 5.56621075e-01
3.23218912e-01 -1.12256181e+00 8.12279940e-01 -5.58218479e-01
2.74235606e-01 6.53481781e-02 -4.31918323e-01 -8.81864250e-01
3.48261535e-01 1.36488834e-02 3.99958432e-01 -5.75662315e-01
-3.96134704e-01 -7.39883184e-01 7.64792636e-02 2.70428777e-01
-3.94282669e-01 3.94052893e-01 1.16674580e-01 1.66463599e-01
-5.29923618e-01 -5.57368159e-01 6.71603441e-01 -3.55140001e-01
-1.14060509e+00 1.80763021e-01 -4.79357332e-01 8.31522763e-01
9.58602905e-01 5.01863182e-01 -2.53737688e-01 5.72676361e-01
-1.11303043e+00 2.24706739e-01 -1.92113101e-01 5.08750141e-01
-2.14428663e-01 -1.39264774e+00 -1.23887944e+00 -2.50345469e-01
3.75341117e-01 -6.37434185e-01 1.71283916e-01 5.81573129e-01
-5.80618799e-01 8.04116845e-01 -1.46237880e-01 3.01839709e-01
-9.67769384e-01 3.71734977e-01 1.90168381e-01 -1.11352265e+00
-1.60739601e-01 7.30578840e-01 -4.44608867e-01 -1.36553764e+00
-2.14192599e-01 2.96075493e-01 -7.65931427e-01 2.88422465e-01
4.67223555e-01 4.59408998e-01 4.13773715e-01 -1.23276436e+00
-9.24570322e-01 2.01876819e-01 -2.22383380e-01 -9.41008106e-02
1.40291810e+00 -1.57807738e-01 -3.90169442e-01 5.92228830e-01
1.53653491e+00 7.27849841e-01 9.32828858e-02 -2.11231813e-01
1.12343967e+00 5.51045358e-01 -4.63621646e-01 -1.17413568e+00
-6.94109321e-01 3.44851553e-01 3.80704641e-01 -6.04537092e-02
6.31012559e-01 -2.65526399e-02 9.13423002e-01 1.04454696e+00
7.62531936e-01 -1.43446565e+00 -8.85788321e-01 1.37843478e+00
4.54525828e-01 -1.30502141e+00 -4.39408630e-01 -1.37376012e-02
-9.74916101e-01 1.12334669e+00 4.02620316e-01 -6.06074743e-02
7.74624407e-01 3.81787062e-01 3.19261640e-01 -1.71405599e-01
-6.36645794e-01 -5.12993515e-01 3.85271549e-01 4.03321385e-01
1.09091544e+00 2.02248648e-01 -6.98436201e-01 9.33392048e-01
-1.72638506e-01 -1.85656264e-01 5.86103976e-01 1.17324972e+00
2.59120185e-02 -1.20854306e+00 -2.09379122e-01 7.50783905e-02
-1.28268027e+00 -7.70636618e-01 -3.30918521e-01 1.13727379e+00
2.64913887e-01 1.08742237e+00 -3.29935312e-01 1.87183067e-01
9.00309741e-01 2.70819008e-01 -1.45835727e-01 -8.96968305e-01
-1.28088534e+00 -2.94916302e-01 8.94711435e-01 -8.12657624e-02
-4.93605733e-01 -7.76316166e-01 -1.62565410e+00 7.54708797e-02
-3.74617815e-01 9.97934699e-01 8.13007355e-01 1.12150526e+00
5.20444512e-01 9.67673734e-02 7.76249945e-01 -1.69116721e-01
-3.51983249e-01 -1.16455352e+00 -9.12016690e-01 3.78323644e-01
-1.93542108e-01 2.10499894e-02 -2.00092375e-01 7.40065351e-02] | [9.84539794921875, 9.81165599822998] |
4f139ba0-5b43-417e-8677-95f16cd0c7be | activenet-a-computer-vision-based-approach-to | 2010.13714 | null | https://arxiv.org/abs/2010.13714v1 | https://arxiv.org/pdf/2010.13714v1.pdf | ActiveNet: A computer-vision based approach to determine lethargy | The outbreak of COVID-19 has forced everyone to stay indoors, fabricating a significant drop in physical activeness. Our work is constructed upon the idea to formulate a backbone mechanism, to detect levels of activeness in real-time, using a single monocular image of a target person. The scope can be generalized under many applications, be it in an interview, online classes, security surveillance, et cetera. We propose a Computer Vision based multi-stage approach, wherein the pose of a person is first detected, encoded with a novel approach, and then assessed by a classical machine learning algorithm to determine the level of activeness. An alerting system is wrapped around the approach to provide a solution to inhibit lethargy by sending notification alerts to individuals involved. | ['Aadit Agarwal', 'Aitik Gupta'] | 2020-10-26 | null | null | null | null | ['activeness-detection'] | ['computer-vision'] | [ 4.94522095e-01 1.84858248e-01 1.36900678e-01 -2.66244680e-01
1.47971064e-01 -7.87698627e-01 5.55615127e-01 2.74892479e-01
-6.43024623e-01 6.23254240e-01 -4.10216749e-02 -1.00758284e-01
-3.50191861e-01 -7.95334637e-01 -7.66581818e-02 -7.38989532e-01
-2.35401854e-01 4.21273977e-01 6.12912253e-02 -1.02630325e-01
2.14777306e-01 8.68979931e-01 -1.37804520e+00 3.12019698e-02
4.92682725e-01 6.02334380e-01 -6.19027577e-03 8.68024230e-01
4.57732767e-01 7.94695616e-01 -9.01560903e-01 -1.37026027e-01
2.63849199e-01 -2.84126371e-01 -6.89162850e-01 3.69348526e-01
3.42301056e-02 -8.33861709e-01 1.11732930e-01 6.20325208e-01
4.24858868e-01 -1.20939448e-01 5.86458206e-01 -1.41808426e+00
6.63060322e-02 -5.74080981e-02 -2.23296106e-01 3.91900271e-01
1.14442194e+00 2.52009720e-01 2.07114786e-01 -4.40062076e-01
4.68360722e-01 1.18306351e+00 6.37957215e-01 6.22577548e-01
-1.17610192e+00 -3.33646744e-01 2.45025367e-01 2.31900156e-01
-1.42040050e+00 -1.49657473e-01 7.13218331e-01 -5.31808794e-01
6.84029818e-01 6.09813750e-01 9.46011722e-01 1.31582570e+00
-5.66573329e-02 2.35359579e-01 1.28090799e+00 -2.60109901e-01
4.44297254e-01 5.06780863e-01 1.74146816e-01 6.24621212e-01
7.01210320e-01 -4.41669300e-02 -2.92888731e-01 -5.53820252e-01
5.40121317e-01 6.58991575e-01 -1.71071187e-01 -1.96019188e-01
-8.53931069e-01 6.91987991e-01 1.98928714e-01 4.47273165e-01
-8.46037447e-01 -4.13585335e-01 1.25322670e-01 4.23473746e-01
5.13266802e-01 3.95668268e-01 -4.05347794e-01 -6.82193935e-02
-5.67161918e-01 4.28297460e-01 8.45547140e-01 1.91335976e-02
7.74900496e-01 -4.91711974e-01 -1.81630537e-01 6.33007362e-02
4.66835320e-01 5.77971756e-01 -5.29715754e-02 -8.64155471e-01
1.57421738e-01 1.05486417e+00 4.67828184e-01 -1.32298148e+00
-7.46988058e-01 -7.37213716e-02 -5.09372771e-01 3.69565606e-01
8.25899914e-02 -7.93181241e-01 -3.03306043e-01 1.50685656e+00
8.77063215e-01 -4.41798614e-03 -2.42240593e-01 7.73687124e-01
3.39017063e-01 5.08193254e-01 -2.73040216e-02 -5.29965341e-01
1.37873816e+00 -2.10835874e-01 -7.56229341e-01 -2.13771462e-01
2.97885418e-01 -3.71497035e-01 3.52336913e-01 7.93919265e-01
-6.18255019e-01 -4.04296756e-01 -7.61433065e-01 7.63328433e-01
-6.69708014e-01 -1.60203487e-01 2.40809619e-01 1.09409225e+00
-1.12364101e+00 4.54879850e-01 -5.63410521e-01 -1.17073429e+00
-1.05689093e-01 4.01746303e-01 -3.21528286e-01 8.86887759e-02
-9.37181711e-01 1.08794534e+00 2.80130446e-01 2.95825928e-01
-7.31514573e-01 -2.41093472e-01 -7.63938725e-01 -4.76484865e-01
3.35394800e-01 -7.67742276e-01 7.54510045e-01 -7.72269905e-01
-1.16178048e+00 1.12353027e+00 5.61374724e-02 -4.24896687e-01
8.09849918e-01 -2.44789153e-01 -4.58703548e-01 4.49012071e-01
5.07093929e-02 4.81922388e-01 9.75611627e-01 -1.22189307e+00
-4.68914568e-01 -8.43791723e-01 3.46868008e-01 2.21173495e-01
-4.98448104e-01 4.89632517e-01 2.10679933e-01 -5.65542802e-02
-2.29565829e-01 -7.95403600e-01 -3.08336884e-01 8.57791752e-02
-2.74970025e-01 -1.13527440e-01 1.13333786e+00 -6.84269309e-01
1.02107525e+00 -1.84313464e+00 -1.47082850e-01 3.26966673e-01
2.50089586e-01 5.74736953e-01 1.04823872e-01 7.44346976e-01
1.87706560e-01 -2.80936569e-01 -7.65935034e-02 -2.30857536e-01
-1.39911816e-01 1.96400404e-01 -1.67419359e-01 7.97183096e-01
2.05758005e-01 3.57282221e-01 -9.22107577e-01 -4.30915922e-01
5.61217964e-01 4.37093914e-01 -3.11955959e-01 6.96513593e-01
2.38264173e-01 5.57282567e-01 -5.92594504e-01 6.85215712e-01
8.24463785e-01 2.49156039e-02 2.60675609e-01 3.81422490e-01
-3.35038215e-01 -1.16680540e-01 -1.10023880e+00 8.74640167e-01
1.01117425e-01 1.56004757e-01 5.81691086e-01 -9.51704383e-01
7.97259510e-01 5.17045438e-01 7.93174207e-01 -2.83426493e-01
2.74737358e-01 -3.07748258e-01 -5.00262022e-01 -9.72033620e-01
2.60218799e-01 3.52049530e-01 -1.45474806e-01 5.05440891e-01
-6.02106571e-01 1.91239595e-01 1.13087907e-01 1.32040596e-02
1.37273395e+00 4.63896990e-02 5.91180444e-01 1.03357680e-01
5.92016339e-01 1.62574098e-01 1.65183902e-01 7.49289513e-01
-6.59181535e-01 9.04274210e-02 1.68068439e-01 -8.54923904e-01
-5.27616203e-01 -1.09604204e+00 7.81082138e-02 8.91208887e-01
8.27411339e-02 -5.45674525e-02 -1.17540467e+00 -5.75075388e-01
-7.97095373e-02 2.87501961e-01 -7.25485384e-01 -1.35200873e-01
-4.81469840e-01 -8.24903488e-01 3.51965845e-01 -3.97634245e-02
6.08836472e-01 -1.06309128e+00 -1.65094519e+00 1.30630434e-01
-1.85827598e-01 -9.74780679e-01 1.39817923e-01 9.44322646e-02
-6.51644826e-01 -1.08149135e+00 -6.42626345e-01 -3.09653401e-01
8.07266176e-01 3.07237059e-01 7.35965073e-01 3.46226811e-01
-5.62334836e-01 8.50834608e-01 -3.77673268e-01 -6.42156541e-01
-8.31888989e-02 -2.21645266e-01 4.86369938e-01 3.79763722e-01
5.61348021e-01 -3.78268450e-01 -7.59910464e-01 2.18113869e-01
-6.50060415e-01 -3.52575511e-01 3.71555805e-01 2.92996150e-02
-1.08773991e-01 -1.94049120e-01 2.95747817e-01 -5.59632242e-01
7.40950286e-01 -6.54593945e-01 -4.76817459e-01 8.66562203e-02
-3.28939795e-01 -6.84473574e-01 4.53308105e-01 -3.91599983e-01
-6.64556682e-01 1.98309556e-01 7.78380558e-02 -1.68614592e-02
-7.73384035e-01 -6.81728870e-02 6.98506534e-02 -1.45825356e-01
6.27647698e-01 1.36479169e-01 -2.59474684e-02 -2.17591077e-01
-7.35258386e-02 9.10350144e-01 4.41257924e-01 7.41085857e-02
1.12531495e+00 6.03704810e-01 -9.03095752e-02 -1.10404217e+00
-6.13057137e-01 -8.30358863e-01 -7.45995700e-01 -7.73764312e-01
1.01709843e+00 -6.60667300e-01 -1.38770318e+00 5.41774213e-01
-1.47173965e+00 -9.04366001e-02 2.03070611e-01 3.15169215e-01
-2.52617329e-01 2.84445465e-01 -2.80807048e-01 -1.39409864e+00
-3.23556811e-01 -3.50095779e-01 1.07866347e+00 2.19317570e-01
-5.59380174e-01 -9.02161896e-01 7.17383862e-01 6.31910503e-01
3.77838463e-01 6.63678825e-01 1.31639913e-01 -6.94636583e-01
-3.25916797e-01 -3.07998002e-01 -7.38825696e-03 1.73426010e-02
4.10722852e-01 -9.40750837e-02 -1.17841601e+00 -4.88125950e-01
3.23525816e-01 -3.89748394e-01 2.40497053e-01 1.86432321e-02
6.41080320e-01 -6.36719704e-01 -5.29840410e-01 2.54634708e-01
1.05819571e+00 5.29860377e-01 4.05028105e-01 1.77019909e-01
1.61849767e-01 9.42795932e-01 6.28000915e-01 8.29432547e-01
2.33146429e-01 7.32196271e-01 7.38587558e-01 -4.25949872e-01
5.77021837e-01 1.16481490e-01 6.00632370e-01 8.87116268e-02
-3.80268931e-01 -2.17458993e-01 -7.74100661e-01 2.16481298e-01
-1.68884158e+00 -1.25347447e+00 6.48030937e-02 2.03226471e+00
3.56287837e-01 -1.01324702e-02 6.09619021e-01 4.78774548e-01
7.30581820e-01 -1.07824907e-01 -2.03607529e-01 -5.55792093e-01
4.89448160e-01 -3.23388100e-01 2.77427942e-01 4.62753117e-01
-1.18666601e+00 2.59102285e-01 7.37827635e+00 -1.72739416e-01
-1.11497319e+00 5.09385504e-02 4.83949453e-01 3.93567123e-02
3.34801227e-01 -4.09453273e-01 -7.03434348e-01 4.56554741e-01
8.79981697e-01 1.85289547e-01 5.55642068e-01 6.97427452e-01
6.57573700e-01 -4.74883080e-01 -9.08151865e-01 7.63986886e-01
4.18070585e-01 -6.29070878e-01 -3.11549991e-01 2.04198226e-01
1.95395321e-01 -3.57252955e-01 -1.77643314e-01 1.73929855e-02
-9.57008377e-02 -6.86772287e-01 3.54179144e-01 5.14665425e-01
2.46244147e-01 -6.74080908e-01 6.43797457e-01 7.97260046e-01
-1.14682400e+00 -2.23183259e-01 8.41057766e-03 -6.84731305e-01
1.53743401e-01 2.64123797e-01 -1.31526589e+00 3.75113398e-01
6.57101750e-01 6.13645650e-04 -4.97776031e-01 1.02347827e+00
-1.67743172e-02 2.39962131e-01 -2.84100980e-01 -4.99704391e-01
1.63016096e-01 -2.52967268e-01 7.43240714e-01 1.20610178e+00
-1.21494077e-01 3.11973482e-01 4.72805649e-01 7.43140519e-01
6.36692703e-01 -1.74801305e-01 -1.10603559e+00 2.92533994e-01
1.58884525e-01 1.31387973e+00 -7.87469387e-01 -2.25502446e-01
-6.00208752e-02 1.23284233e+00 -5.54875955e-02 2.90443212e-01
-7.66586125e-01 -3.77178282e-01 3.69667083e-01 3.70091140e-01
6.41288608e-02 -1.13283843e-01 1.26958236e-01 -8.18755150e-01
8.13881159e-02 -7.62148917e-01 4.43615496e-01 -6.41324997e-01
-8.18613350e-01 6.15349174e-01 3.39688182e-01 -1.00814295e+00
-5.71953177e-01 -6.32691085e-01 -8.34313691e-01 4.52438027e-01
-1.05462193e+00 -8.12519431e-01 -6.43005252e-01 1.01551139e+00
2.39118770e-01 1.27066404e-01 9.79542971e-01 3.02964121e-01
-6.49308801e-01 7.20385388e-02 -6.00487113e-01 3.92975323e-02
4.44803804e-01 -9.85679328e-01 -6.78747967e-02 9.68915164e-01
-3.66936356e-01 7.36339152e-01 9.27598774e-01 -9.24761355e-01
-1.47785723e+00 -1.05227840e+00 1.10226965e+00 -7.40597665e-01
3.77882510e-01 -5.43668687e-01 -4.57901835e-01 5.05009592e-01
3.21838409e-01 -3.90655488e-01 4.52848613e-01 -8.52013528e-02
1.42715305e-01 -2.00061500e-01 -1.74627256e+00 5.48166215e-01
8.62001956e-01 -3.37409347e-01 -7.67783642e-01 4.44776744e-01
4.05477464e-01 2.19531544e-02 -4.05997843e-01 1.94766939e-01
3.78293037e-01 -1.16899741e+00 9.15350318e-01 -3.87539804e-01
-3.55660349e-01 -1.73196524e-01 2.14801699e-01 -8.94372404e-01
-2.15070501e-01 -1.03275239e+00 5.13170939e-03 9.57742631e-01
-3.81512307e-02 -7.98104405e-01 7.15714514e-01 5.36997259e-01
4.91293013e-01 -4.23235893e-01 -1.00274849e+00 -4.79197234e-01
-9.14895952e-01 -5.20614870e-02 1.77547932e-01 8.04962516e-01
9.84645411e-02 2.53771752e-01 -6.07949674e-01 4.61550504e-01
6.67690635e-01 -2.48117864e-01 8.18269253e-01 -1.51666081e+00
-1.25736967e-01 2.20769912e-01 -5.82556546e-01 -3.45472932e-01
-4.98194069e-01 -9.88771468e-02 -1.43463165e-01 -1.40500665e+00
2.73936540e-01 2.08106369e-01 1.19208684e-02 4.71955210e-01
1.17654175e-01 3.01939219e-01 1.05068251e-01 -1.83826372e-01
-7.28884637e-01 -1.41912594e-01 6.13152862e-01 1.11929506e-01
-3.02103102e-01 3.36486250e-01 -4.08028126e-01 9.51731265e-01
7.95364201e-01 -5.05366683e-01 -3.51351976e-01 3.23019139e-02
3.61295879e-01 1.09356202e-01 8.05067956e-01 -1.35741675e+00
2.53670037e-01 -4.45737273e-01 5.93290091e-01 -7.84621060e-01
6.40745223e-01 -1.32082665e+00 2.24860057e-01 1.42349577e+00
9.00791362e-02 3.35684568e-01 -1.06951460e-01 4.85867888e-01
3.86744499e-01 -1.30413741e-01 6.39975369e-01 -1.91807181e-01
-3.01720589e-01 7.01292530e-02 -9.43955898e-01 -4.47520882e-01
1.43989277e+00 -4.90255088e-01 -2.98583329e-01 -1.70776859e-01
-5.28196096e-01 1.17542557e-01 3.53436619e-01 1.15945138e-01
5.76536953e-01 -8.76921058e-01 -5.38028359e-01 3.81279528e-01
4.45328951e-02 -6.85560882e-01 6.72356784e-02 8.86333346e-01
-6.67120814e-01 4.07170504e-01 -5.28802812e-01 -6.27704144e-01
-1.69245350e+00 9.05789137e-01 3.18580300e-01 -2.55802631e-01
-2.69067198e-01 3.68495315e-01 -2.16532737e-01 -2.89148301e-01
4.99551505e-01 -2.42431294e-02 -5.76372921e-01 2.92255878e-01
9.26879287e-01 7.40062058e-01 -4.11559679e-02 -5.28904259e-01
-7.87135184e-01 6.56078994e-01 2.73479551e-01 -1.83699697e-01
1.13618577e+00 -2.53177971e-01 -2.01675206e-01 2.44759858e-01
8.40249181e-01 6.17163926e-02 -1.10093617e+00 1.54697374e-01
-1.42587990e-01 -3.83171320e-01 -4.22365695e-01 -7.12034106e-01
-3.95751208e-01 3.87416601e-01 1.02194726e+00 7.61010587e-01
1.21346617e+00 -4.71665785e-02 3.24902803e-01 9.59289193e-01
6.87042713e-01 -9.76652145e-01 2.73747504e-01 1.04401506e-01
6.17437363e-01 -1.28316021e+00 -1.01008989e-01 -2.69413948e-01
-3.32582653e-01 8.74498367e-01 3.95170867e-01 -5.31495027e-02
3.76051158e-01 4.58586484e-01 8.06168392e-02 -4.55451250e-01
-6.24564230e-01 -1.75029144e-01 -1.96555972e-01 1.09135342e+00
-1.47222474e-01 7.80661628e-02 -2.20546246e-01 1.65552013e-02
2.22282723e-01 1.70415610e-01 4.34748501e-01 1.07472110e+00
-8.80090058e-01 -7.58899629e-01 -1.07476902e+00 -1.70178013e-03
-3.45830858e-01 4.32015181e-01 -1.11907363e+00 6.06617332e-01
6.27577960e-01 1.43683696e+00 2.00564936e-01 -3.35644275e-01
4.51511323e-01 -1.65192798e-01 2.51799852e-01 -4.84489202e-01
-9.27271605e-01 -1.85105816e-01 1.31421372e-01 -5.42639136e-01
-7.07741678e-01 -6.57015800e-01 -6.18302345e-01 -4.55005497e-01
3.17550868e-01 4.08657826e-02 4.34521258e-01 9.69544411e-01
-1.44081727e-01 -3.21177915e-02 1.12618315e+00 -8.51860344e-01
-3.44790936e-01 -7.24382520e-01 -3.13026905e-01 2.64776170e-01
7.22988546e-01 -4.03635979e-01 -3.95505607e-01 -1.75191402e-01] | [8.523344993591309, -0.6538624167442322] |
ccc29c36-b963-4c41-9739-4e0a64fe922a | prompt-based-zero-shot-relation-1 | null | null | https://openreview.net/forum?id=OULoKDV7CO | https://openreview.net/pdf?id=OULoKDV7CO | Prompt-based Zero-shot Relation Classification with Semantic Knowledge Augmentation | In relation classification, recognizing unseen (new) relations for which there are no training instances is a challenging task. We propose a prompt-based model with semantic knowledge augmentation (ZS-SKA) to recognize unseen relations under the zero-shot setting. We present a new word-level sentence translation rule and generate augmented instances with unseen relations from instances with seen relations using that new rule. We design prompts based on an external knowledge graph to integrate semantic knowledge information learned from seen relations. Instead of using the actual label sets in the prompt template, we construct weighted virtual label words. We learn the representations of both seen and unseen relations with augmented instances and prompts. We then calculate the distance between the generated representations using prototypical networks to predict unseen relations. Extensive experiments conducted on three public datasets show that ZS-SKA outperforms state-of-the-art methods under the zero-shot scenarios. Our experimental results also demonstrate the effectiveness and robustness of ZS-SKA. | ['Anonymous'] | 2022-01-16 | null | null | null | acl-arr-january-2022-1 | ['relation-classification'] | ['natural-language-processing'] | [ 5.67884326e-01 1.02844691e+00 -3.94274294e-01 -6.02401555e-01
-5.89306474e-01 -4.10740525e-01 7.43305087e-01 -1.79999415e-02
-6.32164925e-02 9.40866053e-01 3.07646424e-01 -3.71175855e-01
-2.48622403e-01 -1.15262079e+00 -6.63624585e-01 -2.33285055e-01
3.12980026e-01 9.82006073e-01 1.07445531e-01 -6.70919657e-01
-3.37526739e-01 2.82140225e-01 -1.32282948e+00 5.83809257e-01
9.21565235e-01 8.20008993e-01 -2.20194027e-01 3.21196765e-01
-3.49195570e-01 1.01509619e+00 -7.71340489e-01 -7.60970592e-01
3.05077493e-01 -5.53497970e-01 -1.53893578e+00 5.47113605e-02
1.18996687e-01 -4.27592453e-03 -6.82371914e-01 7.72420049e-01
2.51067877e-01 7.81075776e-01 6.96472347e-01 -1.26812041e+00
-1.48628247e+00 7.92328477e-01 -4.63865884e-02 3.07557553e-01
7.37855494e-01 -3.40470552e-01 1.17016673e+00 -1.13044477e+00
1.09720242e+00 1.30340421e+00 2.25556925e-01 8.19498301e-01
-1.35798979e+00 -6.71737731e-01 3.38425249e-01 6.57779157e-01
-1.40353644e+00 -5.56535482e-01 6.84208393e-01 -6.43799901e-02
1.54393911e+00 4.91229951e-01 1.79129347e-01 1.43821979e+00
-3.29705149e-01 4.68954653e-01 8.80441904e-01 -8.39412391e-01
1.68861106e-01 1.92502916e-01 5.82688510e-01 3.97588193e-01
2.32052132e-01 2.01932602e-02 -6.66120350e-01 -1.24712557e-01
4.88864005e-01 -1.42897457e-01 -3.75216842e-01 -2.76333451e-01
-1.15262413e+00 5.28952897e-01 6.27533197e-01 3.71520251e-01
-1.69375896e-01 -3.80947351e-01 1.77979887e-01 6.97884083e-01
7.34242022e-01 8.48671615e-01 -7.85640776e-01 3.02602947e-01
2.82599218e-02 -5.09006418e-02 1.07701039e+00 1.54417896e+00
8.94321859e-01 -3.62412184e-01 -5.62660635e-01 1.06989026e+00
-2.98106104e-01 2.48541832e-01 4.87750560e-01 -5.93906045e-01
6.88652277e-01 1.10070348e+00 5.60192578e-03 -7.98002779e-01
-3.35420251e-01 -5.29273331e-01 -7.42878735e-01 -4.94177014e-01
5.60826845e-02 -1.08814597e-01 -1.01162159e+00 1.78280485e+00
4.74440187e-01 6.40344501e-01 8.87022138e-01 6.95867896e-01
1.38823366e+00 5.03733397e-01 5.74622974e-02 -3.45241517e-01
1.33777738e+00 -1.24652207e+00 -9.92867470e-01 -5.19565582e-01
1.11005461e+00 -2.68635958e-01 9.36320484e-01 -2.55918026e-01
-4.14397746e-01 -5.64286530e-01 -1.02432132e+00 -2.44728908e-01
-8.01783204e-01 -2.34282807e-01 7.87672579e-01 1.68235227e-01
-6.92176998e-01 5.43268144e-01 -3.43142778e-01 -6.61104560e-01
3.17964375e-01 2.86949188e-01 -5.64320445e-01 -2.94409126e-01
-1.75126731e+00 1.26136243e+00 8.01982582e-01 -1.37852896e-02
-5.83947957e-01 -6.48555636e-01 -1.33475292e+00 1.72705784e-01
1.20668018e+00 -7.29924440e-01 1.16694951e+00 -5.03037274e-01
-1.14543056e+00 9.94561791e-01 -4.45076764e-01 -2.87659168e-01
-1.07872777e-01 -2.10481256e-01 -8.01165402e-01 -8.32963213e-02
2.61337012e-01 3.55345428e-01 2.55408108e-01 -1.55128455e+00
-3.55430037e-01 -2.01382920e-01 3.20951074e-01 4.56939012e-01
-3.88318956e-01 -1.06004439e-01 2.04191301e-02 -5.10320008e-01
3.99138659e-01 -6.07749045e-01 -1.32567268e-02 -5.85680962e-01
-6.98700309e-01 -7.81692684e-01 6.78270459e-01 -3.64600748e-01
1.02915406e+00 -1.82442772e+00 8.78667608e-02 1.48030922e-01
3.32372427e-01 4.06617045e-01 -6.57196403e-01 4.13862318e-01
-4.86493081e-01 -2.85953116e-02 4.67731580e-02 1.55757666e-01
-2.64089346e-01 6.77710772e-01 -4.67319578e-01 -4.34123158e-01
5.84157765e-01 1.38983142e+00 -1.52764380e+00 -2.10532010e-01
-2.30568834e-02 1.23265721e-01 1.70716152e-01 6.55798554e-01
-1.49877861e-01 2.23130509e-01 -4.38899487e-01 4.70651031e-01
2.68989116e-01 -6.41542017e-01 5.64567506e-01 -1.94746643e-01
8.93441916e-01 5.29978514e-01 -7.77137220e-01 1.70079541e+00
-4.76381212e-01 1.64357096e-01 -8.69354844e-01 -1.07713044e+00
1.47322905e+00 4.99405950e-01 -1.25844792e-01 -6.22814894e-01
1.96363360e-01 9.54349488e-02 7.27769881e-02 -7.78829873e-01
4.05955344e-01 -4.34356302e-01 5.70394006e-03 2.45061114e-01
6.75079048e-01 1.04717232e-01 1.42609954e-01 5.82459092e-01
1.55888546e+00 2.24724188e-01 6.58218682e-01 1.34353265e-01
3.76630425e-01 -1.08838342e-02 7.14824975e-01 7.76970983e-01
4.27737683e-02 4.21716779e-01 5.63483477e-01 -4.95554239e-01
-4.91625041e-01 -1.14533949e+00 1.84833765e-01 1.20455897e+00
4.35223252e-01 -5.26295483e-01 -2.30558500e-01 -1.33512807e+00
-1.65353298e-01 1.09200978e+00 -7.49004066e-01 -7.55546033e-01
-2.91124493e-01 -4.58766580e-01 1.51052490e-01 6.75752461e-01
2.73270518e-01 -1.36721897e+00 1.60641223e-01 3.15284550e-01
-4.88243580e-01 -1.59417129e+00 -9.11429301e-02 3.97448838e-01
-3.90108466e-01 -1.17871130e+00 -1.91431925e-01 -1.11978841e+00
1.01495695e+00 3.85928601e-01 1.35953164e+00 7.34439353e-03
-1.73873976e-02 7.16500357e-02 -1.00546372e+00 -1.18290313e-01
-4.75908726e-01 3.18251729e-01 9.27019417e-02 6.60940111e-02
9.67900634e-01 -6.13385260e-01 -6.67566955e-02 2.52608150e-01
-6.53269649e-01 1.78905576e-01 3.59053433e-01 1.13411200e+00
3.41104209e-01 -1.67488039e-01 1.13067949e+00 -1.53674674e+00
7.75488615e-01 -7.21118212e-01 1.11420648e-02 8.91062140e-01
-6.40153408e-01 2.59773999e-01 5.56403458e-01 -5.89339375e-01
-1.32922781e+00 -7.33200759e-02 3.59241813e-01 -3.85160863e-01
-3.35049480e-01 4.69110489e-01 -3.73146683e-01 3.27420622e-01
1.12738681e+00 -1.60425454e-01 -4.44835424e-01 -2.50674486e-01
8.72869611e-01 8.42344284e-01 8.09851408e-01 -8.50697041e-01
8.70254159e-01 1.32226810e-01 -7.40103647e-02 -3.00585747e-01
-1.82554257e+00 -4.69855845e-01 -7.44603634e-01 7.83424154e-02
7.16942191e-01 -7.14008927e-01 -3.52212161e-01 -1.10932082e-01
-1.47178948e+00 -2.22236320e-01 -7.88465321e-01 1.68472171e-01
-3.43698949e-01 -3.88968252e-02 -6.11790955e-01 -8.39252651e-01
-3.80829453e-01 -5.63563406e-01 8.97703946e-01 3.18909973e-01
-5.67171156e-01 -9.79239345e-01 -1.34268673e-02 5.78824401e-01
-4.34528068e-02 2.06536993e-01 1.21783781e+00 -1.54260063e+00
-2.80974627e-01 -2.42344141e-01 -4.39209223e-01 2.91864336e-01
5.59397876e-01 -7.67853260e-01 -1.15616953e+00 1.87349379e-01
-2.16032878e-01 -7.07088053e-01 5.39162636e-01 -4.38004702e-01
7.46615827e-01 -3.60036552e-01 -5.65475106e-01 2.19557837e-01
9.59463418e-01 3.06915849e-01 6.01189673e-01 5.89335300e-02
9.15363014e-01 9.01868999e-01 9.28941369e-01 -5.31055480e-02
4.47306186e-01 5.28003454e-01 -2.53976695e-02 3.84694263e-02
-3.16598237e-01 -5.17638922e-01 -9.87529531e-02 9.37433422e-01
-1.20203562e-01 -3.69838238e-01 -8.78824532e-01 6.82957172e-01
-2.06966710e+00 -7.43888795e-01 -8.59678909e-03 1.87100530e+00
1.14040375e+00 5.85742556e-02 -6.19309545e-01 1.34675875e-02
8.96570265e-01 -9.31018889e-02 -5.69780648e-01 -4.13456589e-01
-3.05883825e-01 7.82314837e-01 -2.03362748e-01 7.29363263e-01
-9.24066126e-01 1.57762063e+00 5.46224499e+00 7.40863204e-01
-2.18287766e-01 2.17441171e-01 6.48609459e-01 1.51888296e-01
-2.95481890e-01 2.74911016e-01 -7.12270558e-01 -2.94663817e-01
7.84142077e-01 -3.81619990e-01 3.84317517e-01 8.18525791e-01
-4.34971541e-01 2.63373733e-01 -1.58564889e+00 7.85714805e-01
3.70345533e-01 -1.26447582e+00 3.02370846e-01 -3.20302904e-01
8.78831983e-01 -4.55746293e-01 -4.29296494e-01 8.50712240e-01
6.40787840e-01 -9.77794409e-01 -9.91315767e-02 4.28166747e-01
9.53660250e-01 -3.89598608e-01 1.04764640e+00 1.60157785e-01
-1.03177321e+00 1.28764346e-01 -4.75598216e-01 -4.16457236e-01
4.73865159e-02 4.93373483e-01 -1.14023972e+00 1.10934460e+00
2.20194548e-01 7.81254232e-01 -4.90588874e-01 1.81381747e-01
-9.67471957e-01 2.70110130e-01 4.02328148e-02 4.28964011e-02
-2.26866603e-01 1.69718789e-03 1.89710170e-01 7.44399071e-01
1.46782055e-01 7.43804336e-01 1.51563093e-01 7.97868848e-01
-5.05144179e-01 1.25586554e-01 -8.69017363e-01 5.00945747e-02
9.23613906e-01 1.35770118e+00 -4.80992705e-01 -7.41781652e-01
-5.49530089e-01 1.20534015e+00 9.96186495e-01 6.96679771e-01
-3.13535988e-01 -5.21106720e-01 5.14873207e-01 -3.41277093e-01
-1.31454542e-01 3.89301628e-01 -4.60343063e-02 -1.39854681e+00
1.56158835e-01 -5.87836027e-01 6.18430018e-01 -1.06438160e+00
-1.87876296e+00 9.45864081e-01 3.33143137e-02 -8.91900420e-01
-2.53914446e-01 -4.99294400e-01 -3.48279893e-01 8.60048652e-01
-1.33157873e+00 -1.17124367e+00 -4.69919980e-01 3.27076048e-01
5.64721048e-01 -2.32039347e-01 1.42442071e+00 -4.46615331e-02
-5.89192033e-01 7.18751073e-01 -4.92355466e-01 4.89050865e-01
6.97242498e-01 -1.12834704e+00 6.95682645e-01 6.48995161e-01
5.06129205e-01 5.01248062e-01 5.10870099e-01 -1.00165415e+00
-8.06132853e-01 -1.25388396e+00 1.44536602e+00 -7.62367189e-01
7.63850629e-01 -4.74269927e-01 -1.17606068e+00 1.19616950e+00
2.39082113e-01 4.12242800e-01 9.66069102e-01 6.02030516e-01
-8.31929147e-01 -1.07134366e-02 -9.98191893e-01 6.39063656e-01
1.77851605e+00 -5.32867968e-01 -1.40518534e+00 6.53679430e-01
1.30518436e+00 -4.49063808e-01 -9.16081786e-01 7.66190171e-01
5.64085878e-02 -2.29184911e-01 7.89484918e-01 -1.45020151e+00
4.96807218e-01 -5.68296909e-02 -8.43849778e-02 -1.62435126e+00
-4.67093319e-01 -5.13966024e-01 -6.61720395e-01 1.38823652e+00
8.53167772e-01 -7.81929910e-01 7.38234699e-01 8.57569218e-01
-8.54969397e-02 -9.39967990e-01 -8.71618986e-01 -1.25669479e+00
-2.86396623e-01 -4.35276218e-02 9.34863925e-01 1.45770359e+00
5.76207757e-01 1.29724574e+00 -1.57921150e-01 1.78698540e-01
2.46533737e-01 1.82623312e-01 5.62683880e-01 -1.24752760e+00
-3.24846089e-01 2.72406518e-01 -5.91927111e-01 -6.77054584e-01
6.95600092e-01 -1.30400741e+00 -4.57884930e-02 -1.70579767e+00
4.82545584e-01 -4.19198185e-01 -5.98670244e-01 9.99537051e-01
-8.16665471e-01 6.41544536e-02 -1.42466053e-01 -1.74147889e-01
-6.42982066e-01 6.67638779e-01 1.33159292e+00 -1.38916358e-01
-1.69993699e-01 -4.21224743e-01 -9.54597533e-01 4.44114864e-01
7.81644166e-01 -5.52397549e-01 -8.99732411e-01 -3.50405723e-01
2.09250227e-01 -1.09819442e-01 7.78056756e-02 -6.68695986e-01
-2.39715036e-02 -3.05749178e-01 1.24498084e-01 -6.58016428e-02
5.16575456e-01 -6.72781408e-01 -1.33881092e-01 -1.58886351e-02
-8.45888197e-01 -3.93549383e-01 -2.37811953e-01 7.02366292e-01
-7.82716721e-02 -1.64091021e-01 1.67133719e-01 7.57988915e-02
-7.66123533e-01 1.02597602e-01 2.95485228e-01 4.35781687e-01
1.20038283e+00 1.30530968e-01 -9.16678905e-01 -3.70817780e-01
-1.23877633e+00 3.09198827e-01 -8.46258849e-02 8.74367952e-01
8.29318583e-01 -1.62203419e+00 -6.46908164e-01 2.96908785e-02
9.16252911e-01 2.93527901e-01 4.29729633e-02 1.79019421e-01
1.46286771e-01 1.83411852e-01 2.65558302e-01 8.66061375e-02
-1.17266941e+00 1.07331431e+00 9.38162059e-02 -4.04295743e-01
-6.61386847e-01 1.06490862e+00 2.82735556e-01 -7.38109291e-01
5.45211136e-03 -1.17312983e-01 -2.39795685e-01 -1.71381384e-01
4.84802663e-01 -7.19539262e-03 1.55665934e-01 -4.62993085e-01
-2.80354172e-01 1.55458748e-01 -4.68119532e-01 3.83523665e-02
1.21336877e+00 1.43810004e-01 -8.19279999e-02 5.49655616e-01
9.17033553e-01 -5.34646809e-01 -5.79133451e-01 -9.36103404e-01
4.02447253e-01 -3.89951319e-01 -5.98223746e-01 -1.10443294e+00
-7.49370277e-01 4.44091618e-01 -1.15770753e-02 7.73374364e-02
8.78555238e-01 6.68297529e-01 8.04967105e-01 8.41429293e-01
5.22594035e-01 -8.89310658e-01 2.40859166e-01 6.65575325e-01
9.22710717e-01 -1.25447786e+00 -3.43171895e-01 -1.41718519e+00
-6.90578282e-01 7.47076750e-01 1.25697565e+00 5.15553802e-02
2.68028051e-01 6.46306053e-02 3.50035876e-01 -2.54566699e-01
-1.02057481e+00 -5.99080145e-01 3.29560280e-01 1.05279541e+00
3.33500654e-01 2.28075087e-01 -2.73169339e-01 9.40874100e-01
-2.15988904e-01 -1.87499210e-01 3.55558127e-01 1.04482520e+00
-2.46858075e-01 -1.36698818e+00 3.37018482e-02 7.38904655e-01
2.45400831e-01 -4.02534634e-01 -8.81357253e-01 3.92103463e-01
1.28747597e-01 1.44014347e+00 -2.05537468e-01 -8.72757494e-01
5.66924512e-01 7.36075163e-01 5.25434077e-01 -1.47478247e+00
-4.30352569e-01 -7.56633222e-01 7.34881520e-01 -3.55385453e-01
-1.80714458e-01 -5.61053269e-02 -1.37823522e+00 1.74934298e-01
-7.21200943e-01 3.15504700e-01 -1.13236919e-01 1.33862615e+00
5.47109425e-01 9.78634715e-01 5.13485491e-01 -1.27630055e-01
-4.94797647e-01 -1.24757171e+00 -3.95068467e-01 1.02858055e+00
-1.32355258e-01 -9.29057002e-01 -1.93421572e-01 -6.23202398e-02] | [9.296186447143555, 8.48508071899414] |
c0a9c6dd-da37-41de-a945-555f7a5efb44 | relational-learning-for-joint-head-and-human | 1909.10674 | null | https://arxiv.org/abs/1909.10674v1 | https://arxiv.org/pdf/1909.10674v1.pdf | Relational Learning for Joint Head and Human Detection | Head and human detection have been rapidly improved with the development of deep convolutional neural networks. However, these two tasks are often studied separately without considering their inherent correlation, leading to that 1) head detection is often trapped in more false positives, and 2) the performance of human detector frequently drops dramatically in crowd scenes. To handle these two issues, we present a novel joint head and human detection network, namely JointDet, which effectively detects head and human body simultaneously. Moreover, we design a head-body relationship discriminating module to perform relational learning between heads and human bodies, and leverage this learned relationship to regain the suppressed human detections and reduce head false positives. To verify the effectiveness of the proposed method, we annotate head bounding boxes of the CityPersons and Caltech-USA datasets, and conduct extensive experiments on the CrowdHuman, CityPersons and Caltech-USA datasets. As a consequence, the proposed JointDet detector achieves state-of-the-art performance on these three benchmarks. To facilitate further studies on the head and human detection problem, all new annotations, source codes and trained models will be public. | ['Stan Z. Li', 'Xudong Zou', 'Shifeng Zhang', 'Junliang Xing', 'Zhen Lei', 'Cheng Chi'] | 2019-09-24 | null | null | null | null | ['head-detection'] | ['computer-vision'] | [-2.59399265e-01 3.02371740e-01 1.22975573e-01 -3.00937802e-01
-3.36053491e-01 -4.33753915e-02 4.39797580e-01 -1.04228683e-01
-5.63519597e-01 5.82448602e-01 2.16607988e-01 4.29075122e-01
4.89849538e-01 -5.98538458e-01 -4.54452425e-01 -8.32458615e-01
-1.12255737e-01 3.89902800e-01 7.88672388e-01 -3.46561265e-03
-3.33987802e-01 3.13422740e-01 -1.80104005e+00 -1.86626092e-01
7.20374048e-01 1.01677358e+00 -7.32505172e-02 4.44293022e-01
3.00665766e-01 6.46142364e-01 -7.41510212e-01 -7.15572655e-01
2.99946189e-01 -2.10663944e-01 -2.80010968e-01 2.43972570e-01
5.56284010e-01 -5.45484662e-01 -5.83506107e-01 1.18093741e+00
1.02204287e+00 8.36576146e-05 6.01521432e-01 -1.50501990e+00
-2.91298419e-01 4.49282736e-01 -1.39326191e+00 3.30029130e-01
5.02470136e-01 4.09437567e-01 6.50478661e-01 -9.94875610e-01
2.40520760e-01 1.67527604e+00 6.25286222e-01 6.56603634e-01
-7.40433931e-01 -1.29747510e+00 1.33345336e-01 7.64639229e-02
-1.73813987e+00 -7.19468534e-01 4.30704594e-01 -4.81460363e-01
4.73106295e-01 -5.20217046e-02 7.10717499e-01 1.00915790e+00
-1.89220218e-03 1.21259427e+00 6.94404006e-01 -1.76073745e-01
-1.89552352e-01 7.54497051e-02 2.05407932e-01 1.02662992e+00
8.71236682e-01 2.02990130e-01 -4.01225120e-01 1.39299482e-01
5.12596488e-01 2.87265945e-02 -2.54511446e-01 -4.40747261e-01
-8.43492568e-01 7.30856240e-01 5.80135286e-01 -2.30407924e-03
-1.44629404e-01 -2.09758803e-01 7.12626040e-01 -4.89237905e-01
2.13851914e-01 -2.78875113e-01 7.67848119e-02 5.13657629e-01
-8.35418403e-01 4.78935599e-01 6.39028549e-01 1.29261625e+00
3.96909684e-01 -6.54642805e-02 -5.27436733e-01 7.69679070e-01
4.80597973e-01 8.01194072e-01 4.00186479e-01 -4.94871676e-01
4.20817614e-01 7.15355575e-01 7.48053044e-02 -1.15438330e+00
-7.87850022e-01 -4.14770544e-01 -1.00193584e+00 -2.32727136e-02
4.85628873e-01 -1.91951454e-01 -9.57490504e-01 1.56475592e+00
8.21649909e-01 -1.81513578e-01 -3.18628848e-01 1.17054522e+00
1.36835039e+00 2.46421069e-01 4.01912272e-01 -2.90560275e-01
1.70148635e+00 -1.10816121e+00 -8.90655458e-01 -5.45126677e-01
5.03927350e-01 -5.32306612e-01 6.53930604e-01 2.54398994e-02
-9.79590714e-01 -7.26325750e-01 -1.01228857e+00 -1.38484672e-01
-2.05764368e-01 3.67503554e-01 3.58848810e-01 5.72120607e-01
-5.60524285e-01 7.70776486e-03 -7.72227526e-01 -6.80112720e-01
5.71448863e-01 4.98789310e-01 -2.79007256e-01 6.75287619e-02
-1.01008034e+00 8.36986244e-01 5.21668673e-01 1.73190713e-01
-7.93655574e-01 -5.27440086e-02 -9.87967432e-01 -6.81477338e-02
4.09898013e-01 -6.02556944e-01 1.40409553e+00 -3.93078536e-01
-1.01801074e+00 1.31745255e+00 -5.77521436e-02 -4.12195861e-01
8.33979666e-01 -4.01766121e-01 -5.23031592e-01 -1.12657212e-01
4.96830821e-01 7.90401936e-01 8.89169753e-01 -1.04025173e+00
-1.14414322e+00 -7.55308986e-01 -4.48290557e-01 -3.40186693e-02
-2.09306121e-01 4.31146771e-01 -8.78817737e-01 -3.74608248e-01
8.74504745e-02 -9.12958682e-01 1.57027498e-01 8.26806724e-02
-7.33548462e-01 -5.25635481e-01 9.99182224e-01 -6.24585927e-01
1.25507867e+00 -2.10056758e+00 -6.23604953e-02 -1.55679986e-01
6.16324127e-01 6.31028593e-01 1.35598198e-01 -4.03087556e-01
1.13131210e-01 -2.90020108e-01 7.10892454e-02 -6.96795642e-01
-1.51002347e-01 1.02688141e-01 1.39073133e-01 9.18051541e-01
-9.28449724e-03 7.35170186e-01 -7.93608248e-01 -1.25153530e+00
1.77232489e-01 3.32888752e-01 -1.87741622e-01 4.52717036e-01
3.19107801e-01 3.94523948e-01 -4.10643309e-01 9.15294230e-01
9.11067069e-01 -2.98253428e-02 -1.72391683e-01 -2.69677073e-01
-7.61126727e-02 -2.14520857e-01 -1.16399646e+00 9.02614355e-01
2.19967335e-01 3.22398841e-01 4.39079463e-01 -4.85008806e-01
8.86385739e-01 2.66084820e-01 2.01157689e-01 -7.42949069e-01
5.78600824e-01 1.10666659e-02 1.32951692e-01 -5.97525060e-01
3.66336703e-01 -3.52122821e-02 1.76431593e-02 -9.06713456e-02
-4.63694856e-02 2.94223338e-01 4.49916720e-01 6.50881603e-02
8.34223151e-01 -1.62161231e-01 4.66046572e-01 -1.55989811e-01
7.40717530e-01 -2.97389537e-01 9.74619806e-01 6.40227020e-01
-1.03509998e+00 6.27756774e-01 3.03291768e-01 -3.98688436e-01
-6.45818353e-01 -8.82494032e-01 -1.43706337e-01 1.48442507e+00
3.32803547e-01 -2.62527108e-01 -8.73739541e-01 -7.31229961e-01
1.15259834e-01 3.37425321e-01 -7.19949007e-01 -2.04999506e-01
-8.16671908e-01 -8.94543827e-01 8.40041459e-01 7.89532006e-01
8.13113868e-01 -1.00242758e+00 -7.18989849e-01 3.29195522e-02
-2.38755956e-01 -1.39074683e+00 -4.95321572e-01 -1.28322124e-01
-3.32554191e-01 -1.41464269e+00 -1.10401082e+00 -8.07610333e-01
3.60947728e-01 5.05757391e-01 1.02479923e+00 2.97755182e-01
-3.89274359e-01 -3.73595245e-02 -2.06052408e-01 -7.06069410e-01
-5.27563803e-02 9.58902016e-02 3.57701272e-01 -5.36014624e-02
5.61722636e-01 -1.74694017e-01 -7.76754498e-01 4.88872945e-01
-4.31707919e-01 -1.58421651e-01 6.41538978e-01 5.69273293e-01
1.65473029e-01 -6.05772920e-02 3.92205328e-01 -6.93193793e-01
2.74176925e-01 -2.15465665e-01 -7.13946998e-01 7.81087577e-02
-2.96629041e-01 -3.93676281e-01 1.94489405e-01 -3.98438662e-01
-1.13286936e+00 4.37901616e-01 -1.23100718e-02 -4.12611097e-01
-3.25775146e-01 -2.37784535e-01 -5.59752584e-01 1.03734039e-01
5.98670602e-01 1.00806683e-01 -2.04635352e-01 -4.69477177e-01
1.65028319e-01 7.06904590e-01 1.10013056e+00 -2.38921240e-01
9.47017968e-01 5.26173592e-01 -9.26478803e-02 -8.07643652e-01
-1.22905958e+00 -7.63181150e-01 -8.50698352e-01 -2.70678997e-01
1.13489890e+00 -1.17622757e+00 -7.18085468e-01 6.77437603e-01
-1.30658972e+00 1.98356524e-01 1.51535541e-01 2.44847044e-01
4.18487005e-02 5.04623532e-01 -7.50586152e-01 -1.13757455e+00
-6.86168790e-01 -1.00923765e+00 1.50555432e+00 7.38799453e-01
-5.53001277e-02 -4.05129910e-01 -2.52176374e-01 3.50021601e-01
-8.97875428e-02 2.51131803e-01 2.14886874e-01 -6.64494455e-01
-2.38323256e-01 -7.22796202e-01 -7.35405385e-01 -3.02150641e-02
-1.73085123e-01 1.13499612e-01 -1.14137387e+00 -5.00370443e-01
-3.94674182e-01 -2.35308021e-01 8.71097565e-01 2.77583778e-01
7.93787360e-01 -1.40804246e-01 -8.55999351e-01 4.99458551e-01
5.30957580e-01 -2.69929189e-02 4.73342836e-01 2.93433338e-01
9.26516354e-01 8.15633953e-01 5.49166799e-01 7.54391849e-01
6.46482468e-01 6.55740499e-01 3.55491102e-01 -2.50713289e-01
-3.80374521e-01 -3.44486386e-01 2.59270936e-01 4.70019907e-01
-1.04015335e-01 -1.58010691e-01 -9.14401650e-01 4.89339948e-01
-1.88300288e+00 -7.07009315e-01 -4.26763117e-01 2.05966878e+00
5.34402788e-01 3.62542152e-01 8.69203687e-01 7.44019896e-02
1.29588795e+00 1.17342286e-01 -4.35151756e-01 4.97963995e-01
-1.61015064e-01 -2.01199204e-01 6.04928553e-01 -1.13320082e-01
-1.61598051e+00 1.02505004e+00 5.92596483e+00 5.80821395e-01
-8.97700787e-01 2.62416154e-01 4.22878057e-01 -6.13277070e-02
9.37480450e-01 -4.99229968e-01 -1.46997714e+00 5.03068686e-01
2.90500134e-01 -4.81197461e-02 -2.28486419e-01 1.18627691e+00
1.31971076e-01 -1.04486525e-01 -1.16241920e+00 1.25599217e+00
2.17121437e-01 -4.05193925e-01 -3.04046839e-01 2.34580860e-02
3.88999045e-01 -1.22441635e-01 -1.91894263e-01 8.25773060e-01
2.94696897e-01 -8.24852765e-01 8.59044969e-01 1.49803877e-01
4.56196845e-01 -7.53557742e-01 1.05319333e+00 5.69548726e-01
-1.51858866e+00 -1.59430176e-01 -5.13223946e-01 -4.18517478e-02
1.42896101e-01 5.48682511e-01 -6.21358037e-01 1.00789092e-01
1.03511083e+00 4.21457976e-01 -9.79448974e-01 1.40424657e+00
-5.96894145e-01 3.19648176e-01 -4.72768039e-01 5.04527949e-02
-2.46512964e-01 3.74266446e-01 6.04378879e-01 1.46724164e+00
-5.86695177e-03 2.35199898e-01 5.15420139e-01 8.99501622e-01
-1.24851279e-01 -2.45557949e-02 -4.94503409e-01 4.13870543e-01
4.96438414e-01 1.52293122e+00 -7.82415569e-01 -4.61785436e-01
-3.59694630e-01 7.01128423e-01 2.94656336e-01 1.05052643e-01
-1.09121048e+00 -3.94184172e-01 4.27609921e-01 3.96177113e-01
2.00911149e-01 7.39267245e-02 -1.27163216e-01 -1.14210832e+00
-1.05292790e-01 -6.22055948e-01 5.33639610e-01 -5.15187442e-01
-1.24563992e+00 4.22828466e-01 7.71046057e-02 -9.56116557e-01
-8.07505697e-02 -2.98976839e-01 -7.41144001e-01 3.92393351e-01
-1.10566902e+00 -1.30584097e+00 -8.58076394e-01 5.76235473e-01
3.53062361e-01 -2.82357149e-02 2.55458355e-01 6.42806828e-01
-1.30780792e+00 1.08213758e+00 -5.53338826e-01 7.41225481e-01
8.20299029e-01 -8.54731917e-01 3.07670832e-01 9.60690796e-01
-5.53795278e-01 4.46164280e-01 9.05321419e-01 -7.93063343e-01
-9.46004868e-01 -1.38921845e+00 5.96985281e-01 -4.25878316e-01
2.18283534e-01 -4.49348629e-01 -8.78005683e-01 7.00465620e-01
1.34058557e-02 3.80738854e-01 2.45011479e-01 3.25044803e-02
-3.73080224e-01 -2.23180503e-02 -1.15766251e+00 3.60221893e-01
1.24719691e+00 1.90078262e-02 -7.89757133e-01 4.39158022e-01
6.28725052e-01 -5.25340438e-01 -3.71848732e-01 6.71770394e-01
5.87065160e-01 -1.20327663e+00 9.28951919e-01 -2.00660571e-01
1.47824526e-01 -5.19651949e-01 7.39253238e-02 -8.77442420e-01
-4.58029062e-01 -1.68042421e-01 -5.45403481e-01 1.48241973e+00
-1.08558394e-01 -4.12410498e-01 9.20208335e-01 5.93659580e-01
4.56976146e-02 -3.46997052e-01 -8.43811214e-01 -8.65406215e-01
-1.03453755e-01 1.25387222e-01 5.74767172e-01 5.24727821e-01
-1.87337190e-01 7.40826488e-01 -6.04883969e-01 3.14835697e-01
1.02611923e+00 -1.44536003e-01 1.27008700e+00 -1.35735476e+00
-8.49436522e-02 -4.06251729e-01 -6.19376183e-01 -1.10007739e+00
1.18351921e-01 -3.01220328e-01 4.90123391e-01 -1.19499338e+00
6.55241847e-01 -3.80593352e-02 2.00347770e-02 5.67031384e-01
-5.10466993e-01 3.82123649e-01 1.87037557e-01 3.35575581e-01
-1.06080329e+00 6.81256175e-01 1.19327176e+00 -5.29150032e-02
-1.16056122e-01 2.70078126e-02 -5.00250280e-01 1.15184474e+00
3.80380094e-01 -4.43705022e-01 2.32816100e-01 -1.75409302e-01
-4.47646141e-01 -6.72916546e-02 4.55019623e-01 -1.38504338e+00
5.77727139e-01 2.03876242e-01 7.42929459e-01 -1.03087282e+00
2.54460305e-01 -5.11499286e-01 -4.16738093e-01 6.10713065e-01
1.53037801e-01 -2.57911235e-01 6.59463406e-02 5.65180957e-01
-7.81745538e-02 1.44642130e-01 1.32200086e+00 -5.98025098e-02
-6.41875267e-01 4.23536181e-01 -1.21871665e-01 1.30705193e-01
1.12345982e+00 -1.22749612e-01 -2.94585496e-01 -3.20532650e-01
-4.78713393e-01 6.52670085e-01 3.36160332e-01 4.84590560e-01
3.69295090e-01 -1.13505220e+00 -7.66990006e-01 2.91225582e-01
3.46351534e-01 3.50699306e-01 6.67987242e-02 1.14290988e+00
-3.13444883e-01 3.38814229e-01 -7.08063170e-02 -7.46914744e-01
-1.52671063e+00 7.08467901e-01 5.30921757e-01 1.09172510e-02
-7.27351964e-01 9.97399151e-01 8.21474195e-01 -3.70049804e-01
7.23330259e-01 -1.10919893e-01 -4.23547357e-01 1.39554292e-01
8.54367971e-01 6.08810604e-01 -1.59010530e-01 -1.23824894e+00
-6.27610922e-01 3.25783283e-01 -2.85788119e-01 4.69169199e-01
8.76711130e-01 -2.73982495e-01 6.61625043e-02 -1.77481249e-01
9.54302132e-01 -1.34141490e-01 -1.08912802e+00 -2.36040965e-01
-9.78791490e-02 -4.04176295e-01 -1.32502884e-01 -2.96455950e-01
-1.35846353e+00 9.14931357e-01 1.00422144e+00 -3.05947140e-02
8.80330920e-01 2.42864594e-01 1.09459388e+00 2.06846535e-01
2.87771612e-01 -9.86283362e-01 2.14463565e-02 4.91145968e-01
6.12656653e-01 -1.53711689e+00 2.09984541e-01 -6.84439123e-01
-4.46579188e-01 6.68720007e-01 1.29141593e+00 2.65269298e-02
3.84234756e-01 2.70996183e-01 -1.38973117e-01 -2.42558807e-01
-1.51052639e-01 -6.66570306e-01 2.23055393e-01 7.56040990e-01
5.56438565e-01 2.43984103e-01 -2.47287244e-01 9.76021767e-01
-3.25862914e-01 4.68447758e-03 1.05633266e-01 9.32122290e-01
-7.41273582e-01 -5.22391856e-01 -9.47654963e-01 4.40266639e-01
-5.68843067e-01 3.23896110e-01 -6.13893092e-01 9.92778599e-01
4.83837932e-01 1.03943503e+00 -1.23334020e-01 -4.83752817e-01
7.43561387e-01 -1.67353958e-01 2.82785118e-01 -5.78947365e-01
-2.32535750e-01 3.27363163e-01 -6.01994172e-02 -3.63457352e-01
-2.60281444e-01 -6.31767750e-01 -1.42196989e+00 -5.16185939e-01
-7.41858661e-01 -1.13384500e-01 4.70546186e-02 9.63149965e-01
6.00542240e-02 4.50576365e-01 1.40882418e-01 -1.20066106e+00
-5.42423189e-01 -1.24574721e+00 -8.18627179e-01 4.96302456e-01
1.56520307e-01 -1.27407813e+00 -2.76873678e-01 -7.15070069e-02] | [7.98602294921875, -0.5849825143814087] |
b35b5fde-faf1-49f1-94eb-d9cd1f230531 | view-to-label-multi-view-consistency-for-self | 2305.17972 | null | https://arxiv.org/abs/2305.17972v1 | https://arxiv.org/pdf/2305.17972v1.pdf | View-to-Label: Multi-View Consistency for Self-Supervised 3D Object Detection | For autonomous vehicles, driving safely is highly dependent on the capability to correctly perceive the environment in 3D space, hence the task of 3D object detection represents a fundamental aspect of perception. While 3D sensors deliver accurate metric perception, monocular approaches enjoy cost and availability advantages that are valuable in a wide range of applications. Unfortunately, training monocular methods requires a vast amount of annotated data. Interestingly, self-supervised approaches have recently been successfully applied to ease the training process and unlock access to widely available unlabelled data. While related research leverages different priors including LIDAR scans and stereo images, such priors again limit usability. Therefore, in this work, we propose a novel approach to self-supervise 3D object detection purely from RGB sequences alone, leveraging multi-view constraints and weak labels. Our experiments on KITTI 3D dataset demonstrate performance on par with state-of-the-art self-supervised methods using LIDAR scans or stereo images. | ['Francesca Odone', 'Federico Tombari', 'Fabian Manhardt', 'Nikolas Brasch', 'Issa Mouawad'] | 2023-05-29 | null | null | null | null | ['autonomous-vehicles'] | ['computer-vision'] | [ 2.64581859e-01 -1.57648569e-03 -2.94064164e-01 -7.19231308e-01
-5.99189341e-01 -7.20614433e-01 7.15674639e-01 -6.77450150e-02
-5.66704869e-01 4.95007068e-01 -4.53248888e-01 -4.60697263e-01
2.15816110e-01 -4.70804036e-01 -8.32681298e-01 -5.87513447e-01
2.40357235e-01 5.56047320e-01 6.94841385e-01 -1.61497355e-01
3.29935223e-01 7.22515941e-01 -2.28503871e+00 -2.36454874e-01
4.85795408e-01 1.14088285e+00 4.99183506e-01 4.72128987e-01
-7.37075731e-02 4.76318955e-01 -5.94838522e-02 1.11011625e-03
6.80158496e-01 3.11807990e-02 -2.32889742e-01 4.20661271e-01
8.77814293e-01 -4.39651012e-01 -3.32013667e-01 9.00927842e-01
4.11690593e-01 -5.77898920e-02 6.52191699e-01 -1.60931981e+00
-1.06417397e-02 -3.35928530e-01 -5.71787655e-01 1.90351114e-01
5.24882615e-01 2.39805833e-01 8.42217267e-01 -9.23632801e-01
5.17701149e-01 9.80354786e-01 6.35823250e-01 4.01001185e-01
-1.17655146e+00 -6.63168907e-01 1.40961453e-01 4.26050335e-01
-1.21877706e+00 -7.29878068e-01 9.11737263e-01 -4.43182558e-01
1.08135498e+00 4.35772352e-02 6.12617671e-01 1.04128051e+00
-6.41082302e-02 8.51548195e-01 1.61488891e+00 -1.98075280e-01
3.13710898e-01 4.09269184e-01 -2.13030040e-01 6.35161459e-01
3.24154556e-01 4.70608890e-01 -8.11334133e-01 2.47873247e-01
4.64817643e-01 6.32658228e-02 7.22703934e-02 -1.30077100e+00
-9.36985910e-01 7.22055018e-01 3.39674175e-01 -2.79679030e-01
-1.08896062e-01 -2.19081398e-02 1.97787046e-01 2.49305546e-01
3.97225648e-01 -7.15538114e-03 -4.69114393e-01 -3.69250298e-01
-7.62986779e-01 1.42563879e-02 5.19617677e-01 1.30925810e+00
1.17552614e+00 -6.71934858e-02 6.41018450e-01 5.61382234e-01
3.56425881e-01 8.67839873e-01 7.01098889e-02 -1.11671877e+00
4.97244537e-01 7.06061602e-01 1.79652303e-01 -5.98387718e-01
-4.80184257e-01 -2.25749463e-01 -2.95330256e-01 8.39924693e-01
2.51323819e-01 4.10929322e-01 -1.10101926e+00 1.26937890e+00
5.50426602e-01 -3.14701274e-02 1.53615952e-01 1.00846362e+00
6.72753930e-01 9.67143625e-02 -1.57370433e-01 1.89482063e-01
9.38466311e-01 -6.74182057e-01 -2.35025510e-01 -8.16358984e-01
3.64878148e-01 -7.17753291e-01 9.07482982e-01 4.54685241e-01
-7.18279362e-01 -7.32374370e-01 -1.25391257e+00 -2.33919188e-01
-5.58631420e-01 -1.59030575e-02 5.76704323e-01 9.44666147e-01
-9.94483531e-01 2.08000019e-01 -9.33882475e-01 -6.18782878e-01
4.71696585e-01 2.74191946e-01 -7.41379201e-01 -5.33902049e-01
-7.54570246e-01 1.47858858e+00 4.10365790e-01 -1.25691280e-01
-9.21838641e-01 -3.01221997e-01 -1.19025290e+00 -6.27551079e-01
5.83675802e-01 -4.31840241e-01 1.10443103e+00 -1.58710852e-01
-1.34226036e+00 1.35976577e+00 -1.44459635e-01 -5.82723022e-01
8.12856853e-01 -2.51416892e-01 4.52310666e-02 1.59606338e-01
2.18427479e-01 1.04530001e+00 9.00744081e-01 -1.54276979e+00
-1.03802586e+00 -6.89106643e-01 2.23790094e-01 5.72680652e-01
1.37141943e-01 -4.91756469e-01 -4.50331390e-01 2.45196924e-01
5.89300752e-01 -1.13923204e+00 -1.11837253e-01 1.84027642e-01
-1.01640821e-01 -1.44897401e-01 1.16861665e+00 -8.34851936e-02
1.04888320e-01 -2.20521021e+00 -2.14446828e-01 -1.04336731e-01
5.78126237e-02 7.26192147e-02 2.49034166e-01 2.64919519e-01
3.64321828e-01 -3.73947680e-01 -2.59061038e-01 -6.20936692e-01
2.34609231e-01 7.35993445e-01 -2.27990985e-01 8.64075363e-01
2.90270776e-01 6.63548708e-01 -9.54078913e-01 -5.04244447e-01
8.88914287e-01 4.55657810e-01 -3.66572499e-01 1.08154014e-01
-1.73702791e-01 4.89562660e-01 -2.63356447e-01 7.89950371e-01
7.76244462e-01 6.61116019e-02 -2.56664038e-01 2.14304626e-02
-3.25274974e-01 4.00205880e-01 -1.11112523e+00 1.78215861e+00
-5.26893139e-01 7.75017083e-01 1.73982516e-01 -9.80624616e-01
1.05898213e+00 -3.39458464e-03 3.97907048e-01 -8.15194964e-01
6.44432455e-02 3.66427392e-01 -3.41791183e-01 -5.58010757e-01
5.93885720e-01 -1.74249947e-01 3.01783159e-02 2.59073973e-01
-1.14535384e-01 -8.77418935e-01 -6.48037810e-03 1.34151299e-02
1.01432669e+00 7.81618714e-01 3.25659066e-01 1.20873578e-01
2.90340334e-01 3.72166038e-01 4.04349744e-01 7.22888112e-01
-4.90785569e-01 6.04191959e-01 -3.53676500e-03 -3.28245342e-01
-1.14081168e+00 -1.19238770e+00 -4.46810335e-01 7.96733320e-01
7.59871960e-01 4.97714616e-02 -1.69817224e-01 -6.92810535e-01
4.43851233e-01 8.04897666e-01 -4.50049490e-01 1.82568505e-02
-3.01405638e-01 -2.35617623e-01 2.54231691e-01 6.88689649e-01
4.70600486e-01 -6.48405015e-01 -1.50593531e+00 3.01291533e-02
1.07394382e-01 -1.77437699e+00 1.88215628e-01 6.77280366e-01
-7.42683887e-01 -1.09646487e+00 -2.72059619e-01 -4.83359396e-01
5.43832123e-01 1.00938082e+00 1.03658712e+00 -3.91987443e-01
-4.55432683e-01 7.82985985e-01 -2.34936565e-01 -6.36760533e-01
-2.64807403e-01 -1.25691548e-01 3.11308622e-01 -2.93814242e-01
6.90262794e-01 -6.45980895e-01 -4.75734383e-01 5.98134696e-01
-4.87550169e-01 1.30284429e-01 8.24819446e-01 4.86762762e-01
7.10290670e-01 -1.04755975e-01 2.70018876e-01 -6.43607318e-01
-2.66678333e-01 -1.02834582e-01 -8.91044617e-01 -3.47253084e-01
-6.39607131e-01 -1.82498619e-01 8.26750025e-02 -6.48502782e-02
-9.09595311e-01 6.98698044e-01 1.26693562e-01 -7.05116272e-01
-8.08242381e-01 -2.92249471e-02 -2.53105819e-01 -3.71340811e-01
7.32769549e-01 2.36577421e-01 2.49130085e-01 -2.46496201e-01
4.73828942e-01 7.76781440e-01 5.83836436e-01 -2.05137447e-01
9.87232506e-01 9.98954833e-01 3.20162416e-01 -8.93867552e-01
-1.00891244e+00 -1.08044982e+00 -1.13576472e+00 -3.66270274e-01
7.70837665e-01 -1.20175779e+00 -4.04420882e-01 1.62531510e-01
-8.51589739e-01 -2.62432814e-01 -2.88719833e-01 6.25601768e-01
-9.18607235e-01 3.89015287e-01 1.27610847e-01 -1.07027006e+00
3.63769680e-01 -1.13900542e+00 1.54594600e+00 -9.41042155e-02
2.92086620e-02 -5.23625731e-01 -2.39081308e-01 7.13070869e-01
1.17051408e-01 3.04067940e-01 3.38853031e-01 -3.16934496e-01
-8.91457915e-01 -4.21399534e-01 -3.84102851e-01 3.96606058e-01
1.63596824e-01 -5.57213843e-01 -1.46011567e+00 -9.74623859e-02
-5.45354672e-02 -6.57566905e-01 9.36887145e-01 -4.42869738e-02
6.40467823e-01 5.73560596e-01 -4.92500633e-01 3.82519752e-01
1.23423362e+00 -6.74350709e-02 1.68776110e-01 4.93984669e-01
7.16118276e-01 8.39916885e-01 9.11642253e-01 2.55713254e-01
8.24252248e-01 6.14259303e-01 8.99148703e-01 -1.49757490e-02
-9.92089435e-02 -2.28479221e-01 2.18989104e-01 3.28395993e-01
2.08845273e-01 1.56721473e-01 -1.07674885e+00 5.39052427e-01
-1.69316697e+00 -7.64127433e-01 -1.11219250e-01 2.22273588e+00
5.66609383e-01 6.40885592e-01 -3.20037231e-02 5.59854805e-01
3.02457780e-01 -3.54413898e-03 -9.24493074e-01 4.41727452e-02
-1.46792501e-01 -2.91141540e-01 1.03624988e+00 3.26730937e-01
-1.23289537e+00 8.21198225e-01 6.07771206e+00 3.47900301e-01
-1.00212193e+00 5.59045151e-02 1.04093336e-01 -8.77021998e-02
-1.76568806e-01 -8.16698093e-03 -1.10507405e+00 1.29549606e-02
5.98468184e-01 2.93214321e-01 1.44159257e-01 1.05909324e+00
-1.48983812e-02 -6.05177045e-01 -1.40167987e+00 1.36089516e+00
4.18576598e-01 -7.76072800e-01 -5.90498924e-01 2.35291943e-01
6.24152601e-01 5.96742988e-01 9.26083699e-02 1.56947002e-01
2.60259837e-01 -7.49353230e-01 9.16210711e-01 1.40565500e-01
7.26395309e-01 -5.40929675e-01 5.33706188e-01 7.25465119e-01
-1.06343782e+00 -1.64494216e-02 -4.59533840e-01 -2.93344021e-01
1.99825048e-01 5.55673838e-01 -1.13933349e+00 4.89691377e-01
9.04937565e-01 8.58332813e-01 -7.21982002e-01 1.06289876e+00
-4.09828722e-01 1.99354991e-01 -6.10917807e-01 1.34318396e-01
2.26985216e-01 -1.03234589e-01 5.67870617e-01 7.50316441e-01
1.49689287e-01 3.31371702e-04 3.88611346e-01 5.59721351e-01
4.13505077e-01 -3.31797898e-01 -1.13005614e+00 3.41094971e-01
4.09182668e-01 1.11382937e+00 -7.72316515e-01 -8.27869028e-02
-7.45212495e-01 7.00522125e-01 1.07215092e-01 9.99024957e-02
-5.09423792e-01 -7.85030983e-03 5.69635153e-01 1.39588878e-01
5.99113047e-01 -7.46497869e-01 -4.24392313e-01 -7.87850320e-01
1.91913277e-01 -3.62948626e-01 2.69224085e-02 -9.61743951e-01
-1.09328163e+00 4.43809658e-01 1.49075940e-01 -1.59177411e+00
-3.43637794e-01 -8.61656904e-01 7.53860325e-02 6.02593780e-01
-2.26353526e+00 -1.25391150e+00 -7.87632108e-01 3.67008448e-01
5.59024215e-01 -1.12938983e-02 5.64850926e-01 7.75183439e-02
2.84146275e-02 2.11484581e-02 -1.18897110e-01 -4.91532981e-01
7.10038126e-01 -1.35652447e+00 4.60183173e-01 6.72316253e-01
3.16234678e-01 1.06053911e-01 8.34155440e-01 -4.61646438e-01
-1.73481607e+00 -9.19926345e-01 5.06179512e-01 -8.90114367e-01
3.52214068e-01 -5.60915768e-01 -5.60727000e-01 4.67939466e-01
-4.84097861e-02 3.01620424e-01 4.61580664e-01 -1.00608468e-01
-4.11568075e-01 -2.27539599e-01 -1.08723545e+00 3.24096173e-01
1.37595308e+00 -7.80778885e-01 -5.61745763e-01 2.32680604e-01
3.63742173e-01 -7.47841358e-01 -4.28012252e-01 7.22562551e-01
5.33468723e-01 -1.28182995e+00 1.03086030e+00 3.05909626e-02
-2.76055932e-02 -5.91300309e-01 -5.76729119e-01 -9.73278403e-01
2.43156061e-01 -2.29247496e-01 -5.98554723e-02 8.14412236e-01
9.15371478e-02 -6.55847192e-01 1.13066280e+00 4.47429866e-01
-3.22388589e-01 -4.09042150e-01 -1.14602625e+00 -9.44688916e-01
-4.14847076e-01 -8.09381068e-01 2.07033962e-01 5.20156205e-01
-3.88311327e-01 3.35755140e-01 -1.81158453e-01 3.79648656e-01
1.09888220e+00 3.76484543e-01 1.22187924e+00 -1.54860854e+00
3.05113699e-02 -1.80441320e-01 -1.00243640e+00 -1.33575058e+00
3.32789838e-01 -7.53468931e-01 5.18305361e-01 -1.54531014e+00
-6.08504862e-02 -7.75419116e-01 1.45932371e-02 3.76352221e-01
1.64778039e-01 6.83439672e-01 8.70842580e-03 2.10288391e-01
-6.96694195e-01 6.52423084e-01 9.22250032e-01 -1.22498579e-01
8.87380838e-02 -1.23523679e-02 -2.86383241e-01 6.84856951e-01
7.66768694e-01 -1.65195644e-01 -7.05989897e-01 -4.44342941e-01
1.38538346e-01 -2.60430276e-01 6.18697524e-01 -1.16910625e+00
4.32168067e-01 -1.07229933e-01 3.82530093e-01 -1.30509555e+00
9.86313045e-01 -1.15763545e+00 -3.16067874e-01 1.80878863e-01
1.31593257e-01 -1.50803998e-01 2.72188872e-01 8.78299117e-01
-1.35207608e-01 -1.06860720e-01 6.45608962e-01 -2.63242871e-01
-1.24524081e+00 2.63134152e-01 -2.27282256e-01 -8.34857970e-02
1.24327922e+00 -8.60135257e-01 3.61567512e-02 -2.97066271e-01
-3.67342293e-01 3.22005093e-01 8.65304053e-01 6.47123694e-01
7.79125750e-01 -1.09389317e+00 -3.49685758e-01 5.95322967e-01
5.86067915e-01 4.63577747e-01 -8.64714012e-02 6.44248962e-01
-2.47645229e-01 6.89416885e-01 -2.95399457e-01 -1.34800422e+00
-1.08899271e+00 3.93711954e-01 6.04254231e-02 5.99710703e-01
-7.87593544e-01 6.56724691e-01 1.99352443e-01 -7.61736214e-01
3.86617362e-01 -1.36516437e-01 2.47770417e-02 -7.34201819e-02
9.12084281e-02 2.77130276e-01 3.95632863e-01 -9.03580189e-01
-4.95425701e-01 7.78840840e-01 1.06833450e-01 -2.48541802e-01
1.21419585e+00 -6.31568730e-01 3.17961007e-01 7.54049063e-01
1.01599610e+00 -3.13445568e-01 -1.90827882e+00 -3.64065349e-01
3.05043198e-02 -7.02332079e-01 3.28186989e-01 -4.08019572e-01
-5.16681612e-01 1.10999668e+00 7.80146718e-01 7.42695481e-02
7.84888983e-01 2.44718224e-01 4.52912986e-01 5.10747075e-01
1.01280868e+00 -1.08828473e+00 1.13697894e-01 5.07967114e-01
4.69431013e-01 -1.94584084e+00 2.17903852e-01 -5.65852761e-01
-5.31868160e-01 8.00718486e-01 6.32059693e-01 1.54490888e-01
4.68323082e-01 2.95798182e-01 3.67562592e-01 -1.18365869e-01
-4.81431931e-01 -6.92245305e-01 1.57795072e-01 9.91800368e-01
-1.42052606e-01 -1.45869434e-01 4.72242266e-01 -1.79561496e-01
-3.06301355e-01 -2.94834614e-01 3.03338081e-01 1.34145641e+00
-6.23344719e-01 -9.28219795e-01 -3.28169078e-01 2.23108158e-01
1.64212614e-01 2.63748020e-01 -2.83161610e-01 8.57798338e-01
2.35464156e-01 1.10848403e+00 2.87030521e-03 -3.19194555e-01
4.42813665e-01 1.02187917e-01 8.27642322e-01 -6.78363025e-01
2.71938562e-01 -1.52116209e-01 2.34594643e-02 -7.00924814e-01
-8.15147102e-01 -1.03653288e+00 -1.04863822e+00 2.24443331e-01
-3.98294270e-01 -3.00854117e-01 1.18762970e+00 1.13964903e+00
2.33035922e-01 7.86987171e-02 7.22509623e-01 -1.39708030e+00
-6.19531512e-01 -6.15645587e-01 -4.29350048e-01 2.00276092e-01
5.91560066e-01 -1.25366306e+00 -3.23736429e-01 1.41639173e-01] | [7.870424747467041, -2.525078296661377] |
271d979f-f3d0-4b94-bee7-5d7cd069e099 | investigation-of-synthetic-speech-detection | 1610.03009 | null | http://arxiv.org/abs/1610.03009v1 | http://arxiv.org/pdf/1610.03009v1.pdf | Investigation of Synthetic Speech Detection Using Frame- and Segment-Specific Importance Weighting | Speaker verification systems are vulnerable to spoofing attacks which
presents a major problem in their real-life deployment. To date, most of the
proposed synthetic speech detectors (SSDs) have weighted the importance of
different segments of speech equally. However, different attack methods have
different strengths and weaknesses and the traces that they leave may be short
or long term acoustic artifacts. Moreover, those may occur for only particular
phonemes or sounds. Here, we propose three algorithms that weigh
likelihood-ratio scores of individual frames, phonemes, and sound-classes
depending on their importance for the SSD. Significant improvement over the
baseline system has been obtained for known attack methods that were used in
training the SSDs. However, improvement with unknown attack types was not
substantial. Thus, the type of distortions that were caused by the unknown
systems were different and could not be captured better with the proposed SSD
compared to the baseline SSD. | ['Cenk Demiroglu', 'Ali Khodabakhsh'] | 2016-10-10 | null | null | null | null | ['synthetic-speech-detection'] | ['audio'] | [ 1.36057362e-01 -4.74084355e-02 3.89117569e-01 -1.60702944e-01
-9.11571145e-01 -6.88526630e-01 6.84501588e-01 2.84484550e-02
-2.01323628e-01 6.11091912e-01 2.05895767e-01 -5.15054822e-01
1.92374557e-01 -2.81523705e-01 -5.86304963e-01 -8.01482677e-01
-1.22880429e-01 -4.41922881e-02 7.23253369e-01 -1.33000195e-01
2.39633307e-01 5.76007247e-01 -1.53364611e+00 2.85425812e-01
5.37734866e-01 6.04744792e-01 2.48461068e-01 8.99261534e-01
8.45007151e-02 4.37677026e-01 -1.43813348e+00 -4.70677972e-01
1.90543830e-01 -4.65772033e-01 -7.89388642e-02 -2.03076750e-01
5.83249509e-01 -5.34760892e-01 -5.76478481e-01 1.38650715e+00
7.16099739e-01 -1.70872107e-01 4.34709162e-01 -1.27867591e+00
-9.49147418e-02 6.76444650e-01 -2.63531983e-01 3.69483203e-01
4.24676001e-01 6.42901137e-02 5.23413420e-01 -9.80547786e-01
1.35930359e-01 1.36204064e+00 5.69719255e-01 6.50458217e-01
-8.97196829e-01 -1.10129154e+00 -1.76335514e-01 4.38971967e-01
-1.44817305e+00 -9.08255458e-01 7.52806127e-01 -2.80928463e-01
7.70241380e-01 3.50590140e-01 8.95024911e-02 1.27801585e+00
-5.45153655e-02 5.16932726e-01 9.22613442e-01 -4.35234457e-01
1.25991091e-01 6.75552607e-01 3.28596562e-01 2.85678834e-01
3.33791673e-01 5.16923487e-01 -5.55765271e-01 -4.25705165e-01
1.90702062e-02 -5.67488313e-01 -3.91017497e-01 1.25825042e-02
-9.54097986e-01 7.20737338e-01 -1.53688207e-01 4.27616239e-01
-7.90242478e-02 -1.52431592e-01 4.61412072e-01 2.17029780e-01
1.34434804e-01 2.42453396e-01 -3.11536402e-01 -1.19532026e-01
-1.06141758e+00 1.53295184e-02 7.43513525e-01 8.07260394e-01
3.23092520e-01 5.20045161e-01 2.75716260e-02 7.56751418e-01
4.81623799e-01 6.98781252e-01 5.26431322e-01 -4.53875691e-01
5.67651689e-01 -1.83281705e-01 1.01663999e-01 -1.02610660e+00
-1.18280977e-01 -4.69536752e-01 -2.99328715e-01 2.27396131e-01
5.45463383e-01 -2.43277460e-01 -8.43871593e-01 1.72843814e+00
1.35037959e-01 5.44997573e-01 2.95059592e-01 5.53879857e-01
4.81695145e-01 7.72538722e-01 -2.42298588e-01 -3.69551986e-01
1.27115762e+00 -8.19660127e-01 -1.15370107e+00 -4.08161193e-01
2.12441310e-01 -1.33089685e+00 7.87984669e-01 5.21849811e-01
-9.48462009e-01 -6.05765104e-01 -1.50641000e+00 7.30749965e-01
-2.03840554e-01 -1.17513552e-01 6.44351393e-02 1.65023935e+00
-8.67020130e-01 4.44587380e-01 -4.62251097e-01 -1.22592486e-01
-8.40959921e-02 2.36721620e-01 -2.52904166e-02 2.88804114e-01
-1.43037701e+00 8.64050984e-01 -6.04953468e-02 -5.46437874e-02
-1.14423525e+00 -4.00255769e-01 -5.13547182e-01 4.51077633e-02
2.19711885e-02 2.98876941e-01 1.35782743e+00 -6.45600200e-01
-1.51432562e+00 3.91632169e-01 -2.49335408e-01 -6.93528593e-01
4.74559665e-01 -1.45587325e-01 -1.27283025e+00 2.25287765e-01
-2.94365436e-01 -1.45313526e-02 1.30918348e+00 -1.27430058e+00
-5.94135821e-01 -1.17511496e-01 -2.53196716e-01 -1.14998139e-01
-5.08594930e-01 5.30758798e-01 -1.24151960e-01 -8.00792754e-01
9.37168524e-02 -9.53273535e-01 2.69066215e-01 -3.33229244e-01
-5.00854850e-01 2.95922220e-01 1.22631383e+00 -9.60343778e-01
1.36323440e+00 -2.59255099e+00 -6.06314659e-01 8.74929056e-02
-4.47300792e-01 1.02997780e+00 3.45850289e-02 5.16650319e-01
-6.78195804e-02 1.42198488e-01 -1.14803545e-01 -3.19956064e-01
-6.49449378e-02 -9.14650783e-02 -6.51494861e-01 5.12983263e-01
-1.02531329e-01 -1.29615515e-01 -7.42989361e-01 -1.61498651e-01
3.25897753e-01 6.95352256e-01 -1.45536736e-01 2.68054575e-01
2.90363044e-01 1.33334607e-01 -2.08599232e-02 4.42682385e-01
9.44183528e-01 7.41885185e-01 1.26662841e-02 -1.92025840e-01
6.01627864e-02 7.92644620e-01 -1.39006031e+00 8.98870289e-01
-2.77082890e-01 1.07593751e+00 2.06261814e-01 -6.56751156e-01
9.12755132e-01 8.92256320e-01 -2.86604725e-02 -3.26961547e-01
-8.46711472e-02 5.12410581e-01 4.97637153e-01 -3.53397399e-01
4.53962386e-01 -4.85148430e-02 2.81760573e-01 3.59020323e-01
-4.39147279e-02 -1.18726775e-01 -1.04714736e-01 1.28248349e-01
9.96332526e-01 -4.86488670e-01 -4.62543359e-03 -6.16433918e-02
7.79757977e-01 -5.02628326e-01 5.61215639e-01 8.17909241e-01
-6.65095627e-01 6.88115597e-01 1.25495613e-01 2.20881701e-01
-9.42340136e-01 -1.15727901e+00 -3.64235044e-01 5.74520230e-01
2.07201883e-01 -2.39366516e-01 -8.86404335e-01 -7.31055439e-01
-3.48837435e-01 9.36848402e-01 9.98653397e-02 -4.57151145e-01
-6.21437728e-01 -4.92315859e-01 1.43747389e+00 1.45334795e-01
2.40386084e-01 -1.05095649e+00 -3.05414259e-01 3.64441961e-01
-1.67761192e-01 -1.44652832e+00 -7.39148498e-01 -4.61944751e-02
-5.97441554e-01 -8.99993241e-01 -5.74932814e-01 -7.19145060e-01
4.54299390e-01 6.86027348e-01 4.81366038e-01 -1.17925391e-01
2.79297773e-02 -3.55176604e-03 -3.99116099e-01 -6.44844234e-01
-1.08600402e+00 -3.92525226e-01 5.35307884e-01 3.91984701e-01
2.59200782e-01 -2.21465960e-01 -3.79581839e-01 5.91954589e-01
-6.66930556e-01 -6.70546710e-01 2.31127873e-01 7.02453375e-01
-2.85385609e-01 4.86619800e-01 8.13153028e-01 -6.01558924e-01
6.67741060e-01 -3.08493137e-01 -3.51778686e-01 1.49455294e-01
-4.86858040e-01 -7.02237114e-02 4.69718635e-01 -7.40976751e-01
-1.23266101e+00 -3.15843254e-01 -5.43046117e-01 -2.61565089e-01
-3.74760687e-01 3.93700227e-02 -5.12196422e-01 -3.65866311e-02
6.08695626e-01 2.67887294e-01 -4.43895161e-02 -5.29124320e-01
-1.26307786e-01 1.07899868e+00 4.23131406e-01 -7.07995445e-02
1.05371881e+00 7.40947425e-02 -4.97775584e-01 -1.21334255e+00
-2.21326306e-01 -3.93403262e-01 -1.95169973e-03 -3.57410759e-02
3.07530761e-01 -7.70523548e-01 -2.74920851e-01 1.08605468e+00
-1.29727268e+00 2.65221953e-01 9.41863954e-02 7.20815778e-01
1.22975007e-01 8.58767152e-01 -5.60600221e-01 -1.37277353e+00
-2.13109359e-01 -1.51568878e+00 5.64083040e-01 2.04714268e-01
-2.26485416e-01 -6.42962515e-01 -1.10322252e-01 3.68948847e-01
6.95762277e-01 -3.27070177e-01 6.96647286e-01 -9.76156771e-01
-1.53765053e-01 -6.06702507e-01 1.30937114e-01 8.48968148e-01
4.21572924e-01 3.56343895e-01 -1.54436266e+00 -6.32545590e-01
4.73273695e-01 1.45611748e-01 5.51395297e-01 2.61132717e-01
5.33097208e-01 -4.89419460e-01 -2.16910392e-01 3.32390338e-01
9.98968840e-01 8.97844613e-01 6.87716067e-01 3.58521286e-03
2.69224942e-01 7.57808626e-01 5.22835433e-01 1.40699551e-01
-3.56991231e-01 1.10680521e+00 3.30375671e-01 8.13607872e-02
-3.44179273e-01 -2.71932006e-01 1.13859880e+00 9.53849196e-01
5.41098058e-01 -4.77106571e-01 -5.58067501e-01 5.59799671e-01
-1.15474832e+00 -1.23136377e+00 -3.22181493e-01 2.63475895e+00
5.84306896e-01 5.74415207e-01 8.90616104e-02 8.59504282e-01
1.27167952e+00 2.92953730e-01 -3.22622746e-01 -6.47121191e-01
-3.75526249e-01 6.09398820e-02 5.56432366e-01 6.70536816e-01
-8.43521476e-01 6.33759201e-01 6.82657480e+00 8.89300168e-01
-1.26788163e+00 1.42483816e-01 6.20218627e-02 2.84427032e-02
-2.07224619e-02 -1.69845729e-03 -9.22358096e-01 7.12003767e-01
1.39132965e+00 -1.91675667e-02 1.99504808e-01 5.92563868e-01
2.59394586e-01 9.72465500e-02 -6.59659564e-01 5.96789539e-01
2.78997242e-01 -7.38197565e-01 -2.16179818e-01 1.20763272e-01
3.38909149e-01 -1.80832893e-01 2.32662961e-01 7.58832740e-03
4.39283345e-03 -5.18692374e-01 1.03848815e+00 -7.07888529e-02
4.81022477e-01 -7.89840519e-01 8.01248729e-01 2.57326245e-01
-9.34764743e-01 -5.52869327e-02 -3.43435526e-01 2.05038726e-01
3.63136977e-01 5.45670331e-01 -1.40472984e+00 2.38552660e-01
2.86814123e-01 -1.65195286e-01 -4.01892662e-01 1.14455342e+00
-4.12272573e-01 1.26623464e+00 -2.85990000e-01 -9.62870121e-02
-1.51567072e-01 2.62986481e-01 1.09161150e+00 1.32019198e+00
6.17979765e-01 -5.74531496e-01 -3.76249462e-01 3.57807964e-01
2.13239923e-01 -7.46796876e-02 -5.77018321e-01 -6.10328391e-02
1.11120653e+00 8.00969124e-01 -4.58122671e-01 -3.09583992e-01
-4.10698026e-01 7.65280068e-01 -3.67851347e-01 3.54496181e-01
-9.41250384e-01 -6.99014246e-01 9.83392239e-01 1.05470069e-01
3.05299640e-01 -5.09577654e-02 -1.15577511e-01 -9.01321769e-01
1.17997313e-02 -1.17741036e+00 1.29761711e-01 -4.03018713e-01
-9.60274935e-01 8.79994154e-01 -1.74012318e-01 -1.37476134e+00
-3.41537446e-01 -3.66951734e-01 -6.76572025e-01 8.48744631e-01
-1.24233270e+00 -5.12967646e-01 1.70279190e-01 4.61521536e-01
7.92230189e-01 -5.81858695e-01 8.82187903e-01 5.69138288e-01
-6.14614904e-01 1.21939611e+00 2.68725812e-01 1.06375828e-01
9.16134834e-01 -8.90989602e-01 8.27206135e-01 1.44143677e+00
4.80224401e-01 7.17241168e-01 1.09543920e+00 -5.11482179e-01
-9.47972715e-01 -5.86151600e-01 1.12856472e+00 -1.68484539e-01
5.14748454e-01 -4.79035676e-01 -9.83378828e-01 2.83061028e-01
1.64967105e-01 -3.30617696e-01 5.27514458e-01 -2.90839612e-01
-5.61200917e-01 -1.02993868e-01 -1.40927422e+00 2.89987028e-01
5.00268638e-01 -8.98422241e-01 -6.77719057e-01 4.69348095e-02
6.98372662e-01 -3.45109440e-02 -1.31992638e-01 2.39946455e-01
6.88128054e-01 -1.16206086e+00 1.14092326e+00 -1.86142176e-01
-3.02213520e-01 -5.70134580e-01 -3.05935323e-01 -1.35497546e+00
6.27747923e-02 -7.04999626e-01 -2.65795290e-01 1.71023762e+00
6.49473548e-01 -8.07769358e-01 4.67044711e-01 3.04712176e-01
-2.01313645e-01 1.86093166e-01 -1.03675008e+00 -1.23545587e+00
-1.66313827e-01 -6.89172566e-01 8.26035202e-01 8.90351713e-01
8.53462238e-03 1.60171047e-01 -8.03961813e-01 7.60694802e-01
7.35490382e-01 -6.48793876e-01 5.43923438e-01 -8.29485714e-01
-4.95206654e-01 -3.51131916e-01 -5.07462740e-01 -7.17223704e-01
-1.54494897e-01 -4.07659382e-01 1.83464557e-01 -8.17381740e-01
-2.41517454e-01 -3.41008097e-01 -4.40538466e-01 -2.53312662e-02
-4.49274182e-01 1.48762569e-01 3.18815649e-01 1.47696733e-01
3.71574223e-01 1.42108738e-01 4.95286614e-01 -3.04966360e-01
-8.04120228e-02 5.34317672e-01 -2.91645259e-01 7.14477062e-01
9.14448440e-01 -8.25012565e-01 -4.60381240e-01 -2.17112273e-01
-4.11106080e-01 2.53984421e-01 5.28540052e-02 -1.43361282e+00
3.10805887e-01 2.91532904e-01 -1.85187504e-01 -6.03411674e-01
4.93217766e-01 -8.65638316e-01 3.84126782e-01 6.57445371e-01
-3.06272745e-01 -1.35087982e-01 2.94958591e-01 3.94611686e-01
-3.56521428e-01 -6.44773901e-01 1.04621422e+00 2.90132880e-01
-1.48828566e-01 -2.20881075e-01 -8.04864049e-01 -3.06296766e-01
9.54270899e-01 -3.06927949e-01 -3.23118240e-01 -5.30340016e-01
-3.25850815e-01 -5.46405017e-01 2.96727598e-01 6.24952257e-01
6.20099664e-01 -1.04645264e+00 -7.24766314e-01 3.80033374e-01
-9.38747451e-02 -7.54232407e-01 2.02406660e-01 4.60682422e-01
-3.88118207e-01 5.00487506e-01 2.22317204e-02 -2.25010276e-01
-1.71270835e+00 6.51515782e-01 3.56805921e-01 2.90384889e-02
-2.95264363e-01 8.69685173e-01 9.45795923e-02 -8.32340196e-02
8.15969765e-01 7.79354200e-02 -1.42463982e-01 6.57389686e-02
8.99363518e-01 4.65979844e-01 3.67472261e-01 -9.44885433e-01
-6.91553175e-01 2.80378222e-01 -1.29125506e-01 -5.01144528e-01
7.53448129e-01 -1.44273460e-01 5.68826616e-01 3.53769153e-01
1.09390032e+00 5.72477818e-01 -1.12580287e+00 -2.42814928e-01
1.04830321e-02 -6.16709471e-01 -3.73731889e-02 -6.96076870e-01
-1.04295635e+00 1.20445776e+00 9.69536662e-01 4.36969042e-01
8.41362894e-01 -3.98296058e-01 9.00370002e-01 -9.48315188e-02
5.41675925e-01 -7.77000010e-01 -1.09388150e-01 2.84236521e-01
5.25628746e-01 -8.13087046e-01 -2.69442290e-01 -4.28025335e-01
-5.12148619e-01 9.50580299e-01 1.87732145e-01 2.71933198e-01
5.31331182e-01 3.88615370e-01 4.80656058e-01 3.54087412e-01
-4.43461627e-01 1.24136791e-01 1.16686769e-01 9.32274044e-01
2.81094104e-01 6.43253401e-02 -4.01872247e-01 2.86536843e-01
-2.89724678e-01 -6.92801476e-01 7.92563319e-01 7.38170743e-01
-4.70927775e-01 -1.34424663e+00 -8.75733852e-01 6.68059364e-02
-6.90705001e-01 -1.86663404e-01 -3.96424055e-01 3.55957568e-01
1.74729638e-02 1.57544386e+00 -3.66704613e-01 -8.01161349e-01
4.41971660e-01 3.26478213e-01 5.55891842e-02 -3.58676016e-01
-6.65276051e-01 1.49123877e-01 2.94543505e-01 -1.42428219e-01
-1.01681650e-01 -1.02040219e+00 -1.03179598e+00 -2.96212405e-01
-8.64706874e-01 3.54243726e-01 1.00360715e+00 8.72778952e-01
9.42344442e-02 4.48329210e-01 1.01930356e+00 -4.29870605e-01
-9.60632324e-01 -1.26280046e+00 -6.06966555e-01 4.20385689e-01
7.00631917e-01 -5.61500371e-01 -1.02069795e+00 -4.40547653e-02] | [14.103872299194336, 5.864459991455078] |
e747ac8b-a26e-4fb2-9fac-58ddd8b8be4d | structured-light-dark-field-microscope | 2202.05357 | null | https://arxiv.org/abs/2202.05357v1 | https://arxiv.org/pdf/2202.05357v1.pdf | Structured light dark-field microscope | A resolution-enhanced dark-field microscope by structured light illumination is proposed to improve resolution and contrast. A set of phase-shifted fringes are projected to the sample plane at large angle to capture modulated dark-field images, from which resolution- and contrast-enhanced dark-field image, as well as sectioned dark-field image, can be obtained. Human tissue samples are tested to demonstrate the resolution and contrast enhancement. The system can be implemented in transmission-mode and reflectance-mode, with potential applications ranging from defect detection to biomedical imaging. | ['Rongguang Liang', 'Bofan Song', 'Shaobai Li'] | 2022-02-10 | null | null | null | null | ['defect-detection'] | ['computer-vision'] | [ 1.08817446e+00 -4.08896297e-01 3.62936795e-01 -2.73612320e-01
-3.57549012e-01 -8.55977014e-02 2.64688465e-03 -3.29340667e-01
-5.29058158e-01 1.03399968e+00 -3.05277318e-01 8.82833675e-02
-5.13177700e-02 -5.31392038e-01 4.12174165e-02 -1.20152223e+00
1.65321127e-01 9.55649093e-02 6.73262179e-01 1.45667091e-01
5.30724406e-01 4.34709132e-01 -1.06582582e+00 1.49063796e-01
6.08374894e-01 6.12524331e-01 1.08771777e+00 1.90527171e-01
3.14886957e-01 4.98704761e-01 -5.88537693e-01 2.37350687e-01
-7.06248209e-02 -1.97279483e-01 -4.41849679e-01 3.58285159e-01
3.43975537e-02 -6.72175407e-01 -2.64448315e-01 1.20212626e+00
5.02080023e-01 -9.44590941e-02 4.04671937e-01 -3.21878731e-01
-8.51024210e-01 -2.36940831e-01 -9.54870641e-01 7.08266139e-01
7.12490916e-01 4.11885202e-01 1.24998137e-01 -1.20766377e+00
1.08841753e+00 9.83014107e-01 -2.05465645e-01 8.27091634e-01
-1.52444482e+00 -7.40214765e-01 -5.98881662e-01 8.03065673e-02
-1.22440624e+00 -5.01128018e-01 8.87462497e-01 -3.92263949e-01
7.33173370e-01 -1.09665878e-01 4.39100891e-01 5.46675086e-01
1.03072202e+00 5.48044182e-02 1.85404336e+00 -6.13973677e-01
3.89872715e-02 2.35761315e-01 8.42520446e-02 6.66616023e-01
9.07980800e-01 2.56033301e-01 -2.76350796e-01 2.43638027e-02
9.82495964e-01 4.91573960e-01 -8.99879575e-01 6.84413239e-02
-1.25290203e+00 -2.85155680e-02 1.45752907e-01 6.81015372e-01
-3.01362485e-01 -6.25357509e-01 -2.81559795e-01 -1.56201953e-02
4.79034901e-01 6.48479581e-01 4.66906637e-01 4.57785815e-01
-6.40709221e-01 -4.33476686e-01 1.85301691e-01 3.49962741e-01
9.17728126e-01 4.90260646e-02 5.45035414e-02 8.04572463e-01
5.49545348e-01 1.19998193e+00 2.36157149e-01 -9.95274603e-01
-9.81379002e-02 5.10200620e-01 2.95647711e-01 -4.62566525e-01
-2.39473298e-01 1.45389721e-01 -8.16885293e-01 8.32393229e-01
2.36057311e-01 3.37601337e-03 -9.34369504e-01 8.34444582e-01
4.01447624e-01 -5.05547598e-02 2.60444075e-01 1.21801543e+00
8.36028755e-01 5.16888440e-01 -6.86893463e-01 -8.91420066e-01
1.24110770e+00 -3.65715563e-01 -1.26748359e+00 -5.29409587e-01
4.68172915e-02 -9.08107340e-01 8.89455140e-01 5.41000307e-01
-1.47621512e+00 -2.37369254e-01 -1.32218254e+00 -8.78968239e-02
5.00055611e-01 7.87108764e-02 -1.89565762e-03 2.16078401e-01
-3.48800451e-01 3.96529198e-01 -1.17293835e+00 -1.75565090e-02
4.22656208e-01 3.03317010e-01 -6.13848686e-01 -5.61535895e-01
-5.07371366e-01 5.46588123e-01 -2.20752209e-01 -4.06946279e-02
-4.73321527e-01 -4.95957851e-01 -3.76076311e-01 -2.87020832e-01
-9.19295028e-02 -4.87880468e-01 6.96371377e-01 -1.49038762e-01
-1.84659982e+00 1.40596771e+00 -5.67437232e-01 3.69580314e-02
-3.39326471e-01 2.96026945e-01 -7.69338012e-01 8.90850902e-01
1.96676254e-01 -2.61188358e-01 5.73079944e-01 -1.36312890e+00
-3.01865906e-01 -8.63148808e-01 -4.31317508e-01 4.99369875e-02
7.09473491e-02 4.46680963e-01 3.17849785e-01 1.45192072e-01
3.16399038e-01 -6.64135396e-01 4.32065921e-03 3.14216241e-02
-4.37809259e-01 5.12744248e-01 1.33557451e+00 -2.38322943e-01
1.24568439e+00 -2.19836020e+00 -6.35547757e-01 -1.27915412e-01
4.55677181e-01 5.46408772e-01 8.88751820e-02 6.38551593e-01
6.75857514e-02 -4.05945748e-01 -2.28527412e-01 2.07419723e-01
-9.43140626e-01 -1.73639223e-01 2.54094064e-01 9.51256573e-01
1.22060314e-01 6.69174314e-01 -7.72959769e-01 -5.58168530e-01
4.25972253e-01 6.13084793e-01 -1.95272371e-01 2.41465405e-01
3.04475784e-01 1.27359104e+00 -5.27704537e-01 6.53904974e-01
1.23523355e+00 -7.49221802e-01 1.22741401e-01 -3.40453446e-01
-5.84144890e-01 -1.01605421e-02 -8.02399635e-01 1.12776065e+00
-1.00292884e-01 7.02121556e-01 5.98457873e-01 -3.57948989e-01
1.02038932e+00 1.85704932e-01 1.55223921e-01 -1.14308798e+00
-2.17283174e-01 2.89544016e-01 -8.08218718e-02 -1.00608015e+00
1.79685265e-01 -9.99063492e-01 6.34612858e-01 6.18748128e-01
-4.71241146e-01 -3.59238056e-03 3.15568656e-01 -2.39027664e-01
8.80047023e-01 -3.23646486e-01 3.36971372e-01 -4.19786483e-01
7.44276464e-01 -2.24548921e-01 3.90241891e-01 3.03905737e-02
1.59112051e-01 7.39288509e-01 -1.91382036e-01 -4.56542253e-01
-1.02672327e+00 -9.25316989e-01 -6.08095706e-01 2.14650735e-01
6.49298370e-01 3.41338843e-01 -2.49285564e-01 1.97895899e-01
-3.06879103e-01 3.02988291e-01 -1.18426785e-01 2.23582849e-01
-6.65794075e-01 -6.35559380e-01 -2.32901618e-01 4.33980897e-02
5.91639221e-01 -8.89970303e-01 -9.11000788e-01 5.13733029e-02
-1.33770362e-01 -1.16680610e+00 -6.84643770e-03 -1.26666173e-01
-6.90564275e-01 -1.24725556e+00 -9.36479568e-01 -1.01598859e+00
9.58222985e-01 6.66487396e-01 8.57246518e-01 -8.21404010e-02
-7.55896986e-01 3.27006966e-01 1.57958910e-01 -1.67362019e-01
-2.10782900e-01 -7.35967934e-01 -1.45606488e-01 1.15210675e-01
3.70197237e-01 -6.95106089e-01 -1.18836379e+00 7.53546119e-01
-1.00819278e+00 -1.16617575e-01 5.17514288e-01 1.06583560e+00
1.03348994e+00 -2.87953820e-02 1.66911498e-01 -8.35503161e-01
2.98252434e-01 3.13032895e-01 -9.55578387e-01 8.78993869e-02
-5.00560701e-01 -3.43024433e-01 5.07682502e-01 -3.96174937e-01
-1.57979715e+00 -4.88718539e-01 1.59422681e-01 -1.03258945e-01
-4.20067549e-01 3.56479347e-01 8.20085853e-02 -3.80742013e-01
1.03926861e+00 2.72477984e-01 4.92846102e-01 -2.25066781e-01
-8.54804814e-01 8.79947007e-01 6.85630500e-01 -1.47990501e-02
6.91556931e-01 1.14625049e+00 4.66427058e-01 -1.41871953e+00
-7.03991294e-01 -5.81230521e-01 -2.67668933e-01 -2.50196636e-01
9.27102208e-01 -8.88170362e-01 -7.07800567e-01 5.88543534e-01
-8.92921865e-01 -2.93791533e-01 -1.20114319e-01 1.21372163e+00
-1.52554035e-01 3.98399293e-01 -1.06878924e+00 -7.40643799e-01
-3.98695797e-01 -8.99961889e-01 1.04173779e+00 6.51784480e-01
4.96456623e-01 -1.14774048e+00 2.10674390e-01 4.88622516e-01
4.36223030e-01 3.16840857e-01 7.60811269e-01 4.28077906e-01
-7.63104320e-01 -1.83023289e-01 -2.03748956e-01 1.71546608e-01
4.25097018e-01 1.63215883e-02 -9.43227649e-01 -5.80335975e-01
7.26204276e-01 -3.09288085e-01 4.55682904e-01 1.03635776e+00
7.33187139e-01 1.10737003e-01 -8.85960281e-01 8.94098282e-01
1.84950233e+00 5.76400757e-01 1.20252573e+00 1.81731090e-01
4.21523333e-01 3.05685103e-01 5.91146350e-01 2.38472566e-01
-1.61874026e-01 5.11245191e-01 2.34361127e-01 -5.76349795e-01
-1.27145052e-01 3.55894327e-01 -1.38742581e-01 5.99203050e-01
-2.68025547e-01 -3.84751946e-01 -6.33660734e-01 2.46465370e-01
-7.54603803e-01 -1.35441995e+00 -6.09885693e-01 2.22651553e+00
6.88069820e-01 -1.57497481e-01 -3.36571246e-01 9.63339210e-02
1.08843577e+00 -8.09051022e-02 -6.17109656e-01 4.21781212e-01
-1.18639395e-01 2.16552645e-01 1.74760982e-01 6.83171451e-01
-4.04738486e-01 2.85685211e-01 7.55996609e+00 3.67925376e-01
-1.89538515e+00 -2.65215665e-01 2.55687743e-01 2.19946075e-02
-6.58170402e-01 -2.22370952e-01 -8.68938565e-01 5.38594425e-01
1.82356566e-01 -2.20717028e-01 1.63030237e-01 -5.84676005e-02
3.52616966e-01 -8.00874829e-01 -7.85742104e-01 1.22564340e+00
-2.72872716e-01 -1.15677154e+00 -1.60303965e-01 4.64226395e-01
7.18161464e-01 -1.57163784e-01 2.72115856e-01 -8.17223489e-01
-2.85017759e-01 -7.82015800e-01 -2.74352580e-01 4.73668724e-01
1.67896092e+00 -4.08218533e-01 4.21005785e-01 3.19033831e-01
-7.82202423e-01 1.62793055e-01 -6.34761989e-01 -1.20159864e-01
3.04029465e-01 1.12226236e+00 -7.62028575e-01 1.26115352e-01
6.41898811e-01 7.01362550e-01 1.52250141e-01 7.77820528e-01
-8.42130706e-02 5.64841509e-01 6.97535351e-02 9.38798767e-03
-1.73999578e-01 -6.59320831e-01 5.89832604e-01 7.91173398e-01
3.75583798e-01 6.72411501e-01 2.08626650e-02 1.27646554e+00
5.48714697e-01 -2.86197901e-01 -7.12849200e-01 4.77447249e-02
3.69147509e-01 1.49651909e+00 -9.22743917e-01 -3.88033427e-02
-6.55253947e-01 6.30347908e-01 -4.69566613e-01 8.30085278e-01
-1.74858108e-01 -7.88447797e-01 2.92387515e-01 9.05301392e-01
2.88301498e-01 -1.57984495e-01 1.03076898e-01 -1.36721826e+00
-9.15639177e-02 -3.05433810e-01 -1.47488087e-01 -1.14217639e+00
-1.17319131e+00 5.25698304e-01 -7.66985537e-03 -1.38306320e+00
4.41541523e-01 -6.98209107e-01 -6.33605361e-01 1.17790854e+00
-1.92255843e+00 -5.60647845e-01 -5.10481417e-01 8.22344124e-01
-1.41755809e-04 1.40231237e-01 6.17662907e-01 2.29167089e-01
-3.72435093e-01 -2.43902579e-01 5.21411955e-01 -1.93506986e-01
1.03762054e+00 -8.56941998e-01 -4.14941400e-01 8.14475119e-01
-8.47436249e-01 6.77213728e-01 4.10319120e-01 -6.06127083e-01
-1.30648899e+00 -6.11707807e-01 5.24698198e-01 1.70062706e-01
1.76541790e-01 1.52922392e-01 -9.07356262e-01 4.41105843e-01
5.75355887e-01 6.18914306e-01 1.06376016e+00 -8.81407082e-01
2.75028735e-01 -1.23386398e-01 -1.73378396e+00 1.32076547e-01
6.56671107e-01 -3.83560479e-01 -4.21855688e-01 2.66305774e-01
2.70082980e-01 -6.17765009e-01 -8.74139488e-01 4.13295209e-01
8.90503049e-01 -1.18649232e+00 5.02908349e-01 2.10924834e-01
6.99156642e-01 -4.87689316e-01 2.07903191e-01 -1.24276268e+00
-8.37913930e-01 -5.40507138e-01 6.96408570e-01 6.88642383e-01
1.90622658e-01 -1.25536025e+00 7.20061600e-01 1.17924273e-01
-1.26504347e-01 -4.65509683e-01 -6.13304973e-01 -5.84988475e-01
-4.48176384e-01 6.63061440e-01 2.28622004e-01 4.58692074e-01
2.42909431e-01 7.97585607e-01 4.26683687e-02 1.41441956e-01
1.07922447e+00 3.55406702e-01 2.43178129e-01 -1.38325226e+00
1.23895638e-01 1.86690673e-01 -2.81779706e-01 -1.08902240e+00
-2.71450847e-01 -6.76358104e-01 -2.73835599e-01 -1.82392240e+00
4.18453038e-01 1.69227242e-01 4.20092754e-02 -1.51050404e-01
-2.56234463e-02 5.15053153e-01 -3.64063710e-01 5.52698493e-01
-4.02144283e-01 1.29056245e-01 2.07149744e+00 -5.45902066e-02
-9.27083939e-02 9.26413015e-02 -2.11948857e-01 4.54512388e-01
2.89212555e-01 -3.97318989e-01 -4.48401362e-01 -3.79018039e-01
1.69147685e-01 5.13093412e-01 2.60540217e-01 -1.13475871e+00
2.23556593e-01 -3.00473720e-01 6.40535653e-01 -5.43699145e-01
3.25743258e-01 -6.81993484e-01 2.19641730e-01 6.50206864e-01
-8.74641612e-02 -4.28195745e-01 -3.91044050e-01 2.83828199e-01
-3.68057579e-01 -2.67111123e-01 1.30420172e+00 -5.13341963e-01
-4.08992499e-01 1.36993438e-01 -5.39988160e-01 -2.85159145e-02
1.14992678e+00 -7.29837596e-01 -1.16681325e+00 8.96762460e-02
-5.51927686e-01 -1.69692114e-01 9.80681717e-01 -9.37650084e-01
1.35782540e+00 -1.27112961e+00 -4.98712540e-01 7.91863322e-01
1.95754364e-01 3.22905071e-02 9.40631449e-01 1.20145893e+00
-1.01840103e+00 2.33521834e-01 -6.77886009e-01 -9.51558113e-01
-1.47929287e+00 4.68609810e-01 4.34219092e-01 -4.80658323e-01
-9.80400205e-01 5.65941632e-01 4.74439830e-01 1.65241018e-01
-4.98966724e-01 -5.55082932e-02 -2.93987900e-01 -8.05926800e-01
1.42391419e+00 6.74298942e-01 -1.88672230e-01 -3.25570792e-01
-4.34186250e-01 1.11703658e+00 1.56050846e-01 -1.67968586e-01
1.41989434e+00 -7.85988629e-01 -1.82947129e-01 4.10833597e-01
9.89324272e-01 3.01532686e-01 -1.36775339e+00 -5.13154924e-01
-7.17060745e-01 -9.52389121e-01 1.66661099e-01 -6.79264545e-01
-1.16444612e+00 1.22561681e+00 5.73390126e-01 3.25711519e-01
1.37180722e+00 -1.95331313e-02 7.89635599e-01 1.69541359e-01
3.64525586e-01 -8.54975402e-01 2.44396701e-01 -1.41407430e-01
4.01873648e-01 -1.24741399e+00 3.17548543e-01 -5.66475928e-01
-3.59179765e-01 1.37311566e+00 3.78664434e-01 -2.10177690e-01
5.65010786e-01 8.80887866e-01 8.70339870e-02 -6.90425515e-01
-1.03951526e+00 3.00685912e-02 3.57180610e-02 1.12725389e+00
6.96585596e-01 -2.66607821e-01 -4.52107579e-01 -2.52991050e-01
6.99114382e-01 4.18008745e-01 8.25374186e-01 8.46063673e-01
-6.92986906e-01 -5.81718266e-01 -4.74976063e-01 4.71538007e-01
-9.41002190e-01 2.97213137e-01 2.06015795e-01 3.42379481e-01
-2.82366276e-01 1.14045012e+00 1.27838224e-01 -2.83226166e-02
3.04438561e-01 -4.81690615e-01 9.38097417e-01 -9.88247991e-01
2.06322327e-01 6.84321940e-01 -3.29455286e-01 -3.72881442e-01
-9.15155292e-01 -2.02654943e-01 -1.28931427e+00 -9.50990394e-02
-4.52160448e-01 -8.23787078e-02 3.01643789e-01 6.68479741e-01
2.10035309e-01 1.12826467e-01 8.32523167e-01 -6.86981142e-01
6.80166557e-02 -8.30376565e-01 -1.35864580e+00 5.76526262e-02
8.58534634e-01 -2.61630863e-01 -7.05867767e-01 4.78236191e-02] | [11.388802528381348, -2.630215644836426] |
11b9469f-29fd-4c93-82b3-88d656f77918 | latent-optimal-paths-by-gumbel-propagation | 2306.02568 | null | https://arxiv.org/abs/2306.02568v1 | https://arxiv.org/pdf/2306.02568v1.pdf | Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming | We propose a unified approach to obtain structured sparse optimal paths in the latent space of a variational autoencoder (VAE) using dynamic programming and Gumbel propagation. We solve the classical optimal path problem by a probability softening solution, called the stochastic optimal path, and transform a wide range of DP problems into directed acyclic graphs in which all possible paths follow a Gibbs distribution. We show the equivalence of the Gibbs distribution to a message-passing algorithm by the properties of the Gumbel distribution and give all the ingredients required for variational Bayesian inference. Our approach obtaining latent optimal paths enables end-to-end training for generative tasks in which models rely on the information of unobserved structural features. We validate the behavior of our approach and showcase its applicability in two real-world applications: text-to-speech and singing voice synthesis. | ['Charles Patrick Martin', 'Jing Zhang', 'Christian Walder', 'Xinlei Niu'] | 2023-06-05 | null | null | null | null | ['bayesian-inference', 'singing-voice-synthesis'] | ['methodology', 'speech'] | [ 4.22499403e-02 6.84822321e-01 -1.78998813e-01 -1.90119237e-01
-8.11478555e-01 -5.24042070e-01 7.17012107e-01 -3.48645598e-01
-8.63565803e-02 8.02095890e-01 2.76582867e-01 -1.96815938e-01
-3.66141856e-01 -8.31810892e-01 -1.04104519e+00 -8.91500354e-01
-8.57687145e-02 9.03820753e-01 1.60705596e-01 3.75845954e-02
-6.77866489e-02 3.83804768e-01 -1.44201005e+00 1.47752119e-02
6.52762830e-01 3.56617540e-01 3.61726999e-01 9.47786212e-01
-2.12389335e-01 4.57730651e-01 -3.17642242e-01 -4.03983533e-01
-1.00035124e-01 -7.19309688e-01 -8.49099994e-01 3.07725281e-01
1.25800176e-02 -2.25098878e-01 -8.11249539e-02 1.07201517e+00
1.54240981e-01 4.92973000e-01 1.04104328e+00 -1.34036696e+00
-3.77356559e-01 9.00190830e-01 -1.92770526e-01 1.31095564e-02
2.13293687e-01 -3.23860615e-01 1.55897427e+00 -7.66434968e-01
8.62970054e-01 1.42744279e+00 5.43553889e-01 5.95422387e-01
-1.64870381e+00 -4.64078858e-02 9.90483910e-02 1.00254901e-01
-1.07882929e+00 -3.30394268e-01 7.28083193e-01 -5.65002739e-01
9.00527954e-01 -5.24057560e-02 7.60316610e-01 1.53834534e+00
2.29869843e-01 1.12610137e+00 8.52513611e-01 -5.64648509e-01
5.10723710e-01 2.28499975e-02 7.99454078e-02 9.19266105e-01
2.51227561e-02 1.20457195e-01 -7.70624518e-01 -4.70747083e-01
7.45412529e-01 -2.55291611e-01 -1.59044996e-01 -4.83113974e-01
-9.46959198e-01 1.25130296e+00 -1.45333081e-01 1.61419228e-01
-3.77516836e-01 4.08348799e-01 -1.14491597e-01 -7.48763755e-02
3.63426536e-01 5.45010045e-02 -3.40640396e-01 3.04309167e-02
-1.16391504e+00 4.86854732e-01 1.32923961e+00 7.92902827e-01
6.59277976e-01 3.98896754e-01 -1.04208559e-01 6.56552553e-01
1.07549155e+00 6.69805229e-01 1.00060567e-01 -1.32462978e+00
1.21314980e-01 -5.37410557e-01 2.24486828e-01 -5.70643544e-01
7.61238933e-02 -4.56405550e-01 -5.52507520e-01 2.10736860e-02
5.35565019e-01 -3.65586996e-01 -8.41444552e-01 2.00622511e+00
4.30953890e-01 4.15127248e-01 2.69444045e-02 5.03459454e-01
1.65808156e-01 1.30521441e+00 -8.54441375e-02 -6.53247118e-01
9.52160239e-01 -6.97203100e-01 -9.13729787e-01 1.38982078e-02
-6.45771399e-02 -5.08538365e-01 8.68460536e-01 6.64268911e-01
-1.17665267e+00 -3.56988996e-01 -8.95223916e-01 1.46170974e-01
2.45820969e-01 -2.76024014e-01 4.12315458e-01 6.11668527e-01
-1.16048181e+00 1.22252905e+00 -1.40415168e+00 -9.11705047e-02
7.85131827e-02 1.18227661e-01 -2.56943852e-02 3.14285129e-01
-9.42218065e-01 4.93613303e-01 4.37026352e-01 -8.57605636e-02
-1.62161672e+00 -5.33866882e-01 -7.76702702e-01 1.23417102e-01
2.73677766e-01 -9.00759935e-01 1.43892729e+00 -5.03649771e-01
-2.06816745e+00 2.78205693e-01 -4.45674390e-01 -5.23366809e-01
3.19105387e-01 -1.60637677e-01 3.53004262e-02 1.23843670e-01
-9.41175967e-02 5.19972563e-01 1.58697617e+00 -1.20977437e+00
-3.39035094e-01 -6.12486899e-02 -1.64538473e-01 -8.31761807e-02
-2.23800149e-02 -3.34172785e-01 -3.43145460e-01 -6.27027273e-01
2.89742321e-01 -9.99142766e-01 -2.38922998e-01 -4.62865740e-01
-6.10844672e-01 -4.74758297e-01 3.73384893e-01 -6.78135037e-01
9.61044788e-01 -1.82075822e+00 8.66826117e-01 3.61359119e-01
-3.20518650e-02 -5.29196084e-01 1.19437762e-01 5.17856300e-01
1.89275116e-01 2.99819019e-02 -5.39022565e-01 -7.39469230e-01
5.45777082e-01 7.51094282e-01 -6.44154012e-01 4.22780305e-01
-2.32425183e-01 5.51325798e-01 -8.42823565e-01 -6.64064646e-01
7.16589391e-03 5.66221535e-01 -1.05364370e+00 3.74943584e-01
-8.65545928e-01 3.44550312e-01 -3.61220986e-01 5.34796640e-02
3.34983170e-01 -2.39572644e-01 4.65156555e-01 2.79594183e-01
1.50661856e-01 2.90154368e-01 -1.33161509e+00 1.87347162e+00
-3.80642325e-01 6.57155812e-01 2.58384705e-01 -8.27174127e-01
6.34066641e-01 4.67716157e-01 2.91572660e-01 4.85092759e-01
2.77069714e-02 5.03799180e-03 -4.20802355e-01 -2.84889281e-01
4.50318575e-01 -6.60596848e-01 7.30814114e-02 6.38416588e-01
8.42999339e-01 -2.94084877e-01 5.71976155e-02 3.92033398e-01
5.40472150e-01 5.04256189e-01 -1.55554553e-02 -4.28018242e-01
6.05911985e-02 -3.45343709e-01 4.60855395e-01 1.09987485e+00
2.52725691e-01 4.68225121e-01 8.23636353e-01 2.42740586e-01
-1.09802222e+00 -1.65800071e+00 -2.13559151e-01 1.04901028e+00
-5.49407065e-01 -5.80984592e-01 -1.04222691e+00 -3.68170440e-01
-3.64052176e-01 1.20069814e+00 -4.89360750e-01 3.04748178e-01
-1.84967443e-01 -8.45301390e-01 2.05612451e-01 1.77708790e-01
-7.25225881e-02 -1.05262494e+00 -1.76093698e-01 5.03766239e-01
-3.52132469e-01 -9.21405613e-01 -1.85157105e-01 1.71590280e-02
-1.23551214e+00 -5.67909122e-01 -7.98325121e-01 -3.08353841e-01
2.71828711e-01 -5.30477881e-01 1.16083229e+00 -8.35119367e-01
1.04932681e-01 7.40978241e-01 5.94819039e-02 -2.70057708e-01
-8.60333562e-01 4.79131304e-02 1.55891046e-01 1.59882098e-01
-1.91033274e-01 -9.99366760e-01 -1.76986948e-01 -5.49289845e-02
-6.40918016e-01 -7.47830644e-02 1.65610224e-01 7.93807983e-01
9.16915536e-01 1.80164650e-01 1.74074322e-02 -7.45399296e-01
5.91839492e-01 -6.12420917e-01 -1.01256931e+00 1.71314985e-01
-5.75947821e-01 7.26725161e-01 2.24813551e-01 -2.02370852e-01
-1.34826839e+00 6.17636330e-02 -4.53115016e-01 -4.51376319e-01
-1.25264376e-01 5.74672222e-01 -1.76093608e-01 5.56140780e-01
4.25564826e-01 2.29633331e-01 -1.54758722e-01 -6.36147022e-01
7.85037279e-01 2.74437994e-01 5.32369912e-01 -9.87276793e-01
5.87762475e-01 5.67077816e-01 2.31330305e-01 -1.13105214e+00
-1.01430237e+00 -2.69519091e-02 -4.67703819e-01 -2.24256009e-01
1.11607552e+00 -7.11826444e-01 -7.26145685e-01 3.08070779e-01
-1.50251353e+00 -3.87905627e-01 -5.77528000e-01 6.76896632e-01
-1.02899611e+00 5.18958747e-01 -6.84471011e-01 -1.10574877e+00
-4.67638224e-02 -9.01251495e-01 9.53642011e-01 7.17683733e-02
-1.86093926e-01 -1.35264039e+00 6.86867237e-01 1.14036307e-01
-2.10294291e-01 6.78169727e-02 1.04291940e+00 -3.82445663e-01
-8.43279362e-01 1.97074160e-01 4.67685163e-01 4.74670231e-01
-4.39241141e-01 4.46074635e-01 -1.05813920e+00 -1.01091906e-01
1.00170031e-01 1.73262522e-01 1.08886623e+00 8.41120303e-01
6.64734364e-01 -4.49646592e-01 -2.80877054e-01 5.28769016e-01
1.38803327e+00 -2.30888978e-01 3.35010946e-01 -3.60898823e-01
6.76830411e-01 7.04255939e-01 2.81727109e-02 6.19786501e-01
9.57911387e-02 4.41115975e-01 3.31265777e-01 7.57918239e-01
1.92670986e-01 -8.22366238e-01 6.76536202e-01 1.19491732e+00
-1.72311768e-01 -3.45921516e-01 -7.07480192e-01 9.11938727e-01
-1.80142176e+00 -1.10169315e+00 -1.28035471e-01 2.05730295e+00
9.65698898e-01 6.98793009e-02 1.10245444e-01 -5.36343381e-02
6.08266175e-01 2.99803197e-01 -1.26743928e-01 -5.23009002e-01
2.27899939e-01 5.06319702e-01 1.73482016e-01 1.19445515e+00
-7.25049138e-01 9.74290013e-01 7.52991819e+00 9.95497286e-01
-4.15175110e-01 5.18175781e-01 -8.27543903e-03 7.80362561e-02
-7.95162201e-01 2.28943512e-01 -1.04815471e+00 1.79562017e-01
1.24236572e+00 -4.45379019e-02 6.91900730e-01 9.87522304e-01
1.40133858e-01 7.27454107e-03 -1.10815847e+00 6.27577305e-01
-2.99660742e-01 -1.36552560e+00 -9.76380892e-03 1.39906853e-01
8.89525890e-01 1.76858738e-01 4.73408885e-02 -4.28848341e-02
1.04888940e+00 -7.30683923e-01 8.91141593e-01 6.50827527e-01
2.72638619e-01 -7.17040360e-01 3.47123332e-02 5.14968395e-01
-7.50292361e-01 1.58507854e-01 -3.79808664e-01 2.76797891e-01
5.68137050e-01 7.89217293e-01 -9.62257922e-01 2.62571573e-01
3.69719416e-01 5.37133396e-01 3.47547114e-01 6.05793297e-01
-8.67245436e-01 1.20450318e+00 -7.90798008e-01 -1.70747742e-01
1.57124847e-01 -5.15379071e-01 1.14523292e+00 1.08654523e+00
5.16850233e-01 -8.18601251e-02 -3.02624345e-01 1.36465013e+00
3.54067981e-02 -1.54630899e-01 -4.82378721e-01 -2.38179803e-01
2.28551209e-01 7.44403958e-01 -6.56092346e-01 -1.96929753e-01
-6.77005649e-02 9.52156782e-01 4.49270420e-02 6.37949288e-01
-7.26160407e-01 -1.11411400e-01 6.36694014e-01 -2.26075962e-01
9.07769322e-01 -4.96856064e-01 6.61200956e-02 -1.20185828e+00
-3.33878368e-01 -5.79518437e-01 4.10953164e-01 -7.41693199e-01
-1.17905581e+00 5.37643552e-01 5.34545422e-01 -4.41142023e-01
-8.84951293e-01 -4.95460421e-01 -5.90449631e-01 8.27685833e-01
-9.99532402e-01 -7.98221052e-01 4.56920534e-01 7.84212232e-01
4.84846056e-01 -4.51625176e-02 9.44949269e-01 -3.75137091e-01
-5.02124786e-01 6.65613338e-02 5.64314544e-01 -3.00689012e-01
-1.29049748e-01 -1.61889720e+00 3.67541343e-01 9.82131243e-01
9.31457162e-01 5.00882804e-01 1.29405773e+00 -5.94056129e-01
-1.10083330e+00 -6.97186589e-01 9.16623890e-01 -5.11568785e-01
8.68694961e-01 -4.32856560e-01 -7.13371634e-01 1.03046203e+00
3.97778839e-01 -4.56588477e-01 5.29919922e-01 4.63848799e-01
-1.02376394e-01 2.63057560e-01 -6.32163346e-01 4.95286614e-01
8.00556898e-01 -6.25609159e-01 -8.53326678e-01 5.45373142e-01
6.44812822e-01 -2.28269234e-01 -7.53755569e-01 -1.12303272e-01
4.62212294e-01 -9.20453370e-01 8.91053438e-01 -6.55496240e-01
4.50966597e-01 -4.19714376e-02 -3.32407922e-01 -1.43963981e+00
-1.50323913e-01 -1.27168560e+00 -3.87863696e-01 1.07445812e+00
5.46840131e-01 -3.54901940e-01 7.19920516e-01 1.44839734e-01
7.94853491e-04 -3.97503167e-01 -1.02769530e+00 -6.01669490e-01
1.67999014e-01 -9.54201818e-01 2.82062411e-01 4.32698250e-01
-1.75217584e-01 3.59340072e-01 -5.68302035e-01 5.14954805e-01
1.34142900e+00 1.47003949e-01 4.40760851e-01 -1.20057678e+00
-1.24525750e+00 -1.03831165e-01 1.33736014e-01 -1.34386861e+00
6.23318970e-01 -8.83332014e-01 2.98346907e-01 -1.47244728e+00
7.81688318e-02 3.92247364e-03 -2.58154124e-02 4.59390692e-02
1.19098388e-01 -2.95330048e-01 1.29654869e-01 1.88824490e-01
-4.70437288e-01 7.84594595e-01 9.06469226e-01 1.10759236e-01
-2.95628101e-01 3.20276678e-01 -2.03345865e-01 1.04975820e+00
4.18510705e-01 -1.00917137e+00 -6.21072412e-01 -3.79365921e-01
4.45694238e-01 4.59379822e-01 3.89581501e-01 -6.53494060e-01
1.31021455e-01 -2.19260857e-01 -2.60356009e-01 -6.36865497e-01
5.05840957e-01 -4.28107172e-01 4.01631594e-01 1.92771092e-01
-2.94763982e-01 -5.95700562e-01 -4.34348062e-02 1.02844238e+00
-5.29912412e-02 -6.82311714e-01 7.14631319e-01 -6.09802417e-02
-3.40381205e-01 2.96967447e-01 -8.21025491e-01 1.95384905e-01
5.85172296e-01 2.09713250e-01 4.46944177e-01 -7.47200370e-01
-1.58269286e+00 -1.43125743e-01 -6.43143803e-02 -1.26826316e-01
5.13775110e-01 -1.05693495e+00 -7.79562652e-01 1.07760385e-01
-4.45452780e-01 -1.22351393e-01 2.56423533e-01 6.72859848e-01
-4.14343476e-01 3.94648105e-01 1.50513381e-01 -8.40012491e-01
-9.68583763e-01 2.33818024e-01 4.18590456e-01 -3.85794222e-01
-5.53866804e-01 1.22055674e+00 5.47094122e-02 -2.06555024e-01
2.64705539e-01 -2.67307997e-01 4.80757281e-02 8.15120265e-02
1.38450220e-01 4.02871847e-01 -3.69738489e-01 -2.89366096e-01
7.04638064e-02 2.24652156e-01 1.94133013e-01 -1.03253388e+00
1.38257003e+00 -2.22879767e-01 -1.62074223e-01 8.42507660e-01
9.81970191e-01 -3.63410302e-02 -1.61455631e+00 -2.36282662e-01
-1.51105434e-01 -1.71741635e-01 3.06013703e-01 -1.59118637e-01
-7.64342368e-01 1.21113098e+00 1.51021317e-01 3.53972256e-01
4.45295513e-01 4.54968959e-01 5.63563466e-01 5.90909421e-01
2.82085568e-01 -1.02009690e+00 -6.21130802e-02 4.54673141e-01
7.54677296e-01 -6.25886619e-01 -1.15484305e-01 -1.57347903e-01
-5.36103666e-01 1.05300593e+00 -3.48693937e-01 -1.77746996e-01
1.15410149e+00 3.45301092e-01 -3.98515791e-01 -1.76614374e-02
-8.70025992e-01 -1.55124575e-01 2.58883238e-01 7.28588879e-01
1.27464877e-02 2.56509185e-01 -2.54226979e-02 6.92686737e-01
-4.57678378e-01 -1.40110940e-01 4.50007260e-01 4.89792556e-01
-4.33570057e-01 -1.15583205e+00 -2.17734039e-01 -3.79404016e-02
-6.58012927e-01 -2.35314324e-01 4.41979244e-03 5.50854802e-01
-1.43567875e-01 8.31667423e-01 9.94713679e-02 3.67878415e-02
-1.16518721e-01 5.93441308e-01 8.55275929e-01 -6.68440044e-01
2.44403198e-01 6.05491102e-01 5.67768626e-02 -3.99119884e-01
-4.66081798e-01 -1.13515127e+00 -1.02436507e+00 -3.92813265e-01
-3.45323890e-01 4.55548793e-01 7.86851585e-01 1.20229042e+00
1.26483047e-03 4.56275940e-01 3.55658978e-01 -7.98848808e-01
-8.45279515e-01 -9.76984501e-01 -1.04172194e+00 -1.14612080e-01
2.99777269e-01 -4.96886015e-01 -5.24594188e-01 4.06265438e-01] | [6.886633396148682, 3.8600316047668457] |
67cd68fa-3fb8-49da-a70e-4f042e07310a | interpreting-deep-forest-through-feature | 2305.00805 | null | https://arxiv.org/abs/2305.00805v1 | https://arxiv.org/pdf/2305.00805v1.pdf | Interpreting Deep Forest through Feature Contribution and MDI Feature Importance | Deep forest is a non-differentiable deep model which has achieved impressive empirical success across a wide variety of applications, especially on categorical/symbolic or mixed modeling tasks. Many of the application fields prefer explainable models, such as random forests with feature contributions that can provide local explanation for each prediction, and Mean Decrease Impurity (MDI) that can provide global feature importance. However, deep forest, as a cascade of random forests, possesses interpretability only at the first layer. From the second layer on, many of the tree splits occur on the new features generated by the previous layer, which makes existing explanatory tools for random forests inapplicable. To disclose the impact of the original features in the deep layers, we design a calculation method with an estimation step followed by a calibration step for each layer, and propose our feature contribution and MDI feature importance calculation tools for deep forest. Experimental results on both simulated data and real world data verify the effectiveness of our methods. | ['Yuan Jiang', 'Shen-Huan Lyu', 'Yi-Xiao He'] | 2023-05-01 | null | null | null | null | ['explainable-models'] | ['computer-vision'] | [ 1.82833642e-01 3.36772978e-01 -3.97058487e-01 -7.54311144e-01
-2.61143167e-02 -1.51773999e-02 6.12637639e-01 -9.86022651e-02
3.42209816e-01 1.16351748e+00 2.76715726e-01 -3.39103609e-01
-3.57962519e-01 -1.09862530e+00 -6.83212221e-01 -8.02169740e-01
-1.61403731e-01 6.03013992e-01 7.71941384e-03 -1.35528883e-02
1.64556459e-01 2.40317240e-01 -1.53414869e+00 3.26710820e-01
1.28051150e+00 1.13126504e+00 2.08901584e-01 8.40265304e-02
-5.98200798e-01 7.32283354e-01 -2.19885483e-01 -4.97404516e-01
1.78289518e-01 -1.60322085e-01 -7.59770036e-01 -1.10837802e-01
6.09726161e-02 -4.33238029e-01 -1.46208093e-01 8.47053707e-01
1.14941746e-01 -1.70197979e-01 8.50056291e-01 -1.55584931e+00
-6.99111700e-01 1.02662122e+00 -7.29909122e-01 -9.37239006e-02
-2.47001708e-01 2.70118058e-01 1.10076559e+00 -9.78354812e-01
2.40922138e-01 1.46858788e+00 9.31276143e-01 3.66446733e-01
-1.35576642e+00 -9.76552963e-01 6.07262313e-01 3.48409802e-01
-1.07723880e+00 -1.19632855e-01 7.29854643e-01 -4.54155385e-01
6.47936285e-01 1.73564494e-01 5.24398506e-01 8.84549677e-01
5.24941266e-01 7.57955372e-01 1.30690312e+00 9.23642963e-02
9.85273253e-03 9.10558254e-02 5.50925493e-01 7.33946800e-01
3.89635772e-01 3.38066220e-01 -6.19818628e-01 -1.94862438e-03
8.05849493e-01 5.51288605e-01 -7.33331069e-02 -3.96038413e-01
-9.17089462e-01 1.00522316e+00 1.03589225e+00 -2.96779960e-01
-5.09874463e-01 1.99693576e-01 1.09062612e-01 1.10888258e-01
5.90028882e-01 6.41624033e-02 -6.87599003e-01 1.91599414e-01
-8.68679702e-01 1.93269208e-01 5.03912330e-01 8.23022306e-01
1.10032666e+00 -3.14706936e-02 -2.38751039e-01 7.55598307e-01
5.44880509e-01 2.46936038e-01 3.36591154e-01 -6.28433228e-01
5.51018953e-01 1.02363074e+00 -1.11818008e-01 -1.02141392e+00
-3.96442473e-01 -1.04550910e+00 -1.63408816e+00 1.71392545e-01
1.74900532e-01 4.11025286e-02 -1.17827988e+00 1.71456456e+00
2.89236635e-01 -3.11700720e-02 -3.01023871e-01 9.05903757e-01
7.64935672e-01 5.93692541e-01 1.65729448e-01 -2.68357068e-01
9.90802169e-01 -1.23028982e+00 -6.15805924e-01 -3.27754438e-01
1.33001804e-01 -2.21010029e-01 1.20412254e+00 2.74521828e-01
-6.59390986e-01 -6.86614931e-01 -8.28868866e-01 -1.31381735e-01
-2.67059088e-01 -4.59758379e-02 1.29847729e+00 4.15360451e-01
-7.29924142e-01 9.10654724e-01 -8.33928525e-01 2.85829399e-02
6.91260397e-01 6.24915957e-01 -1.95395797e-01 -3.24129453e-03
-1.24219441e+00 6.11946940e-01 6.52734339e-02 4.77639914e-01
-8.56485128e-01 -6.46783710e-01 -4.37111914e-01 3.70965660e-01
1.65562719e-01 -8.69420528e-01 8.46247733e-01 -1.01198280e+00
-1.01994574e+00 2.57070571e-01 -6.69406235e-01 -5.50533891e-01
7.15046585e-01 -3.12848181e-01 -1.52234420e-01 -5.65782428e-01
3.34014267e-01 7.46585548e-01 8.08032513e-01 -1.22973108e+00
-6.19245112e-01 -6.06149077e-01 -7.17120990e-02 4.96811094e-03
-8.00419897e-02 -6.58432543e-01 8.32843408e-02 -4.28775877e-01
4.46232557e-01 -7.04111755e-01 -5.75769722e-01 -2.19490863e-02
-7.30406225e-01 -5.93784712e-02 5.30594826e-01 -6.33311450e-01
1.37235332e+00 -1.86660755e+00 -9.11805481e-02 2.39591688e-01
7.01710999e-01 -2.81039923e-01 5.93189225e-02 1.86918244e-01
-2.11918443e-01 5.44391215e-01 -5.63553333e-01 -1.18432462e-01
-1.57646358e-01 2.80028820e-01 -4.91425425e-01 -1.89642068e-02
4.64737296e-01 9.41009104e-01 -7.26922691e-01 -4.68908548e-01
6.05054013e-02 2.30747670e-01 -4.31417853e-01 1.09783448e-01
-1.65409580e-01 2.92868316e-01 -5.43035448e-01 6.12983763e-01
1.11018836e+00 -3.90084594e-01 4.38954541e-03 1.47478297e-01
-1.06272124e-01 4.93669629e-01 -9.45119083e-01 8.36474121e-01
-4.69866931e-01 3.20483088e-01 -2.11854383e-01 -7.33611405e-01
1.13640141e+00 -2.21752495e-01 1.76712275e-01 -3.42224121e-01
-4.00189877e-01 1.88717991e-01 1.97949961e-01 -1.27336401e-02
4.21683133e-01 -3.32366854e-01 2.57434368e-01 3.38180631e-01
-2.38166794e-01 3.49679261e-01 -3.05099159e-01 -8.50930512e-02
8.77671003e-01 9.40280408e-02 4.15242970e-01 -2.64852226e-01
3.96594405e-01 -1.09578455e-02 7.22884715e-01 7.24663138e-01
3.03482637e-02 5.71994066e-01 5.72829485e-01 -9.18828726e-01
-7.61908889e-01 -9.40843642e-01 -2.47469276e-01 8.95902038e-01
2.77512729e-01 -1.90987468e-01 -3.69983315e-01 -9.02365983e-01
3.54731828e-01 7.43644178e-01 -8.17092240e-01 -3.52633446e-01
-5.69688566e-02 -1.07381845e+00 9.24243405e-02 6.98365688e-01
9.24503922e-01 -1.12042499e+00 -1.27522469e-01 3.44257385e-01
-2.20396757e-01 -4.28356588e-01 -5.14820814e-02 7.86686361e-01
-1.29934359e+00 -7.82029212e-01 -1.43384859e-01 -3.87104452e-01
6.71780944e-01 4.39890295e-01 1.16363931e+00 1.89230621e-01
6.95394948e-02 -6.10370040e-01 -2.27553807e-02 -3.37469250e-01
-1.46363258e-01 5.33807755e-01 -9.26657096e-02 -6.87200800e-02
4.02971566e-01 -8.64198804e-01 -5.73478222e-01 4.74256963e-01
-5.70733488e-01 6.48812950e-01 9.26323235e-01 1.12677658e+00
6.19630694e-01 1.41429022e-01 6.16232157e-01 -1.04990613e+00
5.12904644e-01 -7.02429056e-01 -2.55730927e-01 1.54386029e-01
-1.18318105e+00 5.23021519e-01 6.48673177e-01 -1.29234239e-01
-1.03801858e+00 5.87201044e-02 5.04915342e-02 -2.06413463e-01
2.48887129e-02 8.13744247e-01 -5.45489252e-01 4.26654756e-01
3.09634686e-01 3.66223216e-01 3.61100174e-02 -6.93593502e-01
1.86797604e-01 5.63480496e-01 2.52525866e-01 -3.34900379e-01
9.63321924e-01 1.89546287e-01 2.64920592e-01 -2.68602431e-01
-7.92937756e-01 1.07588150e-01 -8.39685857e-01 -8.38989094e-02
5.49826920e-01 -8.11595321e-01 -6.24611616e-01 5.96635222e-01
-1.12491035e+00 -6.95277825e-02 -2.33529940e-01 1.60669252e-01
-1.54728577e-01 -9.10541862e-02 -8.75895694e-02 -8.25513482e-01
-4.26529020e-01 -1.05525470e+00 9.13299322e-01 3.20030570e-01
-1.06066063e-01 -8.77160311e-01 -2.16524109e-01 2.29253814e-01
4.01499897e-01 1.74135819e-01 1.40231216e+00 -4.26090688e-01
-9.56300735e-01 -1.25603406e-02 -4.92557168e-01 2.99236983e-01
3.40908617e-01 1.01553850e-01 -1.13141561e+00 2.14978442e-01
-1.22952156e-01 -2.55257394e-02 1.49537349e+00 5.79106748e-01
1.55350590e+00 -6.11272573e-01 -4.82692152e-01 8.43587577e-01
1.26578820e+00 -4.31645624e-02 6.98542655e-01 4.42330450e-01
8.22385132e-01 5.31551242e-01 5.58439970e-01 2.95576602e-01
5.30611217e-01 3.67584497e-01 8.93948257e-01 -3.56566489e-01
-4.39567082e-02 -6.56668007e-01 2.37713471e-01 5.83260119e-01
-4.23275352e-01 3.80046777e-02 -7.70970345e-01 3.77481908e-01
-1.96917260e+00 -1.02232397e+00 -5.60320079e-01 2.19776964e+00
7.45833039e-01 4.01576012e-01 -2.08587393e-01 1.35060206e-01
7.60540009e-01 2.58022517e-01 -1.02095413e+00 -4.58259314e-01
-8.87134746e-02 1.00947574e-01 4.56180036e-01 4.55928385e-01
-9.24864769e-01 9.62140203e-01 6.30475330e+00 6.51300430e-01
-1.12222159e+00 -1.05045006e-01 1.01106226e+00 1.93395257e-01
-7.42861688e-01 3.26189339e-01 -8.56003523e-01 4.48917091e-01
5.58780193e-01 -2.81005114e-01 4.21738714e-01 1.22220480e+00
3.01565289e-01 6.67789578e-02 -1.09056759e+00 4.66284305e-01
-7.52492428e-01 -1.30254638e+00 5.04385948e-01 4.24364597e-01
5.34454763e-01 -2.27985829e-02 1.13304332e-01 4.64460492e-01
4.61368978e-01 -1.43148696e+00 4.91837889e-01 6.06568933e-01
7.18975961e-01 -7.56681800e-01 9.18190420e-01 4.48697746e-01
-1.20336175e+00 -1.55480683e-01 -6.30808771e-01 -5.56822062e-01
-2.43976653e-01 1.00623167e+00 -9.98712182e-01 6.90434992e-01
5.76271236e-01 8.75522256e-01 -7.30884433e-01 7.06038475e-01
-4.04012501e-01 9.35552418e-01 -1.78337574e-01 -5.83283752e-02
4.45357338e-02 -3.00640404e-01 2.90027708e-01 7.29137719e-01
1.47224352e-01 -2.07774386e-01 -3.28345038e-02 1.10517478e+00
-1.63553581e-02 -2.44124196e-02 -5.21372974e-01 1.37549132e-01
5.29936075e-01 1.11936569e+00 -5.00943482e-01 -6.10358901e-02
-1.25192687e-01 5.61462939e-01 4.52447027e-01 1.54303685e-01
-9.73015130e-01 -8.36117268e-02 8.14606369e-01 4.74192053e-01
1.48024410e-01 -5.33304736e-02 -9.28818583e-01 -1.11218452e+00
-1.20997457e-02 -8.01797748e-01 5.44432700e-02 -6.65326953e-01
-1.42551720e+00 5.33019304e-01 -1.99797124e-01 -1.21832228e+00
-3.33522618e-01 -3.14904869e-01 -8.05752814e-01 1.23512149e+00
-1.56631052e+00 -1.28647029e+00 -7.55593777e-01 2.88923562e-01
5.02596200e-01 -5.33778183e-02 7.86878705e-01 -1.13285132e-01
-6.37706518e-01 4.87119228e-01 1.41340956e-01 -2.48764902e-01
2.42213592e-01 -1.33834684e+00 6.16824806e-01 6.18366539e-01
-1.53845012e-01 8.85986030e-01 6.21151268e-01 -7.23358452e-01
-1.03891730e+00 -1.36640751e+00 9.47602808e-01 -1.90043166e-01
4.54384446e-01 -2.90088713e-01 -1.04364026e+00 6.12818182e-01
-2.13798389e-01 -2.40729585e-01 4.85447198e-01 6.66292369e-01
-1.70236439e-01 -5.48319399e-01 -1.07775831e+00 3.61222684e-01
1.37595809e+00 -1.18317813e-01 -3.32406223e-01 1.36244714e-01
8.24856162e-01 5.53041473e-02 -5.18512070e-01 6.41969681e-01
9.23820078e-01 -1.22784150e+00 7.77467787e-01 -7.24670887e-01
1.19990730e+00 -3.18500936e-01 -1.16352960e-01 -1.28721035e+00
-8.03182602e-01 -1.75950363e-01 -1.34189695e-01 1.41501701e+00
6.64246678e-01 -8.47189426e-01 7.30594158e-01 6.13851130e-01
-8.74194503e-02 -1.04599845e+00 -8.25232804e-01 -6.23434007e-01
2.56034508e-02 -3.48462999e-01 1.31347644e+00 7.40467429e-01
-6.18796527e-01 6.72897816e-01 -4.63836282e-01 1.12509891e-01
7.01622903e-01 5.77071965e-01 1.00929320e+00 -1.77048528e+00
-1.16960533e-01 -4.12492990e-01 -2.48585671e-01 -9.44752395e-01
4.51705381e-02 -9.92886841e-01 -1.96057379e-01 -1.83493602e+00
6.79739475e-01 -6.73431218e-01 -3.74855369e-01 7.94815540e-01
-5.43626666e-01 -3.70074004e-01 -3.44768912e-02 5.96069634e-01
1.08484991e-01 9.04237568e-01 1.29573143e+00 -3.52106959e-01
-2.27178752e-01 5.10906100e-01 -1.09742141e+00 8.46819103e-01
5.95926166e-01 -6.79185450e-01 -4.69164014e-01 -4.93674099e-01
4.97003421e-02 -9.47470069e-02 5.77150345e-01 -8.25351417e-01
-2.56620437e-01 -5.35102725e-01 8.16373467e-01 -7.79595971e-01
4.48138714e-02 -8.19888413e-01 5.00215232e-01 5.15894055e-01
-3.75156432e-01 -7.92708248e-02 -1.68294013e-01 6.68497503e-01
-2.27914363e-01 1.10436231e-01 5.82976222e-01 4.35942644e-03
-4.68475968e-01 5.53872705e-01 8.85017365e-02 -3.64891291e-01
6.05783999e-01 -4.04475868e-01 -3.92392039e-01 -4.47872937e-01
-6.67841494e-01 5.30247390e-01 4.31903571e-01 3.28130037e-01
5.55239141e-01 -1.31623626e+00 -6.74390733e-01 3.22784275e-01
-1.12374075e-01 3.78695667e-01 5.04895933e-02 6.70056939e-01
-1.35021195e-01 3.44664991e-01 -3.67779136e-01 -6.43353283e-01
-9.81960177e-01 3.60768199e-01 2.49607190e-01 -7.61254728e-01
-4.62461889e-01 7.57727861e-01 6.14154994e-01 -5.95327616e-01
-3.67966704e-02 -6.22491777e-01 -1.89555570e-01 6.42676055e-02
1.83106422e-01 2.73461610e-01 -1.53941259e-01 -1.99037835e-01
-4.79051828e-01 2.20336169e-01 -1.11484125e-01 7.35340789e-02
1.68818402e+00 -9.05715749e-02 -1.97402954e-01 6.02237105e-01
7.55365252e-01 -1.63491055e-01 -1.41495752e+00 5.30395769e-02
-1.32370189e-01 -4.98591214e-01 9.25657526e-02 -1.03330433e+00
-1.21353555e+00 1.31050539e+00 4.36739802e-01 3.40296596e-01
1.10478294e+00 -2.31300190e-01 6.14712119e-01 1.44964620e-01
4.05663282e-01 -5.81061900e-01 -4.87515420e-01 4.89500165e-01
1.06878626e+00 -1.25295293e+00 2.00052395e-01 -4.91671711e-01
-7.05380023e-01 1.03749442e+00 8.12983453e-01 1.60460904e-01
7.77328432e-01 8.97825211e-02 -1.68670729e-01 6.41175732e-02
-1.14457226e+00 -3.69535089e-02 5.97385131e-02 6.18063748e-01
4.24588859e-01 4.38716352e-01 -2.99837947e-01 1.33865094e+00
-4.74354953e-01 7.32761398e-02 1.37759224e-01 3.48785639e-01
-5.41706085e-01 -9.87118781e-01 -5.57780489e-02 9.80942726e-01
3.24404798e-03 -4.60987419e-01 -7.22917914e-01 8.39357018e-01
2.13366106e-01 6.73866212e-01 -1.21029218e-04 -8.17931116e-01
6.09836988e-02 2.10460141e-01 -1.37628332e-01 -5.17478347e-01
-5.13700724e-01 -3.02039593e-01 -9.35239624e-03 -3.75788212e-01
-2.37664878e-01 -6.45033717e-01 -1.30487394e+00 -6.25900924e-01
-4.50371832e-01 1.67196736e-01 5.95911562e-01 9.76371884e-01
5.12006402e-01 6.27851367e-01 1.00421429e+00 -7.05869615e-01
-6.76123679e-01 -1.14896917e+00 -6.35835052e-01 -2.08737887e-02
3.79739523e-01 -1.01668370e+00 -5.15672207e-01 -1.70221031e-01] | [8.881723403930664, 5.616302967071533] |
015fba58-cdc5-43cd-8ed4-69b85a826f46 | learning-policies-from-human-data-for-skat | 1905.10907 | null | https://arxiv.org/abs/1905.10907v1 | https://arxiv.org/pdf/1905.10907v1.pdf | Learning Policies from Human Data for Skat | Decision-making in large imperfect information games is difficult. Thanks to recent success in Poker, Counterfactual Regret Minimization (CFR) methods have been at the forefront of research in these games. However, most of the success in large games comes with the use of a forward model and powerful state abstractions. In trick-taking card games like Bridge or Skat, large information sets and an inability to advance the simulation without fully determinizing the state make forward search problematic. Furthermore, state abstractions can be especially difficult to construct because the precise holdings of each player directly impact move values. In this paper we explore learning model-free policies for Skat from human game data using deep neural networks (DNN). We produce a new state-of-the-art system for bidding and game declaration by introducing methods to a) directly vary the aggressiveness of the bidder and b) declare games based on expected value while mitigating issues with rarely observed state-action pairs. Although cardplay policies learned through imitation are slightly weaker than the current best search-based method, they run orders of magnitude faster. We also explore how these policies could be learned directly from experience in a reinforcement learning setting and discuss the value of incorporating human data for this task. | ['Christopher Solinas', 'Michael Buro', 'Douglas Rebstock'] | 2019-05-27 | null | null | null | null | ['card-games'] | ['playing-games'] | [-3.09925407e-01 3.09132546e-01 -1.10055715e-01 -6.58872500e-02
-6.54058337e-01 -7.23586380e-01 5.29720783e-01 -3.11266392e-01
-1.00005352e+00 1.23258960e+00 1.23700388e-01 -6.98010027e-01
-4.23772484e-01 -7.52215683e-01 -6.88538909e-01 -4.26782489e-01
-4.02648509e-01 8.59056175e-01 2.83131570e-01 -9.14708674e-01
2.33265936e-01 6.61140457e-02 -1.42143655e+00 5.84357418e-02
5.00989914e-01 7.48657882e-01 1.45296767e-01 9.42001760e-01
2.62578845e-01 1.34384835e+00 -8.08135271e-01 -4.69342619e-01
9.14109290e-01 -5.77047825e-01 -8.29564929e-01 -4.65325534e-01
-3.24502051e-01 -8.55535269e-01 -5.00431001e-01 7.59766400e-01
7.09445417e-01 3.38679880e-01 2.60092020e-01 -1.24993813e+00
-2.97119170e-02 1.08408821e+00 -3.71295035e-01 3.05086821e-01
1.14991210e-01 7.60988772e-01 1.16735363e+00 3.01672459e-01
7.09547341e-01 1.17106533e+00 4.60048169e-01 7.45659709e-01
-1.24341118e+00 -6.05275333e-01 2.94205844e-01 2.34570518e-01
-8.98859084e-01 -2.53091156e-01 6.08814180e-01 -1.08745970e-01
1.08942246e+00 1.97253868e-01 1.17472279e+00 1.10347998e+00
1.09330907e-01 9.49197948e-01 1.31708598e+00 -2.02974841e-01
5.65192461e-01 -3.36357206e-01 -5.68339288e-01 3.60280126e-01
8.78507271e-02 9.76515174e-01 -3.09403181e-01 -2.01522827e-01
9.52128112e-01 -3.52265418e-01 6.73764423e-02 -6.70501292e-01
-7.20440865e-01 1.00251770e+00 4.09850746e-01 -2.27365986e-01
-5.57758152e-01 7.38187313e-01 4.97980386e-01 7.58013248e-01
6.22560009e-02 1.02914560e+00 -5.90573668e-01 -8.43329012e-01
-8.17971408e-01 1.04171145e+00 1.11434686e+00 3.30401421e-01
3.65403414e-01 1.31605133e-01 -1.42903656e-01 3.15140605e-01
3.29570994e-02 7.02260584e-02 3.42725515e-01 -1.53475320e+00
7.22203255e-01 9.90354493e-02 8.14011037e-01 -5.58781922e-01
-6.00677431e-01 -2.33462825e-01 -7.66824558e-02 9.33233380e-01
8.70316088e-01 -7.17494071e-01 -7.34653413e-01 2.04444098e+00
2.61863440e-01 1.10794820e-01 2.00942140e-02 1.02398252e+00
-1.88582137e-01 3.12561423e-01 -8.59969929e-02 3.38999070e-02
9.27588224e-01 -5.55429041e-01 -2.73498952e-01 -5.14830589e-01
6.91113889e-01 -1.90239713e-01 7.39688635e-01 6.78528309e-01
-1.34552944e+00 9.02058333e-02 -9.05390382e-01 2.85581082e-01
-8.04594439e-03 -6.66963220e-01 1.07112324e+00 6.95957839e-01
-8.94761145e-01 1.03488219e+00 -1.03074419e+00 7.28871450e-02
6.08417571e-01 6.20706201e-01 -3.13268676e-02 3.15508723e-01
-1.50279593e+00 1.31409085e+00 3.82552087e-01 1.18119106e-01
-1.23006964e+00 -6.34883046e-01 -6.56918347e-01 1.81655556e-01
1.10729027e+00 -6.20983005e-01 1.85577488e+00 -9.79395032e-01
-2.07618046e+00 4.93830800e-01 7.72147596e-01 -9.71459806e-01
1.07865620e+00 -1.92542560e-02 3.00205648e-01 -2.37428918e-01
7.58749247e-02 6.24629557e-01 4.28393990e-01 -8.20487618e-01
-7.22388506e-01 -1.92240044e-01 8.79890740e-01 6.96958899e-01
3.56598258e-01 -8.58252496e-02 2.11136803e-01 -2.29340404e-01
-6.17433548e-01 -9.88599777e-01 -7.47451663e-01 -1.35099173e-01
-9.03019756e-02 -3.49188186e-02 7.22479299e-02 -4.04343039e-01
1.09041440e+00 -1.65898538e+00 1.13968201e-01 5.78583069e-02
6.78480268e-02 2.34182417e-01 -1.41797259e-01 5.89403927e-01
1.49366856e-01 -7.06184423e-03 1.82965085e-01 -4.17505912e-02
5.15297234e-01 3.59485388e-01 -2.69632310e-01 3.30321848e-01
-2.69397080e-01 1.17648518e+00 -1.00601780e+00 -5.66921569e-02
1.88873112e-01 -3.32125843e-01 -1.06407619e+00 2.01717615e-01
-4.59706247e-01 1.19841650e-01 -4.78572905e-01 8.64453018e-02
2.37493709e-01 2.05363497e-01 5.66176951e-01 6.86711669e-01
-2.58804202e-01 7.21548557e-01 -1.48866856e+00 1.50405133e+00
-5.11623025e-01 3.87279242e-01 4.29816216e-01 -1.12375104e+00
2.38581777e-01 1.08226091e-01 3.57780129e-01 -9.39226449e-01
3.89853656e-01 6.88139582e-03 6.32239819e-01 -1.90625280e-01
5.98873436e-01 -5.98056853e-01 -5.07397354e-01 7.63874590e-01
-3.31177771e-01 -5.48575222e-01 3.12349319e-01 5.96452728e-02
1.19558024e+00 3.57369035e-01 5.09159923e-01 -1.66855678e-01
-2.36169487e-01 3.74128073e-01 7.33369350e-01 1.39504111e+00
-4.80047762e-01 1.05504982e-01 1.03301334e+00 -5.88801026e-01
-1.10018742e+00 -8.98717105e-01 4.05194670e-01 1.21509647e+00
1.21688813e-01 -2.19262689e-01 -6.35515988e-01 -4.92633998e-01
2.60544091e-01 8.34173799e-01 -8.06200564e-01 -3.21245432e-01
-5.86319268e-01 -6.30215943e-01 7.38536417e-01 5.73256314e-01
4.76360828e-01 -1.12581253e+00 -1.14339900e+00 5.87359607e-01
8.63504931e-02 -5.14926076e-01 -4.23644513e-01 3.58345926e-01
-4.99724209e-01 -1.18490779e+00 -3.85613292e-01 -1.05041765e-01
-3.80737819e-02 -1.54358804e-01 1.09925175e+00 3.62561010e-02
-2.48303607e-01 2.19229460e-01 2.03478765e-02 -6.22437119e-01
-4.92632687e-01 -5.06463386e-02 2.86555856e-01 -7.06460834e-01
1.62503347e-01 -5.63511193e-01 -7.27677882e-01 3.18643183e-01
-5.37946105e-01 2.27650017e-01 3.73829752e-01 1.11718750e+00
4.86076847e-02 1.50300771e-01 3.61449748e-01 -9.40541327e-01
1.23468649e+00 -4.24791306e-01 -1.31227207e+00 -1.37000769e-01
-4.78716999e-01 4.04189348e-01 8.32594275e-01 -5.94738781e-01
-1.04772949e+00 -1.50668979e-01 -6.34217486e-02 -1.81509823e-01
1.14297099e-01 4.17884737e-01 2.01385528e-01 1.87610641e-01
8.51166427e-01 7.97991455e-03 4.05019194e-01 -1.94732457e-01
5.24028003e-01 3.29483330e-01 2.59905159e-01 -9.93071675e-01
5.48423469e-01 3.83612365e-01 -8.05692822e-02 -2.30082601e-01
-4.99586612e-01 2.28431616e-02 -2.85343509e-02 -1.48219749e-01
4.19821084e-01 -8.87918293e-01 -1.58886147e+00 5.65880299e-01
-6.85583353e-01 -1.16068327e+00 -6.92992330e-01 3.38312536e-01
-1.15857577e+00 5.34539260e-02 -7.86868334e-01 -1.14095581e+00
1.19714327e-01 -1.06237674e+00 4.26661462e-01 3.01762730e-01
-2.14379817e-01 -7.62875736e-01 3.22819144e-01 3.42608452e-01
5.62063932e-01 -5.58117926e-02 3.43552768e-01 -4.56612349e-01
-6.18090332e-01 -1.03422306e-01 2.94606626e-01 8.11475702e-03
-2.58379281e-01 -3.95341158e-01 -5.34456491e-01 -2.11638153e-01
-1.26722470e-01 -6.04986072e-01 4.88665819e-01 7.18451023e-01
6.61391199e-01 -5.59780836e-01 -1.55457467e-01 4.17566866e-01
1.16279924e+00 3.15959066e-01 7.28957355e-01 8.22232723e-01
1.10330455e-01 5.65165102e-01 6.62647188e-01 7.99661875e-01
6.08904898e-01 8.93384159e-01 6.71904683e-01 3.46947998e-01
3.53093445e-01 -6.73532605e-01 4.10677910e-01 -1.90045252e-01
-2.40790546e-01 -2.61065084e-02 -7.06976235e-01 5.36954343e-01
-2.11979699e+00 -1.57651103e+00 4.18868780e-01 2.20119619e+00
1.04629076e+00 7.31216609e-01 6.31015897e-01 -6.71309531e-02
2.75089473e-01 3.94943319e-02 -9.13870037e-01 -7.50322998e-01
2.48830959e-01 2.60528952e-01 9.55893457e-01 7.87146330e-01
-7.54514396e-01 1.18119001e+00 6.73604393e+00 9.41261768e-01
-7.14427948e-01 -1.59844220e-01 5.74485719e-01 -7.68861532e-01
-6.12084903e-02 2.93996722e-01 -4.91379023e-01 5.60335696e-01
9.00105119e-01 -3.58337522e-01 1.07110107e+00 9.30907071e-01
5.58352113e-01 -6.32413030e-01 -1.05393302e+00 7.59158432e-01
-6.72435522e-01 -1.52952993e+00 -5.76256633e-01 3.53176594e-01
6.36187971e-01 1.47714391e-01 2.67034426e-04 8.36751521e-01
1.53758061e+00 -1.12698805e+00 1.10937786e+00 1.50124088e-01
5.01376450e-01 -9.15465117e-01 6.52246356e-01 7.17555165e-01
-7.85756528e-01 -5.63988805e-01 -3.00989896e-01 -1.18925881e+00
1.83247894e-01 -9.26515386e-02 -7.73853481e-01 1.39133573e-01
4.18111652e-01 1.40281975e-01 1.13771476e-01 8.65209401e-01
-4.69189793e-01 5.79363048e-01 -7.89447904e-01 -5.32597780e-01
6.48596168e-01 -1.87140882e-01 4.14755911e-01 3.97832841e-01
-1.94863796e-01 4.16018754e-01 1.88532308e-01 1.11792243e+00
1.69756666e-01 -4.68962848e-01 -5.84438860e-01 5.22389598e-02
4.05665606e-01 8.08863819e-01 -4.50947434e-01 -4.28103730e-02
4.68260609e-02 7.99222171e-01 6.13584518e-01 1.42899796e-01
-8.14829528e-01 -1.47584289e-01 1.45143259e+00 -4.88057919e-02
4.34453100e-01 -1.19363032e-01 -2.37427816e-01 -1.06047797e+00
-1.08179986e-01 -1.14797103e+00 4.69683886e-01 -6.06459081e-01
-1.04135787e+00 1.64162908e-02 8.09447467e-02 -9.72020268e-01
-9.33010459e-01 -5.49715519e-01 -7.05040872e-01 7.89748967e-01
-1.22589040e+00 -4.68119591e-01 4.90627021e-01 2.87155896e-01
3.18797857e-01 2.56883837e-02 4.29530710e-01 -2.17915967e-01
-3.63315850e-01 4.41877693e-01 1.75195143e-01 1.76133364e-01
2.27812737e-01 -1.40996194e+00 7.15860009e-01 5.83510339e-01
-2.14941264e-03 2.45970905e-01 1.06568718e+00 -3.56245756e-01
-1.33013403e+00 -1.73971623e-01 1.01819756e-02 -6.31306767e-01
9.43636000e-01 -3.82982254e-01 -2.90523022e-01 6.57448471e-01
-7.49975964e-02 -3.07793349e-01 1.36726469e-01 3.63802195e-01
-4.03207503e-02 7.35347047e-02 -1.05504632e+00 1.07401955e+00
1.15500653e+00 -4.20137227e-01 -6.87189341e-01 -1.43878773e-01
3.57321769e-01 -8.26361299e-01 -3.18224609e-01 -2.61118829e-01
6.87607229e-01 -1.16284180e+00 9.32735085e-01 -1.15506828e+00
3.96040589e-01 -1.32251844e-01 2.64113545e-01 -1.81310046e+00
-3.16326112e-01 -1.17823458e+00 1.10553257e-01 5.20366013e-01
3.21484625e-01 -5.35318434e-01 1.37835371e+00 1.10503399e+00
2.71999896e-01 -6.66168451e-01 -1.27725756e+00 -9.88931000e-01
6.01274669e-01 -6.28209710e-01 6.41740680e-01 4.93288666e-01
5.11684537e-01 1.40760779e-01 -8.01622093e-01 -1.81881413e-01
5.75600207e-01 7.09242150e-02 9.83141899e-01 -8.42012525e-01
-9.43835974e-01 -6.62149012e-01 -2.60746926e-01 -1.12450290e+00
1.44821435e-01 -5.16459703e-01 3.43224823e-01 -1.30010200e+00
4.30877320e-02 -5.76883793e-01 -6.61257133e-02 5.43822765e-01
-1.47620738e-01 -2.73397744e-01 5.79588652e-01 -2.31923148e-01
-7.65984356e-01 4.67163146e-01 1.25154936e+00 -1.07508125e-02
-2.80255526e-01 2.45146200e-01 -9.51408625e-01 5.77148557e-01
9.37835753e-01 -4.86299753e-01 -4.58234429e-01 -3.64427328e-01
6.52355850e-01 5.35851479e-01 2.74052888e-01 -7.27208972e-01
3.31635386e-01 -6.94202125e-01 -4.02258858e-02 1.01925567e-01
3.95495892e-01 -5.45722187e-01 1.90155074e-01 8.45037460e-01
-4.57811475e-01 1.01757199e-02 3.02553535e-01 6.80068076e-01
2.22337857e-01 -1.60121426e-01 5.33159435e-01 -5.57962239e-01
-9.24381435e-01 5.96267246e-02 -8.73109698e-01 5.10536492e-01
9.24863279e-01 -2.36086607e-01 -1.75958470e-01 -1.03443241e+00
-4.71389890e-01 6.04521751e-01 4.26368654e-01 1.40809923e-01
1.85962185e-01 -8.81835938e-01 -6.15806699e-01 -1.63144827e-01
-2.43316993e-01 -1.70629799e-01 2.19436139e-01 4.82751995e-01
-5.44890881e-01 2.06136346e-01 -4.88063753e-01 1.52007848e-01
-8.40243936e-01 4.58859622e-01 9.42894936e-01 -8.49517584e-01
-4.57716733e-01 9.02304351e-01 6.55633435e-02 -5.36054075e-01
3.20831011e-03 -1.98078737e-01 1.99668989e-01 -1.72645852e-01
4.67385948e-01 2.76941806e-01 -2.69568294e-01 8.02253038e-02
-2.65907168e-01 -2.76685834e-01 -2.17031181e-01 -6.60512388e-01
1.47141802e+00 7.32709467e-02 4.88383532e-01 4.74884734e-02
3.85174096e-01 -3.50542843e-01 -2.00878835e+00 1.72256827e-01
-6.42885789e-02 -4.87087756e-01 1.20566748e-01 -1.05453074e+00
-7.65110731e-01 5.06927371e-01 1.44141257e-01 3.16381812e-01
6.59500301e-01 -3.78071249e-01 6.04855299e-01 5.84153652e-01
9.06477869e-01 -1.66410851e+00 -1.11162283e-01 6.15716875e-01
2.67571688e-01 -1.18768060e+00 -5.06435111e-02 4.32221174e-01
-8.85504842e-01 7.80981898e-01 6.77269876e-01 -3.68043542e-01
2.83315063e-01 5.82128346e-01 2.14036167e-01 -1.19406536e-01
-1.17702758e+00 -4.69487578e-01 -5.46336114e-01 7.04509377e-01
-1.55944884e-01 2.09928289e-01 -3.51369560e-01 8.21168363e-01
-6.21207058e-01 2.43261576e-01 9.63962674e-01 1.06722999e+00
-2.90942669e-01 -1.22487557e+00 -3.05664808e-01 6.32361054e-01
-5.64021111e-01 -1.08429594e-02 -2.33344436e-01 9.84496057e-01
-2.33566895e-01 9.14549589e-01 6.83305860e-02 -1.44540817e-01
3.28857511e-01 -3.30735207e-01 8.14550400e-01 -5.42755723e-01
-7.45306313e-01 -4.76912856e-01 4.00979131e-01 -9.33912277e-01
1.23904891e-01 -6.68350875e-01 -1.07983804e+00 -7.86034107e-01
-2.64476627e-01 2.69810021e-01 3.53561342e-01 1.00734258e+00
1.73177630e-01 2.42963478e-01 3.87525558e-01 -1.06753933e+00
-1.42707503e+00 -5.46345949e-01 -8.22905898e-01 3.52805525e-01
2.28889942e-01 -8.36668193e-01 -4.24307406e-01 -7.05536485e-01] | [3.6492295265197754, 1.6597737073898315] |
804844fc-7d76-41d9-a011-35a64796e81b | scanbank-a-benchmark-dataset-for-figure | 2106.15320 | null | https://arxiv.org/abs/2106.15320v1 | https://arxiv.org/pdf/2106.15320v1.pdf | ScanBank: A Benchmark Dataset for Figure Extraction from Scanned Electronic Theses and Dissertations | We focus on electronic theses and dissertations (ETDs), aiming to improve access and expand their utility, since more than 6 million are publicly available, and they constitute an important corpus to aid research and education across disciplines. The corpus is growing as new born-digital documents are included, and since millions of older theses and dissertations have been converted to digital form to be disseminated electronically in institutional repositories. In ETDs, as with other scholarly works, figures and tables can communicate a large amount of information in a concise way. Although methods have been proposed for extracting figures and tables from born-digital PDFs, they do not work well with scanned ETDs. Considering this problem, our assessment of state-of-the-art figure extraction systems is that the reason they do not function well on scanned PDFs is that they have only been trained on born-digital documents. To address this limitation, we present ScanBank, a new dataset containing 10 thousand scanned page images, manually labeled by humans as to the presence of the 3.3 thousand figures or tables found therein. We use this dataset to train a deep neural network model based on YOLOv5 to accurately extract figures and tables from scanned ETDs. We pose and answer important research questions aimed at finding better methods for figure extraction from scanned documents. One of those concerns the value for training, of data augmentation techniques applied to born-digital documents which are used to train models better suited for figure extraction from scanned documents. To the best of our knowledge, ScanBank is the first manually annotated dataset for figure and table extraction for scanned ETDs. A YOLOv5-based model, trained on ScanBank, outperforms existing comparable open-source and freely available baseline methods by a considerable margin. | ['Jian Wu', 'Edward A. Fox', 'William A. Ingram', 'Sampanna Yashwant Kahu'] | 2021-06-23 | null | null | null | null | ['table-extraction'] | ['miscellaneous'] | [-4.93717194e-02 4.22579229e-01 -1.56030282e-01 -1.81072131e-01
-9.67691362e-01 -7.70746589e-01 5.19420147e-01 3.53336871e-01
-5.27015030e-01 8.32833827e-01 1.61678419e-02 -6.91219628e-01
-3.30635458e-02 -1.09808397e+00 -1.09750640e+00 -1.07918411e-01
2.60369092e-01 6.63572431e-01 1.41532188e-02 1.06178232e-01
2.53453106e-01 1.01947367e+00 -1.51258361e+00 3.31213295e-01
7.27192700e-01 8.38766575e-01 -6.00797795e-02 6.92160070e-01
-5.47422469e-01 4.54894930e-01 -1.10242426e+00 -7.80865252e-01
1.02599740e-01 -2.50278533e-01 -8.84522498e-01 -1.09704651e-01
1.06889045e+00 -8.14082146e-01 -4.96668577e-01 6.89778805e-01
5.05540133e-01 -2.47256950e-01 7.40213752e-01 -1.18455088e+00
-9.50012028e-01 9.04842138e-01 -6.36997938e-01 4.09254164e-01
3.89862657e-01 -2.08152473e-01 8.61034989e-01 -9.24734712e-01
9.84662771e-01 1.21779847e+00 6.00734174e-01 4.41920727e-01
-9.00455296e-01 -8.13319325e-01 -2.36393556e-01 6.63057715e-02
-1.08956909e+00 -5.54845929e-01 5.94082057e-01 -3.20162624e-01
1.01414776e+00 1.22964911e-01 7.71838605e-01 1.15300930e+00
-2.23178491e-02 8.92123282e-01 8.45379651e-01 -8.06232512e-01
1.33539056e-02 2.60453403e-01 1.83255777e-01 8.53668213e-01
8.24331582e-01 -8.36867094e-01 -7.20423520e-01 3.17730933e-01
9.05019104e-01 -4.80621457e-01 -2.44936779e-01 -1.79713629e-02
-1.15023267e+00 5.91491699e-01 1.12575598e-01 6.01068556e-01
-1.31493211e-01 5.09788021e-02 4.12232965e-01 8.53367522e-02
5.44755399e-01 4.06379580e-01 -4.72766250e-01 -2.14203134e-01
-1.37762773e+00 4.21443403e-01 9.33022201e-01 1.27206659e+00
5.39150059e-01 4.41576280e-02 -2.61108186e-02 7.17459023e-01
1.70521975e-01 6.00152194e-01 3.89189482e-01 -7.17973888e-01
9.12425935e-01 9.48936164e-01 -2.00649321e-01 -1.15970170e+00
-2.78892338e-01 -2.64063716e-01 -7.43874669e-01 2.22435802e-01
8.42756808e-01 2.16884792e-01 -1.12049925e+00 1.08454251e+00
2.08353803e-01 -6.63499713e-01 -8.85791034e-02 5.91463268e-01
1.46575320e+00 8.22474241e-01 -7.72678927e-02 1.10702410e-01
1.53845358e+00 -4.68090862e-01 -9.37650502e-01 -1.12744339e-01
5.22737324e-01 -9.17737901e-01 1.21061563e+00 7.65485346e-01
-1.45010686e+00 -3.71911705e-01 -1.22130275e+00 -5.89240015e-01
-1.12642753e+00 5.38423419e-01 3.62983674e-01 9.11699355e-01
-9.53346372e-01 7.64998198e-01 -6.90150142e-01 -4.63015854e-01
1.11017740e+00 2.39739880e-01 -4.81756866e-01 -3.17981350e-04
-7.82354832e-01 8.77146721e-01 1.02454990e-01 1.58197194e-01
-9.52569097e-02 -8.82479668e-01 -7.83483982e-01 2.06384793e-01
4.81762141e-01 -3.64679456e-01 1.31725216e+00 -4.09158558e-01
-1.05870152e+00 1.39089322e+00 8.15686882e-02 -4.03024614e-01
6.73846424e-01 -2.78000444e-01 -3.69360715e-01 5.77769756e-01
1.89705670e-01 5.58381617e-01 4.72759366e-01 -1.13343871e+00
-2.61333346e-01 -4.77253109e-01 -1.49884865e-01 -3.40189844e-01
-6.35554433e-01 3.28630209e-02 -8.34074020e-01 -8.83236468e-01
-1.47050455e-01 -4.12463009e-01 4.08395112e-01 2.63400674e-01
-4.18429703e-01 -4.21590328e-01 1.05576456e+00 -1.08694577e+00
1.25057685e+00 -1.66890407e+00 -2.96671152e-01 1.39657274e-01
3.66956383e-01 5.23203969e-01 1.31107002e-01 4.29286808e-01
1.54462680e-01 7.41531134e-01 -3.47263187e-01 -2.90009141e-01
4.36130166e-01 -2.14915276e-02 -2.54912287e-01 3.54769766e-01
4.21430290e-01 8.71727228e-01 -4.12056357e-01 -8.13383520e-01
6.56276494e-02 5.15098155e-01 -2.85383016e-02 -5.47983646e-02
-3.20071161e-01 -1.89469591e-01 -4.48682308e-01 9.15480793e-01
9.25409496e-01 -2.45072901e-01 3.28439251e-02 -2.27387309e-01
-1.40879005e-01 4.13375258e-01 -1.09476888e+00 1.36129880e+00
-2.53973007e-01 1.16636324e+00 5.62970750e-02 -8.23020637e-01
9.45898712e-01 1.17858328e-01 2.27338493e-01 -9.77471888e-01
2.57490516e-01 4.52968657e-01 -4.22350794e-01 -3.26802313e-01
7.87817836e-01 2.92672485e-01 2.91874446e-02 5.66017568e-01
1.96848676e-01 -3.57649326e-01 9.74184453e-01 7.99278796e-01
9.65498090e-01 3.92563462e-01 1.29902482e-01 1.88317355e-02
5.19296944e-01 2.37338141e-01 -2.23242529e-02 6.07224345e-01
8.23784322e-02 7.25009918e-01 7.17891395e-01 -4.36423182e-01
-1.42931092e+00 -7.43921161e-01 -2.98707485e-01 4.99985337e-01
-5.05069494e-01 -4.31254238e-01 -1.16482031e+00 -6.38217688e-01
-6.13586009e-02 5.42697906e-01 -4.25626278e-01 3.68406087e-01
-8.39526653e-01 -4.29335266e-01 8.40403259e-01 6.08960032e-01
5.68961561e-01 -1.18900824e+00 -6.38091207e-01 2.34738737e-01
2.42323905e-01 -1.41628730e+00 -6.18938394e-02 1.60895735e-01
-7.04785168e-01 -1.33903229e+00 -1.18675435e+00 -7.54550815e-01
7.37465203e-01 -1.42471716e-01 1.31433761e+00 3.02108556e-01
-4.29676384e-01 7.26682484e-01 -3.74019474e-01 -7.84833848e-01
-5.54678023e-01 2.28649035e-01 -2.94469059e-01 -5.29295206e-01
5.28831780e-01 -4.13015664e-01 -1.58174455e-01 -2.57858872e-01
-1.27775741e+00 -6.73530474e-02 8.06799650e-01 4.55573827e-01
4.33219314e-01 9.27179232e-02 3.30199271e-01 -1.13444769e+00
7.26221263e-01 -6.77916855e-02 -7.95556366e-01 2.68471658e-01
-6.68151438e-01 -3.04778181e-02 7.37963676e-01 -3.14360596e-02
-9.97225821e-01 -3.43382776e-01 -1.36925757e-01 -1.68594077e-01
-4.09265161e-01 5.94801307e-01 -3.42840284e-01 1.89065963e-01
3.66924018e-01 -1.08252034e-01 -2.27904558e-01 -8.42837155e-01
3.24461430e-01 8.18161011e-01 7.61383116e-01 -5.33457696e-01
1.01463759e+00 1.50606841e-01 1.25180557e-01 -9.74116445e-01
-6.03152156e-01 -2.69375235e-01 -1.08696651e+00 -3.14911067e-01
7.28898704e-01 -6.84599817e-01 -5.83567798e-01 5.77658296e-01
-1.33640993e+00 -3.80670160e-01 -1.39026493e-01 1.64401099e-01
-1.07813202e-01 3.62770975e-01 -7.39745915e-01 -6.78283751e-01
-3.58022839e-01 -7.69389331e-01 1.15267277e+00 4.23691064e-01
-2.09207788e-01 -7.01229155e-01 -3.40391308e-01 5.26057601e-01
9.44916680e-02 4.55853492e-01 9.33606088e-01 -6.40807748e-01
-7.31010139e-01 -2.87675679e-01 -6.46739721e-01 1.08099706e-01
-2.40668431e-01 5.97554088e-01 -8.85864973e-01 7.68216029e-02
-5.48606157e-01 -4.92074132e-01 9.17998075e-01 1.99740484e-01
1.26163971e+00 -5.35188854e-01 -3.62449676e-01 2.91328639e-01
1.30044138e+00 1.93760440e-01 8.01882625e-01 8.88964653e-01
7.65782654e-01 6.66556656e-01 1.72067583e-01 2.80514210e-01
4.61223274e-01 2.12004453e-01 1.23512551e-01 -7.02570975e-02
-3.63655001e-01 -1.52761936e-01 1.03831179e-01 8.99665952e-01
-5.13043217e-02 -7.45299578e-01 -1.16638446e+00 5.42338252e-01
-1.20232332e+00 -8.13741922e-01 -6.30108953e-01 1.65552258e+00
1.01608014e+00 4.23773080e-01 1.81218073e-01 5.20132482e-01
3.51010293e-01 1.13868758e-01 -3.23583364e-01 -4.87940818e-01
-2.50990450e-01 8.18151534e-01 5.79733968e-01 -2.12154478e-01
-1.02062380e+00 7.85092831e-01 5.81448603e+00 8.15617800e-01
-9.29330945e-01 -3.41755629e-01 8.97079468e-01 -2.23012082e-02
-1.41809821e-01 -4.04206365e-01 -1.09981811e+00 2.61415988e-01
1.19474399e+00 4.36115712e-02 -1.79165304e-02 7.88487732e-01
1.75610274e-01 -2.63041317e-01 -1.03098857e+00 8.68983030e-01
1.41428769e-01 -1.79406977e+00 3.27110171e-01 1.85956657e-01
3.36949110e-01 -5.74875951e-01 1.01735346e-01 1.26424894e-01
1.35526970e-01 -1.30187941e+00 1.03429222e+00 5.45951784e-01
8.90903652e-01 -7.90064216e-01 7.67804861e-01 -1.01264954e-01
-9.16563928e-01 4.82600152e-01 -4.11097854e-01 2.18776643e-01
-1.42230749e-01 8.05316985e-01 -8.54049444e-01 5.69890141e-01
1.11424673e+00 6.52386248e-01 -1.02342176e+00 9.67374802e-01
-1.92137837e-01 7.00087488e-01 -2.54028708e-01 -3.61507475e-01
3.12403023e-01 -1.68689415e-01 1.82308137e-01 1.51902747e+00
5.26677072e-01 8.20527151e-02 -5.24133801e-01 1.17348504e+00
-7.85626590e-01 1.87402546e-01 -5.66303253e-01 -7.57332861e-01
5.78674197e-01 1.28685176e+00 -1.44183719e+00 -4.92096156e-01
-5.45809746e-01 6.80163026e-01 2.74703234e-01 1.80585667e-01
-5.58270991e-01 -8.49320412e-01 -1.66040644e-01 2.35328928e-01
5.36191106e-01 -4.53334570e-01 -5.54005027e-01 -8.93358648e-01
3.82323533e-01 -1.15525341e+00 4.15927529e-01 -1.01805806e+00
-1.13464129e+00 5.82830846e-01 -2.06228085e-02 -9.99087751e-01
-3.19233187e-03 -1.10286772e+00 -2.83941180e-01 6.77225649e-01
-1.31815195e+00 -1.24323368e+00 -2.84936637e-01 1.77013010e-01
5.61332285e-01 -2.53596127e-01 5.73103845e-01 4.09689307e-01
-8.39248657e-01 5.89162707e-01 2.82359064e-01 7.00396717e-01
7.88428366e-01 -1.53741622e+00 6.45408213e-01 8.26914310e-01
4.63542104e-01 6.19856954e-01 3.56723517e-01 -7.31694102e-01
-1.56090856e+00 -7.68414497e-01 9.60919023e-01 -5.54272294e-01
6.61551893e-01 -6.52905047e-01 -1.13372195e+00 6.48989558e-01
4.16390330e-01 -3.45864236e-01 4.93559748e-01 -3.12759697e-01
-2.82596737e-01 -3.26047949e-02 -1.03549993e+00 4.14457679e-01
7.24414289e-01 -3.33032012e-01 -6.91803217e-01 2.37805098e-01
5.20971596e-01 -6.65229261e-01 -1.01767969e+00 -1.10740416e-01
5.91497183e-01 -8.73919845e-01 9.49200153e-01 -2.76945472e-01
9.59170341e-01 -7.38056097e-03 3.13416541e-01 -7.71117568e-01
2.82213509e-01 -5.07604122e-01 -3.22929561e-01 1.66245866e+00
5.15985191e-01 -2.40472481e-01 1.14498734e+00 7.91402161e-01
-1.96953490e-01 -6.37016416e-01 -7.67796218e-01 -7.12407649e-01
3.85328054e-01 -2.92212635e-01 6.54732227e-01 9.37260449e-01
-3.01347941e-01 1.95086867e-01 1.57042667e-02 -3.27560574e-01
4.27510709e-01 -9.74059775e-02 9.95862126e-01 -1.41160750e+00
3.59069794e-01 -7.73786306e-01 -1.34872332e-01 -7.44369745e-01
6.42270148e-02 -7.78171539e-01 -3.14122826e-01 -2.09315252e+00
6.76137023e-03 -7.39596486e-02 4.41144168e-01 6.62956119e-01
1.71420723e-01 4.92211193e-01 1.83414936e-01 2.65895128e-01
-2.82359719e-01 1.77535176e-01 1.28233933e+00 -2.94560909e-01
-4.40363586e-02 -4.80656952e-01 -6.54450655e-01 6.27913475e-01
6.00706398e-01 -4.84098524e-01 1.59767255e-01 -2.76533723e-01
4.67646897e-01 -3.67000788e-01 2.81193554e-01 -1.03396308e+00
1.90780431e-01 1.46614090e-01 1.01913595e+00 -1.30600750e+00
9.84617975e-03 -6.17236733e-01 -3.54369223e-01 -2.99224077e-04
-1.22535974e-01 8.58697668e-02 6.97474003e-01 2.94723868e-01
-1.28808141e-01 -4.18061763e-01 4.18335170e-01 -3.68823737e-01
-2.71846026e-01 5.99065982e-02 -8.68830860e-01 -2.68152216e-04
6.41932905e-01 -5.64286232e-01 -5.52914500e-01 -2.80906081e-01
-4.01616842e-01 -5.13385311e-02 4.94330108e-01 1.89344242e-01
5.82314134e-01 -1.05248392e+00 -5.24199545e-01 -3.29379216e-02
-2.83251584e-01 4.77848977e-01 -2.05187261e-01 3.95745099e-01
-1.15763938e+00 7.49585748e-01 -4.47848231e-01 -5.11990562e-02
-1.31161189e+00 3.45084816e-01 -2.13899866e-01 -3.89639944e-01
-8.06460440e-01 6.31638885e-01 -5.40487111e-01 -3.86019647e-01
4.34152514e-01 -5.98048747e-01 -5.11112213e-01 4.39608634e-01
5.75173318e-01 6.14082098e-01 4.97254878e-01 -5.77029228e-01
-2.68979281e-01 4.03492242e-01 -5.31054735e-02 -4.47555408e-02
2.02761889e+00 1.39667884e-01 -2.32372224e-01 3.30455393e-01
1.22559547e+00 4.13936108e-01 -6.71425879e-01 1.73087165e-01
2.45269254e-01 -1.96392685e-01 1.09580927e-01 -8.91638994e-01
-1.10793519e+00 9.38706756e-01 1.93863735e-01 4.57242072e-01
9.74200487e-01 -8.63150284e-02 1.00136232e+00 6.17387295e-01
-1.28931150e-01 -1.21403897e+00 1.97021857e-01 3.91100854e-01
8.88338685e-01 -1.16086698e+00 6.86648071e-01 -3.69304061e-01
-4.29872535e-02 2.00373149e+00 5.43366849e-01 1.98078975e-01
1.96731135e-01 4.17005032e-01 -1.14600576e-01 -5.11754930e-01
-1.01385124e-01 2.89987419e-02 6.32010758e-01 6.84534132e-01
6.74203396e-01 -4.70111132e-01 -3.60358626e-01 6.36926830e-01
-6.16748691e-01 1.18149808e-02 9.76000786e-01 1.19069266e+00
-1.93507344e-01 -1.29989731e+00 -8.67500007e-01 7.00717032e-01
-7.82866597e-01 -6.17334843e-02 -1.07268560e+00 1.45420599e+00
-1.16468094e-01 6.35988295e-01 2.31788248e-01 3.05017263e-01
2.95892209e-01 1.64568305e-01 6.82009876e-01 -3.82034659e-01
-4.72328395e-01 -1.31477155e-02 3.93327743e-01 -1.13193013e-01
-6.42356038e-01 -6.20533824e-01 -1.30517387e+00 -6.24523878e-01
-4.93883826e-02 -8.29898641e-02 8.44970107e-01 8.01803172e-01
3.02605867e-01 7.20156133e-01 -2.29136080e-01 -8.15099657e-01
-5.45806251e-02 -8.95950317e-01 -4.85045522e-01 1.10141568e-01
1.15727492e-01 -3.45854282e-01 -1.34312257e-01 5.16562879e-01] | [11.655952453613281, 2.806732654571533] |
cbfe3ff9-cb0f-4f13-833d-fa0546ed1772 | exploring-the-trade-offs-unified-large | 2304.09138 | null | https://arxiv.org/abs/2304.09138v1 | https://arxiv.org/pdf/2304.09138v1.pdf | Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Task | Recently, ChatGPT and GPT-4 have emerged and gained immense global attention due to their unparalleled performance in language processing. Despite demonstrating impressive capability in various open-domain tasks, their adequacy in highly specific fields like radiology remains untested. Radiology presents unique linguistic phenomena distinct from open-domain data due to its specificity and complexity. Assessing the performance of large language models (LLMs) in such specific domains is crucial not only for a thorough evaluation of their overall performance but also for providing valuable insights into future model design directions: whether model design should be generic or domain-specific. To this end, in this study, we evaluate the performance of ChatGPT/GPT-4 on a radiology NLI task and compare it to other models fine-tuned specifically on task-related data samples. We also conduct a comprehensive investigation on ChatGPT/GPT-4's reasoning ability by introducing varying levels of inference difficulty. Our results show that 1) GPT-4 outperforms ChatGPT in the radiology NLI task; 2) other specifically fine-tuned models require significant amounts of data samples to achieve comparable performance to ChatGPT/GPT-4. These findings demonstrate that constructing a generic model that is capable of solving various tasks across different domains is feasible. | ['Tianming Liu', 'Dajiang Zhu', 'Xiang Li', 'Dinggang Shen', 'Quanzheng Li', 'Wei Liu', 'Gang Li', 'Lin Zhao', 'Zhengliang Liu', 'Chong Ma', 'Haixing Dai', 'Xiaowei Yu', 'Chao Cao', 'Lu Zhang', 'Zihao Wu'] | 2023-04-18 | null | null | null | null | ['specificity'] | ['natural-language-processing'] | [-8.40340108e-02 4.43358272e-01 -2.74627090e-01 -4.14578617e-01
-1.28748798e+00 -4.26262498e-01 3.77653867e-01 4.53712106e-01
-5.13456464e-01 6.39575660e-01 4.29649323e-01 -7.77044594e-01
-6.25235558e-01 -6.17154777e-01 -2.04929337e-01 -1.82952777e-01
-1.46271855e-01 1.08637559e+00 1.35636061e-01 -2.10032821e-01
1.86652586e-01 3.37345600e-01 -8.85713637e-01 6.06101692e-01
1.13338065e+00 5.41054904e-01 3.75423938e-01 6.34637773e-01
-2.29249552e-01 1.17522407e+00 -5.05381882e-01 -4.57600683e-01
-1.35403886e-01 -8.05332735e-02 -1.15017569e+00 -2.34607980e-01
3.14068466e-01 -3.56890969e-02 -6.99613318e-02 6.26613140e-01
6.84289157e-01 5.15653864e-02 6.82400942e-01 -8.72118890e-01
-7.69506931e-01 7.94634819e-01 -2.37933040e-01 4.97679621e-01
5.61887324e-01 2.57040083e-01 1.10117209e+00 -3.14646780e-01
6.56949580e-01 1.27897596e+00 8.25638473e-01 5.87391436e-01
-1.25307190e+00 -5.85837483e-01 8.07350352e-02 1.40827298e-02
-1.32767820e+00 -2.50775456e-01 4.16656673e-01 -3.69047225e-01
1.34738612e+00 1.09401077e-01 5.25579572e-01 1.17421305e+00
6.57446980e-01 7.52033293e-01 1.30406988e+00 -3.37117702e-01
2.35353470e-01 1.36469707e-01 3.56970549e-01 7.16624439e-01
2.26574197e-01 -2.89414376e-01 -5.09036660e-01 -3.75428408e-01
8.49291146e-01 -4.29545164e-01 3.51377986e-02 3.33720475e-01
-1.47850478e+00 9.27981436e-01 2.93712169e-01 6.02504492e-01
-3.41180712e-01 -1.33171380e-01 4.99993801e-01 3.87018770e-01
5.46457767e-01 8.15455377e-01 -6.22634113e-01 -3.83807510e-01
-8.40773702e-01 4.65113074e-01 1.12589192e+00 9.09159184e-01
1.49228573e-01 -3.76125157e-01 -4.15730387e-01 1.26949561e+00
2.20994428e-01 2.15834349e-01 8.16942334e-01 -8.73606920e-01
7.06274450e-01 6.93269312e-01 -3.91373873e-01 -1.00668418e+00
-9.18241680e-01 -4.38592494e-01 -5.30357003e-01 -4.58313465e-01
4.38204795e-01 -9.10151154e-02 -6.12833142e-01 1.78834212e+00
1.64651982e-02 -2.68480957e-01 1.39295891e-01 5.85649133e-01
1.07241523e+00 3.13399315e-01 6.89298809e-01 1.38104022e-01
1.74341655e+00 -8.39856386e-01 -5.99884152e-01 -7.97862113e-01
1.11652100e+00 -8.53115320e-01 1.36798716e+00 3.74718219e-01
-1.20231211e+00 -3.72523904e-01 -5.41407824e-01 -4.77114201e-01
-1.99391320e-01 8.20815843e-03 9.25102293e-01 5.65386176e-01
-1.20893586e+00 8.40829462e-02 -7.13441074e-01 -6.40820980e-01
2.87723213e-01 1.55170977e-01 -3.83155733e-01 -3.07418466e-01
-1.24370730e+00 1.41581428e+00 4.58669066e-01 -1.54761374e-01
-4.99478310e-01 -7.65969217e-01 -9.16422129e-01 1.91332906e-01
4.05089289e-01 -9.56992984e-01 1.70070863e+00 -2.57023126e-01
-1.15098464e+00 1.12036598e+00 -1.70449317e-01 -5.59774876e-01
3.98407787e-01 2.00058132e-01 -4.60911840e-01 3.36955786e-01
4.52723503e-01 5.74329555e-01 2.74256885e-01 -7.68544137e-01
-4.01919067e-01 -3.20488214e-01 2.63061464e-01 3.29128593e-01
-2.12411165e-01 1.51576698e-01 -3.35591525e-01 -8.21105480e-01
2.75054649e-02 -9.52005029e-01 -3.75614524e-01 -3.70061845e-02
-2.94799805e-01 -4.49384362e-01 1.54012874e-01 -5.24026155e-01
1.51736152e+00 -1.93885648e+00 -2.02197999e-01 -1.20416870e-02
5.36286652e-01 1.29757434e-01 -2.29684383e-01 6.41233087e-01
-3.83010134e-02 3.43644530e-01 -3.25781137e-01 -1.91277936e-01
-1.26822636e-01 6.16191447e-01 2.05699936e-01 -2.18589641e-02
2.44129077e-01 1.21482074e+00 -9.03247237e-01 -1.12559104e+00
4.90977615e-02 -4.19811569e-02 -9.04647648e-01 -1.81949288e-01
-4.35186923e-01 4.14937347e-01 -7.60759890e-01 5.74786425e-01
2.77258486e-01 -6.81965053e-01 3.75857562e-01 1.23642169e-01
5.00426553e-02 6.01853073e-01 -5.65400422e-01 1.58154416e+00
-6.92599297e-01 3.79583895e-01 -2.25085262e-02 -9.15090144e-01
6.26563132e-01 4.07746017e-01 3.71383578e-01 -8.89759362e-01
9.49083194e-02 2.27897376e-01 4.70036030e-01 -9.44769204e-01
3.68640631e-01 -7.11826622e-01 -3.14523429e-01 6.50760651e-01
-1.20047964e-01 -3.33477348e-01 3.69800359e-01 3.54230911e-01
1.24169695e+00 -5.06896615e-01 5.38908899e-01 -5.45094311e-01
5.71928859e-01 2.80757487e-01 3.41743678e-01 9.83302593e-01
-2.85730034e-01 3.81665498e-01 5.78754961e-01 1.12320092e-02
-6.02246523e-01 -8.55957866e-01 -4.76936668e-01 1.05036724e+00
-3.68626177e-01 -4.99139577e-01 -6.25319064e-01 -5.96081316e-01
-8.03287327e-02 9.58704591e-01 -5.39095640e-01 -6.28366470e-02
-5.49658954e-01 -8.11660588e-01 9.34660375e-01 4.98407632e-01
4.47499484e-01 -1.18167794e+00 -4.35247988e-01 3.26097101e-01
-7.34545350e-01 -1.49132907e+00 -3.31302881e-01 6.25104159e-02
-1.11108685e+00 -1.07610321e+00 -5.30228972e-01 -1.00066972e+00
5.80120027e-01 1.32896364e-01 1.27966559e+00 2.93303337e-02
-1.82826862e-01 6.71313703e-01 -4.24157619e-01 -3.94643754e-01
-8.55544746e-01 4.36017007e-01 -4.06101555e-01 -7.16054797e-01
5.79959273e-01 -2.87506074e-01 -2.51110941e-01 2.90162414e-01
-9.20519948e-01 2.39740565e-01 8.35096955e-01 7.72875011e-01
2.80715883e-01 7.04953000e-02 6.47253335e-01 -1.11089635e+00
1.27698493e+00 -7.53447890e-01 1.31313071e-01 2.98233509e-01
-4.74702954e-01 4.72472534e-02 3.59909147e-01 -5.20023584e-01
-1.28712440e+00 -8.09380412e-01 -4.22932506e-01 3.24437290e-01
-5.24951890e-02 1.19857264e+00 3.39366794e-01 1.16599482e-02
8.50166440e-01 2.19547912e-03 2.24035695e-01 -3.25203538e-01
5.62336594e-02 6.08292282e-01 2.28425324e-01 -1.12725246e+00
4.59766388e-01 2.48765901e-01 -3.35922688e-01 -9.82251287e-01
-1.18915534e+00 -2.64980882e-01 -2.10761517e-01 9.24699977e-02
8.57837081e-01 -8.31803918e-01 -6.42073035e-01 1.34795874e-01
-8.99620056e-01 -6.25979543e-01 -1.27012879e-01 6.45526588e-01
-5.64723492e-01 4.58828956e-01 -1.05576730e+00 -4.15450573e-01
-3.07172805e-01 -1.22677803e+00 1.14658737e+00 -1.28945097e-01
-8.78413677e-01 -1.59207284e+00 -3.34219597e-02 9.34942842e-01
3.58975828e-01 -4.52932306e-02 1.53749740e+00 -9.46556866e-01
-1.26704574e-01 -2.48324990e-01 -4.09265161e-01 1.83429152e-01
1.87397692e-02 -4.01331753e-01 -5.61049163e-01 -1.34629533e-02
4.53332216e-01 -4.31631058e-01 3.05868030e-01 4.27228928e-01
1.09719372e+00 -2.71131903e-01 -3.39068562e-01 1.98355362e-01
1.20006430e+00 1.69569179e-01 3.06690991e-01 4.56184477e-01
2.77082324e-01 5.49895227e-01 5.53439200e-01 1.74892962e-01
7.92873502e-01 4.30928290e-01 -1.45637885e-01 1.94060579e-01
-2.00091928e-01 -1.95068061e-01 1.64479762e-01 9.60405707e-01
1.37564853e-01 -8.23632926e-02 -1.47897518e+00 4.99051511e-01
-1.67010617e+00 -6.94837809e-01 -9.79846939e-02 1.67488170e+00
1.04642844e+00 4.44939077e-01 -1.90068215e-01 -1.12402104e-01
2.27047384e-01 3.74289379e-02 -3.56381148e-01 -6.70145869e-01
-3.42243165e-02 3.92787397e-01 1.59591883e-02 3.56384873e-01
-5.46791852e-01 8.57585013e-01 6.93110943e+00 1.01034153e+00
-8.86401951e-01 2.74986297e-01 6.35557473e-01 -7.57581294e-02
-2.52731144e-01 -2.58814096e-01 -6.78642511e-01 2.42973402e-01
1.14762735e+00 -3.61214876e-01 1.20548829e-01 5.97139418e-01
4.28716928e-01 -3.41567725e-01 -1.31570005e+00 7.64830410e-01
4.29026932e-02 -1.20165968e+00 2.57713437e-01 1.98159978e-01
3.70426983e-01 2.59715058e-02 -1.16855083e-02 7.97621489e-01
3.33825588e-01 -1.11642158e+00 5.64937830e-01 2.87303895e-01
4.69535232e-01 -2.64482707e-01 6.60149753e-01 6.82870686e-01
-8.53737116e-01 -1.70272976e-01 -2.87177384e-01 -2.89974660e-01
1.99023604e-01 4.22785908e-01 -1.06357288e+00 5.54497182e-01
4.01794255e-01 5.54294229e-01 -6.64387643e-01 8.19226086e-01
-2.12421492e-01 6.86321080e-01 -2.61888027e-01 7.06135854e-02
5.81890643e-01 1.57307640e-01 3.52347016e-01 1.49521291e+00
1.43162832e-01 3.03201407e-01 3.86664808e-01 8.09765697e-01
1.93911687e-01 2.80536741e-01 -3.92640084e-01 -3.14390302e-01
5.83518267e-01 1.07903266e+00 -7.59307504e-01 -3.57253313e-01
-6.42947495e-01 3.45511258e-01 6.68097794e-01 1.30090892e-01
-7.88326800e-01 1.64849281e-01 6.25910878e-01 2.83154398e-01
-6.96289167e-02 -3.22834373e-01 -6.32115960e-01 -1.08107209e+00
-3.50053050e-02 -1.16400743e+00 7.85219431e-01 -8.67456794e-01
-1.74633789e+00 5.54626048e-01 2.16764644e-01 -9.07300472e-01
-3.45890522e-01 -7.58831143e-01 -3.02376330e-01 8.47137630e-01
-1.51267159e+00 -1.20418215e+00 -1.82980984e-01 7.60695636e-01
7.26631999e-01 1.16615787e-01 1.05469048e+00 2.69699663e-01
-5.01723588e-01 5.25205851e-01 -2.89019227e-01 3.12278241e-01
7.93199658e-01 -9.63037789e-01 3.07474524e-01 2.90950954e-01
-2.70275891e-01 1.09068418e+00 4.68013614e-01 -8.01619887e-01
-1.16099405e+00 -7.08616316e-01 1.25395131e+00 -7.24999726e-01
9.55266595e-01 -1.45745859e-01 -9.99262214e-01 9.84356523e-01
-1.48639724e-01 -3.55825037e-01 1.04601610e+00 3.50034773e-01
-2.25878894e-01 2.80611396e-01 -1.29470241e+00 7.00454772e-01
1.10392666e+00 -6.84388936e-01 -1.13749003e+00 5.96047282e-01
7.60681510e-01 -5.95900357e-01 -1.35853732e+00 1.51018724e-01
4.13691670e-01 -8.36597085e-01 1.03332198e+00 -6.56883597e-01
7.30773807e-01 3.26911271e-01 6.37847930e-03 -1.05210364e+00
-5.94714582e-01 -2.59909868e-01 2.89884180e-01 7.75112391e-01
5.63875496e-01 -9.66879129e-01 5.42358994e-01 9.29695129e-01
-2.63579428e-01 -9.58671987e-01 -9.09465134e-01 -7.45273471e-01
6.49154484e-01 -8.38204205e-01 1.08973205e-01 1.06311321e+00
3.92041177e-01 3.73102337e-01 1.71057642e-01 -2.27107527e-03
3.01409096e-01 -5.63233756e-02 4.15333390e-01 -1.36652899e+00
-4.30245101e-01 -4.72385377e-01 -1.06040128e-01 -7.52470672e-01
3.20443213e-01 -1.21179867e+00 -3.17414552e-01 -1.89647532e+00
2.79644966e-01 -6.69293284e-01 1.08057246e-01 7.94403493e-01
-1.84473202e-01 -2.38118526e-02 1.75594836e-01 2.54117846e-01
-2.65589952e-01 1.78939290e-02 1.41995990e+00 -1.49574280e-02
-2.72228997e-02 -1.22862726e-01 -1.40283644e+00 7.63923109e-01
7.43684769e-01 -4.27729875e-01 -6.44667506e-01 -5.92579305e-01
3.23378861e-01 4.12577838e-01 2.17292666e-01 -9.19838667e-01
3.43576610e-01 -2.48181239e-01 1.13332197e-02 -2.18993589e-01
2.69643873e-01 -4.89414185e-01 -1.15883723e-01 4.47430164e-01
-6.13496959e-01 6.59884606e-03 5.34118772e-01 3.75894338e-01
-2.81735450e-01 -4.07511950e-01 6.06487334e-01 -5.74508727e-01
-6.93660080e-01 6.11965060e-02 -7.90408075e-01 6.11718237e-01
8.37646782e-01 -2.48237669e-01 -4.29685980e-01 -2.75542468e-01
-1.01376438e+00 4.66160685e-01 1.10720381e-01 4.20365840e-01
5.14609039e-01 -8.47812176e-01 -8.00062776e-01 3.28831039e-02
2.38099098e-01 7.60489255e-02 5.00496268e-01 1.18928897e+00
-6.02298915e-01 9.16186810e-01 3.78648415e-02 -5.17385125e-01
-1.15512478e+00 5.44204891e-01 2.42421567e-01 -9.64795113e-01
-8.03054154e-01 5.84423900e-01 4.06723887e-01 -7.16793418e-01
1.69620812e-02 -6.53319895e-01 -5.16794287e-02 -4.67426218e-02
3.93855006e-01 1.07157670e-01 5.52219301e-02 -2.47226611e-01
-3.22982788e-01 2.43826658e-01 -4.27126169e-01 -8.02953765e-02
1.22224271e+00 -6.19480871e-02 -2.22691372e-01 4.76535320e-01
1.00129330e+00 -2.31435835e-01 -3.83704424e-01 -3.22358817e-01
2.43950441e-01 -6.20139465e-02 -1.31448144e-02 -1.05443454e+00
-5.50817370e-01 6.01567388e-01 -1.17578626e-01 4.71883342e-02
8.54057431e-01 3.18707705e-01 6.90133095e-01 5.36248207e-01
6.69708252e-01 -8.56855571e-01 1.63718164e-01 7.09403753e-01
8.70687366e-01 -1.13924992e+00 -4.37785350e-02 -4.52780247e-01
-8.52861226e-01 1.01497245e+00 5.46522021e-01 1.00689434e-01
7.35213995e-01 3.52086037e-01 9.92310643e-02 -6.18838012e-01
-9.37594771e-01 6.29287958e-02 1.51246846e-01 5.53903162e-01
9.31455433e-01 7.05679134e-02 -5.40313125e-01 6.41497016e-01
-6.00625753e-01 2.72451073e-01 4.15598065e-01 1.14043105e+00
-1.61036640e-01 -1.02837670e+00 -3.59722584e-01 8.20886374e-01
-3.63921762e-01 -3.84205103e-01 -1.94099456e-01 1.06145632e+00
-2.19364852e-01 9.51603234e-01 -1.14699647e-01 1.31750241e-01
3.16624522e-01 2.99861491e-01 5.01312912e-01 -1.07460356e+00
-8.68676364e-01 -1.08195968e-01 6.20281398e-01 -5.10046542e-01
-3.33569020e-01 -6.94836438e-01 -1.29760969e+00 -4.25709724e-01
-2.53500566e-02 2.12350503e-01 3.16001624e-01 1.12462401e+00
2.85730392e-01 7.03939557e-01 -3.88698399e-01 -3.33453059e-01
-7.01063275e-01 -1.03237855e+00 -5.29662430e-01 1.02313429e-01
-7.07427561e-02 -5.14678836e-01 -1.22234290e-02 -3.33203644e-01] | [8.8742036819458, 8.50212574005127] |
24c60e53-cf8a-43c7-b7f0-6a18eb28134b | bdis-bayesian-dense-inverse-searching-method | 2205.03133 | null | https://arxiv.org/abs/2205.03133v1 | https://arxiv.org/pdf/2205.03133v1.pdf | BDIS: Bayesian Dense Inverse Searching Method for Real-Time Stereo Surgical Image Matching | In stereoscope-based Minimally Invasive Surgeries (MIS), dense stereo matching plays an indispensable role in 3D shape recovery, AR, VR, and navigation tasks. Although numerous Deep Neural Network (DNN) approaches are proposed, the conventional prior-free approaches are still popular in the industry because of the lack of open-source annotated data set and the limitation of the task-specific pre-trained DNNs. Among the prior-free stereo matching algorithms, there is no successful real-time algorithm in none GPU environment for MIS. This paper proposes the first CPU-level real-time prior-free stereo matching algorithm for general MIS tasks. We achieve an average 17 Hz on 640*480 images with a single-core CPU (i5-9400) for surgical images. Meanwhile, it achieves slightly better accuracy than the popular ELAS. The patch-based fast disparity searching algorithm is adopted for the rectified stereo images. A coarse-to-fine Bayesian probability and a spatial Gaussian mixed model were proposed to evaluate the patch probability at different scales. An optional probability density function estimation algorithm was adopted to quantify the prediction variance. Extensive experiments demonstrated the proposed method's capability to handle ambiguities introduced by the textureless surfaces and the photometric inconsistency from the non-Lambertian reflectance and dark illumination. The estimated probability managed to balance the confidences of the patches for stereo images at different scales. It has similar or higher accuracy and fewer outliers than the baseline ELAS in MIS, while it is 4-5 times faster. The code and the synthetic data sets are available at https://github.com/JingweiSong/BDIS-v2. | ['Maani Ghaffari', 'Jianyu Lin', 'Qiuchen Zhu', 'Jingwei Song'] | 2022-05-06 | null | null | null | null | ['stereo-matching-1'] | ['computer-vision'] | [ 1.88835546e-01 2.08795890e-02 4.37246226e-02 -8.76391828e-02
-1.00645542e+00 3.29842642e-02 1.30602598e-01 -3.82823683e-02
-6.68250024e-01 6.24991000e-01 1.23713687e-01 -3.67265463e-01
-1.03698045e-01 -6.79890752e-01 -6.61336541e-01 -1.05522525e+00
4.11954910e-01 3.95205736e-01 4.38470811e-01 -1.86494030e-02
2.91339278e-01 5.49269021e-01 -1.83072531e+00 -5.04363440e-02
1.00291944e+00 1.16448188e+00 7.50016630e-01 3.39798212e-01
7.58400634e-02 1.09635226e-01 -1.38682246e-01 -1.51120022e-01
4.43337739e-01 6.15547299e-02 -1.70717001e-01 -3.53986979e-01
4.49217677e-01 -5.33765554e-01 -4.61142510e-01 1.34125137e+00
9.95866477e-01 -7.00461417e-02 5.37196100e-01 -7.98222423e-01
5.06976200e-03 -1.48554653e-01 -7.58478522e-01 1.54264227e-01
7.00326450e-03 8.90003666e-02 1.37147546e-01 -8.39496195e-01
5.75673223e-01 8.95850658e-01 6.90099418e-01 3.48438114e-01
-9.76488888e-01 -8.45077813e-01 -4.75456953e-01 8.44473243e-02
-1.41594493e+00 -2.99603641e-01 6.29013956e-01 -4.26418900e-01
5.93349040e-01 8.48725811e-02 6.61017716e-01 7.93792069e-01
9.77850497e-01 3.34816843e-01 1.19670987e+00 -3.05926710e-01
1.20258950e-01 -7.65286982e-02 -1.16143405e-01 7.91327596e-01
4.52611059e-01 5.69196343e-01 -3.13777059e-01 -3.24393809e-01
1.45182288e+00 2.52601385e-01 -5.45960486e-01 -4.32959795e-01
-1.11334491e+00 5.91782451e-01 3.67545635e-01 2.39969328e-01
-5.52432418e-01 2.18893830e-02 3.62344414e-01 -1.62820876e-01
3.31566751e-01 -1.37751149e-02 -3.39872926e-01 -1.30248100e-01
-6.12156332e-01 -8.20229277e-02 5.23800671e-01 1.06327510e+00
6.70672894e-01 -1.58721469e-02 -1.55702531e-01 9.43971276e-01
1.47397816e-01 5.75013578e-01 4.84887213e-01 -1.13127005e+00
3.61614041e-02 2.59162664e-01 1.88094750e-02 -1.14629710e+00
-5.36443353e-01 -5.23851991e-01 -1.34170187e+00 4.49866742e-01
3.25040668e-01 1.04997411e-01 -1.14728773e+00 1.39629567e+00
4.87112284e-01 3.12017560e-01 -2.94828117e-01 1.01267111e+00
1.08744133e+00 2.09464490e-01 -3.44481111e-01 -3.14425349e-01
1.40597224e+00 -5.61839223e-01 -8.26896667e-01 -1.94840774e-01
3.90687615e-01 -1.01863313e+00 9.56352234e-01 4.50656563e-01
-1.00839818e+00 -3.66800070e-01 -9.15191472e-01 -7.74910524e-02
2.47071728e-01 2.31985793e-01 5.92870712e-01 6.19221091e-01
-1.23375034e+00 4.81512457e-01 -1.11674678e+00 -7.67619163e-02
4.95515317e-01 6.00624323e-01 -5.00432849e-01 -2.67879397e-01
-6.74677074e-01 7.51518846e-01 -1.08556524e-01 4.68731791e-01
-6.74945116e-01 -7.25416303e-01 -9.20661926e-01 -3.16733897e-01
8.30492154e-02 -9.36630249e-01 8.89160872e-01 -7.94221222e-01
-1.59452426e+00 1.21922028e+00 -3.66970003e-01 9.11274832e-03
5.53692639e-01 -6.07384108e-02 4.60432433e-02 1.25173688e-01
4.37293723e-02 5.62519550e-01 5.25811076e-01 -1.13833368e+00
-4.08557713e-01 -5.94664991e-01 -2.51297861e-01 3.74013633e-01
1.88954562e-01 -2.16792539e-01 -7.34854460e-01 -5.29109299e-01
7.08324134e-01 -9.89012599e-01 -4.04931277e-01 3.67879897e-01
-2.81966597e-01 3.45484525e-01 -1.09862611e-02 -7.55179167e-01
8.58161271e-01 -2.33422232e+00 -3.34998578e-01 3.42677571e-02
1.80987015e-01 -8.34436566e-02 7.39484504e-02 -8.55391622e-02
3.39054167e-02 -4.75258917e-01 -9.64676663e-02 -4.13165182e-01
-3.79048795e-01 1.79371849e-01 2.43943200e-01 9.37711000e-01
-6.92646444e-01 4.48716283e-01 -6.29279375e-01 -6.49647772e-01
4.05088007e-01 7.53718674e-01 -5.69520295e-01 1.41316205e-01
4.17430192e-01 7.60171771e-01 -1.15981296e-01 7.76273847e-01
1.17051303e+00 5.02576828e-02 -4.41402644e-02 -6.71259820e-01
-1.91034228e-01 -1.09940067e-01 -1.27740610e+00 2.10707617e+00
-5.05330861e-01 4.81843472e-01 5.43992162e-01 -6.08840883e-01
9.35115874e-01 1.95325777e-01 6.01479471e-01 -9.38381493e-01
4.47147310e-01 7.69032717e-01 -5.35947196e-02 -3.76344085e-01
4.11567360e-01 -3.25469881e-01 3.38688850e-01 -1.96893662e-01
-2.10813493e-01 -2.44037285e-01 -3.23244154e-01 -2.71332294e-01
9.19605911e-01 1.54873073e-01 1.96833178e-01 -6.34440601e-01
3.12139779e-01 4.20511961e-02 9.86394882e-01 6.07091546e-01
-3.04945618e-01 1.12734056e+00 5.28173558e-02 -5.03733635e-01
-8.62242579e-01 -9.86705661e-01 -6.49158597e-01 3.16466421e-01
7.33935893e-01 3.14569473e-02 -4.44938600e-01 1.10616289e-01
-2.97411501e-01 3.96291882e-01 -4.29301530e-01 -2.73686107e-02
-4.64486778e-01 -7.66769052e-01 4.71116453e-02 4.13384080e-01
4.93113160e-01 -8.13805342e-01 -6.17518008e-01 1.51225910e-01
-3.99883032e-01 -1.04273391e+00 -3.39596063e-01 8.97056535e-02
-1.27575588e+00 -1.06836402e+00 -9.99007642e-01 -8.89136612e-01
7.90898383e-01 3.24986666e-01 9.64023888e-01 -1.12449273e-01
-6.80954456e-01 6.77255690e-02 1.79111019e-01 -4.03196454e-01
-1.21598937e-01 -3.84505510e-01 2.44978424e-02 -4.57443655e-01
2.16647521e-01 -5.72512031e-01 -1.22721517e+00 5.27376354e-01
-6.93962812e-01 3.48951459e-01 6.55998647e-01 1.09319651e+00
1.09769702e+00 -2.08732814e-01 -1.38528302e-01 -5.15882492e-01
1.12277299e-01 -1.16809510e-01 -8.79547119e-01 -3.56703252e-01
-5.94182789e-01 -2.84733683e-01 2.17781827e-01 -2.92564988e-01
-1.06827915e+00 5.57753108e-02 -4.47805911e-01 -6.11153722e-01
-2.84747005e-01 2.47238249e-01 2.34361626e-02 -2.14824855e-01
5.83173096e-01 1.60721377e-01 5.65154672e-01 -2.27125242e-01
-4.04557705e-01 4.63375956e-01 5.94255030e-01 -3.88586611e-01
2.83487737e-01 8.17353189e-01 1.10141397e-01 -7.14493871e-01
-5.26408672e-01 -6.18116915e-01 -2.21822619e-01 -2.86625504e-01
9.69746947e-01 -1.20499325e+00 -7.29794204e-01 8.79064560e-01
-1.15299082e+00 -4.19653952e-01 1.26755208e-01 9.46365535e-01
-6.65965021e-01 4.21065658e-01 -8.83357227e-01 -5.22051871e-01
-6.11445785e-01 -1.60204363e+00 1.19903922e+00 4.44628716e-01
1.30101308e-01 -7.48033762e-01 4.80508804e-02 5.15269101e-01
5.12437642e-01 1.31278202e-01 7.59968817e-01 2.46762522e-02
-6.90357327e-01 -2.00814947e-01 -3.79509836e-01 2.07607180e-01
2.18444154e-01 -2.29112789e-01 -1.04786873e+00 -3.52732360e-01
3.90042573e-01 1.30413592e-01 5.15574574e-01 1.22244298e+00
1.34164751e+00 2.16244727e-01 -5.19077003e-01 1.16123176e+00
1.76847482e+00 2.97380239e-01 9.77614641e-01 5.49731016e-01
6.58484578e-01 4.35190529e-01 9.21398103e-01 4.40777063e-01
2.18683809e-01 6.62216008e-01 7.66655087e-01 -4.32191908e-01
-3.21944505e-02 1.56415537e-01 -3.94999012e-02 7.79595435e-01
-2.35796049e-01 1.05240494e-01 -8.85409534e-01 4.01525468e-01
-1.62142408e+00 -5.16978800e-01 -2.84080595e-01 2.60584402e+00
7.09548473e-01 -4.92377505e-02 -4.74849880e-01 -2.47131646e-01
7.90310144e-01 -1.74002945e-01 -4.94378209e-01 -2.83013061e-02
-2.78280452e-02 3.29862803e-01 8.70555997e-01 5.21209240e-01
-9.07242000e-01 5.04705846e-01 5.13873196e+00 1.26630950e+00
-1.12488759e+00 1.24710441e-01 8.05066705e-01 4.79911175e-03
-3.09620500e-01 -2.15421647e-01 -7.29366720e-01 3.60382497e-01
4.68818665e-01 1.74539998e-01 -1.04303779e-02 7.46708512e-01
3.08708012e-01 -7.35742390e-01 -6.67437375e-01 1.64411187e+00
4.04139236e-02 -1.46400130e+00 -4.30440575e-01 4.30921793e-01
5.56791484e-01 4.01931584e-01 -1.32042378e-01 -8.74898210e-02
-1.88288793e-01 -9.90388393e-01 3.42722625e-01 6.32893205e-01
1.11028087e+00 -6.92427039e-01 1.27127194e+00 3.42722267e-01
-8.38344336e-01 2.45150983e-01 -6.20553851e-01 2.78770596e-01
7.58941546e-02 7.45718598e-01 -4.46520984e-01 6.35273159e-01
8.73278081e-01 4.72450167e-01 3.16519733e-03 1.36338782e+00
1.10648908e-01 -1.31226992e-02 -5.56780934e-01 2.86088288e-01
-1.99814856e-01 -5.00121355e-01 5.91976821e-01 7.29115129e-01
7.09046304e-01 1.37114361e-01 -1.76900715e-01 5.45941234e-01
3.77738774e-01 7.39053190e-02 -4.13765550e-01 7.49366224e-01
3.33751529e-01 1.32140875e+00 -8.53181899e-01 1.98683962e-02
-3.69694531e-01 9.65826154e-01 -1.80138722e-01 2.57092267e-01
-8.51936460e-01 -1.88521802e-01 6.26228034e-01 3.76989126e-01
1.65672377e-02 -1.59347743e-01 -5.77239156e-01 -9.96075630e-01
1.41827598e-01 -7.55725265e-01 2.47218102e-01 -9.52959120e-01
-1.12858081e+00 6.97948575e-01 -1.21658877e-01 -1.52192938e+00
1.50899410e-01 -8.45130086e-01 -3.99550885e-01 1.04326427e+00
-1.52240694e+00 -6.60371780e-01 -8.64254832e-01 6.96119845e-01
3.70624810e-01 2.10605226e-02 9.38184857e-01 4.70775843e-01
-3.61468971e-01 3.21145803e-01 3.58855128e-01 -1.00591078e-01
9.54464972e-01 -8.20246994e-01 -3.25955421e-01 6.68150008e-01
-6.67153776e-01 6.01699471e-01 7.16612875e-01 -7.56922901e-01
-1.43410552e+00 -5.26346803e-01 2.96247721e-01 8.35597515e-03
2.26214558e-01 -3.25993672e-02 -6.57640576e-01 2.55898446e-01
2.58438326e-02 2.58118212e-01 6.47609890e-01 -1.75444365e-01
2.82307506e-01 -2.78341115e-01 -1.34366894e+00 6.22636378e-01
1.02098823e+00 -2.31803671e-01 -2.24459127e-01 1.86720029e-01
3.21062505e-01 -1.19254076e+00 -8.42377365e-01 9.16119218e-01
6.87574863e-01 -1.41599143e+00 8.61214757e-01 5.14374852e-01
5.06235659e-01 -3.21140319e-01 -3.58220100e-01 -8.26448083e-01
-2.75007963e-01 -3.27072233e-01 4.50257033e-01 6.83141172e-01
1.37565032e-01 -9.43318248e-01 1.02280951e+00 6.48824334e-01
-7.26173759e-01 -8.50931585e-01 -1.41359985e+00 -5.33573747e-01
-1.44895971e-01 -3.72583598e-01 -2.86196824e-02 5.82619429e-01
-3.96043569e-01 -2.47613341e-01 3.24709490e-02 3.67658675e-01
9.56071556e-01 2.19585866e-01 6.62141144e-01 -1.10135889e+00
-2.51669884e-01 -2.60721594e-01 -5.91738880e-01 -1.00813925e+00
-2.26063222e-01 -6.89955115e-01 3.20031524e-01 -1.75780177e+00
3.45649570e-01 -6.95308089e-01 -7.45838061e-02 6.10895716e-02
-6.61074892e-02 2.27627113e-01 -4.04385567e-01 3.32750827e-01
7.18105212e-02 6.02655590e-01 1.48693871e+00 1.48222938e-01
-1.67886913e-01 6.29140213e-02 -3.81324619e-01 8.45800877e-01
6.65671647e-01 -5.17916083e-01 -3.37675065e-01 -5.66243589e-01
1.47414759e-01 2.73252904e-01 5.30992806e-01 -1.05551946e+00
4.83487040e-01 1.26289859e-01 3.17424595e-01 -8.59085619e-01
5.56746662e-01 -9.18497622e-01 5.61185300e-01 5.94250560e-01
4.57530916e-01 -9.66356620e-02 4.72174436e-01 5.05658329e-01
-3.92083019e-01 -6.52097538e-02 1.09796524e+00 -1.90882206e-01
-5.73192418e-01 6.61267877e-01 -2.17685476e-01 -7.57298395e-02
8.06222379e-01 -7.51052022e-01 -1.89703256e-01 -1.43844694e-01
-5.36648929e-01 -1.86362430e-01 8.20011735e-01 -3.80544588e-02
8.92098486e-01 -1.12049532e+00 -5.52450001e-01 3.26033056e-01
5.00239469e-02 5.09626329e-01 9.68145370e-01 1.33620656e+00
-1.08179152e+00 1.21316709e-01 -3.20934117e-01 -1.16833401e+00
-1.25641799e+00 1.60767660e-01 6.41301036e-01 -9.88972187e-02
-8.34179342e-01 8.56630206e-01 6.40018225e-01 -3.80029380e-01
2.97735363e-01 -2.73612648e-01 -9.81486309e-03 -4.24266189e-01
3.38005930e-01 1.93475842e-01 3.06964040e-01 -4.51535314e-01
-3.91499996e-01 8.19347441e-01 9.62330773e-02 -1.61151821e-03
1.25894570e+00 -1.92064032e-01 -1.31150052e-01 1.91170812e-01
1.02750683e+00 1.60465334e-02 -1.21098113e+00 7.87669718e-02
-6.19080424e-01 -6.54972911e-01 6.29528463e-01 -4.30097282e-01
-1.27687347e+00 7.29922056e-01 1.17813349e+00 -6.19535625e-01
1.21093750e+00 -2.42940277e-01 8.18769574e-01 -2.21899003e-01
8.33305717e-01 -9.00803149e-01 -4.34103400e-01 3.08367491e-01
8.55447769e-01 -1.44014180e+00 1.55705795e-01 -7.14211285e-01
-3.98967892e-01 1.18020308e+00 6.82295978e-01 -1.27909064e-01
8.68954122e-01 6.48035049e-01 2.91028738e-01 -1.66587919e-01
-1.97766826e-01 9.04272422e-02 1.45531505e-01 5.21964848e-01
4.02195752e-01 -1.69451922e-01 -4.15910691e-01 3.92863780e-01
-9.40799490e-02 2.88603812e-01 4.38823074e-01 8.08606744e-01
-3.62457596e-02 -7.47798145e-01 -3.45202446e-01 5.52356839e-01
-6.49094999e-01 -2.51878738e-01 7.37101912e-01 6.74769700e-01
1.81526598e-02 6.92848921e-01 1.66496336e-01 -1.30954489e-01
3.58489513e-01 -6.35239363e-01 5.60424924e-01 -4.75292712e-01
-3.30463231e-01 5.74830234e-01 3.03125884e-02 -1.13269973e+00
-4.07765239e-01 -5.42805374e-01 -1.15602207e+00 -1.73143998e-01
-2.89274901e-01 -3.00658613e-01 8.72469902e-01 4.27546680e-01
4.13529962e-01 3.60860437e-01 3.20030123e-01 -1.08291221e+00
1.59772094e-02 -7.20411837e-01 -7.72058487e-01 1.59530528e-02
2.09929615e-01 -8.41966629e-01 -6.92846298e-01 -3.74064267e-01] | [13.773874282836914, -3.066627264022827] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.