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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
5547b82e-a576-461d-9dcc-f9f8c5eb1d1c | methodology-for-capacity-credit-evaluation-of | 2303.09560 | null | https://arxiv.org/abs/2303.09560v1 | https://arxiv.org/pdf/2303.09560v1.pdf | Methodology for Capacity Credit Evaluation of Physical and Virtual Energy Storage in Decarbonized Power System | Energy storage (ES) and virtual energy storage (VES) are key components to realizing power system decarbonization. Although ES and VES have been proven to deliver various types of grid services, little work has so far provided a systematical framework for quantifying their adequacy contribution and credible capacity value while incorporating human and market behavior. Therefore, this manuscript proposed a novel evaluation framework to evaluate the capacity credit (CC) of ES and VES. To address the system capacity inadequacy and market behavior of storage, a two-stage coordinated dispatch is proposed to achieve the trade-off between day-ahead self-energy management of resources and efficient adjustment to real-time failures. And we further modeled the human behavior with storage operations and incorporate two types of decision-independent uncertainties (DIUs) (operate state and self-consumption) and one type of decision-dependent uncertainty (DDUs) (available capacity) into the proposed dispatch. Furthermore, novel reliability and CC indices (e.g., equivalent physical storage capacity (EPSC)) are introduced to evaluate the practical and theoretical adequacy contribution of ES and VES, as well as the ability to displace generation and physical storage while maintaining equivalent system adequacy. Exhaustive case studies based on the IEEE RTS-79 system and real-world data verify the significant consequence (10%-70% overestimated CC) of overlooking DIUs and DDUs in the previous works, while the proposed method outperforms other and can generate a credible and realistic result. Finally, we investigate key factors affecting the adequacy contribution of ES and VES, and reasonable suggestions are provided for better flexibility utilization of ES and VES in decarbonized power system. | ['Weiwei Yang', 'Wenrui Huang', 'Ziyi Zhang', 'Lin Cheng', 'Peng Li', 'Ning Qi'] | 2023-03-16 | null | null | null | null | ['energy-management'] | ['time-series'] | [-8.15476954e-01 -1.12294219e-01 2.82910429e-02 1.01867929e-01
-3.15600112e-02 -5.15568554e-01 6.37921333e-01 2.17959240e-01
1.13390379e-01 1.12705624e+00 1.54106408e-01 -4.96547580e-01
-3.20946723e-01 -9.45713639e-01 -1.02773398e-01 -9.10098314e-01
-2.68314004e-01 1.71207026e-01 -9.20530781e-02 -2.44958550e-01
1.66633636e-01 6.38520658e-01 -1.60626388e+00 -5.80738962e-01
1.27996445e+00 1.10320652e+00 4.22908008e-01 -3.30899023e-02
2.17535436e-01 3.78158122e-01 -9.73492146e-01 1.54519841e-01
1.45075187e-01 -2.92445511e-01 -2.37339288e-01 -2.44882435e-01
-1.29996014e+00 -7.98981607e-01 -3.83730326e-03 1.16713846e+00
8.40277016e-01 1.30620643e-01 7.24484921e-01 -1.58631659e+00
-7.93151498e-01 8.04923117e-01 -4.15373653e-01 5.16115963e-01
1.05075218e-01 2.47842550e-01 3.19322318e-01 -8.25684965e-01
-1.11328334e-01 7.45242596e-01 1.10378869e-01 -2.52520647e-02
-6.68334842e-01 -6.46809995e-01 -1.22070648e-01 1.56573027e-01
-1.53627884e+00 -2.52144605e-01 7.77185917e-01 -2.97959477e-01
1.48881555e+00 3.97781223e-01 1.09350324e+00 9.10384133e-02
4.64391708e-01 4.20555651e-01 1.25869095e+00 -4.79961216e-01
5.77006757e-01 4.32406783e-01 -1.31999869e-02 -2.94334561e-01
6.91217244e-01 2.03697845e-01 1.96964480e-02 7.54098594e-02
4.22280610e-01 -2.74472803e-01 -3.40727031e-01 6.07737862e-02
-6.73727632e-01 2.09235802e-01 1.71664521e-01 6.39910698e-01
-5.21367073e-01 -3.15701097e-01 3.68230790e-01 -1.03354327e-01
1.26462772e-01 2.32830614e-01 -7.39695430e-02 -1.61310568e-01
-1.03404748e+00 -1.85025275e-01 5.89322090e-01 9.61804807e-01
6.40827045e-02 1.09646189e+00 -2.96808481e-01 1.24606080e-01
9.28812250e-02 9.62799907e-01 7.53322065e-01 -6.17143333e-01
1.95710838e-01 5.41448653e-01 8.63838017e-01 -6.79999709e-01
-4.72853839e-01 -7.17538595e-01 -9.76918340e-01 3.52505624e-01
-1.31935641e-01 -2.63720065e-01 -5.10812700e-01 1.47443306e+00
-3.27438489e-02 -1.86552390e-01 2.07800120e-01 7.08465278e-01
1.13856249e-01 8.74898434e-01 5.31758592e-02 -8.97712708e-01
1.06867850e+00 -2.63511121e-01 -1.21572495e+00 4.96824056e-01
2.63100654e-01 -3.73816341e-01 6.10697627e-01 2.92961448e-01
-1.65430582e+00 -3.34563345e-01 -1.30743515e+00 6.30843282e-01
-6.50531411e-01 1.99801043e-01 8.67590830e-02 6.58667922e-01
-1.01039398e+00 5.54202676e-01 -8.27936232e-01 -2.84525156e-02
-1.93256900e-01 7.37467408e-02 4.27266896e-01 7.64390528e-01
-1.59444082e+00 1.58059025e+00 7.48526752e-01 6.51441157e-01
-8.01427364e-01 -6.22211814e-01 -4.42670792e-01 4.55219448e-01
3.16534966e-01 -2.69732744e-01 9.99805868e-01 -3.39165568e-01
-1.36053848e+00 -1.10261455e-01 3.17947984e-01 -6.15993261e-01
3.96532565e-01 2.17258349e-01 -1.02939618e+00 1.22429676e-01
-2.67940104e-01 -3.33688945e-01 2.63863020e-02 -1.14307845e+00
-4.93878067e-01 -3.33040208e-01 -2.33043954e-01 4.45367843e-01
-4.81270790e-01 -1.34713957e-02 5.73835194e-01 -5.64066589e-01
-1.91644058e-01 -5.39122403e-01 -2.11199019e-02 -6.44021809e-01
-2.94125557e-01 -4.55884099e-01 8.23149145e-01 -1.19508994e+00
1.69015658e+00 -1.75151694e+00 3.19743529e-02 4.21690285e-01
-3.30993116e-01 5.13715565e-01 7.35456049e-01 9.56674576e-01
-1.16482161e-01 3.53026092e-01 -1.54284149e-01 6.70580044e-02
4.79759842e-01 3.72528136e-01 -3.82006139e-01 3.45166534e-01
-1.49015009e-01 7.11614251e-01 -8.39727342e-01 1.53565809e-01
8.86587799e-01 2.72854984e-01 2.99416840e-01 1.91012844e-01
5.87805137e-02 1.24291100e-01 -4.53674316e-01 9.20155764e-01
8.47594321e-01 -6.10593148e-02 1.57106608e-01 -2.69032925e-01
-4.81650680e-01 -2.83437729e-01 -1.53927326e+00 7.71415293e-01
-5.30921876e-01 1.74603909e-02 2.05378398e-01 -1.10329986e+00
8.97898972e-01 4.12954658e-01 6.27099276e-01 -1.17846441e+00
1.02471083e-01 4.74535793e-01 -1.09965146e-01 -3.51137459e-01
7.54914224e-01 -1.21114336e-01 9.97027382e-02 4.42835063e-01
-2.13695124e-01 -7.95708299e-02 1.74450889e-01 8.94195884e-02
2.93492138e-01 -1.27445623e-01 4.85938638e-01 -9.49157238e-01
7.00178504e-01 -5.30736983e-01 7.62700200e-01 -1.85655400e-01
-3.10519725e-01 -3.71100098e-01 3.63147587e-01 2.40566671e-01
-1.10995340e+00 -9.97162700e-01 -2.75705427e-01 -4.39003110e-02
6.04965150e-01 9.40658003e-02 -3.70126218e-01 6.59390092e-02
2.32429072e-01 1.78277993e+00 -1.58571079e-01 -3.59015584e-01
-3.23768139e-01 -1.09853792e+00 1.40424088e-01 7.61041343e-01
6.01765096e-01 -5.64885497e-01 -1.09867215e+00 2.84206599e-01
1.87571108e-01 -5.96340775e-01 6.56367689e-02 2.49797627e-01
-4.34878618e-01 -9.06022191e-01 -7.49822140e-01 1.21423014e-01
7.96640575e-01 8.31026807e-02 9.89439249e-01 3.20200592e-01
1.04275413e-01 1.57817170e-01 -2.34054357e-01 -4.86347049e-01
-2.74118006e-01 -5.02859950e-01 5.89740396e-01 -6.74383461e-01
-2.21439637e-02 -5.16282082e-01 -7.90450096e-01 5.01839101e-01
-7.77478814e-01 -7.54098669e-02 2.84835368e-01 6.59234762e-01
4.26277399e-01 8.66437316e-01 1.36853993e+00 1.17116934e-03
1.00618947e+00 -8.19961965e-01 -1.00433183e+00 5.52661955e-01
-1.65656412e+00 -1.16767861e-01 9.25692558e-01 1.45886675e-01
-1.33109391e+00 -6.97937965e-01 1.82162508e-01 -2.96621233e-01
3.49573314e-01 6.97642565e-01 -4.29243028e-01 2.50521332e-01
-2.84304887e-01 3.97127628e-01 7.67355645e-03 -3.88916969e-01
7.35649168e-02 7.40535438e-01 5.62301517e-01 -5.36023736e-01
8.52671504e-01 -7.52246231e-02 2.80661136e-01 -2.59419352e-01
1.49185613e-01 3.96504886e-02 -2.47349963e-01 -5.21923304e-01
4.29951698e-01 -1.07304132e+00 -1.02216911e+00 6.60295606e-01
-5.25083065e-01 -1.88468564e-02 -3.75467479e-01 4.58968073e-01
-2.53956169e-01 5.46855032e-01 -2.40492716e-01 -1.47164333e+00
-5.68358839e-01 -1.15414810e+00 1.96563601e-01 5.74863493e-01
3.44562620e-01 -9.20175910e-01 -4.16534156e-01 -2.84633011e-01
8.64385366e-01 6.22644484e-01 8.86932552e-01 -3.59668434e-01
-5.48606753e-01 5.46263494e-02 8.03019330e-02 8.23233545e-01
1.40500367e-01 2.53576696e-01 -3.44774902e-01 -8.47890317e-01
2.05633312e-01 5.00225369e-03 -1.22491039e-01 3.03130060e-01
8.92723262e-01 -3.86653006e-01 -1.55645937e-01 5.22431955e-02
2.07724071e+00 9.42524850e-01 8.33323777e-01 4.45995808e-01
-3.14276397e-01 3.75311762e-01 9.04923201e-01 1.18854320e+00
4.74565744e-01 5.26392758e-01 7.35777617e-01 1.20211422e-01
3.36066842e-01 -1.06710508e-01 2.96433926e-01 9.42479610e-01
-1.43398270e-01 -4.84360158e-01 -8.18576038e-01 6.60791874e-01
-1.53675878e+00 -9.92321670e-01 -7.53310770e-02 2.49949026e+00
4.03042436e-01 3.38735938e-01 4.81103994e-02 4.97872382e-01
6.75077558e-01 -2.05339909e-01 -7.50212610e-01 -4.55801249e-01
-5.63208640e-01 -2.41169974e-01 6.80048347e-01 1.58698857e-01
-2.18182262e-02 -2.73164967e-03 5.83489656e+00 8.06443334e-01
-1.02409792e+00 1.18804565e-02 7.71752179e-01 -1.75418466e-01
-6.51297450e-01 1.13565683e-01 -6.51107848e-01 1.19170094e+00
1.44234240e+00 -1.29522157e+00 4.20168340e-01 5.41834831e-01
8.72017980e-01 -7.08552182e-01 -6.24850631e-01 4.37525392e-01
-3.83853734e-01 -1.00498581e+00 -2.69831389e-01 1.92805067e-01
7.52659976e-01 -4.38542724e-01 -3.57079536e-01 2.33638406e-01
4.88795154e-02 -6.09902561e-01 1.10134923e+00 1.02377295e+00
6.19983256e-01 -1.19381285e+00 1.24180639e+00 5.55300415e-01
-1.39219356e+00 -6.24809742e-01 -2.01447383e-01 -1.56895131e-01
8.85290205e-01 7.59029090e-01 -2.49660119e-01 1.26333058e+00
7.50481367e-01 9.64621454e-02 -4.07758147e-01 6.07834816e-01
-8.65308717e-02 3.23637098e-01 -4.80964363e-01 2.36720573e-02
-1.73833266e-01 -6.31927371e-01 3.25838894e-01 4.27946627e-01
7.21369445e-01 4.44110364e-01 -1.45665661e-01 1.06739998e+00
5.19784033e-01 -2.64712662e-01 -1.08105704e-01 -5.20906374e-02
1.41154373e+00 1.16493618e+00 -6.04399145e-01 -5.70832789e-01
-2.02748820e-01 2.96376199e-01 -3.66274655e-01 4.67205524e-01
-9.45434690e-01 -3.78271461e-01 2.44643569e-01 1.05166681e-01
-1.71114266e-01 -3.15515339e-01 -6.25861585e-01 -8.67692828e-01
2.97231466e-01 -1.50069162e-01 8.20696279e-02 -1.12739158e+00
-1.09649289e+00 2.56922573e-01 5.16847074e-01 -1.32176292e+00
-6.26576722e-01 -8.76711123e-03 -8.96606088e-01 1.48671556e+00
-1.75216174e+00 -8.37492883e-01 -7.21832588e-02 3.51750940e-01
1.32228479e-01 -2.27704614e-01 5.14795423e-01 4.53437328e-01
-1.09127903e+00 3.84289116e-01 9.69426513e-01 -5.85779369e-01
-1.72941014e-01 -1.21474314e+00 -3.33369821e-01 1.30839372e+00
-1.06468892e+00 4.54620004e-01 9.21809733e-01 -8.34942400e-01
-1.46427679e+00 -4.96224254e-01 4.67065901e-01 2.64286727e-01
6.99792266e-01 1.41281620e-01 -9.08306658e-01 2.54843116e-01
7.12815225e-01 -4.77360368e-01 2.61017531e-01 -7.41865456e-01
5.77523291e-01 -1.55046791e-01 -1.54206753e+00 3.63390476e-01
4.07690555e-01 -3.03779542e-01 -4.65299129e-01 -1.37975693e-01
4.00480449e-01 -1.32973626e-01 -1.44494843e+00 5.64610541e-01
2.82438248e-01 -8.83146644e-01 7.58736551e-01 1.33073226e-01
-2.76880234e-01 -5.55036008e-01 -2.53645837e-01 -1.64694571e+00
-1.48402900e-01 -5.30418873e-01 -5.32919466e-01 1.82477415e+00
2.81169936e-02 -9.78837013e-01 5.55747710e-02 1.14316177e+00
-6.36102736e-01 -8.28119218e-01 -1.25777948e+00 -1.18351424e+00
2.17144117e-01 1.45218715e-01 1.31757009e+00 8.86995435e-01
5.21216452e-01 -5.17606497e-01 -2.37123638e-01 3.80142957e-01
6.82351351e-01 -6.11195453e-02 1.15102381e-01 -6.76488817e-01
2.41494432e-01 -4.69837695e-01 1.71734840e-01 -1.65166892e-02
-1.44709751e-01 -4.71187204e-01 -4.79435325e-01 -1.94756913e+00
-1.46583198e-02 -4.36769515e-01 -7.25793362e-01 2.84711272e-01
3.31897065e-02 -6.20122671e-01 4.25125301e-01 5.36145031e-01
3.12922239e-01 1.22946012e+00 8.15607309e-01 2.80911714e-01
-2.08896920e-02 -9.66488943e-02 -3.72054011e-01 4.34120536e-01
9.29904401e-01 1.94291487e-01 -6.98831201e-01 -9.27831903e-02
1.84295475e-01 7.13643968e-01 1.90801188e-01 -1.01692462e+00
2.89208949e-01 -4.55171525e-01 3.12290221e-01 -1.12934554e+00
-1.48527056e-01 -1.27216673e+00 1.13450372e+00 7.70641804e-01
3.21438760e-01 4.78490502e-01 1.71761125e-01 4.34995532e-01
-8.18695650e-02 -2.84839272e-01 5.39663672e-01 8.07995498e-02
-6.92326546e-01 -2.16443196e-01 -3.41946036e-01 -5.55797637e-01
1.73409891e+00 -5.51512957e-01 -8.27107906e-01 -2.16240734e-01
-7.07029343e-01 8.81421864e-01 5.44893146e-01 3.34795982e-01
2.41935596e-01 -1.27917814e+00 -3.53947043e-01 -5.78360930e-02
-3.47332805e-01 -4.83551949e-01 5.50556540e-01 6.42518282e-01
-2.56073743e-01 7.14114368e-01 -5.31753004e-01 -1.32286206e-01
-4.17374164e-01 7.20721364e-01 5.98553538e-01 -1.43155232e-01
-3.26490968e-01 -8.04523081e-02 -5.50402880e-01 3.25021386e-01
4.46195565e-02 -3.20252746e-01 -1.52124062e-01 2.47550189e-01
2.74139017e-01 1.07591641e+00 2.41107568e-01 -5.01334608e-01
-3.38879734e-01 2.36854609e-02 6.71089709e-01 -6.50080096e-04
1.06727648e+00 -7.03356743e-01 -1.03159279e-01 3.43433231e-01
4.44724917e-01 -2.38163024e-01 -1.09080195e+00 2.59764940e-01
5.48518542e-03 -2.26718202e-01 2.11525351e-01 -1.34100950e+00
-1.06416678e+00 4.16170955e-01 6.07177675e-01 7.01844513e-01
1.57166660e+00 -6.02360725e-01 5.48038900e-01 -2.11814374e-01
7.76282310e-01 -1.65994513e+00 -4.38942581e-01 -1.41867712e-01
9.14767504e-01 -6.82125211e-01 2.72456884e-01 -1.19264815e-02
-5.06415546e-01 8.35752130e-01 6.32907450e-01 1.44042239e-01
8.73361230e-01 5.64173400e-01 -8.53412807e-01 1.65125683e-01
-6.16021216e-01 2.15983391e-01 -2.60392338e-01 2.79567003e-01
5.98851964e-02 5.36936283e-01 -1.02012527e+00 1.10730195e+00
5.62036261e-02 1.54653743e-01 9.62499321e-01 1.13641691e+00
-3.70229870e-01 -6.75151467e-01 -3.13605368e-01 4.93574172e-01
-4.15167928e-01 2.11110413e-01 5.33453763e-01 9.09652293e-01
1.88955665e-01 1.04892385e+00 1.66907281e-01 -1.32586107e-01
6.61669731e-01 -1.36642367e-01 -1.48857340e-01 5.96029274e-02
-4.68054593e-01 5.19998409e-02 1.23444155e-01 -1.01496197e-01
-2.41937488e-01 -6.90270483e-01 -1.79776978e+00 -5.42570293e-01
-8.07311654e-01 7.31122851e-01 1.02758372e+00 9.34318304e-01
2.83102274e-01 6.93385184e-01 1.12967730e+00 -7.11359680e-01
-1.26573062e+00 -9.09351587e-01 -1.32509971e+00 -3.32083814e-02
-2.56948858e-01 -9.22167361e-01 -9.89070833e-01 -4.43099648e-01] | [5.669347763061523, 2.5211541652679443] |
716443d0-083f-44ac-a19e-940401dbf019 | bira-net-bilinear-attention-net-for-diabetic | 1905.06312 | null | https://arxiv.org/abs/1905.06312v2 | https://arxiv.org/pdf/1905.06312v2.pdf | BiRA-Net: Bilinear Attention Net for Diabetic Retinopathy Grading | Diabetic retinopathy (DR) is a common retinal disease that leads to blindness. For diagnosis purposes, DR image grading aims to provide automatic DR grade classification, which is not addressed in conventional research methods of binary DR image classification. Small objects in the eye images, like lesions and microaneurysms, are essential to DR grading in medical imaging, but they could easily be influenced by other objects. To address these challenges, we propose a new deep learning architecture, called BiRA-Net, which combines the attention model for feature extraction and bilinear model for fine-grained classification. Furthermore, in considering the distance between different grades of different DR categories, we propose a new loss function, called grading loss, which leads to improved training convergence of the proposed approach. Experimental results are provided to demonstrate the superior performance of the proposed approach. | ['Matthew Chin Heng Chua', 'Kerui Zhang', 'Ziyuan Zhao', 'Xuejie Hao', 'Li Chen', 'Xin Xu', 'Jing Tian'] | 2019-05-15 | null | null | null | null | ['diabetic-retinopathy-grading'] | ['medical'] | [-3.17288004e-02 -2.32268602e-01 -3.04368045e-02 -6.24616265e-01
-4.11634266e-01 -1.75745636e-02 2.64345318e-01 -2.74057984e-01
-1.52715325e-01 7.75871813e-01 4.45814043e-01 -2.76696682e-01
-1.79021195e-01 -7.83421814e-01 -6.75670058e-02 -8.57160091e-01
3.30782324e-01 -6.04158528e-02 2.42530316e-01 7.70374984e-02
4.90540504e-01 7.06328392e-01 -1.46845758e+00 4.33770120e-01
1.44096661e+00 1.34303522e+00 -1.58519782e-02 3.67124707e-01
-2.58213252e-01 1.29527152e+00 -4.66109544e-01 -3.61977428e-01
1.61767259e-01 -3.01162809e-01 -4.98085886e-01 4.66966294e-02
9.75652039e-01 -8.45807493e-01 -4.72130001e-01 1.25375307e+00
8.60547841e-01 -1.65446594e-01 9.40914154e-01 -3.58776897e-01
-1.09421587e+00 1.64180189e-01 -9.49255824e-01 6.56389892e-01
-1.51169419e-01 3.05027872e-01 6.34246528e-01 -6.80181444e-01
8.58524665e-02 1.46267557e+00 4.27761257e-01 5.24887741e-01
-9.39835608e-01 -5.15205443e-01 -9.94559675e-02 6.67657137e-01
-1.28966582e+00 -3.58407557e-01 6.56682611e-01 -8.41474056e-01
1.29312396e-01 8.69751871e-02 5.61007380e-01 6.23637557e-01
2.09101811e-01 6.30746365e-01 1.60048115e+00 -2.12885533e-02
-7.17090443e-02 -7.37973750e-02 4.21846747e-01 5.18111050e-01
4.88519490e-01 2.01769054e-01 4.19101626e-01 1.59301192e-01
9.76820111e-01 8.79073143e-02 -5.26518762e-01 -2.95383990e-01
-9.35820282e-01 6.61682963e-01 8.85122597e-01 -1.44073451e-02
-3.05368364e-01 -6.84577748e-02 2.38754407e-01 6.89739808e-02
2.99906254e-01 4.21161242e-02 -1.62953623e-02 3.02461386e-01
-5.70272148e-01 4.49930653e-02 5.86055592e-03 4.13318813e-01
3.39972109e-01 2.58818269e-03 -7.05868542e-01 1.14676571e+00
4.27778244e-01 3.13182205e-01 5.16276836e-01 -8.17814767e-01
3.10008407e-01 1.01948023e+00 1.51943162e-01 -9.39609885e-01
-3.76129687e-01 -7.35936284e-01 -1.37517536e+00 6.89332306e-01
4.18129683e-01 -1.14539646e-01 -1.38501561e+00 1.08149087e+00
2.70095021e-01 1.74274996e-01 -5.41971624e-02 1.32462287e+00
1.31312501e+00 2.51774132e-01 -6.55969679e-02 -1.48597151e-01
1.32356501e+00 -7.88226068e-01 -6.07766569e-01 3.17414925e-02
2.82131612e-01 -6.21527791e-01 9.54374611e-01 4.02573645e-01
-1.11033392e+00 -6.77486837e-01 -8.17119420e-01 -4.52313274e-01
2.97721121e-02 6.63026929e-01 6.56973779e-01 4.06075299e-01
-1.08213294e+00 1.46382019e-01 -3.47656220e-01 -2.32178688e-01
9.69146013e-01 1.88509896e-01 -1.52956089e-02 -2.97432572e-01
-7.96745479e-01 9.96268332e-01 5.73142432e-02 5.50304890e-01
-5.30941963e-01 -4.75687832e-01 -4.95206833e-01 -5.91913126e-02
-5.12207113e-02 -9.43663359e-01 8.96058917e-01 -6.88865662e-01
-1.32260096e+00 9.43370640e-01 -1.64306402e-01 -1.19877405e-01
6.88985527e-01 -1.12358682e-01 -5.75203896e-01 2.46343225e-01
-2.66441524e-01 2.63532400e-01 7.50457942e-01 -1.14325535e+00
-9.47538853e-01 -7.50531316e-01 2.57718861e-01 1.40149906e-01
3.14618722e-02 1.81950226e-01 6.58891201e-02 -5.73873818e-01
1.14613682e-01 -1.65888950e-01 -3.15187991e-01 2.71945983e-01
-4.03535485e-01 -3.52024525e-01 5.69994092e-01 -7.75012851e-01
1.22107184e+00 -2.05650806e+00 -1.14987031e-01 1.41432643e-01
7.58281648e-01 5.44620574e-01 5.44043668e-02 -5.20651340e-01
2.58733146e-02 1.62236691e-01 3.42214969e-03 2.53203362e-01
-3.33314121e-01 -7.25117177e-02 -1.21758461e-01 4.12026465e-01
3.18036765e-01 8.05496573e-01 -4.91958708e-01 -4.14459050e-01
2.25797862e-01 5.87959707e-01 -1.40669271e-01 1.73414066e-01
1.77165389e-01 5.84153056e-01 -6.48881197e-01 7.94140399e-01
1.00422251e+00 -3.46623868e-01 -4.97346789e-01 -6.43083751e-01
-2.51296669e-01 1.02433853e-01 -9.25382972e-01 7.50980675e-01
-1.15660995e-01 4.21684355e-01 -2.96504855e-01 -9.94929910e-01
1.06989896e+00 4.19910662e-02 1.23701096e-01 -8.32597613e-01
4.25217718e-01 2.38324210e-01 3.31477970e-01 -7.72345781e-01
2.59690508e-02 2.07177684e-01 6.37261868e-01 -1.20262474e-01
-4.06435102e-01 3.84917319e-01 2.28444099e-01 -4.27914798e-01
7.29161739e-01 -2.18267217e-01 3.27274054e-01 2.76688132e-02
8.21343899e-01 -3.42039615e-01 7.40241528e-01 5.05653441e-01
-3.13547373e-01 7.71607876e-01 6.78647459e-01 -7.74041831e-01
-9.55134988e-01 -8.40131283e-01 -8.31728280e-01 1.30149022e-01
4.90481526e-01 5.00029087e-01 -3.30894232e-01 -7.45888472e-01
8.47529992e-02 9.39282030e-02 -6.14932418e-01 -1.87259447e-02
-4.30305213e-01 -1.20492351e+00 2.12743849e-01 5.45871019e-01
7.93966472e-01 -7.75864184e-01 -1.18189901e-01 -1.12809613e-01
4.08358909e-02 -7.59045720e-01 -4.15970027e-01 -6.54636919e-01
-9.57875371e-01 -1.36419165e+00 -1.33837688e+00 -9.65165257e-01
8.70580375e-01 3.72297227e-01 8.99016976e-01 8.52963924e-02
-6.41548812e-01 -1.90527618e-01 -1.57412440e-01 -4.72572073e-02
-5.75569458e-02 -3.89203489e-01 -2.10404351e-01 6.16005421e-01
6.35969818e-01 -4.51811463e-01 -1.32253969e+00 2.99540669e-01
-4.54376757e-01 -2.98042297e-01 1.25083709e+00 8.27076793e-01
7.72029996e-01 2.33509447e-02 6.01566970e-01 -8.63014340e-01
5.59340179e-01 -2.03347936e-01 -5.91988981e-01 2.39661723e-01
-7.07591951e-01 -2.55037040e-01 2.58895189e-01 -3.27131867e-01
-1.11710107e+00 -4.84862268e-01 1.14311852e-01 -2.82490820e-01
-3.90872151e-01 3.49567860e-01 -2.73882776e-01 -6.65891647e-01
5.72568595e-01 2.68142283e-01 5.61490804e-02 -7.27261424e-01
2.56393850e-01 1.21140218e+00 5.63707829e-01 -1.76213533e-01
4.91036832e-01 2.92099774e-01 4.43221889e-02 -5.89085460e-01
-1.02142704e+00 -4.56510633e-01 -2.11840183e-01 -2.78250035e-02
9.61065114e-01 -1.00604594e+00 -8.07318032e-01 7.67714620e-01
-1.05475771e+00 2.31388900e-02 4.86799404e-02 7.80440986e-01
-3.86756003e-01 5.55949092e-01 -6.16706550e-01 -5.79365432e-01
-4.12968129e-01 -1.17222309e+00 7.53051758e-01 8.21566463e-01
4.81999129e-01 -7.73091197e-01 -1.29578561e-01 7.43860245e-01
5.66366255e-01 2.95100033e-01 1.34265113e+00 -1.09942369e-01
-7.70933151e-01 -3.57644670e-02 -1.15285397e+00 7.90107846e-01
2.81763077e-01 1.88665301e-01 -7.13405132e-01 -1.79829344e-01
-2.18566582e-01 -2.14387491e-01 1.14609814e+00 6.74188316e-01
1.60348451e+00 -3.54740292e-01 -1.69762537e-01 8.69454086e-01
1.47499704e+00 4.96324360e-01 1.21750093e+00 2.56577134e-01
8.98624241e-01 3.84506077e-01 4.79685873e-01 2.97460288e-01
5.39234877e-01 5.99154115e-01 4.56657767e-01 -6.68055713e-01
-6.69819832e-01 3.85898054e-01 -1.36846274e-01 4.58100170e-01
-6.16022944e-01 -6.73266798e-02 -6.23080015e-01 5.97259820e-01
-1.63048589e+00 -9.13873553e-01 -6.21837795e-01 2.15881991e+00
9.28258061e-01 -8.72042775e-02 -1.08859606e-01 -2.37208098e-01
8.58137250e-01 -9.28087160e-02 -7.39340067e-01 -1.89036861e-01
-2.81150997e-01 2.51304567e-01 3.79843682e-01 1.29156768e-01
-1.15551066e+00 4.55345064e-01 5.98550940e+00 7.98539937e-01
-1.34033513e+00 -1.22350559e-01 8.72484326e-01 8.61635432e-02
-1.66144148e-01 -3.14022541e-01 -8.69757175e-01 8.93774509e-01
4.11772169e-02 2.68450473e-02 2.27866173e-01 5.11982501e-01
7.35130310e-01 1.36380360e-01 -7.70046055e-01 1.00370347e+00
-1.69195756e-02 -9.57706153e-01 4.11437094e-01 1.20030947e-01
7.69846320e-01 -2.08924606e-01 2.83971936e-01 5.46551310e-02
1.56096295e-01 -1.22665572e+00 -1.28173560e-01 1.15016496e+00
9.13872302e-01 -7.68481374e-01 1.14598632e+00 -2.54541218e-01
-6.43926919e-01 -2.01920480e-01 -7.63066173e-01 2.41518706e-01
-1.37556612e-01 8.71340990e-01 -3.44257623e-01 2.62704849e-01
7.41129041e-01 9.62230563e-01 -7.44244158e-01 1.91731048e+00
-3.44189882e-01 5.30035913e-01 3.29826832e-01 3.85641724e-01
-7.74625614e-02 -5.33499777e-01 5.76802909e-01 6.72325015e-01
5.92804432e-01 3.01987320e-01 -7.06814751e-02 9.56349671e-01
-1.25967041e-02 2.12434888e-01 -2.81362116e-01 2.43283719e-01
6.29570335e-02 1.26204360e+00 5.67347221e-02 -4.68569919e-02
-5.81988096e-01 5.30199707e-01 9.90574956e-02 7.44377136e-01
-4.27489638e-01 -6.92047656e-01 6.70895875e-01 3.97298217e-01
3.99139255e-01 2.27955997e-01 -4.03674275e-01 -1.26476228e+00
1.98352903e-01 -7.60161698e-01 3.28404844e-01 -9.58794653e-01
-1.65941453e+00 4.24254328e-01 -6.48986578e-01 -1.51490009e+00
3.78839374e-01 -6.54415667e-01 -7.09053874e-01 1.16303289e+00
-2.16668296e+00 -1.31442320e+00 -8.57411444e-01 5.51942289e-01
3.73945348e-02 -4.79299307e-01 2.52794355e-01 6.60722256e-01
-7.03889310e-01 6.82830811e-01 2.76676714e-01 1.27475560e-01
1.01668131e+00 -1.38608503e+00 -2.68886030e-01 7.33089566e-01
-7.79158831e-01 5.11563599e-01 1.63448974e-01 -4.80174661e-01
-5.72417915e-01 -1.44935298e+00 5.78944385e-01 -3.61815505e-02
4.57746923e-01 5.46206534e-01 -9.50370789e-01 3.34176123e-01
-1.09527789e-01 3.45761895e-01 5.41306198e-01 -5.33145554e-02
-3.89349133e-01 -7.08082676e-01 -1.24952281e+00 5.99522352e-01
8.16800773e-01 -8.81794542e-02 -5.76903999e-01 1.58320427e-01
3.28798562e-01 -3.87475073e-01 -1.11352134e+00 8.87006879e-01
6.02746606e-01 -9.97058153e-01 1.01808143e+00 -5.83669543e-01
7.29594767e-01 -6.16542161e-01 1.56472087e-01 -1.11189616e+00
-5.11583805e-01 -8.90328288e-02 -2.62574196e-01 1.14368951e+00
-1.21936938e-02 -8.24097037e-01 5.78634977e-01 2.53290981e-01
-2.50733554e-01 -8.02597404e-01 -6.49188578e-01 -4.28861707e-01
1.75279394e-01 5.70017874e-01 5.21783113e-01 8.96410882e-01
-7.09754586e-01 1.21744245e-01 -2.31477827e-01 4.52415735e-01
9.91430163e-01 2.20540181e-01 3.97047043e-01 -1.53397012e+00
-1.08478874e-01 -9.62715447e-01 -9.62339044e-01 -1.06504345e+00
-3.61072272e-01 -6.67658985e-01 -2.69264370e-01 -2.06643844e+00
4.12423044e-01 -5.85972667e-01 -6.47934794e-01 2.65348792e-01
-4.73548263e-01 6.53819382e-01 -4.81784552e-01 3.52331102e-01
-3.18403065e-01 5.63449860e-01 1.84185028e+00 -5.11273265e-01
-1.55678317e-01 3.35229516e-01 -1.10453522e+00 7.46912539e-01
6.15401864e-01 6.36564121e-02 -3.40882480e-01 -4.99597132e-01
-4.56478260e-02 -8.49053077e-03 6.22299373e-01 -9.23505247e-01
-7.39888325e-02 -2.13530183e-01 5.41802824e-01 -5.80609024e-01
-8.28645080e-02 -4.99153554e-01 -4.00561333e-01 1.12027228e-01
-3.29741150e-01 -6.97495162e-01 -1.89316228e-01 4.04013127e-01
-4.31490391e-01 5.07247373e-02 1.26635230e+00 9.91465673e-02
-5.94313681e-01 7.19150722e-01 -1.83198489e-02 -4.83246706e-02
9.58004117e-01 -4.68999535e-01 -8.76895070e-01 -2.23122351e-02
-7.74732232e-01 3.98641229e-01 2.32122034e-01 1.63205981e-01
7.66576767e-01 -1.39233804e+00 -1.14110255e+00 -1.47668198e-01
3.43071312e-01 2.37945259e-01 5.40298581e-01 1.25605226e+00
-7.12711632e-01 2.88087636e-01 -3.05522323e-01 -5.38346946e-01
-1.34738243e+00 2.28974551e-01 7.87764311e-01 8.44191611e-02
-7.51496911e-01 6.04528725e-01 5.57961702e-01 1.95080955e-02
3.32337797e-01 -5.43196440e-01 -1.09775412e+00 5.90902427e-03
9.73669171e-01 4.93218601e-01 8.55023414e-02 -3.42448682e-01
4.71567959e-02 1.08081329e+00 -6.11297667e-01 7.52129793e-01
1.05943382e+00 -4.03365314e-01 -4.76954699e-01 7.92657435e-02
5.84872961e-01 -1.48657635e-02 -1.18290770e+00 -4.99743313e-01
-3.20836216e-01 -6.65713429e-01 5.62467873e-01 -1.22674417e+00
-1.37106454e+00 1.09519386e+00 1.31534660e+00 7.53295571e-02
1.12355232e+00 -2.41930142e-01 8.88429105e-01 1.04945488e-01
1.79119751e-01 -4.02470499e-01 -2.15557456e-01 1.48051769e-01
7.65027344e-01 -1.43133259e+00 -5.96495345e-02 -2.90106714e-01
-4.56167936e-01 1.21904850e+00 7.74051487e-01 -1.19705521e-01
3.06683809e-01 -4.20427233e-01 5.05363107e-01 -1.68477446e-02
-2.01111287e-01 -5.86432636e-01 6.45832777e-01 7.88754582e-01
3.35715383e-01 -5.54017909e-02 -9.34228063e-01 7.75509775e-01
2.16743335e-01 4.87089753e-01 7.76728868e-01 1.68824509e-01
-7.76351750e-01 -9.06704307e-01 -4.07811580e-03 1.02336609e+00
-6.51105762e-01 -1.76874191e-01 -2.28325576e-01 3.15125227e-01
4.19098914e-01 7.54358113e-01 1.15403503e-01 -1.61083505e-01
3.00374836e-01 -5.68187058e-01 4.32400107e-01 -5.39780796e-01
1.12663684e-02 -7.05372244e-02 -9.27585363e-03 -4.00254190e-01
-4.41791266e-01 -2.54983544e-01 -8.44614148e-01 -1.89501777e-01
-4.73830029e-02 -3.23931962e-01 2.67672300e-01 8.19930315e-01
3.96380603e-01 5.91425657e-01 8.71286511e-01 -2.39246249e-01
-6.66347802e-01 -9.83318686e-01 -7.97513664e-01 1.29089579e-01
7.76117206e-01 -7.47314990e-01 -3.80218595e-01 -2.52998509e-02] | [15.811872482299805, -3.981214761734009] |
db249a63-ec4d-4879-b0fd-71e1bab09126 | deep-learning-for-end-to-end-atrial | 1810.00475 | null | http://arxiv.org/abs/1810.00475v1 | http://arxiv.org/pdf/1810.00475v1.pdf | Deep Learning for End-to-End Atrial Fibrillation Recurrence Estimation | Left atrium shape has been shown to be an independent predictor of recurrence
after atrial fibrillation (AF) ablation. Shape-based representation is
imperative to such an estimation process, where correspondence-based
representation offers the most flexibility and ease-of-computation for
population-level shape statistics. Nonetheless, population-level shape
representations in the form of image segmentation and correspondence models
derived from cardiac MRI require significant human resources with sufficient
anatomy-specific expertise. In this paper, we propose a machine learning
approach that uses deep networks to estimate AF recurrence by predicting shape
descriptors directly from MRI images, with NO image pre-processing involved. We
also propose a novel data augmentation scheme to effectively train a deep
network in a limited training data setting. We compare this new method of
estimating shape descriptors from images with the state-of-the-art
correspondence-based shape modeling that requires image segmentation and
correspondence optimization. Results show that the proposed method and the
current state-of-the-art produce statistically similar outcomes on AF
recurrence, eliminating the need for expensive pre-processing pipelines and
associated human labor. | ['Shireen Elhabian', 'Riddhish Bhalodia', 'Evgueni Kholmovski', 'Anupama Goparaju', 'Nassir Marrouche', 'Alan Morris', 'Ross Whitaker', 'Tim Sodergren', 'Joshua Cates'] | 2018-09-30 | null | null | null | null | ['atrial-fibrillation-recurrence-estimation'] | ['medical'] | [ 7.88179114e-02 8.99592862e-02 -4.27880883e-03 -5.49414575e-01
-1.10954010e+00 -6.15656972e-01 3.49570811e-01 5.70020139e-01
-3.22739154e-01 6.15686715e-01 1.44615278e-01 -7.59930432e-01
-2.20201880e-01 -7.65679955e-01 -3.80198151e-01 -4.93239611e-01
-3.26871514e-01 9.29277837e-01 -5.59555173e-01 1.96683347e-01
1.62199095e-01 8.27565789e-01 -7.83944368e-01 1.07815899e-01
9.29555237e-01 1.32643282e+00 -1.38385311e-01 6.04124308e-01
-8.75601247e-02 9.69892740e-03 -3.27089757e-01 -1.05220396e-02
4.59180415e-01 -5.34492731e-01 -5.36413252e-01 -1.03584521e-01
7.53965020e-01 -2.12192759e-01 -7.70265162e-02 3.84049743e-01
1.13734424e+00 -4.18158919e-01 8.52533698e-01 -3.59916836e-01
-5.69275200e-01 3.03177029e-01 -2.45409861e-01 6.00092292e-01
-2.00210035e-01 1.57244846e-01 4.63531226e-01 -1.01988113e+00
4.77653235e-01 6.75880194e-01 1.18182623e+00 2.58842707e-01
-1.48262858e+00 -4.14065152e-01 -3.70018005e-01 -4.34990913e-01
-1.34091043e+00 -4.51103628e-01 7.35242903e-01 -6.41800284e-01
9.52967167e-01 2.26232618e-01 1.08455563e+00 5.47291934e-01
1.83551311e-01 4.95592117e-01 1.07775939e+00 -4.77157444e-01
6.50404319e-02 -2.14988038e-01 5.02776466e-02 8.86239529e-01
5.67358315e-01 2.44682208e-01 -1.66489616e-01 -5.25437534e-01
1.20298553e+00 5.09041883e-02 -2.77583927e-01 -6.98393643e-01
-1.28293633e+00 8.01221788e-01 4.62150991e-01 5.96108735e-01
-6.40422821e-01 3.28338772e-01 4.13680196e-01 7.58113265e-02
5.73995173e-01 6.85328066e-01 -5.61064780e-01 -1.59196362e-01
-1.61638415e+00 1.98113903e-01 6.43138349e-01 5.84623396e-01
3.66267443e-01 3.23373020e-01 -4.23699051e-01 7.16128111e-01
1.85213968e-01 5.27231812e-01 4.46709514e-01 -6.23403490e-01
1.38225555e-01 7.21139133e-01 -2.36384645e-01 -8.78385603e-01
-8.56733978e-01 -1.25367975e+00 -1.20625162e+00 8.65742713e-02
5.88823855e-01 -1.47287279e-01 -1.29270566e+00 1.37607372e+00
-1.47295490e-01 2.14577302e-01 -2.66706228e-01 6.61738932e-01
8.93922031e-01 -2.23359808e-01 -1.39704454e-04 -3.01907033e-01
1.22388995e+00 -5.16549051e-01 -3.07731211e-01 -1.14431344e-01
9.46002245e-01 -5.62032402e-01 9.79913771e-01 2.02911839e-01
-1.34727228e+00 -2.99658895e-01 -9.18618083e-01 6.57937005e-02
-5.23129888e-02 6.13310635e-01 9.38359737e-01 1.02555907e+00
-1.38458705e+00 7.85831869e-01 -1.19552159e+00 -2.24871993e-01
1.27642524e+00 6.81911170e-01 -3.21175963e-01 3.09855968e-01
-5.98183811e-01 1.01609361e+00 2.41614189e-02 2.94870794e-01
-7.29951620e-01 -1.11300838e+00 -8.48013639e-01 1.10334665e-01
-2.32625321e-01 -1.19176388e+00 8.05353582e-01 -6.46342754e-01
-1.19463181e+00 1.25676835e+00 -3.36245328e-01 -5.60072124e-01
5.76417923e-01 -1.80664033e-01 1.73022732e-01 8.17650408e-02
-3.87396999e-02 4.48544681e-01 8.23224723e-01 -9.94058967e-01
-1.83221307e-02 -6.06665850e-01 -5.12991786e-01 -6.56473786e-02
-1.97535142e-01 -1.37124404e-01 -1.28761474e-02 -9.95653689e-01
4.32475537e-01 -9.27159786e-01 -6.55345798e-01 2.51332670e-01
8.55469406e-02 6.92762658e-02 3.12928081e-01 -8.08847904e-01
1.21306407e+00 -1.74537802e+00 -1.86502039e-01 5.30472279e-01
5.94309151e-01 4.39553142e-01 -4.55527380e-02 -1.14161409e-01
-1.05822667e-01 6.00424886e-01 -7.70183861e-01 -3.92811269e-01
-5.44885516e-01 -6.75306767e-02 1.17516099e-02 7.14026272e-01
2.71862239e-01 1.46654367e+00 -5.91837108e-01 -4.64011341e-01
1.71050638e-01 6.30550086e-01 -6.98015749e-01 5.81726879e-02
2.31961936e-01 9.45254385e-01 -4.32611406e-01 6.32352412e-01
7.13054717e-01 -4.29161757e-01 1.92711487e-01 -2.99738348e-01
6.34161383e-02 2.77857602e-01 -5.75698435e-01 2.20535374e+00
-6.85257316e-01 3.05478662e-01 -1.54014096e-01 -1.49513638e+00
1.18848312e+00 5.23690045e-01 8.71750653e-01 -4.54438925e-01
3.20164710e-01 6.72233284e-01 3.62602293e-01 -5.41855134e-02
-4.86453086e-01 -3.71545821e-01 1.41566902e-01 6.70833826e-01
1.37474626e-01 -3.29069972e-01 -2.05472670e-02 -2.89533883e-01
9.66890872e-01 1.73564255e-01 5.06023586e-01 -7.51616240e-01
6.74839079e-01 -5.93883544e-02 5.44072509e-01 1.02192235e+00
-1.21803217e-01 9.57618594e-01 1.72728851e-01 -1.20305884e+00
-1.09872139e+00 -1.10901904e+00 -5.55338562e-01 2.06045017e-01
-5.30575454e-01 -3.68292540e-01 -5.91250598e-01 -6.08311415e-01
1.73787456e-02 1.89391479e-01 -6.41895413e-01 -1.20478114e-02
-1.08414197e+00 -1.07608008e+00 7.09593654e-01 8.42149258e-01
2.07539439e-01 -1.11387658e+00 -8.92371714e-01 2.45267496e-01
2.83725429e-02 -7.07031131e-01 -3.87996316e-01 -6.35347469e-03
-1.62408900e+00 -1.01649773e+00 -1.11282134e+00 -7.92899251e-01
9.90702748e-01 -5.31305969e-01 1.44077837e+00 4.03638810e-01
-8.24520469e-01 2.76850581e-01 2.19543781e-02 -6.30061269e-01
-1.97180167e-01 1.88405633e-01 -1.38530657e-02 -1.63655937e-01
1.16642967e-01 -9.64700937e-01 -1.16222286e+00 -2.76371330e-01
-4.07256573e-01 -1.09183557e-01 1.04457343e+00 9.25096810e-01
8.95084620e-01 -6.42205834e-01 7.94012725e-01 -8.47470760e-01
7.92219639e-01 1.35165527e-01 -3.13888401e-01 2.12577537e-01
-9.86832023e-01 2.56125834e-02 4.48082328e-01 -1.96519941e-01
-5.80685139e-01 2.30148032e-01 1.81043059e-01 -4.83514369e-01
-1.86831683e-01 9.20177341e-01 4.18628633e-01 -3.73995543e-01
9.05020654e-01 4.87648010e-01 4.35723335e-01 -4.26151425e-01
3.90236825e-01 4.29822922e-01 4.79054958e-01 -6.02521777e-01
6.03798926e-01 6.74995840e-01 5.08150876e-01 -6.14270091e-01
-7.24375665e-01 -3.64344984e-01 -1.15732265e+00 2.30603784e-01
7.37201393e-01 -7.66754091e-01 -4.48110223e-01 3.19305927e-01
-1.16667700e+00 -2.10066482e-01 -3.96805376e-01 5.51915884e-01
-9.55435097e-01 3.15930009e-01 -3.12429577e-01 -5.39404631e-01
-1.22933877e+00 -1.06218970e+00 1.12961483e+00 -1.04050018e-01
-3.53171527e-01 -1.11061382e+00 1.37474909e-01 2.01063260e-01
9.87215102e-01 5.42236805e-01 9.29675043e-01 -6.87161386e-01
-5.12597680e-01 -4.22936410e-01 -3.76366943e-01 2.41661102e-01
4.78120089e-01 -6.13458872e-01 -8.99583340e-01 -4.36377496e-01
1.80197999e-01 2.83030365e-02 7.60215282e-01 1.16421843e+00
1.43101811e+00 -1.06500655e-01 -2.34941259e-01 1.14613295e+00
1.21125054e+00 3.61915529e-02 4.27776009e-01 2.16951862e-01
6.23248279e-01 -2.02789214e-02 4.97385114e-02 2.87671596e-01
1.61710992e-01 4.26766634e-01 -1.33158371e-01 -8.36734235e-01
-3.66024792e-01 2.86583871e-01 -3.65898848e-01 5.29404759e-01
-6.02622449e-01 4.76013750e-01 -1.28413451e+00 5.57508886e-01
-1.60509789e+00 -6.05006039e-01 1.33409612e-02 2.39642835e+00
8.92522037e-01 -8.00513253e-02 1.38320148e-01 -5.77694327e-02
2.73161680e-01 -1.54639661e-01 -2.38517195e-01 -2.43975505e-01
-3.40911597e-02 9.36015725e-01 3.09650570e-01 4.39645082e-01
-1.32161534e+00 6.28924489e-01 6.75447178e+00 4.08110201e-01
-1.37918198e+00 1.49676606e-01 1.06642532e+00 1.45293653e-01
-1.67541623e-01 1.52717665e-01 -2.69376040e-01 -7.17726052e-02
9.32631075e-01 -1.42667308e-01 2.11782590e-01 4.51514482e-01
4.12596673e-01 2.05371723e-01 -1.18912816e+00 1.26637971e+00
1.45753458e-01 -1.88152623e+00 1.01545706e-01 1.09723173e-01
3.31436574e-01 1.05931036e-01 -1.01209097e-01 -1.30939603e-01
-5.13683677e-01 -1.40985489e+00 1.88396633e-01 8.09245229e-01
1.16218650e+00 -3.77155453e-01 8.38143229e-01 1.69192217e-02
-1.20305431e+00 1.22054115e-01 -1.69973955e-01 1.63385600e-01
2.96909600e-01 9.31941092e-01 -1.08156371e+00 5.25769889e-01
5.40494621e-01 8.30151737e-01 -7.06904948e-01 1.12517905e+00
2.19182283e-01 7.40700662e-01 -4.09188658e-01 4.89470482e-01
-1.74017876e-01 -3.95096451e-01 5.28559864e-01 1.31506264e+00
5.81156909e-01 1.06074534e-01 3.87374371e-01 1.33854651e+00
8.79581422e-02 2.86335617e-01 -6.72606528e-01 -1.71444759e-01
1.09035827e-01 1.40755236e+00 -1.00497937e+00 -3.50191951e-01
-2.91289955e-01 5.42583585e-01 1.68868631e-01 8.35645199e-02
-2.28498489e-01 -1.05307857e-02 1.11681134e-01 6.85132742e-01
2.54786224e-03 -4.52624708e-01 -1.08054340e+00 -9.85620439e-01
7.84458667e-02 -7.32662916e-01 4.04094279e-01 -2.28501782e-01
-1.20121455e+00 8.16660345e-01 -2.66459227e-01 -1.15723848e+00
-2.29446024e-01 -6.19915724e-01 -7.47410476e-01 1.31198633e+00
-1.48765564e+00 -1.56381428e+00 -2.81497568e-01 1.39280915e-01
2.22918883e-01 -4.17510420e-01 1.41110623e+00 2.21610993e-01
3.51052098e-02 5.86244166e-01 -4.36671197e-01 4.08476382e-01
4.62246180e-01 -1.38839281e+00 5.77595532e-01 5.90254724e-01
2.86941469e-01 9.71431375e-01 5.55994771e-02 -7.37116933e-01
-1.18641603e+00 -8.03527892e-01 9.62480903e-01 -7.77698517e-01
1.50761262e-01 -1.42611697e-01 -6.68506920e-01 4.40691501e-01
-1.66135862e-01 7.49429643e-01 8.94846857e-01 2.29712874e-01
1.76704019e-01 -6.79352432e-02 -1.02896142e+00 1.76427424e-01
1.16731167e+00 -4.26129162e-01 -4.58619863e-01 3.13373834e-01
-1.18192293e-01 -5.46162486e-01 -1.18118203e+00 1.04603100e+00
5.91336429e-01 -7.13208497e-01 1.30080891e+00 -6.29119992e-01
7.24891499e-02 -1.19271457e-01 3.10936958e-01 -1.06704164e+00
-3.62692207e-01 -7.09005058e-01 -1.21092901e-01 5.80527842e-01
6.82107091e-01 -5.17668486e-01 1.13779366e+00 6.05212748e-01
-3.45978141e-01 -1.16391921e+00 -9.86140370e-01 -5.81341684e-01
4.57388043e-01 -1.74663812e-01 2.26053461e-01 8.11856449e-01
-2.53283113e-01 -2.04481464e-02 1.25116035e-01 -7.90470466e-02
5.34584939e-01 4.35470968e-01 5.63686669e-01 -1.74148011e+00
7.64120072e-02 -5.85607231e-01 -6.29699290e-01 -3.72114956e-01
3.82438465e-03 -1.61772525e+00 -2.76967645e-01 -1.92211699e+00
2.54081339e-01 -9.45228100e-01 -4.05009598e-01 5.99577725e-01
-7.18227252e-02 3.29128295e-01 2.00109277e-02 2.33477965e-01
1.72074914e-01 4.07125741e-01 1.41435170e+00 -2.22645756e-02
-5.17057359e-01 2.29206011e-01 -7.49545038e-01 7.14238048e-01
7.93735206e-01 -5.39855599e-01 -4.62097764e-01 -3.36942255e-01
5.32517508e-02 1.18657380e-01 4.48573440e-01 -9.88019168e-01
-2.08072681e-02 4.47440118e-01 8.61141503e-01 -3.48063052e-01
2.48381924e-02 -6.75076067e-01 -7.28661343e-02 8.05426419e-01
-1.42642900e-01 3.09057981e-01 4.76987064e-01 1.48376822e-01
-7.88309649e-02 8.74943212e-02 6.93223476e-01 -2.60231942e-01
2.66829759e-01 7.50494659e-01 -1.54417306e-01 2.08455116e-01
4.69650686e-01 -4.22611803e-01 1.60616174e-01 -3.83779794e-01
-1.25125825e+00 -3.38513196e-01 1.00792058e-01 1.19046703e-01
7.50387490e-01 -1.12605739e+00 -1.18809438e+00 4.70349520e-01
-2.52393484e-01 2.69320339e-01 -6.12851195e-02 1.43052423e+00
-8.20543826e-01 5.98951280e-01 -1.59927458e-01 -1.00505555e+00
-9.86551285e-01 1.66833431e-01 7.75140882e-01 -6.03727281e-01
-1.15785229e+00 7.15798914e-01 1.60900772e-01 -6.91684425e-01
-2.01297939e-01 -6.24215424e-01 -9.30668190e-02 -1.93283394e-01
8.71894956e-02 1.34568559e-02 5.07872283e-01 -4.70532954e-01
-5.63371301e-01 8.13691854e-01 1.13883942e-01 1.00470863e-01
1.51988733e+00 2.74764240e-01 -3.02750200e-01 -3.28287408e-02
8.38651299e-01 -1.33332759e-01 -6.41824365e-01 2.81218626e-02
1.26404986e-01 -3.56018662e-01 4.88895655e-01 -1.02331531e+00
-1.32457364e+00 1.06514275e+00 1.25126588e+00 -3.51080358e-01
1.04374814e+00 -8.50755721e-02 6.42625511e-01 2.39860252e-01
2.50689000e-01 -6.77268565e-01 -2.43237615e-01 9.96808112e-02
1.23138821e+00 -1.06329679e+00 2.90647686e-01 -3.73483717e-01
-2.11146414e-01 1.24296713e+00 9.88290757e-02 -3.17466587e-01
1.23943412e+00 3.72252643e-01 5.39329946e-01 -4.56858635e-01
-7.25112930e-02 9.62739661e-02 8.03338945e-01 5.92922509e-01
9.61722434e-01 1.11859269e-01 -7.07104862e-01 7.33062744e-01
-1.74646109e-01 1.94402754e-01 1.02242202e-01 8.50828886e-01
-3.73786725e-02 -1.50314224e+00 8.12463835e-02 1.10588562e+00
-8.49179566e-01 -5.66642761e-01 -2.09060416e-01 4.39617336e-01
-9.31391213e-03 3.75606179e-01 6.80320337e-02 2.82176733e-01
1.46974668e-01 1.37006149e-01 7.53567100e-01 -7.46277690e-01
-7.76419818e-01 3.80517930e-01 -1.55765656e-02 -4.80591387e-01
-4.72590417e-01 -7.49223769e-01 -1.23176944e+00 4.31769818e-01
-3.28974366e-01 -1.45640031e-01 6.97061181e-01 9.62811172e-01
8.30020010e-01 4.78498667e-01 2.38526061e-01 -1.03447998e+00
-2.89429605e-01 -1.06719708e+00 -2.97498941e-01 3.75057489e-01
3.48331600e-01 -4.74042267e-01 -1.26512975e-01 8.81658047e-02] | [14.217845916748047, -2.4569380283355713] |
c436ee24-93c8-4e2f-98d8-3c62f91df129 | electrocardiography-separation-of-mother-and | 1411.1446 | null | http://arxiv.org/abs/1411.1446v1 | http://arxiv.org/pdf/1411.1446v1.pdf | Electrocardiography Separation of Mother and Baby | Extraction of Electrocardiography (ECG or EKG) signals of mother and baby is
a challenging task, because one single device is used and it receives a mixture
of multiple heart beats. In this paper, we would like to design a filter to
separate the signals from each other. | ['Wei Wang'] | 2014-11-05 | null | null | null | null | ['electrocardiography-ecg'] | ['methodology'] | [ 3.38899940e-01 -1.79831535e-01 3.06025565e-01 -5.30503631e-01
-5.45425825e-02 -4.52052861e-01 -3.58599275e-01 1.76375881e-01
-9.49501246e-02 6.47469640e-01 -1.33665621e-01 -4.00205821e-01
1.17216878e-01 -4.91413385e-01 -6.48634881e-02 -6.67998016e-01
-6.16395026e-02 -2.73881555e-01 -1.88549489e-01 1.96616456e-01
-1.47712618e-01 3.82117301e-01 -1.03237510e+00 1.41485363e-01
6.92072213e-01 1.14794946e+00 -4.76832390e-02 1.05103707e+00
8.43804628e-02 5.46035409e-01 -8.61072421e-01 -1.06681667e-01
1.70188457e-01 -1.14988303e+00 -1.59664333e-01 -3.09015095e-01
-1.57502666e-01 -3.67960870e-01 3.02174799e-02 1.02087379e+00
1.07396042e+00 -6.49481475e-01 7.62291551e-01 -8.53653491e-01
3.32818478e-01 6.69954419e-01 -6.11345589e-01 4.22971636e-01
3.03054214e-01 -3.85589808e-01 1.24868691e-01 -6.83862269e-01
1.67019904e-01 5.07430315e-01 1.09783471e+00 3.23613465e-01
-1.24298131e+00 -8.83295536e-01 -4.39812511e-01 -8.75016600e-02
-1.62898588e+00 -3.90546560e-01 1.11793387e+00 -2.56494880e-01
4.89500135e-01 3.57685119e-01 9.60078537e-01 9.92792308e-01
3.90230954e-01 4.53250915e-01 1.12727058e+00 -6.60757124e-01
7.95701742e-02 2.20675275e-01 6.18566200e-02 3.58056933e-01
6.27478540e-01 -1.66946262e-01 -6.02199137e-02 -3.46729815e-01
8.88566613e-01 2.00398862e-01 -6.78030431e-01 2.22517803e-01
-7.70746708e-01 3.23015720e-01 -5.30968308e-01 4.35520530e-01
-6.04188621e-01 1.21156037e-01 2.63668388e-01 6.01786613e-01
-4.08988446e-02 2.62533844e-01 -3.04775894e-01 -1.93440303e-01
-1.09943414e+00 9.04612616e-02 1.09634662e+00 8.44170809e-01
3.50075573e-01 -1.00928634e-01 8.61089081e-02 4.83940780e-01
3.75208110e-01 6.75211251e-01 3.60434651e-01 -4.95013058e-01
3.95210266e-01 7.42334127e-02 1.08480632e-01 -1.30705869e+00
-7.93723702e-01 -3.55238259e-01 -1.16227829e+00 -1.07645504e-01
4.34487998e-01 -8.62637758e-01 -6.20953739e-01 1.29672778e+00
4.14445907e-01 4.62363452e-01 2.23020598e-01 6.83438540e-01
1.39665759e+00 6.00451827e-01 2.74996962e-02 -8.44808757e-01
1.26507998e+00 3.18144821e-02 -1.27581096e+00 -1.79227918e-01
7.32508451e-02 -1.04828739e+00 -2.63480563e-02 7.98106730e-01
-1.02293491e+00 -7.16803730e-01 -1.15111232e+00 4.05788690e-01
2.03779101e-01 2.77821720e-01 2.81018198e-01 9.29253817e-01
-5.08871615e-01 7.07980454e-01 -6.20159745e-01 9.93933827e-02
6.98184222e-02 2.60331571e-01 -1.56258330e-01 5.96041501e-01
-1.36793876e+00 8.59190941e-01 2.11268976e-01 5.93089700e-01
-1.16253033e-01 -3.05989057e-01 -5.98217726e-01 -2.03797385e-01
-2.03187674e-01 -2.92964160e-01 1.08702624e+00 -7.90359378e-01
-1.48584592e+00 6.08675122e-01 -6.66235015e-02 -8.51471350e-02
4.86637741e-01 -2.09520742e-01 -8.46490383e-01 1.89860612e-01
-4.54127222e-01 -5.26647329e-01 1.45963788e+00 -6.37113273e-01
-5.09676158e-01 -5.56324601e-01 -7.05309868e-01 -2.45078072e-01
7.64919221e-02 1.01040035e-01 -1.16450176e-01 -8.50523949e-01
6.89224660e-01 -5.15907824e-01 -1.13592267e-01 -9.83778834e-01
-1.85386807e-01 2.31462374e-01 5.39176762e-01 -1.04649723e+00
1.52638590e+00 -2.33066201e+00 -3.59415561e-02 6.12962425e-01
4.48869199e-01 4.72787082e-01 4.24264908e-01 5.17800987e-01
-1.47075489e-01 -6.92351982e-02 5.94437383e-02 4.58261520e-02
-6.04466379e-01 3.35188471e-02 -1.90737680e-01 9.10616517e-01
4.21227925e-02 6.27837896e-01 -5.36838651e-01 -5.35441756e-01
1.25057340e-01 6.08114064e-01 1.47703618e-01 5.41720450e-01
7.39220083e-01 8.08403075e-01 -5.27303219e-01 4.94641423e-01
1.09825003e+00 1.41687959e-01 4.35577959e-01 -4.09191489e-01
7.10007995e-02 2.24188387e-01 -1.69269228e+00 1.40549719e+00
-1.87834188e-01 3.62258434e-01 2.80711412e-01 -9.46972013e-01
1.30171716e+00 1.01791012e+00 4.51017201e-01 -3.54521245e-01
8.42233479e-01 2.98284829e-01 1.14714973e-01 -1.17913055e+00
-3.57624650e-01 -4.93711501e-01 -9.82991084e-02 5.96692681e-01
1.56301662e-01 -1.47101834e-01 -8.58701095e-02 -2.65540808e-01
1.26937973e+00 -4.03303951e-01 7.65808761e-01 -2.50135571e-01
4.62411046e-01 -5.91328442e-01 1.07562757e+00 6.00076973e-01
-2.83037126e-01 8.21104228e-01 5.29833257e-01 -7.17059433e-01
-4.42541689e-01 -6.89899087e-01 -2.04442158e-01 -2.14898288e-02
5.19609042e-02 -4.55701768e-01 -6.18832290e-01 -4.99378145e-01
2.97506079e-02 -5.60963713e-02 -3.21558625e-01 -9.82548222e-02
-9.55552578e-01 -9.85083222e-01 9.98878598e-01 6.04120016e-01
1.35845557e-01 -7.93176055e-01 -1.13072407e+00 9.41762567e-01
-3.45321417e-01 -8.71725023e-01 -2.54706472e-01 4.81566638e-01
-9.41517532e-01 -9.85144615e-01 -9.02850091e-01 -3.93656373e-01
4.41211045e-01 -1.46949634e-01 1.03570485e+00 1.57369092e-01
-6.64279699e-01 -1.06649645e-01 -5.38387239e-01 -1.19995034e+00
-3.37603986e-01 -1.10097498e-01 1.59018129e-01 6.46861315e-01
4.43395168e-01 -8.54547679e-01 -7.10766613e-01 1.50162607e-01
-4.71844792e-01 -5.64706288e-02 3.59254599e-01 4.45067227e-01
2.75108427e-01 3.36617708e-01 7.13927507e-01 -7.91140914e-01
8.41507912e-01 -3.97320151e-01 -6.41747594e-01 5.91163263e-02
-3.14657986e-01 -4.37906086e-01 7.42664337e-01 -4.77726310e-01
-7.04616070e-01 3.43094349e-01 -3.82734209e-01 -4.49469239e-02
-5.20753741e-01 1.21662505e-01 -3.41965914e-01 -1.56612858e-01
4.05867189e-01 1.84153710e-02 -5.22700092e-03 -7.36772418e-01
-1.75194144e-01 1.10190701e+00 6.92234814e-01 -1.28641248e-01
3.00736487e-01 3.55970822e-02 9.89773497e-02 -9.85279858e-01
-2.95148194e-01 -4.88660067e-01 -5.72284341e-01 -4.13314342e-01
6.83454812e-01 -7.69060612e-01 -7.40585327e-01 7.37302363e-01
-1.66537166e+00 1.03501417e-01 7.04399273e-02 1.10929096e+00
-5.49778827e-02 3.01992476e-01 -5.39023817e-01 -1.06263936e+00
-7.49253213e-01 -7.06165910e-01 4.52206850e-01 5.72434008e-01
-5.64162314e-01 -5.24408460e-01 3.25080365e-01 -2.13245809e-01
2.68682301e-01 6.47912681e-01 2.64233440e-01 -2.23041385e-01
2.29482621e-01 -5.45054913e-01 1.23560816e-01 4.78052914e-01
5.20251215e-01 2.19424739e-01 -1.13660610e+00 -2.29179785e-01
1.05207944e+00 1.92377135e-01 3.64397645e-01 5.22828698e-01
9.60458338e-01 -4.58995923e-02 -1.96908146e-01 8.34379792e-01
1.45902824e+00 6.28035724e-01 8.09768438e-01 -5.53918839e-01
3.88512284e-01 5.55617273e-01 3.51848215e-01 5.44482410e-01
-1.33466930e-03 1.53397873e-01 -2.99180727e-02 -3.85404497e-01
3.80343735e-01 1.20611183e-01 -1.02646507e-01 8.40041459e-01
-5.56011081e-01 -1.62686303e-01 -8.04222345e-01 1.47607207e-01
-1.62843204e+00 -7.48022377e-01 -7.59508252e-01 2.10065150e+00
8.28923166e-01 -1.56625614e-01 1.89920411e-01 8.38082492e-01
7.56954432e-01 -3.11753243e-01 -2.82307208e-01 -4.19567019e-01
1.32105172e-01 6.12161219e-01 5.51694036e-01 7.94314519e-02
-1.05039430e+00 -9.59218293e-02 7.84255505e+00 6.15867674e-02
-1.69385028e+00 -7.50500336e-02 5.05736172e-01 2.13382065e-01
1.27115637e-01 -2.33296826e-01 -7.52743125e-01 8.35880399e-01
9.26966965e-01 1.85390100e-01 -2.35100582e-01 4.40928668e-01
2.39483006e-02 -1.65807739e-01 -9.54712927e-01 1.52931428e+00
5.03290780e-02 -5.33587635e-01 -7.60511696e-01 -2.71620512e-01
2.64148086e-01 -6.47014856e-01 -6.05419517e-01 -2.84331262e-01
-5.95296204e-01 -1.08502436e+00 4.32295144e-01 6.45945430e-01
6.56475544e-01 -6.83309734e-01 9.34602499e-01 6.02021515e-01
-1.16311169e+00 2.18617171e-01 -2.92367399e-01 -2.07568660e-01
2.27402866e-01 1.21237445e+00 -5.93035698e-01 7.07481027e-01
6.97095931e-01 3.97633761e-01 -2.13250548e-01 1.14453661e+00
-3.15796643e-01 9.62376535e-01 -5.66461146e-01 1.90166414e-01
-5.17194331e-01 -1.45576701e-01 3.05611849e-01 1.38932264e+00
4.29261565e-01 8.97426963e-01 1.39229298e-02 6.16552591e-01
3.21442127e-01 3.47688347e-01 -8.01603436e-01 2.82118618e-01
2.25473002e-01 1.34701252e+00 -7.64471412e-01 -3.75055283e-01
-6.55020952e-01 6.68805063e-01 -4.46103841e-01 2.54784137e-01
-8.85380805e-01 -1.21276164e+00 1.98457703e-01 3.06336105e-01
-5.93650900e-02 6.23807013e-02 -5.97741902e-01 -1.15271723e+00
1.79288819e-01 -8.68232131e-01 2.37246260e-01 -2.26384714e-01
-8.61488283e-01 6.60931826e-01 -4.02954698e-01 -1.35320246e+00
-1.88741028e-01 -7.19457269e-02 -1.03450000e+00 1.45792150e+00
-9.89386082e-01 -3.72884512e-01 -4.21358138e-01 5.82107902e-01
-2.28691727e-01 1.02338716e-01 7.77479470e-01 7.85594046e-01
-2.68716514e-01 5.79294086e-01 -6.15546048e-01 3.19966227e-01
5.11068106e-01 -1.05621231e+00 2.85111129e-01 8.62663805e-01
-6.50518537e-02 6.70721292e-01 9.50395823e-01 -6.99832022e-01
-1.42439055e+00 -6.20249212e-01 1.12723231e+00 -1.12907507e-03
-2.26362512e-01 -1.69582129e-01 -1.01809180e+00 1.43306494e-01
1.28053367e-01 1.80523559e-01 9.75166798e-01 -3.12003344e-01
3.57899010e-01 -6.45921469e-01 -1.16987216e+00 -1.18688181e-01
3.35834235e-01 -1.30390733e-01 -8.27005148e-01 -5.48841298e-01
-2.44112521e-01 -4.81219381e-01 -9.88642871e-01 9.82892334e-01
1.00842631e+00 -9.54878986e-01 6.36037171e-01 -3.11728030e-01
-2.58545637e-01 -4.29527640e-01 2.69622952e-01 -1.09045231e+00
-1.86803818e-01 -1.14984882e+00 -1.59980386e-01 1.36164534e+00
6.36672229e-02 -7.93588459e-01 4.57087904e-01 4.92467821e-01
5.70891678e-01 -6.00760758e-01 -5.51742792e-01 -6.14188373e-01
-7.38377810e-01 -2.18669266e-01 6.78927660e-01 6.88589513e-01
3.16898555e-01 5.51914334e-01 -9.08540964e-01 1.90587223e-01
7.81042516e-01 1.47409379e-01 4.94456947e-01 -1.36916924e+00
-4.66130733e-01 9.13386270e-02 -4.62374032e-01 -6.03587747e-01
-7.43417561e-01 -2.17987835e-01 1.66705236e-01 -1.26325870e+00
-4.32606190e-01 -3.96470457e-01 -5.89760780e-01 -5.33680432e-02
-3.33331317e-01 3.38654369e-01 -1.68635063e-02 -2.76991397e-01
3.14219818e-02 -1.48245052e-01 8.19908202e-01 2.27813631e-01
-5.97871542e-01 6.43052757e-01 -5.75093627e-01 9.82213736e-01
7.70989239e-01 -7.97704279e-01 -4.15909410e-01 -5.41155413e-02
3.70761365e-01 7.17002332e-01 4.06965502e-02 -1.03945363e+00
1.58294708e-01 1.67872518e-01 8.55108559e-01 -8.15103412e-01
-4.20761257e-02 -7.88796961e-01 9.47808385e-01 5.16211569e-01
1.64338291e-01 6.42053932e-02 -1.85787573e-01 1.20387711e-01
-4.62393850e-01 -4.26406473e-01 9.28985536e-01 -3.08605582e-01
2.92835861e-01 1.68773964e-01 -7.50571251e-01 -4.65767421e-02
7.61715531e-01 -9.13824812e-02 4.66440529e-01 -2.06009820e-01
-7.90503025e-01 4.08017524e-02 -1.88983589e-01 2.44587101e-02
7.91976810e-01 -1.21914542e+00 -6.66341305e-01 6.21879697e-01
-2.80496955e-01 1.25096977e-01 2.83358335e-01 1.15819860e+00
-8.20950866e-01 -1.69728268e-02 -3.51666093e-01 -4.36880410e-01
-1.71285021e+00 1.80586696e-01 3.22783798e-01 1.19360320e-01
-9.17696357e-01 6.70318723e-01 -2.32985348e-01 4.12032515e-01
3.27932268e-01 -4.62433845e-01 -6.31310761e-01 3.77399504e-01
1.09753513e+00 6.58220708e-01 2.41153881e-01 -2.10177138e-01
-5.10339975e-01 9.03385758e-01 3.40626568e-01 1.62707835e-01
1.11670554e+00 -1.13326773e-01 -3.34658653e-01 3.53374094e-01
1.20908511e+00 1.46868378e-01 -2.24131942e-01 2.60633707e-01
-1.83317587e-01 -5.04759550e-01 -2.75709659e-01 -2.24485889e-01
-1.01806223e+00 9.94683385e-01 6.52381480e-01 5.36886930e-01
1.54106617e+00 -4.28117871e-01 1.00919533e+00 1.59209576e-02
5.10989308e-01 -1.16859901e+00 -4.00378913e-01 -1.71947718e-01
6.96846426e-01 -8.08892369e-01 1.29301306e-02 -4.34792936e-01
-2.91311443e-01 1.40041387e+00 4.32536565e-02 -2.65174896e-01
1.22216606e+00 5.59158087e-01 5.79172015e-01 -9.27240625e-02
-3.94561023e-01 1.28582224e-01 7.05744773e-02 5.24428368e-01
6.49772406e-01 6.58901036e-02 -1.01389825e+00 1.22966421e+00
3.16773951e-02 6.05056524e-01 6.42251253e-01 1.20412838e+00
-3.20881695e-01 -1.39575195e+00 -6.95835173e-01 6.36727691e-01
-1.51657665e+00 3.82880300e-01 -1.75315887e-01 3.83845679e-02
4.91173714e-01 1.12709785e+00 -4.57462788e-01 -3.89488012e-01
4.93291050e-01 1.82581276e-01 5.74550688e-01 -4.76761043e-01
-6.65648460e-01 6.25099659e-01 -4.17203829e-02 -3.83976728e-01
-4.58455652e-01 -5.50748050e-01 -1.23810816e+00 8.14569816e-02
-3.43342662e-01 2.72376627e-01 7.88025558e-01 5.57117701e-01
3.70143056e-02 5.20501137e-01 8.42364013e-01 -3.39138418e-01
-4.08825040e-01 -9.96723711e-01 -1.30543554e+00 1.04088999e-01
7.71602452e-01 -1.28021151e-01 -2.80432135e-01 3.89429837e-01] | [14.171606063842773, 3.171779155731201] |
3102fced-683c-40a6-b7e2-b646f104476f | icassp-2022-acoustic-echo-cancellation | 2202.13290 | null | https://arxiv.org/abs/2202.13290v1 | https://arxiv.org/pdf/2202.13290v1.pdf | ICASSP 2022 Acoustic Echo Cancellation Challenge | The ICASSP 2022 Acoustic Echo Cancellation Challenge is intended to stimulate research in acoustic echo cancellation (AEC), which is an important area of speech enhancement and still a top issue in audio communication. This is the third AEC challenge and it is enhanced by including mobile scenarios, adding speech recognition rate in the challenge goal metrics, and making the default sample rate 48 kHz. In this challenge, we open source two large datasets to train AEC models under both single talk and double talk scenarios. These datasets consist of recordings from more than 10,000 real audio devices and human speakers in real environments, as well as a synthetic dataset. We also open source an online subjective test framework and provide an online objective metric service for researchers to quickly test their results. The winners of this challenge are selected based on the average Mean Opinion Score achieved across all different single talk and double talk scenarios, and the speech recognition word acceptance rate. | ['Robert Aichner', 'Karsten Sørensen', 'Sebastian Braun', 'Hannes Gamper', 'Marju Purin', 'Tanel Parnamaa', 'Ando Saabas', 'Ross Cutler'] | 2022-02-27 | null | null | null | null | ['acoustic-echo-cancellation', 'acoustic-echo-cancellation'] | ['medical', 'speech'] | [ 1.42663226e-01 -2.92279065e-01 5.90974689e-01 -2.99945951e-01
-1.46760917e+00 -5.47424138e-01 3.80751520e-01 -2.81585395e-01
-5.70817113e-01 2.43024051e-01 6.97951674e-01 -3.65835726e-01
1.23602502e-01 6.73803389e-02 -3.99003863e-01 -4.53086764e-01
-3.84829253e-01 -2.16657650e-02 2.86469340e-01 -3.48557562e-01
9.29526463e-02 6.30334066e-03 -1.78282356e+00 4.45194155e-01
7.82058537e-01 9.42736089e-01 2.86768526e-01 1.21165252e+00
2.00944945e-01 2.22111911e-01 -1.04124033e+00 -4.95161206e-01
3.81780118e-02 -4.23005700e-01 -2.55115986e-01 -3.73990476e-01
4.32286650e-01 -4.54833359e-02 -1.13921754e-01 1.09199584e+00
1.58471942e+00 2.73509502e-01 2.11324364e-01 -8.27894390e-01
-1.93126663e-03 7.38057733e-01 -1.52275693e-02 3.03983033e-01
7.22882211e-01 2.32026652e-01 8.63669932e-01 -1.27031827e+00
1.72937542e-01 1.13516784e+00 8.50291014e-01 7.13421166e-01
-7.12435484e-01 -1.02549934e+00 -6.50014654e-02 4.00247663e-01
-1.16296780e+00 -1.30935252e+00 6.06320798e-01 -9.83001664e-03
1.22139800e+00 6.82982266e-01 5.51763833e-01 1.30410659e+00
-3.37069809e-01 8.03161323e-01 1.01004839e+00 -6.53532326e-01
5.89156449e-01 1.51928842e-01 -2.20535006e-02 -1.34013489e-01
-3.49025965e-01 4.48400080e-01 -1.08329964e+00 -1.83782637e-01
-7.80934766e-02 -8.08678269e-01 -7.54474342e-01 3.73221308e-01
-1.10822570e+00 3.06773484e-01 -2.99670249e-01 2.68401295e-01
-1.71446845e-01 2.52931677e-02 3.39692593e-01 6.69357896e-01
3.66543710e-01 4.19855326e-01 -4.17392969e-01 -7.94649303e-01
-8.60170305e-01 4.15900439e-01 1.16323316e+00 9.26276267e-01
6.84724227e-02 6.57108068e-01 -1.63864985e-01 1.48024130e+00
4.28801060e-01 1.09698224e+00 5.76965809e-01 -9.95132446e-01
6.42832994e-01 -3.70817870e-01 2.21462920e-01 -7.38942921e-01
-1.91591337e-01 -8.45225096e-01 -5.51822364e-01 8.72411649e-04
-9.81189460e-02 -5.37948430e-01 -7.66504705e-01 1.64411843e+00
5.57902604e-02 5.01742840e-01 3.51527594e-02 1.01426816e+00
8.78650486e-01 7.27715015e-01 -1.66610911e-01 -2.99053490e-01
1.19590819e+00 -1.01732266e+00 -1.28669906e+00 -4.24177140e-01
4.37448353e-01 -1.22366571e+00 1.00744104e+00 8.79897594e-01
-1.27186215e+00 -5.08015633e-01 -1.30009222e+00 4.74162966e-01
-3.63152683e-01 -1.31476417e-01 3.04267079e-01 1.47605705e+00
-1.37230647e+00 1.16907485e-01 -3.95636767e-01 1.85911790e-01
-2.75370985e-01 3.27533931e-01 -9.28827226e-02 -5.99119626e-02
-1.50810254e+00 6.36086345e-01 -3.76297563e-01 3.53888758e-02
-9.28920686e-01 -9.71934199e-01 -6.49387717e-01 1.15572259e-01
1.71084076e-01 4.06441931e-03 1.70583487e+00 -5.23007989e-01
-1.77252769e+00 5.05150259e-01 -1.80278212e-01 -5.33281088e-01
3.19241613e-01 -4.49856013e-01 -1.46549678e+00 -2.99063027e-01
-3.11491847e-01 4.46568012e-01 9.39575672e-01 -1.03766084e+00
-7.73363948e-01 -3.46320532e-02 -5.36341131e-01 3.47690433e-01
-3.29148293e-01 3.35387498e-01 -6.94585621e-01 -8.95862520e-01
-6.18590489e-02 -8.08913052e-01 -6.72329813e-02 -6.27772033e-01
-1.87844947e-01 1.94903597e-01 7.52492845e-01 -1.02677691e+00
1.37698531e+00 -2.53613257e+00 -2.91224688e-01 3.23534489e-01
-2.57641941e-01 7.47875392e-01 -3.53745103e-01 1.70093492e-01
-6.86054900e-02 9.08058062e-02 -1.67549402e-01 -6.68862641e-01
2.49011189e-01 -4.21160996e-01 -2.91559875e-01 1.01836817e-02
-2.32530702e-02 2.32773155e-01 -6.65092945e-01 7.30297044e-02
2.67727494e-01 6.26062036e-01 -7.28170991e-01 2.92279422e-01
3.48120779e-01 2.12355465e-01 2.32476011e-01 4.38336760e-01
1.10881996e+00 5.86666167e-01 -7.29187205e-02 1.20783664e-01
-2.02004954e-01 6.35423720e-01 -1.74441218e+00 1.48204362e+00
-8.14292729e-01 8.82167101e-01 7.26207018e-01 -4.54179466e-01
8.36405396e-01 8.91782701e-01 5.33245876e-02 -9.16625798e-01
-8.78271237e-02 8.02379906e-01 1.19828708e-01 -2.49609068e-01
4.72605914e-01 1.01408646e-01 2.12358430e-01 2.56958783e-01
3.08168054e-01 -5.76626420e-01 -1.90049466e-02 1.00975804e-01
1.18467391e+00 -7.83810854e-01 -1.91321433e-01 -3.00489783e-01
7.06004024e-01 -8.40747774e-01 4.21108276e-01 8.75762284e-01
-5.71533501e-01 8.83583069e-01 -2.18692943e-01 1.69451028e-01
-6.45099759e-01 -1.24983585e+00 -8.83492902e-02 1.03303528e+00
-1.86180398e-01 -6.13672197e-01 -9.98758912e-01 -8.36795866e-02
-4.06467527e-01 7.45948076e-01 7.10493699e-03 -1.09614775e-01
-3.52512211e-01 -3.52493197e-01 8.91774178e-01 1.39210463e-01
4.04090196e-01 -1.03129983e+00 2.53162310e-02 3.63308698e-01
-6.88477159e-01 -1.27480698e+00 -9.78531063e-01 1.97348014e-01
-2.62370735e-01 -5.78282595e-01 -1.19429410e+00 -9.65834022e-01
-1.64689139e-01 2.34687299e-01 1.07243514e+00 -1.26464188e-01
-1.97426736e-01 7.45955825e-01 -5.44525504e-01 -8.08220387e-01
-5.74194252e-01 -1.87978167e-02 5.45731723e-01 4.45519909e-02
1.74591795e-01 -4.90455866e-01 -7.15228200e-01 6.52255535e-01
-5.64170003e-01 -4.22865391e-01 2.21898660e-01 4.13904488e-01
1.80450156e-01 -6.60962015e-02 8.78797352e-01 -2.83844888e-01
1.21289766e+00 -5.51356450e-02 -4.98918325e-01 1.71488017e-01
-5.06469190e-01 -3.79311293e-01 1.56187296e-01 -5.63810170e-01
-1.21606278e+00 -1.96006209e-01 -1.05221951e+00 6.02422431e-02
-2.33051218e-02 2.58489639e-01 -4.58093435e-01 -2.87225656e-02
6.50505900e-01 2.39479944e-01 -4.64498162e-01 -6.96121156e-01
9.62010026e-02 1.41390467e+00 6.73767507e-01 -2.40751505e-01
4.99001116e-01 -1.14319749e-01 -6.59226120e-01 -1.25772250e+00
-3.32285851e-01 -7.79784322e-01 1.78435147e-01 -4.39769536e-01
3.63097847e-01 -1.03639233e+00 -6.59330428e-01 8.37904274e-01
-1.15940845e+00 -1.99467167e-01 -2.68069431e-02 9.84944463e-01
-2.18792871e-01 9.31680575e-02 -3.73036921e-01 -1.37796521e+00
-6.65005565e-01 -1.25689256e+00 1.05859864e+00 9.24194604e-02
-2.61417627e-01 -5.80929995e-01 2.58646250e-01 2.05759168e-01
1.13427639e+00 -7.48718739e-01 2.47957394e-01 -5.94062865e-01
-1.27473129e-02 -2.66883403e-01 3.65597427e-01 7.49656439e-01
-4.92778979e-03 -3.81176114e-01 -1.49535811e+00 -4.15348411e-01
2.31002361e-01 -1.82866395e-01 6.98676467e-01 4.72858280e-01
8.24267924e-01 9.19708908e-02 4.53698076e-03 4.07762408e-01
7.46105373e-01 6.01621509e-01 9.75628138e-01 -1.87032774e-01
-9.14086923e-02 6.04099095e-01 2.17015371e-01 4.24362928e-01
-1.25232935e-01 8.63730431e-01 5.31835034e-02 -2.72081252e-02
-5.01775444e-01 -1.21009313e-01 6.67576134e-01 1.72034895e+00
2.00957790e-01 -6.66336238e-01 -8.08505297e-01 4.93055463e-01
-9.14561629e-01 -7.90491462e-01 -2.17764691e-01 2.52052641e+00
9.47037041e-01 1.11418977e-01 -9.84548926e-02 6.49319351e-01
7.73056209e-01 2.85264160e-02 -1.24343425e-01 -6.65720105e-01
-4.54373389e-01 6.75319672e-01 3.01239789e-01 9.86493528e-01
-8.65763724e-01 6.16061985e-01 7.27913952e+00 1.16365898e+00
-1.27257466e+00 1.69446379e-01 4.52385634e-01 -1.96843699e-01
-3.46397191e-01 -4.13711220e-01 -8.68059874e-01 3.63138497e-01
1.62101698e+00 6.13689274e-02 6.43846333e-01 4.90547031e-01
3.49546999e-01 1.08085245e-01 -6.86642766e-01 1.24398077e+00
2.25910753e-01 -9.76089716e-01 -5.01524031e-01 -7.32989386e-02
6.08846366e-01 3.25798333e-01 4.73050296e-01 7.24122703e-01
-3.84330228e-02 -8.60308707e-01 6.98038936e-01 2.24180326e-01
9.95991468e-01 -4.73198056e-01 6.75564647e-01 6.40878752e-02
-1.17739379e+00 7.09020421e-02 6.29356354e-02 1.82394966e-01
3.63972396e-01 5.73903501e-01 -6.99446976e-01 1.84118673e-01
9.87265050e-01 1.22558512e-01 -2.68986166e-01 1.58589709e+00
-3.59662287e-02 1.22491896e+00 -4.95104074e-01 -1.52531296e-01
-1.93029463e-01 3.81579787e-01 8.98274064e-01 1.67433786e+00
5.98472297e-01 2.31078211e-02 -4.87493157e-01 1.67422876e-01
-1.39802560e-01 1.68430477e-01 -2.62344152e-01 1.95663497e-01
7.96560824e-01 8.85794938e-01 -2.11661477e-02 1.96467806e-02
-1.63466528e-01 8.76285315e-01 -5.15771210e-01 6.36587977e-01
-8.15751016e-01 -8.85116160e-01 7.24236190e-01 -1.56983837e-01
1.51727408e-01 -1.40673056e-01 5.99901415e-02 -7.58373499e-01
4.85111997e-02 -1.38157701e+00 -1.85391665e-01 -7.96122670e-01
-9.29010570e-01 7.08596468e-01 -4.29975480e-01 -1.37264168e+00
-4.02869016e-01 -7.56684899e-01 -6.39370263e-01 1.18966186e+00
-1.41353703e+00 -2.56830394e-01 4.39388864e-02 5.44167340e-01
8.27824354e-01 -3.70536208e-01 1.12855482e+00 1.10175800e+00
-1.98800460e-01 1.27098250e+00 3.01227480e-01 -2.33612046e-01
9.60031629e-01 -1.05631030e+00 8.04310024e-01 6.18012369e-01
1.91213712e-01 5.86760521e-01 1.07315099e+00 -2.57846981e-01
-1.16901374e+00 -7.54500210e-01 1.06191909e+00 -1.35368556e-01
3.53166789e-01 -8.69284511e-01 -8.52747083e-01 -9.46485102e-02
3.83394271e-01 -3.23220313e-01 7.79781759e-01 2.41308585e-01
-1.15342699e-01 -2.71120220e-01 -8.51049006e-01 6.26837969e-01
1.06859803e+00 -6.53230786e-01 -1.52495280e-01 5.14552295e-02
1.00654328e+00 -5.70377648e-01 -5.73171556e-01 5.04902363e-01
6.91197038e-01 -8.64041209e-01 9.27772224e-01 -9.64105874e-02
-1.66805729e-01 -4.08080705e-02 -5.33227801e-01 -1.69019854e+00
2.17238605e-01 -1.23800361e+00 3.17153777e-03 1.56006408e+00
1.05552089e+00 -6.13788664e-01 5.18961012e-01 2.78558731e-01
-5.54151475e-01 -2.23817274e-01 -1.06556034e+00 -1.00131083e+00
-9.40860510e-02 -1.26102173e+00 5.10096312e-01 3.90697271e-01
-7.80496895e-02 1.73529252e-01 -6.12344801e-01 1.47070423e-01
4.14580703e-01 -9.46008742e-01 6.11785173e-01 -8.45453143e-01
-5.00748873e-01 -3.12653333e-01 -1.97680622e-01 -1.28441882e+00
-3.46335381e-01 -4.26292837e-01 5.29850423e-01 -1.11989284e+00
-5.59879780e-01 -2.97871858e-01 -2.92978317e-01 -1.54246569e-01
-1.29298465e-02 9.53199491e-02 2.03352988e-01 -2.39309430e-01
-4.39995468e-01 7.88072705e-01 9.02113974e-01 -4.41919118e-01
-3.40332001e-01 5.89956164e-01 -6.38103306e-01 4.92131859e-01
7.58899927e-01 -4.21488255e-01 -4.01813656e-01 -5.33146322e-01
-2.68604811e-02 1.36355907e-01 -7.07732886e-03 -1.48111963e+00
4.92022306e-01 3.69660795e-01 -1.59231395e-01 -5.20467460e-01
8.26339543e-01 -6.07876301e-01 -2.58640777e-02 2.60698915e-01
-6.26389742e-01 -1.70396119e-01 5.71431041e-01 4.94633198e-01
-4.28943038e-01 -8.05074647e-02 6.42496109e-01 3.41806620e-01
-4.90567803e-01 -2.13897526e-01 -6.09600604e-01 3.97647202e-01
2.44902402e-01 -3.72348959e-03 -7.37138316e-02 -1.12985778e+00
-7.58551717e-01 1.12378284e-01 -4.69548076e-01 7.41022944e-01
7.91924179e-01 -1.19297576e+00 -1.02292287e+00 4.14517879e-01
1.67586178e-01 -7.06059813e-01 5.49975812e-01 7.02515244e-01
-4.83909324e-02 5.70537090e-01 3.32601935e-01 -5.46059668e-01
-1.43335056e+00 -1.68769687e-01 6.58982992e-01 8.74003321e-02
-2.75888592e-01 1.20776129e+00 -8.01852420e-02 -6.99168742e-01
8.61618996e-01 -1.02758318e-01 -8.07233378e-02 -5.41595399e-01
1.03025007e+00 4.71566290e-01 8.53452563e-01 -5.09629071e-01
-4.10551190e-01 2.94400841e-01 1.35168135e-01 -1.00263512e+00
7.34326482e-01 -2.47891143e-01 5.16202211e-01 2.81642377e-01
1.27184820e+00 6.87841058e-01 -6.67314470e-01 -1.55022085e-01
-1.40101925e-01 -4.31158811e-01 2.84113497e-01 -1.30481672e+00
-7.61685789e-01 1.06141412e+00 1.43598270e+00 4.29289602e-02
1.26691020e+00 -3.42701107e-01 7.94279218e-01 2.81283289e-01
2.48834401e-01 -1.36702871e+00 -1.15852784e-02 8.19993854e-01
1.19597304e+00 -1.07117736e+00 -6.51913583e-01 -3.73293221e-01
-5.91163397e-01 5.44882178e-01 3.97155851e-01 4.21007603e-01
1.06893504e+00 7.45330989e-01 5.79111636e-01 2.82705992e-01
-7.12581396e-01 -2.01537125e-02 4.34185177e-01 1.01839638e+00
8.60727906e-01 1.14950366e-01 -2.91384071e-01 9.58915412e-01
-6.22226536e-01 -4.25505549e-01 1.62984833e-01 5.06461143e-01
-4.86287713e-01 -1.28430831e+00 -4.17088568e-01 2.89198011e-01
-6.40827477e-01 -4.08366710e-01 -4.85151619e-01 1.56314433e-01
-2.47293770e-01 1.82660306e+00 -2.17629150e-01 -7.58887768e-01
7.79362440e-01 -3.10585238e-02 -9.15673450e-02 -2.10057601e-01
-7.53615260e-01 3.13271552e-01 3.96290570e-01 -2.58341432e-01
6.23691678e-02 -4.98783022e-01 -1.05960393e+00 -1.77022889e-01
-6.07767165e-01 5.52882254e-01 1.30766988e+00 6.23926163e-01
4.84079808e-01 8.03523302e-01 7.66827047e-01 -7.63887584e-01
-7.29959190e-01 -1.33726084e+00 -5.87592006e-01 2.51996577e-01
4.52006280e-01 -3.15256327e-01 -8.50165427e-01 -2.13873640e-01] | [14.976506233215332, 5.934491157531738] |
6f460abc-0242-441f-840c-a14bfa38dfe1 | object-contour-and-edge-detection-with | 1904.13353 | null | https://arxiv.org/abs/1904.13353v2 | https://arxiv.org/pdf/1904.13353v2.pdf | Object Contour and Edge Detection with RefineContourNet | A ResNet-based multi-path refinement CNN is used for object contour detection. For this task, we prioritise the effective utilization of the high-level abstraction capability of a ResNet, which leads to state-of-the-art results for edge detection. Keeping our focus in mind, we fuse the high, mid and low-level features in that specific order, which differs from many other approaches. It uses the tensor with the highest-levelled features as the starting point to combine it layer-by-layer with features of a lower abstraction level until it reaches the lowest level. We train this network on a modified PASCAL VOC 2012 dataset for object contour detection and evaluate on a refined PASCAL-val dataset reaching an excellent performance and an Optimal Dataset Scale (ODS) of 0.752. Furthermore, by fine-training on the BSDS500 dataset we reach state-of-the-art results for edge-detection with an ODS of 0.824. | ['Vijesh Soorya Rao', 'Udo Zoelzer', 'Andre Peter Kelm'] | 2019-04-30 | null | null | null | null | ['contour-detection'] | ['computer-vision'] | [-4.00228538e-02 5.18959016e-02 7.30434358e-02 6.85751811e-02
-5.08431375e-01 -2.98168153e-01 4.80527014e-01 2.90972203e-01
-7.59934664e-01 2.81753540e-01 -1.01643831e-01 -8.63073394e-02
1.07610881e-01 -9.57415938e-01 -5.38715541e-01 -3.50665718e-01
-3.10470790e-01 2.19548285e-01 1.11836231e+00 -5.59057117e-01
1.80073276e-01 9.05771613e-01 -1.82400739e+00 4.42440242e-01
5.96451402e-01 1.30722630e+00 -1.26828089e-01 8.42725337e-01
-1.72825411e-01 5.92845201e-01 -4.40400422e-01 -5.26268244e-01
3.62634301e-01 3.56330462e-02 -8.55243683e-01 -2.45844498e-01
9.58607912e-01 -5.30591235e-02 -4.99645025e-02 1.07254910e+00
3.29853684e-01 -8.11415985e-02 4.38475937e-01 -7.78152823e-01
-2.84001440e-01 2.24402294e-01 -7.77107596e-01 2.92986900e-01
1.12400368e-01 -2.39598736e-01 9.83093023e-01 -1.07357347e+00
1.00477850e+00 9.58948612e-01 1.12147653e+00 3.71020168e-01
-1.20605624e+00 -4.01292652e-01 2.09521621e-01 2.78195113e-01
-1.42563152e+00 1.90344304e-01 7.03599572e-01 -4.97649759e-01
9.32615280e-01 -5.03609665e-02 9.62314427e-01 4.79125589e-01
4.34804827e-01 6.53092682e-01 1.11484802e+00 -3.60941857e-01
4.24466878e-02 -2.14134410e-01 3.87622148e-01 9.55870509e-01
4.01604414e-01 3.18685412e-01 -4.01097447e-01 3.75965863e-01
8.12472343e-01 -3.42418551e-01 -4.43220744e-03 -4.11740422e-01
-9.23327088e-01 7.93005705e-01 9.74639893e-01 5.04443586e-01
-5.79004467e-01 2.01712266e-01 4.35003787e-01 1.23804770e-01
5.19289374e-01 2.85741001e-01 -6.52635098e-01 1.26470760e-01
-1.29574800e+00 2.03930929e-01 7.22592354e-01 6.67573512e-01
8.49110067e-01 1.62548572e-01 -4.19477731e-01 5.66614509e-01
-1.84501186e-02 -8.36022198e-02 4.03832309e-02 -6.88008070e-01
4.86928299e-02 7.74746358e-01 -8.07457566e-02 -7.81280220e-01
-8.90120566e-01 -1.03066671e+00 -8.15081894e-01 1.04369962e+00
6.00386560e-01 -1.70197770e-01 -1.43542016e+00 1.23449957e+00
3.82791609e-01 3.39025855e-01 -6.38591945e-02 9.45172548e-01
1.07478392e+00 3.55939448e-01 1.06006168e-01 1.93718895e-01
1.73887300e+00 -1.06445193e+00 -2.10343495e-01 -8.24381858e-02
5.61033726e-01 -7.70804465e-01 7.50839472e-01 6.24072611e-01
-9.34337616e-01 -8.13178003e-01 -1.34819055e+00 -1.21314824e-01
-5.99434674e-01 2.42790893e-01 7.88632870e-01 7.02266574e-01
-1.41093290e+00 9.52960968e-01 -6.88885033e-01 -1.89301103e-01
5.64089239e-01 1.72237307e-01 -3.89791906e-01 7.78905824e-02
-9.06396031e-01 8.94519210e-01 7.17755556e-01 1.57708719e-01
-5.92152357e-01 -9.21290815e-01 -7.30436504e-01 1.57104000e-01
3.89215201e-01 -6.15715384e-01 7.28924453e-01 -5.07494569e-01
-1.40110469e+00 8.96585405e-01 2.94883817e-01 -7.35410213e-01
8.74656796e-01 -3.04152429e-01 -3.11224014e-01 2.88574845e-01
-7.97607154e-02 1.12933481e+00 8.42676163e-01 -1.28164029e+00
-1.24421275e+00 -9.60113630e-02 2.90985137e-01 -1.10360488e-01
-3.10535163e-01 8.83185863e-02 -5.70804477e-01 -7.60110795e-01
1.58563927e-01 -8.03509355e-01 -1.90405712e-01 8.71396363e-02
-2.30481982e-01 -3.01647097e-01 8.39563429e-01 -4.57658589e-01
9.67784107e-01 -2.02074051e+00 1.74616918e-01 8.49895701e-02
3.72541994e-01 4.62149024e-01 -2.16311231e-01 -6.29820973e-02
-2.46499762e-01 1.46577209e-01 -3.11642230e-01 -6.64102614e-01
-4.14289206e-01 -2.72892296e-01 3.22001338e-01 2.90052921e-01
5.96897900e-01 8.96654248e-01 -8.31839263e-01 -6.25003755e-01
4.39831167e-01 7.24661410e-01 -6.56627655e-01 8.66203662e-03
-9.91287604e-02 1.02209665e-01 -1.11546427e-01 4.85356838e-01
9.68031287e-01 -6.57603517e-02 -3.84733111e-01 -5.81242502e-01
-6.52445018e-01 -2.43102536e-01 -1.39229751e+00 1.69991219e+00
-3.63391429e-01 8.42279434e-01 4.38492745e-03 -4.09964204e-01
9.70274210e-01 7.78241903e-02 6.89660370e-01 -5.90978980e-01
1.34036615e-01 1.94212258e-01 1.79099105e-02 8.25600103e-02
8.65835249e-01 1.62757993e-01 4.77646664e-02 -2.41922721e-01
4.24979985e-01 -1.84282124e-01 6.19287729e-01 8.54781941e-02
1.03939748e+00 3.89259309e-01 9.47002694e-02 -7.47224092e-01
6.92383885e-01 1.64761037e-01 3.74685049e-01 5.87146461e-01
-1.28231928e-01 1.02284396e+00 5.08287549e-01 -6.43058717e-01
-1.00015378e+00 -8.49339604e-01 -4.75915909e-01 1.19279122e+00
2.34559886e-02 -5.61032534e-01 -1.05023551e+00 -6.70394957e-01
-1.58937782e-01 4.89865392e-01 -1.06806517e+00 1.09865613e-01
-7.74153411e-01 -8.58437657e-01 5.14033377e-01 6.63343608e-01
9.52672958e-01 -1.27999246e+00 -9.68316138e-01 3.87744308e-01
3.25829327e-01 -1.32779574e+00 -7.27685392e-02 3.67738128e-01
-6.61528051e-01 -1.10860038e+00 -9.43545580e-01 -8.04785430e-01
4.37298656e-01 -5.98868355e-02 1.33424973e+00 3.17075908e-01
-5.54703534e-01 -4.87524644e-03 -5.36377251e-01 -2.73918539e-01
-2.40974814e-01 3.88818294e-01 -6.14491940e-01 -3.04202195e-02
-9.31598842e-02 -1.75518960e-01 -7.12228775e-01 9.52296257e-02
-9.16041315e-01 -7.18011521e-03 5.61478913e-01 7.31400490e-01
4.21947926e-01 -9.31179337e-03 2.23516554e-01 -6.43143773e-01
3.09437424e-01 2.49770612e-01 -9.02681231e-01 1.34277707e-02
-6.18998528e-01 -8.89878348e-03 6.29711747e-01 -1.86790973e-01
-9.01068330e-01 3.39736760e-01 -5.56743562e-01 -1.59817994e-01
-3.24279308e-01 3.38759094e-01 4.42962319e-01 -5.54299295e-01
7.35948563e-01 -1.25677407e-01 -5.39651155e-01 -5.54695368e-01
5.14940321e-01 -1.50375813e-02 7.53768563e-01 -2.12947711e-01
8.24258745e-01 4.98612046e-01 3.62893701e-01 -9.01072979e-01
-9.78549898e-01 -5.11784196e-01 -9.16009903e-01 -3.53662431e-01
1.19910514e+00 -6.73870385e-01 -7.72619247e-01 8.32083881e-01
-1.15175951e+00 -3.17806065e-01 -5.13883352e-01 1.39735878e-01
-2.88856059e-01 1.46474108e-01 -7.60227621e-01 -5.01227021e-01
-3.80115449e-01 -1.01280439e+00 1.16908789e+00 3.98856252e-01
3.39451671e-01 -8.19978476e-01 4.84731570e-02 -8.04234743e-02
4.96517658e-01 5.60732245e-01 5.96612215e-01 -3.17885816e-01
-5.76208532e-01 -1.09745137e-01 -7.14631617e-01 3.18749905e-01
-3.23477358e-01 1.58611730e-01 -9.77924943e-01 -3.11134040e-01
-3.43529314e-01 -1.71432287e-01 1.49495959e+00 4.23891276e-01
9.52705264e-01 3.70096058e-01 -1.12138942e-01 8.90348792e-01
1.69652152e+00 -2.80748308e-01 8.63504648e-01 5.29669642e-01
8.77466381e-01 3.06864023e-01 5.52712202e-01 1.84343383e-01
3.53899211e-01 7.78998554e-01 6.67149901e-01 -6.47899449e-01
-6.35816455e-01 6.55310601e-02 -1.06107496e-01 2.40156740e-01
-4.39038545e-01 7.23549351e-02 -7.74289608e-01 5.19071281e-01
-1.66764867e+00 -6.08931661e-01 -5.55507958e-01 2.03953338e+00
5.47514319e-01 7.37384677e-01 3.19658279e-01 2.96769023e-01
6.50831759e-01 3.61872792e-01 -9.03931633e-02 -4.59138304e-01
-9.09714475e-02 5.19901216e-01 8.24683070e-01 4.87824529e-01
-1.41653967e+00 1.47712469e+00 6.54314899e+00 9.70615029e-01
-1.32883108e+00 5.12912646e-02 4.16320056e-01 5.50565422e-01
2.06859007e-01 -1.33609533e-01 -1.02903903e+00 3.59395635e-03
6.75485313e-01 2.89256454e-01 1.90409914e-01 7.50425756e-01
-4.63997602e-01 -2.00269997e-01 -6.86799884e-01 7.11081564e-01
-5.41760176e-02 -1.54946136e+00 -2.18928903e-01 -2.29340345e-01
7.81247437e-01 3.61373484e-01 -1.85800076e-01 3.78183305e-01
2.13057905e-01 -9.68521416e-01 9.76904750e-01 3.88002932e-01
8.20689619e-01 -7.67015457e-01 7.71795988e-01 8.72168541e-02
-1.91201282e+00 8.20589289e-02 -4.65917349e-01 5.35290055e-02
2.25351676e-01 6.33012593e-01 -5.45012891e-01 8.56195152e-01
8.23328316e-01 5.94716728e-01 -1.00381136e+00 1.36679935e+00
-2.92877465e-01 3.52254659e-01 -3.92316312e-01 8.94925073e-02
4.38904643e-01 -3.28285620e-02 3.57946396e-01 1.77018774e+00
5.63953212e-03 -1.93008274e-01 2.46688455e-01 7.51554668e-01
-1.14656337e-01 1.71722919e-01 -1.23748422e-01 5.35330832e-01
-2.82130148e-02 1.79982781e+00 -1.28921795e+00 -4.78256643e-01
-2.20431030e-01 7.97764242e-01 3.94724280e-01 5.71571589e-02
-8.41265082e-01 -4.98955399e-01 4.18310106e-01 -1.09183043e-01
6.61943734e-01 -2.59566426e-01 -3.05991441e-01 -8.28743339e-01
-1.86876103e-01 -4.63400245e-01 4.26423609e-01 -5.05854249e-01
-8.61042500e-01 1.03847647e+00 -1.30872214e-02 -1.05793154e+00
3.20828031e-03 -9.14874911e-01 -6.07590795e-01 7.78136611e-01
-1.84372413e+00 -1.38658118e+00 -5.44019341e-01 3.30758542e-01
5.85801721e-01 1.53127238e-01 8.07049513e-01 4.04487520e-01
-3.59075606e-01 4.80573535e-01 -5.36863029e-01 4.23084527e-01
1.67998910e-01 -1.54082322e+00 8.88231039e-01 1.06672609e+00
1.46044433e-01 7.64868110e-02 5.46572089e-01 -6.16702855e-01
-8.12947094e-01 -1.13514721e+00 5.75399637e-01 -1.92477047e-01
6.49406254e-01 -3.84309441e-01 -1.03919077e+00 3.67541611e-01
1.69479519e-01 4.87207472e-01 -2.41942078e-01 -2.02729460e-02
-3.35111350e-01 -3.27282883e-02 -1.13760960e+00 6.01402581e-01
1.23693454e+00 -2.64915615e-01 -4.81713504e-01 4.42325138e-02
7.46778369e-01 -6.66784108e-01 -1.14520919e+00 7.78022051e-01
6.15621924e-01 -1.41628003e+00 1.13803279e+00 -3.13130021e-01
2.62847930e-01 -3.26031983e-01 2.39235342e-01 -1.22977936e+00
-5.69388628e-01 -4.66073811e-01 1.18385412e-01 9.48437154e-01
4.78643268e-01 -4.89418298e-01 1.09505427e+00 -8.27871412e-02
-4.12810832e-01 -9.00371313e-01 -1.03167784e+00 -6.92309916e-01
2.07319990e-01 -5.70650697e-01 3.60408545e-01 4.55691546e-01
-5.06579459e-01 2.77310610e-01 -1.19617492e-01 4.26063910e-02
6.88740313e-01 1.15377977e-01 6.14519298e-01 -1.68371069e+00
1.83053941e-01 -7.26234615e-01 -7.60291338e-01 -9.83236969e-01
7.40247872e-03 -7.60409296e-01 1.24094009e-01 -1.61191905e+00
-1.13978740e-02 -3.48832190e-01 -4.65008855e-01 3.76179814e-01
-2.84955114e-01 8.60972822e-01 5.65835714e-01 -1.72607899e-01
-5.70373416e-01 3.12851429e-01 1.39647746e+00 1.23350630e-02
-1.97466239e-01 -1.26017973e-01 -3.27117950e-01 9.92103815e-01
6.63488746e-01 -5.30323267e-01 2.94267982e-01 -8.07802007e-02
1.57884702e-01 -1.66380242e-01 5.01711309e-01 -1.57471907e+00
2.62865335e-01 2.60913223e-01 4.43496823e-01 -9.71584022e-01
4.91666704e-01 -8.37633848e-01 -1.65695399e-01 8.15194130e-01
-2.84532569e-02 -3.12636420e-02 5.63036680e-01 1.54655606e-01
-1.62847474e-01 -2.93348581e-01 1.06494045e+00 3.71992216e-02
-1.19903350e+00 3.71683657e-01 -8.94123912e-02 7.71686360e-02
8.76256466e-01 -4.89707947e-01 -3.58257353e-01 1.12973556e-01
-8.24215770e-01 5.96407626e-04 5.36779642e-01 5.21614850e-01
5.87076426e-01 -1.11147583e+00 -9.54350829e-01 2.45033219e-01
1.94171041e-01 3.29078399e-02 9.54499096e-02 6.67225718e-01
-8.59181821e-01 2.74891496e-01 -6.74907744e-01 -9.15154815e-01
-1.11902916e+00 3.63423705e-01 6.03320718e-01 -4.51934725e-01
-9.22987342e-01 9.78720844e-01 6.60576746e-02 -4.26882766e-02
8.65899622e-02 -6.91424787e-01 -6.81629777e-01 2.46321172e-01
2.70383984e-01 5.13248026e-01 5.13696313e-01 -6.57738507e-01
-4.73349512e-01 1.14146364e+00 1.10631123e-01 2.37289630e-02
1.14588964e+00 4.10854816e-01 -3.29077244e-02 8.74947291e-03
1.17584264e+00 5.95273115e-02 -1.62248194e+00 1.25288427e-01
2.44646057e-01 -2.67860115e-01 4.49567974e-01 -6.37478828e-01
-1.40187085e+00 6.87026918e-01 1.02179253e+00 2.89112359e-01
9.77703512e-01 -2.49195904e-01 4.94962007e-01 1.25400409e-01
3.75698745e-01 -1.14576149e+00 2.96560913e-01 8.11828852e-01
8.43847692e-01 -1.14867783e+00 1.04357019e-01 -7.14126527e-01
-4.40472305e-01 1.28887463e+00 4.27683145e-01 -6.32677972e-01
7.22481549e-01 4.69127744e-01 6.53175190e-02 -3.33186179e-01
-2.75547326e-01 -8.78054321e-01 6.23707712e-01 5.96869886e-01
4.92851377e-01 4.34965603e-02 -3.53409648e-01 -1.21297166e-02
-2.33363315e-01 1.04509749e-01 5.47931671e-01 7.34431803e-01
-6.20313406e-01 -9.17995036e-01 -3.04457009e-01 3.06323230e-01
-6.80171967e-01 -2.54649878e-01 -1.72794849e-01 1.10187340e+00
2.88380444e-01 7.94643760e-01 1.47421062e-01 -3.28859985e-01
7.11603463e-01 -1.44130275e-01 4.29889172e-01 -6.13555789e-01
-1.03927338e+00 -7.47471899e-02 1.30102381e-01 -7.81854212e-01
-3.33680689e-01 -4.07307595e-01 -1.31878948e+00 -2.08933037e-02
-5.43471336e-01 -1.29385188e-01 7.57279038e-01 6.40610099e-01
1.89040869e-01 1.05766320e+00 1.63816556e-01 -1.25708759e+00
-2.55273789e-01 -8.94660234e-01 -3.99377167e-01 4.85393584e-01
3.97525132e-01 -6.80326402e-01 -1.89677954e-01 -2.23962083e-01] | [9.461695671081543, 0.1936718225479126] |
fdc8b43a-25d3-4910-a9db-515530c891d9 | a-clustering-framework-for-lexical | 2004.00088 | null | https://arxiv.org/abs/2004.00088v1 | https://arxiv.org/pdf/2004.00088v1.pdf | A Clustering Framework for Lexical Normalization of Roman Urdu | Roman Urdu is an informal form of the Urdu language written in Roman script, which is widely used in South Asia for online textual content. It lacks standard spelling and hence poses several normalization challenges during automatic language processing. In this article, we present a feature-based clustering framework for the lexical normalization of Roman Urdu corpora, which includes a phonetic algorithm UrduPhone, a string matching component, a feature-based similarity function, and a clustering algorithm Lex-Var. UrduPhone encodes Roman Urdu strings to their pronunciation-based representations. The string matching component handles character-level variations that occur when writing Urdu using Roman script. | ['Jia Xu', 'Hassan Sajjad', 'Faisal Kamiran', 'Asim Karim', 'Abdul Rafae Khan'] | 2020-03-31 | null | null | null | null | ['lexical-normalization'] | ['natural-language-processing'] | [ 3.06425303e-01 -7.34753847e-01 -2.27052048e-01 -4.16485250e-01
-9.70167398e-01 -1.19378507e+00 5.64551234e-01 1.08435929e-01
-3.59550059e-01 5.98717153e-01 4.96517211e-01 -3.17771643e-01
4.16167974e-01 -9.67460811e-01 -1.36739492e-01 -5.13817370e-01
7.02113032e-01 5.33990741e-01 -1.80534050e-01 -2.06932157e-01
4.78999168e-01 8.39521945e-01 -1.23244750e+00 2.11126089e-01
8.49982858e-01 4.95708317e-01 1.98025376e-01 7.19262242e-01
-4.34481472e-01 6.84284747e-01 -9.36733842e-01 -6.14430606e-01
5.24302483e-01 -8.26441646e-01 -5.44212043e-01 -3.03871602e-01
2.82796562e-01 -3.38457137e-01 -4.77870345e-01 1.29708540e+00
7.12620437e-01 4.17903155e-01 1.12473524e+00 -4.41591561e-01
-1.08809185e+00 1.04968393e+00 -2.54031360e-01 2.45193258e-01
5.21522164e-01 -6.16355240e-01 9.89898205e-01 -8.60907733e-01
9.27712798e-01 1.34068608e+00 6.00005209e-01 7.10581601e-01
-1.00106406e+00 -4.69907045e-01 -7.29787648e-01 8.63643959e-02
-1.63460803e+00 -2.10103244e-01 4.56318498e-01 -5.38660586e-01
1.22335315e+00 4.39303547e-01 1.07545689e-01 7.71037459e-01
1.32226840e-01 4.72058892e-01 6.59774065e-01 -7.22614765e-01
1.61708772e-01 -1.12730265e-01 3.20924848e-01 -1.91094354e-01
2.34502718e-01 -3.07137996e-01 8.01993161e-02 -1.74886584e-01
9.03083503e-01 -1.22666717e-01 2.35809863e-01 3.76840144e-01
-7.21291423e-01 1.03176510e+00 -5.41776657e-01 5.89532793e-01
-1.04843207e-01 -1.87386692e-01 8.93771350e-01 3.18740249e-01
7.03452677e-02 1.87122151e-01 -2.44372502e-01 -8.21131289e-01
-8.12257469e-01 -1.30217979e-02 5.70980072e-01 1.31965947e+00
5.40538669e-01 2.57658154e-01 -2.70565391e-01 1.65149629e+00
5.48125021e-02 5.90164304e-01 8.85702372e-01 -9.30648863e-01
3.18029374e-01 1.79908931e-01 -3.33260626e-01 -3.80358279e-01
2.49200210e-01 4.76392627e-01 -6.17380977e-01 -2.54246056e-01
2.86933839e-01 -2.01431498e-01 -7.03830838e-01 1.47954535e+00
1.31769866e-01 -2.96342403e-01 2.31503516e-01 2.95821905e-01
7.49211609e-01 9.26483691e-01 -1.91586286e-01 -5.34051239e-01
1.37293315e+00 -7.91205823e-01 -1.13560736e+00 3.72682422e-01
3.32551807e-01 -1.49647856e+00 1.21877098e+00 3.55159581e-01
-1.09228396e+00 -5.28828263e-01 -1.15009463e+00 -6.44642591e-01
-5.15779972e-01 1.75609365e-01 2.41413772e-01 1.48739195e+00
-7.02399015e-01 7.43672729e-01 -4.87910062e-01 -4.22501326e-01
-1.87547863e-01 -1.43269226e-02 -2.52325326e-01 6.13935664e-02
-1.16929519e+00 9.27421033e-01 7.25751996e-01 -4.09118205e-01
-8.20640102e-02 -2.72650242e-01 -1.14255440e+00 -2.11905733e-01
-4.48878318e-01 2.50710666e-01 1.34404933e+00 -6.72385693e-01
-2.05841160e+00 1.00831890e+00 -3.10629994e-01 -1.73570797e-01
4.64282185e-01 1.08144917e-01 -7.22718835e-01 -1.37814268e-01
-2.33405549e-02 -1.08407743e-01 7.23685682e-01 -8.16040397e-01
-7.65402138e-01 -1.99285552e-01 -8.54618907e-01 3.31707835e-01
-1.79063469e-01 8.74899030e-01 -7.45565057e-01 -1.35912585e+00
5.78608066e-02 -4.50859934e-01 2.10578069e-01 -1.19764411e+00
2.57597893e-01 -5.47580719e-01 6.67722762e-01 -1.42163301e+00
1.98743308e+00 -2.08408833e+00 -2.00539425e-01 7.24554777e-01
-4.40577626e-01 1.59081265e-01 9.18266326e-02 6.00788116e-01
-1.50243327e-01 1.37718379e-01 -1.80844441e-01 -2.30133504e-01
1.60771817e-01 6.73373342e-01 -2.49272332e-01 3.90963286e-01
-7.34288841e-02 7.47953653e-01 -9.79385912e-01 -3.03317994e-01
2.83589333e-01 3.57720733e-01 -3.45362395e-01 2.03778833e-01
2.73750931e-01 -4.25109081e-02 4.20012176e-01 8.57387066e-01
9.89355922e-01 9.35115457e-01 4.76401091e-01 1.74527198e-01
-4.95540321e-01 6.68729901e-01 -1.08375764e+00 1.31193733e+00
-4.17710543e-01 3.94850731e-01 -4.08237875e-01 -4.55543756e-01
1.32523823e+00 1.44098967e-01 2.95835584e-01 -5.65531194e-01
7.89034963e-01 6.14472210e-01 4.19527180e-02 -9.46676359e-02
1.22442651e+00 6.10693395e-02 -4.86373723e-01 5.60079455e-01
2.84965754e-01 -5.98113477e-01 8.84907365e-01 -8.85818619e-03
7.88295805e-01 1.37011781e-01 9.08596039e-01 -2.23890826e-01
7.23146796e-01 -3.90805423e-01 7.61625469e-01 6.42919183e-01
8.41883793e-02 1.31855941e+00 5.09346902e-01 1.95360050e-01
-1.50927937e+00 -1.20654118e+00 -7.00677931e-01 9.48308885e-01
-4.32299793e-01 -5.72774589e-01 -1.16481531e+00 -3.96087706e-01
-1.34617805e-01 1.20315433e+00 -5.89822710e-01 8.55734199e-02
-9.91814196e-01 -5.20175278e-01 1.16678512e+00 4.88192588e-01
-2.20534857e-02 -1.12440550e+00 2.88292050e-01 3.67098719e-01
-6.21196479e-02 -1.04505205e+00 -1.28075159e+00 2.60083407e-01
-5.17612040e-01 -8.22738290e-01 -9.13852990e-01 -1.05038023e+00
3.92846525e-01 -7.56183341e-02 7.51051247e-01 -4.99471754e-01
-3.64424028e-02 9.40190926e-02 -7.16473162e-01 -3.17236274e-01
-1.24120891e+00 1.37137234e-01 2.61945635e-01 -2.30653614e-01
1.05612695e+00 -3.12556416e-01 3.58326524e-01 1.51325598e-01
-1.01774859e+00 -6.70132339e-01 1.06462367e-01 6.02335989e-01
8.98528099e-01 -2.05322161e-01 2.99945533e-01 -1.04221559e+00
7.86092699e-01 -4.92651254e-01 -6.33587182e-01 2.68786401e-01
-2.96435148e-01 -3.21362406e-01 9.36302245e-01 -4.64827150e-01
-1.10246825e+00 -1.69094011e-01 -8.98067534e-01 -1.80762395e-01
-6.89504221e-02 2.77929157e-01 -7.67271936e-01 9.26968902e-02
7.07195699e-01 4.34153438e-01 -1.90577582e-01 -8.59210014e-01
1.98947623e-01 1.55562067e+00 1.06998289e+00 -6.62117541e-01
6.02241337e-01 -3.87260132e-02 -7.27799356e-01 -1.20513487e+00
-8.31325576e-02 -7.15816855e-01 -9.32067931e-01 1.11924537e-01
8.37508261e-01 -6.43258989e-01 -1.71337187e-01 7.25276828e-01
-1.28473783e+00 -3.28963958e-02 -6.03479981e-01 3.35518003e-01
-6.46427155e-01 9.16071773e-01 -9.51034307e-01 -6.28510416e-01
-5.62865853e-01 -7.69742548e-01 5.32384932e-01 5.39155424e-01
-4.62607831e-01 -8.75149727e-01 4.87447560e-01 7.26679480e-03
1.01960190e-01 1.02977790e-01 1.10347652e+00 -9.94691610e-01
5.53336501e-01 -2.17337325e-01 -2.09666729e-01 1.03227830e+00
7.15429783e-01 4.34830815e-01 -7.13155925e-01 1.10077607e-02
-1.50593534e-01 3.70958000e-01 2.21884459e-01 -3.79453748e-02
9.10373211e-01 -1.71809524e-01 5.56619108e-01 8.18457603e-01
1.21337557e+00 9.56391633e-01 9.09178078e-01 2.55888700e-01
6.48299634e-01 2.69210394e-02 5.43817818e-01 5.60079038e-01
2.84056783e-01 6.55608654e-01 -3.77118826e-01 4.21106339e-01
-3.64523441e-01 -3.46279591e-01 7.39389360e-01 1.63550019e+00
-1.66952938e-01 3.80634740e-02 -8.34822595e-01 6.13801956e-01
-1.53150368e+00 -1.11701691e+00 -1.37553573e-01 2.45820808e+00
1.34136915e+00 -1.66632414e-01 1.54138327e-01 3.70161593e-01
9.67024624e-01 -3.07961464e-01 -2.70215511e-01 -1.49527872e+00
-7.55771339e-01 5.64005673e-01 6.75079465e-01 5.20758033e-01
-8.28839302e-01 1.40915275e+00 6.55920792e+00 1.37767458e+00
-8.91607881e-01 2.12721258e-01 2.26671353e-01 4.48997438e-01
-5.28978467e-01 -2.66673893e-01 -9.57257211e-01 5.86696506e-01
7.67641962e-01 -3.62815529e-01 7.64067829e-01 8.37639809e-01
2.75416672e-01 1.09602280e-01 -1.03315842e+00 1.33909321e+00
4.93149817e-01 -1.16863716e+00 4.09838974e-01 -1.30617961e-01
1.10023379e+00 -1.23204125e-04 -4.12530214e-01 1.67127982e-01
4.24383938e-01 -9.09264863e-01 1.07666647e+00 5.79289496e-02
1.36543894e+00 -1.17673659e+00 8.63278866e-01 -2.03562498e-01
-1.13301921e+00 4.35910165e-01 -8.04041088e-01 4.70694825e-02
1.86717898e-01 1.90564897e-02 -7.35562205e-01 5.55550933e-01
6.42727852e-01 7.08027661e-01 -3.26603353e-01 9.07747686e-01
-3.69819760e-01 8.36696684e-01 -3.18946391e-01 1.39842564e-02
9.19697061e-02 -9.68583822e-01 5.05212188e-01 1.94069326e+00
6.60413623e-01 4.60016057e-02 -3.79068196e-01 1.92455620e-01
-1.31256089e-01 8.81403148e-01 -4.03840959e-01 -3.46457541e-01
7.95175254e-01 9.90388989e-01 -8.79070103e-01 -4.40068662e-01
-3.62605989e-01 1.35297394e+00 3.31906192e-02 9.59995538e-02
-6.09219611e-01 -1.06241131e+00 1.15972042e+00 -2.33708337e-01
2.94003516e-01 -4.73038673e-01 -8.43683898e-01 -1.28537238e+00
-3.22722197e-01 -9.68973339e-01 5.79981446e-01 -3.81054431e-01
-1.41670501e+00 5.59209526e-01 -1.55733004e-01 -1.21689272e+00
-5.19646645e-01 -8.19694698e-01 -5.48943162e-01 9.89457667e-01
-9.58833277e-01 -8.34448814e-01 1.86603099e-01 6.70709312e-01
6.61902189e-01 -5.89290619e-01 1.07836890e+00 6.19765341e-01
-4.85585690e-01 1.00593078e+00 1.02149045e+00 6.54911935e-01
8.67576540e-01 -1.40476394e+00 7.36213088e-01 1.16918755e+00
2.83135511e-02 8.77427816e-01 5.42455971e-01 -9.43010271e-01
-9.86062825e-01 -9.01787519e-01 1.55076849e+00 -3.29334259e-01
6.79791272e-01 -6.06602848e-01 -7.25414574e-01 6.75562322e-01
3.80430371e-01 -7.24036753e-01 1.14349258e+00 -5.55147469e-01
-4.32066053e-01 1.96298823e-01 -1.38083339e+00 9.01163816e-01
9.70654309e-01 -5.43524563e-01 -1.10646534e+00 -4.04566191e-02
3.43285561e-01 -4.24745768e-01 -1.13079584e+00 -2.30650261e-01
5.74864566e-01 -3.55443686e-01 6.81973815e-01 -3.12485754e-01
-1.69599941e-03 -4.40184742e-01 -5.50163150e-01 -1.13416338e+00
-4.22826618e-01 -1.07339001e+00 1.42878264e-01 1.94323003e+00
2.17788801e-01 -5.52499533e-01 2.19636843e-01 1.87513024e-01
-2.14910105e-01 3.48796308e-01 -1.08755040e+00 -9.44738567e-01
5.17589629e-01 -6.30554378e-01 7.38961816e-01 1.11952734e+00
2.13219300e-01 3.00742500e-02 -3.74388486e-01 -3.30933392e-01
2.55636096e-01 -3.07419658e-01 3.70288432e-01 -8.54006827e-01
-3.03527545e-02 -7.41432726e-01 -3.56740773e-01 -7.58575499e-01
1.63408071e-01 -1.01004517e+00 -1.20481253e-01 -1.22811341e+00
-1.57911509e-01 -3.02478641e-01 1.10404521e-01 3.55068445e-01
-6.70463266e-03 5.30986667e-01 3.86945575e-01 1.12620644e-01
8.22798535e-02 3.11790437e-01 4.86414373e-01 1.66336820e-01
-4.39704955e-01 1.64596289e-01 -1.82164803e-01 7.11059213e-01
1.09067214e+00 -5.61967134e-01 1.65592566e-01 -2.73575902e-01
1.30460337e-01 -4.13929939e-01 -9.53509986e-01 -4.35839802e-01
-1.78589091e-01 -3.24121118e-01 2.77710468e-01 -8.00512612e-01
-1.76356584e-01 -6.58806443e-01 1.69478774e-01 2.15311438e-01
2.14454412e-01 5.99575341e-01 4.67783809e-02 -4.93315011e-01
-3.36626381e-01 -9.34259593e-01 1.14178503e+00 1.04038209e-01
-6.01780057e-01 -6.03409447e-02 -1.29196143e+00 1.03593081e-01
9.06885147e-01 -7.43127406e-01 1.25472903e-01 -1.34982198e-01
-8.61422196e-02 -2.96721131e-01 7.33323455e-01 8.08423102e-01
3.50377262e-01 -1.65366125e+00 -9.91633654e-01 5.08755445e-01
-6.06173761e-02 -5.75184584e-01 -1.53203502e-01 2.57457256e-01
-1.32450664e+00 8.40176865e-02 -4.98874128e-01 1.20632894e-01
-1.53060257e+00 2.14545056e-01 7.01436996e-02 1.51446452e-02
-1.30778968e-01 5.67437649e-01 -4.33048546e-01 -9.01874304e-01
1.43879399e-01 -9.50364694e-02 -6.17374659e-01 6.74229026e-01
8.14162731e-01 8.98192704e-01 5.44133604e-01 -1.19331861e+00
-2.76153833e-01 6.08302176e-01 4.21797633e-02 -3.95755708e-01
8.48293722e-01 -4.39377129e-01 -5.70479691e-01 5.53355336e-01
1.25675893e+00 9.16032434e-01 -5.70826411e-01 -1.02028601e-01
2.79686451e-01 -5.40649295e-01 -5.27576208e-01 -4.41325366e-01
-4.48877245e-01 5.60386658e-01 1.38113037e-01 -6.33861646e-02
8.85073960e-01 -3.94843310e-01 1.04094946e+00 2.33124003e-01
1.07094355e-01 -1.94779646e+00 -7.71600366e-01 1.68984008e+00
6.81916416e-01 -6.88756108e-01 -4.08513606e-01 -2.33544201e-01
-6.76952362e-01 1.55200648e+00 1.91216737e-01 -1.77265882e-01
4.90325481e-01 6.32852793e-01 5.44082224e-01 8.98057401e-01
9.11932066e-02 -2.38283738e-01 2.86537290e-01 8.90672684e-01
6.93891287e-01 4.62755710e-02 -1.30638385e+00 1.03920472e+00
-9.50785100e-01 -5.99636078e-01 6.64851367e-01 6.05956495e-01
-3.06104928e-01 -1.79561877e+00 -7.52782047e-01 2.41011098e-01
-9.30779338e-01 -5.98663032e-01 -4.73395288e-01 4.46805567e-01
2.95740068e-01 6.59913361e-01 4.54424739e-01 -3.22190166e-01
3.43414128e-01 1.80051401e-01 4.69604433e-01 -7.79157758e-01
-1.14487278e+00 5.05494297e-01 8.07871893e-02 -7.45399743e-02
2.13352367e-01 -1.38650036e+00 -1.48213959e+00 -5.59892416e-01
1.66736573e-01 2.65728921e-01 7.08011568e-01 6.18502438e-01
-2.76459306e-01 -7.23813707e-03 7.50661373e-01 -6.72459424e-01
-4.88830805e-01 -1.04299605e+00 -7.46121347e-01 3.22621018e-01
-3.11495453e-01 9.87502635e-02 -5.47912903e-02 1.14015460e-01] | [10.757638931274414, 10.524426460266113] |
b3024531-2abd-48cb-aec3-e4702a8adb4e | investigating-sampling-bias-in-abusive | null | null | https://aclanthology.org/2020.alw-1.9 | https://aclanthology.org/2020.alw-1.9.pdf | Investigating Sampling Bias in Abusive Language Detection | Abusive language detection is becoming increasingly important, but we still understand little about the biases in our datasets for abusive language detection, and how these biases affect the quality of abusive language detection. In the work reported here, we reproduce the investigation of Wiegand et al. (2019) to determine differences between different sampling strategies. They compared boosted random sampling, where abusive posts are upsampled, and biased topic sampling, which focuses on topics that are known to cause abusive language. Instead of comparing individual datasets created using these sampling strategies, we use the sampling strategies on a single, large dataset, thus eliminating the textual source of the dataset as a potential confounding factor. We show that differences in the textual source can have more effect than the chosen sampling strategy. | ['Sandra Kübler', 'Dante Razo'] | null | null | null | null | emnlp-alw-2020-11 | ['abusive-language'] | ['natural-language-processing'] | [ 8.08107257e-02 -1.36950463e-01 -6.37169123e-01 -1.15246356e-01
-7.06536353e-01 -7.71962225e-01 9.85300601e-01 4.07206804e-01
-8.11513007e-01 9.28090632e-01 8.25090826e-01 -6.06528878e-01
2.34727487e-01 -6.85669422e-01 -2.68395156e-01 -3.43056053e-01
3.76323014e-01 2.62869805e-01 1.49818853e-01 -6.78506792e-02
6.39512956e-01 4.78367776e-01 -9.60132122e-01 9.42341983e-02
7.04518318e-01 2.09962904e-01 -2.44231075e-01 5.44514954e-01
-3.78261864e-01 1.21383345e+00 -1.24413347e+00 -4.68803465e-01
-1.36483004e-02 -5.99726379e-01 -8.91902685e-01 3.61445509e-02
5.05764961e-01 -5.00397325e-01 -1.82359874e-01 1.01556790e+00
4.79800612e-01 -5.86279994e-03 7.91167915e-01 -8.46086025e-01
-4.45613116e-01 9.45696950e-01 -9.47761297e-01 7.95723379e-01
5.52025080e-01 9.76523310e-02 8.11038613e-01 -5.57052970e-01
9.56864059e-01 1.66561198e+00 4.31067258e-01 4.54688102e-01
-1.40959454e+00 -1.23393786e+00 1.85789242e-01 -1.30774930e-01
-1.36015868e+00 -7.44958580e-01 8.76849294e-01 -8.87067139e-01
4.59908783e-01 1.78259075e-01 6.10666156e-01 1.85294807e+00
1.11429073e-01 4.16737735e-01 1.48860157e+00 -3.27931583e-01
1.14471927e-01 6.50321364e-01 5.82223594e-01 1.19524591e-01
9.02227819e-01 -1.97059706e-01 -5.62907159e-01 -9.43513691e-01
1.70683667e-01 -1.32561654e-01 -2.70935982e-01 1.24585852e-01
-7.53001273e-01 1.52352834e+00 9.82680842e-02 6.50471926e-01
-2.10834220e-01 -1.34896860e-01 5.61267376e-01 1.16417035e-01
7.70226896e-01 8.80952537e-01 -3.84085625e-02 -3.26384068e-01
-1.03062093e+00 4.29985464e-01 8.93710136e-01 4.59922731e-01
4.81636614e-01 -8.03485140e-02 -2.99415290e-01 9.60867941e-01
1.20951056e-01 5.74972570e-01 7.45420039e-01 -6.79189026e-01
3.96951973e-01 3.70799273e-01 3.88278037e-01 -1.17345047e+00
-1.66602567e-01 -5.06763086e-02 -7.23159462e-02 -3.70960161e-02
6.43940985e-01 -5.41762948e-01 -5.65075755e-01 1.75094640e+00
1.99667960e-01 -6.41038120e-01 -4.76078629e-01 7.14607954e-01
5.98940492e-01 5.59021413e-01 4.85206217e-01 -5.80140769e-01
1.40159583e+00 -3.42579186e-01 -8.85701597e-01 -5.17468929e-01
7.77074933e-01 -1.13671780e+00 1.32698131e+00 4.49025422e-01
-8.53644609e-01 1.58761784e-01 -1.01592016e+00 -1.63773164e-01
-3.84480447e-01 -7.11929798e-01 4.28775191e-01 9.64638352e-01
-6.47131085e-01 2.43491024e-01 -2.21583411e-01 -7.34612703e-01
3.11013430e-01 -3.40393066e-01 -4.65714093e-03 2.15779617e-01
-1.35758805e+00 1.05529916e+00 -1.59643218e-01 -8.08351994e-01
-8.69708538e-01 -7.04617977e-01 -4.85609710e-01 -4.47937161e-01
6.31856740e-01 -1.68060094e-01 1.34406173e+00 -1.11248136e+00
-1.03321135e+00 1.19935536e+00 -5.33559740e-01 -3.63797158e-01
6.83430016e-01 -3.28836948e-01 -2.27402478e-01 2.84043010e-02
4.55837846e-01 1.76133424e-01 9.09656346e-01 -1.10882354e+00
-2.52631426e-01 -4.89202857e-01 -1.89784214e-01 -4.93878173e-03
-3.93071771e-01 8.45237315e-01 3.69116485e-01 -7.18133211e-01
-3.26686591e-01 -7.21609235e-01 2.36110762e-02 -4.14876014e-01
-4.49045777e-01 -4.25367542e-02 7.72302985e-01 -7.21420765e-01
1.37926650e+00 -2.14274812e+00 -8.78290311e-02 1.95338111e-03
4.86704111e-01 1.07666925e-02 4.14212644e-01 5.38089454e-01
1.27952605e-01 8.34518731e-01 -2.28850488e-02 -4.01735932e-01
-1.82460546e-01 -5.17369211e-02 -5.97538590e-01 8.04625034e-01
-5.73248602e-02 3.24086159e-01 -8.97196054e-01 -6.66238606e-01
-1.88193128e-01 3.68273765e-01 -3.48473638e-01 2.34360993e-02
2.56670862e-01 2.24961713e-01 -2.83224612e-01 4.56570745e-01
4.84418482e-01 2.06940487e-01 6.81206062e-02 4.38102484e-01
-3.13074201e-01 9.39346194e-01 -6.06519043e-01 6.89739108e-01
-5.31421840e-01 1.12383127e+00 3.02395314e-01 -3.24747086e-01
8.65680158e-01 1.65274411e-01 -7.86317289e-02 -3.32979202e-01
2.61232853e-01 2.33350858e-01 2.45079949e-01 -1.37039587e-01
7.35522389e-01 -6.52024925e-01 -1.45917252e-01 8.60507131e-01
-5.89533925e-01 -3.57228607e-01 1.21800691e-01 5.64280689e-01
9.68627810e-01 -7.39718139e-01 7.95198023e-01 -5.69537699e-01
4.60629985e-02 2.40248770e-01 4.20778722e-01 1.12525666e+00
-5.57111800e-01 4.54383224e-01 9.97353137e-01 -1.23808786e-01
-9.48260903e-01 -8.41077983e-01 -5.30425072e-01 1.12251365e+00
-1.79951891e-01 -3.34686339e-01 -5.28561532e-01 -7.38884091e-01
7.58536980e-02 1.20889831e+00 -8.60209405e-01 -3.10633868e-01
-3.03428501e-01 -8.95168006e-01 7.69569457e-01 -1.49402812e-01
-2.35827826e-02 -8.85556579e-01 -8.54779899e-01 -9.72509012e-02
-3.47942710e-01 -8.96938026e-01 -4.77915168e-01 -5.49376849e-03
-7.29482532e-01 -9.82147038e-01 -5.49140573e-01 6.25028163e-02
3.04880440e-01 3.74941379e-01 1.25124621e+00 2.58119553e-01
-1.42970324e-01 1.64766923e-01 -4.66178805e-01 -9.33659315e-01
-1.01200724e+00 3.64082158e-01 1.64738689e-02 -2.25830317e-01
8.58670592e-01 -3.40925723e-01 -2.01453090e-01 -2.19733790e-01
-7.62894809e-01 -4.70908821e-01 1.58723742e-01 4.09205109e-01
-2.81730056e-01 -4.34466660e-01 5.69190860e-01 -1.44153214e+00
1.02119470e+00 -9.72121358e-01 -2.55524248e-01 -4.54537541e-01
-5.60419798e-01 -4.60462451e-01 2.08829358e-01 -8.56794417e-01
-8.22051883e-01 -6.80380344e-01 3.88700962e-02 -1.78692844e-02
-3.51826429e-01 1.69945270e-01 1.89513415e-01 1.68026209e-01
8.87291312e-01 -2.84612775e-01 3.13100740e-02 -5.10105014e-01
-2.36745432e-01 1.02056766e+00 -4.32224572e-01 -3.47611874e-01
5.30985057e-01 6.37862802e-01 -6.61896467e-01 -1.15968549e+00
-1.02819419e+00 -4.78305310e-01 -3.73473257e-01 -5.16191162e-02
7.58656383e-01 -8.54284346e-01 -6.95673600e-02 2.32554317e-01
-1.14892697e+00 -4.29293543e-01 -1.04101077e-01 4.85076815e-01
-3.53843942e-02 1.49195030e-01 -7.82584250e-01 -1.21781766e+00
-2.67015666e-01 -1.12147462e+00 7.61153221e-01 -2.04490378e-01
-1.21399045e+00 -9.39994931e-01 2.98992932e-01 3.33602101e-01
4.79197145e-01 3.12127382e-01 8.40799749e-01 -1.11082661e+00
1.34612620e-01 -2.80539453e-01 -1.50463030e-01 -1.92756262e-02
3.11500877e-01 4.47878867e-01 -1.10897982e+00 -2.55940765e-01
4.83608425e-01 -4.42303270e-01 6.89705729e-01 3.82233113e-01
5.47258675e-01 -6.30560338e-01 -4.74729151e-01 -5.74326366e-02
1.16588759e+00 2.98985422e-01 4.45930302e-01 5.43153763e-01
5.58448434e-01 8.03109348e-01 2.60931671e-01 5.39541304e-01
7.19607770e-02 5.25038540e-01 -1.48274913e-01 1.32919788e-01
1.03100635e-01 -3.86439115e-01 6.95787609e-01 3.33734751e-01
6.60116553e-01 -1.20721459e-01 -1.01884639e+00 8.97698343e-01
-1.04657996e+00 -1.14767110e+00 -2.56714046e-01 2.19650078e+00
1.08545744e+00 4.32126224e-01 7.84208059e-01 2.19686493e-01
7.79503465e-01 5.61766744e-01 -7.09715933e-02 -8.65850687e-01
-1.11083940e-01 -1.04096323e-01 5.12663901e-01 1.19765592e+00
-6.78156614e-01 7.29485273e-01 7.63001871e+00 5.07351875e-01
-1.27966774e+00 2.75375217e-01 7.90450692e-01 -6.33434057e-01
-3.72743756e-01 -6.75936639e-02 -8.48477364e-01 6.61980808e-01
1.14111698e+00 -3.40365559e-01 1.79415587e-02 7.38631546e-01
6.47678137e-01 -5.04805565e-01 -8.14012349e-01 2.70283669e-01
3.59066457e-01 -6.13553524e-01 1.20645657e-01 4.75075871e-01
3.31839621e-01 -7.63874277e-02 -3.34890839e-03 2.72838026e-01
5.94884992e-01 -1.04948032e+00 1.02370405e+00 -7.60359019e-02
2.85226285e-01 -5.28766572e-01 7.37366617e-01 4.08200145e-01
-9.69037414e-02 -4.55641784e-02 -2.18869671e-01 -6.82603955e-01
1.94470763e-01 1.09937143e+00 -8.55189860e-01 -4.06079948e-01
7.51825690e-01 2.89125562e-01 -7.26767600e-01 2.69236356e-01
-2.62150258e-01 1.39921403e+00 -2.78193444e-01 -4.34456199e-01
1.56139567e-01 -5.60806431e-02 9.82714772e-01 1.26787317e+00
-1.06994890e-01 -1.29530758e-01 -2.08512262e-01 9.03815031e-01
4.23943205e-03 3.37596089e-01 -1.15506935e+00 -2.86762834e-01
6.74273431e-01 1.13957405e+00 -8.14213037e-01 -4.99714017e-01
-5.00521719e-01 4.15476382e-01 4.97779608e-01 1.53327078e-01
-4.76322144e-01 -2.18434945e-01 8.42190623e-01 7.42977381e-01
-1.05386481e-01 -1.55068748e-02 -6.94816470e-01 -1.00177324e+00
-3.94729495e-01 -1.29446483e+00 5.09887040e-01 -4.54642475e-01
-1.24637926e+00 1.41562134e-01 4.66843992e-01 -3.47270787e-01
-2.02662900e-01 -1.94431588e-01 -4.02217180e-01 1.09917200e+00
-8.31258535e-01 -3.91016573e-01 1.22963707e-03 1.54346284e-02
4.99913186e-01 3.04606855e-01 3.29257399e-01 7.73631409e-02
-6.61023319e-01 4.05951113e-01 -3.04484665e-01 1.57792240e-01
1.04918408e+00 -9.46308613e-01 6.34687021e-02 7.81832397e-01
1.14530828e-02 1.07754302e+00 1.13177764e+00 -9.82572258e-01
-6.67125225e-01 -5.96855998e-01 1.21000528e+00 -9.23380435e-01
1.06293988e+00 -7.09873497e-01 -9.63720143e-01 8.57575715e-01
3.40744674e-01 -8.60165477e-01 8.36001873e-01 4.62553889e-01
-6.44318283e-01 3.37699801e-01 -1.32040966e+00 9.16972697e-01
1.03083920e+00 -4.42407906e-01 -7.60105133e-01 1.58219993e-01
7.90254772e-01 -3.13589461e-02 -5.33429444e-01 -1.47965312e-01
4.41434652e-01 -1.08020043e+00 4.93984193e-01 -6.56507850e-01
7.59624958e-01 3.69479448e-01 -8.26310962e-02 -1.26584899e+00
-3.83265167e-01 -4.20630127e-01 3.32666069e-01 1.46772695e+00
5.05638719e-01 -9.68846440e-01 3.17929000e-01 3.86379421e-01
4.51075345e-01 -4.02796626e-01 -7.87135720e-01 -4.29034621e-01
7.03263462e-01 -2.43427232e-01 5.46470165e-01 1.27374244e+00
1.38175815e-01 5.34559548e-01 -2.12463304e-01 -2.96520501e-01
3.19029540e-01 -6.38253838e-02 8.91434968e-01 -1.15229774e+00
-4.30895984e-02 -6.29243612e-01 8.53050593e-03 -4.27516013e-01
2.35304207e-01 -2.71274865e-01 -2.47357234e-01 -8.92155290e-01
5.97830594e-01 -5.91809265e-02 3.25128704e-01 6.57785591e-03
-4.69621003e-01 4.08051223e-01 3.25152069e-01 3.24099839e-01
-4.03438061e-02 1.03197806e-01 8.01707089e-01 -4.26770449e-02
-4.15003210e-01 -3.67596984e-01 -1.38492203e+00 8.75987887e-01
7.16188431e-01 -7.92882919e-01 -3.08408529e-01 -1.73603579e-01
2.31541693e-01 -3.89498681e-01 2.39548832e-01 -4.79943812e-01
-4.43431169e-01 -4.93348509e-01 2.30277181e-01 -1.67943522e-01
1.83825508e-01 -4.10122514e-01 -1.41759470e-01 5.90854585e-01
-6.86851501e-01 2.20242456e-01 2.84749746e-01 2.53509939e-01
3.85611244e-02 -7.00839162e-01 9.78081167e-01 -3.66888851e-01
1.73152477e-01 -2.70255238e-01 -1.22293782e+00 6.53699279e-01
9.13536668e-01 -1.37535810e-01 -3.77798229e-01 -8.64226699e-01
-2.01582208e-01 -4.36914176e-01 1.01257539e+00 3.18255752e-01
5.46788424e-03 -9.23308492e-01 -8.84552598e-01 -2.91394532e-01
6.10460900e-02 -5.16117156e-01 -2.68159539e-01 9.78928268e-01
-2.36475289e-01 2.07257256e-01 2.96838760e-01 -2.26212256e-02
-1.25899291e+00 6.85180962e-01 2.63158649e-01 -1.23276047e-01
-4.10376817e-01 5.15298128e-01 2.04882592e-01 5.77133708e-02
-6.74568415e-02 2.32582361e-01 -2.20180720e-01 6.12460911e-01
7.61470556e-01 5.94110668e-01 -2.23508656e-01 -9.52883661e-01
-5.11229098e-01 -5.20119742e-02 -5.45324206e-01 -6.20269060e-01
7.52932847e-01 -2.42917925e-01 -2.46086746e-01 1.31132042e+00
1.15351403e+00 9.05547500e-01 -2.84366339e-01 -6.72502294e-02
9.54301730e-02 -7.42988527e-01 1.55805156e-01 -4.58131790e-01
-4.89523262e-01 5.79365551e-01 -2.13768762e-02 7.55543470e-01
4.61831152e-01 1.37288719e-01 5.72159469e-01 -2.32694924e-01
2.68818468e-01 -8.12269509e-01 1.89454295e-02 3.02332312e-01
1.07746470e+00 -1.15273440e+00 5.79057872e-01 -5.14909148e-01
-6.72272503e-01 5.48325419e-01 5.13674915e-01 -2.20889211e-01
4.86378402e-01 1.99061334e-01 4.83001143e-01 -4.25772995e-01
-7.47347534e-01 2.00881764e-01 -1.64361805e-01 4.52418834e-01
9.30248141e-01 6.64774105e-02 -1.18762958e+00 4.54606920e-01
-6.90593183e-01 -3.10464978e-01 1.16066575e+00 8.74948919e-01
-2.40387991e-01 -7.05261350e-01 -9.59007025e-01 8.92742634e-01
-1.04144228e+00 -1.63129494e-01 -1.56592572e+00 1.16409922e+00
-1.84076995e-01 1.05459452e+00 3.45200032e-01 -1.64655209e-01
1.31647643e-02 4.13580567e-01 6.09875806e-02 -9.46701407e-01
-7.33373642e-01 -1.43111154e-01 6.72136962e-01 -1.72771111e-01
-2.28276446e-01 -1.11790562e+00 -5.13647795e-01 -8.10297847e-01
-3.37086856e-01 2.90667683e-01 2.80777693e-01 1.01823795e+00
1.45281851e-01 -7.47848824e-02 3.95195961e-01 -5.13248384e-01
-6.82470202e-01 -1.44318628e+00 -5.94660103e-01 6.60427392e-01
6.55294716e-01 -7.17175007e-01 -1.07317066e+00 -4.58262086e-01] | [8.68535327911377, 10.380178451538086] |
f65c325b-fb0f-4263-9913-ba9ff1732563 | diffmix-diffusion-model-based-data-synthesis | 2306.14132 | null | https://arxiv.org/abs/2306.14132v1 | https://arxiv.org/pdf/2306.14132v1.pdf | DiffMix: Diffusion Model-based Data Synthesis for Nuclei Segmentation and Classification in Imbalanced Pathology Image Datasets | Nuclei segmentation and classification is a significant process in pathology image analysis. Deep learning-based approaches have greatly contributed to the higher accuracy of this task. However, those approaches suffer from the imbalanced nuclei data composition, which shows lower classification performance on the rare nuclei class. In this paper, we propose a realistic data synthesis method using a diffusion model. We generate two types of virtual patches to enlarge the training data distribution, which is for balancing the nuclei class variance and for enlarging the chance to look at various nuclei. After that, we use a semantic-label-conditioned diffusion model to generate realistic and high-quality image samples. We demonstrate the efficacy of our method by experiment results on two imbalanced nuclei datasets, improving the state-of-the-art networks. The experimental results suggest that the proposed method improves the classification performance of the rare type nuclei classification, while showing superior segmentation and classification performance in imbalanced pathology nuclei datasets. | ['Won-Ki Jeong', 'Hyun-Jic Oh'] | 2023-06-25 | null | null | null | null | ['nuclei-classification', 'classification-1'] | ['medical', 'methodology'] | [ 1.24689907e-01 1.67124882e-01 -1.48293644e-01 -2.55843848e-01
-6.98904395e-01 -1.57227516e-01 2.14847967e-01 2.04839379e-01
-5.43103158e-01 6.51367486e-01 -3.27066868e-03 1.26757145e-01
1.80802912e-01 -1.05721176e+00 -3.95411164e-01 -1.34298480e+00
3.92974645e-01 6.73407197e-01 4.94821489e-01 -2.50117946e-02
2.14025363e-01 4.70867604e-01 -1.42709482e+00 3.77342373e-01
1.03114676e+00 8.13125312e-01 2.70009130e-01 3.33232850e-01
-3.10495555e-01 4.62771177e-01 -6.12019122e-01 -3.14621687e-01
1.59381088e-02 -5.32940805e-01 -6.92886591e-01 7.33369142e-02
-5.18371165e-02 -1.79730028e-01 -1.81058347e-01 1.30093849e+00
7.74510741e-01 -1.62902042e-01 9.49231625e-01 -1.08659732e+00
-4.34032798e-01 5.59014678e-01 -9.21365201e-01 3.44964266e-01
-3.87051463e-01 2.98483223e-01 7.26449907e-01 -3.90048504e-01
7.29854524e-01 9.44213688e-01 5.31563759e-01 8.88655245e-01
-9.71466720e-01 -8.28322232e-01 -3.20795387e-01 1.08140424e-01
-1.25918913e+00 -1.31242067e-01 7.11273134e-01 -5.89173079e-01
4.04712647e-01 1.83997110e-01 9.11559999e-01 7.95688689e-01
1.76233217e-01 9.76776123e-01 1.11867619e+00 -1.91029996e-01
3.14744323e-01 -2.71613523e-02 8.15682113e-02 4.46911067e-01
4.73717928e-01 -3.10167015e-01 -3.28286327e-02 1.85482189e-01
7.59862661e-01 7.04631880e-02 -3.04985702e-01 -1.56957760e-01
-1.14225829e+00 7.07653344e-01 5.49395800e-01 7.68789530e-01
-2.72194475e-01 -2.02330917e-01 4.19359118e-01 -1.76677242e-01
6.33739293e-01 2.33434543e-01 -2.57207435e-02 1.33910477e-01
-1.10963118e+00 2.92332202e-01 3.20161492e-01 4.11926925e-01
4.72908497e-01 -1.18830651e-01 -5.30219495e-01 9.70833063e-01
2.61116564e-01 4.35885549e-01 8.25931191e-01 -7.05246925e-01
1.55590639e-01 1.09749663e+00 -2.31844008e-01 -9.21435237e-01
-8.67641330e-01 -8.05910289e-01 -1.25550735e+00 2.67880797e-01
8.49437833e-01 1.07431002e-01 -1.18487704e+00 1.54146588e+00
5.09837747e-01 -9.37635452e-02 1.53974429e-01 1.03539360e+00
8.05760503e-01 6.73574805e-01 4.92463112e-02 -2.98990816e-01
1.28916109e+00 -9.97886240e-01 -9.68657076e-01 1.98982880e-01
1.06670439e+00 -4.86397922e-01 1.07237589e+00 5.29325306e-01
-8.60513091e-01 -5.11353254e-01 -9.63225663e-01 -5.53482696e-02
-2.80381441e-01 2.71453321e-01 5.37577808e-01 7.68394470e-01
-7.88968027e-01 5.21621227e-01 -1.01607180e+00 -2.76092678e-01
9.99559760e-01 3.42210054e-01 -2.45348826e-01 -1.06737748e-01
-9.44968998e-01 4.90082026e-01 4.56343710e-01 1.50813773e-01
-7.34976649e-01 -7.75825441e-01 -4.36757982e-01 5.51524498e-02
-2.37225424e-02 -4.57949668e-01 9.20333385e-01 -7.74491131e-01
-1.31491351e+00 1.09831274e+00 2.07487926e-01 -1.85716152e-01
6.29492044e-01 4.43490118e-01 -3.15224044e-02 2.28268310e-01
6.79639652e-02 1.04735827e+00 3.52285773e-01 -1.10342562e+00
-5.03844738e-01 -5.91940522e-01 -2.93389171e-01 8.15728977e-02
-4.78069991e-01 -4.13254827e-01 -3.92866045e-01 -6.11895680e-01
2.51854897e-01 -9.36504662e-01 -3.68039757e-01 1.14051841e-01
-3.66409838e-01 -2.03770041e-01 6.04798496e-01 -5.16877592e-01
8.64388704e-01 -2.31556487e+00 2.63245441e-02 2.39445657e-01
4.07571584e-01 3.90827209e-01 7.12318271e-02 -1.87166438e-01
2.67950119e-03 4.01799172e-01 -2.40875378e-01 -3.65236223e-01
-2.44464859e-01 1.34547427e-01 2.81067580e-01 6.55251384e-01
1.77830741e-01 7.26946235e-01 -6.95362210e-01 -7.53234863e-01
-2.13152677e-01 4.83787149e-01 -7.17141390e-01 1.35125995e-01
-1.68593511e-01 5.01838744e-01 -3.65331322e-01 6.69941068e-01
1.00405478e+00 -3.91096503e-01 2.92610377e-01 -4.62631613e-01
2.60220826e-01 -3.06400746e-01 -9.92906332e-01 1.50805795e+00
5.07062115e-02 2.42537290e-01 -1.23194242e-02 -1.01664758e+00
9.91538107e-01 1.51573256e-01 4.91931796e-01 -9.12903786e-01
4.46367562e-01 4.33739513e-01 4.86132324e-01 -5.23709953e-01
1.80803701e-01 -5.03572404e-01 1.98381767e-01 2.04018116e-01
1.34608392e-02 -1.40580550e-01 4.61757302e-01 6.83742091e-02
7.47738421e-01 -2.37313941e-01 -1.35474920e-01 -3.36064637e-01
4.67087567e-01 -8.28998387e-02 8.70895326e-01 3.61694485e-01
-4.02288407e-01 8.33586693e-01 9.44478869e-01 -2.04275772e-01
-1.15989649e+00 -6.32983744e-01 -2.34460562e-01 3.57320726e-01
2.57516205e-01 5.38965389e-02 -1.10431731e+00 -8.83850574e-01
-3.12630028e-01 2.84365416e-01 -7.45668769e-01 -2.25269362e-01
-2.82249629e-01 -1.57548296e+00 7.63077915e-01 5.59057355e-01
6.57369375e-01 -9.69550848e-01 -2.18814924e-01 -6.75597712e-02
-3.88920754e-01 -7.08164394e-01 -1.88281819e-01 1.10363267e-01
-9.40261781e-01 -1.05653465e+00 -1.06132257e+00 -8.24592054e-01
1.03489184e+00 -5.97537532e-02 6.51084661e-01 3.55916083e-01
-4.14768249e-01 -4.21841592e-01 -3.04807723e-01 -2.38440827e-01
-6.28859937e-01 2.57869333e-01 -1.69325382e-01 -8.61433917e-04
1.34859845e-01 -3.45396340e-01 -8.78148437e-01 3.22805852e-01
-1.23383045e+00 1.90726131e-01 6.94862783e-01 9.43754971e-01
8.95405591e-01 4.21279252e-01 6.20521724e-01 -1.05157578e+00
2.74277687e-01 -2.89700866e-01 -4.94982034e-01 -5.00326641e-02
-5.84510148e-01 -8.73768479e-02 5.47545731e-01 -3.97061169e-01
-9.31389153e-01 -4.55533825e-02 -5.17413914e-01 -1.37780204e-01
-1.42486438e-01 2.89501578e-01 -3.43805254e-01 -1.40142469e-02
6.19360924e-01 2.14755908e-01 4.00005996e-01 -2.50354052e-01
-1.10834129e-01 6.27574503e-01 1.03328124e-01 -2.81284481e-01
2.24960223e-01 8.13940167e-01 1.03974901e-01 -6.20593250e-01
-6.65997803e-01 -4.01527196e-01 -4.40805018e-01 -2.78909832e-01
1.00252843e+00 -6.41466916e-01 -6.18657589e-01 1.04144061e+00
-8.22193682e-01 -4.02864635e-01 -3.41689497e-01 4.62824851e-01
-2.74317443e-01 3.19178373e-01 -8.71815026e-01 -5.38566768e-01
-2.96762139e-01 -1.53716481e+00 1.07727313e+00 5.64093351e-01
6.18161559e-02 -7.71762073e-01 1.16404206e-01 6.83931351e-01
3.34189713e-01 1.83894366e-01 1.19483030e+00 -8.16051364e-01
-4.54653054e-01 -9.32051614e-02 -3.61576200e-01 3.40435475e-01
-6.63770875e-03 1.51619807e-01 -9.36276734e-01 -1.64490268e-01
-8.17722380e-02 -4.16125655e-01 1.05843747e+00 5.57833731e-01
1.39032340e+00 1.64244518e-01 -7.93773115e-01 4.96908575e-01
1.31502652e+00 3.36858302e-01 1.01105297e+00 1.72498003e-01
5.59807360e-01 7.17528164e-01 6.04252756e-01 2.59127468e-02
1.91285670e-01 4.46276903e-01 4.86686558e-01 -6.36570394e-01
-5.57339549e-01 1.19390726e-01 -1.98625833e-01 9.11130548e-01
7.53623396e-02 -5.86478710e-01 -1.14786828e+00 8.28788579e-01
-1.63039482e+00 -7.83784330e-01 -3.82863581e-01 1.73993373e+00
1.03808236e+00 1.79494590e-01 1.09717518e-01 4.32459623e-01
8.15476120e-01 -1.10309981e-01 -5.25430679e-01 2.58119613e-01
-1.93599164e-01 3.88300419e-02 2.25694075e-01 1.40507907e-01
-9.24303412e-01 6.65844381e-01 6.09620428e+00 1.40464926e+00
-1.24703670e+00 1.87812880e-01 1.28071415e+00 -4.63402607e-02
-3.75163674e-01 -5.02893209e-01 -9.39489424e-01 6.10447049e-01
4.29532409e-01 3.85468006e-01 -2.79333293e-01 4.51421797e-01
1.39295861e-01 -2.71591783e-01 -6.86829746e-01 8.71958852e-01
-4.08943184e-02 -1.45861411e+00 2.08490789e-01 3.00813854e-01
7.01873839e-01 -1.65389851e-01 3.35691310e-02 1.99089438e-01
-1.67324454e-01 -1.01263702e+00 3.36621076e-01 5.25289297e-01
5.56584239e-01 -8.02854538e-01 1.25464761e+00 4.18786287e-01
-4.89795893e-01 1.19841486e-01 -4.59250033e-01 3.66934121e-01
-1.24626063e-01 1.08641291e+00 -8.28952014e-01 3.60838801e-01
5.97295046e-01 3.84427130e-01 -6.27847433e-01 1.26871467e+00
1.78488806e-01 7.15035021e-01 -3.68868530e-01 -2.19958320e-01
-1.99465305e-02 -3.53245169e-01 1.50076210e-01 9.96713281e-01
2.52458394e-01 2.76940931e-02 8.49919990e-02 9.80798841e-01
-2.97853053e-01 2.90158719e-01 -2.29900986e-01 -1.25572547e-01
9.15625915e-02 1.58487093e+00 -1.57700610e+00 -1.93371385e-01
4.10671309e-02 5.85103571e-01 1.82215720e-01 3.42898746e-03
-9.35205817e-01 -4.16248441e-01 1.51121020e-01 4.21364158e-01
1.17102630e-01 1.56832710e-01 -4.14211303e-01 -8.54213834e-01
-2.49068096e-01 -8.07941794e-01 2.75515199e-01 -5.02057672e-01
-1.23788524e+00 4.90434587e-01 -4.02435303e-01 -1.06989276e+00
3.98513824e-01 -4.74726051e-01 -3.04221302e-01 5.74696124e-01
-1.41149843e+00 -1.09480870e+00 -3.48351091e-01 8.09085742e-02
2.52312094e-01 -7.23121921e-03 4.51492220e-01 7.09186018e-01
-7.95053899e-01 5.75546980e-01 1.16378903e-01 2.01954424e-01
6.29063308e-01 -1.13119400e+00 -1.16633885e-01 5.80759943e-01
-3.10684890e-01 2.01424226e-01 3.73868048e-01 -7.15557694e-01
-7.70807624e-01 -1.00230825e+00 4.84134346e-01 1.20358216e-02
1.82548255e-01 -4.07494783e-01 -1.02610278e+00 9.41457823e-02
-8.84500239e-03 1.46846429e-01 9.37816203e-01 -2.79695779e-01
1.39996946e-01 -2.85536528e-01 -1.61948240e+00 5.81654489e-01
7.18118548e-01 -1.40357792e-01 -2.25202978e-01 4.17022467e-01
5.93578875e-01 -4.24760431e-01 -8.14390302e-01 5.88694572e-01
4.10143763e-01 -9.95956242e-01 5.34644306e-01 -2.17921123e-01
5.99776506e-01 -5.52608371e-01 1.00324132e-01 -1.30263960e+00
-3.33482832e-01 2.08657831e-01 3.34116876e-01 1.37816000e+00
4.55823004e-01 -3.81816417e-01 1.21247351e+00 2.25688249e-01
-6.82240874e-02 -1.03226364e+00 -8.39876533e-01 -4.06763673e-01
3.36821616e-01 4.52989824e-02 4.99385446e-01 9.19436991e-01
-2.29294509e-01 1.29960999e-01 1.37885138e-01 -6.53614551e-02
4.61383373e-01 -7.19222948e-02 4.34753895e-01 -1.13487482e+00
-4.99973968e-02 -4.73308235e-01 -5.77218413e-01 -6.57493174e-01
2.48795003e-03 -1.01601613e+00 -8.03804398e-02 -1.47272015e+00
5.00275314e-01 -7.24098623e-01 -2.59686798e-01 4.52032954e-01
-1.73538551e-01 8.34017634e-01 -1.39059022e-01 2.53568828e-01
-5.26553750e-01 5.78248441e-01 1.85523903e+00 -4.32278275e-01
7.36168772e-02 -1.45584390e-01 -7.05465555e-01 6.40441835e-01
8.20423067e-01 -7.19732821e-01 -4.89974439e-01 -1.21112339e-01
3.13036919e-01 -1.97366655e-01 1.39399514e-01 -1.30734777e+00
4.58245464e-02 7.08043575e-02 6.92702949e-01 -7.39742577e-01
1.55253887e-01 -4.99515742e-01 2.63238102e-02 7.10774243e-01
-2.05866963e-01 -5.25038362e-01 1.37599617e-01 5.11527956e-01
-2.84129083e-01 -3.15148145e-01 1.28379238e+00 -1.65037706e-01
-8.67072120e-02 3.03945035e-01 -3.94179523e-01 8.31679180e-02
1.14007485e+00 -3.11126351e-01 -5.24631619e-01 -1.30333221e-02
-6.34012699e-01 2.52241433e-01 5.29518187e-01 2.50588413e-02
4.00974303e-01 -1.25010407e+00 -5.80886364e-01 2.78599441e-01
-5.31841628e-02 4.01711106e-01 6.86442316e-01 1.22906876e+00
-9.12215233e-01 3.58560868e-02 -3.65149558e-01 -9.27193224e-01
-1.04303634e+00 4.07457143e-01 6.62946284e-01 -6.62623942e-01
-3.83892596e-01 9.91453767e-01 4.45295483e-01 -6.62148595e-01
6.24731109e-02 -4.77855682e-01 -6.51438117e-01 2.42327482e-01
4.76031899e-01 3.76968175e-01 3.96437407e-01 -3.27947915e-01
-2.66402751e-01 5.03806591e-01 -3.94411385e-01 2.67668217e-01
1.21529031e+00 8.27664509e-02 -3.47877979e-01 3.16701144e-01
1.07243681e+00 6.94428459e-02 -1.09788239e+00 2.93717265e-01
-3.11102152e-01 -2.40410641e-01 2.61617303e-01 -8.22801590e-01
-1.61823440e+00 9.86805022e-01 1.06008458e+00 2.14433730e-01
1.06275606e+00 -1.57235771e-01 9.28669989e-01 -1.27030507e-01
6.09202534e-02 -1.01699781e+00 1.25688776e-01 6.39526099e-02
3.45243782e-01 -1.07362759e+00 -1.58565059e-01 -5.39690554e-01
-4.94999945e-01 1.05465579e+00 8.42794180e-01 6.09723888e-02
5.39808869e-01 5.13833702e-01 2.78181285e-01 -3.92878652e-01
-3.41239721e-01 -3.28753218e-02 -1.28750294e-01 6.56378746e-01
3.92011344e-01 -8.58113170e-02 -6.44704044e-01 9.47683394e-01
5.31712286e-02 1.13532580e-01 5.38073063e-01 6.56500340e-01
-3.65010917e-01 -1.17604935e+00 -2.15961576e-01 5.75669289e-01
-7.94916868e-01 9.24222320e-02 -2.49123156e-01 6.60583675e-01
5.29182374e-01 5.46017110e-01 2.63364702e-01 -1.61344588e-01
1.28606692e-01 -3.58045064e-02 5.59181869e-01 -4.07185286e-01
-5.62613487e-01 2.73779452e-01 -2.49104172e-01 -1.22955121e-01
-4.47405815e-01 -3.66584212e-01 -1.57505429e+00 -1.67694390e-01
-6.16386592e-01 1.55280858e-01 4.43744987e-01 9.14331794e-01
2.39120603e-01 9.18580711e-01 3.55640620e-01 -5.68738818e-01
-3.66264790e-01 -8.96554470e-01 -9.71410155e-01 5.28094172e-01
5.51563278e-02 -6.91098332e-01 -2.60410845e-01 -9.57364514e-02] | [14.880566596984863, -3.038268566131592] |
26172129-f57e-4b8e-8f46-4c70bd9ad114 | analysing-mathematical-reasoning-abilities-of-1 | 1904.01557 | null | http://arxiv.org/abs/1904.01557v1 | http://arxiv.org/pdf/1904.01557v1.pdf | Analysing Mathematical Reasoning Abilities of Neural Models | Mathematical reasoning---a core ability within human intelligence---presents
some unique challenges as a domain: we do not come to understand and solve
mathematical problems primarily on the back of experience and evidence, but on
the basis of inferring, learning, and exploiting laws, axioms, and symbol
manipulation rules. In this paper, we present a new challenge for the
evaluation (and eventually the design) of neural architectures and similar
system, developing a task suite of mathematics problems involving sequential
questions and answers in a free-form textual input/output format. The
structured nature of the mathematics domain, covering arithmetic, algebra,
probability and calculus, enables the construction of training and test splits
designed to clearly illuminate the capabilities and failure-modes of different
architectures, as well as evaluate their ability to compose and relate
knowledge and learned processes. Having described the data generation process
and its potential future expansions, we conduct a comprehensive analysis of
models from two broad classes of the most powerful sequence-to-sequence
architectures and find notable differences in their ability to resolve
mathematical problems and generalize their knowledge. | ['Felix Hill', 'Edward Grefenstette', 'David Saxton', 'Pushmeet Kohli'] | 2019-04-02 | analysing-mathematical-reasoning-abilities-of | https://openreview.net/forum?id=H1gR5iR5FX | https://openreview.net/pdf?id=H1gR5iR5FX | iclr-2019-5 | ['math-word-problem-solving', 'mathematical-question-answering', 'mathematical-reasoning', 'math-word-problem-solving', 'math-word-problem-solving'] | ['knowledge-base', 'natural-language-processing', 'natural-language-processing', 'reasoning', 'time-series'] | [ 2.33204156e-01 3.17524038e-02 3.23566109e-01 -5.07164657e-01
-3.02494764e-01 -9.13273573e-01 8.08813751e-01 2.99237847e-01
-2.28494585e-01 6.61735356e-01 6.62645325e-02 -9.57126796e-01
-7.98451245e-01 -1.00178480e+00 -6.34385765e-01 -8.71149674e-02
-2.28281841e-01 8.63335609e-01 -3.74912210e-02 -5.45109808e-01
5.19540250e-01 4.71823961e-01 -1.47655487e+00 4.03142035e-01
1.10490263e+00 7.12638915e-01 2.84154892e-01 9.16899800e-01
-5.03663957e-01 1.45384181e+00 -5.83814979e-01 -6.40901089e-01
1.37189701e-01 -4.79692608e-01 -1.12482762e+00 -4.78896171e-01
7.27854729e-01 -2.00929895e-01 -4.44063067e-01 8.57385278e-01
9.70021412e-02 3.12198341e-01 6.99965239e-01 -1.05675805e+00
-1.25091302e+00 9.28188682e-01 3.34021568e-01 5.48717856e-01
7.01513827e-01 3.24725986e-01 1.10698950e+00 -5.38870215e-01
5.84035635e-01 1.29874766e+00 7.75204539e-01 7.19152451e-01
-1.24423635e+00 -4.13962454e-01 4.77381982e-03 5.94681442e-01
-1.20615017e+00 -4.98986840e-01 3.86919469e-01 -4.56695855e-01
1.25425398e+00 2.30567202e-01 7.32929587e-01 7.81770647e-01
-2.98659485e-02 8.03308845e-01 1.01161647e+00 -4.59262222e-01
1.37815207e-01 4.64619920e-02 4.19899136e-01 9.79353428e-01
1.17158875e-01 1.80586711e-01 -4.93346930e-01 5.54997325e-02
9.14694428e-01 -3.88396770e-01 -3.48363221e-01 -1.51486501e-01
-1.29686141e+00 5.64575076e-01 3.49401087e-01 4.14753765e-01
-1.36722460e-01 1.96938664e-01 1.37334272e-01 7.32142985e-01
-1.89379603e-01 1.22201145e+00 -7.25416481e-01 -1.65445939e-01
-9.20251310e-01 6.41569555e-01 1.27294528e+00 8.42455626e-01
4.78371054e-01 2.17232525e-01 -1.75862387e-01 3.56467158e-01
-2.20417418e-02 3.09533477e-01 4.63009030e-01 -1.09471786e+00
5.57860732e-01 5.31574547e-01 -1.01493336e-01 -9.14197743e-01
-4.02374059e-01 -6.11822665e-01 -5.26946545e-01 5.81633188e-02
8.03932071e-01 -2.56728977e-02 -6.62273943e-01 1.90968561e+00
-1.06198817e-01 7.09493384e-02 2.56924570e-01 6.59792006e-01
8.45992386e-01 6.34117365e-01 9.99427289e-02 1.66264717e-02
1.03246498e+00 -5.17658055e-01 -3.11761796e-01 -2.57370293e-01
5.61233401e-01 -2.48237997e-01 1.06119311e+00 5.30584157e-01
-1.57112575e+00 -7.64762580e-01 -9.59960997e-01 -4.87005055e-01
-4.77198035e-01 -2.60977894e-01 8.96445394e-01 4.62708861e-01
-1.26724195e+00 9.28114653e-01 -4.89790738e-01 -6.36208951e-02
3.49242985e-01 1.82536244e-01 -1.03748724e-01 -9.76931825e-02
-1.27432227e+00 1.45046926e+00 7.04391718e-01 -6.83520809e-02
-6.35076404e-01 -1.17154729e+00 -7.93288946e-01 5.04850209e-01
1.84095263e-01 -1.11909962e+00 1.39146030e+00 -7.51140773e-01
-1.34411681e+00 7.50334680e-01 -1.19669316e-02 -6.04920328e-01
1.76625058e-01 -4.63532098e-02 -2.26328835e-01 -4.13743146e-02
-2.74200052e-01 4.77807909e-01 2.82983959e-01 -9.25887048e-01
-5.68881989e-01 -3.65552127e-01 2.48505831e-01 1.79234877e-01
7.94959962e-02 -1.84123874e-01 3.18847001e-02 -5.84407628e-01
1.48365155e-01 -3.43929559e-01 8.70817434e-03 -2.36258224e-01
6.72704726e-02 -4.02950168e-01 -5.98861789e-03 -7.04599380e-01
1.12812781e+00 -1.90255046e+00 5.40180624e-01 2.42884442e-01
3.72574419e-01 1.57284588e-01 -2.35291943e-01 3.11502904e-01
-1.59358695e-01 2.43381485e-01 -8.78505409e-02 1.00334108e-01
4.65713710e-01 1.36351526e-01 -6.24141872e-01 -1.82424039e-01
3.76563489e-01 1.43104613e+00 -1.12095129e+00 -3.65959585e-01
1.20961972e-01 -8.76912102e-02 -5.19534469e-01 2.80285656e-01
-8.22446644e-01 6.87262788e-02 -2.93347031e-01 4.06531990e-01
1.40197217e-01 -4.58707303e-01 2.83699334e-01 2.03764692e-01
-2.42980551e-02 8.48399162e-01 -1.03355718e+00 1.71175194e+00
-4.98007178e-01 8.57148767e-01 -1.69606000e-01 -1.20068562e+00
8.47357869e-01 1.99762389e-01 -2.22515002e-01 -8.12562048e-01
-3.46887372e-02 1.33512825e-01 4.74866718e-01 -7.63431907e-01
4.04361337e-01 -2.41600424e-01 1.18391186e-01 6.32484198e-01
3.74355286e-01 -5.05793214e-01 6.49606884e-01 1.78556681e-01
1.21398807e+00 2.57980138e-01 1.95085093e-01 -1.06906481e-01
5.11136174e-01 2.40904838e-01 1.57415438e-02 1.14155388e+00
1.43158332e-01 9.89158154e-02 4.24450040e-01 -7.25029826e-01
-9.85731542e-01 -1.42422569e+00 -3.95570211e-02 1.33680832e+00
-4.95241374e-01 -2.79563874e-01 -4.20979589e-01 -1.97495356e-01
5.99323660e-02 1.26070690e+00 -4.70875084e-01 -1.79026291e-01
-6.16681755e-01 -4.54206854e-01 7.55457103e-01 4.13566917e-01
5.07423103e-01 -1.36056936e+00 -6.29620373e-01 2.20393866e-01
-8.30847099e-02 -8.84236813e-01 3.44005793e-01 2.63781965e-01
-1.02448523e+00 -9.93139386e-01 -2.62117654e-01 -8.65653753e-01
2.77449489e-01 -1.93239078e-01 1.63575256e+00 3.63709956e-01
-2.48127893e-01 4.96273935e-01 -1.25850275e-01 -5.12321532e-01
-6.14843965e-01 4.53743413e-02 -1.64275125e-01 -7.14213669e-01
4.46771950e-01 -8.48956168e-01 -4.77349060e-03 -3.11316073e-01
-8.19598436e-01 6.52819723e-02 7.93379545e-01 6.20498300e-01
-1.68873727e-01 2.32532233e-01 4.28102374e-01 -6.82980895e-01
8.99482608e-01 -5.35409808e-01 -4.88956511e-01 6.31265044e-01
-4.75634336e-01 4.33072001e-01 7.90336490e-01 -3.61923933e-01
-9.29670632e-01 -3.69482815e-01 1.89154421e-03 -1.96168020e-01
-3.87777328e-01 8.13253284e-01 1.74898151e-02 1.05197422e-01
8.82002592e-01 6.24907434e-01 8.93459395e-02 -4.10449743e-01
8.40102911e-01 1.32008538e-01 9.61112320e-01 -1.18702292e+00
9.64247882e-01 -8.76380354e-02 1.88243296e-02 -5.90785921e-01
-9.28858221e-01 -7.48570263e-03 -4.90640461e-01 1.51381925e-01
4.36643124e-01 -5.35479307e-01 -9.75234151e-01 2.17865184e-01
-1.30312145e+00 -5.81127524e-01 -3.82037789e-01 3.03501368e-01
-6.43648446e-01 2.10980862e-01 -7.86329031e-01 -6.97252274e-01
-1.78004310e-01 -7.52052784e-01 2.82536238e-01 2.35271826e-01
-6.21628881e-01 -1.29509282e+00 -8.48087594e-02 4.40548062e-01
6.25998557e-01 -1.34910092e-01 1.78007901e+00 -9.34417844e-01
-8.09679210e-01 2.32806683e-01 -2.63017297e-01 1.90565556e-01
-3.32496405e-01 -6.17904402e-02 -7.07656085e-01 1.37247071e-01
1.83320090e-01 -5.92062175e-01 6.81864798e-01 -3.71831073e-03
1.27864027e+00 -3.86315137e-01 1.43828690e-01 5.98974049e-01
1.19725537e+00 -2.12012827e-02 6.90229952e-01 2.97283709e-01
2.18105838e-01 6.78110659e-01 -1.60940304e-01 1.33386582e-01
5.97961009e-01 9.60253626e-02 1.73750799e-02 4.34252739e-01
5.78129245e-03 -4.26507771e-01 1.38445988e-01 7.66414642e-01
-1.72375917e-01 2.15713996e-02 -1.27987599e+00 4.04595941e-01
-1.59060800e+00 -1.27221930e+00 7.60747120e-02 1.88974953e+00
1.38332438e+00 1.92282602e-01 -2.80779712e-02 2.20810667e-01
1.88013494e-01 -2.87064195e-01 -3.54905874e-01 -5.33677936e-01
-2.49216482e-02 9.34016466e-01 -1.10260181e-01 6.04979038e-01
-5.83540440e-01 8.89525354e-01 7.79731750e+00 6.66128159e-01
-7.59986043e-01 -4.47627604e-01 3.92317384e-01 7.31626078e-02
-3.37283880e-01 -1.85038462e-01 -4.10194606e-01 1.71829432e-01
1.26102924e+00 -2.21864671e-01 1.08559048e+00 5.35082340e-01
-3.21231872e-01 3.39534953e-02 -1.82250524e+00 6.73749447e-01
6.90750480e-02 -1.76500666e+00 4.80837017e-01 -4.15871769e-01
4.90821779e-01 -1.93693876e-01 1.24831036e-01 7.08406270e-01
6.45767272e-01 -1.65656054e+00 8.51930439e-01 9.27720487e-01
4.32096750e-01 -2.63743550e-01 3.71522486e-01 6.48710608e-01
-6.94375694e-01 -3.83783460e-01 -2.41457388e-01 -8.53720605e-01
-2.39553809e-01 1.31331205e-01 -8.22095156e-01 5.38880467e-01
3.85831535e-01 4.46659029e-01 -7.15426862e-01 8.78087938e-01
-4.44380343e-01 4.33067083e-01 -2.00520575e-01 -4.71170247e-01
-1.94187518e-02 -8.58819932e-02 2.12210611e-01 1.37283111e+00
1.05257839e-01 5.38088918e-01 -2.07260400e-02 1.61318922e+00
1.84209347e-01 -3.13778132e-01 -4.64902401e-01 -3.48867863e-01
7.01762795e-01 8.21306527e-01 -3.36630583e-01 -4.10948575e-01
-3.53644252e-01 4.48227912e-01 7.40950346e-01 4.35595036e-01
-6.18622065e-01 -3.14839065e-01 4.92007524e-01 -6.54003862e-03
1.05111375e-01 -6.00970328e-01 -8.35346103e-01 -1.08829951e+00
-6.11444600e-02 -1.25570250e+00 3.49721074e-01 -1.05405021e+00
-1.46592963e+00 5.00075035e-02 1.87744081e-01 -3.03415567e-01
-5.12891769e-01 -1.03551006e+00 -6.82340264e-01 1.10672116e+00
-1.19901192e+00 -8.56542706e-01 -1.61882758e-01 4.27328467e-01
2.57664204e-01 -3.85693282e-01 9.53812659e-01 -7.81194270e-02
-1.72151998e-01 4.34242070e-01 -1.13908658e-02 4.53174680e-01
-4.61624116e-02 -1.39531589e+00 5.67708135e-01 5.01492679e-01
3.81638378e-01 1.15040708e+00 6.91892743e-01 -2.38077700e-01
-1.65671468e+00 -5.74161708e-01 9.59732890e-01 -9.40966368e-01
1.04680836e+00 -2.06489027e-01 -1.06812811e+00 8.02030206e-01
2.76432429e-02 -6.11607909e-01 5.47033489e-01 3.62635285e-01
-6.24004424e-01 1.37731796e-02 -9.32854772e-01 7.33527720e-01
1.12509620e+00 -6.65233374e-01 -1.56218147e+00 1.79009318e-01
6.99263275e-01 -4.67854410e-01 -7.82826841e-01 1.95050582e-01
4.92985934e-01 -9.79015708e-01 1.20294619e+00 -1.22260129e+00
8.60740066e-01 -9.75296199e-02 -7.46800825e-02 -1.17683542e+00
-6.54159307e-01 -5.79995513e-01 -3.31039637e-01 9.19873178e-01
6.52746439e-01 -4.17126030e-01 6.47134066e-01 6.89261794e-01
-9.69037265e-02 -7.29160070e-01 -7.25334942e-01 -4.68433470e-01
6.01984620e-01 -6.58404708e-01 7.05628455e-01 1.04167080e+00
3.65563333e-01 5.41954517e-01 5.24430037e-01 -1.15003409e-02
4.32722092e-01 3.51477683e-01 6.52327061e-01 -1.35197401e+00
-5.44492424e-01 -8.98763418e-01 -3.04780692e-01 -1.15208411e+00
2.66203701e-01 -1.35816109e+00 -1.03484824e-01 -1.53924775e+00
7.51658157e-02 -4.32325482e-01 -1.33495867e-01 3.68178546e-01
-1.74292624e-01 -3.22295547e-01 2.84500897e-01 3.57923806e-02
-5.61403573e-01 1.57959893e-01 1.07245803e+00 -5.55292927e-02
1.25151351e-01 -2.66103476e-01 -8.69895875e-01 7.25843847e-01
8.33027184e-01 8.16425085e-02 -5.92725039e-01 -8.45181465e-01
8.16970348e-01 1.87298074e-01 6.51064157e-01 -1.16102803e+00
4.50708210e-01 -4.71064150e-01 6.89087927e-01 -3.27587157e-01
1.36340037e-01 -4.17124242e-01 -1.09479919e-01 4.65998590e-01
-7.26226211e-01 3.28274250e-01 3.31494510e-01 1.83775485e-01
1.01885647e-01 -4.27504778e-01 4.32403594e-01 -7.49928594e-01
-1.01846027e+00 -1.94829956e-01 -3.19670945e-01 5.66258848e-01
5.54616153e-01 -1.35335803e-01 -5.80928385e-01 -2.71176457e-01
-7.74340272e-01 4.66629744e-01 2.11854964e-01 3.78903300e-01
6.65100098e-01 -8.95122290e-01 -8.49771023e-01 1.64897293e-01
-1.86515272e-01 -5.78779820e-03 -3.81422341e-02 3.64029676e-01
-7.01925755e-01 7.00433016e-01 -3.88911337e-01 -2.24554121e-01
-6.52490497e-01 6.49859667e-01 5.65050900e-01 -3.63337994e-01
-2.34607011e-01 9.85022843e-01 -1.09013215e-01 -7.23689020e-01
3.47808272e-01 -7.55893290e-01 -2.02681810e-01 -4.29902494e-01
4.66407627e-01 2.67203867e-01 -1.61801666e-01 2.99688578e-01
-6.11952581e-02 1.58372849e-01 1.29789591e-01 -1.79841474e-01
1.26522434e+00 1.99934542e-01 -4.46508706e-01 5.62397003e-01
4.90530103e-01 -4.90207404e-01 -4.99577016e-01 -3.43896836e-01
3.43513250e-01 -5.91656901e-02 -3.41383994e-01 -1.25926673e+00
-3.00667584e-01 9.77257371e-01 -1.45016193e-01 2.78121173e-01
7.30015934e-01 1.15535334e-02 4.71249849e-01 9.76769090e-01
2.33922079e-01 -8.25640380e-01 1.08120285e-01 1.11063576e+00
8.05091918e-01 -8.04417193e-01 -5.56980893e-02 -1.26787245e-01
-1.12276763e-01 1.40634513e+00 6.75176084e-01 2.74928380e-02
2.51116961e-01 2.66639531e-01 -2.10510731e-01 -2.75682241e-01
-1.16606319e+00 -1.12091102e-01 2.61917323e-01 7.43389547e-01
7.05792964e-01 -1.63277894e-01 1.52515978e-01 6.38047457e-01
-8.10442448e-01 2.66901016e-01 2.43774697e-01 7.91316032e-01
-6.01143777e-01 -7.53913581e-01 -3.57427210e-01 5.13042510e-01
-1.02000870e-01 -3.89570594e-01 -5.21585107e-01 8.11973333e-01
2.90076673e-01 7.99229026e-01 1.95455655e-01 -2.43808761e-01
8.47893655e-02 6.01000428e-01 1.01413536e+00 -6.87039554e-01
-6.46615684e-01 -1.00523925e+00 2.20010951e-01 -1.51318908e-01
-4.91930135e-02 -4.65220630e-01 -1.23799682e+00 -6.81729078e-01
1.61831021e-01 3.18995982e-01 4.07487094e-01 1.22778106e+00
1.11516431e-01 6.64963424e-01 1.66870542e-02 -5.52499771e-01
-1.25073445e+00 -9.67465222e-01 -1.62320688e-01 5.65665007e-01
3.24847668e-01 -2.45775282e-01 -2.81125188e-01 1.27489507e-01] | [9.44970417022705, 7.216930866241455] |
4264ccd9-ba6c-4963-9d0b-53c932be431b | budgeted-multi-armed-bandits-with-asymmetric | 2306.07071 | null | https://arxiv.org/abs/2306.07071v1 | https://arxiv.org/pdf/2306.07071v1.pdf | Budgeted Multi-Armed Bandits with Asymmetric Confidence Intervals | We study the stochastic Budgeted Multi-Armed Bandit (MAB) problem, where a player chooses from $K$ arms with unknown expected rewards and costs. The goal is to maximize the total reward under a budget constraint. A player thus seeks to choose the arm with the highest reward-cost ratio as often as possible. Current state-of-the-art policies for this problem have several issues, which we illustrate. To overcome them, we propose a new upper confidence bound (UCB) sampling policy, $\omega$-UCB, that uses asymmetric confidence intervals. These intervals scale with the distance between the sample mean and the bounds of a random variable, yielding a more accurate and tight estimation of the reward-cost ratio compared to our competitors. We show that our approach has logarithmic regret and consistently outperforms existing policies in synthetic and real settings. | ['Klemens Böhm', 'Edouard Fouché', 'Vadim Arzamasov', 'Marco Heyden'] | 2023-06-12 | null | null | null | null | ['multi-armed-bandits'] | ['miscellaneous'] | [-1.67681605e-01 2.70337705e-02 -9.56821144e-01 -3.01467985e-01
-1.34459674e+00 -8.09312165e-01 -3.60241123e-02 9.37651023e-02
-7.23974824e-01 1.48077989e+00 -1.50990263e-01 -6.58454716e-01
-7.14445412e-01 -7.00443685e-01 -8.17538977e-01 -7.25584567e-01
-1.38053507e-01 9.41029847e-01 -1.10796236e-01 9.83515531e-02
4.17812228e-01 3.34451109e-01 -9.01289463e-01 -1.62058882e-02
6.09708965e-01 1.58761775e+00 -1.47488534e-01 6.66299462e-01
5.82929105e-02 7.05230176e-01 -8.45169783e-01 -7.47738361e-01
6.35272086e-01 -5.49277008e-01 -7.98556685e-01 -8.87822658e-02
-2.85067916e-01 -6.99586034e-01 7.17583150e-02 1.02554059e+00
2.36882523e-01 2.65985936e-01 4.88147944e-01 -1.20200741e+00
-3.06280613e-01 1.20460629e+00 -1.32547736e+00 4.66016829e-01
2.35109344e-01 -1.08554073e-01 1.26027334e+00 3.05314720e-01
2.78214663e-01 1.23994434e+00 1.59572676e-01 6.64708376e-01
-1.53934765e+00 -5.97535610e-01 4.54655468e-01 -3.67013216e-02
-8.38235497e-01 -1.85114428e-01 3.50711524e-01 3.48671004e-02
4.98066604e-01 4.88964856e-01 8.41337562e-01 6.93760157e-01
-1.99438035e-01 1.08047104e+00 1.20351064e+00 -6.19672954e-01
6.16786361e-01 1.62677124e-01 7.38110468e-02 1.88596129e-01
5.12760818e-01 3.19319844e-01 -4.04920429e-01 -4.80969340e-01
7.47427225e-01 3.55382822e-02 -1.75507382e-01 -4.49191481e-01
-6.76679134e-01 1.04522455e+00 1.36141762e-01 -2.97038019e-01
-6.95363164e-01 8.24991524e-01 4.01077941e-02 2.31878743e-01
4.32521939e-01 2.50579953e-01 -4.25270379e-01 -4.31834131e-01
-1.00206006e+00 5.90966403e-01 7.19911754e-01 1.07221270e+00
2.88663983e-01 -4.15742069e-01 -7.82334149e-01 6.15039766e-01
6.91686794e-02 5.42680442e-01 -7.58234039e-02 -1.37449574e+00
8.96577656e-01 -9.57433358e-02 1.24635196e+00 -2.57096946e-01
-1.43010886e-02 -5.57157159e-01 -1.37178317e-01 3.92477632e-01
7.65760303e-01 -5.99993289e-01 -5.61039984e-01 1.75821340e+00
2.85805404e-01 -2.89808154e-01 -1.92533627e-01 8.62671971e-01
-3.57517272e-01 4.29555118e-01 -2.04429388e-01 -7.83934295e-01
9.15770531e-01 -8.41529906e-01 -4.98393983e-01 -3.24066639e-01
1.17716283e-01 -3.79851341e-01 6.87828958e-01 6.03707373e-01
-1.64173484e+00 4.46702331e-01 -8.28157067e-01 8.40133846e-01
1.85036212e-01 -1.90186858e-01 8.74999106e-01 1.20387089e+00
-4.39132959e-01 5.77941954e-01 -7.07538843e-01 4.40109611e-01
6.32808089e-01 3.09781313e-01 3.64268929e-01 -1.99399889e-02
-5.81307471e-01 6.81578457e-01 2.51181692e-01 -9.45928097e-02
-8.90162051e-01 -6.24926627e-01 -2.89136857e-01 2.64416665e-01
1.00842619e+00 -4.59001482e-01 1.90246165e+00 -9.24733460e-01
-1.78480530e+00 4.12151128e-01 5.98398857e-02 -9.54526186e-01
9.55186248e-01 -1.17571257e-01 3.33585411e-01 -5.54435067e-02
1.50195971e-01 1.10372923e-01 6.23027861e-01 -1.07530892e+00
-1.17221105e+00 -3.40738147e-01 3.20037127e-01 1.64264828e-01
-1.46669522e-02 8.64243656e-02 -1.25042409e-01 -4.44228262e-01
-2.06762597e-01 -8.76120389e-01 -5.86138129e-01 -5.10683060e-01
-4.26077098e-01 -1.57377675e-01 -1.83578059e-01 -1.09704487e-01
1.29320467e+00 -1.71683717e+00 -8.43314081e-02 4.32753652e-01
-3.02903742e-01 -1.84899867e-01 5.20128831e-02 3.24119747e-01
3.08491409e-01 2.30426475e-01 3.46874446e-01 -2.13111043e-01
2.71427691e-01 2.57769283e-02 -4.12116468e-01 5.66770554e-01
-4.91285771e-01 7.06217289e-01 -7.57425964e-01 -1.85672984e-01
-1.84772432e-01 -7.12964296e-01 -6.12446070e-01 2.33642027e-01
-6.16150081e-01 1.51578174e-03 -5.52980900e-01 5.16840994e-01
6.22455359e-01 -3.12665731e-01 1.85229197e-01 6.33641541e-01
-6.38570562e-02 3.28203924e-02 -1.31078684e+00 1.08690035e+00
-2.87877411e-01 7.81020224e-02 2.67747343e-01 -1.28486860e+00
3.86587918e-01 -6.49097562e-02 6.20592654e-01 -4.76306826e-01
3.52180004e-01 2.12537169e-01 -1.88767970e-01 -4.92505468e-02
3.85301709e-01 -4.78746027e-01 -2.03494281e-01 8.00370991e-01
-3.76178622e-01 8.81898701e-02 3.87042135e-01 1.71582162e-01
9.20015872e-01 -1.99611202e-01 3.48943859e-01 -1.79961175e-01
-1.15224928e-01 -5.06936014e-02 4.39719707e-01 1.40780067e+00
-2.91833073e-01 5.53219803e-02 1.01732159e+00 -2.96616167e-01
-7.42600620e-01 -9.67111945e-01 1.65386885e-01 1.35389042e+00
3.11083704e-01 3.95741642e-01 -4.99145508e-01 -6.47433460e-01
6.61313832e-01 1.05465794e+00 -9.21693385e-01 3.44939053e-01
-1.09662004e-01 -6.74285471e-01 -7.33661577e-02 4.48000491e-01
2.29878023e-01 -5.82373023e-01 -9.79571462e-01 5.95859885e-01
-1.37426093e-01 -8.23627532e-01 -7.05013812e-01 1.96575254e-01
-6.17630959e-01 -9.60639596e-01 -9.58808184e-01 1.54299378e-01
2.69805133e-01 2.93291152e-01 1.06130302e+00 -5.45318544e-01
-6.82465732e-02 3.78127754e-01 -2.80193359e-01 -8.86346161e-01
4.81791049e-02 -1.74833164e-01 -2.35532433e-01 -7.64490664e-02
6.11919872e-02 -5.87159358e-02 -9.09944057e-01 3.11683834e-01
-4.94698495e-01 -2.56973535e-01 4.01198775e-01 8.90035152e-01
7.87851155e-01 -6.09353781e-02 8.30635428e-01 -6.79833531e-01
1.05487454e+00 -4.27996397e-01 -1.28520167e+00 5.23537636e-01
-6.28997743e-01 2.07588196e-01 3.90235126e-01 -6.56939566e-01
-9.60215628e-01 -2.57119924e-01 4.52264369e-01 -2.39552662e-01
2.47271001e-01 3.22015464e-01 3.45428109e-01 1.14322364e-01
4.88387018e-01 5.74476346e-02 -1.10855289e-01 -2.44145140e-01
4.02855635e-01 4.59696054e-01 1.84672415e-01 -1.16064799e+00
-1.90873537e-02 3.93997639e-01 1.76050529e-01 2.51672603e-02
-1.32438385e+00 -3.55910480e-01 4.62334812e-01 -1.90011457e-01
-6.72262236e-02 -5.04064620e-01 -1.66521060e+00 -2.01690674e-01
-8.02335203e-01 -3.89786959e-01 -6.50157154e-01 7.25019276e-01
-1.25961912e+00 2.25075148e-02 -3.41266006e-01 -1.84430039e+00
-2.94997722e-01 -8.19356620e-01 5.04657984e-01 4.99522686e-01
1.09887794e-01 -3.33221257e-01 3.51800919e-02 3.33203107e-01
3.33857030e-01 3.88525158e-01 6.63999319e-01 -3.22647214e-01
-5.51141083e-01 -2.97178686e-01 -2.06541345e-01 9.54631940e-02
-1.97526038e-01 -2.10555226e-01 -1.34371459e-01 -5.97351432e-01
-2.19815359e-01 -5.71781516e-01 7.23954976e-01 1.14727128e+00
1.42372513e+00 -7.11432874e-01 -4.95480806e-01 2.55602837e-01
1.47505414e+00 6.25707984e-01 1.99318662e-01 7.46237218e-01
-6.24323785e-01 1.98424071e-01 1.12161839e+00 1.24641669e+00
-5.65123409e-02 4.87643659e-01 7.76638687e-01 5.23912072e-01
7.64207482e-01 -1.03409603e-01 -5.66328540e-02 -6.98201358e-01
-2.81450808e-01 -6.36908054e-01 -3.98258328e-01 7.53088236e-01
-2.28631282e+00 -1.18085968e+00 5.55905700e-01 2.67575979e+00
9.76614654e-01 5.29271364e-01 9.66444671e-01 -1.81780495e-02
7.21580923e-01 -1.68859586e-01 -1.12210560e+00 -6.88617289e-01
2.38098890e-01 2.09246233e-01 1.30954921e+00 4.26304162e-01
-7.21023560e-01 5.07380247e-01 7.21013689e+00 1.17504632e+00
-5.37518561e-01 9.77864861e-03 1.15377140e+00 -1.19357073e+00
-7.47903511e-02 -1.49747223e-01 -1.02065694e+00 6.90864980e-01
8.69537711e-01 -6.00317836e-01 9.81881857e-01 1.10708737e+00
1.90199628e-01 -5.53931117e-01 -1.07878673e+00 8.22752059e-01
-5.88248968e-01 -1.52812493e+00 -4.95613545e-01 3.44503105e-01
8.73256087e-01 -2.24468544e-01 2.36348256e-01 2.58366674e-01
1.21814728e+00 -9.49385166e-01 1.07102025e+00 4.73924220e-01
7.67300665e-01 -1.46630156e+00 6.80907011e-01 6.07644379e-01
-6.56211078e-01 -5.02682567e-01 -3.13658953e-01 -1.23868726e-01
2.56115764e-01 4.89240110e-01 -6.16214454e-01 2.75006205e-01
6.85744226e-01 -2.72488683e-01 6.04340136e-01 1.29824531e+00
-2.08774079e-02 5.52184463e-01 -6.48333430e-01 -7.32154071e-01
6.50254369e-01 -3.75058681e-01 1.77563354e-01 9.23080802e-01
4.25394505e-01 4.11158949e-01 1.02333419e-01 7.90805697e-01
-2.16426238e-01 1.31168813e-01 5.15571460e-02 -2.96899099e-02
6.92393780e-01 7.82736063e-01 -6.31319880e-01 -2.59599507e-01
-4.37789336e-02 4.10322696e-01 5.97779572e-01 2.41086632e-01
-1.11828566e+00 -3.12718123e-01 7.37236202e-01 -1.93175808e-01
6.62336349e-01 1.82207271e-01 -3.79534841e-01 -6.00012779e-01
1.34706169e-01 -5.77470779e-01 7.55832076e-01 -1.96836978e-01
-1.29685795e+00 1.07785694e-01 2.66673416e-01 -8.19558680e-01
-4.35731471e-01 -3.93432528e-01 -3.62034231e-01 9.42342579e-01
-1.39426410e+00 -4.83525157e-01 3.70969564e-01 3.41879278e-01
3.92230511e-01 -1.75809171e-02 4.75249469e-01 -2.94289112e-01
-5.44993639e-01 8.04261684e-01 7.91229606e-01 -2.45313659e-01
3.80735137e-02 -1.26156008e+00 -2.52031773e-01 4.74383771e-01
-3.22077811e-01 2.66672939e-01 8.48083138e-01 -2.42486119e-01
-1.18540323e+00 -5.40650904e-01 -2.28640288e-01 -4.89489920e-03
7.75100529e-01 2.75293142e-01 1.85288876e-01 7.37845838e-01
-2.93620043e-02 6.03392906e-02 7.89310157e-01 3.51304591e-01
-1.64323375e-01 -3.92285436e-01 -1.52286994e+00 4.32164609e-01
7.50307798e-01 3.61981750e-01 -2.52093989e-02 3.53667527e-01
5.16655445e-01 -4.63222980e-01 -6.38788998e-01 1.33713827e-01
1.02764904e+00 -1.10509062e+00 7.76355267e-01 -1.10011077e+00
1.64089024e-01 4.48162794e-01 -1.62274882e-01 -1.64579463e+00
-3.17806691e-01 -1.15448272e+00 -3.22675496e-01 7.98450232e-01
7.15175152e-01 -7.85037398e-01 1.26552975e+00 1.00518715e+00
5.64982951e-01 -1.12604010e+00 -1.31323588e+00 -1.19217253e+00
3.05607051e-01 -4.31201011e-01 8.73802960e-01 1.64312810e-01
4.04201716e-01 -2.24831834e-01 -6.71268702e-01 3.87930451e-03
1.01714361e+00 7.72485375e-01 5.14381468e-01 -6.93516791e-01
-7.93773592e-01 -7.99343407e-01 3.76509845e-01 -1.37570977e+00
-2.12340519e-01 -5.43839782e-02 2.97581088e-02 -1.34344137e+00
5.40313303e-01 -7.34541237e-01 -5.78469217e-01 2.11010203e-01
5.44401410e-04 -2.12484494e-01 3.07841122e-01 -1.56327978e-01
-9.51093197e-01 1.94939181e-01 1.19984794e+00 -1.87894538e-01
-3.84778261e-01 7.79641688e-01 -1.10754573e+00 3.98689270e-01
9.02646840e-01 -7.22626746e-01 -1.44488275e-01 -2.03597665e-01
3.73034775e-01 1.06711102e+00 -2.31296852e-01 -3.23055297e-01
6.94023445e-02 -1.12860680e+00 1.90760717e-01 -9.24256623e-01
2.92212963e-01 -7.79103577e-01 8.57231468e-02 5.57238519e-01
-7.21830487e-01 -2.67697126e-01 -5.38852774e-02 9.59755540e-01
3.83033365e-01 -5.93617976e-01 8.64870548e-01 -4.13591146e-01
3.17448050e-01 3.11905771e-01 -1.87654123e-01 2.03990024e-02
1.44099343e+00 2.25539461e-01 -5.43180943e-01 -8.79760683e-01
-5.56546986e-01 7.00466573e-01 -4.49187867e-02 -2.08696425e-01
2.80168831e-01 -1.09516728e+00 -6.49563193e-01 -2.86885262e-01
-1.40714973e-01 -2.71480054e-01 8.65374226e-03 5.26379049e-01
-1.50408700e-01 5.29548466e-01 6.17627054e-02 -9.06475186e-02
-9.93724048e-01 8.32501471e-01 4.61697459e-01 -7.43131638e-01
1.25700071e-01 9.86260533e-01 -4.69706476e-01 3.70739281e-01
5.47578335e-01 -3.07612151e-01 2.79383063e-01 -1.25606731e-01
8.71974468e-01 8.83961141e-01 -3.00375909e-01 1.77099839e-01
-1.15936868e-01 9.92346331e-02 -1.54242635e-01 -7.01513827e-01
1.32522666e+00 -7.11788982e-02 2.43191779e-01 -6.33542985e-02
5.03200233e-01 2.41109580e-02 -1.48339427e+00 -2.76865304e-01
5.53617545e-04 -1.08461690e+00 7.99470022e-02 -1.11721349e+00
-9.86195385e-01 3.26825678e-01 3.59193116e-01 9.66954708e-01
9.05488968e-01 2.67363526e-02 5.13521850e-01 2.80784458e-01
8.55743408e-01 -1.30102623e+00 -1.01522610e-01 3.86021696e-02
6.43395126e-01 -1.00423002e+00 3.17896217e-01 -1.34335179e-02
-7.65980840e-01 7.83770740e-01 2.45820910e-01 -2.94957578e-01
3.98064971e-01 2.87847847e-01 -4.12294894e-01 3.02324504e-01
-8.27232599e-01 -4.76390570e-01 -1.90698072e-01 3.46942693e-01
-5.81730902e-02 6.90511286e-01 -6.53319776e-01 8.24120164e-01
-2.30920926e-01 1.15936764e-01 3.72869194e-01 1.00636518e+00
-5.89278996e-01 -1.04879820e+00 -6.45229936e-01 8.07678759e-01
-1.05090523e+00 3.13104570e-01 -6.85140416e-02 5.19772470e-01
-4.47401017e-01 1.33574629e+00 1.23032182e-02 2.68498302e-01
3.01518530e-01 -4.20258224e-01 8.53267372e-01 -2.22406432e-01
-1.78332537e-01 3.16336304e-01 2.40375131e-01 -4.58609909e-01
-3.41499031e-01 -5.48367441e-01 -6.34133935e-01 -6.66532397e-01
-6.98842824e-01 5.99540114e-01 7.43469298e-01 7.56852269e-01
1.33743975e-02 2.98983961e-01 1.08572555e+00 -6.54219329e-01
-1.45653284e+00 -8.72092307e-01 -1.01699376e+00 6.80127591e-02
3.86100024e-01 -6.91873193e-01 -3.59048516e-01 -7.57730007e-01] | [4.500638484954834, 3.2593393325805664] |
52689a52-0dd2-4e48-a154-39615b6a6d0a | automatic-classification-of-variable-stars-in | 1310.7868 | null | http://arxiv.org/abs/1310.7868v1 | http://arxiv.org/pdf/1310.7868v1.pdf | Automatic Classification of Variable Stars in Catalogs with missing data | We present an automatic classification method for astronomical catalogs with
missing data. We use Bayesian networks, a probabilistic graphical model, that
allows us to perform inference to pre- dict missing values given observed data
and dependency relationships between variables. To learn a Bayesian network
from incomplete data, we use an iterative algorithm that utilises sampling
methods and expectation maximization to estimate the distributions and
probabilistic dependencies of variables from data with missing values. To test
our model we use three catalogs with missing data (SAGE, 2MASS and UBVI) and
one complete catalog (MACHO). We examine how classification accuracy changes
when information from missing data catalogs is included, how our method
compares to traditional missing data approaches and at what computational cost.
Integrating these catalogs with missing data we find that classification of
variable objects improves by few percent and by 15% for quasar detection while
keeping the computational cost the same. | ['Karim Pichara', 'Pavlos Protopapas'] | 2013-10-29 | null | null | null | null | ['classification-of-variable-stars'] | ['miscellaneous'] | [-1.34643570e-01 -1.65697888e-01 -1.89368993e-01 -7.54118383e-01
-5.85316598e-01 -6.61541700e-01 7.48401105e-01 -1.92743987e-01
-2.40090087e-01 1.37152827e+00 -3.68435904e-02 -5.32669902e-01
-6.83653116e-01 -7.74786770e-01 -3.24177772e-01 -6.58716261e-01
-1.55138016e-01 1.18280494e+00 3.42291564e-01 2.70994186e-01
3.45781267e-01 6.70548677e-01 -1.52737558e+00 -7.63827637e-02
4.78964329e-01 7.77743459e-01 3.12132686e-01 5.34770250e-01
-1.47552282e-01 1.12705803e+00 -6.00182831e-01 -1.18363172e-01
2.33611763e-01 -2.46648669e-01 -7.42224276e-01 -1.34705482e-02
3.24087679e-01 -2.10447237e-01 -4.78420228e-01 9.34432030e-01
1.34883821e-02 -1.09196745e-01 1.03557861e+00 -1.46593964e+00
-1.70711547e-01 5.04557788e-01 -4.70106184e-01 2.10944414e-01
2.59875171e-02 1.44297078e-01 1.06017184e+00 -7.43616104e-01
6.97782516e-01 1.32635891e+00 8.30003917e-01 -2.61304528e-01
-1.62192702e+00 -8.47908318e-01 -3.97540480e-01 1.45738989e-01
-1.67036629e+00 -3.85175288e-01 6.66361272e-01 -8.62649739e-01
8.18099022e-01 2.45631114e-01 3.87945741e-01 6.55909479e-01
2.23484948e-01 3.80051322e-02 1.25226474e+00 -4.30619180e-01
4.21986073e-01 2.42103159e-01 5.29902279e-01 3.59086186e-01
8.43128204e-01 4.81439322e-01 -6.57496274e-01 -7.43898511e-01
7.20746219e-01 -1.47823453e-01 2.25783169e-01 -3.69321376e-01
-1.13949168e+00 1.03829646e+00 -2.91314512e-01 -3.96470800e-02
-2.94721037e-01 1.15382433e-01 -1.88214615e-01 5.16908765e-01
5.13268232e-01 5.03330350e-01 -8.45641434e-01 1.44203737e-01
-1.21049201e+00 5.34360707e-01 1.17761195e+00 9.18987155e-01
1.03840387e+00 2.63488978e-01 3.84364933e-01 7.28289723e-01
6.01812422e-01 5.69511890e-01 -1.01283323e-02 -1.22183478e+00
3.27527374e-02 3.79423946e-01 6.14002049e-01 -7.67514288e-01
-4.85999763e-01 -3.54996860e-01 -4.68056709e-01 6.29346669e-01
6.27685070e-01 -1.47533730e-01 -8.89766097e-01 1.33048344e+00
1.05122752e-01 -1.72348365e-01 -1.33339122e-01 5.06904900e-01
6.55564964e-01 2.12572798e-01 -1.93779588e-01 -4.49616224e-01
1.02908289e+00 -6.02115802e-02 -7.71407843e-01 -6.78633675e-02
3.68176550e-01 -7.58401752e-01 3.15991759e-01 8.94032001e-01
-5.37803352e-01 -3.79013151e-01 -1.12822628e+00 2.81558752e-01
-1.79187775e-01 -9.20837373e-02 9.15911257e-01 6.70469701e-01
-7.10608780e-01 7.56450534e-01 -1.06986165e+00 1.10468261e-01
2.33967081e-02 5.53731620e-01 -3.80043834e-01 5.08861654e-02
-7.51119733e-01 9.19440329e-01 5.68390250e-01 -3.78847122e-01
-9.14001107e-01 -5.89871049e-01 -6.01131558e-01 4.56749350e-02
3.62199992e-01 -5.88135719e-01 1.24732208e+00 -4.37308669e-01
-8.29875290e-01 4.65703845e-01 -3.53094399e-01 -4.32719857e-01
2.01041624e-01 2.03876093e-01 -4.76769805e-01 -7.20302090e-02
-1.62501726e-02 2.72418112e-01 5.98908484e-01 -1.36065257e+00
-5.91112912e-01 -6.02211118e-01 -6.80759430e-01 -4.22248721e-01
4.25700247e-01 1.35168180e-01 2.92202495e-02 -5.50577700e-01
8.10518205e-01 -7.19051659e-01 -7.33848587e-02 -3.40551794e-01
-2.61560947e-01 -4.64882135e-01 8.44633639e-01 -9.04700339e-01
6.80847943e-01 -2.01307058e+00 -1.08893834e-01 5.35772264e-01
3.61693740e-01 -7.43266404e-01 2.15183318e-01 3.33029151e-01
-1.81512490e-01 1.26641482e-01 -3.92657548e-01 -2.33374879e-01
-4.30265069e-02 7.59141386e-01 -4.74177636e-02 6.88117146e-01
1.54372260e-01 1.59463622e-02 -4.40266550e-01 -4.14761275e-01
3.24668974e-01 2.56081279e-02 -3.81895244e-01 2.01302707e-01
-4.35125291e-01 4.56622332e-01 -6.99042454e-02 7.31906593e-01
1.04151583e+00 -6.08389825e-02 4.80349392e-01 2.94250399e-01
-4.59244668e-01 4.51197803e-01 -1.62715852e+00 1.28665066e+00
-1.36480778e-02 7.41059005e-01 2.39043564e-01 -7.91069329e-01
1.53151500e+00 1.77893236e-01 4.52051520e-01 -3.55204284e-01
-7.74759352e-02 1.80622295e-01 8.02194774e-02 -3.76603514e-01
6.14208221e-01 -3.04992080e-01 2.17001196e-02 2.82521546e-01
5.43709040e-01 -4.19424921e-01 -6.04060991e-03 3.19698989e-01
1.35699368e+00 5.44982255e-02 2.27607012e-01 -3.55590194e-01
-1.03851981e-01 3.31985682e-01 9.87815499e-01 1.21594620e+00
2.47076005e-01 4.55686450e-01 8.19097519e-01 -4.18983489e-01
-1.21925688e+00 -1.17341673e+00 -4.74530637e-01 6.37939095e-01
-3.64535451e-01 -1.70245886e-01 2.77030200e-01 -3.08505267e-01
2.79446632e-01 1.14067769e+00 -2.92568922e-01 2.18905166e-01
5.68081886e-02 -1.01679492e+00 1.92676172e-01 1.60258085e-01
1.37904719e-01 -7.51129568e-01 -1.46833435e-01 8.74647349e-02
1.25316143e-01 -8.63563478e-01 5.61624765e-01 6.06824577e-01
-1.07554841e+00 -1.18498361e+00 6.40017465e-02 -4.39262480e-01
4.00967926e-01 -8.91796201e-02 1.38209665e+00 8.51581767e-02
-3.45086664e-01 1.28214911e-01 -3.49361956e-01 -4.53342915e-01
-4.37270880e-01 -1.83914602e-01 1.31571740e-01 -5.03830910e-01
6.06986046e-01 -7.04994500e-01 1.06157780e-01 4.42020059e-01
-6.36461139e-01 -2.85428852e-01 5.84155202e-01 1.11203611e+00
4.04347867e-01 6.18423522e-01 4.16631639e-01 -8.21422935e-01
-9.93503481e-02 -8.92680407e-01 -1.51065588e+00 2.48627327e-02
-6.56032860e-01 3.95656437e-01 -1.15040921e-01 -8.54532942e-02
-1.45280766e+00 5.78709483e-01 7.82861412e-02 -2.05609843e-01
-4.60759968e-01 7.05233753e-01 -2.47425035e-01 -1.31992579e-01
5.97163439e-01 -1.90357462e-01 1.92281350e-01 -1.05700004e+00
2.12395806e-02 8.76445293e-01 9.33762610e-01 -5.10142565e-01
7.32476652e-01 4.25219119e-01 3.37156594e-01 -6.82806432e-01
-6.51362240e-01 -7.13936329e-01 -1.12010896e+00 -6.62691673e-05
4.48610127e-01 -9.68873024e-01 -5.37710369e-01 2.26874322e-01
-1.10596550e+00 2.11052243e-02 -1.05989069e-01 1.20169830e+00
-3.40897352e-01 1.28305092e-01 -2.33319044e-01 -1.18553424e+00
3.37298483e-01 -8.23905826e-01 5.64275324e-01 -2.03816071e-01
-2.47748613e-01 -8.01368415e-01 3.77777427e-01 1.88478962e-01
1.09543644e-01 1.70076445e-01 9.76373136e-01 -9.77733970e-01
-7.46070504e-01 -2.26651922e-01 -3.04840028e-01 1.49074584e-01
-1.02375513e-02 -8.53786338e-03 -8.22094560e-01 -2.54381597e-01
2.24130660e-01 -9.95955914e-02 9.60499227e-01 4.40728366e-01
1.09839964e+00 -1.87621012e-01 -3.82599205e-01 2.13213205e-01
1.54593992e+00 1.93845555e-01 6.46337748e-01 5.80364466e-02
1.74494058e-01 8.33571792e-01 4.77832347e-01 7.53414750e-01
1.40275374e-01 4.13998306e-01 4.72955942e-01 3.57182890e-01
1.16853910e-02 -6.54224753e-02 -1.27555996e-01 6.29720092e-01
3.03156257e-01 1.15273468e-01 -1.07143688e+00 7.32801914e-01
-1.63293326e+00 -1.11678016e+00 -8.63996565e-01 2.43133807e+00
7.36210287e-01 1.78490788e-01 2.40445435e-02 6.96412995e-02
4.58075076e-01 -2.78646797e-01 -3.35639834e-01 3.06779385e-01
-8.06503221e-02 2.21376836e-01 8.88449311e-01 7.38911092e-01
-8.34151149e-01 4.25827622e-01 8.23505116e+00 5.18119454e-01
-2.08052129e-01 1.77517653e-01 1.91484317e-01 -2.00973362e-01
-3.00311655e-01 7.92270243e-01 -8.06139290e-01 4.56899136e-01
1.12361622e+00 3.83115053e-01 3.97525966e-01 6.14875972e-01
2.79619277e-01 -7.76193261e-01 -9.25263941e-01 8.54973733e-01
-8.77444521e-02 -1.27259982e+00 -4.65857834e-01 3.84241641e-01
7.04617798e-01 3.37271392e-01 -6.07520700e-01 2.50201285e-01
1.24044549e+00 -8.72198343e-01 3.98907661e-01 1.02126980e+00
3.71582717e-01 -8.50816071e-01 1.04874194e+00 3.82570207e-01
-5.42715251e-01 8.75442550e-02 -4.86836374e-01 -6.85031474e-01
-1.29352257e-01 1.07703805e+00 -1.23736453e+00 5.57186306e-01
7.35330820e-01 3.43749523e-01 -8.18471014e-01 1.38131607e+00
-2.12448210e-01 1.07058549e+00 -5.90085387e-01 1.47298142e-01
-3.80853266e-01 -3.28065306e-01 6.14551127e-01 7.69530177e-01
3.65596086e-01 1.64088298e-04 2.33851641e-01 1.13219798e+00
3.41463298e-01 -6.71608627e-01 -6.59745514e-01 3.58825356e-01
9.84899879e-01 1.02054751e+00 -6.48606837e-01 -4.18609858e-01
-5.42760015e-01 3.21395069e-01 -7.60959759e-02 1.98793903e-01
-1.29653558e-01 -4.73408580e-01 3.80997002e-01 -1.47283822e-01
4.55959499e-01 -6.60517514e-01 -7.81506419e-01 -8.58949959e-01
-3.01254809e-01 -6.03258729e-01 5.96211493e-01 -1.05900109e+00
-1.59851611e+00 -6.50243089e-02 4.17814970e-01 -8.17185223e-01
-5.92572927e-01 -7.52770841e-01 -2.69733310e-01 1.03347111e+00
-7.81834066e-01 -8.10828447e-01 -1.27170607e-01 2.56527781e-01
1.54457539e-01 -6.38828099e-01 5.86390257e-01 -7.73527175e-02
-1.87555835e-01 -1.27883390e-01 4.92105842e-01 8.60302448e-02
6.06089711e-01 -1.44361329e+00 -1.06409434e-02 5.16925871e-01
1.86058000e-01 4.51275498e-01 1.09877348e+00 -1.24867392e+00
-1.16248512e+00 -5.77173412e-01 9.26696301e-01 -7.21244872e-01
8.96916866e-01 -3.29622060e-01 -1.03564167e+00 9.22471583e-01
1.77437797e-01 -1.77326813e-01 6.47808909e-01 7.15597749e-01
-4.38045353e-01 1.75446823e-01 -1.26530206e+00 -1.95255473e-01
5.13738871e-01 -3.62902641e-01 -1.08723474e+00 3.44547838e-01
5.53416610e-01 2.40044445e-01 -1.04864454e+00 2.96225488e-01
5.82930863e-01 -8.35062444e-01 6.60106540e-01 -5.21069050e-01
-3.11719060e-01 -6.17941678e-01 -4.63944405e-01 -1.20947993e+00
-3.94965500e-01 -2.16422424e-01 3.61945182e-01 1.30134106e+00
3.44637424e-01 -6.27999783e-01 6.71336293e-01 6.50867105e-01
2.26381868e-02 4.63927299e-01 -1.27396953e+00 -1.06834853e+00
1.00483499e-01 -7.30717003e-01 6.03569269e-01 1.18255401e+00
-2.74333924e-01 3.24311852e-01 -6.07099533e-01 5.49696028e-01
1.15619218e+00 -9.44078993e-03 7.80606627e-01 -2.09041429e+00
-5.32284081e-01 3.49742360e-02 -5.06322861e-01 -3.47745329e-01
1.52234212e-01 -6.93960249e-01 2.73946114e-03 -1.17821562e+00
4.98126596e-01 -5.55234194e-01 1.79544184e-02 6.21370554e-01
4.35928166e-01 -6.00552484e-02 -2.03433231e-01 5.29803276e-01
-3.35656106e-01 2.87605673e-01 3.95291746e-01 2.32385304e-02
-1.10546157e-01 9.31352656e-03 -2.25386187e-01 8.14063668e-01
8.22425723e-01 -1.10677123e+00 1.47543147e-01 -1.05743363e-01
4.00067270e-01 5.10689855e-01 8.42596412e-01 -9.09408092e-01
2.59616375e-01 -2.22411990e-01 9.38921273e-01 -1.47283566e+00
3.20375949e-01 -7.94010401e-01 5.86667538e-01 3.13288242e-01
-4.38208543e-02 -3.96633558e-02 -3.44863459e-02 5.53005397e-01
-2.36728713e-01 -8.73187423e-01 4.57091600e-01 -3.15833002e-01
-5.77652335e-01 -3.09524864e-01 -8.00164819e-01 -4.29789305e-01
4.58843470e-01 4.68600780e-01 -1.29654780e-01 -4.59695637e-01
-1.16467273e+00 3.08698624e-01 3.62226784e-01 3.29594128e-02
3.51213694e-01 -1.16357899e+00 -9.22196031e-01 3.91437590e-01
-8.59648213e-02 -2.95582533e-01 -2.21735016e-02 7.01567948e-01
-2.81000495e-01 3.69418144e-01 -1.98751375e-01 -6.16933942e-01
-1.28960180e+00 4.03500944e-01 1.81582943e-01 2.38814428e-02
-8.11164379e-02 4.04394507e-01 -4.98109460e-01 -7.83303082e-01
7.31255338e-02 1.99363776e-03 -7.35271163e-03 8.88054594e-02
3.77539605e-01 6.33031726e-01 1.22712411e-01 -2.33122811e-01
-1.82323545e-01 -1.39546975e-01 7.99073875e-02 -5.79382956e-01
1.35720479e+00 -1.08788647e-01 -5.28825939e-01 8.23499918e-01
7.14286685e-01 -4.59745526e-03 -1.10307217e+00 -4.68930244e-01
4.63964224e-01 -8.95475686e-01 3.53936970e-01 -9.85701561e-01
-6.26484454e-01 5.47568917e-01 5.72963357e-01 3.25468272e-01
4.93053675e-01 4.35751319e-01 -3.84548038e-01 4.37268168e-01
6.34446442e-01 -9.04017508e-01 -3.93591911e-01 4.67171103e-01
8.41453791e-01 -1.28881836e+00 4.92402732e-01 -1.68627545e-01
-2.83734053e-01 1.04421663e+00 4.26377177e-01 1.94436405e-02
8.42087746e-01 5.04275978e-01 -3.87380540e-01 -5.80230832e-01
-1.02508020e+00 -2.38024637e-01 -7.75780752e-02 7.05177069e-01
1.48400754e-01 2.79175699e-01 -3.57822806e-01 5.05446017e-01
-4.88056153e-01 -1.48472721e-02 8.27459335e-01 8.82014811e-01
-7.14057565e-01 -1.15514088e+00 -1.15829647e+00 1.10674572e+00
-2.75713325e-01 -5.68468682e-03 -5.73794723e-01 1.09117806e+00
7.82946572e-02 1.25822520e+00 5.02469718e-01 -1.44243360e-01
-2.25670204e-01 3.51019084e-01 2.75546908e-01 -5.40036678e-01
1.27946794e-01 2.94913262e-01 4.65627939e-01 4.14010622e-02
-3.88722032e-01 -1.24132931e+00 -9.25527811e-01 -2.57601112e-01
-6.95280194e-01 3.28138679e-01 8.15013409e-01 1.06021416e+00
-6.35574758e-02 4.35142040e-01 5.95267475e-01 -6.14808559e-01
-8.31140339e-01 -1.35588038e+00 -1.05193794e+00 -8.36382732e-02
3.30156267e-01 -1.03316665e+00 -7.18979120e-01 -7.10621253e-02] | [7.305171489715576, 3.9191501140594482] |
add8eac0-e91f-4144-ac92-74f82c17bd91 | cia-net-robust-nuclei-instance-segmentation | 1903.05358 | null | http://arxiv.org/abs/1903.05358v1 | http://arxiv.org/pdf/1903.05358v1.pdf | CIA-Net: Robust Nuclei Instance Segmentation with Contour-aware Information Aggregation | Accurate segmenting nuclei instances is a crucial step in computer-aided
image analysis to extract rich features for cellular estimation and following
diagnosis as well as treatment. While it still remains challenging because the
wide existence of nuclei clusters, along with the large morphological variances
among different organs make nuclei instance segmentation susceptible to
over-/under-segmentation. Additionally, the inevitably subjective annotating
and mislabeling prevent the network learning from reliable samples and
eventually reduce the generalization capability for robustly segmenting unseen
organ nuclei. To address these issues, we propose a novel deep neural network,
namely Contour-aware Informative Aggregation Network (CIA-Net) with multi-level
information aggregation module between two task-specific decoders. Rather than
independent decoders, it leverages the merit of spatial and texture
dependencies between nuclei and contour by bi-directionally aggregating
task-specific features. Furthermore, we proposed a novel smooth truncated loss
that modulates losses to reduce the perturbation from outliers. Consequently,
the network can focus on learning from reliable and informative samples, which
inherently improves the generalization capability. Experiments on the 2018
MICCAI challenge of Multi-Organ-Nuclei-Segmentation validated the effectiveness
of our proposed method, surpassing all the other 35 competitive teams by a
significant margin. | ['Pheng-Ann Heng', 'Efstratios Tsougenis', 'Yanning Zhou', 'Omer Fahri Onder', 'Qi Dou', 'Hao Chen'] | 2019-03-13 | null | null | null | null | ['multi-tissue-nucleus-segmentation'] | ['medical'] | [ 2.16703445e-01 2.76141584e-01 -1.71805188e-01 -3.99179667e-01
-1.12378490e+00 -5.56341529e-01 1.50799349e-01 4.14814174e-01
-5.89049578e-01 7.50379384e-01 -4.16808203e-03 4.42332551e-02
6.27074465e-02 -4.40544367e-01 -7.56227672e-01 -1.21892226e+00
2.19024494e-01 5.17035365e-01 2.98495531e-01 2.64487773e-01
-9.53672919e-03 4.52225149e-01 -1.15707266e+00 1.56446576e-01
1.24322307e+00 1.13221455e+00 9.91726071e-02 5.17751932e-01
1.69077255e-02 4.71716255e-01 -3.56177390e-01 -5.56752980e-01
9.41781998e-02 -3.31339896e-01 -5.59776366e-01 1.96942165e-01
5.34702361e-01 -1.43498525e-01 -2.82238089e-02 1.30001414e+00
7.21925318e-01 -1.72708541e-01 8.71677458e-01 -9.44931865e-01
-5.70153356e-01 6.12455845e-01 -7.25733459e-01 1.31870359e-01
-3.52804035e-01 3.72662067e-01 9.03359532e-01 -8.41768444e-01
4.55067128e-01 8.84305060e-01 7.94969440e-01 5.87758303e-01
-1.13215673e+00 -5.18342018e-01 1.92810576e-02 -1.43340647e-01
-1.60367644e+00 -4.21057612e-01 5.13463318e-01 -4.44882274e-01
3.83633763e-01 2.19551474e-01 5.71977437e-01 7.19016314e-01
1.55543134e-01 1.15451765e+00 7.54044056e-01 6.77762553e-02
1.07296765e-01 -1.81066729e-02 5.53085431e-02 7.71220267e-01
5.73095739e-01 -4.93055850e-01 -1.05416916e-01 1.10634699e-01
6.69316113e-01 6.58272803e-02 -4.63440061e-01 -3.21144819e-01
-1.38380039e+00 5.77156663e-01 6.65738702e-01 1.80951044e-01
-3.52742523e-01 7.97321573e-02 5.44566512e-01 -2.11002931e-01
4.85611320e-01 2.73509473e-01 -3.85009199e-01 1.78835303e-01
-1.18275213e+00 -4.15877774e-02 3.72219741e-01 7.11271882e-01
6.18543565e-01 -4.57915887e-02 -5.36304951e-01 7.77104616e-01
4.56058562e-01 3.71296495e-01 4.81096387e-01 -7.36632168e-01
3.03825855e-01 9.72260475e-01 -3.02278578e-01 -8.30061793e-01
-8.25051367e-01 -8.85242641e-01 -1.28645265e+00 -2.84810290e-02
9.33009326e-01 -7.37262741e-02 -1.27167881e+00 1.82646668e+00
5.92449427e-01 1.38073295e-01 -1.41209990e-01 1.11215401e+00
9.49577153e-01 2.99083769e-01 1.99777722e-01 -2.09488124e-01
1.44977987e+00 -9.56471145e-01 -6.77970290e-01 -1.13984272e-01
8.90213311e-01 -5.70468366e-01 9.17566061e-01 2.75442243e-01
-9.72267807e-01 -2.41148204e-01 -1.11108768e+00 -3.55550766e-01
-2.40636915e-01 3.71049017e-01 6.94293559e-01 4.00462627e-01
-9.37691271e-01 4.09382463e-01 -1.11226523e+00 -1.33533508e-01
1.09655178e+00 6.89793527e-01 -3.50529760e-01 -2.53523514e-02
-6.90207720e-01 5.48665702e-01 5.82157910e-01 4.69889224e-01
-5.42030811e-01 -9.50150132e-01 -8.95509362e-01 2.00422369e-02
2.69475281e-01 -8.06213319e-01 9.40854549e-01 -8.16072583e-01
-1.32281280e+00 8.26633751e-01 -3.73232849e-02 -3.17789584e-01
5.60879409e-01 1.26307711e-01 -3.61091830e-02 2.87754893e-01
1.13381408e-01 1.09416127e+00 5.20909190e-01 -1.07698238e+00
-6.58921778e-01 -6.89421058e-01 -5.46787202e-01 2.39166573e-01
-4.70983326e-01 -6.48759007e-01 -8.73911917e-01 -6.77665472e-01
4.53363329e-01 -8.67887199e-01 -2.33312622e-01 3.13608378e-01
-7.80090392e-01 -1.69212356e-01 6.65727913e-01 -7.33061612e-01
1.01208508e+00 -2.13313842e+00 2.07869902e-01 2.96099722e-01
5.08549869e-01 1.26447961e-01 -3.86472382e-02 -4.06077862e-01
2.37208262e-01 1.88979492e-01 -4.62797463e-01 -4.84250605e-01
-9.70667973e-02 1.19956151e-01 2.69136190e-01 8.60428095e-01
3.87626410e-01 1.09965563e+00 -8.47221971e-01 -9.16421056e-01
-2.24220343e-02 5.66396296e-01 -6.39600933e-01 -7.02559128e-02
-2.07080200e-01 6.36331856e-01 -4.67310101e-01 1.12520063e+00
6.65519953e-01 -5.15387952e-01 3.09903733e-02 -4.92365777e-01
3.91866863e-01 -1.69495374e-01 -8.86808753e-01 1.67362785e+00
-1.64145157e-01 4.40075070e-01 3.27574044e-01 -1.04431808e+00
5.29820144e-01 3.72791588e-01 5.59786022e-01 -4.78099048e-01
2.57912934e-01 4.36842293e-01 1.67926371e-01 -4.17562187e-01
1.47722602e-01 -1.18922807e-01 -8.76388997e-02 -9.14289057e-03
2.05935776e-01 1.06918241e-03 2.93272465e-01 1.78683341e-01
8.95321667e-01 -1.09953530e-01 7.03258291e-02 -4.75438088e-01
5.71304560e-01 -3.37333918e-01 1.13982570e+00 3.16357702e-01
-5.30995309e-01 9.25951600e-01 7.15519071e-01 -1.26810417e-01
-8.72550130e-01 -1.00596547e+00 -2.77969599e-01 8.67679775e-01
2.02186704e-01 6.83040544e-02 -7.63950527e-01 -1.06228173e+00
-4.49460968e-02 3.20038885e-01 -8.01944077e-01 -1.74362794e-01
-4.27797645e-01 -1.11668956e+00 7.04631507e-01 6.44135594e-01
2.67070234e-01 -7.50523031e-01 -1.00368723e-01 1.01278305e-01
-3.51038665e-01 -1.10053945e+00 -7.49984503e-01 3.70737046e-01
-9.25253987e-01 -9.65479851e-01 -1.03960240e+00 -7.90261090e-01
1.09281683e+00 -1.04408838e-01 1.04541099e+00 2.99489588e-01
-2.89402127e-01 -1.30575880e-01 -1.04336798e-01 -3.47883731e-01
-2.84934878e-01 5.14671564e-01 -2.89271414e-01 1.15348883e-01
2.25714743e-01 -3.36974293e-01 -8.62489462e-01 2.08002329e-01
-1.00066388e+00 1.01728693e-01 9.02554452e-01 9.53001142e-01
1.01180518e+00 1.00730278e-01 7.92949796e-01 -1.07534206e+00
1.53539747e-01 -4.53403801e-01 -4.92555737e-01 3.59527707e-01
-3.60275418e-01 -6.39932901e-02 6.64969563e-01 -1.77585766e-01
-8.54926586e-01 4.68275875e-01 -2.78228760e-01 -2.33882040e-01
4.24542427e-02 3.83091748e-01 -4.20760393e-01 -1.72183916e-01
3.85209829e-01 1.99984670e-01 1.12037398e-01 -7.71736279e-02
1.05467148e-01 3.80847037e-01 7.16526210e-01 -2.85029143e-01
5.89446902e-01 5.86946428e-01 2.15041757e-01 -6.18822813e-01
-9.52379584e-01 -5.30677319e-01 -5.08824050e-01 -9.51889902e-02
1.04366088e+00 -9.48725641e-01 -7.91823864e-01 6.71303153e-01
-8.84164333e-01 -1.72823891e-01 -1.35852024e-01 3.80577624e-01
-2.23920852e-01 4.20985699e-01 -9.43649650e-01 -4.43269730e-01
-5.47389507e-01 -1.47675574e+00 1.26893032e+00 6.83116376e-01
-1.25241680e-02 -9.74199593e-01 -2.04504952e-01 7.02680826e-01
2.43660420e-01 4.71126884e-01 8.39451492e-01 -8.75100136e-01
-6.60076022e-01 -3.51963788e-01 -3.53918612e-01 3.15587133e-01
1.73376784e-01 2.61210054e-01 -9.80874896e-01 -3.77593309e-01
-4.03447241e-01 -5.40023267e-01 1.26299536e+00 8.11318874e-01
1.34026933e+00 -1.61718577e-01 -5.38176894e-01 9.35321033e-01
1.20019317e+00 -2.06380397e-01 4.62635458e-01 -3.72200608e-02
9.58367825e-01 5.28032362e-01 4.81422722e-01 2.34061182e-01
5.08857548e-01 3.81369948e-01 5.56513429e-01 -5.46428978e-01
-1.42807767e-01 4.69109006e-02 -8.27433094e-02 8.62144828e-01
1.22154631e-01 -4.46099788e-01 -8.73619258e-01 7.79485404e-01
-1.67765546e+00 -5.18100679e-01 -1.24436244e-01 1.97171462e+00
1.04177809e+00 1.70187324e-01 4.24107052e-02 -6.41810000e-02
6.67590737e-01 -2.09820911e-01 -9.22734261e-01 2.06570700e-01
-2.49967963e-01 -4.00081230e-03 6.02417707e-01 3.04731339e-01
-1.42419946e+00 8.20300877e-01 4.93511295e+00 1.23538280e+00
-1.09063089e+00 -8.30426142e-02 1.31459820e+00 -8.19791481e-02
-2.63216227e-01 -4.58916247e-01 -9.58169341e-01 6.72094166e-01
5.63870251e-01 3.00476015e-01 -9.84106213e-02 5.53883493e-01
8.73179883e-02 -6.77217916e-02 -1.02109563e+00 6.94190502e-01
-1.27637405e-02 -1.33481884e+00 4.86761890e-02 1.38796031e-01
8.34273458e-01 1.35852173e-01 2.30426505e-01 2.13979080e-01
2.45628916e-02 -1.14278615e+00 5.26432574e-01 5.45178771e-01
6.35065377e-01 -8.79406273e-01 1.13354838e+00 3.31036091e-01
-1.03515863e+00 1.31316468e-01 -4.01885360e-01 5.88566422e-01
1.23223988e-03 1.00305247e+00 -9.07618999e-01 4.68592942e-01
3.52061868e-01 6.61847770e-01 -7.42986083e-01 1.32956302e+00
6.68473840e-02 6.87757134e-01 -6.44051075e-01 1.30609110e-01
1.56595469e-01 -1.47760123e-01 3.57799172e-01 1.29788613e+00
3.49975556e-01 -1.50828902e-02 2.32903287e-01 8.46934259e-01
-4.56211627e-01 1.26908988e-01 4.87995781e-02 -1.22161366e-01
2.84217060e-01 1.72031999e+00 -1.43956828e+00 -1.87323242e-01
-2.10815862e-01 8.57673407e-01 3.56956452e-01 2.65706539e-01
-8.81386697e-01 -2.25619987e-01 3.43088597e-01 8.09608549e-02
2.63445407e-01 1.05593421e-01 -7.00422049e-01 -9.64622438e-01
-6.06192201e-02 -6.95626080e-01 5.43630064e-01 -1.13051109e-01
-1.37106836e+00 5.03209174e-01 -6.13356590e-01 -1.20716417e+00
3.15450937e-01 -4.10468489e-01 -3.91149908e-01 5.83586633e-01
-1.46471882e+00 -1.35371733e+00 -1.99930176e-01 2.28742540e-01
2.75864720e-01 1.19532816e-01 3.66220534e-01 6.15355253e-01
-9.72838283e-01 1.05495489e+00 5.51797487e-02 3.14779848e-01
7.74089158e-01 -1.56004179e+00 -3.37862521e-02 7.67728031e-01
-2.18803361e-01 4.45337683e-01 3.86205584e-01 -4.70986575e-01
-1.09436536e+00 -1.42082989e+00 5.23434043e-01 -2.85870939e-01
3.19083571e-01 -4.48197871e-01 -1.13767648e+00 4.05954331e-01
-1.00966297e-01 4.78864998e-01 9.19908047e-01 -2.09504291e-01
7.08973631e-02 -1.85825959e-01 -1.18094015e+00 6.72045052e-01
5.91078401e-01 -2.09585354e-01 1.29084457e-02 4.58220035e-01
6.98459208e-01 -6.87134981e-01 -1.06734061e+00 6.49954319e-01
2.95936465e-01 -8.69845331e-01 9.31049466e-01 -1.45692214e-01
4.37615246e-01 -4.73218679e-01 1.11662790e-01 -1.06553388e+00
-2.63059109e-01 -2.82123089e-01 -5.89288138e-02 1.39151502e+00
6.55992448e-01 -4.05802637e-01 1.18990779e+00 5.36287606e-01
-5.87945342e-01 -1.17328489e+00 -1.05449378e+00 -3.29432577e-01
2.71423995e-01 -2.11514503e-01 3.66512179e-01 7.65975833e-01
-2.83763051e-01 3.98167849e-01 -1.44036978e-01 2.25300863e-01
7.95602679e-01 -1.02910072e-01 5.12117922e-01 -1.07195854e+00
-1.77879408e-01 -7.74662375e-01 -5.84481001e-01 -1.02237236e+00
6.36819899e-02 -1.16490376e+00 2.31055990e-01 -1.40944541e+00
3.95829856e-01 -4.92196232e-01 -5.16349792e-01 5.26073158e-01
-6.36335731e-01 7.35860348e-01 -1.61006302e-01 1.78620905e-01
-9.68864202e-01 5.43330848e-01 1.75420856e+00 -2.37324670e-01
-2.17192597e-03 1.98770300e-01 -8.94669890e-01 8.65782797e-01
6.12030506e-01 -5.01949906e-01 -3.92734945e-01 -2.21747160e-01
3.09801340e-01 -6.45843148e-02 3.28015953e-01 -1.07090807e+00
3.75188380e-01 1.68996543e-01 8.06103647e-01 -8.60042870e-01
2.00809225e-01 -7.07470238e-01 -2.01935083e-01 3.51775885e-01
-3.46520633e-01 -5.35240412e-01 2.13285267e-01 7.96551406e-01
-2.18608737e-01 1.89111028e-02 1.07327318e+00 8.32556188e-02
-1.01499058e-01 5.99000454e-01 -1.41862631e-01 2.89095640e-01
1.03825259e+00 -4.61589277e-01 -2.64853001e-01 -9.61432979e-03
-6.31803453e-01 6.78115308e-01 4.95276988e-01 -1.39740989e-01
3.77848685e-01 -1.17805028e+00 -7.55741179e-01 1.43170491e-01
8.35150480e-02 7.88345456e-01 6.60354137e-01 1.42066205e+00
-6.94388807e-01 2.65753329e-01 1.53169692e-01 -1.03389049e+00
-9.47456837e-01 2.31833115e-01 4.40905213e-01 -5.01041472e-01
-4.68072116e-01 1.35241258e+00 6.37590826e-01 -5.73934793e-01
2.79886752e-01 -7.30658770e-01 -1.83650553e-01 2.95723090e-03
2.29027420e-01 1.87702730e-01 3.48021001e-01 -6.45391107e-01
-4.09630835e-01 3.96110862e-01 -5.05247414e-01 4.66275305e-01
1.07454574e+00 -1.31047443e-01 -1.51934937e-01 2.41023973e-01
1.31576884e+00 -2.39620268e-01 -1.60362315e+00 -2.12811664e-01
1.82687417e-01 -1.47687066e-02 2.49835432e-01 -9.61632013e-01
-1.62899518e+00 8.65923941e-01 5.33495128e-01 -6.92927465e-02
1.17246532e+00 -1.08772747e-01 1.12201524e+00 1.85139745e-01
-2.17969686e-01 -1.19215834e+00 -1.21362336e-01 2.27135062e-01
3.27898175e-01 -1.45206559e+00 5.09478860e-02 -4.23313200e-01
-6.71998203e-01 9.72708344e-01 6.61120832e-01 1.39214680e-01
4.60435718e-01 4.45188195e-01 1.36181727e-01 -2.56987810e-01
-6.78333461e-01 -1.08076893e-02 4.60292697e-01 4.35118169e-01
5.40128827e-01 9.84681919e-02 -1.11818917e-01 9.69229817e-01
1.29061401e-01 -1.51017502e-01 3.20320249e-01 4.06856716e-01
-4.56042349e-01 -6.13266528e-01 -1.21150032e-01 7.33825803e-01
-8.22639644e-01 -3.85107822e-03 -2.36184865e-01 7.48322725e-01
2.77159601e-01 3.99650931e-01 8.14126804e-02 -1.38896052e-02
1.84652079e-02 -3.12492490e-01 2.37994656e-01 -4.38950121e-01
-5.41845918e-01 3.61117542e-01 -3.10887039e-01 -3.24631065e-01
-2.61115462e-01 -6.42321825e-01 -1.69638693e+00 -1.47096306e-01
-5.41844487e-01 -3.40557620e-02 3.50131929e-01 1.03056753e+00
3.08806539e-01 7.17648923e-01 4.22764480e-01 -6.40967250e-01
-4.86517042e-01 -8.24812174e-01 -6.97356820e-01 3.67447615e-01
4.10142511e-01 -5.26069462e-01 -3.67427051e-01 5.06666861e-02] | [14.926093101501465, -3.00956392288208] |
4d848584-b86d-417b-9e84-7df18c2cea98 | extraction-of-cropland-field-parcels-with | null | null | https://www.tandfonline.com/doi/full/10.1080/22797254.2023.2181874?src= | https://www.tandfonline.com/doi/epdf/10.1080/22797254.2023.2181874?needAccess=true&role=button | Extraction of cropland field parcels with high resolution remote sensing using multi-task learning | Parcel-level farmland information contains rich spatial distribution and boundary details, which is crucial for digital agriculture and agricultural resource surveys. However, the spatial complexity and heterogeneity of features resulting from high resolution makes it difficult to obtain parcel-level information quickly and accurately. In addition, existing methods do not sufficiently take into account the spatial topological information, particularly for blurred boundaries. Here, we develop a multi-task network model to extract plot-level cropland information. Specifically, the model consists of a cascaded multi-task network with integrated semantic and edge detection, a refinement network with fixed edge local connectivity, and an integrated fusion model. To validate the performance of the model, two typical tests were conducted in Denmark (Europe) and Chongqing (Asia) with high-resolution remote sensing images provided by Sentinel-2 (10 m) and Google Earth (0.53 m) as data sources. The results show that our proposed model outperforms other baseline models and exhibits higher performance. This study is expected to provide important support for the design of new global agricultural information management systems in the future. | ['Shiran Song &Yongxing Wu', 'Jia Xu', 'Fei Peng', 'Juanjuan Yu', 'Peng Yang', 'Leilei Xu'] | 2023-02-14 | null | null | null | european-journal-of-remote-sensing-2023-2 | ['edge-detection'] | ['computer-vision'] | [ 1.13511369e-01 -2.82722831e-01 -1.71717048e-01 -2.55457640e-01
-2.08954707e-01 -6.96880102e-01 2.32925624e-01 5.04955828e-01
-1.38450325e-01 8.20778847e-01 -3.40800472e-02 -6.04783297e-01
-4.29466635e-01 -1.48962402e+00 -5.16088188e-01 -6.78661048e-01
-5.30663848e-01 -8.26160014e-02 2.11301133e-01 -4.89486933e-01
-2.49284536e-01 6.44250154e-01 -1.55119753e+00 2.13353246e-01
1.32787466e+00 9.00601923e-01 8.48040700e-01 4.86328751e-01
-1.66350137e-02 -3.20401527e-02 -2.77694967e-02 2.50365704e-01
3.89862269e-01 -5.18928235e-03 -3.13581377e-01 1.36832818e-01
1.42052218e-01 -5.44981718e-01 2.02817261e-01 1.38292086e+00
3.62558037e-01 -7.63491243e-02 3.44065815e-01 -9.74169910e-01
-5.16869128e-01 4.09063756e-01 -1.08540857e+00 6.73600286e-03
-2.52099574e-01 -1.55430660e-01 8.62893403e-01 -7.27097869e-01
4.74816322e-01 1.03037775e+00 1.03554380e+00 -6.11848652e-01
-1.23923457e+00 -7.41835833e-01 5.68397343e-01 -2.74275485e-02
-1.73838162e+00 -2.66111791e-01 6.00930989e-01 -4.86840844e-01
4.59836453e-01 1.44900799e-01 7.54902124e-01 3.33971441e-01
4.93918419e-01 3.02785277e-01 1.08008194e+00 -9.13950279e-02
-6.73111826e-02 -1.67819634e-01 -5.47446758e-02 4.80317563e-01
9.12639678e-01 3.24227035e-01 -6.93803057e-02 2.68565095e-03
1.17070246e+00 3.95218939e-01 -1.92364767e-01 -3.75767946e-01
-1.09824920e+00 6.92044795e-01 1.04980087e+00 4.54785198e-01
-1.00553024e+00 -2.03822270e-01 7.18290433e-02 2.03900412e-01
8.67079437e-01 1.38788879e-01 -6.34303331e-01 5.67314506e-01
-1.20380199e+00 1.87011033e-01 4.68207002e-01 1.01027179e+00
1.02284789e+00 7.74230389e-03 2.87817597e-01 7.64383495e-01
4.10331666e-01 9.28771257e-01 -4.04708236e-01 -9.37660575e-01
3.05615753e-01 6.70403600e-01 3.18784624e-01 -1.56022167e+00
-7.44100332e-01 -6.60496354e-01 -1.42949796e+00 2.39262760e-01
1.58690944e-01 -5.73021114e-01 -8.73194456e-01 1.40547287e+00
2.06215173e-01 1.30540580e-01 -1.05238948e-02 1.07450783e+00
8.27448130e-01 8.01188886e-01 3.31718713e-01 -6.62318990e-02
1.47674835e+00 -6.07843101e-01 -9.72646654e-01 -2.73286879e-01
6.42908692e-01 -6.18453264e-01 4.49609816e-01 -7.62570202e-02
-4.84444499e-01 -7.07975984e-01 -1.11556005e+00 5.55196762e-01
-9.37882721e-01 6.00695133e-01 9.94655967e-01 2.88421929e-01
-1.05996108e+00 3.93307328e-01 -6.72222912e-01 -6.20593071e-01
4.73442346e-01 -2.31173769e-01 -4.66538131e-01 -1.41779944e-01
-1.35258472e+00 8.42884719e-01 5.97947538e-01 1.10764861e+00
-5.32094777e-01 -6.05289876e-01 -1.13498187e+00 1.79720670e-01
3.61995965e-01 -3.95368695e-01 4.24064428e-01 -7.74484813e-01
-8.60386908e-01 6.50836766e-01 -8.92697945e-02 -1.07551128e-01
3.38468194e-01 -1.97247341e-01 -5.42035162e-01 -9.20364037e-02
5.67840993e-01 6.21182084e-01 3.11781675e-01 -1.52886415e+00
-1.15290070e+00 -7.04860091e-01 8.05442396e-04 4.49670047e-01
-2.03178264e-03 -1.16798416e-01 1.63960569e-02 -8.65010142e-01
5.67619801e-01 -6.07784808e-01 -5.17510474e-01 1.29651085e-01
-2.49331705e-02 5.71026266e-01 6.43580794e-01 -9.83130336e-01
1.19904625e+00 -2.23796511e+00 -2.37597942e-01 2.04753742e-01
1.68870807e-01 2.84137815e-01 -3.76449138e-01 4.02523994e-01
9.47902203e-02 2.49645129e-01 -4.74675149e-01 5.21539569e-01
-4.34261084e-01 1.83429971e-01 1.68715626e-01 4.13297057e-01
2.45791256e-01 9.19781268e-01 -9.44587409e-01 -2.76925147e-01
5.54582357e-01 2.91739047e-01 4.15467136e-02 -9.14332047e-02
2.52804365e-02 3.57875437e-01 -8.56948555e-01 9.82988238e-01
1.45666039e+00 -1.89483330e-01 1.66581362e-01 -3.80633444e-01
-7.84892797e-01 -4.70353931e-01 -1.35716569e+00 1.37799978e+00
-3.57316226e-01 4.70460415e-01 8.68120790e-01 -9.21902657e-01
1.11750948e+00 2.58049726e-01 4.14342821e-01 -5.93224823e-01
-3.02716881e-01 2.18747556e-01 -6.88988045e-02 -4.31766540e-01
6.47836506e-01 1.44719511e-01 -1.43653946e-02 -1.44184873e-01
-4.19923067e-01 -6.28832430e-02 -1.47488043e-01 -2.93055445e-01
5.22369146e-01 4.38689470e-01 3.38697702e-01 -5.84777296e-01
2.73822427e-01 5.53967237e-01 7.59715855e-01 6.75233305e-01
-3.00719291e-01 4.78955686e-01 2.46247709e-01 -6.05937600e-01
-8.69371355e-01 -8.95593464e-01 -4.03885722e-01 8.91412675e-01
5.06686032e-01 4.21544872e-02 -2.35754713e-01 -2.60522664e-01
6.15256011e-01 3.19530189e-01 -5.35881877e-01 3.39984685e-01
-1.87513173e-01 -1.22820961e+00 4.64214802e-01 4.07594562e-01
1.18785727e+00 -8.93058181e-01 -4.20730293e-01 5.03465533e-01
-3.93407941e-01 -1.17720652e+00 1.83799028e-01 1.74318850e-01
-1.04498684e+00 -9.98374224e-01 -8.65164101e-01 -6.79457128e-01
6.44419611e-01 9.16407108e-01 8.53751302e-01 -2.51976162e-01
-2.48508770e-02 -3.22315425e-01 -4.81956691e-01 -2.96913981e-01
9.35090557e-02 4.49006557e-01 -5.85503638e-01 -2.45198086e-01
3.13799441e-01 -6.10351682e-01 -5.72517812e-01 4.94218439e-01
-7.38433003e-01 4.41819757e-01 1.04261458e+00 6.99433327e-01
4.37785715e-01 5.32714069e-01 8.95284057e-01 -7.73384571e-01
2.57194132e-01 -8.33994389e-01 -9.39544618e-01 4.39602137e-01
-5.31984627e-01 -5.11284351e-01 2.38267049e-01 1.71788514e-01
-1.27557576e+00 3.14474016e-01 1.16910130e-01 2.28992656e-01
-5.86744010e-01 1.29492211e+00 -3.82664174e-01 -1.14287846e-01
2.69797921e-01 -1.49738621e-02 -9.40168574e-02 -5.68381608e-01
2.62319863e-01 8.81569862e-01 5.28225720e-01 -8.12630728e-02
8.08804154e-01 4.82117832e-01 3.78129855e-02 -1.17685115e+00
-5.32808244e-01 -5.03913045e-01 -9.23122346e-01 -4.42382962e-01
7.07553208e-01 -1.43155646e+00 -3.40550154e-01 8.45882535e-01
-1.06926930e+00 -2.96584785e-01 3.21807444e-01 6.82892263e-01
1.50588164e-02 6.35001361e-02 -3.71926218e-01 -6.18757784e-01
-2.64655411e-01 -6.25442564e-01 8.98821294e-01 2.63256907e-01
2.78329909e-01 -1.02555382e+00 -2.64585584e-01 6.14468418e-02
8.95714223e-01 7.08543360e-01 7.59507596e-01 9.80232134e-02
-5.86787820e-01 -1.05153747e-01 -1.06319618e+00 6.94239661e-02
8.52052033e-01 8.70717689e-02 -6.64372623e-01 -1.80372283e-01
-3.70682597e-01 3.42128098e-01 1.10042226e+00 1.03941238e+00
6.69224083e-01 1.78786829e-01 -5.40500522e-01 8.62915993e-01
1.71736693e+00 1.32217273e-01 3.84837121e-01 4.75199163e-01
6.45551682e-01 8.89845073e-01 1.00954092e+00 4.93844867e-01
6.23273015e-01 3.29468936e-01 7.88351893e-01 -8.71711910e-01
1.24774575e-01 -6.44762367e-02 -4.19809669e-02 2.37468466e-01
-2.96604186e-01 -9.00186151e-02 -1.00204468e+00 8.77319396e-01
-2.20544338e+00 -9.88165796e-01 -5.12301266e-01 1.96447539e+00
2.56810814e-01 -2.09594995e-01 -3.18392068e-01 -2.22475171e-01
1.09991968e+00 6.38223231e-01 -5.16296506e-01 2.30326146e-01
-6.50905311e-01 -8.51517394e-02 1.44705379e+00 3.47521186e-01
-1.54344690e+00 1.27409267e+00 6.12057686e+00 3.98325562e-01
-9.98756886e-01 -3.25339846e-02 3.07901204e-01 4.45373267e-01
-1.80619404e-01 1.21402014e-02 -5.93472362e-01 1.18375383e-01
4.72282827e-01 3.18433903e-02 1.74748346e-01 4.69178557e-01
7.78748155e-01 -5.75562477e-01 -4.23723496e-02 3.85104746e-01
-6.10065341e-01 -1.37953222e+00 -1.21452607e-01 9.28663760e-02
8.60171020e-01 2.60473192e-01 -3.82426172e-01 1.45405754e-02
6.58533275e-01 -7.94979751e-01 3.60448331e-01 4.82241720e-01
7.38513172e-01 -5.61092794e-01 1.08403575e+00 2.76750177e-01
-2.00314522e+00 -3.55964638e-02 -3.99311244e-01 -3.29663038e-01
2.12095812e-01 8.60945880e-01 -6.12564348e-02 1.21735597e+00
9.12592292e-01 1.19724226e+00 -4.07185942e-01 1.04786205e+00
-1.48319244e-01 2.63816297e-01 -5.30148625e-01 3.95737499e-01
5.53324878e-01 -5.39826214e-01 2.85820544e-01 1.06355059e+00
5.88949502e-01 1.76504388e-01 3.37721378e-01 6.33677721e-01
1.43137470e-01 2.61675240e-03 -1.00668907e+00 1.94190323e-01
7.61252880e-01 1.45099652e+00 -8.40804636e-01 -2.12568305e-02
-4.85528558e-01 6.28078759e-01 -2.31013939e-01 6.80095613e-01
-5.48278987e-01 -6.30950093e-01 8.25264096e-01 6.09431788e-02
2.45714098e-01 -5.87545693e-01 -4.32654023e-01 -1.02048790e+00
2.90372898e-03 -4.26809102e-01 1.42244577e-01 -8.64314914e-01
-8.52602959e-01 1.61257043e-01 6.47694319e-02 -1.03674340e+00
2.82973289e-01 -4.54407364e-01 -5.84142208e-01 1.24403191e+00
-2.24525476e+00 -1.49890983e+00 -9.43378508e-01 2.89809573e-02
2.21563146e-01 1.07514694e-01 9.22163129e-01 3.50045413e-01
-6.09278500e-01 -2.52399594e-01 4.39304292e-01 1.00209191e-01
5.22654891e-01 -8.97073150e-01 6.29949391e-01 9.56458151e-01
-6.51647747e-01 -8.11431631e-02 2.56576329e-01 -9.67963338e-01
-1.07184958e+00 -1.72576523e+00 8.43402088e-01 3.83473784e-01
5.80471575e-01 5.94659597e-02 -9.38228309e-01 6.38464451e-01
-7.66289458e-02 1.56167358e-01 2.98344165e-01 2.44030207e-01
2.46113032e-01 -5.56238055e-01 -1.19653153e+00 2.62596428e-01
1.04816699e+00 -8.87691751e-02 -1.13941722e-01 1.26172557e-01
4.28053498e-01 -1.22070469e-01 -1.03375494e+00 9.32769060e-01
8.80686164e-01 -7.60440648e-01 6.75173759e-01 3.87325622e-02
2.14239642e-01 -4.64324683e-01 -3.62442225e-01 -1.61271989e+00
-8.30180943e-01 4.95152175e-03 5.59108317e-01 1.15491629e+00
4.51443523e-01 -9.38715398e-01 5.80390155e-01 -9.15558413e-02
-2.33898615e-03 -6.79458678e-02 -5.66743672e-01 -8.01142573e-01
-6.06074110e-02 -1.11963011e-01 9.41588581e-01 1.03220308e+00
-4.52912122e-01 -6.32405514e-03 -1.20999627e-01 9.52471912e-01
5.62909484e-01 4.10581052e-01 5.86361587e-01 -1.74009812e+00
7.17559516e-01 -4.96724129e-01 -2.81932324e-01 -9.17666256e-01
5.77860661e-02 -4.96769488e-01 -1.10858560e-01 -1.84305823e+00
-1.74838863e-02 -8.60603034e-01 -1.83779895e-01 6.99135244e-01
-2.81705499e-01 -3.86513434e-02 -1.16623923e-01 2.24311069e-01
1.13293327e-01 6.35253549e-01 1.10377860e+00 -4.74119745e-02
-4.70951051e-01 1.87388882e-01 -5.98260283e-01 6.26473308e-01
1.08153057e+00 -3.51229578e-01 -8.00268352e-02 -7.45357096e-01
3.35489661e-01 2.65994638e-01 4.85452116e-01 -7.78656840e-01
5.51178828e-02 -5.47071874e-01 5.00019431e-01 -1.08561993e+00
-1.29582375e-01 -1.10181189e+00 5.61591148e-01 3.27310383e-01
1.60448834e-01 3.55518349e-02 5.70507586e-01 3.56095254e-01
-3.86282682e-01 1.25952542e-01 4.88797724e-01 -1.06191136e-01
-1.13407874e+00 4.72298980e-01 -4.58804429e-01 -5.66916704e-01
1.05651021e+00 -2.92785853e-01 -3.93117249e-01 -3.93573418e-02
-6.49246633e-01 9.46447551e-01 6.40083253e-01 6.05658412e-01
4.88467306e-01 -1.22591317e+00 -1.21721077e+00 5.68606377e-01
3.10212791e-01 2.32669294e-01 2.85430223e-01 6.72878087e-01
-9.20324028e-01 3.95893335e-01 -6.32333338e-01 -5.67194879e-01
-9.73251760e-01 6.62274063e-02 3.23378265e-01 -1.33920804e-01
-4.96088356e-01 2.33008802e-01 4.87645250e-03 -6.36889637e-01
-2.88791209e-01 -5.01849115e-01 -4.24067259e-01 5.67291319e-01
7.68500119e-02 3.28006566e-01 -1.01368301e-01 -8.38157833e-01
-3.54594946e-01 7.85962999e-01 5.06021202e-01 6.82309386e-04
1.60588050e+00 -4.68016535e-01 -2.53737897e-01 3.76872867e-01
5.93768954e-01 -3.67483050e-01 -1.27614450e+00 -2.79550761e-01
1.96285546e-01 -5.04894912e-01 7.04038620e-01 -5.94229758e-01
-1.31885099e+00 6.57235086e-01 5.89224160e-01 3.65699857e-01
1.28431606e+00 -4.45475429e-01 4.03057307e-01 1.92791164e-01
5.06554961e-01 -9.11038876e-01 -9.51142192e-01 3.72800410e-01
7.32946694e-01 -1.51412189e+00 1.48837551e-01 -6.51370704e-01
-3.03349257e-01 1.06775784e+00 4.18531448e-01 8.62648562e-02
1.11502945e+00 3.12706828e-01 1.60186633e-01 -2.05866650e-01
-3.52703124e-01 -8.29239964e-01 -1.08636416e-01 7.67454565e-01
4.09500748e-01 5.05829871e-01 -3.58447544e-02 2.34247059e-01
3.57749641e-01 3.12297553e-01 1.39368579e-01 9.26754653e-01
-7.90750563e-01 -5.87897956e-01 -6.11209989e-01 6.28091633e-01
-6.74653426e-02 -1.72294691e-01 9.72837582e-02 8.81611526e-01
1.44234195e-01 1.01266956e+00 8.36108774e-02 -2.11697444e-01
4.29688334e-01 -4.03788328e-01 1.68841202e-02 -5.67183137e-01
-3.49476784e-01 8.57661664e-02 3.90090682e-02 -3.55055124e-01
-6.14178658e-01 -6.33470416e-01 -8.27032387e-01 -6.08742356e-01
-5.86962581e-01 8.04814398e-02 8.03723991e-01 6.40344203e-01
6.04280472e-01 5.93594849e-01 7.69278228e-01 -1.13995206e+00
2.63625849e-02 -1.18567693e+00 -1.12559545e+00 -4.48250562e-01
4.35897768e-01 -8.02206337e-01 -1.88868031e-01 -1.17618956e-01] | [9.35145092010498, -1.586998462677002] |
9e075a31-8944-47fd-b7ec-65c13c81e785 | visual-storytelling-via-predicting-anchor | 2001.04541 | null | https://arxiv.org/abs/2001.04541v1 | https://arxiv.org/pdf/2001.04541v1.pdf | Visual Storytelling via Predicting Anchor Word Embeddings in the Stories | We propose a learning model for the task of visual storytelling. The main idea is to predict anchor word embeddings from the images and use the embeddings and the image features jointly to generate narrative sentences. We use the embeddings of randomly sampled nouns from the groundtruth stories as the target anchor word embeddings to learn the predictor. To narrate a sequence of images, we use the predicted anchor word embeddings and the image features as the joint input to a seq2seq model. As opposed to state-of-the-art methods, the proposed model is simple in design, easy to optimize, and attains the best results in most automatic evaluation metrics. In human evaluation, the method also outperforms competing methods. | ['Bowen Zhang', 'Hexiang Hu', 'Fei Sha'] | 2020-01-13 | null | null | null | null | ['visual-storytelling'] | ['natural-language-processing'] | [ 1.45991340e-01 2.22089067e-01 -2.53828943e-01 -4.25005436e-01
-8.46194923e-01 -4.73307192e-01 1.01584268e+00 -1.64533511e-01
-6.80389822e-01 7.83831179e-01 8.83713603e-01 2.42225513e-01
5.37666857e-01 -6.95127487e-01 -9.38206136e-01 -4.88871992e-01
2.16998711e-01 3.63691539e-01 9.88323390e-02 -2.76753485e-01
3.57689321e-01 9.71842930e-02 -1.38926566e+00 7.58498013e-01
4.45657521e-01 7.90330827e-01 4.73739505e-01 8.29308093e-01
-2.45025337e-01 1.11657774e+00 -6.69890881e-01 -6.88138664e-01
-3.98893058e-02 -5.92976451e-01 -7.23365009e-01 1.86141878e-01
3.25106919e-01 -5.59569895e-01 -7.13711500e-01 7.74797857e-01
6.40885890e-01 2.04997137e-01 8.79075825e-01 -1.03043127e+00
-1.18209445e+00 6.66007340e-01 -5.03559589e-01 1.06394134e-01
5.67006171e-01 1.68140173e-01 1.28689623e+00 -1.41403353e+00
1.20875108e+00 1.25935102e+00 2.37571061e-01 7.32332766e-01
-1.25709426e+00 -3.56990218e-01 1.18345976e-01 5.52091360e-01
-1.43365717e+00 -4.48988289e-01 6.91568911e-01 -5.13449788e-01
9.08739626e-01 -2.70253271e-02 9.21359181e-01 1.76907027e+00
2.36435145e-01 1.18648338e+00 7.48230517e-01 -2.54981995e-01
1.33409470e-01 2.49039546e-01 -4.16383594e-01 7.94760585e-01
-2.86032319e-01 4.28694636e-02 -8.17688525e-01 2.44585887e-01
8.27148318e-01 -1.50626406e-01 -1.45659924e-01 -2.89159477e-01
-1.53382504e+00 1.11369228e+00 6.24397516e-01 9.42834914e-02
-4.18766409e-01 5.09713173e-01 4.69126761e-01 -1.00368895e-01
4.25685465e-01 5.85818529e-01 2.14531258e-01 -1.02430940e-01
-7.52674282e-01 6.86618090e-01 3.99638176e-01 8.55456471e-01
3.72759342e-01 9.02028978e-02 -8.50488424e-01 9.03635681e-01
1.06366314e-01 1.92641720e-01 3.99433285e-01 -8.80984783e-01
5.90566456e-01 2.30049580e-01 3.77709895e-01 -9.47257280e-01
-4.79125753e-02 -1.51288003e-01 -4.77561206e-01 9.96288955e-02
9.51885059e-03 -4.36399542e-02 -9.85987127e-01 1.58735704e+00
-5.16098477e-02 2.82087862e-01 2.41511852e-01 1.19750357e+00
1.25538790e+00 1.25900352e+00 2.23249137e-01 -5.95622472e-02
1.40540278e+00 -1.26222551e+00 -8.52025986e-01 -5.60033381e-01
2.41450965e-01 -6.60454094e-01 1.32857215e+00 1.35997593e-01
-1.09960449e+00 -5.86832702e-01 -1.30322623e+00 -3.09748232e-01
-2.13504136e-01 2.14088231e-01 3.03447872e-01 -5.69546297e-02
-8.00821304e-01 3.85970861e-01 -3.80625099e-01 -1.21305257e-01
5.26464760e-01 -1.98256359e-01 -3.83990109e-01 -2.31382191e-01
-1.22817934e+00 1.17533398e+00 6.06412590e-01 -2.55051553e-01
-1.34569919e+00 -5.55146575e-01 -1.09313965e+00 -5.83933406e-02
9.34152082e-02 -7.51218557e-01 1.32312405e+00 -9.45067406e-01
-1.52799988e+00 9.58489656e-01 -8.26242268e-02 -3.94905835e-01
4.91015762e-01 -2.82156289e-01 -1.41643137e-01 2.64285237e-01
1.74103945e-01 1.29248536e+00 8.98412704e-01 -1.43795645e+00
-4.22443032e-01 3.61357063e-01 9.47220698e-02 4.74819243e-01
-3.45741063e-01 4.66329753e-02 -4.90556985e-01 -8.75226259e-01
-4.29814965e-01 -5.21824181e-01 -3.54679465e-01 8.51828158e-02
-4.24145579e-01 -1.18719496e-01 5.55569947e-01 -6.13831401e-01
1.00503552e+00 -2.36264205e+00 4.11210537e-01 -4.27036643e-01
1.33021295e-01 -8.26186985e-02 -5.04146218e-01 5.15545189e-01
2.88825855e-02 -1.57433838e-01 -7.96678439e-02 -4.96006429e-01
-4.15272173e-03 2.54434317e-01 -5.48351347e-01 2.07514361e-01
4.23253953e-01 1.30253434e+00 -1.21019876e+00 -7.62447119e-01
1.87867731e-01 4.64321196e-01 -3.88458997e-01 7.67213285e-01
-5.43234110e-01 1.70818493e-01 -3.50507796e-01 5.98707013e-02
8.47928226e-02 -9.74881724e-02 -2.70446017e-02 -1.57081053e-01
-7.02197477e-02 3.03619117e-01 -7.65234530e-01 1.89628649e+00
-3.90622348e-01 9.39482391e-01 -6.44431889e-01 -8.58702362e-01
1.03314340e+00 5.94591260e-01 -1.82099584e-02 -5.94532371e-01
5.57034612e-02 -8.96155536e-02 -4.05157179e-01 -8.74583423e-01
6.62431180e-01 -3.81206572e-01 -4.97423381e-01 3.37086797e-01
4.40232277e-01 -3.77015710e-01 2.63977796e-01 1.77135885e-01
8.81425261e-01 2.94569135e-01 3.99106562e-01 2.35732049e-01
1.68933332e-01 9.11719874e-02 3.65742356e-01 5.45050204e-01
2.59528756e-01 1.01825571e+00 7.52281487e-01 -7.81895220e-01
-1.58668959e+00 -1.53569388e+00 2.92803943e-01 1.03120279e+00
9.80783999e-02 -5.98997533e-01 -7.45638490e-01 -6.59756899e-01
-3.97676408e-01 1.14045203e+00 -7.82798350e-01 -1.31797418e-01
-5.43239057e-01 -3.21648419e-01 3.75096112e-01 7.12969542e-01
2.56713182e-01 -1.45680678e+00 -6.72724426e-01 1.72763705e-01
-3.49845946e-01 -1.32017791e+00 -7.14094043e-01 -1.82966158e-01
-2.77671009e-01 -5.19491971e-01 -9.18382525e-01 -1.06316590e+00
5.62919855e-01 -5.31686693e-02 1.11798906e+00 -4.02315557e-01
-3.52174640e-01 -1.78088564e-02 -3.90838027e-01 -3.11253965e-01
-4.21105742e-01 -1.96704030e-01 -2.26372108e-01 2.01202661e-01
-1.69490159e-01 -2.27775842e-01 -5.30939102e-01 -2.12628543e-01
-9.48117256e-01 7.07428873e-01 7.46878028e-01 1.11411035e+00
7.46614695e-01 -4.99429077e-01 4.91423398e-01 -7.51189947e-01
7.45221734e-01 -4.15697217e-01 -2.72889823e-01 1.13810472e-01
-1.46089017e-01 1.67290866e-01 8.19227755e-01 -7.25715101e-01
-9.13488388e-01 2.20540017e-01 -1.23209968e-01 -6.46418154e-01
-5.38249016e-02 4.21590000e-01 -6.05698228e-02 6.09981418e-01
5.50237894e-01 1.89383432e-01 -2.44070977e-01 -1.49087429e-01
9.04788971e-01 4.34420586e-01 7.90394545e-01 -2.39788607e-01
7.06654787e-01 1.98940098e-01 -4.15146410e-01 -9.03965652e-01
-1.06172752e+00 -4.41149063e-03 -4.04932618e-01 -5.32093525e-01
1.46222579e+00 -8.83813620e-01 -2.03467637e-01 1.48208523e-02
-1.75291443e+00 -2.38750875e-01 -4.71183896e-01 3.98824811e-01
-9.31101084e-01 -1.41999304e-01 -4.13303256e-01 -7.17335045e-01
-1.39915526e-01 -1.08812380e+00 1.09631801e+00 2.62206674e-01
-4.75593626e-01 -7.53982365e-01 2.13097811e-01 2.10957676e-01
-4.30468470e-02 6.42053068e-01 9.55348551e-01 -4.61356580e-01
-5.64395607e-01 -2.18784735e-01 -2.43149936e-01 2.45539933e-01
-2.58491606e-01 -1.28016695e-01 -8.40319157e-01 9.75737199e-02
-2.44728506e-01 -7.53785789e-01 9.56774950e-01 3.49879384e-01
1.13242817e+00 -3.96668375e-01 -1.68409765e-01 4.48047757e-01
1.47500229e+00 9.91984382e-02 7.89914012e-01 1.89037487e-01
7.40332723e-01 5.34737289e-01 6.01874292e-01 6.63171768e-01
4.48781341e-01 7.34521985e-01 3.36531520e-01 -4.41585518e-02
-1.28678516e-01 -8.03361118e-01 7.48530805e-01 7.35886335e-01
1.77880973e-01 -3.29790622e-01 -7.66517937e-01 8.94703627e-01
-1.98117697e+00 -1.24488914e+00 1.66243464e-01 1.69410133e+00
8.22003126e-01 1.58728436e-01 8.56302585e-03 -3.01920533e-01
6.38287425e-01 7.85856128e-01 -2.15232819e-01 -6.66802108e-01
-2.52651304e-01 2.56141126e-01 1.58139676e-01 4.84100223e-01
-9.58326995e-01 1.19117105e+00 7.19264030e+00 7.47453153e-01
-8.65812719e-01 2.36876413e-01 7.48998225e-01 -5.08689225e-01
-5.24357498e-01 -9.93781090e-02 -5.12013137e-01 2.76210666e-01
7.85043418e-01 -2.06472501e-01 4.01928604e-01 8.48737955e-01
3.44279051e-01 1.02604426e-01 -1.31371462e+00 9.69567060e-01
5.53717017e-01 -1.86563623e+00 3.48915577e-01 -3.32784534e-01
8.54987562e-01 -2.74680674e-01 2.61480331e-01 1.94484159e-01
3.86891693e-01 -1.48474383e+00 1.18574250e+00 6.74633741e-01
1.00967407e+00 -8.63233984e-01 7.05535531e-01 1.41665414e-01
-8.81819129e-01 -1.04469858e-01 -3.33575517e-01 -1.73647463e-01
6.37622356e-01 1.56925231e-01 -9.16890681e-01 1.42829165e-01
4.39969152e-01 7.30753779e-01 -3.22483748e-01 7.35490084e-01
-7.97987521e-01 4.17861849e-01 2.37419680e-01 -4.49738503e-01
5.80588877e-01 1.82517692e-01 4.78226811e-01 1.34791040e+00
2.39809096e-01 5.53266555e-02 2.89044261e-01 1.04316449e+00
-4.03048038e-01 2.28079051e-01 -8.65192652e-01 -3.18117470e-01
3.41312200e-01 1.15748680e+00 -4.46674347e-01 -5.02620816e-01
-4.56862122e-01 1.23985994e+00 6.12466991e-01 3.11203629e-01
-9.82557058e-01 -4.29094642e-01 5.90472460e-01 6.20750785e-02
6.43573284e-01 -1.48747161e-01 -2.67962217e-01 -9.56882477e-01
-2.65128650e-02 -7.02377439e-01 1.38933137e-01 -1.25342810e+00
-1.22982430e+00 8.17651033e-01 2.38054141e-01 -1.15084791e+00
-4.61517125e-01 -6.66782081e-01 -8.90729249e-01 5.40735781e-01
-1.17277896e+00 -1.14873779e+00 -1.87843159e-01 1.97497532e-01
1.01733613e+00 -3.12542647e-01 9.21713114e-01 -2.65837371e-01
-2.89752603e-01 4.74830747e-01 -5.15753180e-02 3.41700196e-01
5.77963829e-01 -1.11554635e+00 6.41763389e-01 6.77664757e-01
5.19312561e-01 -4.70160991e-02 9.56806839e-01 -4.49892253e-01
-1.04852271e+00 -1.06796622e+00 9.73786473e-01 -3.60019892e-01
7.30323911e-01 -8.26852083e-01 -4.60851252e-01 5.43488503e-01
8.33059549e-01 -8.75191838e-02 6.19907618e-01 -4.26885724e-01
-4.55623299e-01 1.12200737e-01 -7.63073444e-01 1.01857519e+00
9.18995321e-01 -3.96863937e-01 -8.32370222e-01 2.91658461e-01
9.67729807e-01 -4.21162218e-01 -6.40613139e-01 -2.11648867e-01
5.79496384e-01 -5.35009086e-01 9.38042343e-01 -7.33494997e-01
1.45259345e+00 -8.42872933e-02 -2.94312596e-01 -1.55774379e+00
-5.34359634e-01 -3.27481776e-01 -4.29263711e-02 1.09395325e+00
6.89621210e-01 6.76525533e-02 7.08174467e-01 -2.18103416e-02
-7.38832131e-02 -9.40182567e-01 -9.31382477e-01 -5.70954084e-01
-1.21084660e-01 -2.83912241e-01 4.64873314e-01 5.62711477e-01
3.03318501e-02 9.52960670e-01 -7.48411655e-01 -1.71991557e-01
4.79325771e-01 1.46905750e-01 6.93727255e-01 -6.41573191e-01
-3.22467327e-01 -2.11418882e-01 -4.70742971e-01 -1.05693734e+00
4.61992264e-01 -8.83753657e-01 4.83956873e-01 -1.82715654e+00
4.09621984e-01 1.93961114e-01 -1.49800465e-01 3.10227752e-01
-2.71505952e-01 5.26200652e-01 4.21523005e-01 -2.97457665e-01
-6.11252666e-01 9.96091604e-01 1.44490230e+00 -4.12248820e-01
5.39092682e-02 -5.99081278e-01 -6.00364447e-01 4.94161397e-01
5.46724737e-01 -5.00797987e-01 -4.16895747e-01 -7.57121623e-01
1.29271924e-01 1.47659346e-01 4.05521631e-01 -7.23690033e-01
-7.57881403e-02 -4.63346601e-01 6.57892525e-01 -5.01959383e-01
7.22064316e-01 -3.97774160e-01 -9.05664861e-02 1.54975370e-01
-7.55189121e-01 1.94060296e-01 -1.20608009e-01 3.98582041e-01
-2.89501458e-01 -2.99460262e-01 7.25500762e-01 -2.70264089e-01
-7.77468562e-01 3.17044526e-01 -4.96200979e-01 2.57416606e-01
1.12773931e+00 -1.96165040e-01 -1.19105130e-01 -6.81598008e-01
-6.82879448e-01 1.87307671e-01 4.61769313e-01 9.10067320e-01
1.26580179e+00 -1.86079192e+00 -1.24000609e+00 -1.57577753e-01
3.54762137e-01 -2.35514082e-02 4.95226011e-02 2.56904334e-01
-4.39128160e-01 1.43537104e-01 -4.80547428e-01 -3.95053178e-01
-1.03234017e+00 7.01144457e-01 1.50400037e-02 -2.41180599e-01
-7.03827322e-01 9.44492221e-01 4.86134529e-01 9.15248394e-02
1.57956377e-01 1.35187313e-01 -4.20165807e-01 1.48617163e-01
8.25420141e-01 -1.13456063e-01 -5.20145178e-01 -6.75153971e-01
-5.01466244e-02 2.59524673e-01 -1.78396568e-01 -7.06491053e-01
1.66908562e+00 2.40683496e-01 2.76623935e-01 8.81946564e-01
1.39867008e+00 -3.66014272e-01 -1.48647499e+00 -5.15585691e-02
-1.63396403e-01 -5.10959864e-01 -1.41432047e-01 -5.23614168e-01
-8.09271932e-01 8.63165021e-01 2.47305766e-01 -3.01729679e-01
7.51880407e-01 3.85950863e-01 7.60293901e-01 1.22791290e-01
2.66257320e-02 -1.18087304e+00 7.00664282e-01 4.26182270e-01
1.36720169e+00 -9.15021896e-01 -9.06829610e-02 -6.86856210e-02
-1.32785463e+00 9.52571869e-01 6.80774987e-01 -6.19728923e-01
-2.67339740e-02 3.24250340e-01 3.32846977e-02 -8.72421116e-02
-1.19492483e+00 -2.54373923e-02 2.99423575e-01 6.39205754e-01
4.10486370e-01 2.89404429e-02 -2.78435230e-01 6.99181676e-01
-4.07839417e-01 -1.19576730e-01 5.63019872e-01 4.43106651e-01
-3.81317586e-01 -9.05836105e-01 -2.60742784e-01 3.53798330e-01
-2.70314097e-01 -8.04729462e-02 -5.03089666e-01 5.17487526e-01
1.05420202e-01 5.34329534e-01 2.96996593e-01 -4.96580452e-01
5.27660012e-01 2.00475633e-01 5.84113777e-01 -6.56553566e-01
-3.58102471e-01 -3.40131968e-01 3.87571990e-01 -4.90912646e-01
-5.60025424e-02 -5.90930402e-01 -1.13303757e+00 -4.57325168e-02
7.26378262e-02 -1.12994676e-04 5.12997329e-01 1.03064406e+00
1.16429701e-01 6.25662923e-01 7.84663796e-01 -1.05036020e+00
-2.81008214e-01 -9.96130407e-01 -1.31181180e-01 5.88640511e-01
1.98071420e-01 -6.87422574e-01 8.63952935e-02 3.65055919e-01] | [11.173843383789062, 0.7338366508483887] |
5c707b77-9111-4470-b791-b86918312352 | hasp-a-high-performance-adaptive-mobile | 1809.01697 | null | http://arxiv.org/abs/1809.01697v1 | http://arxiv.org/pdf/1809.01697v1.pdf | HASP: A High-Performance Adaptive Mobile Security Enhancement Against Malicious Speech Recognition | Nowadays, machine learning based Automatic Speech Recognition (ASR) technique
has widely spread in smartphones, home devices, and public facilities. As
convenient as this technology can be, a considerable security issue also raises
-- the users' speech content might be exposed to malicious ASR monitoring and
cause severe privacy leakage. In this work, we propose HASP -- a
high-performance security enhancement approach to solve this security issue on
mobile devices. Leveraging ASR systems' vulnerability to the adversarial
examples, HASP is designed to cast human imperceptible adversarial noises to
real-time speech and effectively perturb malicious ASR monitoring by increasing
the Word Error Rate (WER). To enhance the practical performance on mobile
devices, HASP is also optimized for effective adaptation to the human speech
characteristics, environmental noises, and mobile computation scenarios. The
experiments show that HASP can achieve optimal real-time security enhancement:
it can lead an average WER of 84.55% for perturbing the malicious ASR
monitoring, and the data processing speed is 15x to 40x faster compared to the
state-of-the-art methods. Moreover, HASP can effectively perturb various ASR
systems, demonstrating a strong transferability. | ['ChenChen Liu', 'Zirui Xu', 'Xiang Chen', 'Fuxun Yu'] | 2018-09-04 | null | null | null | null | ['mobile-security'] | ['miscellaneous'] | [ 1.55294403e-01 -1.02498755e-01 1.99212343e-01 -1.06598800e-02
-9.61690485e-01 -6.69618666e-01 2.11714432e-01 -3.57722938e-01
-3.22754681e-01 3.71400982e-01 2.06482679e-01 -7.56777525e-01
3.79945606e-01 -4.80242848e-01 -5.18687487e-01 -6.63319230e-01
1.11870140e-01 -3.39045435e-01 3.32382739e-01 -5.07250309e-01
-1.55923098e-01 5.42762876e-01 -1.00437450e+00 3.41452837e-01
7.16283441e-01 8.13042223e-01 3.03371204e-03 8.70193779e-01
3.75604421e-01 5.82771122e-01 -1.35465264e+00 -5.91464818e-01
2.55651802e-01 -1.61773600e-02 -2.93844610e-01 -2.16240615e-01
-3.92069668e-01 -4.96091247e-01 -1.11368370e+00 1.27693665e+00
9.26807225e-01 6.21091686e-02 -2.16085720e-03 -1.27480721e+00
-7.57193208e-01 5.22125423e-01 -4.50064152e-01 2.28789598e-01
5.37423909e-01 4.81604427e-01 3.63902003e-01 -3.25449228e-01
-2.73345500e-01 1.43874764e+00 4.41813648e-01 9.56739008e-01
-6.27327502e-01 -8.92655730e-01 4.24128734e-02 1.65106580e-01
-1.61884642e+00 -8.38193417e-01 7.29644656e-01 1.71196058e-01
1.01681554e+00 8.82448137e-01 2.06531301e-01 1.34241319e+00
-7.70118684e-02 7.75154471e-01 6.80352032e-01 -1.60686105e-01
1.25022635e-01 3.35628033e-01 -7.81900659e-02 1.58466011e-01
6.80800900e-02 3.75466615e-01 -3.80149990e-01 -5.06278276e-01
2.00161666e-01 2.94954535e-02 -7.74430513e-01 7.05436766e-01
-9.88017082e-01 3.09340119e-01 2.76299845e-02 2.19778687e-01
-1.82021126e-01 7.24524111e-02 6.67515397e-01 2.62314707e-01
3.06725413e-01 2.14105353e-01 -5.68948805e-01 -5.36698580e-01
-4.22489047e-01 -2.59124398e-01 6.40306473e-01 8.68764222e-01
9.97605771e-02 4.86758530e-01 -7.17017287e-03 9.41777706e-01
5.28533518e-01 1.16001570e+00 8.51776600e-01 -5.81865191e-01
8.63648713e-01 1.52835310e-01 6.02025352e-02 -1.25776041e+00
5.40924557e-02 -1.11093886e-01 -9.20788050e-01 -1.14280246e-01
-3.41074951e-02 -3.76258254e-01 -5.48234344e-01 1.38815904e+00
3.57555151e-01 4.33121204e-01 3.28898400e-01 6.35959804e-01
4.80439067e-01 9.81603384e-01 -6.56341538e-02 -5.10870278e-01
1.30726016e+00 -6.44537628e-01 -1.22750294e+00 -1.87918112e-01
5.90291739e-01 -7.87621081e-01 1.42273343e+00 2.10319519e-01
-7.60473847e-01 -2.94201136e-01 -1.28423774e+00 4.12348121e-01
-4.47070420e-01 6.80709071e-03 1.00775145e-01 1.58927178e+00
-8.53160799e-01 2.33936552e-02 -7.97472060e-01 1.14926420e-01
3.85098696e-01 6.49060190e-01 -2.17841789e-01 2.13493198e-01
-1.61253595e+00 5.18653989e-01 1.62348449e-01 1.99831188e-01
-5.62944055e-01 -5.70954680e-01 -8.16388428e-01 6.35779127e-02
2.07977787e-01 -4.15016785e-02 1.43650746e+00 -6.60103917e-01
-2.04497719e+00 5.48743904e-01 -1.35384083e-01 -4.34064388e-01
5.25555074e-01 -5.53175583e-02 -1.27283204e+00 8.02276880e-02
-5.90700507e-01 -2.98196465e-01 1.02627921e+00 -1.00119674e+00
-3.16274464e-01 -6.06953382e-01 -5.26249334e-02 1.42887548e-01
-9.43800092e-01 4.91436571e-01 -3.67591023e-01 -1.01147866e+00
-2.19312951e-01 -9.98520911e-01 -1.76598504e-01 -3.98095399e-01
-5.00575364e-01 4.16310161e-01 1.45466483e+00 -1.00595355e+00
1.68847704e+00 -2.63589716e+00 -4.29028332e-01 3.82271588e-01
-3.78431901e-02 1.26835597e+00 1.47790998e-01 9.00463685e-02
-2.76894439e-02 3.93172950e-01 -1.45497024e-01 -1.87491432e-01
6.64131790e-02 1.32722750e-01 -7.01694965e-01 5.10034919e-01
-4.29342240e-01 8.73309851e-01 -6.64498210e-01 -4.81704995e-02
5.04111886e-01 8.51650715e-01 -3.13723505e-01 3.56384844e-01
2.87563264e-01 1.05818674e-01 -4.20710415e-01 6.01649046e-01
8.63153934e-01 2.07846463e-01 5.19973412e-02 1.10196158e-01
6.10399008e-01 1.81172073e-01 -1.00774324e+00 7.38232255e-01
-6.72395110e-01 7.14916646e-01 3.23960960e-01 -6.00984156e-01
1.01258409e+00 6.56123459e-01 -1.78317986e-02 -6.08801365e-01
4.06777382e-01 1.77793890e-01 -6.99942634e-02 -5.72765768e-01
3.55597615e-01 4.35920984e-01 -1.25657782e-01 4.05125022e-01
-5.69199443e-01 9.48185623e-02 -9.37058687e-01 -1.65745430e-02
1.25231564e+00 -7.83787966e-01 3.22179466e-01 1.89110920e-01
1.10616159e+00 -9.72333312e-01 4.02258307e-01 5.67457557e-01
-6.01737738e-01 2.12167323e-01 -2.96082962e-02 2.09041890e-02
-6.52025342e-01 -8.18968952e-01 3.05296600e-01 8.12723577e-01
1.05510890e-01 -3.93221051e-01 -1.15983963e+00 -7.43182659e-01
-2.15568081e-01 8.52818251e-01 -1.28699005e-01 -5.96188188e-01
-6.24065042e-01 -7.54858792e-01 1.33822072e+00 2.95539707e-01
8.15830350e-01 -9.32761788e-01 5.18760756e-02 -2.48362543e-03
-8.24809894e-02 -1.43282294e+00 -1.05349612e+00 -4.00412858e-01
-3.34114522e-01 -6.16316915e-01 -5.81927001e-01 -6.23172164e-01
5.20710111e-01 5.54856420e-01 3.39063555e-01 2.58808434e-01
-1.07598692e-01 4.28644329e-01 -5.16283929e-01 -4.23111200e-01
-1.13464856e+00 -4.65666950e-02 4.70231712e-01 4.11028802e-01
3.92641962e-01 -6.85006797e-01 -3.58973801e-01 5.68081379e-01
-1.02695286e+00 -7.52380073e-01 5.92106432e-02 6.14830494e-01
1.03537217e-01 5.24483085e-01 6.77694619e-01 -5.17764449e-01
8.77762496e-01 -2.40405530e-01 -3.67216200e-01 3.62171918e-01
-3.46547514e-01 -3.75399292e-01 1.09102952e+00 -9.82455015e-01
-8.75821710e-01 -2.68538475e-01 -7.89598763e-01 -3.73995483e-01
-8.39539021e-02 -9.93426815e-02 -1.20238674e+00 -4.47833627e-01
6.27863765e-01 7.40336418e-01 -1.07197791e-01 -1.61658555e-01
3.08574319e-01 1.76775825e+00 4.16452199e-01 -2.11303279e-01
1.16927719e+00 1.41315743e-01 -4.92312670e-01 -1.32275915e+00
-1.49917409e-01 -3.12148511e-01 1.98799804e-01 -8.99257511e-02
3.82772714e-01 -9.00522172e-01 -1.19280386e+00 1.09822965e+00
-1.17343199e+00 -1.86022893e-01 2.24007890e-01 3.29468727e-01
-1.78404137e-01 7.70125031e-01 -7.28142262e-01 -1.20972133e+00
-8.27013373e-01 -1.43134868e+00 8.93561304e-01 1.83177337e-01
3.64405997e-02 -7.93109357e-01 -3.71979207e-01 5.56836307e-01
5.20518959e-01 -2.96284378e-01 3.82496834e-01 -9.24795806e-01
-1.71524376e-01 -5.10868073e-01 1.49622291e-01 7.29453683e-01
4.68660682e-01 -7.68195465e-02 -1.15239155e+00 -4.90386844e-01
4.29114431e-01 2.37748697e-01 1.59740429e-02 -5.43244965e-02
1.56566858e+00 -1.07673883e+00 -3.08173597e-01 7.66586363e-01
7.46456206e-01 8.73148620e-01 1.05800712e+00 2.12029904e-01
7.48363435e-01 1.54333681e-01 5.93106151e-01 4.55603153e-01
-1.02209769e-01 9.61157262e-01 3.67043883e-01 1.14690103e-01
2.79259324e-01 -3.30956340e-01 8.82766187e-01 1.07640934e+00
5.22704303e-01 -5.11110365e-01 -6.34240091e-01 1.98790252e-01
-1.52052557e+00 -1.06299376e+00 6.62655234e-02 2.41088915e+00
8.13773632e-01 1.61982909e-01 1.00830369e-01 6.08982623e-01
9.67259884e-01 5.41114748e-01 -5.36360443e-01 -5.16051888e-01
-1.02523498e-01 -1.64678823e-02 6.43949449e-01 7.20247865e-01
-9.20081973e-01 9.59272981e-01 5.97442722e+00 1.33439422e+00
-1.19639683e+00 3.94738048e-01 7.54449844e-01 -2.63441782e-02
-2.24214822e-01 -6.41490698e-01 -6.07417583e-01 1.08351195e+00
1.14624846e+00 -2.11385012e-01 8.17621410e-01 1.01173055e+00
5.09558082e-01 7.52780199e-01 -4.32376504e-01 1.45408916e+00
1.65321127e-01 -8.38378549e-01 -7.20041897e-03 2.07122535e-01
1.09395742e-01 -2.22550973e-01 4.69898283e-01 1.30982250e-01
1.13989979e-01 -9.57631648e-01 2.18816787e-01 -1.50093481e-01
9.79844153e-01 -1.16021121e+00 7.10503757e-01 4.99026984e-01
-1.20074010e+00 -3.47217679e-01 -2.45394245e-01 1.43113583e-01
2.74476588e-01 3.78968984e-01 -7.79506624e-01 2.65520185e-01
6.43979311e-01 1.00773826e-01 -3.71630430e-01 3.22204411e-01
-2.51823902e-01 9.47587907e-01 -4.34052020e-01 -4.66028452e-01
-1.36827394e-01 9.36788917e-02 8.56593311e-01 1.31950021e+00
3.86830807e-01 4.06235188e-01 -1.35170355e-01 3.12578939e-02
-2.13331848e-01 1.12856165e-01 -7.10557938e-01 -3.98585834e-02
1.16922772e+00 8.75615299e-01 -6.83180243e-02 -9.30155888e-02
3.58445458e-02 1.39945531e+00 -1.91616222e-01 4.02317226e-01
-1.10325015e+00 -8.17747533e-01 1.17359972e+00 -2.18413305e-03
-2.73262002e-02 -2.54124552e-01 -1.50039181e-01 -1.18278146e+00
3.21986258e-01 -1.59391749e+00 5.13243154e-02 -7.13392973e-01
-9.11120951e-01 6.74065053e-01 -6.98045194e-01 -1.08364832e+00
1.87902763e-01 -4.77857560e-01 -6.19346917e-01 7.27053761e-01
-1.05003703e+00 -1.03510845e+00 1.36396676e-01 9.40067232e-01
4.74606872e-01 -7.75885403e-01 8.49427164e-01 5.28396666e-01
-7.96009839e-01 1.55229890e+00 1.78093672e-01 3.83924961e-01
2.09264368e-01 -6.67777658e-01 8.90346348e-01 1.26800716e+00
5.56926504e-02 8.13098013e-01 5.36886990e-01 -4.39018399e-01
-1.46050274e+00 -1.21585929e+00 5.47521353e-01 -4.21700090e-01
7.15616643e-01 -5.88110089e-01 -9.43975568e-01 5.36733925e-01
-6.34177998e-02 -5.82027808e-02 9.92130935e-01 -5.63040376e-01
-5.42834103e-01 -3.60944211e-01 -1.55280387e+00 1.06092811e+00
8.80521953e-01 -1.16116023e+00 -2.70825505e-01 3.48591715e-01
1.50517333e+00 -5.44533372e-01 -7.29208708e-01 1.35488406e-01
2.49463841e-01 -5.91161013e-01 1.14629662e+00 -4.29769635e-01
-3.76966029e-01 -4.53431487e-01 -4.96156454e-01 -1.09329665e+00
1.96526036e-01 -1.70258570e+00 -6.34054959e-01 1.59607458e+00
2.87444085e-01 -1.13598764e+00 6.80869818e-01 6.33708954e-01
1.21304937e-01 -4.58266705e-01 -1.20132244e+00 -8.03656220e-01
-4.21546787e-01 -7.20274150e-01 1.14315581e+00 9.16021347e-01
6.62667602e-02 -9.28015858e-02 -7.55780160e-01 9.23095703e-01
3.72754127e-01 -1.04270363e+00 8.34507227e-01 -2.24316776e-01
-4.52498704e-01 -1.29749821e-02 -5.86516023e-01 -1.25911391e+00
2.44093701e-01 -5.23002148e-01 -6.76031411e-02 -6.17273986e-01
-4.56338644e-01 -2.29205549e-01 -3.41762990e-01 3.63119245e-01
-5.26744604e-01 -5.52297719e-02 2.65155315e-01 -7.50943348e-02
-3.43383908e-01 5.69725215e-01 8.31685066e-01 -2.14436918e-01
-3.20078909e-01 5.83897293e-01 -7.13581324e-01 5.38827956e-01
1.05174279e+00 -4.65961307e-01 -6.22851014e-01 -2.50896484e-01
-2.75384784e-01 1.65497363e-01 3.83006185e-02 -9.02497709e-01
5.28476872e-02 -5.00188097e-02 -2.44564444e-01 -1.26586124e-01
3.88253212e-01 -1.25489342e+00 1.18882842e-02 5.87509394e-01
-1.82266921e-01 -2.77967881e-02 2.85218418e-01 6.12607360e-01
8.27382430e-02 1.59594759e-01 8.27319086e-01 2.62072384e-01
-1.75867796e-01 3.75330836e-01 -5.84335983e-01 -6.99111149e-02
1.02423191e+00 -1.03154682e-01 -4.21387672e-01 -6.66716933e-01
-2.57403940e-01 -8.13494101e-02 3.06945801e-01 5.27526081e-01
8.11055005e-01 -1.20208836e+00 -3.47178936e-01 4.01581317e-01
-2.18817011e-01 -4.56792593e-01 4.76093560e-01 1.46149904e-01
-4.48481709e-01 9.93002877e-02 4.92140383e-01 -2.22255662e-01
-1.88827205e+00 8.92103910e-01 4.89184827e-01 -6.54225945e-02
-3.90101463e-01 6.80279911e-01 -1.70165241e-01 -5.77420592e-01
4.52303618e-01 2.24805653e-01 1.41745031e-01 -5.66188037e-01
1.08277857e+00 5.61685145e-01 1.31443739e-01 -7.64141738e-01
-4.50705826e-01 1.78402871e-01 -2.62672566e-02 -1.57269284e-01
6.33764625e-01 -4.54070598e-01 3.75796184e-02 -7.08225295e-02
1.49172950e+00 5.03240883e-01 -7.95608461e-01 -1.76520482e-01
-3.52126807e-01 -6.99598014e-01 -6.58995509e-02 -6.86797440e-01
-1.21059227e+00 7.61236131e-01 7.74972975e-01 4.42734331e-01
1.14560020e+00 -5.12347043e-01 1.46340179e+00 4.84745979e-01
4.36578453e-01 -9.88902569e-01 3.01285759e-02 2.60398567e-01
6.47535205e-01 -1.09251690e+00 -3.56642067e-01 -3.84042770e-01
-7.91101813e-01 6.59911990e-01 3.74689043e-01 3.33639145e-01
8.70452642e-01 7.01169014e-01 4.42352742e-01 5.10414302e-01
-2.69596905e-01 4.93688673e-01 1.11333095e-02 1.15174890e+00
-2.86691844e-01 2.96542406e-01 7.45079666e-02 9.13687348e-01
-4.11302298e-01 -4.70244855e-01 4.81224328e-01 6.58993840e-01
-2.20129624e-01 -1.02253485e+00 -6.24376416e-01 1.24552965e-01
-8.70673835e-01 -8.98809880e-02 -3.28863084e-01 2.06588283e-01
-2.64206141e-01 1.57756269e+00 -3.89105380e-01 -1.00029731e+00
4.03900951e-01 -3.95649701e-01 -3.58177871e-01 -2.66240954e-01
-6.38418019e-01 -1.50327697e-01 4.80559841e-02 -5.28752744e-01
1.54594362e-01 -2.94096291e-01 -1.10247600e+00 -7.20363140e-01
-4.21011090e-01 1.68041393e-01 7.05940783e-01 9.78725493e-01
5.43978989e-01 5.57260573e-01 1.38788915e+00 -4.01924849e-01
-9.43328381e-01 -6.51944697e-01 -4.98422533e-01 2.49964014e-01
5.34129620e-01 2.13174261e-02 -7.79345214e-01 -2.52236962e-01] | [13.99654483795166, 5.829981803894043] |
eb1d089a-b206-4ac7-81e6-0c5a9b26fc4d | easy-and-efficient-transformer-scalable | 2104.12470 | null | https://arxiv.org/abs/2104.12470v5 | https://arxiv.org/pdf/2104.12470v5.pdf | Easy and Efficient Transformer : Scalable Inference Solution For large NLP model | Recently, large-scale transformer-based models have been proven to be effective over various tasks across many domains. Nevertheless, applying them in industrial production requires tedious and heavy works to reduce inference costs. To fill such a gap, we introduce a scalable inference solution: Easy and Efficient Transformer (EET), including a series of transformer inference optimization at the algorithm and implementation levels. First, we design highly optimized kernels for long inputs and large hidden sizes. Second, we propose a flexible CUDA memory manager to reduce the memory footprint when deploying a large model. Compared with the state-of-the-art transformer inference library (Faster Transformer v4.0), EET can achieve an average of 1.40-4.20x speedup on the transformer decoder layer with an A100 GPU | ['Gongzheng li', 'Zeng Zhao', 'Xiaoxi Mao', 'Changjie Fan', 'Bai Liu', 'Duan Wang', 'Jingzhen Ding', 'Yadong Xi'] | 2021-04-26 | null | null | null | null | ['inference-optimization'] | ['audio'] | [-1.20348506e-01 -4.26287912e-02 -8.28724280e-02 -3.52103561e-01
-9.54196036e-01 -4.63437915e-01 2.12344870e-01 -3.80161822e-01
-7.73654506e-02 5.43897867e-01 -4.18376364e-02 -8.41015041e-01
3.14412504e-01 -1.12081754e+00 -9.20953274e-01 -4.73359317e-01
5.70090473e-01 6.21501923e-01 4.69089627e-01 -4.83194254e-02
4.09014784e-02 9.54726636e-02 -1.43407965e+00 3.18107665e-01
8.89452338e-01 1.08939016e+00 5.63964486e-01 6.50538504e-01
-1.41417056e-01 7.94382691e-01 -5.35282731e-01 -9.15746689e-01
-9.88877416e-02 -2.07579672e-01 -6.56902313e-01 -4.21280652e-01
4.47844982e-01 -7.08187401e-01 -3.54938388e-01 1.03873098e+00
8.02785516e-01 -4.46258813e-01 7.48175085e-02 -1.18793643e+00
-3.60044032e-01 1.11063063e+00 -3.46315116e-01 5.11794873e-02
3.27574126e-02 1.69407412e-01 1.09964359e+00 -8.38039398e-01
1.84000254e-01 1.21023405e+00 7.96846747e-01 1.70648932e-01
-9.21043456e-01 -1.13692164e+00 -3.56942564e-02 3.40829432e-01
-1.40625119e+00 -6.57678127e-01 3.23011965e-01 -1.37821019e-01
1.69797039e+00 2.74914712e-01 8.36412847e-01 1.05274248e+00
4.45426136e-01 1.00883508e+00 6.75086021e-01 -1.98272467e-02
3.86210456e-02 -9.28966627e-02 1.04657158e-01 1.20930886e+00
-6.84464769e-03 -2.37839818e-01 -4.73387837e-01 -1.42991066e-01
7.01474369e-01 -1.76174223e-01 2.69127548e-01 3.94441396e-01
-1.17523754e+00 7.32301891e-01 1.93467125e-01 -1.32371895e-02
-3.28498259e-02 6.03670537e-01 8.57851565e-01 2.27438241e-01
4.61065561e-01 9.01109427e-02 -5.57882190e-01 -6.26145661e-01
-9.40468252e-01 3.19602698e-01 7.77863741e-01 1.48067021e+00
7.27291048e-01 2.61875302e-01 -4.94666725e-01 8.63333762e-01
2.61669070e-01 6.46859944e-01 1.80592358e-01 -8.30512464e-01
7.51051426e-01 5.43617308e-01 -4.80703801e-01 -6.44089520e-01
-8.35109577e-02 -5.88739812e-01 -1.04709935e+00 -3.95295560e-01
1.90931559e-01 -1.14008477e-02 -5.96153915e-01 1.55739248e+00
2.70991415e-01 1.47667423e-01 -2.30908349e-01 5.69728017e-01
6.29505873e-01 9.20663536e-01 -2.63885166e-02 7.91677460e-02
1.62003708e+00 -1.50052917e+00 -9.27770436e-01 -4.53595310e-01
7.41003275e-01 -1.02007210e+00 1.19154251e+00 4.20694649e-01
-1.35089839e+00 -5.64991593e-01 -1.11087847e+00 -6.86999977e-01
-2.54646480e-01 5.74003816e-01 1.10493052e+00 6.20845616e-01
-1.01133382e+00 3.98758322e-01 -1.18285763e+00 -6.79703150e-03
3.40782106e-01 4.82251227e-01 1.61070749e-01 3.66236418e-02
-1.11643565e+00 7.77178645e-01 4.23821807e-01 3.64281535e-01
-1.02500784e+00 -9.59394574e-01 -8.29901218e-01 3.43238086e-01
2.81747401e-01 -9.88944113e-01 1.51170409e+00 -3.96293700e-01
-1.95277190e+00 6.07831717e-01 -4.88615632e-01 -4.46460575e-01
3.77178252e-01 -4.49387640e-01 -2.85483062e-01 -4.48973566e-01
-1.50098875e-01 3.62908155e-01 8.31309974e-01 -2.36005068e-01
-7.37075031e-01 -2.17245236e-01 9.38751251e-02 -1.38379008e-01
-3.47558200e-01 1.83796108e-01 -1.02207160e+00 -6.29200995e-01
-2.50299305e-01 -9.43337083e-01 1.68062840e-02 -1.13100834e-01
-6.84057236e-01 -3.04257572e-01 7.93696880e-01 -8.73158634e-01
1.62318003e+00 -1.95246863e+00 1.83865309e-01 -1.60969898e-01
4.90810186e-01 4.10097182e-01 3.21344256e-01 1.35528028e-01
4.39249188e-01 -2.69005299e-01 -1.97783187e-02 -4.53177899e-01
4.84914869e-01 3.33404124e-01 -4.22032595e-01 4.77962531e-02
-9.21041891e-02 1.22122908e+00 -7.40766585e-01 -6.90975428e-01
2.96072423e-01 4.40254807e-01 -9.94196892e-01 4.11755204e-01
-2.85812914e-01 -8.11397210e-02 -5.89202583e-01 8.24300289e-01
7.99677730e-01 -4.49342877e-01 3.93828303e-01 -5.47130167e-01
-1.39412954e-01 7.83592343e-01 -7.59780884e-01 1.82865655e+00
-8.11768532e-01 7.56720722e-01 7.44122118e-02 -7.70895004e-01
5.78763843e-01 2.87051409e-01 -5.39697520e-02 -7.19773293e-01
3.19415361e-01 3.95729154e-01 -9.87576321e-02 -1.93857491e-01
5.65902352e-01 1.98009953e-01 -2.59322971e-01 4.94594365e-01
3.58996540e-01 1.92387663e-02 1.49494410e-01 6.68895468e-02
1.10996008e+00 7.60658234e-02 7.67875016e-02 -3.82415235e-01
2.94273496e-01 -2.76175618e-01 6.20926678e-01 6.14292443e-01
2.74227530e-01 2.00867161e-01 6.31032825e-01 -4.42124873e-01
-1.07916403e+00 -1.10425436e+00 -1.07205994e-01 1.33791041e+00
-2.86433131e-01 -9.52750623e-01 -1.11483622e+00 -2.38587871e-01
-2.45423630e-01 7.67677069e-01 -5.94237410e-02 -7.20339268e-02
-7.22074986e-01 -9.19516623e-01 1.03376269e+00 8.87854993e-01
1.20035768e+00 -6.43084109e-01 -5.86742461e-01 4.16001290e-01
-2.30774909e-01 -1.33588600e+00 -6.63925827e-01 1.08676866e-01
-8.43450546e-01 -5.33490539e-01 -2.06691250e-01 -6.86035693e-01
2.73993522e-01 -2.34986946e-01 1.52716088e+00 -2.91350391e-02
-2.14189127e-01 -4.60548460e-01 9.98202339e-02 -2.59497643e-01
-3.06526810e-01 6.65000796e-01 -2.09782213e-01 -5.12739480e-01
3.26558411e-01 -6.71575725e-01 -3.30852151e-01 2.59472519e-01
-4.38234866e-01 8.63230705e-01 7.54612029e-01 8.01055729e-01
6.04336500e-01 -6.56462908e-02 8.79666582e-03 -9.70377088e-01
6.47602081e-01 -2.33195856e-01 -1.08463895e+00 5.63308418e-01
-6.80535913e-01 2.80710816e-01 8.35007548e-01 -2.81778127e-01
-1.18008792e+00 -1.07614890e-01 -7.85240054e-01 -3.59566808e-01
6.26187623e-01 2.63895273e-01 -2.99948424e-01 1.57874435e-01
3.99148874e-02 3.99923265e-01 -2.46787235e-01 -4.28613901e-01
1.69750839e-01 6.34189248e-01 3.24998975e-01 -9.02913928e-01
5.09055972e-01 -1.41138464e-01 -2.48106033e-01 -3.26545179e-01
-1.02527070e+00 1.30547300e-01 -2.14820236e-01 1.23795867e-01
8.03339183e-01 -1.24489903e+00 -1.09901667e+00 7.75055945e-01
-1.30483198e+00 -6.58231318e-01 3.19188982e-01 2.39748195e-01
-3.37167084e-01 -1.44123778e-01 -1.05137742e+00 -3.45008761e-01
-1.04837823e+00 -1.80491483e+00 1.55070627e+00 -8.25577378e-02
-8.86746645e-02 -9.39903498e-01 -1.21512592e-01 4.59307820e-01
6.97258413e-01 -3.66712362e-01 9.55634773e-01 -3.31395753e-02
-1.13556790e+00 6.53303862e-02 -4.80595022e-01 3.31400067e-01
-1.93164855e-01 5.92403412e-02 -1.08335114e+00 -2.51525342e-01
-1.65976569e-01 -2.82624990e-01 5.58701515e-01 1.26219586e-01
1.70970047e+00 -3.79823595e-01 -5.92443109e-01 1.18600154e+00
1.26519310e+00 -8.95721689e-02 7.10474968e-01 -1.26586571e-01
9.13659096e-01 -3.75943482e-01 4.14733469e-01 3.84996295e-01
5.62006593e-01 9.24459636e-01 -6.92167878e-03 -9.38572362e-02
-5.25032282e-02 -5.76454341e-01 4.52275932e-01 1.55299795e+00
-6.34522960e-02 -2.20345989e-01 -6.71400130e-01 2.83024251e-01
-1.81706977e+00 -6.62090838e-01 -2.06406415e-02 1.90961850e+00
1.06526995e+00 3.64014745e-01 -1.61771327e-01 4.70366213e-04
3.35063070e-01 1.36322886e-01 -5.94660580e-01 -7.30665028e-01
2.39241168e-01 6.27977967e-01 5.73798358e-01 4.64554310e-01
-7.28190482e-01 1.28519571e+00 7.26605034e+00 1.40862012e+00
-1.11199784e+00 4.39546824e-01 4.39167500e-01 -1.22684658e-01
-2.49594003e-01 5.05734198e-02 -1.30475283e+00 6.69454694e-01
1.28539705e+00 -1.14264391e-01 6.31777883e-01 1.08521700e+00
-2.43306398e-01 1.29693836e-01 -1.15218091e+00 1.05379903e+00
-2.58460999e-01 -1.56148744e+00 9.13242474e-02 5.40265292e-02
2.51159191e-01 1.46303847e-01 6.38439804e-02 7.22703397e-01
4.69686687e-01 -8.66469681e-01 6.92067266e-01 1.07267834e-01
9.03783500e-01 -8.75907302e-01 6.60677910e-01 1.64768726e-01
-1.54654431e+00 1.81463525e-01 -6.18492663e-01 -2.74288058e-01
3.02633524e-01 9.24243927e-01 -7.39055693e-01 2.44619682e-01
8.01745534e-01 6.70482218e-01 -4.30644274e-01 3.41157556e-01
-4.28037107e-01 7.96567202e-01 -4.57808971e-01 -1.03732653e-01
2.09146470e-01 -2.34723702e-01 -6.53403699e-02 1.37999821e+00
4.69571263e-01 -1.17638499e-01 -1.66320547e-01 9.86392915e-01
-2.27480322e-01 -3.08466673e-01 -2.62486100e-01 -1.48337726e-02
7.42952526e-01 1.32489204e+00 -3.27263355e-01 -6.33419931e-01
-4.38879371e-01 1.13961184e+00 6.76390827e-01 -4.90404889e-02
-1.63746619e+00 -3.04240137e-01 9.82469440e-01 -8.95790234e-02
2.60839790e-01 -1.93366870e-01 -3.19816977e-01 -1.31197429e+00
9.38643441e-02 -9.53749418e-01 1.67356387e-01 -8.83808911e-01
-7.23172784e-01 5.73124826e-01 -2.05710009e-01 -7.84977853e-01
-2.70298034e-01 -6.40972614e-01 -3.20829123e-01 7.51283526e-01
-1.32458353e+00 -1.32858968e+00 -2.11587191e-01 4.99622285e-01
6.42690361e-01 -1.36793599e-01 9.56324458e-01 9.03995633e-01
-9.24784541e-01 1.18626678e+00 1.64709501e-02 2.26404667e-01
3.46399933e-01 -1.09585273e+00 1.01958728e+00 7.59075940e-01
-1.63869321e-01 9.48794127e-01 4.89218950e-01 -3.03287148e-01
-2.21086073e+00 -1.23073709e+00 1.02164865e+00 -3.85772318e-01
8.40704262e-01 -8.83937538e-01 -5.90337217e-01 1.28357005e+00
3.74668628e-01 -7.90072978e-02 3.71219039e-01 3.31352293e-01
-4.88896936e-01 -4.08937931e-01 -8.46500993e-01 7.16365159e-01
1.37117851e+00 -8.32473099e-01 -5.53154387e-02 5.19442797e-01
9.07579005e-01 -1.04420924e+00 -1.25472295e+00 2.07944319e-01
8.02583396e-01 -8.33984017e-01 1.09745383e+00 -1.23915739e-01
5.44319093e-01 -1.25033483e-01 -1.93729267e-01 -1.00308037e+00
-3.08769077e-01 -7.59365618e-01 -5.11157155e-01 1.22331417e+00
4.81601924e-01 -7.69675255e-01 5.51669002e-01 3.44967484e-01
-4.59120780e-01 -9.20476735e-01 -8.33469510e-01 -4.64441419e-01
1.52405128e-02 -6.83287621e-01 8.28894973e-01 3.79268497e-01
-7.83045739e-02 7.65964091e-01 -5.60389161e-01 8.02749246e-02
6.47319674e-01 3.51245016e-01 9.56128240e-01 -6.78551316e-01
-6.21744812e-01 -3.76168370e-01 -1.57377988e-01 -1.48415089e+00
3.28413993e-01 -8.65835726e-01 -1.02933593e-01 -1.25393617e+00
4.69882816e-01 -4.79748368e-01 6.90929294e-02 6.59408510e-01
-1.60191536e-01 8.30051899e-02 -4.23657298e-02 -1.93040252e-01
-6.08388543e-01 4.82487172e-01 1.18415022e+00 -2.58025825e-01
3.97580773e-01 -9.14473981e-02 -4.59107488e-01 5.01658440e-01
6.32100761e-01 -3.33986253e-01 -5.70085227e-01 -1.28159368e+00
5.49902439e-01 -2.88089179e-02 1.49292648e-01 -9.97013569e-01
2.83818483e-01 2.66177028e-01 1.00855216e-01 -8.21134865e-01
5.12715995e-01 -5.76413929e-01 4.81005818e-01 4.01054472e-01
-7.82158598e-02 4.39299822e-01 4.21986312e-01 1.82137154e-02
-1.74294099e-01 1.12987377e-01 6.38897836e-01 -1.03882432e-01
-6.15665913e-01 3.31909895e-01 -3.29141408e-01 1.24547400e-01
6.96288168e-01 1.82372436e-01 -3.29469979e-01 9.22909379e-02
-1.89361691e-01 1.90766007e-01 9.31747630e-02 3.23316604e-01
3.98799121e-01 -1.27227223e+00 -5.02482712e-01 4.26595360e-01
-1.54859349e-01 5.28392717e-02 2.58503109e-01 8.40401113e-01
-7.71828115e-01 7.05705225e-01 -1.44449258e-02 -7.39497006e-01
-1.25577641e+00 3.98286700e-01 3.35833281e-01 -5.90966761e-01
-7.56705940e-01 8.50020409e-01 1.37987942e-01 -6.03684664e-01
3.19708623e-02 -7.96816707e-01 6.37788951e-01 -3.17630500e-01
6.47061229e-01 4.49638307e-01 4.53661859e-01 2.98646628e-03
-2.67964095e-01 5.01563191e-01 -9.43348035e-02 2.09295049e-01
1.13094985e+00 2.79849946e-01 -4.55320120e-01 1.80788755e-01
1.34234869e+00 -1.40219986e-01 -9.78383064e-01 -1.37658149e-01
-3.88293862e-01 -2.79758811e-01 3.78849506e-01 -5.94879806e-01
-1.39320004e+00 1.02324009e+00 3.57270181e-01 -2.67849892e-01
1.20119786e+00 -1.51404053e-01 1.41350925e+00 5.77172518e-01
5.99457681e-01 -1.07041264e+00 -4.95601624e-01 8.01956952e-01
4.12788808e-01 -8.21378529e-01 8.20165426e-02 -5.54726362e-01
-2.57934064e-01 9.33210433e-01 5.79644501e-01 1.25208899e-01
6.34250641e-01 1.15134943e+00 -4.32475924e-01 -1.02932096e-01
-1.15220118e+00 1.45691454e-01 -2.05652881e-02 1.23279639e-01
5.93522131e-01 3.68671268e-01 -6.85461015e-02 5.54661572e-01
-5.74396849e-01 2.28279158e-01 -2.20168978e-01 6.83853149e-01
-1.47317335e-01 -9.92400467e-01 5.06402105e-02 5.30687392e-01
-4.91152465e-01 -5.90643644e-01 1.27702087e-01 6.24786198e-01
-1.36533052e-01 5.82176745e-01 3.35978687e-01 -5.42225301e-01
1.66771784e-01 -7.56670162e-02 8.08573544e-01 -2.93837458e-01
-8.23777854e-01 3.61685157e-02 3.17981452e-01 -8.07417691e-01
1.27526432e-01 -1.88666359e-01 -1.00890529e+00 -9.49247956e-01
-2.09785223e-01 -1.78185016e-01 5.55824578e-01 1.11382866e+00
6.31616116e-01 9.04258668e-01 -2.24091485e-03 -5.51515281e-01
-4.61809933e-01 -1.07795155e+00 -3.59512091e-01 -2.38126442e-01
-2.05067173e-01 -5.90496957e-01 4.70855907e-02 -9.80904922e-02] | [8.709635734558105, 3.608332395553589] |
9c3c771e-c5c9-4acd-a3c2-a5c339b4c008 | estimating-the-frame-potential-of-large-scale | 2205.09900 | null | https://arxiv.org/abs/2205.09900v3 | https://arxiv.org/pdf/2205.09900v3.pdf | Estimating the randomness of quantum circuit ensembles up to 50 qubits | Random quantum circuits have been utilized in the contexts of quantum supremacy demonstrations, variational quantum algorithms for chemistry and machine learning, and blackhole information. The ability of random circuits to approximate any random unitaries has consequences on their complexity, expressibility, and trainability. To study this property of random circuits, we develop numerical protocols for estimating the frame potential, the distance between a given ensemble and the exact randomness. Our tensor-network-based algorithm has polynomial complexity for shallow circuits and is high-performing using CPU and GPU parallelism. We study 1. local and parallel random circuits to verify the linear growth in complexity as stated by the Brown-Susskind conjecture, and; 2. hardware-efficient ans\"atze to shed light on its expressibility and the barren plateau problem in the context of variational algorithms. Our work shows that large-scale tensor network simulations could provide important hints toward open problems in quantum information science. | ['Liang Jiang', 'Yuri Alexeev', 'Junyu Liu', 'Minzhao Liu'] | 2022-05-19 | null | null | null | null | ['tensor-networks'] | ['methodology'] | [ 2.98744231e-01 1.88562900e-01 -7.49425516e-02 -9.66127142e-02
-5.01583040e-01 -9.82873380e-01 5.07989466e-01 -1.06115816e-02
-3.36731344e-01 7.82647908e-01 -1.14853665e-01 -8.67221832e-01
-7.91626051e-02 -1.13450134e+00 -7.22608805e-01 -1.23668694e+00
-2.18777567e-01 5.15595794e-01 -1.66608505e-02 -3.35618675e-01
6.66775703e-01 4.94493425e-01 -1.07371175e+00 2.34000206e-01
7.42404222e-01 7.28339612e-01 -4.07623857e-01 1.03315234e+00
2.48183981e-01 9.18240845e-01 1.07442982e-01 -4.93232220e-01
5.18419921e-01 -9.48599637e-01 -9.30467844e-01 -8.67496192e-01
3.23239058e-01 -4.47497755e-01 -1.00291312e+00 1.50478315e+00
3.76782775e-01 7.89174289e-02 6.17361248e-01 -8.53017092e-01
-4.76576895e-01 9.93887544e-01 1.41657339e-02 3.89852077e-01
1.14356816e-01 5.24057150e-01 1.41131127e+00 -2.65344620e-01
8.12810957e-01 7.56251931e-01 4.24809247e-01 7.28059590e-01
-1.78661513e+00 -7.46991992e-01 -1.08917654e+00 3.67840737e-01
-1.50851452e+00 -3.79614294e-01 5.17764688e-01 -2.78662682e-01
1.00052154e+00 2.68246949e-01 8.67180288e-01 6.85558856e-01
5.07694483e-01 1.31951690e-01 1.19772208e+00 -5.54429233e-01
3.93844038e-01 -1.47771001e-01 1.25506163e-01 1.20290840e+00
5.82797170e-01 5.63724995e-01 -6.57246768e-01 -3.33086282e-01
6.70601308e-01 -2.24325210e-01 -3.17459553e-01 -1.54995233e-01
-1.38021159e+00 9.67041969e-01 5.51405013e-01 2.98562527e-01
1.06357280e-02 8.18388462e-01 2.74818093e-01 4.27485108e-01
-3.02608520e-01 8.93694401e-01 -1.72215611e-01 -2.63841301e-01
-7.61448264e-01 4.90425706e-01 1.08424246e+00 5.38732708e-01
1.05455732e+00 -2.34003738e-01 7.93956071e-02 -4.17695343e-01
-8.11393335e-02 8.29939604e-01 -4.54533473e-02 -1.50325537e+00
2.45536283e-01 8.38992521e-02 1.67947456e-01 -5.92761278e-01
-4.78602350e-01 -7.07910135e-02 -9.34518158e-01 7.55836368e-02
8.02445948e-01 -4.79235426e-02 -4.45288301e-01 1.58869588e+00
2.67405838e-01 -5.30386455e-02 1.57062933e-01 7.83904254e-01
5.33642292e-01 8.06855619e-01 -4.50842410e-01 -2.18532339e-01
9.48505640e-01 -3.72658223e-01 -3.20215225e-01 4.31232035e-01
1.15188420e+00 -3.79767448e-01 5.05565166e-01 2.71189392e-01
-1.07820165e+00 -1.68960452e-01 -1.18761051e+00 -3.84946406e-01
-6.39332831e-02 -4.60317612e-01 1.29082537e+00 1.17054725e+00
-9.44404721e-01 1.41852319e+00 -9.53741431e-01 3.49548236e-02
8.87922496e-02 5.37186086e-01 -1.53865099e-01 -1.43190876e-01
-8.78352463e-01 7.46519625e-01 2.64528126e-01 2.65763193e-01
-7.55819917e-01 -4.47331369e-01 -2.05881402e-01 9.61552933e-02
-3.14636081e-02 -8.29717159e-01 9.27510202e-01 -1.68686256e-01
-1.72029948e+00 6.91090822e-01 -1.52805209e-01 -4.96986657e-01
2.11658120e-01 6.70756817e-01 -4.78829071e-02 3.28717560e-01
-2.18726978e-01 3.87610227e-01 3.52384746e-02 -8.59336555e-02
2.14884698e-01 -7.02376783e-01 3.92051905e-01 -2.80103624e-01
2.52687156e-01 -5.72562099e-01 5.75813353e-01 2.98503101e-01
6.00816727e-01 -1.39681256e+00 -4.52092201e-01 -2.40809456e-01
-5.60909033e-01 -1.09118000e-01 -6.80171922e-02 1.37640804e-01
5.82303584e-01 -1.66333389e+00 2.91424066e-01 5.43448627e-01
6.17574930e-01 -7.59979859e-02 -3.00866514e-02 7.17401147e-01
1.72516033e-01 2.84217119e-01 6.72354847e-02 4.32757080e-01
2.03156173e-01 1.88847885e-01 -1.68679878e-01 9.56713676e-01
-3.02603900e-01 1.04381800e+00 -9.60281551e-01 -2.47523144e-01
7.09058344e-02 1.67370707e-01 -1.13500452e+00 -8.72599185e-02
-2.41458759e-01 6.49579287e-01 -5.29510260e-01 2.10384995e-01
6.49079442e-01 -5.13449728e-01 4.46195751e-01 -3.87699783e-01
-3.67612422e-01 7.52013147e-01 -7.73477435e-01 1.85323215e+00
-2.42608208e-02 8.61945689e-01 3.35092694e-02 -7.52348602e-01
2.36883476e-01 9.78402346e-02 1.45020366e-01 -7.67748356e-01
4.04444069e-01 5.12316883e-01 5.86002469e-01 -4.86683667e-01
6.93146527e-01 -4.76758718e-01 -2.09361576e-02 6.88861787e-01
4.23750170e-02 -6.77139997e-01 2.01144353e-01 4.62013274e-01
1.24906325e+00 -2.02601813e-02 -3.69658142e-01 -6.77714229e-01
1.14038445e-01 9.77530554e-02 -8.97183418e-02 1.24098802e+00
-1.78820387e-01 2.84237832e-01 9.32951987e-01 -5.99215209e-01
-1.60453176e+00 -9.79267061e-01 -2.78608143e-01 7.71881878e-01
4.20035154e-01 -7.54186034e-01 -7.02929914e-01 2.56608456e-01
-2.29960859e-01 6.37601852e-01 -5.34707367e-01 -2.96912938e-01
-2.44045153e-01 -9.80267823e-01 8.26393068e-01 -1.68787658e-01
4.52360779e-01 -3.05776268e-01 -3.22037220e-01 -1.23946304e-02
3.20704877e-02 -1.14366090e+00 -1.60305202e-01 3.62882137e-01
-9.37348366e-01 -1.12700021e+00 -4.92985621e-02 -6.33401796e-02
5.10059357e-01 -3.45522817e-03 7.23959088e-01 5.93813919e-02
-2.05693543e-01 -1.17696702e-01 1.60193682e-01 1.98626935e-01
-7.94464588e-01 7.35758319e-02 2.27082133e-01 -4.63372707e-01
2.85809129e-01 -7.78795362e-01 -1.02173531e+00 -8.82197693e-02
-7.02192485e-01 8.82116556e-02 2.97459215e-01 8.56854975e-01
3.06875765e-01 -2.63958275e-01 -4.50507909e-01 -7.89973259e-01
2.49751091e-01 -1.39952868e-01 -1.11686254e+00 8.43293965e-02
-5.15729427e-01 9.26202834e-01 8.66030097e-01 1.50753126e-01
-2.63906181e-01 -1.10417388e-01 -1.43953875e-01 2.01141879e-01
5.58135211e-01 2.68323421e-01 4.14283723e-01 -7.88127899e-01
8.48011017e-01 3.03283095e-01 -1.72294021e-01 2.14830413e-01
7.12976396e-01 3.71827334e-01 3.57383519e-01 -1.02534854e+00
7.70646513e-01 5.60724735e-01 9.15951788e-01 -1.05533063e+00
-9.12353694e-01 -1.69934943e-01 -5.24313569e-01 1.02206968e-01
8.52909029e-01 -6.54211581e-01 -1.77538741e+00 6.22555427e-03
-1.32289231e+00 -1.50859758e-01 -3.74890059e-01 6.23692989e-01
-5.15912235e-01 4.84010160e-01 -1.05474210e+00 -1.11639750e+00
-2.61777699e-01 -1.23764980e+00 7.34745860e-01 2.04544589e-01
2.35560030e-01 -6.32836938e-01 3.81497502e-01 4.44696873e-01
5.01686454e-01 2.60930240e-01 9.75519955e-01 -2.39464521e-01
-1.36612022e+00 -2.35987663e-01 -3.03721458e-01 -4.95388657e-02
-8.44301045e-01 3.20621487e-03 -9.07176375e-01 -2.73409128e-01
-9.93690416e-02 -6.06690943e-01 9.62928236e-01 2.63658371e-02
1.02651978e+00 -2.66314834e-01 2.57535409e-02 7.78485417e-01
1.43284178e+00 -1.68635026e-01 8.20359290e-01 -2.30113909e-01
7.59844422e-01 1.05273090e-02 -5.92551351e-01 3.00850034e-01
1.02825448e-01 2.42132217e-01 2.32596129e-01 6.65922701e-01
2.49262691e-01 -5.41238427e-01 2.95014173e-01 1.54259348e+00
-6.56202912e-01 2.03511477e-01 -4.77811277e-01 -4.15158831e-02
-1.22340894e+00 -1.46484172e+00 -5.99351168e-01 2.25898933e+00
7.08543360e-01 2.10662320e-01 -3.37145552e-02 1.92457624e-02
3.62888038e-01 1.16357923e-01 -4.34322864e-01 -6.45309985e-01
-2.04830542e-01 7.87722468e-01 1.00793374e+00 6.49871647e-01
-3.40767950e-01 7.24869311e-01 6.91516542e+00 8.15508008e-01
-9.33834791e-01 4.92302388e-01 4.90630150e-01 4.00922698e-04
-8.96242499e-01 6.38969481e-01 -5.90997517e-01 2.43908390e-01
1.28133833e+00 -1.10820673e-01 1.09168649e+00 4.17954564e-01
-1.33676454e-01 -2.67190397e-01 -1.35007977e+00 1.07876849e+00
-5.27197003e-01 -2.10879683e+00 -1.83637425e-01 4.40219581e-01
9.60114002e-01 6.06335342e-01 -8.55683759e-02 1.40148908e-01
2.89297134e-01 -1.01765680e+00 4.54523295e-01 1.70139357e-01
1.03130198e+00 -6.13580287e-01 4.79436904e-01 2.20918581e-01
-8.76827598e-01 1.78350821e-01 -7.51548231e-01 -5.74378550e-01
-4.21877623e-01 5.16595840e-01 -3.51825982e-01 3.08031607e-02
-2.76251864e-02 1.54359594e-01 3.19346674e-02 5.16782105e-01
-6.79420158e-02 6.68784678e-01 -7.44699061e-01 -9.06241596e-01
4.60736096e-01 -9.59107697e-01 3.81146103e-01 6.73284173e-01
1.94306552e-01 5.88345289e-01 -3.30724001e-01 1.54293633e+00
-3.83085877e-01 -2.13280767e-01 -5.94094694e-01 -8.02864909e-01
2.67498642e-01 1.07061100e+00 -7.85063684e-01 -1.71445563e-01
1.72689885e-01 9.43360507e-01 5.98805323e-02 1.63036883e-01
-5.99846661e-01 -6.76306129e-01 3.51000428e-01 -7.47874901e-02
2.49699384e-01 -6.61698103e-01 -4.84072953e-01 -1.78546929e+00
-1.93525270e-01 -4.04964894e-01 -2.12253168e-01 -4.72060591e-01
-7.50199020e-01 1.65155426e-01 -7.59138644e-01 -5.06166220e-01
-2.42459904e-02 -8.00382137e-01 -5.44182956e-01 7.22005963e-01
-1.09563029e+00 -4.68313724e-01 1.95602015e-01 3.31873387e-01
-5.00371575e-01 2.67268449e-01 1.04475617e+00 -6.21675439e-02
-5.89314997e-01 4.17196155e-01 9.47648823e-01 1.48476124e-01
-2.14434996e-01 -1.13669479e+00 4.77920383e-01 7.93745041e-01
4.55044657e-01 6.70426905e-01 9.11050856e-01 -2.24869773e-01
-2.69913864e+00 -4.64992911e-01 6.30344152e-01 -7.12145209e-01
1.16834164e+00 -6.45495355e-01 -2.11994633e-01 3.46134514e-01
-5.70010655e-02 2.35191479e-01 5.89815557e-01 2.18243942e-01
-6.92873478e-01 4.26294506e-02 -1.09076452e+00 3.17509145e-01
9.81403112e-01 -1.37018955e+00 1.67645097e-01 9.16438341e-01
5.07376492e-01 -4.18218493e-01 -8.45982969e-01 -3.01287115e-01
1.04267907e+00 -1.23514700e+00 6.06676519e-01 -5.17165005e-01
8.15643609e-01 -4.52851504e-02 -3.88907462e-01 -6.90286696e-01
-1.48256734e-01 -1.28984821e+00 5.98875098e-02 8.05797651e-02
6.15673423e-01 -6.75080478e-01 1.00484562e+00 7.94281483e-01
1.97689831e-01 -4.07939851e-01 -1.29309452e+00 -5.65527499e-01
5.73959231e-01 -3.60275894e-01 1.52173236e-01 8.23183477e-01
5.01264691e-01 5.48943639e-01 -2.03215986e-01 3.59977484e-02
8.70601475e-01 3.54202896e-01 5.36141157e-01 -7.98089325e-01
-6.69255376e-01 -6.27832890e-01 -6.58156574e-01 -1.19214702e+00
-1.17181748e-01 -1.41400468e+00 -2.90291697e-01 -7.19833910e-01
5.27822614e-01 -4.96660799e-01 2.60181129e-02 -2.81567723e-01
5.17580748e-01 4.39783812e-01 1.65738553e-01 2.77122349e-01
-8.88012171e-01 3.91262919e-01 1.23218095e+00 -1.69685841e-01
1.06339417e-01 -1.43008366e-01 -2.73966134e-01 8.51169974e-02
5.78567088e-01 -6.14201844e-01 7.92781785e-02 -2.12792441e-01
1.19658971e+00 4.05498117e-01 3.08348536e-01 -9.45346057e-01
4.36435252e-01 2.67967004e-02 1.21427067e-01 -2.54041314e-01
3.01489025e-01 -1.30204692e-01 1.25164405e-01 1.01768446e+00
-6.45920932e-01 -1.71758160e-01 -4.06887680e-01 5.67848802e-01
5.13231456e-01 -3.50025475e-01 8.78438890e-01 -3.86006027e-01
1.69446453e-01 3.71685177e-01 -4.31982696e-01 1.60107523e-01
5.41975796e-01 1.89932019e-01 -5.05988896e-01 -2.63711423e-01
-5.36537945e-01 -1.24173656e-01 7.08863735e-01 -7.00499356e-01
2.10878342e-01 -1.08235979e+00 -4.48822618e-01 2.43895531e-01
-2.27076232e-01 -3.72044533e-01 1.40445411e-01 9.33930635e-01
-1.27050042e+00 6.19546950e-01 1.11038983e-02 -6.06925845e-01
-4.54377025e-01 4.08639789e-01 6.89442754e-01 -1.02282444e-03
-1.63710728e-01 8.27313662e-01 -2.44279310e-01 -2.68931329e-01
-3.89489412e-01 -5.23232400e-01 8.91345739e-01 -6.84899986e-01
4.18399423e-01 5.46863019e-01 -1.03829309e-01 -3.31043273e-01
-8.48100856e-02 4.63806629e-01 2.16614708e-01 -9.67654064e-02
1.03690457e+00 1.28006384e-01 -7.74670362e-01 5.27715564e-01
1.45732379e+00 1.22770965e-01 -6.28751576e-01 -1.08217128e-01
-3.02720428e-01 -6.37680814e-02 1.82862207e-01 -1.47980958e-01
-7.28924334e-01 1.21179438e+00 4.00810212e-01 6.01622164e-01
3.36228848e-01 2.30923876e-01 1.05724597e+00 1.28570926e+00
8.18977237e-01 -7.79476702e-01 -4.93230134e-01 4.49131161e-01
-7.01025501e-02 -1.06900620e+00 4.22768630e-02 4.51506153e-02
3.37229311e-01 1.60619986e+00 -5.74255502e-03 -2.74633676e-01
4.96681720e-01 -1.11056127e-01 -7.80868769e-01 -3.74507487e-01
-5.90074480e-01 -9.23679993e-02 -8.18166062e-02 -9.27614346e-02
3.30807507e-01 6.32324994e-01 -1.39387086e-01 -2.09351391e-01
-5.83498180e-01 -1.13697104e-01 1.17850435e+00 4.31484908e-01
-5.61763287e-01 -1.01828575e+00 2.66335215e-02 3.49719375e-01
-4.10436690e-01 -4.95382011e-01 -1.93525031e-01 1.81636915e-01
6.85832351e-02 7.43994117e-01 -1.20070644e-01 -6.33966327e-01
-2.18410254e-01 -9.45722088e-02 1.41393185e+00 -1.92791730e-01
-2.43353352e-01 -5.05428195e-01 8.84489622e-03 -6.50603235e-01
-4.01723564e-01 -4.24595654e-01 -1.17106616e+00 -1.28392887e+00
-7.20730126e-01 7.37353265e-01 9.06609416e-01 1.17020583e+00
2.26924077e-01 -1.36282921e-01 6.96862161e-01 -8.16271722e-01
-9.63502109e-01 -5.79969406e-01 -6.90913498e-01 -1.42023012e-01
3.76575559e-01 1.06996447e-01 -5.83782732e-01 -7.24845231e-01] | [5.616966724395752, 4.907672882080078] |
c7ae22c8-9727-436e-b7d6-275f03fc1726 | deepkey-an-eeg-and-gait-based-dual | 1706.01606 | null | https://arxiv.org/abs/1706.01606v2 | https://arxiv.org/pdf/1706.01606v2.pdf | DeepKey: An EEG and Gait Based Dual-Authentication System | Biometric authentication involves various technologies to identify individuals by exploiting their unique, measurable physiological and behavioral characteristics. However, traditional biometric authentication systems (e.g., face recognition, iris, retina, voice, and fingerprint) are facing an increasing risk of being tricked by biometric tools such as anti-surveillance masks, contact lenses, vocoder, or fingerprint films. In this paper, we design a multimodal biometric authentication system named Deepkey, which uses both Electroencephalography (EEG) and gait signals to better protect against such risk. Deepkey consists of two key components: an Invalid ID Filter Model to block unauthorized subjects and an identification model based on attention-based Recurrent Neural Network (RNN) to identify a subject`s EEG IDs and gait IDs in parallel. The subject can only be granted access while all the components produce consistent evidence to match the user`s proclaimed identity. We implement Deepkey with a live deployment in our university and conduct extensive empirical experiments to study its technical feasibility in practice. DeepKey achieves the False Acceptance Rate (FAR) and the False Rejection Rate (FRR) of 0 and 1.0%, respectively. The preliminary results demonstrate that Deepkey is feasible, show consistent superior performance compared to a set of methods, and has the potential to be applied to the authentication deployment in real world settings. | ['Chaoran Huang', 'Lina Yao', 'Tao Gu', 'Yunhao Liu', 'Zheng Yang', 'Xiang Zhang'] | 2017-06-06 | null | null | null | null | ['gait-identification'] | ['computer-vision'] | [-3.95145155e-02 -3.62522274e-01 1.37157485e-01 -1.19487002e-01
-4.24637973e-01 -5.14527023e-01 7.16955140e-02 -1.06910042e-01
-4.89275903e-01 7.04438865e-01 -3.37509662e-01 -2.70515054e-01
-8.76850113e-02 -3.13759625e-01 -2.45702416e-01 -7.26604283e-01
-8.85359645e-02 -4.01775002e-01 -2.07826197e-01 3.06744158e-01
3.66286069e-01 6.10207796e-01 -1.39672661e+00 -1.03280075e-01
7.34112978e-01 1.33506894e+00 -3.92843097e-01 4.81402248e-01
4.99201238e-01 2.24625781e-01 -9.66500401e-01 -6.01669908e-01
1.90020978e-01 -3.07751566e-01 -4.21644151e-01 -5.48906803e-01
2.28090733e-01 -5.82147896e-01 -3.76125425e-01 1.11510599e+00
9.16143775e-01 -2.28891239e-01 2.49093011e-01 -1.47639418e+00
-6.88978672e-01 2.37680510e-01 -6.93037212e-01 2.59901404e-01
6.95318162e-01 2.43150890e-01 3.01075965e-01 -7.95930803e-01
-2.36398354e-01 7.44971633e-01 9.18789446e-01 9.76681650e-01
-1.12449753e+00 -1.24538457e+00 -2.55391717e-01 2.22035617e-01
-1.89197290e+00 -7.62543380e-01 5.34909368e-01 -1.23884425e-01
8.41541886e-01 2.50063270e-01 6.29784346e-01 1.50596476e+00
4.73743856e-01 3.30392301e-01 1.08652270e+00 -3.23119275e-02
1.77781433e-01 3.47794384e-01 4.89282012e-01 4.47512507e-01
6.21183038e-01 6.93271402e-03 -7.82855570e-01 -5.56223750e-01
7.78206825e-01 4.68269698e-02 -5.86870790e-01 3.26791763e-01
-8.82777452e-01 1.59198776e-01 -4.07973751e-02 2.78896600e-01
-6.47399426e-01 8.98984969e-02 2.20056579e-01 -5.72469505e-03
-1.63423762e-01 4.99888450e-01 -3.35818708e-01 -3.41228366e-01
-7.24439740e-01 -1.79439992e-01 8.35386515e-01 5.70524752e-01
1.93729594e-01 2.16965705e-01 -2.48336390e-01 7.17514992e-01
4.27885681e-01 1.02045131e+00 8.19744825e-01 -4.51413184e-01
1.68716565e-01 5.41490912e-01 3.05980414e-01 -1.01099455e+00
-4.42263275e-01 -1.79742083e-01 -9.27702844e-01 -1.64243147e-01
2.46899471e-01 -4.36900735e-01 -5.41887581e-01 1.78850889e+00
-9.76082459e-02 8.50308478e-01 -2.78644613e-03 6.37325585e-01
6.56071544e-01 6.24230132e-02 2.02439521e-02 -2.24263310e-01
1.56193411e+00 -1.77612656e-03 -7.95952141e-01 -1.80054307e-02
-7.97363892e-02 -5.08460462e-01 9.64293778e-01 6.09141231e-01
-1.00222778e+00 -5.65458834e-01 -1.19287682e+00 6.63369715e-01
-2.78375626e-01 3.49119693e-01 5.13140559e-01 1.69626260e+00
-1.13195336e+00 3.05688590e-01 -8.39945495e-01 -3.44631076e-01
2.58332789e-01 9.88766789e-01 -4.08748567e-01 4.31312025e-01
-1.27406383e+00 6.31346047e-01 -2.06146464e-01 5.34313023e-01
-5.42876065e-01 -3.00160110e-01 -7.39190340e-01 1.71886131e-01
-2.59937257e-01 -3.45358640e-01 8.28157663e-01 -5.38720429e-01
-1.59721351e+00 6.28776014e-01 -3.83083314e-01 -3.58444273e-01
-1.87037915e-01 -1.87111259e-01 -8.54095995e-01 1.72790870e-01
-1.70017391e-01 1.59396976e-01 1.02231967e+00 -6.28612697e-01
-1.98671624e-01 -5.82222641e-01 -3.83736581e-01 -3.92961651e-01
-9.35674310e-01 2.29449525e-01 -1.83043301e-01 -5.39049864e-01
-6.25858083e-02 -8.85048985e-01 2.75597990e-01 -5.73515952e-01
-4.55015182e-01 -5.20767644e-02 4.28079903e-01 -8.60675573e-01
1.32432127e+00 -2.24221110e+00 -4.58835393e-01 7.34168470e-01
1.07392505e-01 5.71991324e-01 -7.04405680e-02 3.66933830e-02
-8.06598365e-02 2.68523395e-01 1.15685269e-01 -2.09336475e-01
-1.56551957e-01 -3.98302257e-01 -2.25639448e-01 7.06294835e-01
1.96857393e-01 7.82353580e-01 -4.93931860e-01 1.37931928e-01
5.95570318e-02 7.08159804e-01 -1.49337426e-01 2.08022669e-01
9.49026048e-01 2.56413281e-01 -4.68026817e-01 1.02039325e+00
7.45954096e-01 -1.87411919e-01 9.80140120e-02 -1.86446115e-01
1.08307093e-01 3.82273078e-01 -1.27159405e+00 9.55978632e-01
-1.24741986e-01 5.15924335e-01 8.45289379e-02 -6.35674000e-01
9.26259577e-01 7.64359474e-01 3.86465013e-01 -7.61072636e-01
5.69134533e-01 2.62687467e-02 7.28647038e-02 -4.20367569e-01
3.88572812e-01 4.35998857e-01 2.32081302e-02 6.52873278e-01
-9.40911025e-02 7.75901318e-01 -4.70066488e-01 -9.39937308e-02
1.20937467e+00 -4.05356020e-01 7.39393979e-02 -1.64910182e-01
6.19351923e-01 -9.05968130e-01 6.02334678e-01 9.10218894e-01
-4.35400277e-01 1.26003698e-01 1.76409677e-01 -7.22507462e-02
-4.17215824e-01 -9.10185993e-01 -4.38611358e-01 2.95922428e-01
3.41821790e-01 -3.15784335e-01 -1.05524027e+00 -4.28129196e-01
1.13185339e-01 2.73904413e-01 -5.66863179e-01 -5.61160266e-01
-2.05673069e-01 -8.61037552e-01 1.28526521e+00 7.02670991e-01
8.56262565e-01 -9.77247894e-01 -6.07643843e-01 8.73870775e-02
-1.82156995e-01 -1.17986131e+00 -4.31665927e-01 -1.03214979e-01
-4.43276286e-01 -1.02127612e+00 -6.11855388e-01 -3.15681785e-01
7.13304102e-01 2.30388030e-01 4.23203528e-01 2.53807068e-01
-2.82770008e-01 7.67371953e-01 -8.80395342e-03 -4.03973103e-01
2.27393910e-01 -1.95595399e-01 9.50265825e-01 5.11592269e-01
7.76397169e-01 -4.64973211e-01 -7.97174513e-01 5.90079665e-01
-3.68186623e-01 -6.97377264e-01 2.36007631e-01 7.94167161e-01
1.85672976e-02 -1.58549920e-02 8.30826700e-01 -1.33672729e-01
9.57210958e-01 -2.50433505e-01 -4.74247903e-01 3.90952796e-01
-7.15893209e-01 -3.74303460e-01 3.35633576e-01 -8.35489810e-01
-6.47465169e-01 -2.36426264e-01 -1.60311669e-01 -1.81518555e-01
-8.93443748e-02 2.74880439e-01 -3.53424281e-01 -5.64842939e-01
4.20821518e-01 3.34264696e-01 -2.69439816e-01 -3.12184274e-01
-4.88274932e-01 1.21054888e+00 7.55909920e-01 -4.03775364e-01
6.26643002e-01 7.05270246e-02 -2.93353081e-01 -9.64772224e-01
-4.64823395e-02 -2.51227587e-01 -1.46431759e-01 -3.45031351e-01
5.04063606e-01 -8.27464461e-01 -1.78064847e+00 1.05454445e+00
-1.06927717e+00 1.10875472e-01 4.85622048e-01 7.81926155e-01
1.80853575e-01 4.15909350e-01 -8.03463519e-01 -1.35906303e+00
-8.30608189e-01 -8.93293679e-01 8.00861359e-01 7.87413955e-01
-4.06448275e-01 -3.74693960e-01 -3.12266797e-01 1.83829606e-01
5.12754738e-01 -5.90470061e-02 3.00388366e-01 -7.22418129e-01
-1.75140649e-01 -8.23343456e-01 -4.08863276e-02 3.79806012e-01
3.85070413e-01 -1.06195308e-01 -1.46114266e+00 -5.08076131e-01
3.14501196e-01 -9.34915915e-02 1.91282019e-01 3.58690798e-01
1.23076415e+00 -2.06862658e-01 -3.21947664e-01 6.00845039e-01
8.28499138e-01 6.93927705e-01 1.06423950e+00 5.16159050e-02
4.39696193e-01 2.70489901e-01 -6.06810115e-02 4.60205764e-01
2.09492922e-01 5.40590703e-01 2.16786601e-02 1.02081396e-01
4.50758249e-01 6.79302812e-02 5.95208824e-01 5.75071990e-01
-2.14264646e-01 -3.06552976e-01 -9.18550253e-01 1.59525082e-01
-1.41211319e+00 -9.53932822e-01 1.57203943e-01 2.69252300e+00
5.60274005e-01 4.66895439e-02 2.34935880e-01 4.78429943e-01
9.06496108e-01 -6.67701960e-01 -7.23452330e-01 -2.78924942e-01
-7.99516514e-02 6.45443618e-01 5.11422813e-01 -1.51998162e-01
-7.54839063e-01 5.26447594e-01 6.41487932e+00 2.38708466e-01
-1.40626144e+00 -7.67370909e-02 6.37061775e-01 -1.68441981e-02
2.91196436e-01 -5.19762337e-01 -9.70448256e-01 7.45822608e-01
1.26248574e+00 4.26495746e-02 5.76787353e-01 4.44567353e-01
1.40515566e-01 -1.55514985e-01 -9.18083131e-01 1.51607859e+00
2.84836411e-01 -8.91567528e-01 -3.60357791e-01 3.25578094e-01
3.97500023e-03 -4.27398413e-01 3.35527539e-01 1.72589257e-01
-2.44279593e-01 -1.07675302e+00 2.70096898e-01 8.45112681e-01
1.00928211e+00 -6.69892192e-01 9.30534422e-01 -5.59128150e-02
-1.18974841e+00 -1.63052544e-01 -6.44325241e-02 -7.67906085e-02
-3.25971365e-01 1.46778867e-01 -5.24603069e-01 2.98724085e-01
9.11857545e-01 3.72308969e-01 -5.63659072e-01 1.06566620e+00
-1.48259312e-01 7.90977359e-01 -3.41691375e-01 -2.23245189e-01
-3.97247136e-01 8.12702477e-02 2.34081492e-01 7.57233024e-01
4.89513487e-01 3.20011199e-01 -3.21518511e-01 6.98143661e-01
-1.79361939e-01 -1.97418302e-01 -3.64386588e-01 -7.78798983e-02
8.76125932e-01 1.18622482e+00 -7.10371137e-01 -7.87938386e-02
-2.93578297e-01 1.03480220e+00 -2.39596620e-01 5.87810814e-01
-9.28302765e-01 -8.48778725e-01 8.80912542e-01 -2.33800307e-01
-1.25976756e-01 4.84982580e-02 -4.88836169e-01 -1.28600752e+00
1.67664260e-01 -1.03908324e+00 1.06035955e-01 -7.59859681e-01
-1.25094914e+00 7.21926570e-01 -4.78411973e-01 -1.14424169e+00
-5.95897883e-02 -5.59424520e-01 -6.55071259e-01 1.48025155e+00
-9.10848916e-01 -7.46533990e-01 -4.12356108e-01 8.90886545e-01
-2.28050888e-01 -2.55688518e-01 1.16676819e+00 5.53298354e-01
-1.17694294e+00 1.42986655e+00 -2.52314419e-01 5.49460530e-01
7.14559436e-01 -6.96987152e-01 5.24753392e-01 9.24558342e-01
-2.28638485e-01 1.37342799e+00 2.39535123e-01 -7.08354473e-01
-1.73150778e+00 -4.97708917e-01 5.92173994e-01 -4.71325785e-01
4.08664882e-01 -4.94712889e-01 -9.06990469e-01 2.83079177e-01
-5.29222451e-02 -1.00099288e-01 1.05689287e+00 1.95614263e-01
-3.08595777e-01 -3.24416608e-01 -1.39100707e+00 5.79647422e-01
5.40992856e-01 -8.63408923e-01 -3.96775991e-01 -3.94961506e-01
8.37178715e-03 -1.95430696e-01 -9.54897761e-01 4.59854871e-01
1.31026113e+00 -6.40409946e-01 9.02394235e-01 -3.75162661e-01
-5.03652275e-01 -2.61928797e-01 7.74822235e-02 -8.74318779e-01
-2.24183097e-01 -9.39000547e-01 -2.05078319e-01 1.65077198e+00
2.47315407e-01 -1.10034072e+00 5.04729569e-01 1.33680367e+00
4.88055974e-01 -4.39564347e-01 -9.88407135e-01 -8.44133675e-01
-6.88102126e-01 -3.46877784e-01 8.63550007e-01 9.13850009e-01
4.33558434e-01 1.15206003e-01 -6.98041439e-01 6.46845937e-01
5.04498601e-01 -3.91723126e-01 6.74462855e-01 -1.22083068e+00
-3.14254910e-02 -3.01833719e-01 -8.39679837e-01 -6.11987650e-01
-4.26930748e-02 -4.12772954e-01 -2.47244552e-01 -7.33929455e-01
1.26230285e-01 -2.06905887e-01 -1.02929592e+00 7.75597751e-01
-1.87651753e-01 4.81799543e-01 -2.80733019e-01 -8.29955488e-02
-6.52116835e-02 2.68642634e-01 3.19599181e-01 -1.30457029e-01
-5.50359666e-01 1.49098754e-01 -8.29770029e-01 6.21969163e-01
9.60315406e-01 -2.66326100e-01 -1.24562301e-01 -2.65598316e-02
1.30105726e-02 1.15398556e-01 4.84769523e-01 -1.20049465e+00
5.21726191e-01 2.31427014e-01 9.80761707e-01 -8.27185139e-02
4.07458782e-01 -6.63538456e-01 -3.59959416e-02 5.37011683e-01
8.13874453e-02 3.79507810e-01 6.75793767e-01 2.50694066e-01
2.09071293e-01 5.15397601e-02 4.58113372e-01 4.54576403e-01
-1.57717332e-01 2.95490682e-01 -6.64106667e-01 -5.35079300e-01
7.22017288e-01 -5.56217790e-01 -5.09638250e-01 -2.64725059e-01
-3.73114735e-01 1.74402595e-01 1.49604276e-01 3.41860086e-01
1.00597131e+00 -1.11869669e+00 -3.42588633e-01 8.07513833e-01
-2.83641219e-02 -1.17075145e+00 1.58622235e-01 1.03440070e+00
1.98110402e-01 3.42587531e-01 -3.63626629e-01 -4.54112500e-01
-1.66871452e+00 2.00562447e-01 5.71486771e-01 3.83390605e-01
-4.38066065e-01 7.10053384e-01 -2.34826356e-01 1.87091708e-01
5.72751522e-01 -1.27217904e-01 -2.93052167e-01 -7.67221823e-02
1.13806915e+00 3.42517138e-01 2.57404685e-01 -4.57828254e-01
-9.46436882e-01 4.56844419e-01 3.23105641e-02 -7.08820894e-02
9.62934911e-01 -3.50041576e-02 -1.13253154e-01 9.30232555e-02
6.15517437e-01 1.38693810e-01 -6.39966726e-01 1.36768967e-01
4.86283861e-02 -4.20071602e-01 -5.44649400e-02 -8.22265744e-01
-9.63467300e-01 7.30265796e-01 1.10104299e+00 2.77632892e-01
1.29186034e+00 -6.14062667e-01 8.68676603e-01 5.22359550e-01
5.60605764e-01 -7.53328204e-01 -1.58021122e-01 1.74903959e-01
3.78185481e-01 -6.92888796e-01 -2.17059061e-01 1.10241815e-01
-3.70552331e-01 1.00166106e+00 6.29215360e-01 -1.59913953e-02
6.78488076e-01 4.50895458e-01 -5.67871146e-02 -7.95118138e-02
-5.10061085e-01 1.70899317e-01 4.87692952e-01 6.41589701e-01
3.60259026e-01 -4.73414175e-02 -1.23019919e-01 1.33674502e+00
-7.22157806e-02 9.79168788e-02 4.81633008e-01 6.34846985e-01
-7.25245550e-02 -9.04911637e-01 -6.43933892e-01 7.23722577e-01
-8.13693285e-01 -1.23476438e-01 -5.03079653e-01 4.72769886e-01
-4.12541963e-02 1.30333662e+00 -4.98388261e-02 -8.77663791e-01
3.66490066e-01 2.73169547e-01 4.25652802e-01 -2.10445553e-01
-8.94210279e-01 -3.09960395e-02 -2.60800451e-01 -7.27268875e-01
-3.79954070e-01 -6.61796153e-01 -9.50119495e-01 -4.91372108e-01
-5.64010262e-01 2.05254391e-01 7.47680008e-01 9.23199117e-01
5.29880345e-01 4.22007412e-01 7.02537775e-01 -5.43038845e-01
-2.49083057e-01 -1.08383620e+00 -7.71488667e-01 -1.15885772e-01
3.82772774e-01 -6.78645134e-01 -2.25341454e-01 -1.61943302e-01] | [13.466826438903809, 2.031203031539917] |
b0313cec-6184-4cca-a78d-192861e0e10c | mggr-multimodal-guided-gaze-redirection-with | 2004.03064 | null | https://arxiv.org/abs/2004.03064v4 | https://arxiv.org/pdf/2004.03064v4.pdf | Coarse-to-Fine Gaze Redirection with Numerical and Pictorial Guidance | Gaze redirection aims at manipulating the gaze of a given face image with respect to a desired direction (i.e., a reference angle) and it can be applied to many real life scenarios, such as video-conferencing or taking group photos. However, previous work on this topic mainly suffers of two limitations: (1) Low-quality image generation and (2) Low redirection precision. In this paper, we propose to alleviate these problems by means of a novel gaze redirection framework which exploits both a numerical and a pictorial direction guidance, jointly with a coarse-to-fine learning strategy. Specifically, the coarse branch learns the spatial transformation which warps input image according to desired gaze. On the other hand, the fine-grained branch consists of a generator network with conditional residual image learning and a multi-task discriminator. This second branch reduces the gap between the previously warped image and the ground-truth image and recovers finer texture details. Moreover, we propose a numerical and pictorial guidance module~(NPG) which uses a pictorial gazemap description and numerical angles as an extra guide to further improve the precision of gaze redirection. Extensive experiments on a benchmark dataset show that the proposed method outperforms the state-of-the-art approaches in terms of both image quality and redirection precision. The code is available at https://github.com/jingjingchen777/CFGR | ['Jiayuan Fan', 'Enver Sangineto', 'Tao Chen', 'Nicu Sebe', 'Jingjing Chen', 'Jichao Zhang'] | 2020-04-07 | null | null | null | null | ['gaze-redirection'] | ['computer-vision'] | [ 5.43887138e-01 -1.13486730e-01 -2.92292535e-02 -4.27551955e-01
-4.61467594e-01 -3.19196939e-01 5.26273072e-01 -5.43700993e-01
-1.53264105e-01 5.31703115e-01 6.82827979e-02 -3.13936472e-01
-1.68231323e-01 -7.48277187e-01 -7.31183648e-01 -1.00469291e+00
5.83439887e-01 -1.19302817e-01 1.64474919e-01 -3.72991949e-01
6.20073020e-01 2.85150200e-01 -1.71675980e+00 6.51306286e-02
1.04611254e+00 1.10927284e+00 3.44972551e-01 3.19203466e-01
5.88579290e-02 3.92482162e-01 -3.75131309e-01 -2.77483404e-01
2.28170842e-01 -6.92690849e-01 -5.09344518e-01 9.87252146e-02
6.05862796e-01 -2.42147788e-01 6.83032498e-02 1.17364883e+00
6.00003958e-01 6.36437386e-02 4.84349310e-01 -1.47343671e+00
-8.64222646e-01 2.69508678e-02 -1.29111421e+00 1.75696909e-01
5.20732820e-01 3.90247583e-01 6.54933453e-01 -7.15280473e-01
3.47002566e-01 1.16429591e+00 1.73322216e-01 7.04531372e-01
-1.36708236e+00 -1.27264118e+00 1.13243811e-01 2.91851699e-01
-1.33886719e+00 -6.79939389e-01 9.73396778e-01 -4.97780949e-01
2.23955229e-01 1.94779992e-01 3.75935823e-01 1.06093144e+00
2.71675229e-01 4.56502646e-01 1.48222709e+00 -4.62797999e-01
-9.79754259e-04 1.15541769e-02 -4.37202066e-01 7.61717081e-01
-4.83846813e-02 2.88999856e-01 -5.91651976e-01 3.06696177e-01
1.01349676e+00 3.31316069e-02 -7.93731272e-01 -5.60029924e-01
-1.14782906e+00 5.71473479e-01 7.32117176e-01 2.49647811e-01
-1.85967952e-01 -1.62838325e-01 -7.42954388e-02 1.03235729e-01
4.53289390e-01 2.92767912e-01 -4.20522578e-02 5.87647185e-02
-8.91384959e-01 6.93395883e-02 3.73509616e-01 7.15871811e-01
9.42703187e-01 -5.90451956e-02 -3.55766743e-01 8.51079643e-01
5.01542091e-01 6.95180953e-01 4.53554720e-01 -6.59556448e-01
6.43202066e-01 4.70558971e-01 1.45091722e-02 -1.31818509e+00
-2.69022077e-01 -9.69999656e-02 -9.13439214e-01 6.07320189e-01
6.32355034e-01 -1.16035536e-01 -8.65310848e-01 2.02034593e+00
5.01134574e-01 4.01865512e-01 -2.97264546e-01 1.12238717e+00
7.51989365e-01 6.42667413e-01 2.19112970e-02 -1.78630412e-01
1.39614058e+00 -9.36222255e-01 -7.55402923e-01 -3.12620521e-01
1.21176183e-01 -7.91232347e-01 1.40067255e+00 2.75975138e-01
-1.11278868e+00 -6.50969446e-01 -9.39230144e-01 -1.83225408e-01
-6.81972206e-02 3.39281559e-01 3.51764679e-01 7.07261503e-01
-1.34169698e+00 2.51777172e-01 -5.64751029e-01 -2.50128120e-01
4.61581051e-01 3.28314155e-01 -3.63325268e-01 7.16597540e-04
-9.99173880e-01 5.88157773e-01 3.94500978e-02 1.68872908e-01
-4.69764680e-01 -7.36801326e-01 -9.61012900e-01 1.03052318e-01
5.44279397e-01 -6.14689291e-01 1.02930844e+00 -1.13669038e+00
-1.98643339e+00 8.46818089e-01 -3.13792586e-01 3.06844682e-01
4.66297597e-01 5.65688834e-02 -3.66759896e-01 8.60342011e-02
1.38495296e-01 8.38568747e-01 1.33348763e+00 -1.26105785e+00
-7.70514309e-01 -5.77076197e-01 2.12360173e-01 4.54957694e-01
-4.04487312e-01 -1.31961092e-01 -7.40997732e-01 -7.83086121e-01
-2.79238336e-02 -9.20100689e-01 3.68199557e-01 1.58263922e-01
-5.55670798e-01 -1.92908630e-01 8.22438419e-01 -5.10867357e-01
1.34362626e+00 -2.12833095e+00 3.94899666e-01 1.25077322e-01
2.61139631e-01 2.12954506e-01 -1.78582400e-01 9.46288332e-02
-4.03889507e-01 2.12444998e-02 -6.82312921e-02 -3.73851418e-01
-3.55555415e-01 -4.09536302e-01 -1.88935131e-01 4.59420055e-01
1.53521627e-01 8.79456580e-01 -9.09272552e-01 -3.83806825e-01
3.06315005e-01 6.52578771e-01 -4.16593254e-01 2.50966042e-01
1.60864756e-01 8.41181457e-01 -3.37030083e-01 5.25548458e-01
9.16399002e-01 -3.39064777e-01 4.61450964e-02 -4.61232752e-01
-2.20558479e-01 6.02298714e-02 -9.24720645e-01 1.72269762e+00
-5.46899498e-01 4.75500435e-01 3.58629003e-02 -5.38333833e-01
9.65382874e-01 9.09506008e-02 2.21533373e-01 -9.15887415e-01
3.19816858e-01 2.47466788e-02 -6.72983825e-02 -4.60873395e-01
2.90015638e-01 -1.14841551e-01 1.06917024e-01 7.09467113e-01
-1.41762853e-01 1.32452827e-02 8.66940524e-03 -4.61821295e-02
4.75710273e-01 3.40987891e-01 2.86857814e-01 -1.75919980e-01
8.96600306e-01 -6.00445688e-01 4.89262640e-01 2.12980434e-01
-1.33957982e-01 8.31977963e-01 7.08097696e-01 -1.63963716e-02
-7.67509580e-01 -8.85956526e-01 -1.71719417e-02 1.11233866e+00
6.32183552e-01 -1.12233996e-01 -8.72723401e-01 -5.99591613e-01
-2.56086648e-01 6.16570234e-01 -9.28162754e-01 -2.95139879e-01
-5.31489730e-01 -4.82358158e-01 2.35709041e-01 2.89480507e-01
7.56732643e-01 -1.27233171e+00 -5.18699288e-01 -4.31675911e-01
-2.92634785e-01 -8.35175097e-01 -1.00122738e+00 -6.36690617e-01
-4.69514847e-01 -1.10524833e+00 -8.73899639e-01 -7.30934858e-01
8.96576226e-01 7.32836723e-01 6.90641344e-01 9.05701891e-03
5.50909266e-02 1.13977544e-01 -3.14505994e-01 -1.20295383e-01
-7.19687939e-02 -2.58138347e-02 -1.25876963e-01 5.37196696e-01
1.35279566e-01 -5.47015131e-01 -8.62255752e-01 5.25150955e-01
-9.71825361e-01 5.72621047e-01 6.75803244e-01 9.00022149e-01
3.22229594e-01 -7.72700831e-02 3.20571899e-01 -8.27071428e-01
7.01910853e-01 -3.69270235e-01 -7.46592522e-01 3.64071816e-01
-6.84285045e-01 -4.76842700e-03 4.49918807e-01 -3.65235656e-01
-1.35308802e+00 -2.10860163e-01 1.02452450e-01 -3.76336873e-01
-9.02739987e-02 7.23633692e-02 -4.19076949e-01 -2.69143254e-01
5.36519885e-01 2.92837441e-01 3.19626004e-01 -2.92594463e-01
2.93998063e-01 6.33075118e-01 4.50383335e-01 -3.87799412e-01
1.02192247e+00 5.21103084e-01 4.17957418e-02 -4.92610276e-01
-7.57581234e-01 -9.57421362e-02 -5.57051122e-01 -3.41869295e-01
8.52487862e-01 -7.53353238e-01 -1.17796075e+00 7.29125977e-01
-8.41993451e-01 -4.43097770e-01 2.20048979e-01 1.91913500e-01
-5.60222924e-01 3.02213252e-01 -2.19054580e-01 -3.93941104e-01
-3.74382734e-01 -1.37815511e+00 1.33816028e+00 7.05737412e-01
2.49497488e-01 -7.42025673e-01 -1.42223582e-01 4.24388528e-01
4.18981880e-01 2.28516966e-01 7.28272498e-01 1.43837422e-01
-5.93873978e-01 2.58033186e-01 -5.99806786e-01 1.56178385e-01
3.59239697e-01 -3.41755114e-02 -9.30649757e-01 -4.61279005e-01
-5.67239188e-02 -3.05077761e-01 5.72620332e-01 3.45554709e-01
1.28997886e+00 -2.90371537e-01 -3.07611018e-01 9.29895878e-01
1.26706028e+00 2.44836524e-01 8.28005850e-01 3.46459448e-01
7.99628854e-01 6.59614086e-01 7.31936753e-01 2.45101258e-01
5.46505392e-01 9.33252394e-01 3.89242023e-01 -1.40835047e-01
-3.27025890e-01 -3.03577214e-01 1.46517098e-01 2.24959940e-01
-2.02232510e-01 -2.40950927e-01 -7.75570095e-01 2.41132483e-01
-1.66061842e+00 -9.28852618e-01 1.35616064e-01 2.37009668e+00
1.02008879e+00 -9.21232849e-02 -5.84441889e-03 5.14660850e-02
9.27953005e-01 3.44201535e-01 -6.71389580e-01 2.71580601e-03
1.83473498e-01 6.89688697e-02 2.61615574e-01 4.34797287e-01
-8.81016374e-01 8.59109044e-01 4.63362598e+00 9.06450391e-01
-1.65692961e+00 6.32054135e-02 6.52076781e-01 -5.82058579e-02
-2.40615278e-01 -2.81026542e-01 -8.56337309e-01 7.73000777e-01
4.20897871e-01 -9.61498097e-02 7.15324938e-01 3.87361199e-01
2.97891885e-01 -1.80941090e-01 -8.13559830e-01 1.17852271e+00
4.25969243e-01 -1.16630924e+00 -8.97312835e-02 1.02354594e-01
5.54161906e-01 -3.85470569e-01 5.37941694e-01 -1.29121207e-02
-2.38386825e-01 -9.42599833e-01 7.35460937e-01 6.64579630e-01
1.42154288e+00 -6.72468781e-01 3.83656859e-01 1.42641887e-01
-1.00577843e+00 -7.08719417e-02 3.18616666e-02 1.48041651e-01
7.46061802e-02 2.42297441e-01 -5.97801566e-01 4.95682538e-01
8.60493362e-01 7.93766260e-01 -7.42992163e-01 8.42542887e-01
-7.16407061e-01 1.38129160e-01 -2.06007399e-02 1.15789205e-01
-1.21075585e-02 -3.65500122e-01 5.05963743e-01 6.72245681e-01
4.06930983e-01 1.09070621e-01 -2.48893589e-01 8.77814591e-01
-3.69893014e-02 -5.15578091e-02 -4.41138774e-01 3.39983165e-01
5.76270401e-01 1.49075508e+00 -5.24381578e-01 3.14475633e-02
-2.85945684e-01 9.28515732e-01 2.81098664e-01 5.51728606e-01
-8.70062113e-01 -5.88184536e-01 6.52777910e-01 2.70526171e-01
2.98897862e-01 1.06405139e-01 -2.88774639e-01 -1.21343553e+00
1.46359742e-01 -8.28024685e-01 6.14646776e-03 -1.15297568e+00
-9.71983433e-01 7.94550002e-01 3.29867285e-03 -1.33531141e+00
-2.76326716e-01 -4.97599125e-01 -7.40384519e-01 1.16813064e+00
-1.80213308e+00 -1.33259225e+00 -9.28260803e-01 8.65630805e-01
3.10587257e-01 -6.65749311e-02 5.23316741e-01 2.70074904e-01
-7.89982259e-01 9.06984985e-01 -5.90157285e-02 -1.41983964e-02
1.08049226e+00 -1.05807889e+00 1.12633780e-01 8.16506684e-01
-2.80725181e-01 5.16066611e-01 5.02965748e-01 -2.96629578e-01
-1.15472806e+00 -9.36465561e-01 6.50528491e-01 -2.01956496e-01
4.22768563e-01 -3.60604793e-01 -8.59319508e-01 5.01191497e-01
2.22889081e-01 -6.17142059e-02 3.98644954e-01 -1.05236053e-01
-3.24726671e-01 -4.82119679e-01 -1.04635835e+00 7.99257040e-01
9.40011084e-01 -4.14636850e-01 -2.03197986e-01 2.12681629e-02
3.55167896e-01 -6.76399946e-01 -4.91315037e-01 3.64884406e-01
7.24115610e-01 -1.33795631e+00 8.36055040e-01 -8.62716138e-02
5.94944835e-01 -5.52790403e-01 3.36838186e-01 -1.42264748e+00
-3.20582032e-01 -7.00553298e-01 2.05082268e-01 1.41644442e+00
-6.51943777e-03 -8.00936043e-01 4.93182033e-01 3.33502024e-01
2.27301657e-01 -9.39668775e-01 -6.93127751e-01 -3.68451476e-01
-2.58182466e-01 -8.64044577e-02 8.47710788e-01 7.06943929e-01
-1.40579149e-01 5.39869547e-01 -4.74969327e-01 9.41238627e-02
6.03335679e-01 4.27787840e-01 8.86838436e-01 -9.55480933e-01
-5.35181351e-02 -5.55172980e-01 -2.71265268e-01 -1.13892686e+00
1.09163225e-01 -4.87682313e-01 4.51712422e-02 -1.11925578e+00
8.82381126e-02 -6.06639624e-01 -1.82964936e-01 5.48165143e-01
-3.15788537e-01 6.00943029e-01 3.18133503e-01 3.02508295e-01
-3.02936822e-01 5.08961558e-01 1.69514096e+00 1.02095261e-01
-3.34700853e-01 1.65348172e-01 -1.20058167e+00 5.50773859e-01
8.09037328e-01 -2.36756861e-01 -6.08502686e-01 -5.22666991e-01
1.38543203e-01 1.79078028e-01 6.04709089e-01 -7.04390347e-01
3.20801705e-01 -2.96533972e-01 2.83403844e-01 -3.29663694e-01
3.80668908e-01 -5.31440496e-01 -5.72998114e-02 1.19867206e-01
-2.35722393e-01 -1.37088612e-01 2.09022760e-02 5.84272206e-01
-1.04266688e-01 7.52664059e-02 1.08602941e+00 3.27222973e-01
-5.27724981e-01 3.86221558e-01 3.36801052e-01 -1.32024348e-01
1.21596944e+00 -3.33825558e-01 -6.08139992e-01 -4.58055586e-01
-2.11094260e-01 1.96844950e-01 7.22363710e-01 7.61300325e-01
6.13769472e-01 -1.35282815e+00 -5.61280131e-01 5.70355833e-01
1.67355761e-01 -1.26607776e-01 4.35900867e-01 1.13792992e+00
-2.54270613e-01 3.62630695e-01 -5.49573600e-01 -7.06461668e-01
-1.25859177e+00 4.54687297e-01 2.33232468e-01 1.40519449e-02
-3.61742526e-01 7.90288150e-01 7.77344227e-01 -1.30744889e-01
3.87353562e-02 -3.01985722e-02 -5.85500181e-01 -5.69128543e-02
7.43351996e-01 1.67254999e-01 -6.47422299e-02 -9.21084404e-01
-3.05666238e-01 1.00820291e+00 -2.88658720e-02 -5.49952462e-02
1.10762548e+00 -4.72153217e-01 -1.23218186e-01 1.10939704e-01
1.14630532e+00 1.01794116e-01 -1.60566938e+00 -2.43477926e-01
-5.33580005e-01 -9.96459544e-01 8.03735554e-02 -8.12382996e-01
-1.41385698e+00 1.01449597e+00 6.73671722e-01 5.01758493e-02
1.73660266e+00 -1.79113105e-01 6.07674301e-01 -1.59447327e-01
2.24725485e-01 -4.99963671e-01 2.69309580e-01 7.18098581e-02
1.08137298e+00 -1.40206611e+00 -7.84830973e-02 -3.94289792e-01
-7.62508631e-01 1.03548896e+00 8.69035184e-01 7.90212452e-02
6.35006666e-01 -1.34467751e-01 1.32033795e-01 -8.27398300e-02
-4.27233368e-01 -1.44394740e-01 6.37071490e-01 6.42872334e-01
3.01346749e-01 -1.42205566e-01 -2.75988698e-01 2.55849361e-01
-1.89868033e-01 1.20769292e-01 3.38552624e-01 5.02118230e-01
-1.66765764e-01 -9.78468180e-01 -4.70092863e-01 2.42490008e-01
-2.40950376e-01 -1.02226302e-01 6.71911165e-02 6.98158920e-01
2.04614848e-01 1.03074586e+00 1.06392585e-01 -4.80079561e-01
3.01433563e-01 -3.37269396e-01 5.19380748e-01 -5.84074795e-01
-2.29890406e-01 1.50092617e-01 -4.98519123e-01 -7.81289160e-01
-5.65327048e-01 -5.95798492e-01 -8.30819726e-01 -3.83047223e-01
-3.30029011e-01 -1.62664160e-01 5.06338298e-01 7.26237059e-01
5.86199284e-01 5.22509515e-01 8.65842462e-01 -1.17876303e+00
-2.18510196e-01 -1.05811477e+00 -5.64200521e-01 4.04606909e-01
4.26445812e-01 -9.54010606e-01 -2.49736652e-01 1.26373470e-01] | [13.96638298034668, -0.013678831979632378] |
38397679-64be-48c4-ae0f-70c592a7c5ef | towards-arbitrary-view-face-alignment-by | 1511.06627 | null | http://arxiv.org/abs/1511.06627v1 | http://arxiv.org/pdf/1511.06627v1.pdf | Towards Arbitrary-View Face Alignment by Recommendation Trees | Learning to simultaneously handle face alignment of arbitrary views, e.g.
frontal and profile views, appears to be more challenging than we thought. The
difficulties lay in i) accommodating the complex appearance-shape relations
exhibited in different views, and ii) encompassing the varying landmark point
sets due to self-occlusion and different landmark protocols. Most existing
studies approach this problem via training multiple viewpoint-specific models,
and conduct head pose estimation for model selection. This solution is
intuitive but the performance is highly susceptible to inaccurate head pose
estimation. In this study, we address this shortcoming through learning an
Ensemble of Model Recommendation Trees (EMRT), which is capable of selecting
optimal model configuration without prior head pose estimation. The unified
framework seamlessly handles different viewpoints and landmark protocols, and
it is trained by optimising directly on landmark locations, thus yielding
superior results on arbitrary-view face alignment. This is the first study that
performs face alignment on the full AFLWdataset with faces of different views
including profile view. State-of-the-art performances are also reported on
MultiPIE and AFW datasets containing both frontaland profile-view faces. | ['Cheng Li', 'Chen Change Loy', 'Xiaoou Tang', 'Shizhan Zhu'] | 2015-11-20 | null | null | null | null | ['head-pose-estimation'] | ['computer-vision'] | [-3.19437236e-02 -6.59259483e-02 -1.65527165e-01 -6.31257117e-01
-7.46814489e-01 -5.12668192e-01 5.56884706e-01 -5.01202524e-01
-6.32055774e-02 2.24190742e-01 1.14234418e-01 9.38256904e-02
-3.11874300e-01 -2.98189729e-01 -4.20168519e-01 -6.88543141e-01
9.11489204e-02 9.26715851e-01 -3.06954775e-02 -1.21337697e-01
2.47188464e-01 8.38535786e-01 -1.99606168e+00 1.07195586e-01
5.74038208e-01 8.85087788e-01 1.47506714e-01 3.93312633e-01
1.37284905e-01 -4.63046059e-02 -3.55070055e-01 -8.89326274e-01
3.75101835e-01 5.11158817e-02 -3.96131217e-01 5.53408146e-01
1.32665992e+00 -3.29895556e-01 3.14970344e-01 7.57442653e-01
9.27267134e-01 -1.20278262e-01 6.17653728e-01 -1.36679947e+00
-2.58211881e-01 -6.16199747e-02 -8.54183793e-01 -5.19527420e-02
6.21748030e-01 -1.86464623e-01 8.47716868e-01 -1.29838693e+00
5.47414064e-01 1.38851750e+00 7.57801950e-01 7.41700470e-01
-1.17165399e+00 -7.13354528e-01 5.37644804e-01 2.91486472e-01
-1.62647390e+00 -1.11673605e+00 8.45616937e-01 -5.53167284e-01
6.61082029e-01 3.42673212e-01 6.85884118e-01 1.12399173e+00
9.38097388e-02 3.27242166e-01 1.15340817e+00 -3.98870409e-01
7.03174844e-02 4.06160764e-02 -1.80449650e-01 6.25520587e-01
1.45152450e-01 -2.66392101e-02 -7.33079851e-01 -4.77000475e-01
6.72437787e-01 -1.05735641e-02 -3.62682015e-01 -8.29372525e-01
-8.86938155e-01 6.39169872e-01 5.57071008e-02 6.97646365e-02
-2.50784576e-01 -4.60424840e-01 1.48243338e-01 1.05780818e-01
6.43699169e-01 1.53492615e-01 -6.44098997e-01 2.48400003e-01
-1.11280859e+00 2.55429685e-01 6.40252411e-01 1.13341212e+00
4.62824255e-01 -7.52822086e-02 9.54282060e-02 1.14795554e+00
7.37625957e-01 6.95194006e-01 2.33202338e-01 -8.29712570e-01
5.15110612e-01 3.80123466e-01 -5.53164966e-02 -9.49960351e-01
-7.86378801e-01 -3.02691162e-01 -6.87046945e-01 2.07877547e-01
5.43847501e-01 3.79394516e-02 -1.00596285e+00 1.90889406e+00
7.62997091e-01 3.72232348e-02 -4.10798967e-01 8.23584437e-01
1.04784989e+00 -1.21463269e-01 -3.65340970e-02 -4.77407128e-01
1.73966575e+00 -8.29504490e-01 -7.56176472e-01 -4.60523039e-01
2.10328519e-01 -1.11566663e+00 7.41417289e-01 4.65809315e-01
-1.17186177e+00 -5.43580830e-01 -8.50634336e-01 -1.73033401e-02
-6.75036460e-02 4.82772559e-01 3.79819334e-01 8.23032737e-01
-1.44960165e+00 1.58812389e-01 -7.64185309e-01 -5.04478395e-01
2.95593709e-01 8.56301129e-01 -8.05384517e-01 -1.39667271e-02
-6.27720118e-01 1.15168655e+00 -1.86194718e-01 3.89207572e-01
-3.71602386e-01 -6.09718084e-01 -8.33308995e-01 -2.59507179e-01
4.51994449e-01 -9.47849810e-01 1.08124447e+00 -7.78347552e-01
-1.70843291e+00 1.13714314e+00 -6.01504505e-01 1.90246284e-01
7.52400994e-01 -2.05113873e-01 -5.05236864e-01 -1.44264206e-01
-1.14583641e-01 4.59187299e-01 1.18229091e+00 -1.49723911e+00
-2.13163540e-01 -1.20489037e+00 -7.82021582e-02 4.51621145e-01
-1.50636509e-01 2.31245667e-01 -7.95654714e-01 -4.58765090e-01
6.62501931e-01 -1.20474851e+00 6.28821701e-02 1.46416694e-01
-2.41162732e-01 -8.26479644e-02 7.68824220e-01 -7.72073388e-01
1.17006814e+00 -1.73902082e+00 5.23548603e-01 2.30276123e-01
1.28305405e-01 1.98327005e-01 -2.10847538e-02 2.68872857e-01
-1.80101350e-01 -2.15279952e-01 2.54433930e-01 -7.74249494e-01
-1.66222081e-01 9.19515118e-02 -4.74220663e-02 6.99641466e-01
-2.78524190e-01 5.11564732e-01 -3.63606483e-01 -6.31245017e-01
1.92853794e-01 7.57930517e-01 -8.35540771e-01 2.79305756e-01
6.20233230e-02 6.85139775e-01 -1.84938058e-01 8.42182577e-01
1.11774075e+00 -9.76046547e-02 6.28848553e-01 -6.76344991e-01
1.98461842e-02 -6.36753514e-02 -1.43516493e+00 1.60438716e+00
-5.74020982e-01 1.77275017e-01 3.42278302e-01 -3.66381228e-01
7.87116766e-01 5.38493216e-01 6.13786042e-01 -2.32550651e-01
1.36439666e-01 2.35115513e-01 2.41098162e-02 -6.29108012e-01
1.79023877e-01 -6.66559041e-02 4.01754320e-01 2.65101701e-01
2.59362906e-01 -3.83426845e-02 -2.37899631e-01 -4.07933563e-01
2.79235244e-01 5.15827775e-01 4.85674888e-01 -2.22229391e-01
7.88329303e-01 -8.94167602e-01 6.05083704e-01 1.06657676e-01
-6.42426834e-02 9.84548748e-01 3.68823744e-02 -5.04826307e-01
-6.98041916e-01 -9.95627940e-01 -5.37962019e-01 1.17799163e+00
-3.31186056e-02 -5.55355072e-01 -7.99916148e-01 -6.57539308e-01
-5.20795062e-02 5.31735897e-01 -5.65714300e-01 1.73523456e-01
-8.26157928e-01 -8.15041661e-01 -2.08180435e-02 3.87352884e-01
9.60067362e-02 -5.62041819e-01 -3.59893262e-01 -1.02432482e-01
-2.07710370e-01 -1.23584116e+00 -6.98943257e-01 -3.08259547e-01
-8.51118565e-01 -1.19744587e+00 -5.94291031e-01 -4.84848082e-01
9.98661160e-01 3.87279302e-01 1.31019747e+00 5.67481108e-02
5.17393239e-02 6.23364031e-01 -9.39140320e-02 -3.33522409e-01
-1.90807115e-02 9.44710746e-02 4.23479140e-01 3.42436880e-01
3.41926575e-01 -7.07882404e-01 -6.79349422e-01 8.08355153e-01
-2.81220049e-01 -3.66662107e-02 4.08553869e-01 7.30328143e-01
5.90363860e-01 -5.16993403e-01 3.68320525e-01 -8.68691385e-01
1.65931750e-02 -3.02534193e-01 -5.89773655e-01 6.51901960e-01
-5.02804041e-01 -3.20119828e-01 2.95484930e-01 -2.70053744e-01
-1.11083531e+00 1.61679924e-01 -3.33719194e-01 -4.18571919e-01
-2.50773966e-01 -1.61819592e-01 -6.17130876e-01 -3.91968638e-01
3.85145634e-01 -1.05085425e-01 2.52570063e-01 -6.13428295e-01
1.67013958e-01 6.13574207e-01 2.10067555e-01 -6.28386021e-01
7.56131709e-01 5.48875749e-01 1.09610669e-01 -7.71494091e-01
-7.97524810e-01 -3.43499720e-01 -1.37019587e+00 -4.54358518e-01
6.96325898e-01 -8.43276083e-01 -6.72534287e-01 5.49090803e-01
-1.10396886e+00 2.14497030e-01 4.63660061e-01 4.23399538e-01
-5.90194643e-01 3.94182742e-01 -7.25432485e-02 -8.24898303e-01
-3.04057091e-01 -1.40487921e+00 1.56106722e+00 5.99963106e-02
-2.11397544e-01 -9.50527966e-01 -1.23031862e-01 6.36825800e-01
3.16247821e-01 -1.00223953e-02 5.09047031e-01 -5.17823935e-01
-4.01499718e-01 -1.58948109e-01 2.18463734e-01 -1.51932061e-01
2.65196770e-01 2.83439606e-01 -1.31839490e+00 -7.03775346e-01
1.46346420e-01 -1.39912695e-01 2.87005782e-01 5.75243115e-01
9.52394545e-01 -2.58546948e-01 -4.48584884e-01 8.45805228e-01
1.06904519e+00 4.30992618e-03 4.17483240e-01 1.41583800e-01
7.68368959e-01 9.76899385e-01 5.61581790e-01 3.97496462e-01
7.60424137e-01 1.57966828e+00 4.13939059e-01 1.42535558e-02
-1.27604693e-01 -1.10116199e-01 1.92581207e-01 6.82929277e-01
-4.62507427e-01 -3.53044160e-02 -7.81320214e-01 6.93035573e-02
-1.57585037e+00 -9.22731340e-01 2.10814536e-01 2.41973925e+00
4.34477597e-01 -4.34807032e-01 4.29637462e-01 -5.72146624e-02
6.96142256e-01 1.22868784e-01 -3.90488267e-01 -2.62790043e-02
2.16236740e-01 -1.34939790e-01 8.22839439e-02 5.31187296e-01
-1.09729457e+00 7.20277727e-01 6.17276096e+00 4.48405325e-01
-1.26788723e+00 3.05918396e-01 4.69891965e-01 -3.51518929e-01
-1.42321467e-01 -2.98472434e-01 -1.27342069e+00 3.33131492e-01
5.87375879e-01 3.66720438e-01 3.81999612e-01 7.63022184e-01
-6.35599019e-03 1.05735593e-01 -1.10145736e+00 1.21703064e+00
6.25765443e-01 -6.58953309e-01 -1.32552003e-02 3.24902892e-01
4.01145369e-01 -9.92748961e-02 2.16610387e-01 -3.77284326e-02
-2.42537886e-01 -1.01061964e+00 7.79206634e-01 3.74000877e-01
8.60121012e-01 -5.17337859e-01 4.90530670e-01 2.08849907e-01
-1.27365804e+00 -1.01912327e-01 -3.39273244e-01 4.87723261e-01
1.83109939e-01 2.13306040e-01 -7.08580017e-01 6.55590773e-01
7.04889536e-01 4.96408015e-01 -7.53564239e-01 9.62881684e-01
1.36267856e-01 -1.04614571e-01 -4.60202426e-01 6.13003552e-01
-5.37351787e-01 -3.12829107e-01 5.22784472e-01 7.03176141e-01
5.86267948e-01 -1.25522330e-01 2.05754399e-01 2.68825263e-01
2.94281393e-01 2.77017146e-01 -6.54415488e-01 7.72539079e-01
6.24856532e-01 1.51132584e+00 -5.83464682e-01 1.76447079e-01
-6.04198873e-01 6.03897989e-01 4.98217821e-01 2.30405450e-01
-7.56115317e-01 6.85059488e-01 7.33158231e-01 4.97613460e-01
3.25255960e-01 -1.32380739e-01 -7.67370015e-02 -1.37272620e+00
1.95978105e-01 -1.01876163e+00 4.48997378e-01 -5.25706112e-01
-1.21682179e+00 1.08631611e+00 3.41030985e-01 -1.50732052e+00
-2.95370042e-01 -6.04564250e-01 -3.78282249e-01 7.08555698e-01
-1.36768651e+00 -1.77742457e+00 -3.04878265e-01 5.63251853e-01
5.36773741e-01 -2.93580770e-01 9.42708850e-01 5.27334452e-01
-7.76433229e-01 1.07758892e+00 -3.05349946e-01 -4.04584974e-01
1.07043231e+00 -9.44027483e-01 1.17875047e-01 4.65237319e-01
1.93251342e-01 8.07187974e-01 6.26781225e-01 -4.25887525e-01
-1.51192641e+00 -7.85422146e-01 9.24691319e-01 -8.89291286e-01
9.12062079e-02 -4.94336098e-01 -7.31883764e-01 8.90744686e-01
-2.08374753e-04 1.40642449e-01 1.00761962e+00 4.61161375e-01
-4.53741342e-01 -2.10138991e-01 -1.27702606e+00 6.64568305e-01
1.31888556e+00 -2.60743797e-01 -2.76779383e-01 2.86236405e-01
-1.43191233e-01 -8.29199970e-01 -1.03879678e+00 6.67872131e-01
9.72555280e-01 -1.32217789e+00 1.27192354e+00 -3.56430739e-01
-2.04916432e-01 -3.83652270e-01 -2.38235176e-01 -1.23205912e+00
-3.18848938e-01 -4.97828603e-01 -1.34770617e-01 1.37855530e+00
2.27706969e-01 -7.93959200e-01 6.34202898e-01 6.51860833e-01
-2.13226434e-02 -9.76566076e-01 -1.21614218e+00 -4.09886539e-01
-2.16537997e-01 -3.75917368e-02 8.65384281e-01 7.44201839e-01
-3.81186724e-01 3.00748199e-01 -6.28567517e-01 4.72392023e-01
6.41094327e-01 2.99083531e-01 1.06634426e+00 -1.52416694e+00
-2.11631894e-01 -3.52136999e-01 -3.73130858e-01 -7.87336588e-01
4.14126515e-01 -8.05188417e-01 -2.16729477e-01 -1.05639935e+00
1.11859620e-01 -3.38543862e-01 1.51285499e-01 3.66021663e-01
-2.39198625e-01 3.07292402e-01 2.92890102e-01 3.20901632e-01
-2.19882861e-01 4.35681731e-01 1.31597745e+00 2.41389811e-01
-2.90003978e-02 3.71158868e-01 -5.95799565e-01 1.13847983e+00
5.19116640e-01 -1.51639313e-01 -6.35998905e-01 -6.10713482e-01
-9.12098140e-02 2.19652697e-01 3.12739432e-01 -7.94037938e-01
1.77656963e-01 -6.70316517e-02 6.89089239e-01 -6.83648407e-01
8.70333850e-01 -1.01344788e+00 5.17050624e-01 -3.12440116e-02
8.94306526e-02 4.47843552e-01 1.37301803e-01 4.24695522e-01
9.36250389e-02 -1.28158033e-01 9.86285090e-01 9.20891203e-03
-3.71092379e-01 6.60118639e-01 2.36236960e-01 -1.17235005e-01
9.99106705e-01 -4.65159029e-01 -3.58118378e-02 -3.03744018e-01
-9.75989878e-01 -2.12097242e-02 7.87416041e-01 5.70073187e-01
5.01224756e-01 -1.38694882e+00 -7.21642971e-01 8.07858407e-01
1.84977323e-01 -1.12933815e-01 4.83894467e-01 1.15114391e+00
-6.66193664e-02 2.10805506e-01 -2.17302680e-01 -9.07477558e-01
-1.80339003e+00 3.73862088e-01 6.00326419e-01 -8.23313743e-02
-4.39533770e-01 8.81185532e-01 2.33595818e-01 -8.11905980e-01
1.13360308e-01 3.05832207e-01 -6.95215106e-01 4.22055811e-01
5.17970264e-01 3.34194750e-01 3.91662478e-01 -1.42456722e+00
-5.56535184e-01 1.46648049e+00 -2.07297534e-01 1.25213727e-01
1.16795659e+00 -3.84282023e-01 -1.50492892e-01 -1.73514504e-02
1.04287231e+00 3.39828610e-01 -1.14932668e+00 -1.34525821e-01
-1.47566020e-01 -8.14960122e-01 -1.54682651e-01 -5.50416172e-01
-1.40204322e+00 8.09484720e-01 7.84014583e-01 -3.50729585e-01
1.03815305e+00 -1.03910334e-01 4.16079432e-01 -4.47400883e-02
8.39370966e-01 -8.32056761e-01 -1.27242118e-01 2.02271432e-01
1.28699148e+00 -1.27783680e+00 3.18547666e-01 -6.77509189e-01
-6.29528821e-01 1.20441687e+00 9.44432735e-01 3.37597638e-01
9.40738857e-01 2.48134390e-01 2.23440036e-01 -3.67249727e-01
-7.08360612e-01 4.38747108e-02 7.61421442e-01 6.28537476e-01
7.20759034e-01 -1.27511203e-01 -1.78997055e-01 2.56239802e-01
-4.27071154e-01 -1.77657485e-01 1.00491727e-02 6.77089691e-01
1.43544674e-02 -1.38684380e+00 -6.68984771e-01 5.23374379e-01
-5.34717500e-01 2.67676234e-01 -1.76633239e-01 6.97519124e-01
1.95172757e-01 9.40414548e-01 -3.21193300e-02 -3.47817987e-01
5.24837613e-01 1.77704722e-01 9.69235837e-01 -6.42744124e-01
-4.60539758e-01 4.48358089e-01 -1.26416162e-02 -5.20796061e-01
-5.96780717e-01 -9.28424835e-01 -5.75616002e-01 -2.28492931e-01
-5.64439833e-01 -1.42796829e-01 5.43346226e-01 8.05763602e-01
5.98650753e-01 5.87198474e-02 7.09668040e-01 -1.53212607e+00
-7.62250781e-01 -9.41297591e-01 -4.80224937e-01 2.97654986e-01
2.66975701e-01 -1.30852759e+00 -3.70570421e-01 -1.32608384e-01] | [13.404942512512207, 0.3428318500518799] |
e0aa01ae-c29e-4f7a-8ffa-dc549db45627 | semantic-clustering-and-convolutional-neural | null | null | https://aclanthology.org/P15-2058 | https://aclanthology.org/P15-2058.pdf | Semantic Clustering and Convolutional Neural Network for Short Text Categorization | null | ['Hong-Wei Hao', 'Cheng-Lin Liu', 'Heng Zhang', 'Bo Xu', 'Peng Wang', 'Jiaming Xu', 'Fangyuan Wang'] | 2015-07-01 | semantic-clustering-and-convolutional-neural-1 | https://aclanthology.org/P15-2058 | https://aclanthology.org/P15-2058.pdf | ijcnlp-2015-7 | ['learning-word-embeddings'] | ['methodology'] | [-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] | [-7.4483771324157715, 3.7581849098205566] |
7d0fab62-665f-4bcb-847b-e66c8e428b9f | sentence-level-subjectivity-detection-using | null | null | https://aclanthology.org/W13-1615 | https://aclanthology.org/W13-1615.pdf | Sentence-Level Subjectivity Detection Using Neuro-Fuzzy Models | null | ['Mark Clements', 'Samir Rustamov', 'Elshan Mustafayev'] | 2013-06-01 | null | null | null | ws-2013-6 | ['subjectivity-analysis'] | ['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] | [-7.278043270111084, 3.736532211303711] |
4b897728-7b34-44ef-89a4-b5947ce4bea8 | fully-convolutional-geometric-features | null | null | https://github.com/chrischoy/FCGF | https://node1.chrischoy.org/data/publications/fcgf/fcgf.pdf | Fully Convolutional Geometric Features | Extracting geometric features from 3D scans or point clouds is the first step in applications such as registration, reconstruction, and tracking. State-of-the-art methods require computing low-level features as input or extracting patch-based features with limited receptive field. In this work, we present fully-convolutional geometric features, computed in a single pass by a 3D fully-convolutional network. We also present new metric learning losses that dramatically improve performance. Fully-convolutional geometric features are compact, capture broad spatial context, and scale to large scenes. We experimentally validate our approach on both indoor and outdoor datasets. Fully-convolutional geometric features achieve state-of-the-art accuracy without requiring prepossessing, are compact (32 dimensions), and are 600 times faster than the most accurate prior method. | ['Christopher Choy', 'Vladlen Koltun', 'Jaesik Park'] | 2019-10-27 | fully-convolutional-geometric-features-1 | http://openaccess.thecvf.com/content_ICCV_2019/html/Choy_Fully_Convolutional_Geometric_Features_ICCV_2019_paper.html | http://openaccess.thecvf.com/content_ICCV_2019/papers/Choy_Fully_Convolutional_Geometric_Features_ICCV_2019_paper.pdf | international-conference-on-computer-vision | ['3d-feature-matching', '3d-point-cloud-matching', '3d-shape-representation'] | ['computer-vision', 'computer-vision', 'computer-vision'] | [ 6.68822229e-02 -2.47819215e-01 1.04454271e-01 -6.26934469e-01
-1.04809260e+00 -4.25335646e-01 6.96581066e-01 4.42481607e-01
-6.99852109e-01 2.37194419e-01 2.01037712e-02 -2.57522482e-02
-3.58180106e-01 -1.02021372e+00 -1.18121386e+00 -2.95848604e-02
-4.24633086e-01 6.14882410e-01 3.95232826e-01 8.86922255e-02
3.59924823e-01 1.38366473e+00 -1.56509054e+00 -3.57590206e-02
4.01958942e-01 1.42840636e+00 -7.68596604e-02 5.82011521e-01
-1.33252963e-02 2.60446873e-02 -2.35147402e-02 5.93938902e-02
5.46609998e-01 4.95471984e-01 -6.92707479e-01 -2.64053848e-02
1.22683263e+00 -5.72740495e-01 -6.01745546e-01 5.59973121e-01
4.55290616e-01 5.69165051e-02 6.23032451e-01 -7.10772514e-01
-6.31464541e-01 -2.58510411e-01 -4.54892337e-01 -9.39185172e-02
3.15366119e-01 -1.90134868e-02 7.83076644e-01 -1.34292316e+00
5.85632384e-01 1.22812939e+00 1.28623712e+00 1.51335761e-01
-1.23956275e+00 -4.60422784e-01 9.38838273e-02 -1.76433682e-01
-1.77919817e+00 -2.93724656e-01 6.67939544e-01 -4.61230099e-01
1.22985482e+00 1.74713507e-01 6.76394999e-01 3.55005920e-01
1.52354091e-01 3.39048833e-01 7.60400295e-01 -8.82525370e-02
7.02440664e-02 -5.62775850e-01 -2.18995646e-01 1.06957340e+00
4.21623468e-01 3.61174405e-01 -3.20110172e-01 -2.64712334e-01
1.27890003e+00 5.13350427e-01 -2.96026655e-02 -6.90047383e-01
-1.35402358e+00 8.60939801e-01 9.66620505e-01 5.54631837e-02
-5.15479386e-01 6.81936324e-01 -1.91015616e-01 2.46252358e-01
6.79766953e-01 4.44702536e-01 -6.38822377e-01 -7.09421113e-02
-9.88513529e-01 4.26341742e-01 3.68972898e-01 1.21521795e+00
1.25245428e+00 -3.86334896e-01 2.35914797e-01 4.41212952e-01
3.04466963e-01 9.75308478e-01 -7.26752207e-02 -1.09190094e+00
1.12514168e-01 6.24371290e-01 1.10501550e-01 -9.17437434e-01
-7.64866948e-01 -3.90852779e-01 -5.94970763e-01 5.42801678e-01
1.76511943e-01 1.58464134e-01 -1.22460413e+00 1.20198894e+00
5.81530154e-01 2.10039541e-01 -4.32103455e-01 8.67855310e-01
9.06082690e-01 2.61592150e-01 -4.52754527e-01 5.40451407e-01
1.02415133e+00 -5.43259203e-01 1.02228723e-01 -1.60353988e-01
5.56824803e-01 -9.57163453e-01 6.64878130e-01 1.58551764e-02
-1.00076520e+00 -5.37310779e-01 -9.94101226e-01 -5.00491023e-01
-3.14547449e-01 -3.32755074e-02 8.09071243e-01 2.54210502e-01
-1.09100461e+00 9.67473805e-01 -1.13918149e+00 -4.18577194e-01
7.00136185e-01 7.43518829e-01 -5.78687727e-01 -4.12390918e-01
-4.47323948e-01 6.72000229e-01 -2.11334363e-01 -2.12122113e-01
-5.87395430e-01 -1.12871873e+00 -1.05887890e+00 -9.00485739e-02
-1.37550920e-01 -8.11813831e-01 1.05726933e+00 -9.52181891e-02
-1.21478391e+00 9.66240168e-01 -1.56443715e-01 -2.00286582e-01
4.01589900e-01 -6.25193477e-01 -3.51041742e-02 2.36144170e-01
1.54343739e-01 7.99174666e-01 5.74502945e-01 -1.00956976e+00
-3.81976277e-01 -6.08064830e-01 4.21130471e-02 -2.97377072e-02
2.11890981e-01 -2.11502925e-01 -4.31385249e-01 -4.03284281e-01
6.75787270e-01 -1.00664163e+00 -4.98099238e-01 8.70985448e-01
-1.07599542e-01 -1.32138714e-01 9.86378491e-01 -2.54131794e-01
3.60357821e-01 -2.27755952e+00 -3.98271054e-01 3.92990261e-01
2.49933213e-01 2.41236445e-02 -2.64990717e-01 2.31120273e-01
2.95321703e-01 4.19303961e-02 -2.78963536e-01 -5.19316018e-01
1.02157466e-01 6.55942112e-02 -1.60773382e-01 9.19881225e-01
4.86103654e-01 1.09241796e+00 -7.37468302e-01 -4.18090552e-01
6.90791786e-01 9.24918711e-01 -7.21123278e-01 -4.57404256e-02
-1.21533751e-01 5.39456487e-01 -7.30369806e-01 8.13752890e-01
9.31855559e-01 -4.20642495e-01 -7.41672337e-01 -3.85912031e-01
-2.40922526e-01 4.42684889e-01 -1.09517086e+00 2.41068625e+00
-7.42901802e-01 6.58549845e-01 -1.48667768e-01 -5.54446459e-01
1.05541623e+00 -2.33550280e-01 8.63750219e-01 -5.39290130e-01
-4.62332815e-02 3.61877292e-01 -5.20966053e-01 2.52938773e-02
5.31098247e-01 1.18878908e-01 -7.38668740e-02 3.40018958e-01
4.72040325e-02 -8.33586633e-01 -3.45214635e-01 -2.42154881e-01
1.42954481e+00 3.30584437e-01 2.02187985e-01 -1.07597448e-01
1.95160851e-01 3.22289914e-02 3.05009484e-01 7.09227383e-01
2.74104655e-01 1.02282858e+00 -2.40349799e-01 -8.95235777e-01
-1.10054326e+00 -1.29618788e+00 -5.74281096e-01 5.52912712e-01
2.41419509e-01 -4.26124990e-01 -2.22107500e-01 -3.98267180e-01
5.85171342e-01 3.92155275e-02 -4.66588169e-01 2.25904226e-01
-8.19528043e-01 -1.83033086e-02 4.13896561e-01 8.43456030e-01
5.58595598e-01 -4.18697238e-01 -9.20257568e-01 3.65304828e-01
4.38227475e-01 -1.44114578e+00 -3.27996850e-01 1.21482074e-01
-1.22982061e+00 -1.09130049e+00 -4.56890553e-01 -6.49215996e-01
9.24571872e-01 4.48071063e-01 1.27306998e+00 2.73415327e-01
-6.46320760e-01 4.57361132e-01 -1.83839530e-01 -2.63489336e-01
4.00022954e-01 2.49274090e-01 -3.10298484e-02 -4.40439224e-01
3.13868374e-01 -8.89158010e-01 -7.03217506e-01 3.45941454e-01
-5.77746630e-01 -2.37013698e-01 8.01018655e-01 5.97470641e-01
1.14012384e+00 -4.46262747e-01 -2.32476026e-01 -4.38734651e-01
-1.60196111e-01 -3.12209744e-02 -9.99219477e-01 -1.95586249e-01
-2.37807155e-01 3.50872636e-01 3.02431732e-01 -5.63907400e-02
-4.93748516e-01 5.44599473e-01 -2.91942388e-01 -7.66935170e-01
-4.14016545e-01 2.93310910e-01 2.31037229e-01 -9.23187077e-01
7.95275152e-01 4.68438677e-03 -1.33459285e-01 -6.71044350e-01
4.71869439e-01 4.01046842e-01 4.26330835e-01 -8.21839511e-01
1.24670410e+00 1.00040042e+00 6.05551898e-01 -9.19091880e-01
-9.77624834e-01 -5.63399255e-01 -1.16472626e+00 1.47857472e-01
6.37311101e-01 -1.08882654e+00 -6.39067471e-01 3.20780247e-01
-1.27251577e+00 -3.71356428e-01 -5.09793580e-01 8.06747317e-01
-7.17279911e-01 -9.18431804e-02 -3.47869515e-01 -3.01804483e-01
-2.81328112e-01 -9.19017971e-01 1.77428055e+00 1.34683222e-01
8.39490518e-02 -7.27616668e-01 1.75425306e-01 -8.11889693e-02
5.83001435e-01 6.49758279e-01 5.13510406e-01 -2.22513214e-01
-1.19580817e+00 -4.16958302e-01 -5.61361611e-01 -3.88264507e-02
1.66395813e-01 -6.79600686e-02 -1.09944928e+00 -2.92608678e-01
-5.32380462e-01 -3.08363795e-01 8.99605691e-01 5.18296242e-01
1.38903511e+00 8.95579755e-02 -4.37025756e-01 1.32247889e+00
1.56121969e+00 -3.86116982e-01 4.42384779e-01 6.24900423e-02
6.98073030e-01 2.37627089e-01 6.20477855e-01 4.53700215e-01
5.20617604e-01 5.81640422e-01 6.69256687e-01 -1.78215146e-01
-2.89612144e-01 -1.42892465e-01 -2.17239290e-01 6.04534507e-01
-2.71227777e-01 3.39604616e-01 -9.10457492e-01 6.18060410e-01
-1.65152442e+00 -7.54579604e-01 -1.32447511e-01 2.22998762e+00
4.15041208e-01 1.11981280e-01 -3.79546434e-01 -2.79250532e-01
3.58546346e-01 2.56681323e-01 -6.30381465e-01 -3.91313806e-02
1.43419623e-01 8.95618260e-01 1.03910244e+00 5.02143323e-01
-1.51536441e+00 9.34234977e-01 6.51783705e+00 4.38265741e-01
-1.28163493e+00 -3.80205475e-02 2.21959025e-01 -3.23840857e-01
-1.86276957e-01 -1.16128534e-01 -8.03308845e-01 -1.47497699e-01
6.60612583e-01 2.02427119e-01 2.34193578e-01 1.16317523e+00
-2.08485991e-01 6.72197565e-02 -1.25741708e+00 1.19919908e+00
-5.42894080e-02 -1.70239854e+00 -3.05592507e-01 4.89594996e-01
7.56241977e-01 1.01921153e+00 -3.61932442e-02 -8.88401642e-03
4.24259216e-01 -1.18910980e+00 6.71660900e-01 6.05812609e-01
1.24409759e+00 -7.55645871e-01 4.93246913e-01 5.10427207e-02
-1.64402163e+00 2.91880518e-01 -7.84143746e-01 -1.53654069e-01
1.50385350e-01 1.00473189e+00 -5.49651921e-01 4.82961506e-01
8.56553555e-01 8.96367431e-01 -6.61366403e-01 1.39835536e+00
1.98561046e-02 1.66998848e-01 -1.10441411e+00 -8.00958797e-02
2.79842854e-01 2.38977119e-01 3.03404540e-01 1.05127752e+00
5.68787694e-01 2.06588611e-01 4.06389713e-01 9.28708673e-01
-2.37474680e-01 -1.46022171e-01 -8.37198734e-01 3.10134500e-01
6.56511545e-01 1.15467358e+00 -5.69363713e-01 -6.99692406e-03
-5.33301830e-01 7.99616694e-01 3.86330694e-01 -1.15515422e-02
-5.73669136e-01 -7.51431167e-01 1.12472796e+00 4.27036017e-01
6.67796195e-01 -8.88093889e-01 -4.65843856e-01 -9.82643545e-01
1.48862794e-01 4.53128777e-02 -2.41859019e-01 -5.39606690e-01
-1.19478548e+00 4.74502474e-01 -1.48257673e-01 -1.38285148e+00
-5.60860448e-02 -7.89830506e-01 -4.18061137e-01 7.38324165e-01
-1.91045284e+00 -1.43538153e+00 -8.80100071e-01 8.19788098e-01
2.29641587e-01 3.28324676e-01 9.10754800e-01 3.50852817e-01
3.06809276e-01 2.82548457e-01 5.45961708e-02 4.29226935e-01
4.76135343e-01 -1.06231797e+00 1.00483561e+00 5.10422349e-01
2.97109306e-01 6.66283607e-01 -2.37470381e-02 -5.37718892e-01
-1.56088018e+00 -1.39175177e+00 7.27565289e-01 -3.92946392e-01
2.29000881e-01 -3.50278735e-01 -5.47556281e-01 6.23547792e-01
-5.14459312e-01 9.34325814e-01 5.66205680e-01 1.99136674e-01
-6.07084572e-01 -1.67765126e-01 -1.35637510e+00 2.08951887e-02
1.62928855e+00 -7.02429771e-01 -5.56610405e-01 3.48780960e-01
8.55256796e-01 -8.89912248e-01 -1.12948954e+00 6.56258404e-01
6.60757720e-01 -7.23270893e-01 1.41065979e+00 -2.95020789e-01
7.55832270e-02 -4.18980598e-01 -4.65094924e-01 -1.02799571e+00
-5.64574659e-01 -4.93692636e-01 -3.01077142e-02 5.32103956e-01
9.30429846e-02 -4.60900515e-01 9.60986197e-01 3.08659971e-01
-5.60469747e-01 -7.44015098e-01 -1.08183205e+00 -9.89639640e-01
6.46746084e-02 -7.12482870e-01 9.28455830e-01 7.94954479e-01
-6.33053601e-01 -1.48008540e-01 2.16982931e-01 5.06299913e-01
9.81372118e-01 5.16080976e-01 1.00922298e+00 -1.78579342e+00
2.38702700e-01 -2.91361064e-01 -1.08218563e+00 -1.49038100e+00
-3.03440448e-03 -7.87886143e-01 1.35080069e-01 -1.64016354e+00
-3.72263938e-01 -8.76006901e-01 -1.19371399e-01 5.59495270e-01
3.52119297e-01 6.25689387e-01 -5.97571023e-02 3.88452858e-02
-5.17522991e-01 6.30979359e-01 1.05999124e+00 -2.50374883e-01
7.24952668e-02 -1.44737333e-01 -2.42435813e-01 8.41864467e-01
5.90878367e-01 -5.20518243e-01 4.54980694e-02 -9.00805891e-01
2.96987351e-02 -3.11053336e-01 6.88498497e-01 -1.50848746e+00
2.32069477e-01 -3.11692864e-01 8.43695343e-01 -1.09445560e+00
7.51596391e-01 -9.49793518e-01 8.22591968e-03 3.99184257e-01
7.98119307e-02 1.79482356e-01 2.58509010e-01 3.95043671e-01
2.67168880e-02 1.53239714e-02 7.82516718e-01 -1.86079025e-01
-5.31631351e-01 9.62449431e-01 3.36137593e-01 5.65982005e-03
8.03358018e-01 -3.20368022e-01 5.79134226e-02 -1.32604465e-01
-5.35002828e-01 -9.53340158e-02 8.89306366e-01 2.74738908e-01
9.95723605e-01 -1.66017723e+00 -7.22285867e-01 4.47093934e-01
2.08592489e-01 7.68841028e-01 2.52933390e-02 4.95646566e-01
-1.14613163e+00 5.02599895e-01 -1.23914391e-01 -1.11897802e+00
-9.53452826e-01 2.54691780e-01 2.59832233e-01 1.10678654e-02
-8.83501649e-01 9.22865212e-01 7.28932470e-02 -8.12188566e-01
1.57845486e-02 -7.64253318e-01 5.03617525e-01 -4.70567763e-01
3.92026454e-01 2.36265078e-01 3.96353036e-01 -6.60234153e-01
-7.19653189e-01 1.46624899e+00 1.24417134e-01 2.61463504e-02
1.77040017e+00 1.66437462e-01 1.05888158e-01 3.49865258e-02
1.52663279e+00 1.01810828e-01 -1.49348402e+00 -6.14172935e-01
-1.07360467e-01 -9.24953043e-01 4.04539317e-01 -2.36292943e-01
-1.13307750e+00 1.03121853e+00 7.55744159e-01 -3.34032685e-01
6.43528044e-01 2.76476443e-01 9.01512563e-01 7.87976801e-01
7.87579417e-01 -7.22033322e-01 3.97977494e-02 8.09734702e-01
8.72335613e-01 -1.30010819e+00 4.81141359e-01 -4.50527161e-01
2.97599971e-01 1.26916397e+00 4.56100971e-01 -7.48096883e-01
1.16544783e+00 3.26886117e-01 -2.67443150e-01 -6.22361660e-01
-2.47270688e-01 -4.91235077e-01 5.63479424e-01 7.48870552e-01
2.33593524e-01 -1.03333712e-01 2.48205617e-01 -7.98651725e-02
-3.00993413e-01 -4.42823097e-02 3.94005738e-02 1.30303717e+00
-5.86138368e-01 -8.53148639e-01 -3.62739503e-01 5.22865176e-01
-1.39023915e-01 -6.01313934e-02 -1.05228633e-01 7.16874957e-01
4.55772765e-02 4.77845401e-01 5.26317000e-01 -4.45660442e-01
5.54856837e-01 -3.66088450e-01 8.60012293e-01 -6.55827045e-01
-2.89096534e-01 -1.13112852e-01 -1.35705054e-01 -1.21072519e+00
-4.30156440e-01 -7.63130426e-01 -1.36057174e+00 -4.24581736e-01
-3.42889279e-01 -3.16042602e-01 1.10920656e+00 8.14372778e-01
8.90007734e-01 1.64244726e-01 7.27042377e-01 -1.40168095e+00
-3.06903094e-01 -7.73444355e-01 -1.84339598e-01 2.08001420e-01
5.38083196e-01 -8.30054641e-01 -1.15766771e-01 -2.16443062e-01] | [7.748584270477295, -3.2763779163360596] |
d35e7008-6b9b-418b-9838-ea9bb74a3f3d | url-a-representation-learning-benchmark-for | 2307.03810 | null | https://arxiv.org/abs/2307.03810v1 | https://arxiv.org/pdf/2307.03810v1.pdf | URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates | Representation learning has significantly driven the field to develop pretrained models that can act as a valuable starting point when transferring to new datasets. With the rising demand for reliable machine learning and uncertainty quantification, there is a need for pretrained models that not only provide embeddings but also transferable uncertainty estimates. To guide the development of such models, we propose the Uncertainty-aware Representation Learning (URL) benchmark. Besides the transferability of the representations, it also measures the zero-shot transferability of the uncertainty estimate using a novel metric. We apply URL to evaluate eleven uncertainty quantifiers that are pretrained on ImageNet and transferred to eight downstream datasets. We find that approaches that focus on the uncertainty of the representation itself or estimate the prediction risk directly outperform those that are based on the probabilities of upstream classes. Yet, achieving transferable uncertainty quantification remains an open challenge. Our findings indicate that it is not necessarily in conflict with traditional representation learning goals. Code is provided under https://github.com/mkirchhof/url . | ['Enkelejda Kasneci', 'Seong Joon Oh', 'Bálint Mucsányi', 'Michael Kirchhof'] | 2023-07-07 | null | null | null | null | ['representation-learning'] | ['methodology'] | [-7.60203972e-02 4.12785172e-01 -2.31624335e-01 -6.81860626e-01
-1.15928864e+00 -6.73151016e-01 9.14240658e-01 5.61198950e-01
-4.35195208e-01 6.74314797e-01 6.76991940e-01 -3.87212485e-01
-3.34403157e-01 -9.58017707e-01 -8.27045739e-01 -2.05739528e-01
-3.06846388e-02 5.57918966e-01 -1.27346933e-01 -2.09645219e-02
2.20606595e-01 3.06694746e-01 -1.41493213e+00 9.67909694e-02
9.69904006e-01 1.34502733e+00 -2.35942528e-01 2.92360634e-01
-1.29918382e-01 6.28833592e-01 -2.57873803e-01 -7.38175333e-01
2.90893376e-01 -8.47382396e-02 -8.63907158e-01 -6.69211566e-01
3.06828737e-01 -3.61353338e-01 -3.37769419e-01 1.13677239e+00
2.48875260e-01 2.22573474e-01 1.15640163e+00 -1.26973879e+00
-1.08560956e+00 1.14613497e+00 -1.69142157e-01 3.50120276e-01
-4.24799770e-02 4.85814326e-02 1.39446032e+00 -7.91055858e-01
6.36648834e-01 1.14193106e+00 7.03939736e-01 4.63919073e-01
-1.14386415e+00 -6.21220350e-01 8.61247256e-02 2.15654239e-01
-1.25394213e+00 -3.24959397e-01 3.78501236e-01 -6.94384813e-01
7.76284933e-01 -7.54340142e-02 6.82475194e-02 1.10381615e+00
1.50948152e-01 5.00504136e-01 9.57401812e-01 -2.36649901e-01
4.22994137e-01 3.37021083e-01 2.76367873e-01 4.80262727e-01
5.94941556e-01 5.01300275e-01 -3.07895869e-01 1.53255649e-02
4.66289490e-01 -1.11383237e-01 -2.58362085e-01 -3.70018452e-01
-9.73868251e-01 1.09774828e+00 9.11215723e-01 2.25634843e-01
-8.81508216e-02 7.53678083e-01 3.88528466e-01 1.67625830e-01
6.47831500e-01 8.41723800e-01 -5.46558738e-01 -4.74291116e-01
-8.43206763e-01 -1.48648309e-04 6.42644167e-01 8.05656672e-01
9.71493483e-01 -2.74802372e-02 -2.43773028e-01 3.88404638e-01
4.30546492e-01 6.57617599e-02 3.70031834e-01 -1.03770995e+00
4.28910255e-01 5.96380413e-01 1.07727740e-02 -8.23502183e-01
-1.11344658e-01 -3.60000312e-01 -4.06543911e-01 2.08058596e-01
2.42425770e-01 -1.75829500e-01 -9.80427623e-01 1.86896741e+00
4.05723862e-02 3.09428394e-01 7.00251833e-02 5.90087831e-01
6.27151489e-01 6.34357333e-01 1.22700810e-01 3.69166940e-01
8.90710890e-01 -6.98948205e-01 -2.72263110e-01 -4.58359234e-02
8.64218354e-01 -3.45384151e-01 9.92527306e-01 1.09604575e-01
-6.96028948e-01 -2.92595804e-01 -1.15747380e+00 -1.27675980e-01
-7.07182407e-01 -2.92417884e-01 6.55128777e-01 6.72410965e-01
-1.01178920e+00 1.11698365e+00 -8.38826358e-01 -1.57702595e-01
6.09895408e-01 4.58668992e-02 -3.71889889e-01 -2.73408979e-01
-1.38461554e+00 1.40823424e+00 6.76521838e-01 -1.12373285e-01
-9.08099949e-01 -9.52399254e-01 -9.92583275e-01 2.48788416e-01
4.82404567e-02 -5.56390584e-01 1.05391788e+00 -6.98055983e-01
-1.19980395e+00 3.43821764e-01 5.16695738e-01 -5.92892826e-01
5.49189568e-01 -2.25606143e-01 -1.70703590e-01 -2.12373227e-01
4.48654704e-02 8.39268267e-01 6.90904021e-01 -1.17861867e+00
-4.91540998e-01 -1.86321259e-01 1.88878924e-01 -3.36302482e-02
-4.26317811e-01 -1.99600488e-01 -4.67667952e-02 -4.38608378e-01
-3.42394680e-01 -6.67077005e-01 -1.99131891e-01 1.08207591e-01
-1.24218360e-01 -2.90199697e-01 3.16462606e-01 -5.59393108e-01
1.09525192e+00 -2.20217657e+00 2.61088550e-01 2.46952280e-01
8.30852166e-02 4.39109430e-02 -2.77993679e-01 3.33052456e-01
4.84614000e-02 7.12557495e-01 -5.78317523e-01 -2.58678794e-01
3.89377624e-01 1.97438881e-01 -3.50084722e-01 2.54750520e-01
6.73613310e-01 9.52996850e-01 -1.14246845e+00 -2.17566282e-01
2.16005251e-01 7.40257323e-01 -7.63072491e-01 9.43395644e-02
-2.92699128e-01 2.93985248e-01 -2.34413877e-01 4.10193771e-01
5.34974098e-01 -3.15286189e-01 -1.12198748e-01 -2.14946613e-01
1.90890253e-01 4.86046791e-01 -9.66118932e-01 1.71147752e+00
-6.53871834e-01 5.77107847e-01 -4.00793552e-01 -7.79562533e-01
8.81691039e-01 -4.71746624e-02 2.91599780e-01 -1.88401654e-01
4.02293980e-01 2.67820865e-01 1.15447216e-01 8.42722356e-02
6.94674253e-01 -1.45223305e-01 -3.00125718e-01 4.72858250e-01
4.70877379e-01 -5.05729079e-01 7.13493004e-02 3.28358024e-01
1.16908777e+00 2.75258392e-01 1.44436121e-01 -2.98148274e-01
6.56129867e-02 -1.72892064e-01 4.15434837e-01 4.20691103e-01
-2.96465367e-01 7.69175589e-01 5.01202881e-01 -6.26792312e-02
-9.10046220e-01 -1.43111658e+00 -4.73461181e-01 7.43911624e-01
-1.17248118e-01 -6.00018620e-01 -4.03808296e-01 -8.84619355e-01
4.93717879e-01 1.06708705e+00 -1.00678194e+00 -5.61777413e-01
2.53480196e-01 -3.83711249e-01 5.73005021e-01 8.68167579e-01
2.40819842e-01 -4.70252544e-01 -3.70673239e-01 5.28334267e-02
-3.98506895e-02 -8.30965340e-01 -1.56956777e-01 2.83227742e-01
-8.80041659e-01 -8.92814934e-01 -4.41421807e-01 -4.66096886e-02
5.30895352e-01 -3.38651240e-01 1.14982295e+00 -1.70323730e-01
-1.24697834e-01 6.79123938e-01 -5.61333835e-01 -6.37834430e-01
-3.88488799e-01 1.49594963e-01 4.53540608e-02 -3.79115462e-01
5.21733701e-01 -5.62217593e-01 -5.56327462e-01 9.86536499e-03
-9.27898288e-01 -4.36388731e-01 4.78411317e-01 6.92558348e-01
4.37715799e-01 -7.58037493e-02 7.93044031e-01 -6.60295904e-01
8.38511884e-01 -1.04442763e+00 -5.98918855e-01 2.37316847e-01
-1.08934319e+00 4.60419089e-01 2.00779676e-01 -3.16183828e-02
-1.08833885e+00 -2.92155206e-01 -5.80468513e-02 -4.23613638e-01
1.70606613e-01 8.86079609e-01 2.20923483e-01 1.99861392e-01
1.00858057e+00 -5.04360616e-01 -6.16113879e-02 -3.39580178e-01
9.62693274e-01 6.10916197e-01 2.40874335e-01 -9.67193305e-01
7.02867210e-01 2.69085288e-01 -3.01833004e-01 -3.59154254e-01
-8.16543281e-01 -8.75176564e-02 -6.17534220e-01 -7.54266679e-02
7.09838152e-01 -9.23418403e-01 -1.14935189e-02 -2.56536990e-01
-1.00029027e+00 -1.50438279e-01 -7.82627165e-01 6.77172422e-01
-5.03816605e-01 2.00195640e-01 -3.83425534e-01 -6.14002943e-01
-3.36970776e-01 -1.12137198e+00 8.47409070e-01 1.69102222e-01
-3.69321227e-01 -1.12355399e+00 2.44383097e-01 2.48505726e-01
8.36127341e-01 2.10897207e-01 9.88521636e-01 -8.19033384e-01
-6.68159425e-01 -3.13104242e-01 -5.71116567e-01 8.54806304e-01
1.59940749e-01 1.91541851e-01 -1.09449613e+00 2.42458805e-02
-3.98176432e-01 -5.17285764e-01 1.27733207e+00 3.09701353e-01
1.11323905e+00 -3.23852226e-02 -1.55329844e-02 5.28343379e-01
1.58264744e+00 -2.96407789e-01 7.52923131e-01 2.25470528e-01
4.28281933e-01 6.52903259e-01 4.12013113e-01 4.52499360e-01
6.25532150e-01 2.51355112e-01 5.32838643e-01 6.56169772e-01
-1.56257540e-01 -4.76006866e-01 3.21311295e-01 6.84625626e-01
-2.99714655e-02 -1.09837756e-01 -1.20341301e+00 5.67285240e-01
-1.76707315e+00 -6.67908907e-01 4.54952449e-01 2.21789575e+00
9.54801083e-01 8.62251297e-02 -2.97875315e-01 -1.83871701e-01
4.53419268e-01 2.60494873e-02 -5.71039200e-01 -6.92708492e-01
4.58928674e-01 2.85043329e-01 4.23310339e-01 5.23630142e-01
-8.56182337e-01 8.63523126e-01 5.98461103e+00 5.34493327e-01
-8.64005983e-01 1.14520267e-01 7.93367147e-01 4.55397554e-02
-8.93743873e-01 1.38032675e-01 -6.68011606e-01 4.77759600e-01
1.37365484e+00 -5.97192764e-01 3.08499515e-01 1.00329995e+00
-3.76136839e-01 3.02533004e-02 -1.51440191e+00 7.50612557e-01
-1.59147710e-01 -1.44074500e+00 2.40359068e-01 7.22493455e-02
8.48824620e-01 4.04207796e-01 3.73620927e-01 6.20602131e-01
7.66062438e-01 -1.31889021e+00 5.63877404e-01 6.90786898e-01
8.00992787e-01 -8.55970263e-01 8.53509307e-01 -8.28589648e-02
-9.22681093e-01 -8.80212709e-02 -6.64169729e-01 -4.16806005e-02
3.52485515e-02 7.53645897e-01 -9.52541232e-01 5.35012484e-01
5.86682737e-01 8.04619074e-01 -5.63898087e-01 1.06616354e+00
-4.28966373e-01 5.40720820e-01 -3.52386117e-01 1.59048975e-01
2.19262719e-01 -1.78861603e-01 2.16817752e-01 1.14480305e+00
6.69839203e-01 -2.42700905e-01 -3.26724470e-01 1.28133416e+00
-5.36719322e-01 -4.09168331e-03 -9.10545111e-01 -6.63947463e-01
6.33157790e-01 1.05311370e+00 -3.61972958e-01 -1.19895987e-01
-3.11398983e-01 6.85245395e-01 5.64614058e-01 1.03731155e-01
-8.07366192e-01 -4.00564641e-01 9.78976905e-01 -2.20261425e-01
1.87003523e-01 -2.60656834e-01 -3.71559441e-01 -1.29088867e+00
-2.71166146e-01 -5.16703606e-01 4.51327324e-01 -6.19349062e-01
-1.65526879e+00 5.57141602e-01 2.43812174e-01 -9.94847596e-01
-5.47710359e-01 -7.20674396e-01 -5.82090259e-01 8.48498225e-01
-1.81065214e+00 -1.02947915e+00 -1.75360322e-01 2.20926180e-01
1.89540297e-01 2.77418699e-02 8.88078988e-01 1.28769726e-01
-3.95909309e-01 5.06322563e-01 1.59943968e-01 6.78923950e-02
7.29107440e-01 -1.24484777e+00 3.08861494e-01 8.25150311e-01
2.37016320e-01 7.05000579e-01 6.62222564e-01 -4.74735588e-01
-9.74543095e-01 -1.26886570e+00 5.95918059e-01 -1.06729221e+00
9.25921679e-01 -4.76922803e-02 -8.19133222e-01 9.11524534e-01
7.01651582e-03 1.91836417e-01 8.01152825e-01 4.01283711e-01
-8.32107008e-01 -1.97455473e-02 -1.21300697e+00 2.17133731e-01
8.76453519e-01 -7.02278435e-01 -8.60899866e-01 -4.20683296e-03
9.84130561e-01 -9.66110229e-02 -1.24726403e+00 5.80000758e-01
4.02929097e-01 -8.17682624e-01 7.89997816e-01 -7.36983836e-01
8.27094138e-01 -6.71512075e-03 -6.02290332e-01 -1.73674607e+00
-2.48348236e-01 1.29823908e-02 -2.37784073e-01 1.33437300e+00
8.42196941e-01 -8.31876457e-01 5.33650339e-01 1.20331526e+00
-1.40268818e-01 -6.58746839e-01 -9.21351612e-01 -1.02105033e+00
8.06181192e-01 -7.29085565e-01 7.79473007e-01 8.58780265e-01
1.96803689e-01 1.52072325e-01 2.16359980e-02 4.99148406e-02
6.31160319e-01 -2.70346999e-01 3.42443198e-01 -1.50541091e+00
-9.08328444e-02 -5.37791133e-01 -9.17790830e-01 -5.45215070e-01
2.77113527e-01 -1.29326272e+00 -7.47285783e-02 -1.85936308e+00
8.29734281e-02 -6.86708868e-01 -7.88624883e-01 3.71863008e-01
3.42665724e-02 -1.02263063e-01 2.60329157e-01 -9.14776549e-02
-2.71920145e-01 7.67530441e-01 6.70756161e-01 -2.07382172e-01
1.62363723e-01 -2.46771693e-01 -1.10144794e+00 5.97563922e-01
9.96567667e-01 -4.04724985e-01 -6.61088347e-01 -6.17924452e-01
6.00110471e-01 -5.76267183e-01 2.13282555e-01 -1.11894345e+00
9.64730307e-02 -4.09787595e-02 2.46806800e-01 -1.06550917e-01
3.70297253e-01 -8.28081250e-01 -9.17261913e-02 1.95256799e-01
-6.21183872e-01 -4.74673584e-02 3.39684188e-01 8.63163054e-01
-2.21981049e-01 -4.66951132e-01 6.23440266e-01 -1.15024790e-01
-8.91796410e-01 4.25101846e-01 8.09739456e-02 2.66653955e-01
1.01259029e+00 1.98960692e-01 -5.48945010e-01 -3.70454699e-01
-4.87938136e-01 2.36878082e-01 5.27106524e-01 5.86938679e-01
7.21962094e-01 -1.40371490e+00 -7.63641596e-01 -1.15557842e-01
4.61087376e-01 -1.04111135e-01 -6.21059239e-02 4.10724670e-01
-2.50894636e-01 4.39489663e-01 -2.35777035e-01 -3.01242828e-01
-5.04322946e-01 4.03847933e-01 3.48152816e-01 -1.15864977e-01
-2.84592807e-01 1.08720088e+00 -1.07099794e-01 -6.74638271e-01
1.98153064e-01 -7.53451824e-01 -4.96959351e-02 3.07814181e-01
4.81583118e-01 3.97296369e-01 -1.82621181e-02 -3.16973954e-01
-2.99651295e-01 1.32586628e-01 -5.57077937e-02 -3.02175313e-01
1.49442637e+00 9.36913863e-02 5.62443919e-02 6.29036307e-01
1.37678397e+00 -3.50354731e-01 -1.26124215e+00 -2.28269339e-01
2.49590755e-01 -7.45536208e-01 3.55213851e-01 -9.50717151e-01
-9.50530410e-01 1.11428726e+00 6.15842104e-01 -1.19749866e-01
6.17703974e-01 1.16498590e-01 4.03168857e-01 3.28142554e-01
6.26639962e-01 -1.12177384e+00 7.78568834e-02 5.97827852e-01
1.07783425e+00 -1.38144338e+00 -1.63968261e-02 7.47277588e-02
-6.49810851e-01 1.02281737e+00 5.61803877e-01 -8.20555538e-02
1.06888402e+00 1.45517856e-01 -2.07511172e-01 -8.38082060e-02
-8.73920262e-01 -3.86618257e-01 3.94586354e-01 7.52163827e-01
6.10934973e-01 1.52772993e-01 -7.34763220e-02 7.00143874e-01
-1.18883595e-01 2.09684297e-01 5.61649024e-01 6.59109652e-01
-4.62289006e-01 -1.10205841e+00 1.56585291e-01 8.73274565e-01
-9.71449018e-02 -3.25399131e-01 -2.77923733e-01 5.29714048e-01
-4.53336835e-02 7.67153859e-01 5.68058528e-02 -6.77724957e-01
1.19844243e-01 2.40700349e-01 3.93791139e-01 -8.82866323e-01
-1.36433542e-01 -1.00379002e+00 2.87402183e-01 -5.80566168e-01
6.92829192e-02 -4.98040259e-01 -1.18042505e+00 -3.63129258e-01
-4.08271074e-01 2.53375947e-01 1.01583672e+00 6.57549739e-01
7.12430894e-01 4.34627354e-01 3.25913608e-01 -7.03041375e-01
-1.16881216e+00 -1.03123319e+00 -4.25937682e-01 2.43568391e-01
1.04269780e-01 -9.42037523e-01 -6.46479368e-01 -3.62930804e-01] | [9.446083068847656, 3.3209407329559326] |
004ac58a-848a-4292-8a4e-8d290b58f72f | on-the-role-of-seed-lexicons-in-learning | null | null | https://aclanthology.org/P16-1024 | https://aclanthology.org/P16-1024.pdf | On the Role of Seed Lexicons in Learning Bilingual Word Embeddings | null | ["Ivan Vuli{\\'c}", 'Anna Korhonen'] | 2016-08-01 | null | null | null | acl-2016-8 | ['cross-lingual-entity-linking'] | ['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] | [-7.245156764984131, 3.7968530654907227] |
ef1f3c1c-8543-4812-a533-ed17e03f4057 | boosting-weakly-supervised-object-detection-2 | 2303.10937 | null | https://arxiv.org/abs/2303.10937v1 | https://arxiv.org/pdf/2303.10937v1.pdf | Boosting Weakly Supervised Object Detection using Fusion and Priors from Hallucinated Depth | Despite recent attention and exploration of depth for various tasks, it is still an unexplored modality for weakly-supervised object detection (WSOD). We propose an amplifier method for enhancing the performance of WSOD by integrating depth information. Our approach can be applied to any WSOD method based on multiple-instance learning, without necessitating additional annotations or inducing large computational expenses. Our proposed method employs a monocular depth estimation technique to obtain hallucinated depth information, which is then incorporated into a Siamese WSOD network using contrastive loss and fusion. By analyzing the relationship between language context and depth, we calculate depth priors to identify the bounding box proposals that may contain an object of interest. These depth priors are then utilized to update the list of pseudo ground-truth boxes, or adjust the confidence of per-box predictions. Our proposed method is evaluated on six datasets (COCO, PASCAL VOC, Conceptual Captions, Clipart1k, Watercolor2k, and Comic2k) by implementing it on top of two state-of-the-art WSOD methods, and we demonstrate a substantial enhancement in performance. | ['Adriana Kovashka', 'Cagri Gungor'] | 2023-03-20 | null | null | null | null | ['weakly-supervised-object-detection', 'multiple-instance-learning'] | ['computer-vision', 'methodology'] | [ 1.04612619e-01 1.20167963e-01 -4.71828543e-02 -3.45556676e-01
-9.76738632e-01 -4.07585651e-01 6.18127108e-01 2.56370991e-01
-7.44061947e-01 6.52853966e-01 7.49657080e-02 1.80626720e-01
3.05718660e-01 -6.69628441e-01 -8.02489460e-01 -6.60723567e-01
3.01002264e-01 4.96839643e-01 9.52634394e-01 2.00019032e-02
3.68400335e-01 6.30765975e-01 -1.55097556e+00 4.35276002e-01
7.52201676e-01 1.37505305e+00 4.08104807e-01 3.87729168e-01
-2.73595750e-01 8.14247787e-01 -5.26109636e-01 -4.93937641e-01
3.34588617e-01 -6.38561845e-02 -5.76436579e-01 1.63123757e-01
7.76558161e-01 -4.02011901e-01 -2.72616684e-01 1.04597807e+00
5.53710699e-01 2.75409490e-01 7.28149951e-01 -1.11186790e+00
-3.07044446e-01 2.89205819e-01 -7.26276994e-01 2.41763115e-01
2.98770607e-01 1.19145140e-01 8.95344257e-01 -1.26827276e+00
7.17399120e-01 1.54640186e+00 3.30562383e-01 6.12664759e-01
-1.07592845e+00 -6.48064494e-01 4.89728302e-01 2.44775817e-01
-1.28951430e+00 -4.01768118e-01 9.60066199e-01 -4.18323308e-01
7.45654762e-01 -2.02167198e-01 6.15225971e-01 9.75433469e-01
-1.98817864e-01 1.22941709e+00 9.19896543e-01 -4.84457046e-01
3.97420764e-01 3.31695735e-01 -5.41004352e-02 9.40025210e-01
1.32526025e-01 7.52154272e-03 -7.62918770e-01 1.26025197e-03
5.22613943e-01 -1.59059778e-01 -5.73085062e-02 -6.97077453e-01
-1.19709003e+00 6.84096754e-01 7.36136734e-01 -2.44335771e-01
-1.65070891e-02 9.05037895e-02 2.84159273e-01 -3.75727296e-01
6.72124803e-01 3.15651029e-01 -2.70177633e-01 2.01571256e-01
-8.64481807e-01 4.46152329e-01 4.45126384e-01 9.66957748e-01
8.87388527e-01 -3.05582166e-01 -2.46097550e-01 7.61773229e-01
4.74011898e-01 4.26408798e-01 2.97459304e-01 -8.53212118e-01
7.52712548e-01 8.29920769e-01 3.49055618e-01 -9.01745677e-01
-3.47930402e-01 -1.74629062e-01 -3.97768408e-01 3.14479291e-01
4.52941418e-01 -4.06075269e-02 -1.03631318e+00 1.34036911e+00
6.88591957e-01 4.79182638e-02 4.47444133e-02 1.17220855e+00
8.39017749e-01 7.60201097e-01 1.02630168e-01 1.65011197e-01
1.18071973e+00 -1.39965928e+00 -3.73956144e-01 -6.30947053e-01
4.03035253e-01 -5.99907577e-01 1.02682340e+00 5.89540184e-01
-9.99843299e-01 -6.04014575e-01 -1.10419583e+00 -3.49170536e-01
-4.24961686e-01 4.31911975e-01 4.71272767e-01 3.19585890e-01
-7.09680438e-01 3.23255837e-01 -8.39485466e-01 -1.70298457e-01
7.46934652e-01 1.21811599e-01 -1.63823351e-01 -2.18143448e-01
-8.21750402e-01 9.23031092e-01 6.30287468e-01 1.21581279e-01
-1.28892708e+00 -5.35711944e-01 -1.11037910e+00 -2.54421324e-01
5.20051599e-01 -4.38410223e-01 1.17277694e+00 -8.10647011e-01
-1.32485759e+00 8.93022299e-01 -1.46973595e-01 -3.76213998e-01
8.28413606e-01 -4.04060811e-01 -1.22413158e-01 4.03902739e-01
1.80942446e-01 1.33926535e+00 7.84317374e-01 -1.44044197e+00
-8.66769850e-01 -5.86554110e-01 2.19627842e-01 5.52079976e-01
-1.67753935e-01 -1.09229602e-01 -8.03346455e-01 -5.73933363e-01
5.14637053e-01 -7.99857199e-01 -2.00285852e-01 8.80326986e-01
-5.31914353e-01 -2.89569676e-01 7.68243372e-01 -4.17779237e-01
8.07012022e-01 -2.24983478e+00 2.39794135e-01 -9.90520492e-02
4.47037518e-02 9.72570255e-02 6.60179108e-02 -3.16783190e-02
4.75993007e-01 -2.26191118e-01 -4.50771481e-01 -8.37009490e-01
-1.53030539e-02 6.32005557e-02 -2.06718385e-01 5.57064772e-01
3.74444157e-01 5.58913231e-01 -9.12263453e-01 -8.15045238e-01
4.84962940e-01 3.30895007e-01 -6.23378932e-01 4.35210496e-01
-6.97973251e-01 1.46624044e-01 -3.07851881e-01 8.63704741e-01
8.34351301e-01 -1.13623843e-01 -1.77663371e-01 -2.33697176e-01
-1.87378377e-01 -2.36378126e-02 -1.41045392e+00 1.79536557e+00
-2.66017437e-01 6.14359200e-01 -2.03871652e-01 -8.03380311e-01
1.10556281e+00 -3.12959820e-01 -9.22534242e-02 -6.25063062e-01
3.28943320e-02 2.30844736e-01 -3.65918368e-01 -5.28088510e-01
4.80512261e-01 7.85261989e-02 5.99655099e-02 -9.42381471e-02
1.23701543e-02 -3.62057507e-01 2.25152716e-01 1.18625641e-01
6.71927750e-01 4.09810215e-01 3.24654490e-01 -1.62709020e-02
6.41632497e-01 6.05838299e-02 4.98921037e-01 4.48223650e-01
-4.36562449e-01 8.04309189e-01 5.55411577e-01 -2.95730472e-01
-9.94959116e-01 -1.15708220e+00 -2.59580761e-01 9.99106526e-01
7.11414576e-01 3.02161220e-02 -5.43549955e-01 -8.64377201e-01
1.36469245e-01 6.85511947e-01 -7.58718908e-01 1.39412791e-01
-2.15185136e-01 -5.08647799e-01 4.17788833e-01 7.54304290e-01
7.17382133e-01 -1.13995039e+00 -5.87279737e-01 7.69135356e-02
-6.36468604e-02 -1.37830722e+00 -4.26807702e-01 2.79169977e-01
-6.62783146e-01 -9.55672085e-01 -8.85856926e-01 -8.68339956e-01
7.19464540e-01 1.43003866e-01 8.05888951e-01 -3.40488613e-01
-3.59085381e-01 2.00619057e-01 -2.20922098e-01 -6.09916031e-01
-7.71615505e-02 -1.12271108e-01 -1.30323946e-01 5.06435446e-02
2.84681499e-01 -4.28511985e-02 -9.07048523e-01 3.81133169e-01
-7.51129568e-01 1.82949454e-01 4.53221470e-01 5.85835218e-01
8.62940788e-01 -3.76684457e-01 4.12325650e-01 -7.84837723e-01
2.74910107e-02 -3.62518042e-01 -1.06567311e+00 4.77220304e-02
-4.50711250e-01 5.58238849e-02 3.16084445e-01 -3.89391094e-01
-1.31781995e+00 4.13424402e-01 9.10285488e-02 -5.76612592e-01
-8.02455395e-02 9.99738052e-02 -2.87742376e-01 -1.29606903e-01
6.61619484e-01 1.83315620e-01 -2.73697108e-01 -3.75085741e-01
4.04761642e-01 5.38329065e-01 5.11143267e-01 -4.85387743e-01
6.36319220e-01 8.53320122e-01 -1.79190278e-01 -6.00974798e-01
-1.25354862e+00 -6.37348533e-01 -7.14689970e-01 -2.58789748e-01
1.02015591e+00 -1.14605212e+00 -4.49905902e-01 5.57134807e-01
-1.36194599e+00 -1.67790577e-01 -2.10309792e-02 4.25017387e-01
-3.93400580e-01 3.86420369e-01 -3.43356103e-01 -8.60395968e-01
-1.61030620e-01 -1.07571101e+00 1.31150687e+00 2.45634630e-01
1.73166677e-01 -7.47062445e-01 2.82774330e-03 5.54264605e-01
-4.64267470e-02 2.36710668e-01 7.79321074e-01 -3.71663690e-01
-8.57845843e-01 -1.87204003e-01 -6.03505254e-01 3.43990684e-01
-3.27030629e-01 -8.50317776e-02 -1.17048287e+00 -7.94448331e-02
-5.63773334e-01 -6.11922622e-01 9.72970068e-01 3.48790020e-01
1.47591352e+00 3.07975593e-03 -4.04969126e-01 6.48173153e-01
1.43390334e+00 1.74227014e-01 5.14018238e-01 4.96670395e-01
6.87193334e-01 6.84316158e-01 9.44612265e-01 6.39117539e-01
4.74000454e-01 7.75458574e-01 8.58911991e-01 -9.91093367e-02
-1.44730151e-01 -4.45976466e-01 3.35949957e-01 2.29206920e-01
3.23532909e-01 -4.35055315e-01 -9.23668981e-01 8.26682568e-01
-1.74469876e+00 -6.77225292e-01 2.37652019e-01 1.94054472e+00
7.13715196e-01 4.78976339e-01 5.25426269e-02 -4.99156043e-02
6.76247954e-01 3.30039352e-01 -8.77393723e-01 -1.86657738e-02
-1.47905499e-01 -1.18586563e-01 2.79254347e-01 3.97237122e-01
-1.30552018e+00 1.06684172e+00 5.38926935e+00 6.82315767e-01
-8.78382385e-01 -1.87600926e-02 6.31156445e-01 -2.43125856e-01
-1.63284704e-01 -1.79621965e-01 -1.15088165e+00 3.28520387e-01
1.41054064e-01 1.35217711e-01 7.32040405e-02 1.32030714e+00
8.74858871e-02 -5.13095438e-01 -1.27982461e+00 1.13834536e+00
3.70968819e-01 -1.31423402e+00 3.37384157e-02 -4.57509905e-01
8.80521059e-01 5.45215011e-02 2.05392670e-02 3.04020315e-01
-6.92670718e-02 -6.38614833e-01 9.40704823e-01 3.15657169e-01
6.02759540e-01 -6.62981451e-01 6.40147805e-01 3.49063784e-01
-1.04782712e+00 -2.04855978e-01 -6.09459758e-01 2.15938181e-01
-1.80897582e-02 5.69236636e-01 -8.92640889e-01 1.11188874e-01
8.32150578e-01 6.48993611e-01 -6.91510677e-01 1.24533868e+00
-3.89075577e-01 2.35412970e-01 -3.08477134e-01 -2.74837226e-01
3.89553010e-01 1.60938844e-01 4.32857722e-01 1.16969693e+00
1.49247721e-01 6.82049468e-02 1.60353482e-01 9.62392926e-01
-2.11892813e-01 1.33622453e-01 -2.81553119e-01 2.51189023e-01
5.32350719e-01 1.19310081e+00 -8.32171082e-01 -4.73723203e-01
-3.68199497e-01 1.02630353e+00 4.73568588e-01 2.03489199e-01
-8.48121226e-01 -2.90159076e-01 4.25585032e-01 2.21181139e-01
4.44267839e-01 -8.39435533e-02 -2.46955588e-01 -1.09806180e+00
2.20723808e-01 -5.05392194e-01 4.58355039e-01 -1.15243769e+00
-1.20274222e+00 5.02469957e-01 8.74153152e-02 -1.27101052e+00
2.70813406e-01 -7.79840887e-01 -4.03314590e-01 6.49138391e-01
-1.84910941e+00 -1.00247788e+00 -7.45728850e-01 4.21359092e-01
8.76783013e-01 -5.31510636e-02 3.01831186e-01 2.72869408e-01
-4.45712686e-01 4.46715921e-01 -1.03714444e-01 7.59658664e-02
7.80586898e-01 -1.22160459e+00 1.72377065e-01 6.85602248e-01
-1.20402714e-02 -8.29237252e-02 4.20688659e-01 -6.74300492e-01
-8.70666325e-01 -1.34507120e+00 5.93918562e-01 -4.22649473e-01
3.91158462e-01 -5.65271914e-01 -6.81871176e-01 3.69561136e-01
-1.91971689e-01 4.71439898e-01 1.60319701e-01 -2.34286875e-01
-4.08619553e-01 -2.27801412e-01 -1.23614156e+00 6.15219295e-01
1.13030291e+00 -3.38907421e-01 -6.60813510e-01 3.27823818e-01
9.94707286e-01 -7.29126513e-01 -3.18621576e-01 3.30982149e-01
4.03688580e-01 -9.63190556e-01 9.59851980e-01 -2.65898705e-01
8.17993164e-01 -4.72224146e-01 -3.15754920e-01 -9.37298894e-01
6.17031641e-02 -7.96164125e-02 -1.64572626e-01 1.00185466e+00
4.16746110e-01 -1.35242000e-01 1.05087256e+00 4.59621638e-01
-2.83306271e-01 -8.04944038e-01 -1.04193819e+00 -4.72486377e-01
-2.76367217e-01 -5.61861396e-01 3.36022496e-01 6.10557437e-01
-2.59503871e-01 6.73019737e-02 -8.31390470e-02 4.99356270e-01
9.07095134e-01 3.12022254e-04 8.14139903e-01 -9.40545440e-01
-2.81637877e-01 -1.96665004e-01 -6.03619933e-01 -1.29521000e+00
1.04763344e-01 -7.75720596e-01 2.90467650e-01 -1.48068357e+00
2.89960742e-01 -3.92613173e-01 -1.72781661e-01 4.65878755e-01
-1.35645062e-01 4.23049182e-01 2.59691298e-01 2.72300895e-02
-8.98685396e-01 9.02908683e-01 1.23388886e+00 -3.20869088e-01
-2.49907315e-01 -1.32048205e-01 -3.75877678e-01 1.05926931e+00
3.09978902e-01 -4.53917205e-01 -3.75732213e-01 -4.94219929e-01
7.69549236e-02 5.74771687e-02 7.06476629e-01 -1.30934775e+00
3.10259223e-01 -1.97565004e-01 6.40224934e-01 -1.09975624e+00
6.33452833e-01 -7.61094868e-01 -5.51464975e-01 2.91953355e-01
-4.75561351e-01 -2.38903001e-01 4.17601466e-01 8.72718036e-01
-2.12488025e-01 -4.02814895e-01 1.04824567e+00 -8.02465379e-02
-1.18074322e+00 3.45835179e-01 3.12255463e-03 2.02128336e-01
1.30224943e+00 -2.92101443e-01 -2.15546250e-01 -5.03642000e-02
-7.35829830e-01 4.26891685e-01 3.01316410e-01 4.02302235e-01
9.88763213e-01 -1.12695467e+00 -5.31212687e-01 1.65064514e-01
5.69043338e-01 6.32677257e-01 2.15050876e-01 3.32632065e-01
-7.57312238e-01 2.06341952e-01 4.05804180e-02 -8.73476386e-01
-1.04519475e+00 4.60453480e-01 5.02042234e-01 4.65178527e-02
-5.65121353e-01 1.29202545e+00 5.23165286e-01 -3.17796201e-01
7.66456723e-01 -3.33658904e-01 -1.40143603e-01 1.74591392e-01
4.19400930e-01 2.36949369e-01 -4.08607982e-02 -2.09780037e-01
-5.51854610e-01 6.35459423e-01 -2.18713105e-01 -2.32917935e-01
1.18885684e+00 -1.98759824e-01 1.22390330e-01 4.32332069e-01
1.01419270e+00 -2.48752981e-01 -1.75780201e+00 -4.32437241e-01
-9.43138599e-02 -6.93365932e-01 9.33549553e-02 -8.38508308e-01
-8.71141732e-01 1.00159717e+00 7.51873851e-01 -4.22888815e-01
1.00101149e+00 2.77714223e-01 5.27884424e-01 4.89880562e-01
2.83455491e-01 -1.22842789e+00 6.15338326e-01 2.42135257e-01
9.07815337e-01 -1.62149978e+00 1.18922874e-01 -3.28731000e-01
-8.13281238e-01 1.01536310e+00 1.19402766e+00 -1.58094779e-01
5.65719247e-01 1.60869598e-01 -2.81724352e-02 -4.35044914e-02
-5.81141472e-01 -1.61268532e-01 3.26044351e-01 4.76677120e-01
-1.23974206e-02 -2.61225581e-01 -6.03858419e-02 3.74835879e-01
1.39449745e-01 -1.94571927e-01 4.16041851e-01 6.45498633e-01
-6.90973699e-01 -4.93684530e-01 -4.13161278e-01 2.64769733e-01
-1.28123388e-01 -1.63947433e-01 -4.02258009e-01 8.26160550e-01
3.92107606e-01 5.66847563e-01 1.76004767e-01 8.37458745e-02
3.93946290e-01 -1.23929486e-01 4.62873369e-01 -7.81327784e-01
-1.14008367e-01 -1.02590285e-02 -2.18814574e-02 -4.39287007e-01
-4.33860809e-01 -6.47211611e-01 -1.28394830e+00 1.69275388e-01
-5.16029418e-01 -2.12032467e-01 7.80287325e-01 8.48881602e-01
3.61119621e-02 3.73217851e-01 4.17970985e-01 -1.07897639e+00
-3.75093699e-01 -7.15137482e-01 -3.23745936e-01 2.68072605e-01
3.86639267e-01 -9.50297356e-01 -5.10332525e-01 -1.14666976e-01] | [9.2296142578125, 0.9354334473609924] |
5356fb62-e93e-44fe-8e8d-d36b496f9e1b | one-stage-video-instance-segmentation-from | 2203.06421 | null | https://arxiv.org/abs/2203.06421v1 | https://arxiv.org/pdf/2203.06421v1.pdf | One-stage Video Instance Segmentation: From Frame-in Frame-out to Clip-in Clip-out | Many video instance segmentation (VIS) methods partition a video sequence into individual frames to detect and segment objects frame by frame. However, such a frame-in frame-out (FiFo) pipeline is ineffective to exploit the temporal information. Based on the fact that adjacent frames in a short clip are highly coherent in content, we propose to extend the one-stage FiFo framework to a clip-in clip-out (CiCo) one, which performs VIS clip by clip. Specifically, we stack FPN features of all frames in a short video clip to build a spatio-temporal feature cube, and replace the 2D conv layers in the prediction heads and the mask branch with 3D conv layers, forming clip-level prediction heads (CPH) and clip-level mask heads (CMH). Then the clip-level masks of an instance can be generated by feeding its box-level predictions from CPH and clip-level features from CMH into a small fully convolutional network. A clip-level segmentation loss is proposed to ensure that the generated instance masks are temporally coherent in the clip. The proposed CiCo strategy is free of inter-frame alignment, and can be easily embedded into existing FiFo based VIS approaches. To validate the generality and effectiveness of our CiCo strategy, we apply it to two representative FiFo methods, Yolact \cite{bolya2019yolact} and CondInst \cite{tian2020conditional}, resulting in two new one-stage VIS models, namely CiCo-Yolact and CiCo-CondInst, which achieve 37.1/37.3\%, 35.2/35.4\% and 17.2/18.0\% mask AP using the ResNet50 backbone, and 41.8/41.4\%, 38.0/38.9\% and 18.0/18.2\% mask AP using the Swin Transformer tiny backbone on YouTube-VIS 2019, 2021 and OVIS valid sets, respectively, recording new state-of-the-arts. Code and video demos of CiCo can be found at \url{https://github.com/MinghanLi/CiCo}. | ['Lei Zhang', 'Minghan Li'] | 2022-03-12 | null | null | null | null | ['video-instance-segmentation'] | ['computer-vision'] | [ 7.94221833e-02 -1.09042246e-02 -2.55197525e-01 -1.99549466e-01
-4.14402485e-01 -4.11044240e-01 2.13772416e-01 -2.70361215e-01
-3.10576022e-01 6.23807132e-01 -2.69343644e-01 -2.30815068e-01
1.00599989e-01 -8.14131081e-01 -8.60169530e-01 -4.89853680e-01
-2.65648961e-01 -4.14929166e-02 9.70713615e-01 6.87485784e-02
1.43646408e-04 4.08634871e-01 -1.61201000e+00 6.25522316e-01
5.91062307e-01 1.44739640e+00 3.88805509e-01 7.76268244e-01
-1.15231298e-01 1.10447693e+00 -5.64043820e-01 -1.37976348e-01
6.18663073e-01 -5.38651884e-01 -5.46342552e-01 1.05710819e-01
2.99668789e-01 -7.23581612e-01 -6.31878376e-01 7.73771107e-01
3.08810860e-01 -3.81160863e-02 2.77479738e-01 -1.51456547e+00
4.52937447e-02 6.01722658e-01 -8.46348584e-01 4.72588211e-01
1.41499177e-01 3.19220454e-01 7.46766031e-01 -7.47779489e-01
8.98458242e-01 8.70162904e-01 4.24542785e-01 3.90123010e-01
-7.66653836e-01 -1.15201128e+00 3.23392391e-01 3.01638037e-01
-1.23517275e+00 -3.54185164e-01 6.52696669e-01 -5.32098591e-01
7.84537017e-01 3.50774884e-01 9.16958809e-01 7.82199442e-01
2.54645944e-01 1.04778039e+00 8.02555203e-01 -9.57679302e-02
1.14663519e-01 -3.35494101e-01 6.13885708e-02 5.98195732e-01
-1.42144069e-01 -3.06058750e-02 -6.63046062e-01 3.14072043e-01
1.04133964e+00 1.55855402e-01 -4.30048734e-01 2.24531755e-01
-1.15631413e+00 4.54032272e-01 3.91680986e-01 1.59044355e-01
-3.44788909e-01 3.04413587e-01 4.56910908e-01 1.65717408e-01
4.38687056e-01 -1.57677576e-01 -3.74612391e-01 -1.02569409e-01
-1.67771351e+00 3.78463656e-01 4.99922276e-01 1.40128803e+00
9.15605009e-01 2.32762024e-01 -3.66566390e-01 6.59867942e-01
1.34983987e-01 2.57273853e-01 2.88185149e-01 -1.39503872e+00
4.05466527e-01 3.15923393e-01 -2.74826623e-02 -7.40538001e-01
-3.40990990e-01 -4.12083358e-01 -7.07508504e-01 1.93933964e-01
9.52039212e-02 -3.00259054e-01 -1.00748980e+00 1.44994283e+00
3.59717011e-01 6.16536975e-01 -3.66975397e-01 9.69685078e-01
9.90616620e-01 1.08434880e+00 -1.42468400e-02 -4.77204770e-01
1.30721116e+00 -1.22501218e+00 -5.26386738e-01 -3.03326566e-02
4.67744440e-01 -8.39306712e-01 7.35031366e-01 3.54663014e-01
-1.34229779e+00 -8.69634748e-01 -1.08143723e+00 8.92549232e-02
3.45331095e-02 -2.11558212e-02 1.49635300e-01 1.25454873e-01
-9.61930037e-01 3.87649238e-01 -8.50816488e-01 4.01553996e-02
6.92446649e-01 2.98174620e-01 -5.79842888e-02 -1.31906062e-01
-1.11164498e+00 -2.10632440e-02 5.66577613e-01 1.03418887e-01
-1.22721171e+00 -8.96873474e-01 -7.00824916e-01 1.42564341e-01
5.92923045e-01 -2.19375208e-01 1.18175340e+00 -1.24558151e+00
-1.16190672e+00 5.43523610e-01 -2.16271713e-01 -5.44345915e-01
5.93577802e-01 -1.79928020e-01 -3.57684135e-01 5.57259321e-01
2.42759570e-01 1.12897897e+00 8.13871622e-01 -1.12780333e+00
-1.13727808e+00 6.48603812e-02 2.81397015e-01 -1.27530154e-02
-1.00222908e-01 2.85049081e-01 -1.10792303e+00 -7.47659385e-01
-8.83750692e-02 -7.15439737e-01 -3.30638848e-02 9.71672535e-02
-5.49422503e-01 6.62252977e-02 1.07755017e+00 -6.57081604e-01
1.64371109e+00 -2.34273934e+00 -3.14439923e-01 3.04456390e-02
4.41285431e-01 4.89555120e-01 -1.73029453e-01 1.78800657e-01
5.85816428e-02 2.98051517e-02 -9.12685320e-02 -3.55028272e-01
-2.67400593e-01 8.73542577e-02 -1.59583196e-01 3.54526550e-01
1.01617061e-01 7.47170866e-01 -7.24970281e-01 -7.30221510e-01
4.26873296e-01 3.98949116e-01 -7.27453172e-01 2.33427763e-01
-3.04148883e-01 3.63583267e-01 -4.21453923e-01 8.43710780e-01
8.38150799e-01 -6.63943961e-02 4.03654389e-02 -3.62400502e-01
-6.31228566e-01 1.56406477e-01 -1.26226842e+00 1.39360440e+00
-3.61226150e-03 8.42399657e-01 1.92996353e-01 -9.24786747e-01
7.62961268e-01 4.51226532e-01 9.84544814e-01 -8.34933102e-01
2.49622852e-01 2.26823926e-01 -9.01468396e-02 -4.62586820e-01
5.02069116e-01 2.80446112e-01 1.00646242e-01 4.15306501e-02
1.34513170e-01 1.11086383e-01 7.57557511e-01 2.41191536e-01
1.12619781e+00 4.98848140e-01 -1.00706935e-01 -3.17286849e-01
5.26710570e-01 -2.14488171e-02 1.04663634e+00 5.92010438e-01
-5.04854798e-01 1.06200588e+00 7.99050033e-01 -3.16888154e-01
-1.11313987e+00 -8.85213196e-01 -1.33720279e-01 7.86742568e-01
3.85899335e-01 -6.55354798e-01 -1.14909780e+00 -4.95414853e-01
-3.58265311e-01 3.37692171e-01 -3.46659333e-01 2.34991312e-01
-9.23327744e-01 -1.87066406e-01 5.24318159e-01 5.34394085e-01
8.70694280e-01 -1.27203941e+00 -9.12498772e-01 4.72281456e-01
-7.61379674e-02 -1.40328419e+00 -7.13765860e-01 -2.24614982e-02
-4.95261252e-01 -1.21688938e+00 -7.81633615e-01 -7.68092215e-01
4.14277911e-01 4.19630140e-01 9.66156185e-01 1.94272935e-01
-2.04447359e-01 -1.26291858e-02 -5.73906124e-01 -7.59643912e-02
-1.10592708e-01 -4.22478057e-02 -1.51535958e-01 1.53102815e-01
1.64346665e-01 -6.25368595e-01 -1.00780582e+00 6.54168844e-01
-1.17411017e+00 5.45203328e-01 1.99324861e-01 5.03836155e-01
8.91483188e-01 -1.64649673e-02 2.91878670e-01 -6.58825815e-01
-1.42172560e-01 -5.32202303e-01 -7.32482374e-01 -1.65271550e-01
-1.85427994e-01 -6.76281452e-01 8.13411713e-01 -3.22474331e-01
-7.30816960e-01 4.64014076e-02 -3.00177276e-01 -1.00070858e+00
-1.47139400e-01 2.25582898e-01 -2.27162734e-01 3.76242667e-01
2.66122222e-01 1.82927653e-01 -2.15303212e-01 -2.75253952e-01
5.47498800e-02 6.07377887e-01 6.72207117e-01 -3.08066607e-01
6.01105750e-01 5.23835957e-01 -3.79482746e-01 -6.52918279e-01
-7.07615137e-01 -2.97113091e-01 -4.95861441e-01 -6.60700858e-01
1.14012873e+00 -1.05489457e+00 -5.63661575e-01 5.95202863e-01
-1.03370476e+00 -7.76201427e-01 -4.15781975e-01 4.63666409e-01
-4.90948915e-01 1.50594711e-01 -8.39050531e-01 -3.42390478e-01
-3.09375316e-01 -1.52240193e+00 9.47505414e-01 5.87495208e-01
-9.21128243e-02 -3.65470737e-01 -4.48002964e-01 2.32254833e-01
1.18251987e-01 3.17986876e-01 3.32063705e-01 -4.31693584e-01
-8.26943457e-01 1.09738462e-01 -3.88776571e-01 5.99068046e-01
-1.90811127e-01 5.19976974e-01 -8.13629150e-01 -3.20862859e-01
-1.18887372e-01 3.35313044e-02 7.25738704e-01 7.93345392e-01
1.25194395e+00 -2.16023386e-01 -3.28821748e-01 8.66191804e-01
1.46009910e+00 6.74720049e-01 8.70400846e-01 4.33345646e-01
7.08007753e-01 3.01118612e-01 7.52446473e-01 5.94009459e-01
2.55560458e-01 6.80016041e-01 5.28145432e-01 -1.27643645e-01
-4.27947789e-01 -7.08783865e-02 5.13952911e-01 6.91552460e-01
-1.92739844e-01 -5.38449705e-01 -7.59938836e-01 5.47777653e-01
-1.71705723e+00 -1.01043034e+00 -3.55200142e-01 1.94080603e+00
7.15095878e-01 4.31829989e-01 2.40701780e-01 2.07339481e-01
8.63695860e-01 4.77228433e-01 -3.54826361e-01 -2.51160651e-01
-1.10616364e-01 2.75334358e-01 5.51305056e-01 4.10813808e-01
-1.05173576e+00 8.86245430e-01 3.96786094e+00 1.14821911e+00
-1.20977259e+00 1.19686134e-01 9.38861668e-01 -5.02305150e-01
5.29153459e-02 1.38921142e-01 -9.61660326e-01 1.00704503e+00
8.57361376e-01 1.45588160e-01 1.43511489e-01 5.87517262e-01
6.84728682e-01 -4.98475850e-01 -9.31113005e-01 9.18187678e-01
-1.66642591e-01 -1.68197799e+00 -2.27873862e-01 -8.99722129e-02
7.85919249e-01 7.41263926e-02 -1.26676470e-01 2.55815506e-01
-2.61532068e-01 -6.71282411e-01 1.33963811e+00 3.38067025e-01
1.03363657e+00 -6.80474818e-01 5.07313192e-01 1.13114320e-01
-1.68284976e+00 -2.89568566e-02 -1.24514148e-01 8.78631230e-03
5.55826545e-01 6.86673284e-01 -1.61559060e-01 5.80434442e-01
1.17544293e+00 8.19075108e-01 -1.97977871e-01 1.11284161e+00
-1.08201183e-01 8.09714139e-01 -3.65175813e-01 4.50741589e-01
4.81809795e-01 -6.24774843e-02 5.51644683e-01 1.32619488e+00
3.04704934e-01 1.70389608e-01 3.20291221e-01 7.65460789e-01
-1.93481758e-01 -2.52149105e-01 3.95387709e-02 3.37723643e-01
5.25920451e-01 1.16013873e+00 -1.02083325e+00 -6.91294551e-01
-6.69462621e-01 8.18989933e-01 -2.32542843e-01 4.14052457e-01
-1.48617172e+00 -4.58182067e-01 6.54603124e-01 4.83816653e-01
7.60429204e-01 -2.36419782e-01 2.22574379e-02 -1.00147223e+00
2.85195142e-01 -8.56703877e-01 2.57391721e-01 -8.13597322e-01
-6.18384838e-01 8.39789987e-01 1.71139613e-01 -1.53447068e+00
1.15218036e-01 -3.05832505e-01 -6.31784260e-01 6.66321218e-01
-1.56826472e+00 -9.39872086e-01 -5.50120115e-01 7.22329676e-01
1.09088147e+00 7.16716200e-02 7.67006166e-03 7.32634604e-01
-8.37837040e-01 5.22096395e-01 2.96843238e-02 2.77978957e-01
5.46465933e-01 -6.26387596e-01 1.72992721e-01 1.08474970e+00
-1.37045562e-01 2.07287297e-01 4.60544288e-01 -6.65501654e-01
-1.08179259e+00 -1.38842404e+00 5.40283263e-01 1.64706826e-01
4.42021698e-01 -3.95038843e-01 -9.28193152e-01 6.44151449e-01
1.62802890e-01 5.05062640e-01 1.25631019e-01 -8.89876842e-01
-5.23506366e-02 -2.22266406e-01 -1.01302958e+00 4.86557782e-01
1.06596208e+00 -1.87229723e-01 -6.61133751e-02 2.26618409e-01
9.68091369e-01 -7.28339076e-01 -9.40721691e-01 4.46091145e-01
5.47213376e-01 -1.34199417e+00 6.89051569e-01 -1.16419971e-01
8.47757578e-01 -5.72955012e-01 -2.07477748e-01 -3.76723111e-01
-2.00052366e-01 -9.25293922e-01 -2.51258641e-01 1.50445592e+00
1.87478870e-01 -2.95092911e-01 8.35111201e-01 3.41869980e-01
-6.29758775e-01 -1.09189320e+00 -1.02457714e+00 -6.87464476e-01
-1.48381948e-01 -7.64776349e-01 5.34337580e-01 6.62892044e-01
-4.88071442e-01 -1.42282873e-01 -2.25810200e-01 2.00217322e-01
4.27966297e-01 -7.53637822e-03 5.87020040e-01 -7.07528591e-01
-3.41238141e-01 -3.93455476e-01 -2.94716835e-01 -1.31959081e+00
-2.09743053e-01 -5.29558778e-01 -1.63711309e-01 -1.37588811e+00
-5.70264645e-02 -5.17998040e-01 -2.45253190e-01 5.23949623e-01
-9.86939389e-03 7.08487511e-01 6.55394316e-01 5.46045125e-01
-5.37545741e-01 2.37865135e-01 1.23636007e+00 -1.04587115e-02
-2.54994422e-01 -7.96615630e-02 -7.48959407e-02 6.56397581e-01
7.49771774e-01 -3.80828977e-01 -3.61131698e-01 -3.57325256e-01
-2.14372158e-01 1.60326451e-01 3.93842041e-01 -1.24301505e+00
2.07221508e-01 -1.21733040e-01 3.49932402e-01 -7.92406380e-01
3.32596511e-01 -7.36018419e-01 4.38986927e-01 4.31543708e-01
7.89955258e-02 4.71918806e-02 3.12191576e-01 1.89634636e-01
-4.38111722e-01 -1.31962553e-01 9.01252627e-01 -8.79681632e-02
-1.08332944e+00 6.54503763e-01 -3.92665744e-01 1.72171891e-01
1.32507420e+00 -6.17527246e-01 -3.53871167e-01 -9.24175009e-02
-6.42979860e-01 4.81024921e-01 3.83670360e-01 3.41936767e-01
5.31385779e-01 -1.13400853e+00 -6.52386248e-01 3.39879572e-01
-2.95495778e-01 3.17381740e-01 6.50330603e-01 1.09848416e+00
-9.75132346e-01 2.82839507e-01 -2.10180789e-01 -7.74151623e-01
-1.19877434e+00 4.84782696e-01 2.60868847e-01 -6.45563826e-02
-8.57719898e-01 8.18792462e-01 5.02497733e-01 2.89771646e-01
1.60580099e-01 -3.73700529e-01 4.78848405e-02 8.50081220e-02
6.02082968e-01 4.02608067e-01 -2.23187655e-01 -7.57210374e-01
-2.68782258e-01 4.63814527e-01 6.49373680e-02 1.44919381e-02
1.32011831e+00 -9.89205688e-02 -2.78381538e-02 2.92404089e-02
1.28414416e+00 -1.18052647e-01 -1.79907894e+00 1.04891352e-01
-4.46787715e-01 -4.89616483e-01 -2.27296636e-01 -4.27821487e-01
-1.57540810e+00 7.22979248e-01 4.25221950e-01 2.14966789e-01
1.50341022e+00 -2.15441156e-02 1.25592542e+00 -6.04008555e-01
2.58874297e-01 -9.41621780e-01 -2.76740134e-01 4.37022537e-01
5.81689179e-01 -5.50069630e-01 1.41260736e-02 -5.74974716e-01
-3.86911273e-01 1.09834015e+00 8.54429007e-01 -2.29818463e-01
6.51604056e-01 6.09060645e-01 -1.74989194e-01 1.77170057e-02
-6.64664090e-01 -6.11079447e-02 -6.79178676e-03 3.14709365e-01
2.65330106e-01 -1.62300825e-01 -5.04289806e-01 5.70379972e-01
-4.78572734e-02 2.58255273e-01 6.29873037e-01 1.06501520e+00
-2.94422835e-01 -8.89866889e-01 -2.80931979e-01 5.20809770e-01
-5.58203399e-01 -2.25838795e-01 3.32515001e-01 7.97102392e-01
5.31253099e-01 7.95542240e-01 3.18065166e-01 -5.05998075e-01
1.98962241e-01 -1.60778984e-01 6.85775727e-02 -2.97420651e-01
-6.80717468e-01 6.17960870e-01 9.89759043e-02 -1.02003682e+00
-4.66350794e-01 -5.49543977e-01 -1.55921662e+00 -3.89080286e-01
-2.19527662e-01 -2.43872721e-02 2.26607114e-01 7.39707291e-01
5.42931080e-01 8.88932228e-01 5.91147304e-01 -1.17586601e+00
2.43913412e-01 -6.28478885e-01 -5.08542001e-01 1.04317203e-01
2.08663166e-01 -4.63638335e-01 -3.29998404e-01 4.87195194e-01] | [9.185556411743164, -0.10735717415809631] |
dd8b78c2-5700-4223-b190-514ebcebfe96 | stacked-adversarial-network-for-zero-shot | 2001.06657 | null | https://arxiv.org/abs/2001.06657v1 | https://arxiv.org/pdf/2001.06657v1.pdf | Stacked Adversarial Network for Zero-Shot Sketch based Image Retrieval | Conventional approaches to Sketch-Based Image Retrieval (SBIR) assume that the data of all the classes are available during training. The assumption may not always be practical since the data of a few classes may be unavailable, or the classes may not appear at the time of training. Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) relaxes this constraint and allows the algorithm to handle previously unseen classes during the test. This paper proposes a generative approach based on the Stacked Adversarial Network (SAN) and the advantage of Siamese Network (SN) for ZS-SBIR. While SAN generates a high-quality sample, SN learns a better distance metric compared to that of the nearest neighbor search. The capability of the generative model to synthesize image features based on the sketch reduces the SBIR problem to that of an image-to-image retrieval problem. We evaluate the efficacy of our proposed approach on TU-Berlin, and Sketchy database in both standard ZSL and generalized ZSL setting. The proposed method yields a significant improvement in standard ZSL as well as in a more challenging generalized ZSL setting (GZSL) for SBIR. | ['Vinay Kumar Verma', 'Ashish Mishra', 'Anurag Mittal', 'Anubha Pandey', 'Hema A. Murthy'] | 2020-01-18 | null | null | null | null | ['sketch-based-image-retrieval'] | ['computer-vision'] | [ 3.15149099e-01 -2.81999737e-01 -7.05095977e-02 -2.30090335e-01
-1.35776782e+00 -6.86375380e-01 8.10949862e-01 -1.57846332e-01
-3.00588697e-01 8.02157879e-01 -2.16228247e-01 -4.50812653e-02
-5.33706307e-01 -1.07276344e+00 -7.24195123e-01 -8.72390628e-01
3.07546347e-01 6.90600455e-01 3.38296890e-01 -3.91090780e-01
4.14854288e-01 9.87411380e-01 -1.63709557e+00 1.58287272e-01
4.72906291e-01 9.83289361e-01 2.08945855e-01 7.29857266e-01
-3.55483562e-01 3.44085187e-01 -8.16086829e-01 -3.87340933e-01
7.19991326e-01 -2.64084637e-01 -5.08851826e-01 -1.96121614e-02
9.49286878e-01 -5.52275717e-01 -7.07091689e-01 8.70912194e-01
5.38892984e-01 4.56781000e-01 9.30505991e-01 -1.60787773e+00
-8.11228275e-01 7.62683004e-02 -2.83327222e-01 1.94812324e-02
2.68580049e-01 -3.62600356e-01 9.62596893e-01 -1.13422644e+00
9.68534827e-01 1.20149767e+00 3.17585528e-01 5.50962687e-01
-1.04213023e+00 -7.82414258e-01 -1.24356806e-01 1.37745500e-01
-1.70825505e+00 -4.32897359e-01 9.80565250e-01 -1.47682741e-01
3.39385539e-01 3.51115942e-01 3.82474989e-01 9.86979485e-01
-2.07930982e-01 1.01809371e+00 7.65254617e-01 -4.98835653e-01
3.38737488e-01 2.53526747e-01 8.66139680e-02 6.35149896e-01
2.16049895e-01 2.04378635e-01 -5.89445829e-01 -3.57451677e-01
1.06084597e+00 5.46305239e-01 -7.88627714e-02 -8.08272600e-01
-9.65477169e-01 9.73625124e-01 5.66335440e-01 3.74678075e-01
-1.07782826e-01 1.77923515e-01 2.27101356e-01 5.54346025e-01
3.36820781e-01 3.43983144e-01 1.00050762e-01 4.51700807e-01
-1.43257070e+00 3.72100890e-01 6.55122817e-01 1.09386158e+00
6.81421697e-01 1.36990309e-01 -2.47521907e-01 9.35289979e-01
-8.32001194e-02 7.17441261e-01 4.48797613e-01 -7.18428135e-01
3.18011582e-01 2.17234448e-01 1.60917416e-01 -1.16010511e+00
5.82096934e-01 -2.35601485e-01 -7.60585845e-01 4.57501352e-01
3.50553542e-01 5.63379169e-01 -1.05083239e+00 1.60913503e+00
6.67343810e-02 2.70806074e-01 2.31438264e-01 7.94468582e-01
9.53923404e-01 8.12507570e-01 -3.82575691e-01 5.41843213e-02
6.24132156e-01 -8.90260339e-01 -4.79783982e-01 5.58526888e-02
2.00281944e-03 -8.35031331e-01 1.04226565e+00 3.40666682e-01
-1.09121704e+00 -5.65595031e-01 -1.29262424e+00 2.81575434e-02
-6.51224077e-01 1.09558336e-01 3.08685184e-01 5.99169672e-01
-1.25977695e+00 5.94433010e-01 -3.16600055e-01 -4.56745893e-01
3.95448327e-01 3.90384048e-01 -6.80338264e-01 -6.14304543e-01
-9.87443149e-01 4.53683674e-01 2.08871320e-01 -7.13179260e-02
-9.78723645e-01 -4.67589349e-01 -6.63638055e-01 2.91313618e-01
4.01287466e-01 -4.81401622e-01 6.75849140e-01 -1.00151718e+00
-1.20977521e+00 7.53070712e-01 -8.79997909e-02 -2.42762938e-01
6.57082200e-01 1.17004551e-01 -2.00987875e-01 5.09424150e-01
5.46977147e-02 7.77885377e-01 1.13347471e+00 -1.40174568e+00
-1.87279522e-01 -3.07844877e-01 2.29387775e-01 1.29923210e-01
-2.55338371e-01 -4.37207818e-01 -4.85113740e-01 -8.07143748e-01
2.59799093e-01 -9.66775179e-01 1.63453773e-01 6.12121999e-01
-1.84616283e-01 -1.00013487e-01 1.11939311e+00 -3.22136641e-01
7.45492220e-01 -2.14881921e+00 8.93564429e-03 4.48076248e-01
-1.30322084e-01 5.81841886e-01 -6.32722199e-01 8.86835754e-01
-1.46248519e-01 6.13265522e-02 -7.41663799e-02 -2.85195768e-01
-2.28442162e-01 4.68805850e-01 -5.65017045e-01 2.70978540e-01
9.41042155e-02 8.46260369e-01 -8.98266852e-01 -6.63848341e-01
2.76658326e-01 4.56854254e-01 -4.74229038e-01 2.34183103e-01
7.72959292e-02 3.30139808e-02 -5.00193357e-01 7.21827447e-01
7.36117721e-01 -1.82430029e-01 -1.89025477e-01 -6.20921776e-02
3.68159711e-01 -3.56305569e-01 -1.26135015e+00 1.87918878e+00
-4.28022921e-01 5.46361208e-01 -2.58752704e-01 -9.69770849e-01
1.15788901e+00 2.70823151e-01 3.50208074e-01 -5.68905950e-01
-3.31566095e-01 2.69915402e-01 -4.90771025e-01 -1.36619732e-02
4.94930774e-01 -1.93448722e-01 2.39483975e-02 4.31582570e-01
2.39153057e-01 -2.85394341e-01 1.41859710e-01 5.44109106e-01
1.00848687e+00 4.15493324e-02 2.48089004e-02 -1.79724202e-01
6.35936499e-01 -1.92558080e-01 9.75900218e-02 1.12325668e+00
9.93403122e-02 9.35695291e-01 8.98120478e-02 -4.50474828e-01
-1.28451908e+00 -1.53513384e+00 1.30879804e-02 7.53410578e-01
3.65753055e-01 -6.17971756e-02 -4.27805692e-01 -6.36752844e-01
2.20293105e-02 4.85150874e-01 -6.32808208e-01 -2.96154708e-01
-2.03726783e-01 -1.10630132e-01 5.10284662e-01 1.99962497e-01
6.41412795e-01 -1.04020381e+00 -6.48778528e-02 -2.36629769e-02
2.19196919e-02 -7.15016484e-01 -6.80415750e-01 -4.11861658e-01
-7.66603827e-01 -1.09302139e+00 -1.07431293e+00 -8.27550709e-01
8.78130078e-01 6.26394510e-01 8.50836098e-01 1.84715524e-01
-5.39710224e-01 6.79711163e-01 -3.22685689e-01 -1.24561846e-01
-3.51157397e-01 -4.71957996e-02 -2.09422767e-01 7.83597082e-02
6.51224777e-02 -5.22947133e-01 -6.97454035e-01 3.32007378e-01
-1.37719440e+00 -4.07285899e-01 5.25260806e-01 1.26228595e+00
6.34211421e-01 7.40835741e-02 7.87717760e-01 -8.75990331e-01
4.93338019e-01 -2.80057520e-01 -6.05200469e-01 5.69643557e-01
-5.73751390e-01 1.27943829e-01 5.37993610e-01 -6.95026398e-01
-7.74501979e-01 2.59208903e-02 2.62653269e-02 -1.06115627e+00
1.14129506e-01 8.55325162e-02 -8.27260464e-02 -4.32225704e-01
4.80969816e-01 5.48340499e-01 8.74926448e-02 -3.18784475e-01
3.26500893e-01 5.77332079e-01 4.49962735e-01 -6.60698533e-01
1.19949746e+00 5.31038702e-01 2.48126045e-01 -8.63404512e-01
-5.85424185e-01 -6.24936759e-01 -5.49227118e-01 -2.40775608e-02
4.35349584e-01 -7.84089267e-01 -3.97390366e-01 1.37537241e-01
-9.42810774e-01 9.36581194e-02 -4.38482642e-01 1.35563603e-02
-5.45898497e-01 4.67161983e-01 -3.93046468e-01 -9.18455064e-01
-5.36860228e-01 -1.16174209e+00 1.23899043e+00 3.35767455e-02
1.82742119e-01 -8.06451440e-01 4.23425063e-02 1.25627100e-01
3.83436501e-01 2.82420725e-01 9.23366189e-01 -9.51796174e-01
-1.03221989e+00 -7.39599824e-01 -2.45171055e-01 3.81944418e-01
5.33435792e-02 -1.18447877e-02 -9.22316551e-01 -6.27515197e-01
-4.23172772e-01 -5.34825683e-01 7.22021759e-01 2.70234086e-02
1.04290915e+00 -1.95091963e-01 -1.71981931e-01 3.28741252e-01
1.85976481e+00 3.69413853e-01 8.75316322e-01 1.76359385e-01
3.96588326e-01 2.26152882e-01 8.18284452e-01 2.16529042e-01
-2.49809563e-01 8.27317953e-01 1.97570264e-01 -5.96926920e-02
-2.63210744e-01 -5.18323779e-01 -2.56496761e-02 5.65917432e-01
2.59915352e-01 -3.55153114e-01 -5.30694902e-01 6.93351984e-01
-1.66368270e+00 -1.20059609e+00 4.63684708e-01 2.68291736e+00
4.76277024e-01 -1.99431285e-01 -1.32804662e-01 2.99668610e-01
7.38661885e-01 1.46980286e-01 -3.32853258e-01 -2.71076083e-01
-5.44952303e-02 6.48428679e-01 2.85465300e-01 5.68902075e-01
-8.52088034e-01 8.83855164e-01 6.11072969e+00 1.38028717e+00
-1.06707418e+00 8.17749649e-02 4.22460675e-01 -1.19508080e-01
-3.10785323e-01 -1.02408074e-01 -5.96397281e-01 2.16904774e-01
3.94829601e-01 -2.95611560e-01 6.59659207e-01 9.47866619e-01
-4.19900179e-01 -9.09637362e-02 -1.16314673e+00 1.24950910e+00
5.13803124e-01 -1.31651270e+00 5.81822813e-01 -4.09895703e-02
7.85490096e-01 -3.23984057e-01 3.52898002e-01 2.75952876e-01
-4.43400703e-02 -8.76390219e-01 5.08398771e-01 7.41391122e-01
1.22668278e+00 -9.00826454e-01 5.79679847e-01 3.68278176e-01
-1.06041694e+00 6.33036345e-02 -7.89444685e-01 5.35422623e-01
-4.06605214e-01 1.42378688e-01 -8.23303103e-01 6.95806623e-01
3.36315036e-01 3.91030550e-01 -5.83713889e-01 9.28963244e-01
2.09099188e-01 1.23107769e-01 -3.69623780e-01 -3.77943404e-02
3.39992374e-01 -3.08131278e-01 6.29527330e-01 7.45070040e-01
6.08236730e-01 7.70327374e-02 1.78998128e-01 8.53253484e-01
-8.03350583e-02 1.80052385e-01 -1.16947150e+00 -1.69076651e-01
6.32283986e-01 1.05674839e+00 -6.41944408e-01 -5.24990559e-01
-9.73666161e-02 1.32861948e+00 1.74016923e-01 5.09926736e-01
-3.96348536e-01 -6.19502544e-01 3.72507006e-01 1.77777275e-01
4.15519655e-01 -9.38939005e-02 2.70321906e-01 -1.14596498e+00
-6.51625693e-02 -8.51437688e-01 3.93229187e-01 -1.12274003e+00
-1.39760327e+00 7.30579197e-01 3.25642154e-02 -1.53863490e+00
-3.51311862e-01 -4.09262270e-01 -4.71979201e-01 9.54313993e-01
-1.48419106e+00 -1.27134728e+00 -2.62804210e-01 9.38709021e-01
7.59738088e-01 -5.04426360e-01 1.07437885e+00 4.06925350e-01
-8.13120976e-02 8.29126596e-01 5.19999623e-01 9.37238038e-02
8.64882112e-01 -9.81996894e-01 3.55629288e-02 6.66733742e-01
5.32294810e-01 7.01296329e-01 4.34043139e-01 -4.97085422e-01
-1.34795237e+00 -1.00983143e+00 6.94026887e-01 -2.68820763e-01
4.12464470e-01 -2.98678160e-01 -7.76506424e-01 3.98147106e-01
-2.80143678e-01 2.40917087e-01 3.91178310e-01 -3.48482102e-01
-5.62674463e-01 -4.15943891e-01 -1.56735218e+00 4.39361423e-01
8.35750461e-01 -9.05876994e-01 -5.05558431e-01 3.93201858e-01
4.12332147e-01 -1.19862147e-01 -7.07794309e-01 7.20867366e-02
7.21849024e-01 -8.48348558e-01 1.52724624e+00 -4.19459671e-01
5.04733324e-01 -1.51008189e-01 -4.25106347e-01 -1.02633226e+00
-5.03823124e-02 -1.65002674e-01 3.91315222e-01 1.05847657e+00
8.85884762e-02 -5.51690042e-01 8.83881509e-01 4.55305517e-01
3.19793493e-01 -4.87181127e-01 -9.54653323e-01 -9.86160874e-01
-1.81885846e-02 5.05687110e-02 5.96472323e-01 7.96386838e-01
-5.82422256e-01 1.20915733e-02 -4.28532302e-01 1.23287350e-01
8.48565161e-01 3.86618942e-01 8.75610590e-01 -1.19900978e+00
-4.06257749e-01 -7.94866011e-02 -6.89280987e-01 -7.35490918e-01
2.15979844e-01 -1.06470096e+00 -7.03190565e-02 -1.34337056e+00
2.49863982e-01 -7.23842084e-01 -4.73207891e-01 3.37097794e-01
1.21715106e-01 5.27804911e-01 4.54542249e-01 3.45533043e-01
-4.02214289e-01 4.23426539e-01 1.28441834e+00 -3.94766808e-01
1.22862063e-01 7.57818371e-02 -9.51088369e-02 1.29766867e-01
4.80237126e-01 -4.30129558e-01 -9.29320812e-01 -9.45168212e-02
-1.33228838e-01 5.78835368e-01 5.27497768e-01 -9.20347154e-01
2.33731210e-01 5.18230200e-02 4.78353202e-01 -7.94541538e-01
7.99738467e-01 -1.07952523e+00 3.00706476e-01 2.09623262e-01
-4.30411547e-01 -1.06815554e-01 -2.03739498e-02 7.45778859e-01
-4.13327664e-01 -5.14817953e-01 7.41805971e-01 -2.30315492e-01
-4.03821081e-01 6.39725864e-01 1.35819137e-01 -3.09090465e-01
8.37503791e-01 -4.84821290e-01 -2.31179312e-01 -6.67743504e-01
-8.09455395e-01 -2.02357963e-01 6.00111008e-01 3.79394740e-01
1.02276909e+00 -1.55205929e+00 -3.87908340e-01 5.05616069e-01
2.69356191e-01 -2.86885947e-01 2.12728009e-01 1.25155419e-01
-5.99235415e-01 3.41788828e-01 -3.08950424e-01 -3.64782453e-01
-1.31878161e+00 8.74877930e-01 1.03487782e-01 -2.81757504e-01
-5.96320033e-01 7.72303343e-01 4.40753758e-01 -3.33000213e-01
2.20956653e-01 3.54588181e-01 1.26837552e-01 -7.74089545e-02
4.94423330e-01 2.50225902e-01 -1.67672131e-02 -4.58961606e-01
-1.79884713e-02 5.44520020e-01 -1.16731368e-01 -3.45510989e-01
1.28130126e+00 8.96978155e-02 3.40768918e-02 5.07685542e-01
1.42989254e+00 -9.58549678e-02 -8.30023646e-01 -4.43920970e-01
-3.37409765e-01 -9.25111055e-01 8.97675231e-02 -6.63854599e-01
-1.07776558e+00 1.00055385e+00 7.95972049e-01 -6.09018132e-02
1.02136481e+00 -3.57447743e-01 9.16142583e-01 7.78361976e-01
6.85325444e-01 -7.78844476e-01 3.64869654e-01 9.04498994e-03
1.12593842e+00 -1.17764735e+00 -4.11550924e-02 -3.22760463e-01
-2.56702393e-01 1.19534409e+00 1.55384019e-01 -6.48779809e-01
6.14093304e-01 -1.05483294e-01 -1.03168957e-01 -1.72255700e-03
-4.65867013e-01 -4.08575274e-02 4.58547026e-01 3.86499554e-01
-1.35914609e-01 -2.30514213e-01 -4.97257486e-02 -2.04867218e-02
2.49130771e-01 5.68996407e-02 3.02735418e-01 1.04666221e+00
-2.81230599e-01 -1.44136083e+00 -4.86918986e-01 3.95919740e-01
-2.13733494e-01 -2.16195911e-01 -3.83910477e-01 9.58995283e-01
-1.61246851e-01 5.90724587e-01 2.37405319e-02 -9.68034118e-02
2.04123586e-01 2.12206095e-01 6.84463680e-01 -3.95395458e-01
-1.76025271e-01 9.87915620e-02 -2.65117586e-01 -4.60862696e-01
-2.64872462e-01 -2.90370405e-01 -7.86087692e-01 -2.71667510e-01
-4.42125648e-01 2.66326517e-01 7.30468571e-01 5.53953111e-01
1.67895049e-01 6.40329868e-02 8.67417336e-01 -8.81473243e-01
-6.04700685e-01 -5.77008367e-01 -9.36218083e-01 5.55562019e-01
2.82630682e-01 -7.64392614e-01 -3.36737841e-01 -1.42649710e-01] | [11.52896785736084, 0.7251691818237305] |
83373af1-e96f-4328-81a5-203e33899232 | exploiting-selection-bias-on-underspecified | 2210.00131 | null | https://arxiv.org/abs/2210.00131v2 | https://arxiv.org/pdf/2210.00131v2.pdf | Selection Induced Collider Bias: A Gender Pronoun Uncertainty Case Study | In this paper, we cast the problem of task underspecification in causal terms, and develop a method for empirical measurement of spurious associations between gender and gender-neutral entities for unmodified large language models, detecting previously unreported spurious correlations. We then describe a lightweight method to exploit the resulting spurious associations for prediction task uncertainty classification, achieving over 90% accuracy on a Winogender Schemas challenge set. Finally, we generalize our approach to address a wider range of prediction tasks and provide open-source demos for each method described here. | ['Emily McMilin'] | 2022-09-30 | null | null | null | null | ['selection-bias'] | ['natural-language-processing'] | [-2.78534405e-02 8.86376858e-01 -8.76493871e-01 -7.34316945e-01
-8.47192109e-01 -3.52512777e-01 1.01365054e+00 4.55437481e-01
-3.25166166e-01 1.48766840e+00 4.22830999e-01 -2.81213492e-01
-3.21867704e-01 -6.75144970e-01 -7.44600058e-01 -5.20915203e-02
-5.12618721e-01 8.30220819e-01 -7.23445639e-02 4.89884205e-02
1.87544957e-01 -8.41706246e-02 -1.28937864e+00 2.39750400e-01
1.00276542e+00 7.19808578e-01 -7.62649298e-01 1.86065763e-01
2.10439548e-01 7.33870685e-01 -6.77667379e-01 -1.32726800e+00
-2.12221786e-01 9.76378918e-02 -1.07625270e+00 -7.06493676e-01
7.87847281e-01 5.64943068e-02 -2.02039644e-01 9.60166216e-01
4.92213011e-01 -2.95143127e-02 1.14189911e+00 -1.66998887e+00
-6.31906807e-01 1.62284851e+00 -7.07472146e-01 5.59983373e-01
3.69999647e-01 -4.15333211e-01 1.58804071e+00 -1.07413387e+00
9.62295294e-01 1.73549283e+00 7.83621073e-01 6.26074672e-01
-1.59153795e+00 -1.31828165e+00 1.83867171e-01 -6.26742244e-02
-1.44592655e+00 -4.62721854e-01 2.02548906e-01 -6.29037380e-01
9.59867001e-01 3.94504130e-01 1.49882734e-01 1.93620062e+00
4.54780728e-01 5.37834287e-01 1.15442657e+00 -1.24432616e-01
2.54031777e-01 9.29833055e-02 4.80547160e-01 5.73937774e-01
9.00534153e-01 3.50188941e-01 -9.76185620e-01 -8.22924435e-01
2.87820339e-01 -6.33501410e-01 9.22606438e-02 -7.75621757e-02
-1.11088920e+00 1.08992660e+00 1.43558115e-01 1.28302440e-01
1.04261667e-01 4.84493643e-01 3.80478114e-01 7.94227421e-02
1.22980666e+00 7.61354208e-01 -9.47570920e-01 -1.04861632e-01
-1.04397118e+00 8.92324507e-01 9.66323435e-01 5.94680727e-01
2.14366138e-01 -8.51544812e-02 -4.97432113e-01 8.04922998e-01
3.09023529e-01 4.56706494e-01 3.61483335e-01 -7.86281466e-01
4.82655138e-01 -4.68826815e-02 1.51776806e-01 -1.16923356e+00
-6.56726360e-01 -3.67548138e-01 -6.11554861e-01 -4.98282880e-01
5.07300615e-01 -3.76313925e-01 -7.72916019e-01 2.11179471e+00
2.45026648e-01 5.18606842e-01 -9.62407589e-02 5.66365063e-01
9.37977612e-01 -2.53443196e-02 1.00176632e+00 -1.21548414e-01
1.45473266e+00 -5.38560033e-01 -7.22632945e-01 -6.89021945e-01
6.22477949e-01 -4.63996351e-01 6.32066369e-01 1.15203947e-01
-7.98856974e-01 3.52454409e-02 -7.66420007e-01 -2.77682282e-02
-5.84439337e-01 5.32815494e-02 1.42102742e+00 7.56554663e-01
-5.67263842e-01 8.94685030e-01 -3.58908057e-01 -2.71119386e-01
3.78857553e-01 3.26621950e-01 -2.91998982e-01 4.56687182e-01
-1.98091829e+00 1.04734194e+00 5.79732180e-01 -2.45865732e-01
-5.73718846e-01 -1.28457439e+00 -9.71061826e-01 3.52161638e-02
3.30233157e-01 -7.96411991e-01 1.18897843e+00 -4.02365565e-01
-6.74884319e-01 1.05342174e+00 -2.55174845e-01 -4.97165471e-01
5.00819743e-01 -3.16639870e-01 -7.26914823e-01 -7.23032653e-01
4.76933599e-01 4.60942954e-01 5.61537325e-01 -1.01058114e+00
-7.26615369e-01 -3.84646028e-01 -2.98947394e-01 -1.69735715e-01
-1.76729992e-01 1.34631291e-01 2.79016942e-01 -8.86583328e-01
-2.40525618e-01 -8.99850488e-01 -1.66588500e-01 -8.21325958e-01
-7.84722090e-01 -7.54594326e-01 1.44825324e-01 -3.80381465e-01
1.47464061e+00 -1.70467067e+00 1.50878876e-01 4.10535604e-01
6.32300496e-01 -3.82831722e-01 6.73642233e-02 1.04381451e-02
-4.95535433e-01 7.48217344e-01 -2.53498703e-02 -5.15164495e-01
1.75856277e-01 4.83654775e-02 -8.50600660e-01 1.25933081e-01
3.29713076e-01 1.04934943e+00 -1.06829548e+00 -6.06628835e-01
-4.05308843e-01 7.67602306e-03 -4.92737263e-01 -3.85568798e-01
-2.40749255e-01 -7.61159360e-02 -3.50540727e-01 8.60528469e-01
5.56440115e-01 -1.34083375e-01 4.21533555e-01 1.48688182e-01
2.70195931e-01 5.40561497e-01 -7.91303873e-01 1.06659019e+00
-1.41844988e-01 4.67633426e-01 -1.77359715e-01 -6.71368539e-01
6.77864134e-01 8.74324739e-02 6.81922063e-02 -7.75060058e-02
1.25357509e-01 3.87937129e-01 -2.29754467e-02 -1.64992630e-01
6.68130398e-01 -4.08064872e-01 -7.18464196e-01 -1.16604613e-02
2.76201457e-01 4.27185418e-03 1.53830111e-01 4.13225442e-01
8.91094863e-01 -1.54613674e-01 4.32016343e-01 -6.14593506e-01
4.92127724e-02 -2.04326764e-01 7.39382863e-01 1.05121720e+00
-1.46295860e-01 1.55144766e-01 8.80850554e-01 -4.23897415e-01
-7.18888700e-01 -1.35991120e+00 -7.64123857e-01 1.30079889e+00
-2.29115203e-01 -8.40820014e-01 3.63464803e-02 -1.11223149e+00
8.33714783e-01 1.00086236e+00 -1.21090317e+00 -1.13502748e-01
1.23558186e-01 -1.22262430e+00 1.10714161e+00 4.17277902e-01
-2.21214872e-02 -4.44140643e-01 2.49678269e-01 -1.65196195e-01
-3.18519831e-01 -1.03576350e+00 8.21085572e-02 5.52706160e-02
-7.31020808e-01 -1.01692641e+00 -1.46320835e-01 -1.26672402e-01
5.92138059e-02 -8.57529879e-01 1.71514761e+00 -1.71075851e-01
-3.64163280e-01 3.21386904e-02 2.78370500e-01 -6.66460514e-01
-1.49058938e-01 2.90491104e-01 4.87977237e-01 -5.93191564e-01
8.13265979e-01 -5.11231422e-01 1.01213865e-02 -1.77136600e-01
-3.71418983e-01 -3.50338787e-01 4.50198412e-01 8.15585077e-01
1.67327955e-01 -3.37112457e-01 9.83697057e-01 -1.53049982e+00
9.20705736e-01 -1.11242759e+00 -2.70501912e-01 7.60221109e-02
-1.07988429e+00 2.54143298e-01 -4.15003747e-02 -3.92390311e-01
-1.15735984e+00 -4.09458101e-01 1.14600115e-01 3.81880347e-03
5.18841408e-02 6.99487746e-01 1.59427226e-01 4.89901483e-01
9.43362057e-01 -5.66876113e-01 -4.54894036e-01 -2.74347931e-01
5.06175458e-01 3.85572582e-01 3.64341497e-01 -1.03017795e+00
8.21612060e-01 1.52642176e-01 1.19929753e-01 -2.79736578e-01
-1.43053067e+00 1.04968227e-01 -3.82923841e-01 2.05081642e-01
6.72575653e-01 -1.21659029e+00 -7.47220218e-01 -1.49260804e-01
-9.75593150e-01 -3.53854895e-02 1.96575522e-02 5.38136005e-01
-9.34007019e-02 -1.02754526e-01 -5.97598195e-01 -8.90817225e-01
-1.45556942e-01 -6.04272366e-01 1.17436981e+00 1.77473351e-01
-8.68373096e-01 -1.21181631e+00 3.37583661e-01 3.75959039e-01
2.76289824e-02 2.37302914e-01 1.08450198e+00 -1.08150196e+00
1.87369902e-02 -4.11113314e-02 -4.72725660e-01 -4.47429657e-01
-4.15198267e-01 2.83709019e-01 -9.09960508e-01 1.86828583e-01
-9.63918149e-01 -6.31153464e-01 1.29256916e+00 3.77845049e-01
1.24178374e+00 -1.04645550e-01 -9.62013960e-01 2.27815911e-01
9.55130994e-01 -6.71714365e-01 2.29019850e-01 1.04038656e-01
4.97039646e-01 6.96316421e-01 7.71585584e-01 5.66347361e-01
7.71420538e-01 4.22992706e-01 -2.75054369e-02 1.53104469e-01
1.86320126e-01 -6.56214118e-01 5.41065186e-02 -2.80239910e-01
-3.65931958e-01 6.71896935e-02 -1.10561502e+00 6.43209517e-01
-1.95409214e+00 -1.15409172e+00 -3.92668039e-01 1.97705328e+00
1.27685916e+00 3.09863627e-01 -6.14189394e-02 -6.60766482e-01
6.99683011e-01 2.75495023e-01 -2.92765468e-01 -5.42006791e-01
-1.50858238e-01 3.57565910e-01 6.38920248e-01 6.89350367e-01
-1.36344957e+00 1.28164077e+00 8.46832752e+00 1.00203562e+00
-5.54506660e-01 5.89197651e-02 1.08642948e+00 -2.21917793e-01
-8.69137943e-01 7.42820129e-02 -9.48235273e-01 3.37784737e-01
1.23541892e+00 -5.97232521e-01 -2.02173032e-02 9.76616442e-01
-1.41357854e-01 -2.90636063e-01 -1.45650482e+00 5.60533464e-01
-2.68226087e-01 -1.11370647e+00 -8.91754031e-02 1.40624925e-01
8.94135535e-01 -3.97946648e-02 2.99607724e-01 7.89069414e-01
9.10233736e-01 -1.43300319e+00 6.57656133e-01 3.40821236e-01
7.69219577e-01 -7.85003781e-01 7.02887058e-01 -6.60963636e-03
-5.49526930e-01 -2.33188450e-01 -5.63892245e-01 -4.01961058e-01
-1.58354416e-01 1.39029610e+00 -8.24506998e-01 5.04181147e-01
7.89662242e-01 5.99505186e-01 -9.08747971e-01 3.59142691e-01
-3.93295854e-01 8.22141290e-01 -2.52672851e-01 1.16167925e-02
-2.32562348e-01 5.06405294e-01 5.09991944e-01 1.36600804e+00
1.59384161e-01 -2.27293707e-02 -1.94313332e-01 1.25355363e+00
-5.85490525e-01 1.44311264e-01 -8.36914062e-01 -3.08960110e-01
6.99608147e-01 1.24281859e+00 -3.16732138e-01 -2.80164510e-01
-1.80107251e-01 4.94512528e-01 7.32946157e-01 3.20793867e-01
-1.04590786e+00 -2.75177881e-02 8.43160868e-01 -1.35630727e-01
-3.11065048e-01 6.53759241e-02 -6.12909317e-01 -1.62814808e+00
-4.37323600e-01 -4.53570575e-01 8.13789010e-01 -4.45177644e-01
-1.88408327e+00 3.34763862e-02 4.10346150e-01 -3.93154204e-01
-5.70959330e-01 -4.36982125e-01 -4.77440447e-01 8.65260363e-01
-1.16031218e+00 -1.10434127e+00 2.43454427e-01 -3.80740780e-03
-3.43477516e-03 -2.06855044e-01 9.23047781e-01 1.32795542e-01
-6.04193509e-01 7.62700558e-01 -3.49911660e-01 -1.04236297e-01
1.47741497e+00 -1.55954278e+00 3.46293062e-01 4.67829645e-01
2.21309699e-02 9.48559821e-01 1.15164948e+00 -1.25126195e+00
-5.57270527e-01 -9.12768066e-01 1.65367997e+00 -1.07230866e+00
1.14940977e+00 -6.22457743e-01 -3.42243761e-01 1.23723674e+00
8.77063815e-03 -1.22988559e-01 1.14483011e+00 1.56397462e+00
-9.80548501e-01 2.22998202e-01 -1.11989951e+00 5.81963658e-01
1.23406672e+00 -2.03673437e-01 -8.31906378e-01 2.74970353e-01
6.42741501e-01 -5.05418479e-01 -9.27119374e-01 7.77441502e-01
7.44587064e-01 -6.01631880e-01 1.03947771e+00 -1.33053958e+00
1.28149009e+00 3.99787128e-01 1.17551096e-01 -1.42713368e+00
-3.36463571e-01 -2.28997484e-01 -2.11271957e-01 1.33924794e+00
1.18470514e+00 -4.91323531e-01 7.09461272e-01 1.19811773e+00
4.41972345e-01 -7.22662866e-01 -1.10190594e+00 -4.41702157e-01
5.96984327e-01 -5.76226294e-01 4.12424982e-01 1.44699764e+00
5.02645910e-01 6.22759759e-01 -4.92907971e-01 1.94104925e-01
9.65654731e-01 1.54717088e-01 3.59880447e-01 -1.69832182e+00
-9.96098667e-02 -3.05781543e-01 -2.79280931e-01 -1.97871745e-01
9.75697100e-01 -1.01993549e+00 -3.23107511e-01 -9.01582241e-01
7.08347380e-01 -4.37014550e-01 -2.43260294e-01 5.08034170e-01
-6.57817721e-01 2.35787854e-01 -2.49284640e-01 -1.34549215e-01
-6.20023727e-01 4.74180460e-01 5.76155603e-01 -2.53034651e-01
2.56204367e-01 -2.76638977e-02 -1.05714428e+00 7.67134964e-01
5.59936464e-01 -6.21731222e-01 -5.13103664e-01 -1.06295362e-01
7.19801307e-01 -1.75742254e-01 6.37859344e-01 -3.31303149e-01
-1.79109827e-01 -5.64962506e-01 7.98708022e-01 -2.49993220e-01
1.19207896e-01 -3.02883774e-01 -8.25600252e-02 1.47894099e-01
-8.60620141e-01 -1.36196047e-01 3.71601880e-01 6.85068369e-01
2.56976690e-02 6.77974138e-04 2.47971326e-01 1.03905782e-01
-4.88292068e-01 5.45892231e-02 -1.14138134e-01 4.53241140e-01
8.92663956e-01 7.04084337e-01 -7.99362183e-01 -3.20888460e-01
-1.19913185e+00 4.24422681e-01 -1.10416472e-01 8.17632318e-01
2.77839899e-01 -1.39999676e+00 -9.22822535e-01 -2.37182543e-01
2.77033061e-01 -7.85554111e-01 1.72843084e-01 7.26792634e-01
3.03009033e-01 6.50524616e-01 1.74610808e-01 -7.79316053e-02
-1.32829750e+00 3.18202138e-01 2.69063354e-01 -5.06981492e-01
5.54154366e-02 1.36061096e+00 1.26466542e-01 -5.76399207e-01
-9.29611269e-03 -6.22083955e-02 -1.09459721e-01 3.47287059e-01
4.07316804e-01 3.26634645e-01 -2.20058128e-01 -1.35189742e-01
-7.12240160e-01 -2.78058112e-01 3.20643298e-02 -1.75238818e-01
1.16751564e+00 -9.87301245e-02 -4.74518806e-01 7.63531744e-01
7.22760260e-01 4.57569480e-01 -3.45375746e-01 3.25774103e-02
5.15244961e-01 -5.37635386e-01 -2.25051120e-02 -1.30865502e+00
-6.24043405e-01 2.84408838e-01 1.10561527e-01 1.05835244e-01
3.59894633e-01 4.46087241e-01 2.74528172e-02 2.30271414e-01
3.12536359e-01 -1.05787611e+00 -5.24136782e-01 5.76239347e-01
6.93777502e-01 -1.34543157e+00 3.10993761e-01 -8.28095496e-01
-6.26614392e-01 8.12064826e-01 8.72507155e-01 8.85445625e-02
7.55227566e-01 3.38005692e-01 -4.07626748e-01 -4.02145803e-01
-1.30622721e+00 -6.63927868e-02 5.43330491e-01 3.47781211e-01
1.08130705e+00 4.67830151e-01 -1.09963715e+00 1.52796531e+00
-6.54508889e-01 -1.18153520e-01 5.76815903e-01 2.01783299e-01
-2.62332913e-02 -1.10646641e+00 -1.43148452e-01 9.28074300e-01
-9.43283796e-01 -4.08393592e-01 -7.49596477e-01 9.44112897e-01
2.56987244e-01 7.21364617e-01 1.88262939e-01 -5.26472449e-01
9.53899324e-02 6.06732547e-01 4.52883691e-01 -5.68919063e-01
-2.70109802e-01 -3.35362464e-01 8.96627367e-01 -6.94945395e-01
-1.41489282e-01 -8.85709703e-01 -1.03949142e+00 -5.77841341e-01
-8.75294730e-02 1.93860874e-01 3.19522262e-01 7.68915534e-01
4.36283737e-01 2.52120435e-01 6.84888512e-02 -1.83740020e-01
-5.59793651e-01 -1.07360983e+00 -8.30558062e-01 4.10523355e-01
-2.73812213e-03 -1.18551707e+00 -5.24057269e-01 -3.47560674e-01] | [9.770108222961426, 8.126242637634277] |
5f820029-139d-4475-9c29-631ad25f5859 | image-manipulation-via-multi-hop-instructions | 2305.14410 | null | https://arxiv.org/abs/2305.14410v1 | https://arxiv.org/pdf/2305.14410v1.pdf | Image Manipulation via Multi-Hop Instructions -- A New Dataset and Weakly-Supervised Neuro-Symbolic Approach | We are interested in image manipulation via natural language text -- a task that is useful for multiple AI applications but requires complex reasoning over multi-modal spaces. We extend recently proposed Neuro Symbolic Concept Learning (NSCL), which has been quite effective for the task of Visual Question Answering (VQA), for the task of image manipulation. Our system referred to as NeuroSIM can perform complex multi-hop reasoning over multi-object scenes and only requires weak supervision in the form of annotated data for VQA. NeuroSIM parses an instruction into a symbolic program, based on a Domain Specific Language (DSL) comprising of object attributes and manipulation operations, that guides its execution. We create a new dataset for the task, and extensive experiments demonstrate that NeuroSIM is highly competitive with or beats SOTA baselines that make use of supervised data for manipulation. | ['Dinesh Garg', 'Parag Singla', 'Dinesh Khandelwal', 'Arnab Kumar Mondal', 'Kevin Shah', 'Mohit Gupta', 'Poorva Garg', 'Harman Singh'] | 2023-05-23 | null | null | null | null | ['image-manipulation'] | ['computer-vision'] | [ 3.47642481e-01 2.07413867e-01 -2.27051571e-01 -3.49224240e-01
-4.73435730e-01 -5.67186058e-01 7.53572762e-01 2.73419231e-01
-3.91685009e-01 2.76381195e-01 -8.36756229e-02 -6.48796499e-01
2.75280233e-02 -7.95222998e-01 -1.20390975e+00 -2.25304753e-01
6.02727793e-02 7.50573993e-01 5.24269164e-01 -5.38871408e-01
4.10197347e-01 3.28642786e-01 -1.68980539e+00 8.84047687e-01
6.91003561e-01 8.91634881e-01 2.51696736e-01 6.87135994e-01
-6.56498313e-01 1.61020124e+00 -6.40919089e-01 -3.48888278e-01
-1.60396751e-02 -3.19462061e-01 -1.26961553e+00 -2.21113581e-02
7.28667855e-01 -3.47668201e-01 -1.31780103e-01 1.13188696e+00
-8.88208486e-03 8.67838413e-02 8.13969672e-01 -1.75665605e+00
-7.92786360e-01 8.00609350e-01 -2.32126504e-01 1.39141187e-01
5.74772894e-01 6.54926658e-01 9.32037532e-01 -5.97761810e-01
7.56044745e-01 1.88032687e+00 2.06456095e-01 8.30965579e-01
-1.29116893e+00 -4.02726710e-01 1.83705866e-01 5.23361862e-01
-9.95560288e-01 -2.21454680e-01 6.18324339e-01 -6.03510618e-01
1.22238004e+00 1.92849617e-02 6.60233498e-01 1.07266521e+00
8.20690691e-02 1.27439690e+00 9.22790706e-01 -4.68906552e-01
4.01310027e-01 -1.72554031e-01 2.98798144e-01 1.22500920e+00
-2.57471532e-01 2.92169228e-02 -6.20714366e-01 1.68025076e-01
8.31078172e-01 -3.74450773e-01 -5.40532693e-02 -7.98837662e-01
-1.60170269e+00 8.10401499e-01 8.32227051e-01 1.94501251e-01
9.44710225e-02 5.63499272e-01 7.53398240e-01 4.95396614e-01
-1.84218317e-01 8.20840120e-01 -3.87473762e-01 -1.93931740e-02
-5.04447162e-01 4.72494274e-01 7.89150357e-01 1.38219059e+00
4.46415901e-01 2.14264065e-01 -5.38434565e-01 4.00504678e-01
-4.35253195e-02 5.72079599e-01 4.30197746e-01 -1.29097807e+00
5.64454556e-01 8.24023366e-01 -3.43067974e-01 -6.02711678e-01
-3.47226709e-01 4.25148487e-01 -6.07289910e-01 4.52498496e-01
4.47077364e-01 4.25645232e-01 -9.88037705e-01 1.68797135e+00
1.70560300e-01 2.06699789e-01 2.01935172e-01 7.59591162e-01
1.17102420e+00 5.05336344e-01 5.28339446e-01 1.09246269e-01
1.37706006e+00 -1.27640426e+00 -5.53558111e-01 -3.36036503e-01
6.76851988e-01 1.03388391e-01 1.53997028e+00 6.42224789e-01
-1.21980500e+00 -5.57521939e-01 -9.45474625e-01 -6.54185116e-01
-8.29732001e-01 -2.26805180e-01 7.79765904e-01 7.50285760e-02
-1.12404990e+00 2.56544232e-01 -7.25811660e-01 -1.85584366e-01
1.00215685e+00 2.47447133e-01 -3.97774220e-01 -2.10056588e-01
-7.11940587e-01 1.09982848e+00 6.34088397e-01 -2.35605761e-01
-1.39293694e+00 -7.31266260e-01 -1.49724102e+00 4.29584123e-02
8.75957131e-01 -7.86227345e-01 1.44721174e+00 -9.24587369e-01
-1.27575350e+00 1.14534771e+00 6.44289702e-02 -6.21889770e-01
1.43068999e-01 -1.38148099e-01 -1.19721005e-02 6.39095545e-01
2.26166174e-01 1.23389459e+00 9.39608634e-01 -1.35322404e+00
-2.60403395e-01 -4.95151758e-01 5.80738068e-01 -7.54395053e-02
4.40803319e-02 6.25704899e-02 -5.74686050e-01 -5.53516209e-01
-2.59841740e-01 -8.25276911e-01 -1.01403229e-01 5.90732455e-01
-5.70667267e-01 -4.98929411e-01 8.66454005e-01 -4.34943587e-01
6.76297784e-01 -2.03689909e+00 7.12031007e-01 4.07180972e-02
2.60197908e-01 3.37128669e-01 -3.22029203e-01 -4.95846644e-02
-6.34019524e-02 5.46913259e-02 -4.67621565e-01 9.63685010e-03
1.46631166e-01 4.63950008e-01 -4.97814238e-01 4.82585281e-02
6.15380883e-01 1.47765613e+00 -1.16009045e+00 -9.52195525e-01
3.35095882e-01 -4.67149541e-02 -6.52812541e-01 3.45735371e-01
-1.22499406e+00 1.95305839e-01 -3.84569198e-01 8.64076018e-01
8.09141845e-02 -2.71494836e-01 -1.02505922e-01 -2.27079093e-01
3.95979702e-01 -1.56558931e-01 -7.12972760e-01 2.23627448e+00
-3.24404955e-01 6.08760834e-01 -4.71864752e-02 -1.24144125e+00
5.21209002e-01 1.09901153e-01 6.50311410e-02 -6.87473178e-01
1.84615344e-01 -2.72924095e-01 -2.34983861e-02 -9.75632489e-01
3.40254121e-02 5.23991659e-02 -2.21329972e-01 2.06780940e-01
5.55643320e-01 -8.99578750e-01 3.45266670e-01 6.52004898e-01
1.06043291e+00 6.22240603e-01 5.04066169e-01 -1.81099460e-01
5.48038661e-01 5.16885102e-01 -8.32702965e-02 8.36475730e-01
-3.02178681e-01 -3.53366695e-02 8.37494254e-01 -3.15076411e-01
-8.78075123e-01 -1.22786283e+00 2.52354741e-01 1.37301612e+00
3.01796764e-01 -3.43656451e-01 -7.38196373e-01 -8.20335090e-01
2.24395618e-01 8.97564411e-01 -6.49906039e-01 -2.68392086e-01
-5.39317966e-01 1.53033540e-01 6.67968094e-01 7.11247087e-01
5.00180721e-01 -1.86243737e+00 -9.67108488e-01 -1.75872982e-01
1.10781707e-01 -1.51297510e+00 -1.31751671e-01 1.18113212e-01
-7.47898877e-01 -1.37747598e+00 -3.12688529e-01 -9.88178909e-01
6.50266945e-01 -2.52517164e-02 1.64123106e+00 2.76292115e-01
-5.83846092e-01 8.09698403e-01 -3.64949644e-01 -8.74800682e-01
-4.97263730e-01 -2.89672107e-01 -4.05070305e-01 -4.61488664e-01
2.90380180e-01 -2.82442570e-01 6.97218031e-02 -1.40356287e-01
-1.14502573e+00 4.83375847e-01 5.16324103e-01 7.80297399e-01
5.49734414e-01 -3.07828754e-01 4.54239786e-01 -1.13170314e+00
2.57390410e-01 -2.65791684e-01 -7.20466495e-01 5.31644881e-01
3.70551869e-02 4.39543545e-01 5.90336263e-01 -4.25886303e-01
-8.51324558e-01 1.46093979e-01 3.05545658e-01 -8.10756028e-01
-4.42209065e-01 4.80738103e-01 -1.83757886e-01 -1.77878678e-01
1.00639498e+00 1.18445523e-01 1.41929388e-01 5.42589799e-02
8.87701392e-01 2.48259962e-01 1.08033431e+00 -1.03881180e+00
8.55989814e-01 4.90013003e-01 3.88878167e-01 -6.25476658e-01
-1.10521317e+00 -3.24856311e-01 -7.69914329e-01 -1.68958351e-01
1.25985909e+00 -7.27418065e-01 -1.23026001e+00 2.20399499e-01
-1.25561297e+00 -8.64033699e-01 -1.93767607e-01 -1.29468784e-01
-1.13541651e+00 -2.45938683e-03 -5.41204751e-01 -5.28181374e-01
-8.61977190e-02 -1.26780784e+00 1.24989784e+00 -1.07451797e-01
-5.00118174e-02 -7.73047805e-01 -5.46395242e-01 6.09427691e-01
1.53092340e-01 4.69010293e-01 1.56639516e+00 -4.42485839e-01
-9.57536936e-01 3.21060926e-01 -3.09429497e-01 2.73532391e-01
-3.48558158e-01 -2.41750985e-01 -8.12688231e-01 -9.65967338e-05
-3.93614084e-01 -1.30236876e+00 8.33927035e-01 -7.20248371e-02
2.17094874e+00 2.05869954e-02 -2.68837899e-01 5.42217255e-01
1.33612621e+00 -1.14892367e-02 6.22878432e-01 1.78045720e-01
9.66889679e-01 5.86109400e-01 7.69059896e-01 3.71571146e-02
6.36307120e-01 5.12409449e-01 8.68185520e-01 5.55941947e-02
-1.92532837e-01 -1.02034770e-01 3.10939848e-01 3.23489279e-01
1.47751600e-01 1.63655132e-01 -1.29072988e+00 6.27249599e-01
-1.88159215e+00 -8.73527586e-01 7.38720521e-02 1.54255283e+00
1.28708720e+00 1.52738035e-01 1.34578720e-01 6.50310591e-02
1.22890078e-01 -1.44683421e-01 -7.92777598e-01 -5.14649749e-01
1.09440468e-01 6.13355517e-01 1.41737342e-01 3.62067848e-01
-1.09847009e+00 1.36814797e+00 6.15053892e+00 6.54450536e-01
-8.55597675e-01 -2.29986772e-01 1.59710079e-01 2.51865610e-02
6.04785196e-02 -2.41281033e-01 -2.68476218e-01 -4.94286865e-02
7.84615397e-01 -2.99092103e-02 7.28793561e-01 9.02634740e-01
-4.16184753e-01 -3.72305542e-01 -1.78096664e+00 1.08324897e+00
4.90106910e-01 -1.52908587e+00 6.34007096e-01 -6.50335193e-01
4.25584465e-01 -1.30132139e-01 -7.72094131e-02 8.38245749e-01
5.58292627e-01 -1.26157212e+00 8.48392487e-01 5.53039312e-01
8.97732615e-01 -6.04134440e-01 1.22057743e-01 5.49591184e-01
-9.09440577e-01 -3.41584146e-01 -8.70499611e-02 1.37408659e-01
-2.30719045e-01 -1.83092326e-01 -7.84004331e-01 2.84580231e-01
7.37087071e-01 8.49352121e-01 -9.25753176e-01 5.90614438e-01
-4.84369308e-01 2.24664614e-01 2.08611026e-01 -4.17380817e-02
1.49960130e-01 1.73455492e-01 2.79261649e-01 1.03988898e+00
-4.02002245e-01 3.11000049e-01 4.89284724e-01 1.15207803e+00
5.87258954e-03 -1.43589601e-01 -9.46476638e-01 -2.94459999e-01
5.72522208e-02 8.72677505e-01 -4.38624024e-01 -7.12742031e-01
-4.45280045e-01 8.88854444e-01 6.62640810e-01 3.68326217e-01
-8.73068511e-01 -3.05615962e-01 2.67172664e-01 -3.05775821e-01
2.23000064e-01 -3.35500389e-01 -3.32592428e-01 -1.18362427e+00
-8.34797546e-02 -1.22465169e+00 4.44224924e-01 -1.51369166e+00
-1.04792941e+00 1.95169762e-01 4.44137543e-01 -8.38540137e-01
-3.52155387e-01 -1.27122283e+00 -3.28427941e-01 3.33698660e-01
-1.65213168e+00 -1.60441744e+00 -5.44244111e-01 1.16136122e+00
7.73969531e-01 -4.02448088e-01 1.04724371e+00 -1.89585492e-01
-2.63238460e-01 3.32870036e-01 -8.16776276e-01 3.94274861e-01
4.33367729e-01 -1.54871166e+00 1.05712034e-01 3.46353948e-01
3.71425778e-01 3.17470968e-01 4.45762455e-01 -3.40374142e-01
-1.72131169e+00 -1.22235525e+00 2.33006433e-01 -9.17156875e-01
7.97603548e-01 -5.05685866e-01 -8.52762938e-01 1.03735518e+00
1.83757171e-01 2.55405039e-01 4.54414576e-01 -2.94057667e-01
-7.53469765e-01 2.83521056e-01 -1.13636649e+00 8.31999958e-01
1.30092084e+00 -9.01206374e-01 -1.02014887e+00 6.58316731e-01
1.17078328e+00 -6.59551382e-01 -6.90344512e-01 2.70151526e-01
5.60995899e-02 -5.36139786e-01 1.28783596e+00 -1.23311710e+00
8.53803754e-01 -5.20366967e-01 -1.45684868e-01 -1.10764003e+00
9.35529992e-02 -2.02428803e-01 -3.72535318e-01 7.68135726e-01
9.99261141e-02 1.08324811e-01 4.09278691e-01 4.03691918e-01
-1.95567816e-01 -6.01455867e-01 -4.95994180e-01 -7.58791625e-01
2.26870235e-02 -6.70368910e-01 3.31930608e-01 9.76826131e-01
9.02169943e-02 5.32429159e-01 2.77283132e-01 1.34178936e-01
6.82400286e-01 2.90274441e-01 9.55433905e-01 -1.12134302e+00
-3.65950137e-01 -4.65222090e-01 -6.28558517e-01 -6.16293192e-01
1.02973330e+00 -1.32920051e+00 3.06261986e-01 -1.42079353e+00
2.10995585e-01 -1.16266124e-03 1.64390206e-02 1.14934182e+00
-4.37305756e-02 6.37913719e-02 4.66369152e-01 -1.55495554e-01
-1.01746297e+00 4.72048819e-01 1.50281191e+00 -6.92641377e-01
1.26818329e-01 -6.12177849e-01 -4.83565748e-01 9.37959373e-01
3.97590846e-01 2.61251628e-02 -6.43166363e-01 -7.55490720e-01
9.85164717e-02 4.00596231e-01 8.58478189e-01 -1.10043252e+00
3.29014242e-01 -5.82224071e-01 8.19980055e-02 -4.23082083e-01
3.85297656e-01 -9.18172836e-01 -7.33217537e-01 3.39726537e-01
-8.42683315e-01 -6.97351545e-02 4.90957856e-01 4.23465520e-01
-3.39078039e-01 -1.76243946e-01 7.30212212e-01 -3.81057113e-01
-1.37224090e+00 2.51523852e-01 -1.42138926e-02 3.74265164e-01
1.26063347e+00 1.87434509e-01 -6.27109766e-01 -2.38410026e-01
-9.35091078e-01 7.92188525e-01 2.54180729e-01 4.82292086e-01
8.26259553e-01 -1.18745446e+00 -4.03058499e-01 -5.61773255e-02
7.63029873e-01 3.88927311e-01 -2.26452604e-01 4.48686451e-01
-6.97129965e-01 3.04169804e-01 -5.15568376e-01 -7.10476816e-01
-1.17674422e+00 1.14475691e+00 2.73716122e-01 1.70624644e-01
-6.54368699e-01 9.27646816e-01 2.99962223e-01 -5.15430093e-01
5.54526210e-01 -8.08939397e-01 -3.20613354e-01 -4.08293098e-01
6.63863420e-01 -2.41324961e-01 -2.55511582e-01 -3.52925569e-01
-2.14373201e-01 4.25941080e-01 1.50463641e-01 4.94675562e-02
1.20891964e+00 4.56244051e-01 -5.20647526e-01 6.26743138e-01
8.79578412e-01 -6.81661904e-01 -9.23797369e-01 -3.88847828e-01
2.34737128e-01 -1.43815279e-01 -7.58815333e-02 -9.21685338e-01
-7.19149530e-01 1.01618195e+00 4.93301228e-02 -1.49647772e-01
9.71669376e-01 3.79562914e-01 3.40524971e-01 1.20616055e+00
4.97554988e-01 -9.09123600e-01 7.42410660e-01 8.39651287e-01
1.26484156e+00 -1.46932483e+00 -1.68186605e-01 -5.33775806e-01
-7.99601972e-01 1.03330791e+00 1.14575899e+00 -1.29102036e-01
3.94811779e-01 2.98698157e-01 -1.37450397e-01 -5.90011001e-01
-8.70500505e-01 -4.04408634e-01 2.12497249e-01 9.55998957e-01
-9.20208693e-02 -7.69195035e-02 4.41932708e-01 3.25328708e-01
-1.86067134e-01 2.03984424e-01 3.04728478e-01 1.23025084e+00
-3.17820460e-01 -7.23168492e-01 -2.02875838e-01 5.04077971e-01
1.32485762e-01 -1.44729614e-01 -3.99133086e-01 9.47340429e-01
2.15853825e-01 6.46719515e-01 1.90084904e-01 1.42969921e-01
2.83436894e-01 3.52589846e-01 1.01289558e+00 -1.07088614e+00
-5.85008681e-01 -6.30907595e-01 1.32824369e-02 -1.10369825e+00
-5.47994435e-01 -4.89118993e-01 -1.77351213e+00 1.69182062e-01
2.20587075e-01 -4.48012412e-01 5.15735626e-01 1.19322419e+00
-8.69103447e-02 7.93619871e-01 -9.67624858e-02 -7.48653412e-01
-5.12407959e-01 -5.78670681e-01 -2.40952998e-01 8.67875099e-01
5.57107210e-01 -7.40774989e-01 9.21578929e-02 5.20623326e-01] | [10.649928092956543, 2.07368803024292] |
fdb7ae71-1e88-4699-89e2-6c4a9fbef6b7 | cmath-can-your-language-model-pass-chinese | 2306.16636 | null | https://arxiv.org/abs/2306.16636v1 | https://arxiv.org/pdf/2306.16636v1.pdf | CMATH: Can Your Language Model Pass Chinese Elementary School Math Test? | We present the Chinese Elementary School Math Word Problems (CMATH) dataset, comprising 1.7k elementary school-level math word problems with detailed annotations, source from actual Chinese workbooks and exams. This dataset aims to provide a benchmark tool for assessing the following question: to what grade level of elementary school math do the abilities of popular large language models (LLMs) correspond? We evaluate a variety of popular LLMs, including both commercial and open-source options, and discover that only GPT-4 achieves success (accuracy $\geq$ 60\%) across all six elementary school grades, while other models falter at different grade levels. Furthermore, we assess the robustness of several top-performing LLMs by augmenting the original problems in the CMATH dataset with distracting information. Our findings reveal that GPT-4 is able to maintains robustness, while other model fail. We anticipate that our study will expose limitations in LLMs' arithmetic and reasoning capabilities, and promote their ongoing development and advancement. | ['Bin Wang', 'Shuang Dong', 'Wei Liu', 'Jian Luan', 'Tianwen Wei'] | 2023-06-29 | null | null | null | null | ['math-word-problem-solving', 'math-word-problem-solving', 'math-word-problem-solving'] | ['knowledge-base', 'reasoning', 'time-series'] | [-3.70265007e-01 1.40796751e-01 -8.54202583e-02 1.02286704e-03
-8.71854365e-01 -9.06237662e-01 2.89438307e-01 7.89695203e-01
-5.04714012e-01 5.74641228e-01 3.43726665e-01 -7.58312106e-01
-6.02170050e-01 -1.14130640e+00 -6.08832240e-01 -1.11809082e-01
1.50992155e-01 4.66172993e-01 2.28040159e-01 -5.78335583e-01
6.05691791e-01 9.70999077e-02 -1.24333596e+00 4.87876534e-01
1.49372458e+00 3.16184491e-01 1.14141636e-01 7.56054938e-01
-3.99107128e-01 1.34650743e+00 -7.95541048e-01 -1.01134467e+00
1.10831700e-01 4.08428237e-02 -1.25774550e+00 -6.33875489e-01
1.03299034e+00 -8.76141042e-02 -3.42951119e-01 1.08658278e+00
3.98916245e-01 5.91744781e-01 3.26188236e-01 -9.16457176e-01
-1.35524607e+00 1.18999457e+00 -1.19129218e-01 5.64931691e-01
6.22956932e-01 5.52857459e-01 1.25421154e+00 -6.60941184e-01
4.66482162e-01 1.16960001e+00 8.71487975e-01 4.02497947e-01
-1.23994195e+00 -7.52075195e-01 1.51078671e-01 2.44317785e-01
-1.46773803e+00 -1.67693213e-01 3.22360992e-01 -5.61302304e-01
1.34624124e+00 2.37548962e-01 5.98233640e-01 9.31343675e-01
2.79489636e-01 8.33144546e-01 1.24693596e+00 -3.11664075e-01
-8.77404120e-03 -1.89472303e-01 7.81550467e-01 9.00803626e-01
4.90041524e-01 -6.22018933e-01 -6.60822034e-01 6.94216862e-02
5.62095225e-01 -5.27449906e-01 -1.39074743e-01 3.00106674e-01
-1.21228516e+00 4.21335280e-01 2.16056798e-02 4.96119440e-01
2.49274358e-01 1.51280373e-01 -6.13935851e-02 8.44169617e-01
3.41152072e-01 1.25057626e+00 -6.46829188e-01 -7.69319654e-01
-8.38083684e-01 9.01193678e-01 7.60010004e-01 1.13191032e+00
2.60631979e-01 -3.69764399e-03 -3.67784500e-01 8.60652924e-01
6.04007244e-02 2.64040828e-01 6.76694274e-01 -1.00683510e+00
1.16237462e+00 8.50571573e-01 -1.68809012e-01 -9.67026472e-01
-5.50565720e-01 -6.12931371e-01 -3.63345951e-01 -8.66707936e-02
1.08295965e+00 1.73931837e-01 -4.54250634e-01 1.77205837e+00
-2.64579773e-01 2.41088018e-01 -1.50955552e-02 3.69852424e-01
1.34345758e+00 4.71920550e-01 4.63934869e-01 3.93381327e-01
1.03765154e+00 -1.04673767e+00 -6.17891014e-01 -5.38280845e-01
1.22568393e+00 -8.25837791e-01 1.47125447e+00 7.52026796e-01
-1.81819069e+00 -9.37969208e-01 -9.56618071e-01 -6.05149984e-01
-5.80538869e-01 -8.98566097e-02 5.64445674e-01 1.00174117e+00
-1.16927457e+00 7.20908284e-01 -6.69349074e-01 1.44682258e-01
2.60204375e-01 1.22643441e-01 -3.63994390e-01 -4.83116686e-01
-1.16972303e+00 1.15133440e+00 4.51656342e-01 -4.91944909e-01
-4.37685341e-01 -1.47360349e+00 -1.02826619e+00 3.30936641e-01
3.55333328e-01 -2.57218570e-01 1.05259347e+00 -3.90233919e-02
-1.28020096e+00 1.01708817e+00 2.80999333e-01 -5.70241958e-02
4.73127007e-01 -3.93768609e-01 -1.96732119e-01 -2.70337284e-01
1.34895235e-01 3.61649364e-01 -1.66644320e-01 -4.17774141e-01
-2.23197192e-01 -1.03026740e-01 2.43947282e-01 -3.33265066e-02
-3.39241296e-01 2.88716052e-02 -2.34202132e-01 -8.94770503e-01
3.42584252e-01 -4.55396444e-01 -3.97636853e-02 -4.83361393e-01
-4.21844274e-02 -8.02276015e-01 -2.43825659e-01 -8.54887307e-01
1.76754880e+00 -1.74086320e+00 2.13245973e-01 1.52258098e-01
4.16215628e-01 2.25130379e-01 -5.59156120e-01 3.59394342e-01
-1.67306736e-01 5.68794191e-01 3.15193385e-01 -3.22524875e-01
4.68253314e-01 -1.41252344e-03 -1.84638739e-01 3.16185743e-01
3.73544432e-02 1.36883104e+00 -1.13737857e+00 -4.38152313e-01
1.26021162e-01 -2.48795211e-01 -9.16202962e-01 -1.10947145e-02
-3.49687785e-01 -3.31835002e-02 -1.88811690e-01 6.12635255e-01
6.28287852e-01 -1.92907646e-01 -6.29174262e-02 6.15016818e-01
-2.74160713e-01 8.40496123e-01 -1.28785276e+00 1.90096962e+00
-2.73484230e-01 5.27136266e-01 -3.39899361e-01 -6.64541304e-01
6.80771768e-01 -1.38151824e-01 -1.66626833e-02 -7.88457990e-01
-1.45796999e-01 1.76504496e-02 5.80398560e-01 -6.50378287e-01
7.73228407e-01 5.28478205e-01 -1.69334918e-01 4.00176793e-01
2.91508228e-01 -6.68592393e-01 6.81931794e-01 2.22128093e-01
1.50464690e+00 8.69225413e-02 -1.23302648e-02 -7.83997118e-01
4.63946790e-01 -5.95011376e-02 2.74231225e-01 1.12808371e+00
-1.30411163e-01 3.39450479e-01 6.25928581e-01 -3.85900944e-01
-8.12108457e-01 -1.26978743e+00 -5.68496436e-02 1.46625793e+00
-3.67437303e-01 -9.74840403e-01 -5.15146375e-01 -2.48607606e-01
-2.15872750e-02 1.12341142e+00 -2.88978279e-01 -1.34331241e-01
-7.14475214e-01 -5.79982460e-01 1.10995531e+00 5.48837066e-01
5.45418859e-01 -6.54064059e-01 -1.46764189e-01 1.00437403e-01
-2.72945255e-01 -1.14175296e+00 3.85399535e-02 -1.91705480e-01
-7.24650025e-01 -1.16845119e+00 -4.71863389e-01 -7.65457571e-01
4.36571062e-01 -4.83826734e-02 1.69480538e+00 7.20721364e-01
-1.63628384e-02 5.24789214e-01 -3.21754962e-01 -3.31548870e-01
-3.25098634e-01 3.51152420e-01 -3.00707435e-03 -1.12826586e+00
6.84013009e-01 -4.57151562e-01 -4.96241488e-02 -2.29774296e-01
-5.51705718e-01 2.38010332e-01 1.69777066e-01 3.43817204e-01
-3.24139036e-02 3.06832016e-01 2.87906438e-01 -7.38325119e-01
9.20605063e-01 -5.87656140e-01 -7.46580720e-01 3.63344133e-01
-5.16241372e-01 -1.21052489e-01 5.75932443e-01 -5.31433702e-01
-7.72981644e-01 -7.21277952e-01 -5.56808054e-01 4.72438857e-02
-1.00843839e-01 6.20341003e-01 3.82223353e-02 -1.38735428e-01
7.81035781e-01 2.87903965e-01 -6.50249779e-01 -6.18743181e-01
2.24957019e-01 -1.60578580e-03 6.60420179e-01 -1.61495829e+00
8.09900403e-01 -5.03900290e-01 -1.72006607e-01 -8.83994341e-01
-1.02765036e+00 -1.08235762e-01 -4.47736740e-01 -8.83276314e-02
7.27126837e-01 -9.78788257e-01 -1.18504953e+00 4.72392857e-01
-1.07203794e+00 -9.09929574e-01 -9.03251097e-02 4.86697495e-01
-2.16314018e-01 3.91300172e-01 -1.13559103e+00 -5.10082901e-01
7.13315532e-02 -1.32664168e+00 5.70096672e-01 3.60025823e-01
-6.16334081e-01 -1.26367998e+00 2.28562821e-02 8.87436509e-01
3.84143978e-01 -1.62804127e-01 1.75630379e+00 -9.80928540e-01
-5.48409224e-01 1.85930148e-01 -9.03459862e-02 1.66726425e-01
-4.70973074e-01 -5.07376827e-02 -6.45078778e-01 -5.44545725e-02
-2.69699514e-01 -7.77107358e-01 7.07827628e-01 1.55479357e-01
1.50918841e+00 -2.30936304e-01 2.64530241e-01 5.90958118e-01
1.37122083e+00 -2.66163528e-01 6.25511587e-01 5.43022454e-01
6.16573334e-01 3.05658668e-01 6.85207546e-02 -1.40369579e-01
8.97293210e-01 1.00817591e-01 1.84313282e-02 6.41293168e-01
-1.49785072e-01 -4.47799742e-01 3.78495872e-01 1.22505975e+00
-2.93997347e-01 -3.10685754e-01 -1.58025920e+00 6.33325875e-01
-1.44237161e+00 -7.27385879e-01 -6.01323485e-01 2.01019883e+00
1.24561548e+00 3.62031788e-01 -2.40149051e-01 1.58934772e-01
-3.87284383e-02 1.10478334e-01 1.49030700e-01 -5.02018690e-01
-3.04532833e-02 1.07579064e+00 2.16777697e-01 6.35967672e-01
-6.98232353e-01 1.29848540e+00 7.39186907e+00 1.25895202e+00
-4.00714517e-01 1.26179188e-01 5.50747156e-01 -9.30196866e-02
-5.58075845e-01 -4.68934506e-01 -7.65349984e-01 3.78762066e-01
1.16669369e+00 -1.21140324e-01 4.86482561e-01 5.65371871e-01
-2.02603638e-01 -1.48675308e-01 -1.28908491e+00 6.77921593e-01
-3.32131982e-02 -1.36970496e+00 -1.70209542e-01 -2.97043502e-01
1.07498419e+00 -1.55000031e-01 2.42321268e-01 1.06243241e+00
8.68521810e-01 -1.58527589e+00 6.32152259e-01 6.19484544e-01
4.35019493e-01 -6.84007347e-01 5.44938624e-01 6.77173674e-01
-9.81202483e-01 -1.03130057e-01 -4.94694501e-01 -9.31659698e-01
-5.91274381e-01 7.17173815e-02 -2.86531448e-01 2.99122691e-01
6.70446992e-01 3.19849163e-01 -1.30904496e+00 9.34376359e-01
-5.40767789e-01 9.06092286e-01 -1.11314245e-01 -1.69876948e-01
2.93947220e-01 -9.41328481e-02 1.71656027e-01 1.19912732e+00
2.42404327e-01 5.41407347e-01 3.08336675e-01 1.19710815e+00
-1.11802690e-01 2.50666648e-01 -2.39482030e-01 -3.00278902e-01
6.58914268e-01 8.62882733e-01 -6.15494013e-01 -2.47403488e-01
-6.56439245e-01 5.42573094e-01 9.34500933e-01 1.78164378e-01
-7.55319715e-01 -1.90627903e-01 8.85564804e-01 5.94358630e-02
-4.24596131e-01 -6.83102548e-01 -8.36162448e-01 -1.37910378e+00
-2.16439471e-01 -1.17802668e+00 5.46566010e-01 -9.94696379e-01
-1.39031279e+00 -2.44360119e-01 4.84471694e-02 -3.59571099e-01
1.98236674e-01 -9.87116456e-01 -7.32873380e-01 1.10499609e+00
-1.09354794e+00 -8.09759736e-01 -2.77584434e-01 5.16201973e-01
7.22100794e-01 -2.33616829e-01 8.04419577e-01 2.54861861e-01
-6.45251632e-01 1.00445056e+00 -1.62978649e-01 6.33398950e-01
5.82335591e-01 -1.65708244e+00 7.49917984e-01 8.87947917e-01
1.50580153e-01 1.04119301e+00 5.97066820e-01 -7.97744751e-01
-1.35540080e+00 -8.68389249e-01 1.27465165e+00 -1.01227498e+00
1.06619096e+00 -1.92091152e-01 -1.04255342e+00 1.00122404e+00
2.31089100e-01 -3.70226204e-01 8.63803983e-01 3.94358039e-01
-4.13014919e-01 4.51446384e-01 -8.76521170e-01 8.55577707e-01
1.14093494e+00 -3.67789716e-01 -1.27709556e+00 4.16230708e-01
7.91963696e-01 -1.06023073e+00 -1.27691197e+00 5.28161079e-02
2.52985448e-01 -7.77674735e-01 1.31029105e+00 -1.13024306e+00
1.21590400e+00 2.54348159e-01 5.25669903e-02 -1.34877443e+00
-7.13952065e-01 -2.99926877e-01 -1.25635803e-01 1.19476855e+00
3.50066394e-01 -4.95600909e-01 7.39666700e-01 1.14228451e+00
-2.87350029e-01 -8.01698804e-01 -8.53514433e-01 -7.06715167e-01
1.13671708e+00 -1.07699585e+00 6.27264142e-01 1.40652609e+00
3.49008083e-01 -1.83668509e-01 3.67614955e-01 2.38857284e-01
2.87126333e-01 -1.23832293e-01 6.51019752e-01 -1.08604169e+00
-2.99834758e-01 -1.00064850e+00 -3.55159611e-01 -9.02396798e-01
4.91115779e-01 -1.35186195e+00 -5.35368383e-01 -1.56118190e+00
-7.82778338e-02 -5.46701372e-01 -1.03242248e-01 7.03704238e-01
-4.43861485e-01 3.06935787e-01 2.87837386e-01 -5.02284169e-01
-7.35842645e-01 1.20539479e-02 1.33119524e+00 -2.23109499e-01
4.19302508e-02 -2.05947384e-01 -9.44074631e-01 1.05825222e+00
7.67731726e-01 -1.75474092e-01 -3.39407235e-01 -8.71020973e-01
8.50502670e-01 -1.92690998e-01 2.38346472e-01 -1.17608917e+00
3.69379401e-01 -6.32831156e-01 6.74883246e-01 -2.76697785e-01
1.11903455e-02 -1.99750870e-01 -4.32795674e-01 3.70373696e-01
-6.83768570e-01 5.07302999e-01 5.75626791e-01 -2.62733251e-01
1.98640049e-01 -6.85639918e-01 5.27722418e-01 -5.25894344e-01
-6.56806529e-01 -1.68330744e-01 -4.95858788e-01 8.20636451e-01
7.25569367e-01 3.46780904e-02 -9.00535345e-01 -1.14095241e-01
-5.40368140e-01 5.59171259e-01 3.30583751e-02 5.74935794e-01
3.75676900e-01 -1.30832791e+00 -9.87030447e-01 1.89790860e-01
2.16719285e-02 9.93056968e-02 3.07231367e-01 6.06393754e-01
-8.98467422e-01 6.84775412e-01 -3.73142064e-02 -1.33654013e-01
-1.08317006e+00 4.14798737e-01 1.77944720e-01 -5.94713688e-01
-5.18942595e-01 1.38072896e+00 -4.48532045e-01 -7.69654930e-01
2.07622215e-01 -9.88762021e-01 -1.82602808e-01 -2.05859110e-01
7.14349449e-01 9.05030787e-01 1.89071327e-01 -1.10772572e-01
1.62312597e-01 3.35889131e-01 1.64946929e-01 2.95106381e-01
1.28120816e+00 2.38303602e-01 -3.92869592e-01 3.70455623e-01
5.91086984e-01 6.24684095e-01 -3.27879936e-01 -1.63658723e-01
1.41507700e-01 -4.06484753e-01 -2.21729368e-01 -1.04179335e+00
-6.92334592e-01 6.51272237e-01 -2.43015848e-02 -1.70156043e-02
7.32042313e-01 -2.98242360e-01 4.33579654e-01 7.43256152e-01
4.21376079e-01 -1.12000775e+00 2.58341804e-02 1.13090265e+00
4.87378180e-01 -1.04623663e+00 2.40885571e-01 -3.04860801e-01
-6.18388914e-02 1.17491555e+00 1.30714357e+00 -1.61576524e-01
3.51830959e-01 3.08644831e-01 -3.74628991e-01 -8.09285119e-02
-9.49034691e-01 -8.09393749e-02 5.21306574e-01 2.65734732e-01
9.76472020e-01 2.11575255e-02 -4.62223947e-01 1.26971889e+00
-1.15547776e+00 -2.05682516e-01 7.00193763e-01 7.73181975e-01
-4.60334927e-01 -9.46018100e-01 -5.95322669e-01 4.71946418e-01
-6.93388700e-01 -6.44101381e-01 -2.77016670e-01 1.00142562e+00
4.52151895e-01 1.04995739e+00 1.37261257e-01 -2.47970730e-01
2.24978924e-01 6.31050050e-01 8.92856300e-01 -8.66724670e-01
-9.68822777e-01 -7.42982745e-01 -5.20211924e-03 -4.78317469e-01
3.68250877e-01 -2.86807060e-01 -1.00755930e+00 -9.41254616e-01
9.67197046e-02 1.09320350e-01 5.25246300e-02 1.25547242e+00
-3.14568520e-01 8.03117692e-01 -6.29334152e-01 -2.49991983e-01
-6.41802132e-01 -1.05254960e+00 -3.52047890e-01 2.06854492e-01
5.45535609e-02 -3.66173536e-01 -1.12944156e-01 -3.22019428e-01] | [9.781982421875, 7.413180351257324] |
42a0e197-9cb1-4674-9d1e-fdde36229612 | segnbdt-visual-decision-rules-for | 2006.06868 | null | https://arxiv.org/abs/2006.06868v1 | https://arxiv.org/pdf/2006.06868v1.pdf | SegNBDT: Visual Decision Rules for Segmentation | The black-box nature of neural networks limits model decision interpretability, in particular for high-dimensional inputs in computer vision and for dense pixel prediction tasks like segmentation. To address this, prior work combines neural networks with decision trees. However, such models (1) perform poorly when compared to state-of-the-art segmentation models or (2) fail to produce decision rules with spatially-grounded semantic meaning. In this work, we build a hybrid neural-network and decision-tree model for segmentation that (1) attains neural network segmentation accuracy and (2) provides semi-automatically constructed visual decision rules such as "Is there a window?". We obtain semantic visual meaning by extending saliency methods to segmentation and attain accuracy by leveraging insights from neural-backed decision trees, a deep learning analog of decision trees for image classification. Our model SegNBDT attains accuracy within ~2-4% of the state-of-the-art HRNetV2 segmentation model while also retaining explainability; we achieve state-of-the-art performance for explainable models on three benchmark datasets -- Pascal-Context (49.12%), Cityscapes (79.01%), and Look Into Person (51.64%). Furthermore, user studies suggest visual decision rules are more interpretable, particularly for incorrect predictions. Code and pretrained models can be found at https://github.com/daniel-ho/SegNBDT. | ['Joseph E. Gonzalez', 'Henk Tillman', 'Sarah Adel Bargal', 'Alvin Wan', 'Younjin Song', 'Daniel Ho'] | 2020-06-11 | null | null | null | null | ['explainable-models'] | ['computer-vision'] | [ 4.64684993e-01 7.73780763e-01 -4.49058771e-01 -6.29223645e-01
-4.42771524e-01 -3.18356603e-01 2.07980245e-01 6.37922287e-02
-5.12882844e-02 3.92594993e-01 6.52140155e-02 -8.82655680e-01
2.59026140e-01 -6.92734778e-01 -7.82489836e-01 -1.84188932e-01
3.39111656e-01 5.12293279e-01 4.04051632e-01 -1.83648914e-02
4.27076556e-02 2.03805730e-01 -1.55866230e+00 6.74991250e-01
1.18716383e+00 1.16243649e+00 2.38242909e-01 6.16359293e-01
-2.81233490e-01 8.14147413e-01 -3.82079601e-01 -4.29708093e-01
1.14814535e-01 -4.45211262e-01 -1.17677283e+00 1.67705026e-02
8.62081945e-01 -3.31663281e-01 -1.29887676e-02 9.31876004e-01
8.10642168e-02 -3.40673104e-02 7.28463948e-01 -1.20323420e+00
-1.22407866e+00 6.04178369e-01 -5.91824830e-01 2.12273553e-01
3.80663723e-02 4.14079696e-01 1.02365136e+00 -7.46805906e-01
5.93627632e-01 1.27498710e+00 9.52130973e-01 9.03475583e-01
-1.47995639e+00 -5.24594724e-01 3.82001251e-01 2.29507267e-01
-1.10210156e+00 -2.57856965e-01 3.92100692e-01 -4.14854854e-01
1.11287713e+00 4.39025074e-01 8.84644449e-01 1.09927702e+00
1.08040862e-01 1.13419032e+00 1.08602428e+00 -2.58819193e-01
2.55461931e-01 -8.49481821e-02 3.07667196e-01 7.67488956e-01
2.20686242e-01 7.74476398e-03 -2.53397346e-01 4.63743210e-01
9.58520412e-01 1.77473128e-01 -8.72034431e-02 -1.18332550e-01
-1.11656666e+00 8.41730714e-01 1.17806089e+00 5.37550002e-02
-3.12869221e-01 5.22899151e-01 5.42278029e-02 -2.06232816e-01
5.45190096e-01 4.96907324e-01 -5.59727967e-01 1.19851641e-01
-1.29210126e+00 3.12041491e-01 5.95978558e-01 9.07081187e-01
8.63994300e-01 2.96287328e-01 -3.90158921e-01 6.34099782e-01
2.91004777e-01 3.19554776e-01 2.74984270e-01 -1.20042515e+00
2.88633704e-01 5.79901636e-01 -8.36828128e-02 -7.61750638e-01
-6.32993340e-01 -5.66815197e-01 -8.91822517e-01 4.26482350e-01
5.72344005e-01 -1.26283556e-01 -1.67891049e+00 1.45407951e+00
1.05573416e-01 1.62976440e-02 -7.18230680e-02 1.19264567e+00
1.19004989e+00 5.68698347e-01 4.12162721e-01 4.01400745e-01
1.47021019e+00 -1.27863085e+00 -4.40789461e-01 -7.50993550e-01
4.72369790e-01 -4.36503261e-01 1.44585180e+00 1.70246720e-01
-1.02249813e+00 -7.70346880e-01 -9.35899436e-01 -4.63431299e-01
-4.55914944e-01 6.38612956e-02 7.43794799e-01 5.31155944e-01
-1.40005255e+00 4.39649373e-01 -8.45080853e-01 -5.71372092e-01
1.06881559e+00 2.56180018e-01 8.96542594e-02 9.04368386e-02
-8.69502425e-01 8.25007617e-01 4.00546283e-01 -1.58380717e-02
-7.76692808e-01 -8.09669912e-01 -8.77825201e-01 1.23798221e-01
2.61568129e-01 -9.88069654e-01 1.50932252e+00 -1.60229695e+00
-9.83786523e-01 1.03089678e+00 -4.45618540e-01 -9.28713143e-01
6.07785463e-01 -2.60063410e-01 -1.18632756e-01 3.19159508e-01
4.21512246e-01 1.68824804e+00 6.57406569e-01 -1.36256957e+00
-6.77607536e-01 -2.17823386e-01 8.59888270e-02 2.11222500e-01
1.03237055e-01 -2.35347852e-01 -4.81272548e-01 -7.38587558e-01
2.30976701e-01 -8.18790257e-01 -4.88335460e-01 3.47839922e-01
-8.21706355e-01 -1.21870063e-01 1.03382409e+00 -8.40017080e-01
1.00269246e+00 -1.83659339e+00 -4.00612146e-01 -7.85472691e-02
6.09109282e-01 2.81441122e-01 1.04399264e-01 -3.12273026e-01
-1.08550258e-01 6.50164962e-01 -4.89329487e-01 -5.13331473e-01
5.71760014e-02 2.19631821e-01 -3.85089219e-01 4.80835550e-02
4.00830835e-01 1.34599483e+00 -6.23247027e-01 -5.58989584e-01
4.52811301e-01 2.85173655e-01 -5.17532587e-01 -2.12566569e-01
-5.75616121e-01 3.64411712e-01 -3.45794231e-01 8.73375118e-01
5.15792370e-01 -6.40197694e-01 -1.46048918e-01 -1.07104279e-01
2.05984637e-02 2.73498237e-01 -6.77611053e-01 1.55336726e+00
-2.06977203e-01 1.11732197e+00 -2.55756348e-01 -7.41485178e-01
6.72898889e-01 -6.58139214e-02 2.45514121e-02 -9.05949354e-01
-4.34898511e-02 -5.23344204e-02 2.05405056e-02 -4.00691867e-01
5.63769817e-01 9.35302377e-02 6.59552217e-02 8.61110091e-02
-1.07353829e-01 -9.31194350e-02 -1.28563121e-01 7.69926906e-02
8.05467963e-01 2.73782760e-01 2.24928275e-01 -3.20240170e-01
-1.11377731e-01 5.25151193e-01 6.38853252e-01 9.81592059e-01
-4.43663657e-01 1.12103271e+00 5.33622563e-01 -7.85351574e-01
-1.01887202e+00 -1.08094525e+00 -1.56188667e-01 1.12526143e+00
5.42585135e-01 -6.47813315e-03 -1.26629686e+00 -6.89526558e-01
8.38522017e-02 1.23312902e+00 -8.81521046e-01 1.24875471e-01
-2.17882186e-01 -3.42461348e-01 7.44141757e-01 9.30207431e-01
9.18920934e-01 -1.22058308e+00 -9.05701876e-01 2.27424838e-02
-2.18085438e-01 -1.16973138e+00 -2.69813091e-01 3.04920256e-01
-8.73350859e-01 -9.83050525e-01 -5.54831743e-01 -7.13517189e-01
6.39806151e-01 2.36304834e-01 1.51784205e+00 2.93360621e-01
-2.92899042e-01 1.10690743e-01 -1.27235055e-01 -7.34676957e-01
-2.41412759e-01 1.44296199e-01 -3.66615862e-01 -3.38035464e-01
4.81714040e-01 -1.23670995e-01 -9.04759943e-01 4.82972085e-01
-6.86996639e-01 8.71847868e-01 5.70237815e-01 6.05972469e-01
1.00470281e+00 -2.56696463e-01 5.21374345e-01 -1.01305401e+00
2.52596885e-01 -3.25321764e-01 -2.73787588e-01 1.77890435e-01
-8.37009311e-01 -2.49770824e-02 3.47590506e-01 -2.13538349e-01
-1.11219060e+00 6.83529750e-02 -1.16929293e-01 -5.69710374e-01
-7.37518132e-01 1.63970277e-01 1.65763497e-01 1.34221748e-01
9.42795515e-01 -4.95919622e-02 -1.64876133e-01 -2.21580282e-01
5.34919620e-01 5.88503718e-01 7.62865067e-01 -2.87755370e-01
3.72981906e-01 5.44377983e-01 -2.22723812e-01 -5.22019565e-01
-1.16120481e+00 -2.45623291e-01 -5.80150187e-01 -1.86744288e-01
1.45663106e+00 -9.36367035e-01 -3.82526547e-01 3.40859473e-01
-1.09119952e+00 -8.63985538e-01 -3.26079071e-01 -2.10003555e-03
-6.45770192e-01 -8.76759142e-02 -6.68838382e-01 -6.49672747e-01
-5.09981811e-01 -1.18048406e+00 1.20327699e+00 6.35092258e-01
-5.39966106e-01 -1.08210087e+00 -7.29826152e-01 7.96890080e-01
4.36817467e-01 4.92750257e-01 8.87040198e-01 -5.77006817e-01
-7.32499957e-01 3.04290116e-01 -7.20026314e-01 -2.01647375e-02
-2.17794314e-01 4.40808497e-02 -1.23365307e+00 2.74344265e-01
-5.08538246e-01 -2.10003808e-01 1.25633347e+00 9.78786945e-01
1.68555307e+00 -3.81096840e-01 -4.91268814e-01 7.13260233e-01
1.20465171e+00 -1.35473078e-02 6.72820926e-01 3.78700018e-01
9.86800551e-01 5.94885945e-01 5.99384427e-01 -4.81040701e-02
7.15255201e-01 4.90073651e-01 7.80993700e-01 -7.53664911e-01
-4.92686480e-01 -4.64172870e-01 -1.17402680e-01 -9.41718295e-02
1.74960550e-02 -2.28369758e-01 -1.35148621e+00 7.34642625e-01
-2.17863536e+00 -7.68631697e-01 -4.94911849e-01 1.74623430e+00
7.35335588e-01 4.07183290e-01 1.81140557e-01 -2.53185362e-01
7.21386850e-01 1.05544418e-01 -1.01098478e+00 -7.06982791e-01
-1.66368678e-01 9.03147906e-02 6.99067652e-01 4.13600534e-01
-1.38443995e+00 1.42182600e+00 5.71375084e+00 7.87440896e-01
-1.23722649e+00 2.00279087e-01 1.42986345e+00 -6.95898104e-03
-4.46483403e-01 6.94540218e-02 -7.51766086e-01 2.92298406e-01
7.42373526e-01 3.46805900e-01 1.82430819e-01 9.53565419e-01
4.04681295e-01 -2.50497460e-01 -1.11138761e+00 1.03337896e+00
-1.23425812e-01 -1.73962724e+00 1.95610434e-01 3.39894160e-03
9.09577012e-01 2.47546241e-01 3.58143002e-01 2.81287909e-01
5.02858400e-01 -1.57781076e+00 1.10897160e+00 3.97183895e-01
9.75781202e-01 -4.25978899e-01 5.86046278e-01 3.22310597e-01
-9.70944881e-01 -7.20691085e-02 -2.70309538e-01 -1.69187069e-01
-4.91622277e-02 5.42055130e-01 -9.67802525e-01 7.42265061e-02
1.16192782e+00 9.39651787e-01 -8.76333535e-01 9.81722474e-01
-4.61117893e-01 9.00181830e-01 -2.84340292e-01 6.41020760e-02
5.49527526e-01 1.46328360e-01 2.12677732e-01 1.27751505e+00
1.41126234e-02 3.56071219e-02 1.60004646e-01 1.49805987e+00
-1.16336606e-01 -3.49485099e-01 -4.69506711e-01 3.22697729e-01
3.17014128e-01 1.01144326e+00 -1.16949499e+00 -4.99165297e-01
-1.66289389e-01 1.16911197e+00 2.06086144e-01 7.42716730e-01
-1.01939285e+00 -1.45687133e-01 7.50918329e-01 1.98378831e-01
4.85033333e-01 9.77275521e-02 -1.26094925e+00 -8.68694484e-01
-1.93236277e-01 -5.89307249e-01 1.77155346e-01 -1.23405814e+00
-8.87875021e-01 6.03723109e-01 -1.12436034e-01 -9.15372968e-01
-2.21927390e-01 -5.96928596e-01 -6.56003475e-01 7.71338224e-01
-1.41517758e+00 -1.46927309e+00 -5.89926422e-01 2.53355116e-01
1.04227924e+00 2.82377630e-01 6.36281848e-01 -1.77609965e-01
-5.63228428e-01 4.51807529e-01 -2.76355118e-01 2.02149510e-01
2.78081417e-01 -1.59832239e+00 8.52247357e-01 9.19427156e-01
2.74929225e-01 2.49318719e-01 7.42361844e-01 -6.09811902e-01
-5.67256272e-01 -1.45109832e+00 6.35261357e-01 -6.07489109e-01
2.21473873e-01 -2.67479390e-01 -9.37383354e-01 8.30306590e-01
2.76189595e-01 1.01186939e-01 5.11971414e-01 2.15152040e-01
-3.41392368e-01 1.83409363e-01 -1.27343464e+00 9.04677331e-01
1.19628489e+00 -3.42233807e-01 -6.13019645e-01 2.06507638e-01
1.04481089e+00 -6.87241495e-01 -4.58820045e-01 4.24986690e-01
6.48371637e-01 -1.19404125e+00 9.73319232e-01 -5.28059840e-01
7.85702407e-01 -4.06339824e-01 1.13337733e-01 -9.89888012e-01
-4.38508928e-01 -2.92416185e-01 -1.18727386e-01 8.28519523e-01
7.48417497e-01 -4.68294740e-01 1.03285217e+00 9.14737284e-01
-3.15376192e-01 -1.16935766e+00 -6.99637234e-01 -3.35838765e-01
6.62478954e-02 -7.81496286e-01 5.29819906e-01 8.71265531e-01
-5.68665266e-01 2.38886237e-01 9.12087336e-02 1.37165263e-01
5.81968784e-01 2.15568662e-01 5.06901383e-01 -1.08962011e+00
-1.02139197e-01 -7.66972840e-01 -4.21333820e-01 -1.23217762e+00
1.43254131e-01 -7.82150805e-01 -3.28993462e-02 -2.13806200e+00
7.57117271e-02 -4.45164829e-01 -1.13000795e-01 1.12187874e+00
-2.67097831e-01 4.61682320e-01 4.45021063e-01 2.64962912e-01
-8.00686896e-01 2.30406761e-01 1.21092021e+00 -2.36262873e-01
-1.86787128e-01 -1.76368486e-02 -1.12591779e+00 1.02473736e+00
1.00544214e+00 -2.47999996e-01 -4.29306090e-01 -7.08129823e-01
-2.16484368e-01 -1.37647346e-01 8.77701521e-01 -1.09676504e+00
-2.06746645e-02 -2.87965566e-01 8.55818093e-01 -5.99325657e-01
1.29577786e-01 -6.21747255e-01 2.25683898e-02 4.89672750e-01
-5.56143224e-01 -1.80764079e-01 4.18814570e-01 5.48555970e-01
-3.20833735e-02 1.63719174e-03 6.71096385e-01 -1.07823357e-01
-1.26299763e+00 1.76960543e-01 -2.99586594e-01 1.17668852e-01
9.19945359e-01 -8.31001580e-01 -6.04316235e-01 -4.77387339e-01
-7.83893585e-01 4.66157556e-01 6.36083424e-01 5.38884938e-01
7.08124876e-01 -9.10343170e-01 -4.41660434e-01 -7.66759068e-02
9.25202295e-02 5.39128304e-01 2.18959734e-01 6.55520678e-01
-8.34101200e-01 3.49371850e-01 -1.62498876e-01 -9.77126360e-01
-1.15339398e+00 1.84770703e-01 5.53952396e-01 6.10674359e-02
-7.27076709e-01 9.66566384e-01 6.62098885e-01 -4.32933897e-01
8.07496607e-02 -9.29364562e-01 -5.76437004e-02 -3.32876503e-01
2.56883830e-01 5.17423078e-02 -2.22494528e-01 -4.24128622e-01
-2.76309609e-01 4.72818166e-01 5.47135249e-02 1.40128970e-01
9.63737309e-01 -1.65368006e-01 2.10155636e-01 3.05305719e-01
8.14957857e-01 -6.28979206e-01 -1.70983446e+00 3.82432826e-02
-1.28004476e-01 -1.71956614e-01 1.41668037e-01 -1.23506808e+00
-1.05335701e+00 1.08394241e+00 7.39955962e-01 2.10139781e-01
1.17062199e+00 2.59386510e-01 8.14994335e-01 2.52157450e-01
4.62830700e-02 -1.07686865e+00 -1.76205277e-01 3.86010736e-01
6.96782231e-01 -1.55586183e+00 -1.96796298e-01 -5.67128956e-01
-9.70152080e-01 1.02954829e+00 9.37013745e-01 9.38478392e-03
4.39890414e-01 3.65481116e-02 1.87882885e-01 -2.60672003e-01
-6.39328778e-01 -5.18970311e-01 4.96214956e-01 7.72333205e-01
2.64079064e-01 4.90113467e-01 3.52153033e-01 6.77081048e-01
-4.01952296e-01 7.61248171e-02 2.46798187e-01 5.35399616e-01
-5.82485676e-01 -2.99151331e-01 -2.33852282e-01 6.82074308e-01
-3.53673369e-01 -4.25568581e-01 -4.95796144e-01 7.17576444e-01
3.04026544e-01 9.31153953e-01 3.69449854e-01 -3.47582489e-01
7.57113323e-02 -8.47566649e-02 -2.22366266e-02 -6.65677428e-01
-6.27030432e-01 -1.51526451e-01 1.87894791e-01 -6.93805814e-01
-3.77985299e-01 -4.98384535e-01 -1.71701109e+00 -2.47050956e-01
-1.09171331e-01 -3.96490455e-01 5.66227436e-01 1.03740025e+00
6.15112364e-01 7.93040335e-01 -1.59673482e-01 -9.02246654e-01
-2.64154673e-02 -7.33825207e-01 -1.53965220e-01 3.71779293e-01
3.58466804e-01 -4.01035160e-01 -1.01421840e-01 4.04604524e-01] | [9.612991333007812, 0.5520899891853333] |
4524addf-4e85-4af0-b1ff-2a27445cc0c6 | survode-extrapolating-gene-expression | 2111.15080 | null | https://arxiv.org/abs/2111.15080v1 | https://arxiv.org/pdf/2111.15080v1.pdf | SurvODE: Extrapolating Gene Expression Distribution for Early Cancer Identification | With the increasingly available large-scale cancer genomics datasets, machine learning approaches have played an important role in revealing novel insights into cancer development. Existing methods have shown encouraging performance in identifying genes that are predictive for cancer survival, but are still limited in modeling the distribution over genes. Here, we proposed a novel method that can simulate the gene expression distribution at any given time point, including those that are out of the range of the observed time points. In order to model the irregular time series where each patient is one observation, we integrated a neural ordinary differential equation (neural ODE) with cox regression into our framework. We evaluated our method on eight cancer types on TCGA and observed a substantial improvement over existing approaches. Our visualization results and further analysis indicate how our method can be used to simulate expression at the early cancer stage, offering the possibility for early cancer identification. | ['Sheng Wang', 'Tong Chen'] | 2021-11-30 | null | null | null | null | ['irregular-time-series'] | ['time-series'] | [-5.38242757e-02 -1.85742795e-01 -3.64005923e-01 -1.18094668e-01
-7.69084692e-01 -3.68786037e-01 3.24802786e-01 4.38351899e-01
-9.57922935e-02 8.63269269e-01 -7.45907018e-04 -7.28796899e-01
-2.63194054e-01 -8.21183562e-01 -3.13654631e-01 -1.12848425e+00
-5.95867991e-01 3.85370255e-01 -2.06672221e-01 -1.62582859e-01
-1.82896674e-01 6.81745172e-01 -9.82303679e-01 8.63049030e-02
8.94651651e-01 6.55288517e-01 -1.87876180e-01 7.78627455e-01
3.23132961e-03 2.83932269e-01 -4.62157845e-01 9.69881788e-02
-2.27009878e-01 -3.52751076e-01 -4.21361268e-01 -3.05481672e-01
-3.61354530e-01 2.12454319e-01 -5.30935049e-01 7.21512496e-01
4.73314673e-01 -2.53776073e-01 6.61393821e-01 -1.20496535e+00
-1.20837703e-01 2.32716337e-01 -5.47046185e-01 -1.56603292e-01
8.99432376e-02 8.91392305e-02 4.29936051e-01 -3.85464102e-01
6.78285360e-01 8.91459763e-01 1.09132957e+00 6.45141482e-01
-1.57419443e+00 -3.22841018e-01 -2.65797138e-01 -1.67748287e-01
-1.56742167e+00 -9.42012370e-02 3.62278551e-01 -5.64509749e-01
6.69182241e-01 4.86929923e-01 1.02019501e+00 8.53988469e-01
7.87284791e-01 4.91624147e-01 1.10658479e+00 -2.79103518e-01
3.84631902e-01 -1.79065242e-01 2.18549281e-01 6.66091859e-01
-1.28752753e-01 3.25078100e-01 1.20495111e-02 -6.77604437e-01
6.32365346e-01 4.57539082e-01 -3.10077190e-01 2.12076575e-01
-1.05144799e+00 8.98205340e-01 1.95005074e-01 3.93923908e-01
-3.33747953e-01 3.56697172e-01 4.93359387e-01 9.60854515e-02
7.73221135e-01 2.93947041e-01 -6.09194636e-01 -7.64423236e-02
-7.28950500e-01 -9.64935683e-03 9.75652635e-01 4.14931715e-01
4.58018452e-01 -3.42798263e-01 -2.92331278e-01 6.26330554e-01
-6.08143285e-02 -2.70908177e-02 6.34500206e-01 -7.01306343e-01
-5.37618995e-01 8.62717628e-01 -1.68835849e-01 -6.88795567e-01
-9.23429370e-01 -5.92265725e-01 -1.33249950e+00 -9.96801164e-03
6.50406003e-01 -3.52856308e-01 -8.53484035e-01 1.52623594e+00
2.13160917e-01 4.47918057e-01 2.42197603e-01 3.16905349e-01
4.01365340e-01 7.29420364e-01 2.79762536e-01 -4.71472770e-01
1.39788365e+00 -7.54064247e-02 -5.74561059e-01 5.15482187e-01
1.30775845e+00 -2.38774821e-01 6.78049266e-01 2.63190836e-01
-6.85718954e-01 9.75145325e-02 -5.13436437e-01 2.07299560e-01
-4.76338208e-01 2.11619511e-01 1.04507494e+00 4.23084021e-01
-1.06443751e+00 7.75726259e-01 -1.22257626e+00 -4.91392195e-01
5.80608368e-01 4.53191102e-01 -2.76984394e-01 8.41765627e-02
-1.21109807e+00 5.26890755e-01 1.28796697e-01 1.89431697e-01
-9.40574884e-01 -1.17925489e+00 -5.37957788e-01 1.10394403e-01
7.57897124e-02 -8.96250665e-01 9.73818719e-01 -5.83122015e-01
-1.30646372e+00 6.89487100e-01 -3.88422102e-01 -4.39825594e-01
3.53454322e-01 5.59527457e-01 -3.36393714e-01 -2.37805337e-01
-2.72325039e-01 3.55989367e-01 -3.49824615e-02 -6.43304050e-01
-3.09323430e-01 -5.71242750e-01 -4.57914680e-01 -1.92110628e-01
-3.13739985e-01 -2.05213115e-01 -5.78536570e-01 -5.26542246e-01
-8.24141055e-02 -1.15631580e+00 -7.85388947e-01 2.50631243e-01
-5.24726272e-01 -2.64303476e-01 7.28721142e-01 -6.94118142e-01
1.23353219e+00 -2.09492278e+00 7.14320615e-02 2.51631290e-01
1.23056993e-01 8.30213577e-02 1.83966890e-01 5.63651383e-01
-1.62577584e-01 3.98787916e-01 -3.43136787e-01 -7.01874495e-02
-5.24067700e-01 2.28278577e-01 3.90323736e-02 6.50970280e-01
-7.19719008e-03 1.11383104e+00 -8.72872055e-01 -2.48135179e-01
-3.01956147e-01 8.52629840e-01 -3.90870988e-01 7.92566985e-02
-3.53814691e-01 6.18388772e-01 -5.90972245e-01 7.40077198e-01
4.64430481e-01 -2.80961603e-01 2.05323771e-01 1.30604491e-01
-9.52249840e-02 -3.59022230e-01 -5.31034946e-01 1.44257760e+00
-3.37030232e-01 6.49822414e-01 -1.56552821e-01 -8.65519106e-01
7.94883668e-01 4.89423424e-01 8.37368131e-01 -3.47640008e-01
1.79308683e-01 7.06638442e-03 2.05406591e-01 -4.70638037e-01
-1.83062956e-01 -3.09816569e-01 8.41922984e-02 1.47161186e-01
-4.80469465e-01 -3.45565000e-04 9.78552997e-02 2.14124229e-02
1.48210394e+00 -2.77685165e-01 3.86929095e-01 -3.74109536e-01
3.06134790e-01 3.21966887e-01 7.14277625e-01 2.51353800e-01
-5.08499928e-02 4.32677001e-01 1.28248870e+00 -5.60650408e-01
-9.82622087e-01 -5.60462117e-01 -4.60055053e-01 3.64143431e-01
-4.42925245e-01 -3.40901762e-01 -6.32265568e-01 -5.16549706e-01
7.02743530e-02 5.14837146e-01 -9.90163624e-01 -2.65348613e-01
-2.22187042e-01 -1.46763611e+00 9.82466161e-01 3.44228894e-01
1.89950727e-02 -4.55795020e-01 -2.92369634e-01 3.48834008e-01
1.61348477e-01 -4.85559732e-01 -1.67688027e-01 2.95126557e-01
-1.12118721e+00 -1.19111979e+00 -8.83589029e-01 -5.59355974e-01
1.12642789e+00 -3.25897902e-01 7.52475083e-01 1.48666054e-01
-9.11691487e-01 -3.54988016e-02 2.01777026e-01 -6.06629908e-01
-7.76240170e-01 -5.47262356e-02 -2.26361275e-01 -1.71883330e-01
9.55328122e-02 -3.68836552e-01 -7.27397561e-01 3.06855917e-01
-1.00794482e+00 9.88591015e-02 3.84745240e-01 1.09966075e+00
8.37386847e-01 3.35781217e-01 6.48041844e-01 -1.05208826e+00
6.74003303e-01 -8.64441276e-01 -6.77162170e-01 1.34840921e-01
-5.28897047e-01 8.89374092e-02 7.92180300e-01 -3.41743112e-01
-9.60764885e-01 4.27787781e-01 -5.04824698e-01 -1.06330000e-01
-2.75320768e-01 1.03729641e+00 6.06672131e-02 -3.45179625e-02
4.41647202e-01 1.79439485e-01 4.89410400e-01 -3.91225696e-01
-1.25098497e-01 4.75738496e-01 1.57477036e-01 -3.33541423e-01
1.17109798e-01 7.28129506e-01 8.60033333e-01 -7.98852980e-01
-2.31934786e-01 -3.00657898e-01 -4.13254857e-01 -2.92880693e-03
5.77660382e-01 -7.91256487e-01 -1.08238733e+00 7.71568596e-01
-7.38033652e-01 -5.54995835e-01 -7.55854920e-02 2.97032207e-01
-4.44070727e-01 6.00346401e-02 -8.44617903e-01 -6.79668963e-01
-1.83468401e-01 -9.97789860e-01 9.66726840e-01 2.47179285e-01
-3.19922000e-01 -1.56456006e+00 5.51831841e-01 -5.32752693e-01
4.49930847e-01 7.66067445e-01 1.37775886e+00 -6.19678140e-01
-2.84892410e-01 -7.02264905e-01 6.63775057e-02 -2.19822302e-01
1.87396407e-01 5.66762209e-01 -6.75871730e-01 -3.07301819e-01
-2.40861684e-01 2.14131132e-01 5.66973031e-01 7.63534188e-01
1.65645218e+00 -1.50197446e-01 -1.22559690e+00 9.34355795e-01
1.49515021e+00 4.43064600e-01 7.31530428e-01 -7.72079278e-04
1.94262251e-01 4.38947380e-01 4.57989633e-01 3.20302308e-01
5.88019155e-02 6.39669240e-01 2.52453536e-01 -5.73763549e-01
2.49201894e-01 -7.79468641e-02 -1.09329391e-02 9.45309103e-02
-6.96206540e-02 -2.98327416e-01 -1.10372913e+00 5.75091779e-01
-1.72465539e+00 -6.47191763e-01 -4.61351693e-01 2.28375602e+00
8.20885479e-01 -1.95959941e-01 1.44103557e-01 -8.36994499e-02
4.67672795e-01 -5.26344180e-01 -6.33993089e-01 -3.43025029e-01
-2.31073499e-01 3.11253741e-02 3.29383552e-01 2.65703380e-01
-6.86401129e-01 3.84155095e-01 7.57709074e+00 6.85239136e-01
-1.31637990e+00 -1.82503656e-01 1.38091004e+00 9.74910799e-04
-1.54403418e-01 4.71400656e-02 -6.63590074e-01 3.03242862e-01
1.33315861e+00 -4.95880932e-01 -1.41118780e-01 4.90722209e-01
7.19689488e-01 -2.48968393e-01 -1.11026633e+00 4.77686405e-01
-5.81202745e-01 -1.39252198e+00 -3.43135953e-01 5.66111326e-01
7.25090265e-01 -1.56013340e-01 8.75818431e-02 -1.26579800e-03
4.84382242e-01 -1.31475544e+00 -5.03644109e-01 9.00728762e-01
1.04309130e+00 -7.78228939e-01 8.95443082e-01 5.59784651e-01
-6.67710602e-01 -4.35739430e-03 -1.27496600e-01 -3.35150994e-02
1.56237230e-01 8.77006471e-01 -1.35195410e+00 4.69349802e-01
2.65920252e-01 8.43931079e-01 -4.38099861e-01 1.28341150e+00
2.81723976e-01 9.12120998e-01 -3.62391442e-01 -1.53551668e-01
-3.96568999e-02 3.10128443e-02 3.59576374e-01 1.09361625e+00
8.63646686e-01 1.86101258e-01 -2.01166004e-01 7.31081843e-01
3.33663791e-01 4.01073284e-02 -4.50276554e-01 -2.44488671e-01
9.61757600e-02 1.26634681e+00 -8.62804353e-01 -1.56521291e-01
-3.32607061e-01 7.95174122e-01 1.16029903e-01 4.09738630e-01
-7.22972751e-01 -2.74255961e-01 8.90887320e-01 2.56288946e-01
-3.39512855e-01 -1.02271296e-01 -2.98201501e-01 -9.19728458e-01
-5.68535566e-01 -6.38909936e-01 7.69647598e-01 -4.84444499e-01
-1.07935452e+00 2.99964428e-01 -1.09509334e-01 -1.08123147e+00
-2.70845920e-01 -7.49209881e-01 -8.58473420e-01 9.76846159e-01
-1.10511661e+00 -7.83445835e-01 -1.09618150e-01 2.58355051e-01
1.61601067e-01 1.30639583e-01 1.23116529e+00 7.97859952e-02
-1.00110185e+00 3.54731351e-01 5.96096814e-01 -9.80336964e-02
3.55630368e-01 -1.08034217e+00 2.14721322e-01 3.00571412e-01
-4.20196176e-01 5.60279369e-01 8.08331013e-01 -7.18594611e-01
-1.44111359e+00 -1.09033489e+00 7.15794086e-01 -1.23621508e-01
6.73563063e-01 -2.51392573e-01 -1.15172935e+00 5.76059043e-01
-1.62460893e-01 2.35020928e-02 9.36459839e-01 -3.39655182e-03
3.08072567e-01 -2.03274012e-01 -1.11214447e+00 8.03156137e-01
5.24788022e-01 -1.43052310e-01 3.78686547e-01 3.05075198e-01
2.91287690e-01 -5.38188577e-01 -1.10430956e+00 5.24695218e-01
5.96329749e-01 -6.43934250e-01 8.28922153e-01 -7.11358726e-01
3.79282653e-01 -2.49117762e-01 4.13525522e-01 -1.89799416e+00
-3.14521343e-01 -5.67819297e-01 -1.46630325e-03 9.30490553e-01
4.60838854e-01 -8.41515422e-01 1.00795197e+00 7.34377265e-01
4.25789580e-02 -1.37467837e+00 -1.01986551e+00 -4.94456917e-01
3.43045592e-01 -1.33235842e-01 5.66287577e-01 6.97763562e-01
3.95909667e-01 -3.47733408e-01 -8.04823488e-02 9.58347842e-02
2.71827519e-01 -2.92940438e-01 4.38435107e-01 -1.35114408e+00
-3.26193154e-01 -5.13027191e-01 -6.26903713e-01 -4.61971521e-01
2.52287596e-01 -9.31880534e-01 -1.41541481e-01 -1.26496780e+00
5.73894262e-01 -6.07398570e-01 -4.34392512e-01 5.88578522e-01
-2.16131195e-01 9.26992372e-02 -5.75815916e-01 -7.85310492e-02
2.34289229e-01 1.58222929e-01 1.26276839e+00 -4.27987166e-02
-2.08512366e-01 1.73044339e-01 -7.39264250e-01 6.84061468e-01
7.55060256e-01 -5.05681455e-01 1.84787456e-02 3.19516450e-01
2.76361406e-01 5.20981908e-01 4.99968767e-01 -8.04083526e-01
3.93462330e-01 -1.61074251e-01 5.69614172e-01 -5.54247975e-01
1.18451700e-01 -8.91602695e-01 8.41028214e-01 9.65900421e-01
-3.11478287e-01 -9.24584195e-02 5.90877056e-01 4.94878292e-01
-2.24070266e-01 4.31176722e-02 5.48888743e-01 7.63280913e-02
-2.99189180e-01 5.57720423e-01 -7.45182097e-01 -5.73467076e-01
1.30177677e+00 2.45521143e-01 -2.75959224e-01 -3.64610970e-01
-1.04483116e+00 2.61308163e-01 5.56437492e-01 -1.55223444e-01
3.23129147e-01 -1.09067953e+00 -7.28431761e-01 1.57998323e-01
1.76531076e-01 -7.90087730e-02 4.12632227e-01 1.09092104e+00
-4.91091520e-01 5.54950595e-01 7.33273029e-02 -6.67164087e-01
-1.42323983e+00 4.81562167e-01 7.61094272e-01 -5.98176181e-01
-4.24543053e-01 4.83581096e-01 3.64245385e-01 -3.00784349e-01
-6.74317256e-02 -1.43346116e-01 -1.39089882e-01 -1.09840505e-01
3.37802231e-01 4.37414169e-01 6.21230761e-03 -2.96494603e-01
-1.09913357e-01 4.84419942e-01 1.15910703e-02 3.03798705e-01
1.38165534e+00 1.74233049e-01 -4.07109886e-01 7.21104205e-01
1.36040473e+00 -2.78820813e-01 -1.05391026e+00 2.43045703e-01
-2.02573705e-02 -1.16752803e-01 7.81893209e-02 -9.54965413e-01
-1.01908863e+00 7.23995507e-01 5.35288393e-01 3.48754078e-01
1.32468379e+00 1.34886041e-01 5.36961675e-01 1.18454127e-02
7.62860253e-02 -4.33150530e-01 -4.80167449e-01 3.75974923e-01
4.02572751e-01 -9.15927172e-01 -2.09294364e-01 -7.01519191e-01
-2.32139498e-01 1.40450895e+00 2.65673548e-01 2.47504395e-02
8.32921743e-01 7.27583230e-01 1.52132347e-01 -2.50605673e-01
-1.15925324e+00 3.17712873e-01 -1.00646298e-02 4.05526042e-01
8.78722370e-01 2.19680697e-01 -5.07119656e-01 5.75517118e-01
1.89004630e-01 5.40268898e-01 5.95151722e-01 6.79856420e-01
8.81928653e-02 -1.15345693e+00 -3.08928847e-01 6.61517143e-01
-7.27594256e-01 -2.19954681e-02 -2.84968376e-01 8.03562820e-01
-2.76570946e-01 4.21875000e-01 2.98658401e-01 6.71050102e-02
1.87778279e-01 2.69754648e-01 9.14224610e-02 -2.81678915e-01
-3.13473523e-01 2.42407516e-01 7.17041548e-03 -3.62609059e-01
2.18419775e-01 -8.47295165e-01 -1.46795523e+00 -2.14270532e-01
-2.47488365e-01 2.58957207e-01 8.08324754e-01 7.10401475e-01
6.34194076e-01 8.12571466e-01 5.55357516e-01 -4.24191296e-01
-1.60526559e-01 -6.27851367e-01 -7.99077392e-01 3.15124355e-02
3.27352524e-01 -1.43286869e-01 -3.99247348e-01 1.63063452e-01] | [6.058891296386719, 5.539056777954102] |
878687d3-f91d-497f-b591-82d5b2926684 | hide-and-tell-learning-to-bridge-photo | 2002.00774 | null | https://arxiv.org/abs/2002.00774v1 | https://arxiv.org/pdf/2002.00774v1.pdf | Hide-and-Tell: Learning to Bridge Photo Streams for Visual Storytelling | Visual storytelling is a task of creating a short story based on photo streams. Unlike existing visual captioning, storytelling aims to contain not only factual descriptions, but also human-like narration and semantics. However, the VIST dataset consists only of a small, fixed number of photos per story. Therefore, the main challenge of visual storytelling is to fill in the visual gap between photos with narrative and imaginative story. In this paper, we propose to explicitly learn to imagine a storyline that bridges the visual gap. During training, one or more photos is randomly omitted from the input stack, and we train the network to produce a full plausible story even with missing photo(s). Furthermore, we propose for visual storytelling a hide-and-tell model, which is designed to learn non-local relations across the photo streams and to refine and improve conventional RNN-based models. In experiments, we show that our scheme of hide-and-tell, and the network design are indeed effective at storytelling, and that our model outperforms previous state-of-the-art methods in automatic metrics. Finally, we qualitatively show the learned ability to interpolate storyline over visual gaps. | ['Kyung-Su Kim', 'Sanghyun Woo', 'Dahun Kim', 'Yunjae Jung', 'Sungjin Kim', 'In So Kweon'] | 2020-02-03 | null | null | null | null | ['visual-storytelling'] | ['natural-language-processing'] | [ 2.39617124e-01 5.87921619e-01 -2.32151449e-02 -3.58867854e-01
-6.36430323e-01 -6.00396633e-01 1.07047641e+00 -6.98924437e-02
2.89110005e-01 8.40038657e-01 7.92341053e-01 -1.18249550e-01
2.02522278e-01 -8.54396522e-01 -1.21589887e+00 -1.72440901e-01
2.32129365e-01 4.85881686e-01 3.83284427e-02 -1.97771192e-01
-9.97183695e-02 1.14986084e-01 -1.53672206e+00 9.46049273e-01
4.90541488e-01 6.02212071e-01 5.86688995e-01 6.92290545e-01
-3.97789031e-01 1.48596108e+00 -6.66310608e-01 -5.10600984e-01
-6.00932054e-02 -8.50162566e-01 -8.24144423e-01 4.46151078e-01
6.58051729e-01 -6.29767597e-01 -6.89120591e-01 5.91128528e-01
1.66699722e-01 1.87742561e-01 6.77646935e-01 -1.52583063e+00
-1.01289606e+00 1.06221616e+00 -3.22214812e-01 -5.02906561e-01
9.18091714e-01 4.93015498e-01 9.02604222e-01 -1.16513634e+00
1.25028002e+00 1.11708128e+00 5.96925914e-01 7.34462440e-01
-1.16928554e+00 -3.83934408e-01 1.51742876e-01 3.36248308e-01
-1.37749898e+00 -4.12382871e-01 9.37980890e-01 -5.09252250e-01
6.99260175e-01 3.17423671e-01 1.23778355e+00 1.50405157e+00
-4.92917687e-01 1.08104861e+00 8.38554144e-01 -3.58992755e-01
2.16884874e-02 1.55614093e-01 -5.72901368e-01 5.17644823e-01
-2.61253804e-01 -4.97143902e-02 -8.55850816e-01 3.18355888e-01
1.25002098e+00 8.55558515e-02 -4.44808185e-01 -5.34969151e-01
-1.62269819e+00 6.07571900e-01 5.89314878e-01 2.30683029e-01
-4.79869843e-01 4.45562661e-01 1.65042818e-01 -1.26544461e-01
3.75126302e-01 5.20160615e-01 3.75739336e-01 -1.00036979e-01
-1.26210809e+00 4.55904156e-01 6.28893375e-01 1.23672879e+00
4.98798013e-01 1.42851487e-01 -5.56539357e-01 6.20931923e-01
-1.57079250e-02 1.97810069e-01 -4.86324877e-02 -1.25122380e+00
7.22918093e-01 5.14513075e-01 2.89934784e-01 -7.14061320e-01
-8.05823281e-02 -1.40685007e-01 -9.46561515e-01 1.08484574e-01
4.72284466e-01 -9.09518376e-02 -8.63191962e-01 1.68063509e+00
1.01649478e-01 4.63314354e-01 9.94383171e-02 9.37162519e-01
1.34360003e+00 1.07264769e+00 3.13279368e-02 -1.55711740e-01
1.18755376e+00 -1.24953759e+00 -9.82158780e-01 -4.96987909e-01
3.76245111e-01 -6.25823915e-01 1.41113567e+00 8.50847643e-03
-1.55632555e+00 -4.67060804e-01 -1.05352759e+00 -4.04089779e-01
-1.82558104e-01 3.99522856e-02 4.43028897e-01 -1.62685841e-01
-1.17953014e+00 5.62954724e-01 -1.58418298e-01 -4.40802038e-01
5.69822609e-01 -5.06914258e-01 -6.00026369e-01 -3.54431033e-01
-1.14017093e+00 8.35764825e-01 6.84920967e-01 -5.13693355e-02
-1.11793423e+00 -8.35171163e-01 -1.21532440e+00 8.93924162e-02
3.91633600e-01 -1.10141957e+00 1.33272886e+00 -9.56136048e-01
-1.22605860e+00 8.25085223e-01 -1.25962704e-01 -5.57418764e-01
8.71049762e-01 -3.40891397e-03 -1.51410609e-01 3.83565813e-01
1.37711450e-01 1.37705946e+00 5.57114303e-01 -1.94722641e+00
-2.68514931e-01 3.42463583e-01 4.32989389e-01 4.23903883e-01
1.88217070e-02 -2.61861652e-01 -5.85835695e-01 -6.52082801e-01
-1.72599122e-01 -4.83878553e-01 5.04910666e-03 2.90209532e-01
-7.66328335e-01 -2.30542524e-03 8.27608764e-01 -7.21021593e-01
8.83243322e-01 -2.15221858e+00 -1.73647248e-04 -1.77981660e-01
2.81861931e-01 -1.60751250e-02 -2.33682901e-01 8.99662852e-01
-9.78612825e-02 7.42046684e-02 -4.13464934e-01 -8.03575575e-01
-3.85781890e-03 2.29721308e-01 -5.45744419e-01 8.52114111e-02
1.64987773e-01 1.21640635e+00 -1.09835780e+00 -6.74167693e-01
5.46233952e-01 6.38260245e-01 -2.42701665e-01 4.81201470e-01
-7.25354254e-01 4.25099283e-01 1.07873738e-01 3.05631131e-01
4.68964428e-01 -4.82375890e-01 8.71990100e-02 -1.02656744e-01
-1.93242669e-01 5.17603695e-01 -8.65719259e-01 2.29947066e+00
-4.86418515e-01 1.27833045e+00 -5.36337078e-01 -4.72233653e-01
7.76928663e-01 5.85704565e-01 9.41378623e-02 -5.11646926e-01
-6.03253655e-02 -2.16313511e-01 -6.93407416e-01 -7.08481491e-01
7.17501342e-01 -2.93922842e-01 3.91689566e-04 6.92905784e-01
-3.78390700e-02 -5.08449614e-01 2.64377147e-01 4.86835778e-01
8.41395915e-01 5.45981765e-01 2.19794199e-01 5.37277222e-01
-7.41006434e-02 3.48040998e-01 5.35938852e-02 7.56271303e-01
2.59500951e-01 1.40931129e+00 7.20245481e-01 -3.32313627e-01
-1.46016169e+00 -1.24359012e+00 3.50472808e-01 6.09104574e-01
4.07552302e-01 -5.23800731e-01 -8.76466513e-01 -5.73137701e-01
-3.65155101e-01 1.37676752e+00 -6.82930946e-01 1.10559292e-01
-6.46238089e-01 9.17696133e-02 3.96489292e-01 5.56689680e-01
6.33884132e-01 -1.54070830e+00 -6.21878624e-01 9.05798376e-02
-6.76527917e-01 -1.23507643e+00 -6.14334643e-01 -3.88890386e-01
-4.37990040e-01 -8.65748823e-01 -9.46490943e-01 -9.53403890e-01
7.15413868e-01 5.77338576e-01 1.34295774e+00 3.77731374e-03
1.98007673e-01 3.00223857e-01 -3.84422004e-01 -1.63878739e-01
-5.21130502e-01 -3.64388764e-01 -6.04611456e-01 -1.22001432e-01
-2.68864721e-01 -8.35710287e-01 -6.49164736e-01 -3.91367152e-02
-1.09085071e+00 1.27430356e+00 4.03587043e-01 7.00373650e-01
4.23720449e-01 -2.12128118e-01 2.61012644e-01 -8.03087831e-01
5.03051937e-01 -5.68457961e-01 1.47628427e-01 3.06541800e-01
6.85065985e-02 -1.54472262e-01 6.78333998e-01 -6.71509743e-01
-1.22326899e+00 1.78379178e-01 2.61030160e-02 -7.82070100e-01
-1.26801983e-01 3.89826089e-01 -1.88547075e-01 4.74124670e-01
5.66240370e-01 2.57801294e-01 -3.39978248e-01 -1.66078657e-01
1.08842826e+00 2.29453892e-01 9.90009069e-01 -9.22258347e-02
9.31227326e-01 6.28512621e-01 -3.11464220e-01 -5.36110163e-01
-9.21284914e-01 -1.13169685e-01 -4.85497236e-01 -8.59384835e-01
8.35007906e-01 -1.03873610e+00 -5.41229725e-01 5.76355979e-02
-1.78728580e+00 -6.00639701e-01 -8.35102081e-01 2.53771305e-01
-1.04538977e+00 -4.20813262e-02 -4.63389099e-01 -7.13839650e-01
-1.09550040e-02 -5.26473165e-01 9.77747738e-01 2.11293682e-01
-5.59577942e-01 -8.43132675e-01 -1.55441344e-01 3.24538469e-01
-2.98277624e-02 8.49660695e-01 6.76340282e-01 -1.91591546e-01
-8.62844944e-01 -6.49902225e-02 -5.42423785e-01 -1.09521046e-01
-1.83943301e-01 -9.89560485e-02 -9.75223958e-01 2.77590036e-01
-2.45372653e-01 -5.35062075e-01 7.95919895e-01 3.42272371e-01
1.00815427e+00 -6.88264549e-01 -1.93239421e-01 5.35672009e-01
1.34472322e+00 1.48104161e-01 1.05927336e+00 2.52586216e-01
1.00392318e+00 9.48870599e-01 4.86198366e-01 4.52497393e-01
7.60717690e-01 4.67557937e-01 6.42230093e-01 -3.44921052e-01
-7.11743772e-01 -1.32366264e+00 2.44692132e-01 4.61816341e-01
8.72217044e-02 -6.24705911e-01 -7.74180353e-01 9.14067507e-01
-2.20401883e+00 -1.40978277e+00 -2.85156369e-01 1.83480370e+00
7.94503927e-01 2.95136310e-02 1.36966258e-01 1.25572547e-01
7.94605076e-01 5.84789217e-01 -3.80560845e-01 -1.57968760e-01
-4.84362483e-01 -3.50560308e-01 2.10364506e-01 4.60673392e-01
-5.64105809e-01 1.11196244e+00 6.51766300e+00 8.14328492e-01
-7.17526674e-01 5.50059900e-02 5.36770523e-01 -3.30055535e-01
-8.23092878e-01 1.79537997e-01 -1.40047669e-01 1.58040822e-01
3.87920082e-01 -1.26862109e-01 5.75471163e-01 6.49538100e-01
5.06527841e-01 -1.43057689e-01 -1.36688304e+00 1.10020530e+00
4.32852924e-01 -2.11851645e+00 4.09588009e-01 -4.44598436e-01
8.99322391e-01 -6.69951200e-01 -1.15970038e-01 8.26203004e-02
4.30545449e-01 -1.30213106e+00 1.44216251e+00 6.49096966e-01
1.15498936e+00 -6.69006824e-01 3.36033165e-01 4.87623066e-01
-1.20738196e+00 2.40237281e-01 5.66986902e-03 -2.79821903e-01
7.56317019e-01 2.89827228e-01 -9.59763229e-01 3.95892084e-01
3.40007067e-01 9.77012992e-01 -2.65522569e-01 1.13136292e+00
-7.91949451e-01 2.59093940e-01 1.81972802e-01 -5.95748909e-02
2.65403569e-01 8.65262598e-02 5.54419219e-01 1.12333810e+00
6.23830020e-01 2.12066412e-01 -1.47742584e-01 1.32991588e+00
-3.82661492e-01 -1.65975675e-01 -1.04749846e+00 -1.03775688e-01
5.76819420e-01 9.66839492e-01 -5.95376611e-01 -5.01862526e-01
-1.70401856e-01 1.15094662e+00 4.32679415e-01 6.05826795e-01
-9.23147023e-01 -2.14049682e-01 2.34593794e-01 5.13143718e-01
1.77537650e-01 -1.24663584e-01 -4.39343393e-01 -9.53666508e-01
1.46410480e-01 -4.45260733e-01 3.44902575e-02 -2.01118970e+00
-9.91964161e-01 5.19201040e-01 2.61801958e-01 -1.36777890e+00
-5.10790408e-01 9.12141949e-02 -9.45128560e-01 5.52989185e-01
-1.15223181e+00 -1.68288827e+00 -5.89868605e-01 4.40924376e-01
9.48166013e-01 3.51313651e-01 4.48724329e-01 -1.35544375e-01
-3.02226581e-02 1.08307034e-01 -2.29885995e-01 7.56059214e-02
5.71963787e-01 -1.19510889e+00 6.60573542e-01 7.74527311e-01
4.59943563e-01 5.72314523e-02 1.24676609e+00 -7.13726580e-01
-9.05577719e-01 -1.20180786e+00 1.16716278e+00 -3.85262281e-01
4.83764768e-01 -6.67185605e-01 -9.21089888e-01 8.92741680e-01
7.32542872e-01 -3.12782705e-01 2.44102195e-01 -3.89042377e-01
-5.11234641e-01 2.95255959e-01 -9.59307909e-01 1.07357490e+00
1.50697994e+00 -6.11595631e-01 -7.72775710e-01 5.57383597e-01
1.14346504e+00 -5.89721441e-01 -3.99061412e-01 -2.21621349e-01
5.46123922e-01 -1.12878573e+00 1.14602089e+00 -4.17535007e-01
1.31086588e+00 -3.52273613e-01 1.71232715e-01 -1.39539397e+00
-6.54743165e-02 -8.96327317e-01 -6.06584549e-02 1.52310514e+00
4.09887642e-01 1.22896492e-01 7.63398468e-01 4.09107625e-01
-3.02613288e-01 -4.33794230e-01 -6.70049012e-01 -6.36241138e-01
-2.42722541e-01 -5.36875188e-01 8.64929318e-01 1.04675007e+00
2.69327849e-01 4.60225195e-01 -8.68395984e-01 -1.93209350e-01
4.90918279e-01 9.35895666e-02 8.63973737e-01 -6.58699095e-01
-2.07175449e-01 -2.72702247e-01 7.77193829e-02 -1.17134988e+00
4.45215143e-02 -6.26880229e-01 2.93245167e-01 -2.39278316e+00
3.70923012e-01 1.22792646e-02 3.73269111e-01 5.15073001e-01
5.54600507e-02 3.92201215e-01 5.72533369e-01 2.57068574e-01
-7.21199334e-01 5.84364891e-01 1.82282829e+00 -2.13737786e-01
-2.17901304e-01 -4.53620344e-01 -6.09967828e-01 6.41791224e-01
5.65820336e-01 -4.32608724e-01 -6.70293748e-01 -3.83091241e-01
4.83659297e-01 7.07755327e-01 8.65054309e-01 -8.83523703e-01
2.57501394e-01 -3.78511190e-01 4.56785738e-01 -9.70964789e-01
8.12666178e-01 -5.91870368e-01 6.97866082e-01 -7.46342018e-02
-7.62817740e-01 -1.38278678e-01 -4.33256775e-02 4.68435794e-01
-2.20603555e-01 -1.49821654e-01 3.62197459e-01 -2.66374856e-01
-5.27243376e-01 9.06256735e-02 -2.91803122e-01 4.02260795e-02
1.13346314e+00 -5.46441019e-01 -5.92879295e-01 -9.84155595e-01
-5.81592977e-01 3.26432377e-01 6.77247941e-01 4.89555866e-01
9.59517241e-01 -1.86330998e+00 -8.05453539e-01 -2.57469535e-01
2.87924260e-01 4.38164413e-01 5.45363367e-01 2.38464907e-01
-6.23002887e-01 1.97318211e-01 -2.77727485e-01 -4.37838525e-01
-1.13387704e+00 6.11181736e-01 -1.60565637e-02 -1.86476540e-02
-1.05802727e+00 7.23885655e-01 4.89218503e-01 3.85717377e-02
2.31714219e-01 -1.60143927e-01 -3.40175450e-01 2.38767006e-02
6.50330365e-01 9.74467173e-02 -7.06569850e-01 -6.38331115e-01
2.17603713e-01 2.35219672e-01 3.32373917e-01 -6.09638810e-01
1.32425511e+00 -3.19483817e-01 2.68170983e-01 7.76171148e-01
8.60301077e-01 -3.72529119e-01 -1.82219851e+00 -1.05737552e-01
-3.94110650e-01 -5.29298961e-01 -3.01726520e-01 -8.59258890e-01
-6.94415867e-01 9.88151550e-01 -2.35212058e-01 4.00736928e-01
9.36547697e-01 3.93251628e-01 9.44306672e-01 -1.25472676e-02
1.46901637e-01 -7.31508017e-01 3.72446567e-01 1.56903967e-01
1.46926200e+00 -1.01684403e+00 -8.17388371e-02 -5.19708574e-01
-1.00956166e+00 1.00197804e+00 6.45803273e-01 3.21709849e-02
-1.51984259e-01 1.15360655e-01 -1.36701420e-01 -2.42756069e-01
-9.40676212e-01 -2.11341992e-01 2.38617659e-01 8.58589590e-01
1.20862991e-01 3.43002751e-02 1.98579535e-01 4.09860969e-01
-5.48220873e-01 7.57572725e-02 7.91451693e-01 6.71151996e-01
-3.79992545e-01 -5.81625700e-01 -4.34442401e-01 9.58602726e-02
2.99189121e-01 -1.13200516e-01 -7.73043811e-01 1.08857453e+00
2.11695552e-01 9.12357390e-01 2.89685279e-01 -2.20573485e-01
3.15745473e-01 -1.20180935e-01 5.85784078e-01 -5.33098161e-01
-4.15723443e-01 -2.09418312e-01 4.33043331e-01 -4.47901279e-01
-4.55183715e-01 -4.65914518e-01 -1.26358902e+00 -5.65978348e-01
1.97534278e-01 -2.04663768e-01 5.74400067e-01 1.10132229e+00
5.35682105e-02 6.86419785e-01 3.33474785e-01 -9.90860939e-01
4.00456637e-01 -8.41757298e-01 -4.11280364e-01 5.90525806e-01
3.34821075e-01 -4.00678366e-01 -1.84207797e-01 5.63642085e-01] | [11.203455924987793, 0.7780712246894836] |
6ea5d9c0-c13b-4ce0-b201-96705dbf1caa | hact-net-a-hierarchical-cell-to-tissue-graph | 2007.00584 | null | https://arxiv.org/abs/2007.00584v1 | https://arxiv.org/pdf/2007.00584v1.pdf | HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification | Cancer diagnosis, prognosis, and therapeutic response prediction are heavily influenced by the relationship between the histopathological structures and the function of the tissue. Recent approaches acknowledging the structure-function relationship, have linked the structural and spatial patterns of cell organization in tissue via cell-graphs to tumor grades. Though cell organization is imperative, it is insufficient to entirely represent the histopathological structure. We propose a novel hierarchical cell-to-tissue-graph (HACT) representation to improve the structural depiction of the tissue. It consists of a low-level cell-graph, capturing cell morphology and interactions, a high-level tissue-graph, capturing morphology and spatial distribution of tissue parts, and cells-to-tissue hierarchies, encoding the relative spatial distribution of the cells with respect to the tissue distribution. Further, a hierarchical graph neural network (HACT-Net) is proposed to efficiently map the HACT representations to histopathological breast cancer subtypes. We assess the methodology on a large set of annotated tissue regions of interest from H\&E stained breast carcinoma whole-slides. Upon evaluation, the proposed method outperformed recent convolutional neural network and graph neural network approaches for breast cancer multi-class subtyping. The proposed entity-based topological analysis is more inline with the pathological diagnostic procedure of the tissue. It provides more command over the tissue modelling, therefore encourages the further inclusion of pathological priors into task-specific tissue representation. | ['Maria Gabrani', 'Maria Frucci', 'Jean-Philippe Thiran', 'Orcun Goksel', 'Gerardo Botti', 'Giuseppe De Pietro', 'Nadia Brancati', 'Giosue Scognamiglio', 'Lauren Alisha Fernandes', 'Pushpak Pati', 'Guillaume Jaume', 'Florinda Feroce', 'Antonio Foncubierta', 'Anna Maria Anniciello', 'Maurizio Do Bonito', 'Daniel Riccio'] | 2020-07-01 | null | null | null | null | ['histopathological-image-classification'] | ['medical'] | [ 1.70999840e-01 5.40054619e-01 -3.53020698e-01 -1.34889096e-01
-1.74556389e-01 -4.56860721e-01 6.93682313e-01 1.05012476e+00
-1.07386962e-01 4.54968870e-01 2.35439166e-01 -5.11392951e-01
-4.56851512e-01 -1.05765855e+00 -3.94090801e-01 -9.94951904e-01
-5.29349148e-01 7.31219113e-01 2.71264553e-01 -1.73694164e-01
8.76182243e-02 1.05328166e+00 -1.04634643e+00 5.82457483e-01
5.12382269e-01 1.07755244e+00 -8.56977236e-03 7.74928331e-01
-2.77120650e-01 9.96382177e-01 -1.20836325e-01 -9.94075015e-02
-3.39384556e-01 -1.70075670e-01 -8.31356764e-01 -1.96224954e-02
5.58824956e-01 2.82501817e-01 -2.66169399e-01 9.57748711e-01
1.33699700e-01 -5.37451446e-01 1.15388501e+00 -9.85728204e-01
-3.15840662e-01 2.62234777e-01 -4.62164879e-01 9.80951786e-02
-6.93280548e-02 -6.96504340e-02 1.02719712e+00 -4.57381040e-01
1.14486277e+00 8.60473931e-01 9.05312300e-01 2.26473942e-01
-1.28632593e+00 -1.61036998e-01 -1.06443152e-01 2.38769189e-01
-1.32868087e+00 1.64362136e-02 8.63128960e-01 -8.26955020e-01
7.08474457e-01 4.38761771e-01 1.14070165e+00 6.81430519e-01
8.37266266e-01 4.99072522e-01 1.19291437e+00 -2.95690387e-01
2.57142544e-01 -1.18358374e-01 4.99114990e-01 1.09124613e+00
4.53308493e-01 -2.82584369e-01 -6.58413619e-02 -2.40102589e-01
8.17303538e-01 2.05763057e-01 -2.51400441e-01 -7.43436158e-01
-9.91860986e-01 6.29151940e-01 9.56091166e-01 7.74678826e-01
-4.39477265e-01 3.67870241e-01 8.10010552e-01 -1.37639239e-01
5.73905766e-01 1.66624546e-01 -1.75812513e-01 5.63813090e-01
-1.19104290e+00 1.27931340e-02 7.94832110e-01 2.92899221e-01
6.08273625e-01 -2.45590270e-01 -2.22864956e-01 5.18235326e-01
3.58189642e-01 -1.42698690e-01 5.90620458e-01 -4.15649146e-01
-1.52304947e-01 1.43645263e+00 -4.92157996e-01 -1.52986705e+00
-9.91693258e-01 -6.50731146e-01 -1.57428575e+00 1.61642253e-01
5.40367484e-01 7.43966937e-01 -9.88211989e-01 1.27102089e+00
3.65061820e-01 5.78622408e-02 -1.47135437e-01 6.11172259e-01
1.01227164e+00 1.18045136e-01 2.40275726e-01 -1.49870679e-01
1.65978920e+00 -4.35438842e-01 -6.80765927e-01 1.34464502e-01
1.28901887e+00 -2.88750101e-02 5.15997946e-01 -2.35578552e-01
-9.05515850e-01 -1.84555188e-01 -8.59099388e-01 -5.22652939e-02
-8.23840261e-01 4.04457211e-01 8.12242925e-01 2.25674748e-01
-1.38696027e+00 4.51016247e-01 -9.97506738e-01 -5.98110735e-01
8.31578493e-01 5.19129217e-01 -8.07132602e-01 2.31197894e-01
-7.85009503e-01 8.36913168e-01 4.66304213e-01 3.27799797e-01
-6.13334894e-01 -8.96941364e-01 -8.75643253e-01 2.18236789e-01
-2.52469093e-01 -8.32816184e-01 5.29420972e-01 -5.44911623e-01
-8.62393796e-01 1.28819096e+00 -1.59862041e-01 -3.86187375e-01
4.96450573e-01 8.90363336e-01 -1.51144683e-01 4.04396474e-01
-1.13455795e-01 6.92564964e-01 6.50807917e-02 -1.33771205e+00
-4.97877121e-01 -6.17050707e-01 -3.00821751e-01 8.21214076e-03
-3.50114971e-01 -6.35196626e-01 -3.61753225e-01 -5.77269852e-01
3.71845692e-01 -8.00601006e-01 -4.67332810e-01 4.09099668e-01
-4.85380948e-01 -4.08334583e-02 1.10134530e+00 -5.95050931e-01
1.28991377e+00 -2.13933539e+00 3.30146939e-01 5.44437170e-01
7.53508985e-01 -6.69665262e-02 1.52748786e-02 3.96541893e-01
-1.57631993e-01 2.76046067e-01 -2.06783876e-01 -5.28827831e-02
-2.03558400e-01 5.58457822e-02 4.13652062e-01 9.07877982e-01
-1.42455082e-02 1.22680211e+00 -6.84016109e-01 -9.24974561e-01
1.00198932e-01 5.85518122e-01 -5.61324954e-01 -1.30708411e-01
-3.43860202e-02 1.00998595e-01 -3.25824171e-01 8.07291508e-01
5.04754961e-01 -4.73169237e-01 6.26177251e-01 -6.97141349e-01
3.21839809e-01 -2.57327408e-01 -5.32301068e-01 9.82839286e-01
-2.44655535e-01 9.65018868e-01 5.95769823e-01 -1.09016550e+00
7.65089989e-01 2.45781586e-01 9.59101319e-01 -4.63719785e-01
3.38584274e-01 2.55736917e-01 3.10163587e-01 -4.07559842e-01
1.83834389e-01 -1.35013267e-01 4.33297195e-02 4.77163009e-02
-6.77671507e-02 -1.40886952e-03 2.00969160e-01 2.00904757e-01
1.22324014e+00 -2.36480072e-01 6.01940155e-01 -8.05963635e-01
6.19683921e-01 2.01927260e-01 2.75994480e-01 1.75765499e-01
-2.53903449e-01 4.21995044e-01 1.07831573e+00 -8.37111890e-01
-8.14072967e-01 -7.46245444e-01 -4.19097215e-01 7.38484323e-01
1.41978443e-01 -1.13289520e-01 -5.90005398e-01 -5.90778410e-01
3.00678164e-01 2.51366720e-02 -1.46485054e+00 -1.32157952e-01
-6.74915612e-01 -9.27052200e-01 7.20124781e-01 4.09999013e-01
1.24054812e-01 -9.38963771e-01 -5.56324065e-01 1.40901625e-01
-4.61445563e-02 -9.23960447e-01 -1.59218330e-02 4.99130458e-01
-1.08023608e+00 -1.43663561e+00 -4.56570297e-01 -1.05876207e+00
1.24495268e+00 -2.88669437e-01 1.05135334e+00 5.68230808e-01
-7.39457965e-01 1.14591502e-01 -1.10813715e-01 -2.59021521e-01
-6.40259981e-01 1.60128906e-01 -3.09682608e-01 8.33779201e-02
-7.20875189e-02 -6.29482985e-01 -6.80782199e-01 1.96001410e-01
-9.89507496e-01 2.44052812e-01 6.94468081e-01 1.00126040e+00
9.36603904e-01 1.37246668e-01 -1.69139616e-02 -1.18022203e+00
5.53942263e-01 -4.70469445e-01 -1.45173803e-01 3.18138003e-01
-3.50690514e-01 -1.22631103e-01 6.36964202e-01 -1.39766753e-01
-5.35340726e-01 2.04969957e-01 4.30678315e-02 -1.81929201e-01
-1.56981245e-01 8.58318388e-01 4.73145097e-02 -2.98068196e-01
5.91179907e-01 2.30074629e-01 3.41021776e-01 5.46018966e-02
8.95229876e-02 3.26345474e-01 5.85415065e-01 -3.07724804e-01
3.40856940e-01 7.23504066e-01 8.99680614e-01 -7.04814494e-01
-2.42582306e-01 -3.92019033e-01 -9.96477246e-01 -3.27878237e-01
9.02830422e-01 -4.13718969e-01 -8.19875836e-01 3.34312767e-01
-8.88443649e-01 -5.38583517e-01 -1.06610462e-01 1.72451079e-01
-5.53840041e-01 2.15556607e-01 -9.31872785e-01 -3.04530323e-01
-3.24652284e-01 -8.76613021e-01 1.22237074e+00 -1.63428649e-01
-1.70210764e-01 -1.69437242e+00 1.54218480e-01 5.48452176e-02
3.85319591e-01 9.34240580e-01 1.78229535e+00 -4.77926016e-01
-3.81122202e-01 -5.50431252e-01 -4.15273428e-01 -3.92304659e-01
2.50555366e-01 4.00769413e-01 -5.56635797e-01 -2.85956949e-01
-5.89572072e-01 1.09917775e-01 9.05175924e-01 7.78349876e-01
1.24140477e+00 -5.66069126e-01 -1.09793723e+00 8.02333832e-01
1.60369790e+00 -1.18339129e-01 5.43427110e-01 3.46716017e-01
9.48317230e-01 9.19236839e-01 2.87410058e-02 9.85539705e-02
4.39396858e-01 5.69662213e-01 7.87554502e-01 -7.76515961e-01
-3.71082276e-01 -4.98218043e-03 -2.35643297e-01 5.38841724e-01
-2.11384133e-01 -3.43047261e-01 -1.32777047e+00 6.42172515e-01
-1.59184110e+00 -8.24487448e-01 -6.05511665e-01 1.60242510e+00
5.82817674e-01 7.42829293e-02 5.98702952e-03 1.23076349e-01
6.15233302e-01 2.78427657e-02 -4.37495410e-01 -3.38227719e-01
-1.61105692e-02 -2.09687620e-01 4.79083627e-01 5.09728193e-01
-8.07966411e-01 5.74923754e-01 6.30299664e+00 8.43128324e-01
-1.43284941e+00 -1.94974706e-01 1.21590126e+00 3.43490124e-01
-3.24311525e-01 -2.89227903e-01 -4.47053909e-01 1.96190149e-01
6.62704825e-01 -4.07310016e-02 -1.76119238e-01 5.32533228e-01
2.05347687e-01 9.77422595e-02 -1.23434913e+00 5.36131918e-01
-2.81661749e-01 -1.81309879e+00 3.51449192e-01 6.24887824e-01
2.42862135e-01 -6.15620464e-02 -2.96016455e-01 -8.36242177e-03
1.21669702e-01 -1.23875749e+00 4.45399970e-01 6.96805239e-01
1.17223549e+00 -3.24066013e-01 1.16119134e+00 3.70968282e-01
-1.65246606e+00 -1.49094850e-01 -1.63965479e-01 3.44809145e-01
-2.72559881e-01 3.95792067e-01 -1.20540261e+00 6.63857043e-01
4.03476596e-01 7.16908157e-01 -1.08293653e+00 8.45157564e-01
6.36539459e-01 4.86452490e-01 -7.76357157e-03 -1.38576448e-01
2.30113000e-01 -5.65420836e-02 2.31412768e-01 1.75407493e+00
2.83085108e-01 2.28188355e-02 -2.41404511e-02 6.06678486e-01
1.32203579e-01 2.39164472e-01 -5.31464398e-01 -1.24454908e-01
5.69777638e-02 1.75647140e+00 -1.45064104e+00 -2.32862294e-01
1.81102101e-02 4.27201241e-01 6.33882880e-01 2.82510817e-01
-4.88265872e-01 -1.03437692e-01 2.29560181e-01 8.19466233e-01
-1.62727684e-01 6.68772385e-02 -4.61873740e-01 -4.24043775e-01
-2.31903344e-01 -4.72699344e-01 5.06097078e-01 -5.76152802e-01
-1.31174731e+00 6.61421120e-01 -1.89630426e-02 -1.23027706e+00
6.87078610e-02 -8.71306360e-01 -8.25441718e-01 5.58723927e-01
-1.26021051e+00 -1.62133563e+00 -5.77655494e-01 1.02332629e-01
-3.18975486e-02 -5.49056865e-02 9.78457808e-01 -4.99608926e-02
-4.06434506e-01 3.90964627e-01 -6.83218688e-02 2.25004688e-01
-1.12927305e-02 -1.51141071e+00 -2.07561240e-01 -4.34564892e-03
-3.83947909e-01 4.48644400e-01 4.95981663e-01 -6.44114971e-01
-1.21862948e+00 -1.32710314e+00 9.25668597e-01 -3.84099901e-01
7.93433666e-01 -5.63528538e-01 -9.73642826e-01 3.20095807e-01
1.31330699e-01 5.65385520e-01 7.69666314e-01 -5.95133454e-02
-5.52420467e-02 -2.95676291e-01 -1.15285695e+00 6.63893759e-01
7.86896050e-01 -5.02465904e-01 4.63370085e-02 3.60551208e-01
1.05464526e-01 -2.48689204e-01 -1.30785549e+00 6.77659154e-01
7.16956973e-01 -9.22994554e-01 7.70730972e-01 -3.12645435e-01
3.97999227e-01 -2.34005377e-01 8.73190239e-02 -1.16413295e+00
-9.38213885e-01 2.21750125e-01 5.98745346e-02 7.19692051e-01
3.55964214e-01 -4.12082762e-01 1.12269366e+00 1.28493220e-01
-4.27742481e-01 -1.52014267e+00 -1.13631046e+00 -2.84936279e-01
2.37936541e-01 1.07496671e-01 3.17690402e-01 9.73828614e-01
2.66661167e-01 1.56782165e-01 3.95331174e-01 1.16801187e-01
3.49007845e-01 -1.75663516e-01 3.31242591e-01 -1.60151339e+00
-5.34948194e-03 -1.17909801e+00 -1.08853793e+00 -1.68418065e-01
1.95794344e-01 -1.35253549e+00 -4.31615859e-01 -2.06368780e+00
3.63926351e-01 -4.06363010e-01 -4.77246374e-01 5.15480399e-01
6.90620020e-02 3.31835270e-01 -2.38363460e-01 3.29077810e-01
-4.67718393e-01 1.34485766e-01 1.55257034e+00 -6.08883500e-01
-3.80594991e-02 -5.03302276e-01 -4.07702625e-01 6.84836507e-01
5.45691788e-01 -2.06977755e-01 -1.59878060e-01 1.17518313e-01
1.74788982e-01 2.93607861e-01 6.31487012e-01 -1.09632981e+00
4.36776489e-01 -6.51185066e-02 6.05812490e-01 -7.32005954e-01
1.83037058e-01 -1.07903600e+00 5.17476678e-01 8.84387255e-01
-4.46061343e-01 -8.87255277e-03 3.22247297e-01 5.83070993e-01
-4.45020407e-01 2.30593756e-01 6.79849982e-01 -1.92505255e-01
-1.86810344e-02 4.09852087e-01 -4.85377014e-01 -6.60735488e-01
1.08979285e+00 -8.40567410e-01 -5.26873410e-01 5.84621094e-02
-8.14732730e-01 2.35382002e-02 5.84289968e-01 -1.87682286e-01
3.29577744e-01 -1.33562064e+00 -7.01924205e-01 6.11336306e-02
3.43610585e-01 -1.93909332e-02 4.83356982e-01 1.22188151e+00
-1.03575182e+00 5.50976396e-01 -4.62025672e-01 -8.82586062e-01
-1.49007940e+00 2.76886880e-01 7.92770565e-01 -9.12068963e-01
-5.04398584e-01 6.85311973e-01 7.30059862e-01 -2.61474818e-01
1.40314683e-01 -6.73780382e-01 -7.03480542e-01 1.76799223e-01
-1.63528129e-01 3.38987112e-01 1.93641737e-01 -9.62139845e-01
-4.10854161e-01 5.66540539e-01 -1.71766073e-01 4.34173822e-01
1.19555473e+00 2.02092335e-01 -7.96745062e-01 3.67498338e-01
1.27525246e+00 -2.71571755e-01 -8.66758227e-01 1.82417065e-01
2.40201965e-01 1.35258108e-01 1.66605517e-01 -8.23146820e-01
-1.21234882e+00 7.30991185e-01 5.64713299e-01 5.83661914e-01
1.17486680e+00 8.21496323e-02 1.87935606e-01 1.92391708e-01
1.10329293e-01 -6.50425851e-01 -4.58301157e-02 2.86809385e-01
8.60946238e-01 -7.80748367e-01 2.70611793e-01 -8.96988869e-01
-4.60239798e-02 1.37987638e+00 5.02349615e-01 -1.43287852e-01
8.60775948e-01 3.60724300e-01 4.60599847e-02 -9.78782296e-01
-7.89597332e-01 1.03153005e-01 5.77485919e-01 4.51040417e-01
6.96912348e-01 3.96381080e-01 -2.90310025e-01 5.11744618e-01
-2.24917427e-01 2.32759980e-03 3.35523814e-01 5.82538128e-01
-3.16459239e-01 -7.95278788e-01 -6.31492957e-02 7.49293506e-01
-3.75010818e-01 1.38685405e-01 -8.38332295e-01 1.09770751e+00
2.68704385e-01 1.86699256e-01 3.44100475e-01 -1.74275309e-01
1.42068923e-01 -3.59760076e-01 3.95757526e-01 -4.66337085e-01
-7.19907165e-01 9.20282528e-02 -2.09968202e-02 -2.44843096e-01
-1.69745311e-01 -3.48280638e-01 -1.42663527e+00 -8.25380348e-03
-6.39093146e-02 -9.75767970e-02 5.64561963e-01 6.11722589e-01
4.23270851e-01 7.91618943e-01 3.10970753e-01 -8.81276608e-01
3.49012822e-01 -8.63169611e-01 -8.59967411e-01 3.53232861e-01
5.03044367e-01 -4.39567655e-01 -1.84266031e-01 1.07408367e-01] | [15.023271560668945, -2.9427850246429443] |
fb724a59-a6f1-4197-acc3-c34de0ce42da | diverse-controllable-and-keyphrase-aware-a | 2004.03875 | null | https://arxiv.org/abs/2004.03875v2 | https://arxiv.org/pdf/2004.03875v2.pdf | Diverse, Controllable, and Keyphrase-Aware: A Corpus and Method for News Multi-Headline Generation | News headline generation aims to produce a short sentence to attract readers to read the news. One news article often contains multiple keyphrases that are of interest to different users, which can naturally have multiple reasonable headlines. However, most existing methods focus on the single headline generation. In this paper, we propose generating multiple headlines with keyphrases of user interests, whose main idea is to generate multiple keyphrases of interest to users for the news first, and then generate multiple keyphrase-relevant headlines. We propose a multi-source Transformer decoder, which takes three sources as inputs: (a) keyphrase, (b) keyphrase-filtered article, and (c) original article to generate keyphrase-relevant, high-quality, and diverse headlines. Furthermore, we propose a simple and effective method to mine the keyphrases of interest in the news article and build a first large-scale keyphrase-aware news headline corpus, which contains over 180K aligned triples of $<$news article, headline, keyphrase$>$. Extensive experimental comparisons on the real-world dataset show that the proposed method achieves state-of-the-art results in terms of quality and diversity | ['Jiancheng Lv', 'Yeyun Gong', 'Dayiheng Liu', 'Yu Yan', 'Wei Liu', 'Nan Duan', 'Jie Fu', 'Daxin Jiang', 'Bo Shao'] | 2020-04-08 | null | https://aclanthology.org/2020.emnlp-main.505 | https://aclanthology.org/2020.emnlp-main.505.pdf | emnlp-2020-11 | ['headline-generation'] | ['natural-language-processing'] | [ 0.07652437 -0.1340456 -0.2583487 -0.2274738 -1.5146 -0.55916405
0.68611366 0.42064855 -0.5707927 1.1037326 1.1682484 -0.079721
0.0445856 -0.8567742 -1.1006771 -0.41366673 0.36502376 0.3529141
0.5177987 -0.8575714 0.6834857 -0.2298248 -1.4086692 0.6992798
1.0017363 0.90508884 0.7840369 0.83061594 -0.24542944 1.0148356
-0.8999749 -0.55487907 0.13465491 -0.92468816 -0.62919676 0.02857131
0.53777486 -0.33792198 -0.45923194 1.1119834 0.6895583 0.00690774
0.21777661 -0.93290085 -0.75162584 1.5873667 -0.66324484 0.64255947
0.71151125 -0.2359371 1.5837713 -0.9746577 0.75509846 1.0221153
0.2798866 0.16984366 -0.6305203 -0.70491195 0.10792304 0.06282065
-1.1683877 -0.44858822 0.5452452 0.0476805 0.604928 0.5060877
0.90375364 1.0031078 0.34169784 1.3437254 0.9215248 -0.24876766
-0.1892732 0.1333771 0.22577006 0.3212918 0.04171875 -0.29344794
-0.9875835 -0.23270951 0.32442 -0.15408072 -0.6045615 0.45239994
-1.7924486 0.96528786 0.11793537 -0.07290322 -0.6360198 -0.23899539
0.5107952 0.5664644 0.56135726 0.64988244 -0.46813613 -0.39894387
-0.9761507 0.9345247 0.96057165 1.5303298 0.55301744 -0.5011931
-0.8337522 0.8614486 0.13848612 0.92948264 0.60773754 -0.33905694
1.0397892 0.5414202 0.3300785 -1.2698908 -0.034449 -0.6466511
-0.8078418 -0.8729706 -0.23030047 -0.6152504 -0.4384503 1.2231112
0.12138021 -0.29837492 0.18660977 0.68806374 1.2569414 1.4863225
-0.82556087 -0.6861019 1.5450149 -1.3378177 -0.6568516 -0.2701085
0.23010238 -1.378123 1.1101171 0.34599826 -1.3635112 -0.42409962
-0.9124249 -0.07518708 0.07069451 0.34977305 -0.08398296 -0.07095782
-0.6858135 0.05046643 0.14111944 -0.05349934 -0.05177593 -0.34144735
0.08008308 -0.10281218 -1.6473819 0.51293045 0.47416863 -0.5024896
-0.6819002 -1.0121472 -0.6489999 -0.15738817 0.58564126 -0.7193477
1.4773498 -0.4234317 -1.1279792 0.40958518 -0.32552662 -0.49977285
0.5244201 -0.49200514 -0.66433036 0.25029418 0.6507702 0.3937053
0.9894577 -0.7850871 -1.5946138 0.30118886 0.06138231 0.5849113
-0.5027682 0.3686282 -0.75464183 -1.1153483 -0.13332027 -0.6105525
-0.01794595 -0.85035944 -1.0569174 -0.15010278 0.37148866 -0.83365256
1.917918 -1.9380723 0.11296099 0.05629828 0.1476168 -0.20593122
-0.08232835 0.829117 0.3526053 -0.01221187 0.11990368 0.27091303
0.04979414 -0.38893533 -0.841636 -0.0127284 -0.37770736 0.87951255
-1.0996513 -0.5443218 -0.49745473 -0.12682475 -0.40662614 0.38550344
-0.4431362 -0.10104085 -0.5853536 0.24148792 0.376254 -0.35314783
-0.5741206 -0.52650607 -0.32600644 0.69017434 -1.175895 1.1329998
-0.31751138 0.5200305 -0.23264188 -0.2515458 0.93577534 0.13852908
0.2813522 -0.81299996 0.0878825 0.28521574 -0.5116566 -0.27552077
1.3065524 0.05919741 -0.58391833 0.83586174 -0.20302789 -0.2279464
0.9563448 0.85405606 0.86206675 -0.48305094 0.21129228 -0.31145576
0.43163124 0.04134748 0.42186886 0.89134026 0.47664553 0.8677966
0.5217112 -0.05837693 -1.2828944 -0.49685958 0.24946384 1.0940704
0.41565478 -0.9398638 -0.6766198 -0.6370574 -0.32637122 0.99206567
-0.49304804 -0.0133547 -0.6860786 -0.8247647 0.4771317 0.06640427
0.4952077 -0.9105977 -0.29585972 0.5283326 -0.95832187 -1.0861671
-1.459677 -0.33196267 -0.06526618 -0.83670515 -1.456175 -0.9416794
0.78507435 0.6376371 1.3265668 -0.2353159 0.3608391 0.01660309
-1.0218428 -0.52382004 -0.6154411 0.38451466 -0.05342454 0.24807884
0.05273498 -0.03858365 -0.47520608 0.2349886 -0.98334813 0.4247293
0.8686854 0.96254754 0.6099987 0.36429638 0.5935654 -0.98598874
1.3690034 -0.6057965 -0.33809423 0.3903618 -0.71747404 0.04986078
1.0402106 -0.19697908 -0.96325374 -0.6288086 -0.3330385 0.36871183
0.45352665 1.0028403 0.03889712 0.70288867 0.7417051 1.0755502
-0.22913706 -0.43879947 0.45159814 0.65086824 0.352716 -0.3347032
0.8367843 -0.08812915 -0.6452733 -0.85938704 -1.253128 -0.66523314
0.07498958 -0.29330593 0.36531815 -1.1735725 -0.05956309 0.74780965
-1.0748255 0.37391594 -0.40816897 0.3497861 -0.27078807 0.39552605
-0.767218 -0.04907329 -0.822149 -1.0871357 0.8944616 0.530675
-0.10928294 -0.43954515 0.00963919 0.27859166 0.17596628 -0.33122826
0.61057174 -0.8656282 -0.48371738 -0.42591977 -0.2573136 0.23182353
0.12390927 -0.05781116 -0.1491046 -0.29656342 -0.28412032 -0.42585433
0.7777401 0.24011046 0.63952297 -1.1696075 -0.10845721 0.18425849
0.95248425 -0.00882511 0.57626563 0.41831526 0.53530777 0.36659932
1.0680022 0.90390205 0.90393317 0.52882934 -0.1071393 0.02137806
0.08285951 -0.81776524 0.7014934 1.611744 0.30834585 -0.6501771
-0.29068962 0.7572734 -1.70902 -1.3662937 -0.28544223 1.749964
1.3544155 0.5729265 0.36682087 -0.06122445 0.82911175 0.4896869
-0.2703648 0.26767266 -0.5593957 -0.3716505 0.61745167 0.41539478
-0.72235155 0.7615186 5.500654 1.2518727 -0.82906336 -0.26379946
0.5517468 -0.07973009 -0.89322084 -0.11598446 -1.7475126 0.86968786
0.7030111 -1.1281288 0.08190544 0.83681905 0.29802108 -0.05223518
-0.58172965 0.82992446 0.45136166 -1.8711338 0.5286318 -0.34855664
0.85053384 -0.08976052 -0.08749945 0.29087842 0.4460589 -0.2898637
1.0705147 0.46011156 0.621044 -0.9578372 0.7624061 0.6401261
-1.1909095 0.1584898 -0.21135916 0.24030396 0.7195104 1.1672754
-0.71275353 0.5208624 0.75962955 0.8403257 -0.47529393 1.0136501
-0.29640907 0.6306922 -0.24060741 -0.8346282 0.50933635 0.10081264
0.77030504 1.4863281 0.67262363 0.20653635 0.32161388 0.2904663
-0.33111164 0.5848566 -0.15926589 -0.33562088 0.66256976 1.2213945
-0.61351156 -0.64232916 -0.40737137 0.97897094 -0.17746167 0.05516238
-0.8162103 -1.0737128 0.22616093 0.24099138 0.41606122 0.20329127
0.2932807 -1.4334211 0.34016627 -1.4267284 0.34533098 -0.80041915
-1.345308 0.7809112 -0.03064843 -1.462104 -0.25420383 0.19124304
-0.42659667 0.844114 -1.4792722 -0.87734765 -0.02603428 0.40062967
1.1584231 -0.32121104 0.24089168 0.27227154 -0.09869225 0.66883826
0.27119523 0.159335 0.76672786 -1.0352544 0.88557845 1.132516
0.10284079 0.60270786 1.0692335 -0.87296593 -1.5085603 -1.1255381
1.5887953 -0.11539403 0.62749803 -0.15251592 -0.34965977 0.383884
0.5189351 -0.6320036 0.63260764 -0.27113244 0.0180172 -0.27469587
-0.64728767 0.95451456 0.7017191 -0.16507801 -0.9029169 0.6340265
1.4457964 -0.8294815 -0.510432 0.17704031 0.38978904 -0.84507966
0.7851969 -0.26394856 0.98187244 -0.34403974 -0.05356444 -1.7486033
-0.40757135 -0.97641003 -0.17559618 1.4760482 1.0030038 -0.27744907
0.44087508 0.12808774 -0.37728858 -0.82145435 -0.37796596 -0.2659672
-0.5145862 -0.17527546 0.7412878 0.5626222 0.32993555 0.979815
-0.9315811 -0.21394219 0.28971553 0.39444858 0.9145033 -0.64989185
-0.30269626 -0.4119766 0.47485688 -2.064543 -0.47351196 -0.6637042
0.3123542 -1.7778016 0.3032661 -0.17864412 0.16610312 -0.06814663
-0.51759106 -0.05614258 0.17433998 0.24928941 -0.83456194 0.5809108
1.6580641 -0.33215752 -0.23367906 0.2781303 -1.4220812 0.43760243
0.3381629 -0.4073834 -0.55950713 -0.25530204 0.9305683 0.2486958
-0.20916788 -0.7139854 0.47552195 -0.3997487 0.11343012 -1.1326296
-0.08161701 -0.25213686 -0.18981235 0.25905576 -0.8632351 0.5357456
-0.23767504 0.44383344 -0.48485613 -0.3421905 0.46455806 -0.42407638
-0.61575633 0.50733393 -0.39772362 0.85685575 0.65305185 0.28170142
-0.5497853 -0.77566785 0.09272856 0.36003676 0.18972163 0.6917717
0.92329645 -1.3539315 -1.6081324 0.12551422 0.39365664 -0.05515827
0.10816129 0.55388206 -0.4843458 0.468382 0.13955037 -0.08020562
-1.2081783 0.22397931 -0.49354088 -0.29073566 -0.77470034 1.3230815
-0.11348772 -0.09040398 0.09288962 -0.51504683 -0.49169877 0.7210333
1.3044624 0.24407153 0.01262518 -0.7778681 0.19743165 0.38407385
-0.77459455 -0.2878338 1.10714 -0.5095072 -0.13738403 0.37320384
1.339268 0.59300506 -0.725067 -0.6240086 -0.3553645 -0.37672105
-0.04002782 -0.61689234 -0.83775795 0.17640375 -0.3773375 0.49747902
1.1014844 0.11275836 1.8352678 0.32911342 0.4034855 -1.4212896
0.16942658 0.88124084 1.1091295 -0.9946987 0.13729882 -0.10611784
-0.9319263 0.9547713 0.4071122 0.142837 0.55211264 0.05343208
0.19752088 -0.17293194 -0.93216497 0.08384912 0.35729745 -0.04933732
0.26148716 -0.20341742 -0.7326858 0.8707728 -0.90859437 -0.22432882
0.86569005 0.91339195 -0.9219264 -0.89033777 -0.25148836 0.86907107
-0.64132136 -0.6984997 -0.26097727 0.0836257 -0.23552231 0.92847776
-0.38467622 -0.64254475 0.41744906 -0.385902 -0.13495 -0.5635894
-0.6055295 0.27032396 0.32951602 -0.08279914 -0.11630803 -0.59783214
-1.0267385 -0.44608313 -0.39429483 0.8437586 0.2201934 0.8154465
0.4881661 0.3594104 1.1593232 -0.31484365 -0.46295318 -1.0426577
-0.546594 0.44359314 0.5700055 0.15605803 -0.27962306 0.354517 ] | [12.296685218811035, 9.00045108795166] |
bdd5b8f6-91ec-455b-ab86-7534effc4093 | what-do-end-to-end-speech-models-learn-about | 2107.00439 | null | https://arxiv.org/abs/2107.00439v3 | https://arxiv.org/pdf/2107.00439v3.pdf | What do End-to-End Speech Models Learn about Speaker, Language and Channel Information? A Layer-wise and Neuron-level Analysis | Deep neural networks are inherently opaque and challenging to interpret. Unlike hand-crafted feature-based models, we struggle to comprehend the concepts learned and how they interact within these models. This understanding is crucial not only for debugging purposes but also for ensuring fairness in ethical decision-making. In our study, we conduct a post-hoc functional interpretability analysis of pretrained speech models using the probing framework [1]. Specifically, we analyze utterance-level representations of speech models trained for various tasks such as speaker recognition and dialect identification. We conduct layer and neuron-wise analyses, probing for speaker, language, and channel properties. Our study aims to answer the following questions: i) what information is captured within the representations? ii) how is it represented and distributed? and iii) can we identify a minimal subset of the network that possesses this information? Our results reveal several novel findings, including: i) channel and gender information are distributed across the network, ii) the information is redundantly available in neurons with respect to a task, iii) complex properties such as dialectal information are encoded only in the task-oriented pretrained network, iv) and is localised in the upper layers, v) we can extract a minimal subset of neurons encoding the pre-defined property, vi) salient neurons are sometimes shared between properties, vii) our analysis highlights the presence of biases (for example gender) in the network. Our cross-architectural comparison indicates that: i) the pretrained models capture speaker-invariant information, and ii) CNN models are competitive with Transformer models in encoding various understudied properties. | ['Ahmed Ali', 'Nadir Durrani', 'Shammur Absar Chowdhury'] | 2021-07-01 | null | null | null | null | ['dialect-identification'] | ['natural-language-processing'] | [ 4.35197592e-01 4.85409439e-01 2.45808158e-02 -5.50733030e-01
-3.45344901e-01 -8.87506723e-01 6.52675986e-01 3.08850288e-01
-3.27139407e-01 3.91849041e-01 6.80159330e-01 -5.66173851e-01
-2.87266999e-01 -3.24265093e-01 -9.21814919e-01 -5.97157717e-01
-2.77638376e-01 2.14661524e-01 -1.37455598e-01 -2.96451718e-01
1.02186099e-01 5.94025135e-01 -1.70653868e+00 5.79825521e-01
5.54594159e-01 1.22559249e+00 -6.27969578e-02 3.65656495e-01
-1.61930189e-01 8.95703852e-01 -6.17511034e-01 -3.46981287e-01
5.26148155e-02 -5.02516031e-01 -1.10398734e+00 -5.48210777e-02
6.40373766e-01 -1.48088276e-01 -1.37866423e-01 1.12158144e+00
2.64644951e-01 -2.62478292e-01 6.42925978e-01 -1.19924843e+00
-6.12159252e-01 1.02673399e+00 -5.47354743e-02 3.48357081e-01
4.44622748e-02 2.44020745e-01 1.53401852e+00 -6.40359640e-01
5.52843511e-01 1.31275272e+00 5.26615858e-01 5.89761615e-01
-1.42350352e+00 -6.13392234e-01 6.67267978e-01 1.07104168e-03
-1.39486289e+00 -9.33078587e-01 7.77763247e-01 -4.90393192e-01
9.27794099e-01 5.04500687e-01 6.26032174e-01 1.48177803e+00
3.42506394e-02 5.57679713e-01 1.14253032e+00 -1.94506720e-01
2.88599014e-01 5.26894152e-01 2.63266355e-01 7.11020827e-01
5.10044815e-03 1.34602100e-01 -8.46162736e-01 -1.08906887e-01
6.67935133e-01 -4.21229482e-01 -2.76055425e-01 1.53448563e-02
-1.29846179e+00 7.43959308e-01 3.79719377e-01 5.59756815e-01
-2.71252513e-01 6.13116510e-02 6.06096387e-01 5.85515738e-01
2.25041270e-01 6.63046002e-01 -8.35559189e-01 -1.66561037e-01
-6.42633319e-01 -1.56522378e-01 8.08488786e-01 6.54058337e-01
9.37310755e-01 3.51242572e-01 6.79658668e-04 8.15836251e-01
3.13417971e-01 2.18507513e-01 5.43935955e-01 -8.10729265e-01
4.86410201e-01 5.50312161e-01 -4.81047839e-01 -8.45326126e-01
-5.17221332e-01 -6.40966594e-01 -7.59433568e-01 -1.87224485e-02
5.21923184e-01 -1.78437456e-02 -4.62030649e-01 2.34816122e+00
-2.42943272e-01 -4.15587634e-01 -1.72082648e-01 7.30969965e-01
9.12878931e-01 2.25807890e-01 1.55658677e-01 1.06491148e-01
1.48076010e+00 -2.76085317e-01 -3.15157473e-01 -6.15369976e-01
5.33969343e-01 -3.60598832e-01 1.19821239e+00 6.31366968e-02
-9.36121941e-01 -5.29994786e-01 -1.10190582e+00 -7.31605589e-02
-3.91538024e-01 1.23428963e-02 6.76996827e-01 1.09135270e+00
-1.31645823e+00 3.74947816e-01 -3.20758492e-01 -2.72958100e-01
6.58099651e-01 6.13354564e-01 -5.19615352e-01 4.41930532e-01
-1.22403324e+00 7.45630145e-01 1.17200628e-01 1.47680715e-01
-1.07295024e+00 -6.84179425e-01 -9.17661428e-01 4.78819698e-01
3.72448713e-02 -6.32383049e-01 8.81297767e-01 -1.63179517e+00
-1.29518700e+00 1.02440047e+00 -4.71494406e-01 -1.57340512e-01
4.82449867e-02 4.46110874e-01 -3.40690851e-01 2.32785977e-02
-1.46835551e-01 7.11627483e-01 7.81590164e-01 -1.36505616e+00
-4.01181489e-01 -5.75427532e-01 3.16876471e-01 -1.81463175e-02
-4.46681499e-01 1.24383971e-01 1.42673373e-01 -6.83535814e-01
3.41152638e-01 -6.96114063e-01 3.03260475e-01 7.33165517e-02
-7.19261348e-01 2.23708209e-02 5.75047493e-01 -7.30035067e-01
8.96728694e-01 -2.34886670e+00 1.05599714e-02 4.63014543e-01
6.38502598e-01 -3.66453081e-02 -1.18802488e-01 2.93508500e-01
-4.58342493e-01 6.10083044e-01 -2.37257257e-01 -2.77693480e-01
2.21453220e-01 3.45680006e-02 -5.11664152e-01 6.04707897e-01
3.77220303e-01 7.44566739e-01 -3.94049764e-01 -1.28081232e-01
-5.03166132e-02 3.61875027e-01 -6.53703153e-01 -5.18584326e-02
-8.66075158e-02 5.97337842e-01 -1.42826378e-01 7.80612409e-01
5.32918274e-01 2.16323859e-03 2.62924612e-01 -3.09899211e-01
-9.99928936e-02 8.25184822e-01 -9.00816500e-01 1.23802459e+00
-5.68925619e-01 1.10934412e+00 4.50697839e-01 -1.09655166e+00
8.34018350e-01 2.35948801e-01 -1.79804966e-01 -8.02365005e-01
3.80804330e-01 8.17157328e-02 5.91750801e-01 -3.41228515e-01
2.51728952e-01 -2.85365105e-01 -1.64680779e-01 6.67011976e-01
4.35034156e-01 4.30641979e-01 -3.71276349e-01 9.23628658e-02
1.00312126e+00 -5.52793741e-01 7.27817044e-02 -6.38309121e-01
4.09459919e-01 -4.78191197e-01 4.87616658e-01 7.72960842e-01
-3.65715504e-01 5.31682014e-01 1.20915258e+00 -2.46514574e-01
-7.78110385e-01 -1.03018534e+00 -2.85094321e-01 1.43776047e+00
-1.85539335e-01 -1.27172992e-01 -7.86782265e-01 -3.87032002e-01
-1.73855275e-01 7.34346449e-01 -1.06240010e+00 -3.88297886e-01
-1.88776568e-01 -4.12862688e-01 9.20166373e-01 4.68437016e-01
4.74830627e-01 -9.64141846e-01 -4.47359890e-01 -2.44940042e-01
-1.08896956e-01 -1.13731194e+00 -2.55285382e-01 4.95026439e-01
-7.67257452e-01 -7.50793338e-01 -1.21097356e-01 -8.04812014e-01
7.72519290e-01 -8.48316550e-02 1.05782545e+00 1.70400500e-01
-2.10931469e-02 4.56223339e-01 3.39898877e-02 -5.52895188e-01
-4.70869988e-01 2.85589635e-01 -1.24932244e-01 3.06279451e-01
3.50238591e-01 -6.70214891e-01 -3.28316063e-01 4.15031761e-01
-6.81547403e-01 -2.16279805e-01 7.40340233e-01 8.21919322e-01
9.62108448e-02 -2.42701340e-02 6.27163470e-01 -1.03726768e+00
6.66970015e-01 -4.11354542e-01 -1.82065517e-01 2.07709149e-01
-3.25523555e-01 2.05420420e-01 6.14912152e-01 -3.81631106e-01
-9.65826452e-01 -1.83083981e-01 -2.99604774e-01 9.77701247e-02
-5.66717684e-01 4.48019445e-01 -6.00673974e-01 4.56786752e-02
8.04844022e-01 2.76218742e-01 2.56218433e-01 -2.14163482e-01
9.48302224e-02 6.32585466e-01 1.59278527e-01 -7.99819946e-01
6.40102327e-01 5.89208841e-01 -3.96342427e-01 -1.13805854e+00
-4.84015524e-01 -2.30855141e-02 -6.71583593e-01 -1.11761957e-01
7.44534016e-01 -7.85891533e-01 -1.10666680e+00 3.66013676e-01
-1.09863400e+00 -3.08669090e-01 -2.73373991e-01 3.33306938e-01
-3.23004663e-01 5.42421751e-02 -5.38425326e-01 -9.31723833e-01
-1.87775791e-02 -1.33301950e+00 8.11649501e-01 -1.10619500e-01
-6.85617745e-01 -1.13602531e+00 -4.21576440e-01 3.59982818e-01
4.50568259e-01 -1.59161523e-01 1.53569996e+00 -1.13006294e+00
-4.36337411e-01 -3.14603969e-02 -3.74636680e-01 2.38765344e-01
3.74398157e-02 5.95640624e-03 -1.66306138e+00 1.48503957e-02
8.29138234e-02 -2.61835039e-01 9.06180322e-01 3.32362324e-01
1.36956561e+00 -5.05380690e-01 -9.81058460e-03 5.98307908e-01
7.28821933e-01 -4.26465496e-02 4.92325306e-01 9.34480578e-02
5.90649366e-01 1.30296588e+00 -4.40497994e-01 8.03792924e-02
4.40939963e-01 4.40116227e-01 5.22701621e-01 -9.64935794e-02
9.93910879e-02 -3.74191105e-01 5.00087440e-01 5.65085053e-01
1.61052659e-01 3.07851806e-02 -7.88069963e-01 6.72261298e-01
-1.54762304e+00 -8.69305134e-01 1.04427360e-01 2.11770701e+00
7.46561646e-01 3.67990226e-01 1.43035561e-01 1.11021787e-01
5.36590695e-01 3.04003537e-01 -5.79402804e-01 -7.94211805e-01
-3.91060621e-01 5.63454181e-02 2.47058839e-01 4.25904810e-01
-7.57070124e-01 7.31431425e-01 6.75735617e+00 4.86804783e-01
-1.56820416e+00 1.63099077e-02 1.06988549e+00 5.84315546e-02
-8.27625990e-01 -1.94206852e-02 -5.72305977e-01 2.30357200e-01
1.10077810e+00 2.11561978e-01 7.13562548e-01 6.02155924e-01
-5.84219489e-03 1.62923694e-01 -1.47724557e+00 7.04077542e-01
1.12772733e-01 -1.25187588e+00 1.66515097e-01 3.27451319e-01
3.71366665e-02 -3.47128771e-02 4.86038297e-01 2.55927473e-01
1.69024095e-01 -1.52077103e+00 1.35701096e+00 1.58328563e-01
5.93820274e-01 -5.81633151e-01 5.14170587e-01 2.33755767e-01
-8.39175701e-01 -1.87679157e-01 -2.88555086e-01 -1.51776984e-01
-2.55550474e-01 4.19168890e-01 -7.12316394e-01 -7.62541667e-02
7.26173878e-01 3.85625035e-01 -7.75834322e-01 4.18034822e-01
-3.25132877e-01 8.11183274e-01 -7.43152127e-02 -5.40241562e-02
1.11977510e-01 9.32827145e-02 5.24170637e-01 1.07523155e+00
-2.02747732e-02 -4.09616053e-01 -6.41570330e-01 1.45723403e+00
-1.73356563e-01 -6.25035688e-02 -6.43048465e-01 -4.04763281e-01
4.79374766e-01 1.22728074e+00 -7.57081449e-01 -2.01440118e-02
-4.14145321e-01 6.36543810e-01 4.86954480e-01 6.05322182e-01
-4.58490789e-01 -3.73689942e-02 1.03437257e+00 8.88091326e-02
2.58377522e-01 -8.81434977e-02 -7.04817772e-01 -8.40461910e-01
-9.22093019e-02 -8.61942112e-01 2.05129296e-01 -6.11324072e-01
-1.21488333e+00 7.76690006e-01 -2.95983106e-01 -8.00778449e-01
-2.27176949e-01 -8.09671283e-01 -7.24314392e-01 1.02445245e+00
-1.10957360e+00 -1.21366251e+00 2.75836810e-02 6.10669792e-01
2.12981403e-01 -5.47976494e-01 1.05653656e+00 1.90178350e-01
-7.03667641e-01 9.47379351e-01 -3.22896510e-01 4.76682156e-01
3.85229707e-01 -1.02189445e+00 2.39284098e-01 5.71891189e-01
4.73752797e-01 1.20732391e+00 5.56786060e-01 -1.20815210e-01
-1.18046010e+00 -7.51058877e-01 1.04226589e+00 -5.26353717e-01
6.68284893e-01 -9.33933139e-01 -9.05102491e-01 8.82539630e-01
1.50022507e-01 -7.77474493e-02 1.15728688e+00 8.14997971e-01
-1.04609239e+00 -2.13812575e-01 -1.11055815e+00 5.16388893e-01
1.06314111e+00 -1.10121918e+00 -4.91126508e-01 -1.53144479e-01
7.42560685e-01 -8.44820663e-02 -4.66780931e-01 -7.75917321e-02
7.68852413e-01 -1.16233170e+00 7.36417592e-01 -7.92541862e-01
3.96938652e-01 5.38710169e-02 -4.46189702e-01 -1.40839636e+00
-3.04170936e-01 -3.12314987e-01 4.13535714e-01 1.47255838e+00
1.04626906e+00 -9.10523415e-01 4.61825401e-01 7.91201055e-01
-2.72281289e-01 -6.50844753e-01 -1.23524284e+00 -4.20351923e-01
2.52699733e-01 -4.78516638e-01 5.92628539e-01 1.13363349e+00
7.98853189e-02 5.03450394e-01 8.76438152e-03 1.34751081e-01
1.54143497e-01 -1.56798288e-01 3.04860830e-01 -1.28138340e+00
-3.20091754e-01 -7.49416888e-01 -4.66491610e-01 -6.22424364e-01
5.85888863e-01 -1.06974888e+00 -2.66980857e-01 -1.09433258e+00
8.89555216e-02 -3.84422362e-01 -2.30292812e-01 6.49522841e-01
2.66337931e-01 -4.56651412e-02 -2.59551778e-02 2.80114566e-03
-1.31385341e-01 3.08406055e-01 7.14786887e-01 -2.85892904e-01
7.69269988e-02 -9.93317664e-02 -1.50054169e+00 5.95988274e-01
7.59119272e-01 -2.26070747e-01 -4.71080959e-01 -5.68769813e-01
4.98206764e-01 -3.02827030e-01 7.01141477e-01 -5.83034813e-01
-2.53493316e-03 -9.20057576e-03 5.32619596e-01 5.01210392e-02
3.92683089e-01 -8.35364759e-01 -1.91169709e-01 2.83209592e-01
-5.90428650e-01 -1.48086414e-01 4.70211595e-01 2.60481328e-01
-2.51767963e-01 -1.41113579e-01 5.79266369e-01 -2.59472549e-01
-6.40637159e-01 -6.15196675e-02 -7.49875247e-01 2.02423647e-01
3.50607902e-01 -3.04415017e-01 -5.71157038e-01 -6.00715160e-01
-6.41999185e-01 -2.10583240e-01 2.31745228e-01 4.80374873e-01
2.77790219e-01 -9.96630013e-01 -4.21922922e-01 4.58322287e-01
3.56431514e-01 -4.79695350e-01 3.22208583e-01 8.07004035e-01
-5.53385802e-02 3.92831564e-01 -2.85482645e-01 -6.24396443e-01
-9.91195023e-01 1.33709833e-01 5.00656486e-01 3.25297296e-01
1.08547527e-02 1.20609415e+00 7.60081589e-01 -6.91510737e-01
2.18416750e-01 -4.76225317e-01 -1.75262585e-01 5.54818511e-01
2.79325843e-01 -7.16566592e-02 1.75056711e-01 -1.02921319e+00
-6.19298816e-01 2.60237545e-01 -1.73735276e-01 -2.01652944e-01
1.26298094e+00 -1.61893234e-01 -3.30979496e-01 7.45730519e-01
1.39351928e+00 -6.88994825e-02 -9.83852863e-01 -1.33313000e-01
-1.82311058e-01 -7.53510743e-02 -1.17849661e-02 -8.56441200e-01
-1.10928237e+00 1.24891472e+00 3.13185304e-01 2.18034491e-01
8.97428930e-01 3.07823747e-01 1.62614495e-01 1.49295688e-01
1.02208368e-01 -1.15549171e+00 -1.83887437e-01 6.51472628e-01
9.41832542e-01 -9.61463749e-01 -3.98769110e-01 -2.64317870e-01
-7.50325859e-01 9.79847789e-01 5.85040867e-01 3.13854367e-01
6.63971961e-01 1.11559168e-01 3.36961709e-02 -3.04070979e-01
-8.94838631e-01 -9.64591876e-02 3.04222375e-01 5.78738332e-01
6.07129693e-01 3.26962769e-02 2.66461164e-01 1.00131786e+00
-7.17651010e-01 -8.07929456e-01 2.46452615e-01 5.00502646e-01
-3.45428646e-01 -6.29056990e-01 -2.06185803e-01 5.60461640e-01
-2.85317838e-01 -2.84869581e-01 -9.66065407e-01 5.58841586e-01
1.21742420e-01 9.21619296e-01 3.02682519e-01 -6.76428437e-01
2.02242076e-01 3.54288101e-01 2.46664301e-01 -6.67224526e-01
-8.71795654e-01 -2.18151629e-01 3.95015359e-01 -3.45263124e-01
5.93828969e-02 -7.42452323e-01 -1.02120757e+00 -2.16162175e-01
-7.40360618e-02 -1.38272941e-01 8.18475783e-01 1.11701596e+00
4.34897780e-01 7.15266764e-01 4.91149753e-01 -5.35259783e-01
-4.50102955e-01 -8.81108344e-01 -6.36223137e-01 2.82549798e-01
7.19163179e-01 -5.00519514e-01 -7.02917337e-01 -6.87371865e-02] | [10.503838539123535, 8.53777027130127] |
2ccf6d4e-90e4-4cd9-90b0-6485620360dd | sampling-from-gaussian-process-posteriors | 2306.11589 | null | https://arxiv.org/abs/2306.11589v1 | https://arxiv.org/pdf/2306.11589v1.pdf | Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent | Gaussian processes are a powerful framework for quantifying uncertainty and for sequential decision-making but are limited by the requirement of solving linear systems. In general, this has a cubic cost in dataset size and is sensitive to conditioning. We explore stochastic gradient algorithms as a computationally efficient method of approximately solving these linear systems: we develop low-variance optimization objectives for sampling from the posterior and extend these to inducing points. Counterintuitively, stochastic gradient descent often produces accurate predictions, even in cases where it does not converge quickly to the optimum. We explain this through a spectral characterization of the implicit bias from non-convergence. We show that stochastic gradient descent produces predictive distributions close to the true posterior both in regions with sufficient data coverage, and in regions sufficiently far away from the data. Experimentally, stochastic gradient descent achieves state-of-the-art performance on sufficiently large-scale or ill-conditioned regression tasks. Its uncertainty estimates match the performance of significantly more expensive baselines on a large-scale Bayesian~optimization~task. | ['Alexander Terenin', 'José Miguel Hernández-Lobato', 'David Janz', 'Shreyas Padhy', 'Javier Antorán', 'Jihao Andreas Lin'] | 2023-06-20 | null | null | null | null | ['gaussian-processes', 'bayesian-optimization'] | ['methodology', 'methodology'] | [-1.78892631e-02 -1.43383965e-01 -1.78193182e-01 -7.21607447e-01
-1.54082727e+00 -4.65164870e-01 4.92489874e-01 7.33010843e-02
-6.18549049e-01 1.02304161e+00 2.06587747e-01 -4.15951371e-01
-1.61820408e-02 -4.18581635e-01 -7.93659270e-01 -7.81493843e-01
-6.06622882e-02 1.00904596e+00 -1.96176656e-02 1.86018944e-01
3.58583421e-01 2.61468321e-01 -1.10860753e+00 -9.49191451e-02
8.08080435e-01 9.95727777e-01 9.53386500e-02 7.68379509e-01
-1.11208461e-01 5.36612630e-01 -3.07294875e-01 -4.44947302e-01
1.09080873e-01 -1.74185619e-01 -4.94347394e-01 -2.92858154e-01
4.67388153e-01 -2.91891724e-01 -1.35629609e-01 1.24076879e+00
5.96895456e-01 1.75003648e-01 1.11648941e+00 -8.68268609e-01
-3.79468799e-01 7.46278584e-01 -8.07525456e-01 4.95580137e-01
3.45702350e-01 1.54660359e-01 1.24939919e+00 -1.06474698e+00
3.37078840e-01 1.47593391e+00 1.07143509e+00 2.68416673e-01
-1.73101234e+00 -5.21745324e-01 4.14158106e-01 -3.54218066e-01
-1.56472373e+00 -7.58060694e-01 3.18489224e-01 -6.09300852e-01
6.90665603e-01 1.10208996e-01 2.25378126e-01 1.23327470e+00
3.58671665e-01 1.04210484e+00 1.32461190e+00 -1.65018395e-01
5.85171402e-01 9.78273377e-02 3.92492145e-01 5.77638090e-01
3.80858034e-01 1.46281853e-01 -7.49113500e-01 -5.17363071e-01
4.84883040e-01 -2.00024992e-01 -4.26068574e-01 -1.95196643e-01
-1.10427153e+00 9.58560586e-01 1.89657331e-01 -1.06394187e-01
-3.29288363e-01 7.63928831e-01 6.26509488e-02 1.00790881e-01
9.55379426e-01 3.91691834e-01 -6.51277661e-01 -4.88680452e-01
-1.24857867e+00 6.28330052e-01 1.12976944e+00 9.67615783e-01
6.30399644e-01 7.60601461e-02 -4.73188668e-01 6.60791934e-01
6.64380074e-01 9.22340035e-01 1.49892300e-01 -8.99890661e-01
6.81399345e-01 -3.45122159e-01 7.12061644e-01 -6.88716531e-01
-4.17850196e-01 -5.12488365e-01 -6.58578038e-01 6.12048544e-02
7.74239659e-01 -6.51130080e-01 -9.76124108e-01 1.75342548e+00
3.09515715e-01 2.22158998e-01 -3.55868995e-01 8.44201207e-01
9.86853689e-02 6.53191090e-01 9.31852758e-02 -4.56815690e-01
9.21003282e-01 -5.19273400e-01 -6.96851671e-01 -5.05006015e-01
2.54715443e-01 -5.63219190e-01 1.06847036e+00 4.01074052e-01
-9.91201162e-01 -1.78372741e-01 -7.63638914e-01 7.03111142e-02
7.17920214e-02 8.56166333e-02 6.91273391e-01 8.78423333e-01
-9.41552103e-01 1.00008571e+00 -1.11333418e+00 9.56176966e-02
4.87274706e-01 1.39737427e-01 1.96281135e-01 -5.27182184e-02
-7.92877138e-01 8.85441899e-01 1.74845040e-01 3.20219219e-01
-1.20126438e+00 -8.57623160e-01 -6.42836392e-01 9.23362449e-02
2.76552528e-01 -6.72418654e-01 1.58723962e+00 -4.24779773e-01
-1.68810201e+00 4.24064875e-01 -6.79731011e-01 -6.25956655e-01
9.57993031e-01 -8.06477249e-01 -1.82228349e-02 -3.33123893e-01
1.97483405e-01 2.52804816e-01 1.26345694e+00 -1.02707458e+00
-6.35687113e-01 -4.13393855e-01 -5.18827200e-01 2.45728955e-01
2.08731994e-01 1.95624933e-01 -4.81482893e-01 -3.53190243e-01
2.81331241e-01 -9.83445704e-01 -7.21926212e-01 -1.56000629e-01
-6.25110924e-01 -1.92261785e-01 1.82852685e-01 -5.17781079e-01
1.31392562e+00 -1.90958476e+00 2.24461555e-02 5.65839350e-01
2.97429562e-01 -2.91780680e-01 2.95511365e-01 1.33465482e-02
1.78091437e-01 3.27029943e-01 -4.49348181e-01 -7.04201400e-01
3.30972254e-01 3.87158920e-03 -6.17469966e-01 9.38079834e-01
1.66396067e-01 8.59521031e-01 -9.74659920e-01 -3.39812666e-01
-1.36793420e-01 1.17575385e-01 -5.28106034e-01 1.01183532e-02
-4.09761310e-01 3.09284925e-01 -5.39115429e-01 5.50205290e-01
4.26062405e-01 -4.32692617e-01 -7.64027610e-02 1.89989984e-01
6.74749464e-02 2.79824227e-01 -1.32939386e+00 1.57061255e+00
-2.48215690e-01 8.40841830e-01 2.95368791e-01 -8.32434535e-01
4.49577063e-01 1.26287192e-01 2.75450647e-01 2.46159464e-01
1.65667683e-01 2.48821676e-01 -2.57447481e-01 -9.19747278e-02
3.59535098e-01 -5.86258531e-01 -2.51207879e-04 3.76632243e-01
-1.13153271e-01 -6.65143251e-01 -7.80217052e-02 5.99807361e-03
9.13016081e-01 1.79398462e-01 1.51407406e-01 -5.46965003e-01
-1.60445139e-01 -2.93125678e-02 5.37205935e-01 1.43208611e+00
-1.77708790e-01 6.43728793e-01 5.46692610e-01 -1.66863978e-01
-8.53154778e-01 -1.31650019e+00 -4.08928663e-01 1.29050052e+00
-1.36087909e-01 -2.74109840e-01 -4.85459208e-01 -4.93797213e-01
3.97987276e-01 1.02420092e+00 -5.90263069e-01 2.61034250e-01
-1.74058422e-01 -1.34572780e+00 3.68431002e-01 5.59669852e-01
5.00608943e-02 -3.50120991e-01 -9.95700061e-02 4.72112834e-01
4.71384563e-02 -9.34475899e-01 -4.69153762e-01 3.87335420e-01
-1.09146166e+00 -7.54068434e-01 -7.03155577e-01 -1.71585511e-02
5.62218904e-01 -2.65948445e-01 1.48564661e+00 -6.11813664e-01
-1.97808370e-02 2.15252087e-01 2.60133743e-01 -8.29175413e-01
-1.50570825e-01 -9.63606089e-02 3.57848585e-01 -3.02597761e-01
3.87798220e-01 -4.54178989e-01 -4.82862800e-01 1.94152042e-01
-3.14891905e-01 -5.38243175e-01 4.05738294e-01 9.72998977e-01
7.05074966e-01 -7.09442198e-02 3.01730841e-01 -9.89707649e-01
1.06726968e+00 -6.74849391e-01 -8.94749284e-01 1.16416246e-01
-6.80571258e-01 6.11823440e-01 2.08007172e-01 -3.60172868e-01
-1.22952271e+00 1.41276708e-02 -1.15541846e-03 -3.78651649e-01
1.64633825e-01 6.24945343e-01 4.68270212e-01 1.79632679e-01
1.09780788e+00 -3.82906422e-02 -2.50152200e-01 -4.95608151e-01
5.06207645e-01 5.05312443e-01 3.10045570e-01 -1.15882730e+00
5.95264494e-01 5.79057813e-01 8.39909762e-02 -6.58335090e-01
-1.36515045e+00 -4.46673870e-01 -2.79825240e-01 8.87473226e-02
6.32576644e-01 -9.96126533e-01 -5.80244720e-01 1.89345375e-01
-9.20603275e-01 -3.65981311e-01 -4.06206012e-01 6.13107741e-01
-6.11872733e-01 2.13058695e-01 -6.22752845e-01 -1.32445180e+00
-3.53162289e-01 -1.05393255e+00 1.19744503e+00 -1.16647854e-02
-2.52081215e-01 -9.83614683e-01 2.42128298e-01 -5.11596166e-02
3.34875017e-01 3.89034115e-02 5.70956528e-01 -6.21493697e-01
-2.56738275e-01 -3.03715229e-01 -2.76755452e-01 2.88682431e-01
-3.71466547e-01 1.86442062e-01 -9.57886696e-01 -3.09647173e-01
1.83873907e-01 -4.06995744e-01 1.17442656e+00 9.46825445e-01
1.06063068e+00 1.17832730e-02 -5.42638063e-01 6.57798469e-01
1.31047451e+00 -3.02071154e-01 9.65074152e-02 -1.44545421e-01
5.25447667e-01 3.51430267e-01 5.62149048e-01 7.07555652e-01
1.26040593e-01 3.27633202e-01 2.83274725e-02 3.84285212e-01
3.90304267e-01 -2.30846748e-01 4.63628143e-01 5.37699401e-01
-7.45503977e-02 -7.74439722e-02 -1.23909271e+00 5.24421096e-01
-2.08294153e+00 -7.97388613e-01 -1.80804089e-01 2.33415580e+00
1.14321899e+00 3.68570209e-01 -1.20427750e-01 -4.56485480e-01
5.64824104e-01 1.57137439e-01 -7.33007014e-01 -1.90557823e-01
3.92717421e-02 2.13294670e-01 8.99885356e-01 8.62191319e-01
-1.17811096e+00 1.03444612e+00 8.38006592e+00 1.13903475e+00
-6.60960078e-01 2.97408432e-01 8.30151498e-01 -4.95951116e-01
-3.14296842e-01 -3.28191407e-02 -1.32840371e+00 5.89123547e-01
1.12509620e+00 -6.70790672e-02 4.70314264e-01 1.09087205e+00
2.53294319e-01 -4.46084112e-01 -1.46206760e+00 1.12036562e+00
-4.20377761e-01 -1.20978975e+00 -5.12603641e-01 -6.12287819e-02
1.11517346e+00 7.24135280e-01 6.57367706e-02 3.99863303e-01
1.24768555e+00 -1.30813694e+00 7.41749763e-01 6.76999986e-01
7.02279985e-01 -6.86297894e-01 5.90015590e-01 5.29165089e-01
-6.60151303e-01 1.98623091e-02 -6.64776325e-01 -1.37202432e-02
2.98404813e-01 1.21655750e+00 -8.40307295e-01 -1.33786619e-01
7.49588311e-01 4.20797914e-01 -1.58573568e-01 9.64362621e-01
-3.85557204e-01 9.26545084e-01 -1.12697637e+00 -3.24142009e-01
3.02278489e-01 -3.14631879e-01 6.80393040e-01 1.53202760e+00
2.95296758e-01 -1.93853769e-02 1.27999425e-01 1.01497233e+00
-2.00090166e-02 -1.69123217e-01 -5.42261243e-01 -9.20547321e-02
4.45764065e-01 6.15631163e-01 -3.90579641e-01 -3.08337510e-01
-2.47836381e-01 7.12475061e-01 6.09191597e-01 8.09178531e-01
-6.77087426e-01 -1.73929527e-01 8.59713256e-01 -2.18134880e-01
3.75760168e-01 -3.93873096e-01 -6.55050516e-01 -1.44063199e+00
-6.06625602e-02 -6.18819356e-01 2.39930451e-01 -6.29769325e-01
-1.67846584e+00 2.35838816e-01 1.60972252e-01 -6.29022539e-01
-6.30142808e-01 -7.88734674e-01 -3.78989428e-01 1.27710855e+00
-1.25594854e+00 -4.50742006e-01 2.16144726e-01 4.34997022e-01
4.08055931e-01 1.25798568e-01 5.99895954e-01 -2.20146179e-01
-5.45791686e-01 4.46190655e-01 7.58873463e-01 -1.85884252e-01
6.58516705e-01 -1.67042208e+00 3.98621887e-01 9.48702633e-01
1.76306576e-01 7.94718862e-01 1.22064352e+00 -7.32744992e-01
-1.36775482e+00 -6.33321106e-01 5.02868831e-01 -9.13121819e-01
1.01928532e+00 -3.43188912e-01 -6.37519002e-01 8.86273503e-01
-3.49757165e-01 -7.65241385e-02 5.96224606e-01 8.01052749e-01
-1.86535373e-01 9.16669071e-02 -1.11120892e+00 7.32387722e-01
7.27818072e-01 -6.60503626e-01 -6.31077766e-01 6.79122627e-01
4.78953630e-01 -5.94565809e-01 -8.46042395e-01 2.27109462e-01
5.73449135e-01 -6.50645316e-01 8.85953128e-01 -8.95850599e-01
3.90616536e-01 -2.75411606e-01 -2.90923178e-01 -1.42749572e+00
-1.56309500e-01 -1.16486084e+00 -3.55929792e-01 8.44404101e-01
7.40990758e-01 -6.51592731e-01 9.62454677e-01 1.12949800e+00
1.30922005e-01 -7.81624615e-01 -9.54355299e-01 -6.44394577e-01
2.52462387e-01 -1.14457917e+00 4.44985852e-02 5.56507051e-01
-1.49347588e-01 3.18742484e-01 -3.53154302e-01 3.05209517e-01
1.06293190e+00 9.74920392e-02 5.40241420e-01 -1.11111033e+00
-5.24654925e-01 -5.00625551e-01 -7.09628239e-02 -1.57408202e+00
1.91872254e-01 -4.15148169e-01 6.73938453e-01 -1.21002090e+00
1.65382653e-01 -5.40692508e-01 -2.73261905e-01 -5.96886091e-02
-6.16127491e-01 -1.13559611e-01 -9.42394063e-02 3.74089420e-01
-5.49462140e-01 5.27366340e-01 8.95937741e-01 3.43721025e-02
-2.15540051e-01 3.94827962e-01 -6.98439300e-01 1.02671576e+00
5.71929634e-01 -6.92126870e-01 -3.20007503e-01 -3.92389894e-01
4.62915242e-01 1.23544693e-01 -1.47430956e-01 -7.49838591e-01
3.12570095e-01 -3.32147479e-01 5.78523457e-01 -6.98192060e-01
4.34451818e-01 -5.22674322e-01 -5.27349077e-02 4.36556637e-02
-5.76857865e-01 -2.52517968e-01 7.80557245e-02 1.16076136e+00
-2.15966068e-02 -6.28982186e-01 7.53893614e-01 -1.51865497e-01
-2.45086282e-01 2.21025631e-01 -4.39810872e-01 4.62889552e-01
5.22353053e-01 2.97785759e-01 -2.40508858e-02 -6.68995738e-01
-8.57674241e-01 4.72013205e-01 1.90528229e-01 -2.81336695e-01
4.71474379e-01 -9.40300524e-01 -9.03358817e-01 -2.72667348e-01
-2.58705109e-01 2.98943162e-01 -3.69937062e-01 8.30970287e-01
-3.56608957e-01 3.43057007e-01 6.52034700e-01 -8.16589177e-01
-7.45000005e-01 2.43759915e-01 2.71415144e-01 -4.56776589e-01
-2.55436301e-01 1.42358518e+00 7.52528086e-02 -3.40712219e-01
4.29263055e-01 -7.02106714e-01 2.80592352e-01 -1.73508488e-02
5.39475501e-01 4.97503102e-01 -3.02861452e-01 -2.18465608e-02
-2.01333389e-01 3.84483188e-01 -3.31292003e-02 -7.42693484e-01
1.10375071e+00 -1.74773201e-01 -3.29277627e-02 8.31601262e-01
1.04448545e+00 1.32597089e-01 -1.66516662e+00 -3.96969676e-01
2.23772645e-01 -5.57254553e-01 2.83047497e-01 -5.81323743e-01
-4.93154228e-01 9.86394525e-01 3.78206640e-01 1.29468702e-02
3.86389017e-01 -1.86281148e-02 2.24259168e-01 8.05604696e-01
4.04145509e-01 -1.23914444e+00 -2.49784023e-01 7.17920363e-01
7.50340402e-01 -1.50864041e+00 5.05576074e-01 -2.02018589e-01
-6.67822599e-01 9.21497643e-01 1.07639253e-01 -2.63791800e-01
1.00871098e+00 2.63027757e-01 -2.10704163e-01 -2.02976078e-01
-7.74146676e-01 5.92965959e-03 4.28911299e-01 4.84293014e-01
3.70910645e-01 2.64766812e-01 7.78452381e-02 5.08672714e-01
-3.56103718e-01 -2.20046923e-01 9.97980461e-02 8.33287954e-01
-6.40068829e-01 -4.26983267e-01 -4.55454409e-01 8.18656623e-01
-8.39514434e-01 -4.93191600e-01 6.99263588e-02 4.05623496e-01
-5.58318555e-01 1.02171791e+00 -3.91198099e-02 6.30305782e-02
-4.59710769e-02 2.38219619e-01 4.49984014e-01 -6.16758883e-01
-1.55608341e-01 2.69168973e-01 3.78374577e-01 -7.73534536e-01
1.06779626e-02 -1.08225811e+00 -8.22155952e-01 -3.78166527e-01
-5.15851676e-01 2.11458325e-01 9.63724017e-01 9.77402925e-01
1.42851189e-01 2.32185811e-01 2.97264993e-01 -9.67344940e-01
-1.47695744e+00 -1.10366237e+00 -6.60860121e-01 5.87583482e-02
3.41499418e-01 -5.14509320e-01 -6.97585583e-01 -2.01234385e-01] | [6.819884777069092, 3.9244351387023926] |
312d4e4a-9e4f-40a4-8768-9be5282f28a4 | quantifying-facial-age-by-posterior-of-age | 1708.09687 | null | http://arxiv.org/abs/1708.09687v2 | http://arxiv.org/pdf/1708.09687v2.pdf | Quantifying Facial Age by Posterior of Age Comparisons | We introduce a novel approach for annotating large quantity of in-the-wild
facial images with high-quality posterior age distribution as labels. Each
posterior provides a probability distribution of estimated ages for a face. Our
approach is motivated by observations that it is easier to distinguish who is
the older of two people than to determine the person's actual age. Given a
reference database with samples of known ages and a dataset to label, we can
transfer reliable annotations from the former to the latter via
human-in-the-loop comparisons. We show an effective way to transform such
comparisons to posterior via fully-connected and SoftMax layers, so as to
permit end-to-end training in a deep network. Thanks to the efficient and
effective annotation approach, we collect a new large-scale facial age dataset,
dubbed `MegaAge', which consists of 41,941 images. Data can be downloaded from
our project page mmlab.ie.cuhk.edu.hk/projects/MegaAge and
github.com/zyx2012/Age_estimation_BMVC2017. With the dataset, we train a
network that jointly performs ordinal hyperplane classification and posterior
distribution learning. Our approach achieves state-of-the-art results on
popular benchmarks such as MORPH2, Adience, and the newly proposed MegaAge. | ['Chen Change Loy', 'Li Liu', 'Yunxuan Zhang', 'Cheng Li'] | 2017-08-31 | null | null | null | null | ['age-and-gender-classification'] | ['computer-vision'] | [-2.13939399e-01 2.01854035e-01 -2.22778931e-01 -9.78283823e-01
-8.78459573e-01 1.31136579e-02 2.14157775e-01 -2.20306039e-01
-6.62258387e-01 8.01698744e-01 -1.43401064e-02 1.48078442e-01
3.20760190e-01 -6.90144062e-01 -4.97231543e-01 -8.18947315e-01
-1.62950948e-01 8.20322275e-01 -3.76641214e-01 3.70844126e-01
-1.19059086e-01 2.87244052e-01 -1.60106587e+00 -7.77118653e-02
7.40033209e-01 1.67086244e+00 -2.98927903e-01 6.04474127e-01
2.24007010e-01 5.24110556e-01 -4.66741294e-01 -1.10305429e+00
2.43857577e-01 -1.29945770e-01 -8.66458416e-01 -5.81403375e-02
1.02772975e+00 -7.37528443e-01 -2.86071151e-01 1.11709118e+00
6.62306070e-01 -2.43674695e-01 8.29346657e-01 -1.88485670e+00
-8.13754678e-01 6.35269642e-01 -9.52250004e-01 -3.72987866e-01
1.81045696e-01 -2.92814057e-02 7.57220685e-01 -6.97315037e-01
3.85034323e-01 1.52680099e+00 8.05916965e-01 1.08894277e+00
-8.55976045e-01 -1.31768441e+00 -4.42929715e-02 2.58066058e-01
-1.62179661e+00 -6.24209106e-01 6.34551883e-01 -5.23624897e-01
1.60134807e-01 -6.05598055e-02 4.31435615e-01 1.42198086e+00
-1.89039603e-01 6.43391430e-01 1.18126810e+00 -1.39404684e-01
9.47491378e-02 -9.02547613e-02 6.37274534e-02 1.16633737e+00
5.82554191e-02 -1.40347824e-01 -7.37271547e-01 -1.42991379e-01
5.68759382e-01 -1.03907011e-01 -1.63691744e-01 3.61916819e-03
-7.52184093e-01 6.49227619e-01 3.20804030e-01 -4.77282017e-01
-8.01385120e-02 4.31079566e-01 3.11484337e-01 1.83998436e-01
8.14009249e-01 -1.51538759e-01 -6.57089233e-01 2.68172771e-02
-8.89998972e-01 2.50205398e-01 6.71792507e-01 8.11271548e-01
6.77785277e-01 -3.00713331e-01 1.65659888e-03 8.66220951e-01
4.03308302e-01 6.09467745e-01 2.53531516e-01 -1.32999337e+00
2.83366621e-01 2.05874950e-01 -3.85716297e-02 -4.50708389e-01
-2.14358225e-01 1.25994310e-01 -9.85588968e-01 5.44768870e-01
9.65959668e-01 -3.30986381e-01 -1.21082008e+00 2.20169282e+00
4.48045403e-01 1.98729709e-01 -1.54521435e-01 6.97380424e-01
7.86851764e-01 4.43941802e-01 4.32187259e-01 -3.04134011e-01
1.48364067e+00 -8.37440133e-01 -4.89928246e-01 -3.74866165e-02
4.79158223e-01 -4.33510482e-01 7.58454502e-01 5.54359198e-01
-1.00185561e+00 -5.44210076e-01 -8.24516833e-01 -1.71031028e-01
-3.98931891e-01 4.81992602e-01 7.36933410e-01 6.67428195e-01
-1.17806184e+00 8.25586021e-01 -8.18422318e-01 -4.32796597e-01
1.19529438e+00 7.09829807e-01 -7.48628974e-01 1.33052066e-01
-9.46401477e-01 6.67287171e-01 3.68142188e-01 3.43491137e-02
-8.74427795e-01 -8.22810650e-01 -1.01411307e+00 -3.27392668e-01
2.14379638e-01 -6.56452239e-01 1.26727188e+00 -1.11090803e+00
-1.32921195e+00 1.38228703e+00 -5.77301830e-02 -2.01977134e-01
7.35003650e-01 -4.28843439e-01 -3.45912755e-01 1.05001748e-01
1.04831206e-03 1.33834100e+00 1.01895797e+00 -9.82847989e-01
-7.00503469e-01 -8.95672500e-01 -2.24639252e-01 -1.84645429e-01
-7.50344872e-01 3.69150877e-01 -6.92281961e-01 -3.86927724e-01
-3.53792518e-01 -8.52944434e-01 1.97331503e-01 7.65979588e-01
-3.05815876e-01 -6.60567820e-01 7.00345457e-01 -1.10354078e+00
1.11089420e+00 -1.90411282e+00 2.11409926e-01 -1.95023566e-02
5.45944870e-01 -1.31404055e-02 -2.16360744e-02 -2.10286051e-01
-1.87208205e-01 -2.93735601e-02 -2.10851640e-01 -1.01381814e+00
1.16927288e-01 3.24443355e-02 6.00250065e-02 6.79516137e-01
1.83892667e-01 5.21692872e-01 -6.00453079e-01 -9.47332382e-01
-2.74596840e-01 6.15449011e-01 -4.21417862e-01 5.79577327e-01
6.26802444e-02 4.11924928e-01 -1.31537601e-01 9.90979373e-01
9.33022082e-01 2.12701187e-02 -1.14632703e-01 -2.34392509e-01
2.86805421e-01 -3.32320213e-01 -8.70831311e-01 1.52129185e+00
-3.09329629e-01 3.70152235e-01 1.42437354e-01 -6.26678824e-01
9.97759640e-01 2.63589174e-01 3.56991827e-01 -2.63651133e-01
4.65589523e-01 1.78330585e-01 -4.02842313e-01 -3.16963285e-01
2.00918704e-01 1.53776323e-02 -1.89290360e-01 2.08153442e-01
5.38378894e-01 2.71211058e-01 2.91320622e-01 -5.57883270e-02
5.71371615e-01 3.16855192e-01 5.73117957e-02 -1.00910783e-01
5.22659779e-01 -8.51802051e-01 9.42069888e-01 4.49920744e-02
-6.25765920e-01 5.57198107e-01 8.53963614e-01 -4.67698991e-01
-1.16154742e+00 -1.24079394e+00 -2.67925650e-01 1.32472229e+00
-2.71402806e-01 -3.60058010e-01 -1.08305657e+00 -1.07036722e+00
1.87764287e-01 1.14796005e-01 -1.16378307e+00 5.66563271e-02
-3.29041988e-01 -6.65412247e-01 7.48222888e-01 7.79838979e-01
6.87148929e-01 -9.21513557e-01 -1.07588463e-01 -3.84984195e-01
1.62669364e-02 -1.05459583e+00 -6.21180058e-01 -1.85213104e-01
-5.91168880e-01 -1.17617106e+00 -1.10209095e+00 -7.16858447e-01
9.68053937e-01 -7.53061414e-01 1.10379279e+00 9.39508528e-02
-2.90672958e-01 4.53626327e-02 5.91606684e-02 -5.21437407e-01
-1.45935953e-01 7.72975087e-02 4.57842588e-01 1.84760511e-01
5.84045708e-01 -6.62666738e-01 -7.56521285e-01 1.84289366e-01
-3.50024939e-01 1.14293993e-01 4.30289507e-01 6.71259642e-01
3.37550551e-01 -3.11685503e-01 5.45826077e-01 -8.63643646e-01
9.05264616e-02 -3.39096308e-01 -7.54341125e-01 3.34867656e-01
-6.22787714e-01 3.43656354e-02 3.60845298e-01 -5.24493039e-01
-9.34380591e-01 2.03759879e-01 -5.45380294e-01 -4.79608864e-01
-2.92930216e-01 -9.41346865e-03 -5.94254792e-01 1.15705028e-01
2.94010848e-01 -4.32149023e-01 1.50570586e-01 -5.36587059e-01
3.60097110e-01 9.19503272e-01 1.11396098e+00 -8.36294115e-01
8.22197437e-01 3.69298041e-01 -2.82347351e-02 -5.04790366e-01
-1.01942241e+00 -3.05010788e-02 -7.89243698e-01 -3.51688415e-01
1.06372094e+00 -1.09842229e+00 -1.05831707e+00 1.24358785e+00
-9.04267907e-01 -6.42885327e-01 1.60250828e-01 2.11132824e-01
-5.67346573e-01 1.59620196e-01 -8.72719049e-01 -8.57611239e-01
-6.78271234e-01 -9.15101230e-01 1.23739338e+00 6.60306096e-01
-2.36548483e-01 -8.78919065e-01 -1.65415704e-01 4.64772701e-01
3.40515561e-03 5.33083439e-01 7.00511456e-01 -3.66725564e-01
5.15609682e-02 -1.37875870e-01 -3.34272504e-01 5.35735846e-01
-6.45123050e-02 3.92482996e-01 -1.31433439e+00 -3.46721888e-01
-5.78657568e-01 -9.47637200e-01 9.91603732e-01 3.45079213e-01
1.88237286e+00 -3.43090117e-01 -2.24582329e-01 1.00290644e+00
1.27642298e+00 -1.98029295e-01 6.95674896e-01 -8.42829421e-02
8.80005360e-01 8.23613465e-01 5.42472661e-01 5.71050286e-01
5.98370612e-01 6.03185415e-01 3.38484049e-01 -1.05815217e-01
1.28602411e-03 -1.99150786e-01 3.37409765e-01 5.35644054e-01
-2.67134875e-01 3.20502935e-04 -8.09212565e-01 4.22219038e-01
-1.57340622e+00 -6.65200949e-01 2.88727552e-01 2.11917114e+00
1.25911331e+00 3.37782153e-03 4.67704564e-01 -1.00806076e-02
9.21396017e-01 1.07300051e-01 -4.94249016e-01 -2.24799067e-01
1.04041100e-01 2.94144571e-01 5.45275271e-01 4.05757159e-01
-1.31686962e+00 8.26676905e-01 4.91518259e+00 9.73727703e-01
-1.03266692e+00 1.36459917e-01 1.47129655e+00 -1.44554958e-01
3.37296784e-01 -4.64090645e-01 -1.04874408e+00 7.61689544e-01
1.11319149e+00 2.55443947e-03 3.31502050e-01 1.00688708e+00
-3.13067138e-01 -1.05890922e-01 -1.34255731e+00 1.36825633e+00
1.75635487e-01 -8.71588290e-01 -3.29131573e-01 9.28623006e-02
6.22941852e-01 -4.12084520e-01 3.99760693e-01 3.30378771e-01
2.98435092e-01 -1.25223470e+00 8.83573771e-01 6.04254007e-01
1.50940263e+00 -1.04409564e+00 8.05947721e-01 -7.62033090e-02
-1.12857533e+00 -1.18415959e-01 -3.38384867e-01 7.58793205e-02
4.50655399e-03 4.48854506e-01 -3.13495278e-01 2.63467163e-01
1.01968026e+00 6.38862491e-01 -8.36710751e-01 8.05060863e-01
-5.00398636e-01 2.98570305e-01 -1.90060019e-01 3.90899628e-01
-3.59467804e-01 -7.13169575e-02 -2.30352998e-01 8.41373682e-01
4.79189545e-01 -1.74780100e-04 -1.62909865e-01 5.90086281e-01
-6.96477771e-01 -2.40415633e-01 -1.47041827e-01 -2.11054366e-02
5.56006730e-01 1.61864710e+00 -4.92096841e-01 -3.37521046e-01
-2.42328778e-01 1.05557907e+00 7.67291903e-01 5.30839823e-02
-9.54340339e-01 -2.90661424e-01 1.03906250e+00 -9.69660189e-03
7.12313652e-02 -4.71826680e-02 -2.66717356e-02 -8.57332885e-01
-1.09334610e-01 -7.00126767e-01 6.51061475e-01 -9.12094533e-01
-1.63607740e+00 6.23020053e-01 5.70592582e-02 -6.30924821e-01
-1.13282979e-01 -9.55150962e-01 -5.60351789e-01 9.56919074e-01
-1.27031434e+00 -1.56911886e+00 -6.08464241e-01 5.70109367e-01
2.46946022e-01 -2.61310935e-01 8.52506638e-01 4.81922388e-01
-8.94142270e-01 1.21121442e+00 -3.02565962e-01 5.31526685e-01
1.30914414e+00 -1.51176989e+00 2.83232063e-01 6.78185403e-01
-3.07770342e-01 1.85145542e-01 5.24789929e-01 -6.01131439e-01
-8.77726972e-01 -1.25566053e+00 9.05883312e-01 -6.23138666e-01
6.10553384e-01 -6.97022915e-01 -7.35810935e-01 7.66153693e-01
1.71787173e-01 1.69340551e-01 6.77981436e-01 2.29890034e-01
-6.20569944e-01 -3.45887750e-01 -1.29011786e+00 5.45685887e-01
1.12566328e+00 -4.44984257e-01 -2.54278630e-01 1.04881734e-01
5.27543128e-01 -5.13520658e-01 -1.19094217e+00 4.51363623e-01
9.71081257e-01 -7.95963764e-01 8.15090656e-01 -3.65855843e-01
8.25603962e-01 1.81615204e-02 1.07418649e-01 -1.03391469e+00
8.52478519e-02 -5.56105793e-01 -5.31322002e-01 1.73788202e+00
1.97217092e-01 -5.34016728e-01 1.14625490e+00 8.24791074e-01
1.80737004e-01 -1.18784046e+00 -8.14400613e-01 -5.86879075e-01
2.61812806e-01 -2.80953974e-01 8.80319178e-01 6.67781234e-01
-4.98519570e-01 -1.04146078e-02 -5.80589533e-01 3.08068275e-01
1.01095831e+00 -3.67278099e-01 7.66730487e-01 -1.47176325e+00
-1.83030237e-02 -3.83683115e-01 -5.09856939e-01 -6.42935514e-01
6.96188331e-01 -5.60574412e-01 2.42395438e-02 -1.15376735e+00
4.07636821e-01 -4.80997652e-01 -2.76896536e-01 8.15133989e-01
-3.19015175e-01 7.77955413e-01 -8.71721506e-02 -1.47659183e-02
-6.29251301e-01 6.55976713e-01 9.63535845e-01 -2.56264172e-02
3.36628914e-01 -1.38458479e-02 -6.10170126e-01 8.69598508e-01
8.48548710e-01 -4.35854852e-01 -5.15071489e-02 -2.94206500e-01
6.75148070e-02 -7.96848163e-02 3.36471796e-01 -1.01239443e+00
1.13391973e-01 -5.00785038e-02 9.08233404e-01 -5.24677038e-01
5.74835598e-01 -5.01805305e-01 -4.99004237e-02 2.64284551e-01
-3.00561607e-01 -8.44230503e-02 -3.65427397e-02 1.50019139e-01
6.36417344e-02 1.51438452e-02 1.07704747e+00 2.63002217e-01
-7.71689713e-01 1.16560924e+00 4.12050873e-01 7.11945584e-03
9.79189396e-01 -2.15276033e-02 -5.94063818e-01 -3.28445494e-01
-7.26077259e-01 5.20161092e-01 6.64048016e-01 3.65450799e-01
3.57292682e-01 -1.59024119e+00 -8.78462315e-01 1.16439439e-01
2.90976673e-01 -1.41058058e-01 3.21699619e-01 6.61698103e-01
-5.21955192e-01 -1.47593215e-01 -7.18828738e-01 -3.71279836e-01
-1.70051777e+00 3.89718324e-01 3.26389223e-01 2.38558650e-02
-1.33104265e-01 1.42693973e+00 1.28341272e-01 -4.38463211e-01
5.56880474e-01 1.04580536e-01 -2.12297454e-01 3.00553560e-01
7.20052600e-01 2.38407105e-01 -3.31279755e-01 -7.23566592e-01
-3.59423757e-01 6.18260384e-01 -3.82684991e-02 -1.37454450e-01
1.27666652e+00 -1.36349099e-02 -2.49660268e-01 2.91661531e-01
1.47337973e+00 -3.06933045e-01 -1.73862708e+00 -4.13455479e-02
-1.94223151e-01 -5.90586841e-01 -1.54774725e-01 -7.09742367e-01
-1.52177250e+00 8.37647259e-01 9.93581653e-01 -3.37289035e-01
1.31305730e+00 3.10324281e-01 8.08189869e-01 -5.82170766e-03
2.38898024e-01 -1.28096890e+00 9.77067277e-02 2.20508486e-01
7.63360202e-01 -1.55714703e+00 8.32460895e-02 -3.39268327e-01
-5.80629408e-01 1.07629752e+00 1.06126285e+00 2.19239429e-01
6.79639935e-01 1.72532097e-01 2.48751998e-01 1.30696580e-01
-6.41517520e-01 -1.31646901e-01 2.37533450e-01 8.08415890e-01
3.06338489e-01 2.08616376e-01 6.54987898e-03 7.17800915e-01
-6.33368373e-01 6.04021773e-02 1.97348118e-01 4.00708437e-01
-1.76219910e-01 -1.25722909e+00 -2.95417309e-01 5.15770137e-01
-6.51810348e-01 1.42909408e-01 -1.74692571e-01 7.02146471e-01
6.05127990e-01 4.96102720e-01 4.13717210e-01 -3.92388344e-01
-2.75297076e-01 2.44791374e-01 7.48778820e-01 -3.38127553e-01
5.94884939e-02 -2.92673349e-01 2.25006640e-01 -5.39223552e-01
-2.98833221e-01 -6.62794173e-01 -1.03645170e+00 -6.20407462e-01
1.34524703e-01 4.40841876e-02 6.99836254e-01 7.82930255e-01
-1.58547580e-01 2.07485750e-01 5.86270630e-01 -1.00210905e+00
-3.74991804e-01 -1.11095822e+00 -7.80054867e-01 5.13889611e-01
3.24994475e-02 -7.96169460e-01 -1.85391515e-01 2.93913901e-01] | [13.556483268737793, 0.8640176653862] |
71b742a6-28ef-4875-8016-96c80c16a78f | information-redundancy-and-biases-in-public | 2304.14936 | null | https://arxiv.org/abs/2304.14936v1 | https://arxiv.org/pdf/2304.14936v1.pdf | Information Redundancy and Biases in Public Document Information Extraction Benchmarks | Advances in the Visually-rich Document Understanding (VrDU) field and particularly the Key-Information Extraction (KIE) task are marked with the emergence of efficient Transformer-based approaches such as the LayoutLM models. Despite the good performance of KIE models when fine-tuned on public benchmarks, they still struggle to generalize on complex real-life use-cases lacking sufficient document annotations. Our research highlighted that KIE standard benchmarks such as SROIE and FUNSD contain significant similarity between training and testing documents and can be adjusted to better evaluate the generalization of models. In this work, we designed experiments to quantify the information redundancy in public benchmarks, revealing a 75% template replication in SROIE official test set and 16% in FUNSD. We also proposed resampling strategies to provide benchmarks more representative of the generalization ability of models. We showed that models not suited for document analysis struggle on the adjusted splits dropping on average 10,5% F1 score on SROIE and 3.5% on FUNSD compared to multi-modal models dropping only 7,5% F1 on SROIE and 0.5% F1 on FUNSD. | ['Fabien Caspani', 'William Vanhuffel', 'Laurent Lam', 'Joel Tang', 'Pirashanth Ratnamogan', 'Seif Laatiri'] | 2023-04-28 | null | null | null | null | ['key-information-extraction'] | ['natural-language-processing'] | [ 1.69789866e-01 1.73645481e-01 -9.40841883e-02 -7.10177049e-02
-1.06025577e+00 -1.09425247e+00 1.02436507e+00 3.97228271e-01
-1.81675568e-01 5.75745642e-01 2.69129246e-01 -5.33379257e-01
-4.98785973e-01 -6.53617084e-01 -8.02601099e-01 -2.52338380e-01
-1.05280839e-01 5.56509495e-01 3.51420909e-01 -2.03075662e-01
3.82762462e-01 4.31429058e-01 -1.80746484e+00 9.41094100e-01
9.22540843e-01 7.10634410e-01 1.47746995e-01 9.37454283e-01
-5.75882494e-01 6.06026709e-01 -1.19310677e+00 -2.98085958e-01
-3.83756272e-02 -5.93732223e-02 -1.02846014e+00 -1.12887792e-01
1.02508497e+00 -5.65084219e-02 -5.99028766e-02 6.73328936e-01
5.63751876e-01 -1.63494930e-01 8.01280558e-01 -1.45603406e+00
-7.53623009e-01 9.72134948e-01 -3.68159890e-01 1.72698677e-01
7.09952474e-01 2.47829482e-02 1.11217725e+00 -1.07359099e+00
1.27942920e+00 1.37955189e+00 6.29473746e-01 2.92703629e-01
-1.32324088e+00 -4.11844701e-01 1.97064459e-01 7.65197650e-02
-1.24816358e+00 -2.46134043e-01 1.93765774e-01 -4.50412303e-01
1.15131545e+00 7.17810273e-01 2.04771072e-01 1.27203774e+00
3.16450596e-02 1.15236783e+00 1.11977684e+00 -5.75170338e-01
7.01775476e-02 5.33529699e-01 5.23417652e-01 4.77914512e-01
4.99047250e-01 -2.63233215e-01 -5.40073335e-01 4.13249321e-02
1.97860107e-01 -4.62618411e-01 -3.24166507e-01 -2.59282023e-01
-1.12332225e+00 4.18822438e-01 1.33110523e-01 5.63661933e-01
1.05141394e-01 -2.93369025e-01 7.00382173e-01 2.97747761e-01
4.52920556e-01 6.86936140e-01 -5.83733559e-01 -3.39612961e-01
-1.03337514e+00 5.06045341e-01 7.93049335e-01 1.15936041e+00
5.03316045e-01 -2.09172726e-01 -6.62383497e-01 9.44179177e-01
-2.69537330e-01 4.54751492e-01 3.69768173e-01 -5.44255555e-01
1.01281512e+00 9.84931707e-01 5.06936200e-02 -9.19320464e-01
-4.79655683e-01 -8.59044731e-01 -5.88198185e-01 7.47848302e-02
6.49212778e-01 4.11373168e-01 -1.11557841e+00 1.28134656e+00
-1.32929564e-01 -5.89957178e-01 1.04084007e-01 1.66115597e-01
1.07336330e+00 6.45198286e-01 -5.82601801e-02 1.27341494e-01
1.14539790e+00 -7.32603312e-01 -4.94952410e-01 -3.50156456e-01
1.24880624e+00 -8.79457176e-01 1.81167269e+00 5.43061376e-01
-9.99655068e-01 -6.19089901e-01 -1.22195601e+00 -7.59958401e-02
-8.77747416e-01 3.05087417e-01 3.41111749e-01 8.46524060e-01
-9.59263086e-01 6.04574978e-01 -2.43691057e-01 -4.40451145e-01
6.07257962e-01 2.63771461e-03 -5.16676784e-01 -5.90980947e-01
-8.44681919e-01 8.99713814e-01 5.47783911e-01 -2.54124433e-01
-8.90900970e-01 -1.21355474e+00 -5.69855213e-01 1.31960720e-01
5.31634033e-01 -2.73308009e-01 1.04500222e+00 -1.49616584e-01
-8.75758827e-01 8.67591500e-01 4.61463258e-02 -3.23093861e-01
7.84095526e-01 -3.66642743e-01 -7.20097125e-01 -3.67844515e-02
3.54045257e-02 5.12550592e-01 2.27301240e-01 -1.48749781e+00
-6.99912071e-01 -3.84139836e-01 3.15450668e-01 -1.43007800e-01
-3.19775522e-01 -1.14276983e-01 -4.75785941e-01 -4.41877156e-01
-1.43572912e-01 -7.36597478e-01 3.15134794e-01 -4.49604064e-01
-7.69199312e-01 -1.47424966e-01 1.22885299e+00 -6.69423580e-01
1.49803245e+00 -1.85287726e+00 -2.89545264e-02 2.17849240e-01
9.85541418e-02 3.20101798e-01 -4.28139359e-01 7.50364006e-01
-1.65904418e-01 5.50340235e-01 -1.64131299e-02 -2.37929389e-01
2.62368500e-01 -1.01205826e-01 -3.83276641e-01 -1.69529058e-02
1.20620295e-01 6.89807177e-01 -7.22132444e-01 -4.02222335e-01
-6.87031122e-03 3.27865183e-01 -3.01811159e-01 -1.76326632e-01
-4.30400044e-01 -1.66509539e-01 -1.94078237e-02 7.32983053e-01
7.03133941e-01 -1.84431404e-01 7.35651106e-02 -1.80160433e-01
-1.77882135e-01 3.22228074e-01 -1.37922990e+00 1.52460539e+00
-5.80679119e-01 1.09588969e+00 -2.95301229e-01 -4.89538312e-01
8.60189557e-01 -7.35724121e-02 -1.51943797e-02 -1.08729267e+00
-3.53563935e-01 9.20846835e-02 -1.11096189e-03 -1.93073839e-01
1.03355408e+00 6.37271762e-01 -1.61508143e-01 5.10625541e-01
-3.89106199e-02 -2.42639154e-01 8.26891601e-01 7.54154861e-01
1.35882545e+00 3.56612913e-02 -6.45205379e-02 -4.67510134e-01
5.14314592e-01 2.35331357e-01 -1.34190798e-01 8.98488641e-01
3.88747782e-01 6.92781627e-01 8.85271966e-01 -3.67549986e-01
-1.06075811e+00 -1.02525437e+00 -3.61943424e-01 1.12096536e+00
-1.33623183e-01 -1.20355761e+00 -8.23756456e-01 -1.05871022e+00
8.29020068e-02 1.28543901e+00 -5.47278047e-01 -1.05353102e-01
-3.43418390e-01 -8.28655303e-01 8.28726888e-01 6.86727941e-01
3.31110299e-01 -7.14461684e-01 -3.34599704e-01 -1.79634150e-02
7.09355623e-02 -1.15941024e+00 4.89479154e-02 1.30301461e-01
-5.61056256e-01 -1.18335330e+00 -6.06305897e-01 -2.31437683e-01
5.01865327e-01 7.49943554e-02 1.68723071e+00 1.85058322e-02
-5.72320700e-01 5.14804423e-01 -4.44487244e-01 -6.01660013e-01
-7.34668076e-01 4.29417104e-01 -4.96283382e-01 -6.82695389e-01
2.62030870e-01 2.66232099e-02 -3.05751890e-01 5.75578988e-01
-1.03287220e+00 2.69261152e-02 5.28430998e-01 7.25974560e-01
4.70021158e-01 1.79165542e-01 3.45785141e-01 -1.12704301e+00
8.15234303e-01 -3.15725148e-01 -5.07057965e-01 7.06282794e-01
-9.91869092e-01 2.94436753e-01 5.40604949e-01 -3.05079371e-01
-1.02497470e+00 -5.74546278e-01 2.29380861e-01 1.06665872e-01
-1.42104700e-01 4.64999050e-01 -3.22448254e-01 2.83024281e-01
1.02522433e+00 -4.69648046e-03 -5.07296383e-01 -7.73531854e-01
3.81053448e-01 7.89518237e-01 3.99068922e-01 -7.71784306e-01
7.31399894e-01 1.99775830e-01 -2.39893273e-01 -8.66485715e-01
-5.71785510e-01 -2.86667079e-01 -4.81398284e-01 -6.41498789e-02
3.87892395e-01 -5.42511225e-01 -4.24212545e-01 2.27849394e-01
-1.01237488e+00 -3.17428946e-01 -3.64606440e-01 -3.24536487e-02
-1.84833437e-01 2.64458150e-01 -1.96494296e-01 -7.32788861e-01
-3.02332759e-01 -1.12891388e+00 1.37492394e+00 -6.86649457e-02
-5.84912479e-01 -9.09102321e-01 3.07379365e-02 2.77230322e-01
3.01141322e-01 2.14979813e-01 1.42197669e+00 -7.50213265e-01
-5.03521860e-01 -2.86285013e-01 -5.46509862e-01 2.90395945e-01
-2.40249429e-02 5.42848945e-01 -1.10919702e+00 -3.90144050e-01
-8.46401989e-01 -1.17478944e-01 8.73537481e-01 3.33632566e-02
1.13934171e+00 4.51043360e-02 -5.71341097e-01 2.01798543e-01
1.46605062e+00 2.35435665e-01 9.26780343e-01 5.62754571e-01
7.74368048e-01 6.33430779e-01 6.76292360e-01 2.17297837e-01
2.65097767e-01 8.60012650e-01 4.34168309e-01 9.54285916e-03
-5.87020814e-01 -4.11827326e-01 2.58094877e-01 1.69312879e-01
5.20844571e-02 -7.20868647e-01 -1.36681938e+00 6.41529560e-01
-1.47587681e+00 -7.45333612e-01 -3.85015637e-01 2.15220428e+00
5.37250817e-01 5.91303766e-01 1.59191385e-01 6.66157365e-01
4.36172575e-01 1.18333198e-01 -3.09114102e-02 -5.15834451e-01
-4.49751168e-01 9.40584764e-02 3.90359312e-01 2.84000814e-01
-7.49174893e-01 7.48200059e-01 6.28618479e+00 1.04251575e+00
-6.86849773e-01 -2.51446396e-01 3.96870077e-01 -1.71214014e-01
-7.09603012e-01 -1.21580310e-01 -1.23773479e+00 5.21346569e-01
1.17789340e+00 -7.99516588e-02 -5.80076315e-02 7.41468072e-01
-1.10344440e-01 -3.45244110e-01 -1.29764497e+00 7.90532172e-01
3.14237475e-02 -1.62085915e+00 3.68752390e-01 1.54696509e-01
7.59282410e-01 -2.07791016e-01 1.33420303e-01 3.38848203e-01
2.50941575e-01 -1.22534561e+00 8.31951201e-01 4.12622094e-01
8.72580051e-01 -7.99904823e-01 7.67500162e-01 2.29334146e-01
-1.07424879e+00 3.12929763e-03 -3.75111282e-01 2.41901413e-01
-3.47639799e-01 5.57047129e-01 -1.17621672e+00 9.07360494e-01
9.18010116e-01 4.91385877e-01 -1.36395657e+00 9.54147160e-01
-6.53787097e-03 3.15912873e-01 -2.65776902e-01 -7.84903169e-02
3.39648366e-01 2.26993009e-01 5.32012284e-01 1.59112620e+00
3.67063850e-01 -7.49879301e-01 -3.07501584e-01 6.28525138e-01
-2.63997521e-02 2.38260314e-01 -6.68844104e-01 -2.85790354e-01
3.42885733e-01 9.87243831e-01 -7.14178026e-01 -3.50283951e-01
-2.79826283e-01 6.62795186e-01 1.35582030e-01 2.83163548e-01
-6.45463049e-01 -5.16833484e-01 3.61771166e-01 3.54485899e-01
3.42560440e-01 4.28972170e-02 -2.97508568e-01 -8.81655991e-01
3.89339626e-01 -1.11616814e+00 5.35852373e-01 -9.34254706e-01
-8.05383503e-01 7.57835865e-01 4.74731624e-01 -1.18110156e+00
-4.76369828e-01 -8.49559665e-01 -4.04947579e-01 7.85841107e-01
-9.70075309e-01 -1.10374856e+00 -5.15125215e-01 3.78324836e-01
6.38431013e-01 -2.59119391e-01 9.55286205e-01 2.53843874e-01
-7.43327439e-01 7.32698798e-01 4.70480323e-01 -1.39890999e-01
6.87493503e-01 -1.61048532e+00 6.64452612e-01 8.61774147e-01
4.51942474e-01 5.06951392e-01 9.54409182e-01 -5.16664445e-01
-1.07049894e+00 -9.07480419e-01 8.79887044e-01 -8.88087034e-01
5.01070201e-01 -6.15021288e-01 -1.03583229e+00 5.92485189e-01
1.93218708e-01 -1.76292464e-01 3.81061226e-01 3.51288050e-01
-8.03998947e-01 -4.72565787e-03 -1.05146229e+00 7.06459224e-01
1.36043370e+00 -7.13696539e-01 -4.91265148e-01 4.50195998e-01
4.04623330e-01 -4.81936097e-01 -9.44895029e-01 2.77590632e-01
6.53811514e-01 -1.18318284e+00 9.88062143e-01 -7.15468526e-01
5.99914789e-01 -2.54645169e-01 -1.81201130e-01 -1.37677026e+00
9.25369263e-02 -2.60111004e-01 -4.74884249e-02 1.63324475e+00
8.97700012e-01 -1.63556486e-01 7.26972044e-01 3.32834095e-01
-2.06904158e-01 -4.89519000e-01 -5.19333422e-01 -1.13076615e+00
1.65645093e-01 -6.99889064e-01 5.41617572e-01 6.67462170e-01
-7.92935118e-02 2.63246566e-01 4.86758575e-02 -1.16910003e-01
3.25136423e-01 -7.97007605e-02 9.87583578e-01 -1.25665975e+00
-1.26311466e-01 -4.78043586e-01 -4.30269390e-01 -5.73938966e-01
-9.88494381e-02 -9.05615628e-01 -3.70781928e-01 -1.91921353e+00
1.97869942e-01 -2.18704477e-01 -3.00516811e-04 4.10525233e-01
8.97044390e-02 7.14699030e-02 2.74159521e-01 -9.00062397e-02
-6.07863128e-01 -6.80378452e-02 1.05595648e+00 -5.92285991e-01
-1.83207616e-01 -1.01202644e-01 -6.92090094e-01 4.75797921e-01
4.78620321e-01 -4.12986845e-01 -7.64332414e-01 -4.14125353e-01
5.28184235e-01 -4.39433366e-01 3.46113205e-01 -1.09474850e+00
1.50335049e-02 3.29861522e-01 6.03264749e-01 -1.06035256e+00
2.12170519e-02 -6.60782993e-01 1.65475771e-01 3.90120298e-01
-3.58807087e-01 1.98908791e-01 7.52161980e-01 2.65183896e-01
-2.43974194e-01 -3.11830968e-01 1.44178450e-01 5.98239079e-02
-9.38044250e-01 -2.90575564e-01 -1.94608092e-01 2.81473011e-01
8.16006601e-01 -5.55155873e-01 -1.06126666e+00 -2.24176317e-01
-5.14310658e-01 1.96989309e-02 4.00925219e-01 6.92980468e-01
4.54467714e-01 -9.06800449e-01 -7.59539783e-01 7.77583569e-02
6.56010211e-01 -2.44062081e-01 3.79931957e-01 4.35687870e-01
-6.18906736e-01 7.94173419e-01 -2.73805410e-01 -7.24765062e-01
-1.50457275e+00 4.02302593e-01 1.82582974e-01 -7.42094576e-01
-5.15760303e-01 7.03450441e-01 4.18086201e-02 -4.27270323e-01
3.88943881e-01 -6.85319126e-01 -5.98763376e-02 4.18880790e-01
7.37663746e-01 8.65963161e-01 7.08371937e-01 -2.25054890e-01
-5.51582992e-01 4.34355199e-01 -5.16568363e-01 -3.91494222e-02
1.12729537e+00 1.84606537e-01 2.82923371e-01 2.32206970e-01
1.29774582e+00 3.57178032e-01 -7.90047407e-01 7.10701421e-02
4.94612217e-01 -4.19294626e-01 -6.76438725e-03 -1.29410279e+00
-6.24561012e-01 8.01635504e-01 6.66571021e-01 6.97605133e-01
8.69790733e-01 3.18801589e-02 1.69786885e-01 5.10007679e-01
2.84244150e-01 -1.11092889e+00 -1.45794511e-01 4.96769607e-01
1.24222207e+00 -9.71488893e-01 1.97792307e-01 -5.16409516e-01
-4.82266724e-01 1.10567880e+00 4.13117319e-01 4.12612528e-01
1.40613869e-01 4.62699056e-01 -1.39180794e-01 -2.90151119e-01
-7.82680511e-01 -7.25596324e-02 6.28682315e-01 8.38056803e-01
5.08187175e-01 -2.11195216e-01 1.91144906e-02 3.83639038e-01
-5.08116186e-01 -1.33616701e-01 5.49313068e-01 8.93177390e-01
-2.98216492e-02 -1.14281511e+00 -2.22812384e-01 5.42848349e-01
-2.45265707e-01 -1.79398701e-01 -7.81581461e-01 1.54655957e+00
-1.41640469e-01 8.02315176e-01 1.57312885e-01 -4.00703996e-01
9.38759863e-01 2.56824732e-01 5.82590997e-01 -6.73456907e-01
-8.19317043e-01 -2.81293809e-01 7.18201995e-01 -6.19434834e-01
1.01201978e-04 -5.40301979e-01 -7.90007472e-01 -4.51163083e-01
-9.64770168e-02 9.40324143e-02 7.91540742e-01 8.52547765e-01
3.43428761e-01 8.27456892e-01 -1.71225220e-02 -3.60901773e-01
-3.79236132e-01 -1.04462850e+00 -4.43864316e-01 3.18130702e-01
6.57918826e-02 -5.57797909e-01 -4.06881839e-01 -1.45070553e-01] | [11.604430198669434, 2.607855796813965] |
b33ac5be-4d62-4888-ab9c-f6f8280ac5cf | joint-weakly-supervised-at-and-aed-using-deep | 2103.12388 | null | https://arxiv.org/abs/2103.12388v2 | https://arxiv.org/pdf/2103.12388v2.pdf | Joint framework with deep feature distillation and adaptive focal loss for weakly supervised audio tagging and acoustic event detection | A good joint training framework is very helpful to improve the performances of weakly supervised audio tagging (AT) and acoustic event detection (AED) simultaneously. In this study, we propose three methods to improve the best teacher-student framework in the IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events (DCASE) 2019 Task 4 for both audio tagging and acoustic events detection tasks. A frame-level target-events based deep feature distillation is first proposed, which aims to leverage the potential of limited strong-labeled data in weakly supervised framework to learn better intermediate feature maps. Then, we propose an adaptive focal loss and two-stage training strategy to enable an effective and more accurate model training, where the contribution of hard and easy acoustic events to the total cost function can be automatically adjusted. Furthermore, an event-specific post processing is designed to improve the prediction of target event time-stamps. Our experiments are performed on the public DCASE 2019 Task 4 dataset, results show that our approach achieves competitive performances in both AT (81.2\% F1-score) and AED (49.8\% F1-score) tasks. | ['Yuping Wang', 'Jiaen Liang', 'Yijie Li', 'Yanhua Long', 'Yunhao Liang'] | 2021-03-23 | null | null | null | null | ['audio-tagging'] | ['audio'] | [ 2.05807611e-01 -1.89284056e-01 1.20548874e-01 -5.00016510e-01
-1.68487549e+00 -4.57680285e-01 5.35428345e-01 4.20974255e-01
-6.21342659e-01 2.41979674e-01 3.34274679e-01 1.50579512e-01
6.83010519e-02 -3.46131980e-01 -7.39826858e-01 -6.08245194e-01
-2.68125087e-01 5.16184978e-02 5.66523850e-01 1.87568754e-01
-2.04435721e-01 1.42432123e-01 -1.53671384e+00 5.54364920e-01
5.43959737e-01 1.45877326e+00 2.81207800e-01 8.35117459e-01
2.14306578e-01 8.03986609e-01 -5.47757268e-01 -2.03000173e-01
-4.23581116e-02 -1.92428842e-01 -5.68428218e-01 -3.48052114e-01
2.35487923e-01 -9.56065115e-03 -1.93717033e-01 7.48576939e-01
1.05279922e+00 2.73347139e-01 5.74326754e-01 -1.12944794e+00
9.02088135e-02 9.89145935e-01 -3.05768579e-01 4.67281580e-01
1.95921004e-01 4.82468307e-02 1.14340723e+00 -1.23368824e+00
-3.01213190e-03 1.01499128e+00 8.19835186e-01 2.91842550e-01
-8.63612831e-01 -1.09660053e+00 2.03518540e-01 5.97375453e-01
-1.42722642e+00 -6.06351793e-01 9.31628466e-01 -4.09897685e-01
8.56766701e-01 2.06124306e-01 4.57079649e-01 1.16012096e+00
-2.86777288e-01 9.91173804e-01 7.62226701e-01 -5.08506119e-01
1.92639112e-01 -3.14318314e-02 6.48320466e-02 3.60827982e-01
-6.57308161e-01 6.14737831e-02 -1.03671658e+00 -1.83067635e-01
2.02380270e-01 -2.42958799e-01 -1.13610357e-01 2.79277980e-01
-1.05423641e+00 4.31235909e-01 2.70491928e-01 3.15956861e-01
-2.37123773e-01 1.49040863e-01 6.21472597e-01 5.03510498e-02
7.50216901e-01 2.61874259e-01 -6.48889363e-01 -4.66927022e-01
-9.21523154e-01 2.15109020e-01 3.55287045e-01 4.44049984e-01
3.38295609e-01 1.54526904e-01 -5.96321523e-01 1.31127203e+00
3.30085367e-01 4.73363101e-01 3.50769222e-01 -7.62918711e-01
5.66690505e-01 1.03661999e-01 -7.12076249e-03 -5.06851792e-01
-5.06502032e-01 -9.07484531e-01 -4.85268027e-01 -3.73862475e-01
4.58076820e-02 -2.34174937e-01 -8.47799897e-01 1.91619849e+00
4.73406166e-01 9.21019614e-01 -9.07287374e-02 6.84492588e-01
8.56251121e-01 8.74407887e-01 5.23427844e-01 -2.04836950e-01
1.44195735e+00 -7.95883417e-01 -8.25114310e-01 -1.14893638e-01
6.47548556e-01 -1.05751288e+00 1.04744387e+00 3.47891271e-01
-1.15835655e+00 -8.71956468e-01 -8.27825367e-01 1.21455513e-01
9.32820700e-03 4.51355934e-01 2.06222177e-01 3.38607252e-01
-4.83727723e-01 3.15244615e-01 -1.06258321e+00 6.65319487e-02
4.78482038e-01 2.72160292e-01 8.14385042e-02 1.85423180e-01
-1.51478326e+00 4.52244312e-01 5.62494516e-01 6.56532943e-02
-1.31728065e+00 -1.19324291e+00 -7.58313715e-01 2.10480094e-01
3.93238991e-01 -8.58762786e-02 1.55316734e+00 -4.73932952e-01
-1.45703101e+00 7.32926250e-01 -1.71303712e-02 -8.76902282e-01
2.96316504e-01 -5.63386559e-01 -7.18383789e-01 2.25890338e-01
-2.05513854e-02 5.92215300e-01 7.76069701e-01 -7.93299615e-01
-1.15515959e+00 -8.34474638e-02 -2.20145643e-01 3.06903452e-01
-6.11152411e-01 2.61529297e-01 -5.34665823e-01 -9.76345479e-01
-1.81302503e-01 -8.80414307e-01 3.14855054e-02 -3.37330848e-01
-1.98967651e-01 -6.48287058e-01 6.39464498e-01 -7.82782674e-01
1.47750664e+00 -2.63726568e+00 -1.80780292e-01 -2.11510751e-02
-4.86465916e-02 4.85701889e-01 -1.74885035e-01 2.38889456e-01
-5.24418950e-02 -2.48780236e-01 -5.14753051e-02 -6.67451680e-01
1.93889126e-01 -1.33713290e-01 -5.39093971e-01 9.20063928e-02
5.01185656e-01 4.89086837e-01 -8.57530415e-01 -4.26227003e-01
2.33846515e-01 6.46491766e-01 -6.29106939e-01 5.79957843e-01
-4.39118147e-02 3.92951488e-01 -4.00919646e-01 4.66228306e-01
4.56714541e-01 1.66271061e-01 -2.79381722e-01 -4.42196906e-01
-1.72273964e-01 6.33780241e-01 -1.21166694e+00 1.70193768e+00
-7.83874452e-01 4.40670252e-01 2.76943669e-02 -1.04562938e+00
7.02916205e-01 7.26498008e-01 7.08868206e-01 -6.66633964e-01
-6.01495095e-02 2.47263104e-01 -5.82490191e-02 -3.08978677e-01
1.83040097e-01 -6.37877807e-02 -3.55152220e-01 3.08451597e-02
4.21965927e-01 -6.20783539e-03 -5.63015975e-02 2.64371127e-01
1.09229612e+00 -2.27487311e-02 -1.40864342e-01 -5.15121557e-02
5.96591949e-01 -4.11652625e-01 7.94743061e-01 7.33699322e-01
-1.86289817e-01 6.68115079e-01 1.27883583e-01 -9.88460928e-02
-5.44192731e-01 -1.16497803e+00 -3.26683700e-01 1.63077331e+00
-2.07812101e-01 -5.78974843e-01 -7.02829540e-01 -7.12268293e-01
-2.77944058e-01 7.03022063e-01 -2.32225046e-01 -4.34230596e-01
-6.93160295e-01 -8.97147596e-01 9.27403927e-01 8.11090946e-01
3.70403707e-01 -9.67797339e-01 -3.26257944e-01 5.19959867e-01
-3.84284347e-01 -1.45509052e+00 -5.68726242e-01 6.96039557e-01
-3.32539588e-01 -7.53396630e-01 -6.52591348e-01 -9.00872111e-01
-4.08006795e-02 -1.47078946e-01 8.11262727e-01 -4.40533698e-01
-1.21122710e-01 3.54713023e-01 -5.57938337e-01 -7.39999473e-01
-1.97956264e-01 1.22747473e-01 9.46548581e-02 2.81059474e-01
2.48003572e-01 -5.60805976e-01 -5.96634924e-01 2.51719892e-01
-6.33199930e-01 -8.59329328e-02 4.58450377e-01 8.34506035e-01
8.17396462e-01 -8.69681761e-02 9.92348135e-01 -5.55456638e-01
2.65937001e-01 -4.10035789e-01 -4.30595934e-01 -2.74679344e-02
-4.26568002e-01 -2.91834325e-01 6.55226946e-01 -6.77321315e-01
-1.12956440e+00 2.04010546e-01 -7.56713212e-01 -3.29424590e-01
-1.96308181e-01 3.52497131e-01 -2.15807840e-01 3.14682305e-01
4.79955941e-01 1.69351786e-01 -7.80741930e-01 -8.29760969e-01
9.57893655e-02 8.27006698e-01 8.09555411e-01 -5.42915583e-01
6.93904340e-01 1.67306244e-01 -2.94466674e-01 -4.82229739e-01
-1.50166047e+00 -6.96234226e-01 -2.90847152e-01 -2.38347188e-01
8.75378370e-01 -1.44228220e+00 -4.65350419e-01 5.83332658e-01
-8.96022499e-01 -3.86994183e-01 -4.66147333e-01 7.73179054e-01
-3.43190670e-01 4.97468188e-02 -6.06517076e-01 -9.68038261e-01
-3.82857978e-01 -9.14093673e-01 1.33705020e+00 9.71318632e-02
-4.79368754e-02 -5.25494933e-01 2.05892488e-01 3.38992953e-01
3.18585396e-01 7.56613091e-02 6.02815747e-01 -1.10069263e+00
-9.30218846e-02 -1.42760694e-01 -2.03320291e-02 6.42809808e-01
-2.21580982e-01 -2.22670525e-01 -1.49204612e+00 -9.85556394e-02
-1.22422837e-01 -5.19820094e-01 1.05300033e+00 3.95278841e-01
1.51909399e+00 1.95389707e-02 -2.15094164e-01 4.88543808e-01
8.41854990e-01 3.33694637e-01 1.66354433e-01 -5.84834367e-02
5.90894759e-01 2.87361115e-01 9.00203228e-01 6.70727909e-01
5.21269321e-01 1.07414448e+00 2.71965146e-01 -1.22909814e-01
-4.97747451e-01 -3.47397476e-01 7.33260453e-01 1.29955876e+00
2.68688709e-01 -2.49473765e-01 -9.16057587e-01 8.27276528e-01
-1.72843540e+00 -7.33769894e-01 -6.52610809e-02 2.02203274e+00
1.13295960e+00 4.30407166e-01 1.98830456e-01 6.00276649e-01
7.12881923e-01 1.85022965e-01 -2.12818801e-01 1.53299561e-02
1.08639915e-02 5.40142596e-01 -1.02851108e-01 2.86674023e-01
-1.52847350e+00 7.75196016e-01 5.44177961e+00 1.41662061e+00
-9.90560830e-01 5.67429841e-01 4.68629420e-01 -3.71884197e-01
1.16897948e-01 -2.46430561e-01 -1.06140745e+00 7.08100259e-01
1.45866489e+00 9.58988592e-02 -4.12309207e-02 5.50926447e-01
3.04656863e-01 1.44105956e-01 -1.13897049e+00 1.09235179e+00
-2.39564404e-01 -1.09720325e+00 -2.73839325e-01 -3.34417820e-01
5.18994868e-01 1.26782253e-01 1.82370842e-01 8.28341186e-01
-8.07938799e-02 -5.30572414e-01 1.00843108e+00 3.81402403e-01
6.43137932e-01 -9.94816124e-01 6.62240624e-01 2.33113542e-01
-1.62477708e+00 -1.75462738e-01 -3.10630854e-02 2.21398577e-01
4.02414054e-01 9.54961181e-01 -1.03690886e+00 5.13121367e-01
9.81859088e-01 6.07565284e-01 -3.80427927e-01 1.15682387e+00
-1.94676191e-01 1.51467633e+00 -6.09908700e-01 2.10794270e-01
1.32771283e-01 5.87774456e-01 7.33507633e-01 1.69410145e+00
2.67003596e-01 5.27182780e-03 4.11786318e-01 3.85338455e-01
-2.46036261e-01 1.58083528e-01 9.17721987e-02 1.50687978e-01
7.62346029e-01 1.27208936e+00 -4.01677221e-01 -1.41411662e-01
-1.70619041e-01 6.06085479e-01 1.21305279e-01 1.09766141e-01
-1.22212017e+00 -5.10264158e-01 4.10343051e-01 -3.24189961e-02
4.18139726e-01 5.96489832e-02 1.54617757e-01 -1.01698816e+00
-8.63399878e-02 -4.68480587e-01 7.61735857e-01 -5.45309901e-01
-1.10790181e+00 4.94541347e-01 -8.86797532e-02 -1.31176639e+00
-3.18793595e-01 -1.30211398e-01 -7.88739145e-01 4.71833289e-01
-1.66141677e+00 -1.26974368e+00 -1.01248972e-01 6.98203504e-01
7.47047246e-01 -8.87095183e-02 7.21833706e-01 9.66260850e-01
-6.11430705e-01 9.52764153e-01 -1.03136785e-01 9.84302014e-02
9.79112208e-01 -1.30421507e+00 5.69456071e-02 8.37537527e-01
5.48820913e-01 -1.85995728e-01 4.64774489e-01 -2.38383844e-01
-9.24141109e-01 -1.49512637e+00 1.00230682e+00 -2.65629470e-01
6.95382357e-01 -6.63421690e-01 -8.33505809e-01 3.69697481e-01
-1.69475928e-01 2.72118986e-01 8.57498109e-01 2.80809999e-01
-2.13628337e-01 -4.81569111e-01 -7.16552615e-01 1.26427457e-01
9.26373005e-01 -9.02402639e-01 -4.80686575e-01 4.70066577e-01
9.25324082e-01 -3.76349926e-01 -1.08921123e+00 8.69238198e-01
4.18717742e-01 -3.89786541e-01 1.10545027e+00 -4.25798118e-01
-1.18274176e-02 -3.04007739e-01 -3.03203076e-01 -1.02279449e+00
-9.00254026e-02 -6.99300587e-01 -3.88442039e-01 1.83195972e+00
3.50786656e-01 -1.59985889e-02 2.88586169e-01 -8.60264227e-02
-5.57816803e-01 -7.87412047e-01 -1.16112006e+00 -7.02718079e-01
-3.59469533e-01 -1.10453463e+00 2.30805665e-01 7.29833007e-01
-3.28151941e-01 4.32275623e-01 -4.25959229e-01 4.93275404e-01
4.45920348e-01 -1.17728762e-01 4.09226567e-01 -1.29286337e+00
-3.77521843e-01 -1.05579190e-01 -3.09879184e-01 -9.48260367e-01
1.70566022e-01 -9.60935175e-01 3.30910712e-01 -1.01663041e+00
2.14513671e-02 -4.95028079e-01 -1.02182436e+00 6.34354353e-01
-3.84337515e-01 4.47858840e-01 1.71292067e-01 -1.55670494e-02
-1.10819340e+00 7.65177727e-01 6.69619024e-01 2.22891569e-02
-1.84220865e-01 4.12046999e-01 -2.34185189e-01 7.89845109e-01
5.08719325e-01 -8.46845090e-01 -2.84670383e-01 -3.27255428e-01
-5.77467941e-02 3.03371754e-02 4.71144855e-01 -1.23507905e+00
2.10178316e-01 2.62075901e-01 1.63825542e-01 -7.79682040e-01
4.98551577e-01 -5.76329291e-01 -1.49810389e-01 3.00174385e-01
-7.01308250e-01 -4.63656425e-01 2.41976246e-01 7.04519212e-01
-6.03553653e-01 -1.26601189e-01 8.50348413e-01 3.73463720e-01
-5.35431564e-01 2.54304111e-01 -2.88397819e-01 3.27205509e-01
8.37332487e-01 4.06898081e-01 1.21353172e-01 -3.00349206e-01
-1.03955376e+00 3.09705079e-01 -5.42675793e-01 4.86309409e-01
3.15298587e-01 -1.48693073e+00 -9.05114532e-01 5.30402921e-03
2.00461164e-01 -4.00787219e-02 4.74707633e-01 8.86491358e-01
1.94171235e-01 2.21117437e-01 3.45712721e-01 -8.07818115e-01
-1.17207241e+00 -3.36426124e-02 1.48572743e-01 -5.08364797e-01
-4.17092413e-01 1.31541955e+00 2.78111994e-01 -1.88647121e-01
8.49847138e-01 -3.89023900e-01 -3.25173050e-01 1.81725875e-01
5.48421800e-01 4.54191476e-01 4.04891670e-01 -5.46061695e-01
-5.31170726e-01 3.17320287e-01 -5.53405397e-02 -2.67822444e-01
1.52438235e+00 -5.73008545e-02 5.17121911e-01 5.13476312e-01
1.16245639e+00 1.56638786e-01 -1.34361923e+00 -4.00943220e-01
6.29237071e-02 8.02183896e-02 4.06259120e-01 -1.02431035e+00
-9.15766239e-01 1.22116470e+00 1.14295709e+00 2.15025470e-01
1.41028857e+00 1.83291793e-01 1.16706681e+00 5.06801568e-02
-9.74572152e-02 -1.15253353e+00 2.96739131e-01 5.73847830e-01
6.80430114e-01 -1.01938176e+00 -5.49814284e-01 -2.78855294e-01
-6.13030314e-01 7.82842875e-01 5.04193485e-01 2.08542161e-02
7.95268595e-01 5.19363642e-01 -8.90498832e-02 3.07364091e-02
-8.73139560e-01 -2.95949727e-01 7.75056958e-01 3.00127804e-01
3.91763836e-01 -2.58436594e-02 -7.37195387e-02 1.29801667e+00
-8.56973976e-02 -2.76077271e-01 -1.41368166e-01 7.01867223e-01
-5.45990169e-01 -1.04406178e+00 -5.15452251e-02 2.55392045e-01
-9.69616354e-01 -9.18172076e-02 -2.48003602e-02 2.53766418e-01
4.13159877e-01 9.58293080e-01 -1.15791582e-01 -5.41831315e-01
4.73569721e-01 4.31303769e-01 9.74685103e-02 -7.03086197e-01
-9.45625544e-01 6.21171713e-01 1.77711353e-01 -5.06309807e-01
-4.20285732e-01 -6.11024380e-01 -1.38430560e+00 5.78517735e-01
-4.96336699e-01 3.71373951e-01 5.85098922e-01 9.26383674e-01
4.04168814e-01 9.22006130e-01 8.34544718e-01 -7.20343053e-01
-5.12470245e-01 -1.01222479e+00 -4.11075354e-01 3.31015617e-01
4.09086406e-01 -6.24513924e-01 -3.66400927e-01 2.31614113e-01] | [15.203570365905762, 5.1490278244018555] |
dbcf8274-039d-4cc1-a94f-f85510fe4f29 | chan-vese-attention-u-net-an-attention | 2306.16098 | null | https://arxiv.org/abs/2306.16098v1 | https://arxiv.org/pdf/2306.16098v1.pdf | Chan-Vese Attention U-Net: An attention mechanism for robust segmentation | When studying the results of a segmentation algorithm using convolutional neural networks, one wonders about the reliability and consistency of the results. This leads to questioning the possibility of using such an algorithm in applications where there is little room for doubt. We propose in this paper a new attention gate based on the use of Chan-Vese energy minimization to control more precisely the segmentation masks given by a standard CNN architecture such as the U-Net model. This mechanism allows to obtain a constraint on the segmentation based on the resolution of a PDE. The study of the results allows us to observe the spatial information retained by the neural network on the region of interest and obtains competitive results on the binary segmentation. We illustrate the efficiency of this approach for medical image segmentation on a database of MRI brain images. | ['Laurent D. Cohen', 'Nicolas Makaroff'] | 2023-06-28 | null | null | null | null | ['medical-image-segmentation'] | ['medical'] | [ 4.28425461e-01 4.63350624e-01 1.62190303e-01 -3.19882065e-01
-2.95922663e-02 -3.07219148e-01 5.38930953e-01 3.48554850e-01
-9.25462961e-01 8.14359903e-01 -3.87653440e-01 -3.00000191e-01
-2.71497548e-01 -8.78674865e-01 -6.44058049e-01 -8.90452027e-01
-3.36434413e-03 4.00582880e-01 4.85468984e-01 -3.04336488e-01
3.40128690e-01 9.84683633e-01 -1.11680126e+00 1.39337420e-01
7.31061220e-01 9.15461004e-01 3.29135001e-01 5.48546672e-01
-1.92037657e-01 4.09206688e-01 -5.02819061e-01 -8.01586434e-02
1.77392960e-01 -5.05465627e-01 -1.07960820e+00 2.26982206e-01
3.33317765e-03 5.25731668e-02 7.69277290e-02 1.33671188e+00
1.31830961e-01 2.13603497e-01 7.41453290e-01 -5.45024216e-01
-1.39339983e-01 3.16835225e-01 -2.29687020e-01 6.19360507e-01
-1.59540445e-01 -6.70061857e-02 6.76780879e-01 -3.11970085e-01
9.25100863e-01 7.76471376e-01 5.99184573e-01 2.91014075e-01
-1.47445095e+00 1.15991160e-01 -1.36756018e-01 2.86135916e-02
-1.37719727e+00 -2.27651626e-01 6.06505990e-01 -4.82721746e-01
5.25873721e-01 4.05922472e-01 7.23667324e-01 3.56637299e-01
5.87635279e-01 3.13759536e-01 1.20974755e+00 -6.95154250e-01
4.56521958e-01 1.76496089e-01 3.25615525e-01 6.69760108e-01
3.09581190e-01 1.89485978e-02 1.76563814e-01 1.60249755e-01
1.15078413e+00 -1.96945891e-01 -4.42020088e-01 -4.28381920e-01
-7.52842188e-01 9.08714890e-01 7.83625543e-01 1.10152543e+00
-3.35974485e-01 2.59539969e-02 2.71531433e-01 -3.28086168e-02
5.72504699e-01 5.19172013e-01 -2.94074446e-01 4.39946145e-01
-1.14009595e+00 6.76657036e-02 6.45195723e-01 2.59841353e-01
7.10059941e-01 -9.26192701e-02 4.17485572e-02 4.47172135e-01
1.78595915e-01 -1.52632266e-01 3.25391084e-01 -9.56331789e-01
-2.32356161e-01 5.87199748e-01 -7.63868466e-02 -8.68738711e-01
-6.03012681e-01 -4.10847038e-01 -9.23837602e-01 7.20954716e-01
7.18705297e-01 -2.52142012e-01 -1.07071447e+00 1.52772856e+00
2.54616678e-01 -5.03644682e-02 -1.10625692e-01 9.79064763e-01
3.54892254e-01 3.81496727e-01 -1.80046633e-01 -3.87608886e-01
1.04231572e+00 -5.18401980e-01 -7.23026395e-01 2.55930394e-01
5.32103837e-01 -3.78621936e-01 6.09470606e-01 5.22225380e-01
-1.09192050e+00 -4.59263176e-01 -1.03624773e+00 7.46752247e-02
-3.45565468e-01 -1.02427252e-01 4.59670454e-01 7.15817332e-01
-1.11085975e+00 1.20079315e+00 -1.17686188e+00 -3.87109637e-01
4.61925596e-01 7.67759323e-01 -1.92178816e-01 3.06113541e-01
-8.78083050e-01 9.87167656e-01 4.99436677e-01 5.16916513e-01
-2.65337914e-01 -3.75780433e-01 -5.87466598e-01 2.67763019e-01
1.20517343e-01 -3.99730086e-01 8.19913864e-01 -1.33690834e+00
-1.31392586e+00 1.02616036e+00 1.56740308e-01 -6.01936042e-01
9.91760612e-01 3.88129860e-01 -9.67245828e-03 3.86261106e-01
-9.19293612e-02 7.08412349e-01 5.90865135e-01 -1.13938057e+00
-3.19117874e-01 -3.52865309e-01 7.23843277e-02 -2.94421971e-01
2.97056198e-01 -1.06806308e-01 -1.07374616e-01 -5.11009932e-01
2.71472305e-01 -8.30945551e-01 -7.90543854e-01 -1.06922030e-01
-2.98082292e-01 -6.92168102e-02 5.68492889e-01 -5.39758205e-01
8.36163282e-01 -2.12437534e+00 2.24139512e-01 5.87687552e-01
1.29649952e-01 2.37495109e-01 3.84926766e-01 3.77031006e-02
-4.32113349e-01 2.15618044e-01 -7.97698081e-01 2.09292490e-02
-4.78421658e-01 3.63759249e-01 1.08494386e-01 8.13165963e-01
7.93741420e-02 8.04376900e-01 -2.86333442e-01 -6.03060484e-01
2.42501974e-01 6.51945889e-01 -5.93982100e-01 1.02782555e-01
-1.57078132e-01 6.66372180e-01 -6.05810642e-01 -1.00734457e-02
5.97807944e-01 -1.84929267e-01 1.89826488e-01 -1.34957224e-01
-4.93899763e-01 -1.26990303e-01 -1.17371547e+00 1.57927251e+00
-1.14656081e-02 6.84103787e-01 2.92421222e-01 -1.37752962e+00
7.30078220e-01 2.68800139e-01 5.99948466e-01 -6.05627716e-01
7.01986372e-01 2.85189956e-01 3.02163899e-01 -4.00838792e-01
1.36113897e-01 -4.93477941e-01 2.53983945e-01 1.44572854e-01
2.07963195e-02 -1.52113572e-01 2.18527704e-01 -1.61420971e-01
7.82898664e-01 -3.16780955e-02 4.31045890e-02 -1.03394747e+00
5.49950421e-01 1.99492872e-01 9.54756588e-02 6.54515326e-01
2.78513636e-02 7.85381198e-01 7.44268656e-01 -5.61302900e-01
-1.01802289e+00 -6.30694866e-01 -6.88128531e-01 2.37379923e-01
1.92196015e-02 2.45311007e-01 -1.30571210e+00 -4.14431512e-01
-3.45555544e-01 3.77660811e-01 -1.06379414e+00 1.18437052e-01
-7.76817441e-01 -1.03605878e+00 1.74662456e-01 1.75629169e-01
4.51792747e-01 -1.39753532e+00 -1.12177968e+00 3.50888848e-01
2.51417477e-02 -9.15279150e-01 4.44062464e-02 6.95808530e-01
-1.29671085e+00 -1.10925221e+00 -8.33489537e-01 -6.39953136e-01
8.44091117e-01 -4.98705953e-01 7.39590883e-01 3.75484496e-01
-3.35446358e-01 2.31823519e-01 -5.64856119e-02 -6.32690042e-02
-6.71246886e-01 4.06233162e-01 -4.48329389e-01 -3.12135909e-02
-1.98185667e-01 -5.29063284e-01 -4.68252838e-01 -1.04001006e-02
-1.24113500e+00 -1.93057284e-01 2.92047441e-01 5.67620575e-01
4.81373370e-01 1.13457873e-01 2.12339789e-01 -9.87050474e-01
4.72467542e-01 -5.92625476e-02 -9.20339048e-01 4.00769152e-02
-6.92847252e-01 3.17517728e-01 4.85095918e-01 -2.66838908e-01
-8.20236981e-01 3.93486768e-01 -4.84660953e-01 -1.46449000e-01
-2.59376705e-01 3.80954206e-01 4.21409532e-02 -4.71340507e-01
4.94066566e-01 -2.48067342e-02 1.03852019e-01 -4.49066460e-01
5.91795668e-02 2.26278767e-01 5.14415264e-01 -2.97661990e-01
1.91768304e-01 6.68188870e-01 2.20439672e-01 -1.02998197e+00
-3.42409253e-01 -1.90431044e-01 -8.29537570e-01 -3.03376973e-01
1.35071647e+00 -1.30877569e-02 -8.62734258e-01 3.48398238e-01
-1.26852083e+00 -4.34635997e-01 -5.80148458e-01 3.14741403e-01
-7.94834793e-01 3.05408567e-01 -7.00713694e-01 -5.31655252e-01
1.14404503e-02 -1.50741673e+00 4.58692968e-01 2.23943293e-01
7.38748396e-03 -1.24418461e+00 5.89128584e-02 1.39345363e-01
3.37701112e-01 2.77023375e-01 1.06676757e+00 -5.81654906e-01
-6.18664145e-01 -7.03435391e-02 -1.48625061e-01 5.12171328e-01
-1.27730533e-01 -6.49398938e-02 -8.99635911e-01 5.50707914e-02
3.83900911e-01 1.85026258e-01 1.11568403e+00 8.57848167e-01
1.20444798e+00 5.73984943e-02 -1.73479989e-01 5.31475961e-01
1.87298989e+00 2.55296022e-01 9.01611924e-01 3.11025441e-01
4.80742931e-01 7.13512838e-01 4.19900641e-02 9.29517895e-02
-2.59903431e-01 6.97947025e-01 5.69452524e-01 -4.18245256e-01
5.81529103e-02 3.58825713e-01 -3.80745351e-01 3.36373240e-01
-3.47528189e-01 -1.09558143e-01 -8.17145407e-01 5.90907156e-01
-1.75499642e+00 -7.07175851e-01 -5.31011939e-01 2.03206897e+00
6.12763762e-01 4.10047024e-01 -8.52304325e-03 2.70892709e-01
7.96130896e-01 3.89547832e-02 -9.74549279e-02 -6.80067956e-01
9.84228626e-02 4.45211589e-01 6.61634207e-01 9.58386600e-01
-9.35515225e-01 5.59409440e-01 6.73183298e+00 8.08639348e-01
-1.42082381e+00 1.22558229e-01 9.84830260e-01 3.59182805e-01
8.57662875e-03 -7.32251182e-02 -3.66170228e-01 4.89430308e-01
6.94572568e-01 2.30429441e-01 2.04473689e-01 4.41084892e-01
2.83699960e-01 -7.41914570e-01 -8.64399970e-01 5.38589597e-01
-1.01399280e-01 -1.54759121e+00 -9.38781276e-02 2.07700685e-01
5.41629434e-01 -1.79738060e-01 -1.24709867e-01 -4.13100570e-01
-7.64324814e-02 -1.24680245e+00 6.19136453e-01 5.97881675e-01
3.91796470e-01 -6.88751340e-01 7.77789712e-01 3.30691069e-01
-5.60426116e-01 3.11716139e-01 -2.71957010e-01 -1.02476589e-01
2.02877626e-01 4.87768203e-01 -6.86863244e-01 2.69967467e-01
3.35733086e-01 -3.54503989e-02 -3.49885434e-01 1.13216305e+00
1.94799110e-01 4.46360320e-01 -5.29130697e-01 1.41709875e-02
5.73595047e-01 -5.43439627e-01 3.73987645e-01 1.28052509e+00
-2.77167577e-02 2.66173720e-01 -2.78602928e-01 1.14271104e+00
1.61434501e-01 2.77188152e-01 -3.93031299e-01 2.59242237e-01
-6.72066689e-01 1.21361923e+00 -1.63298213e+00 -2.00850680e-01
-1.12454206e-01 9.14449692e-01 2.22920910e-01 3.40639144e-01
-4.34726655e-01 -9.71889272e-02 7.98812583e-02 4.02402908e-01
5.10213256e-01 -2.65239567e-01 -6.96568608e-01 -8.53028893e-01
-2.97723096e-02 -2.76210159e-01 2.56187283e-02 -6.37471259e-01
-5.78395128e-01 7.53714383e-01 1.51469275e-01 -4.46010977e-01
-4.61967513e-02 -7.71669149e-01 -7.07784414e-01 9.20975089e-01
-1.32717264e+00 -4.86540973e-01 7.74937123e-02 5.00761032e-01
1.98174968e-01 2.08595663e-01 6.08627915e-01 2.26076871e-01
-2.55913854e-01 -1.84948832e-01 -5.54018319e-02 1.21761613e-01
-1.54205104e-02 -1.15830147e+00 -4.43045050e-02 7.97942460e-01
1.12220392e-01 3.14649701e-01 1.04496741e+00 -4.83864158e-01
-5.37992477e-01 -4.95609909e-01 9.01869178e-01 -3.27509910e-01
4.61489618e-01 -1.89978287e-01 -1.21076715e+00 4.75234509e-01
4.92338359e-01 1.87820092e-01 1.75321456e-02 -3.15340161e-01
5.53098559e-01 1.48998991e-01 -1.30582666e+00 1.70792639e-01
4.17023182e-01 -9.99119133e-02 -6.71088219e-01 7.70612136e-02
2.99629152e-01 -2.46821940e-01 -5.85868239e-01 3.79589021e-01
2.51611382e-01 -1.28538072e+00 6.79169476e-01 -5.05417764e-01
5.11558354e-01 4.85315621e-02 2.35973626e-01 -1.17771697e+00
-1.27083465e-01 -1.07593104e-01 7.39287853e-01 6.22219324e-01
4.28411931e-01 -4.70221907e-01 8.21396530e-01 6.96546555e-01
-1.62238013e-02 -8.23585033e-01 -1.21537042e+00 -2.99666673e-01
3.41063499e-01 -2.21949950e-01 -1.00750197e-02 9.12843347e-01
-3.47537220e-01 -1.01339750e-01 2.87015110e-01 4.14258949e-02
4.77438778e-01 -8.71541072e-03 -9.76133123e-02 -1.39648187e+00
-2.55792052e-01 -5.63110709e-01 -3.34575027e-01 -5.65029562e-01
1.84474394e-01 -7.41312027e-01 -5.27812168e-03 -1.43101954e+00
-1.01997137e-01 -4.52896208e-01 -2.66221553e-01 1.18551567e-01
2.64170587e-01 3.50981981e-01 1.43377334e-01 6.09533451e-02
-2.54945397e-01 6.14052303e-02 1.38168943e+00 2.25775205e-02
-2.43532151e-01 1.62184656e-01 -2.31853962e-01 8.72249186e-01
8.05096567e-01 -5.43053329e-01 -5.79752214e-02 -1.89391300e-01
1.23451136e-01 2.43174896e-01 6.02097690e-01 -8.55276287e-01
2.79807359e-01 1.60147250e-01 5.39074957e-01 -1.98690340e-01
3.55775580e-02 -1.08168018e+00 1.53795689e-01 7.17468917e-01
-4.11262363e-01 -6.21563382e-02 8.87518078e-02 6.42532622e-03
-2.63689220e-01 -9.00111794e-01 1.22078371e+00 -4.99572814e-01
-3.77384096e-01 2.39594355e-02 -5.53007603e-01 -2.03896001e-01
7.93988883e-01 -3.89855593e-01 2.82223403e-01 -5.46910614e-02
-1.42236876e+00 -3.02286029e-01 4.74865913e-01 -1.70663670e-01
2.74507493e-01 -9.01332974e-01 -2.73234755e-01 3.23170930e-01
-4.20736194e-01 -5.18322103e-02 1.59041569e-01 9.67308521e-01
-9.88644063e-01 3.72448236e-01 -4.33782637e-01 -5.17402172e-01
-1.14621961e+00 6.57121480e-01 1.05611968e+00 -3.21939528e-01
-7.40401804e-01 4.18175608e-01 1.35229319e-01 7.46009052e-02
-3.62875685e-02 -6.27803922e-01 -3.66306067e-01 -1.22071861e-03
7.26748481e-02 1.50024116e-01 3.13513070e-01 -6.07713640e-01
-3.06650341e-01 4.04545069e-01 2.01916873e-01 -3.49512517e-01
1.46611023e+00 -2.98448037e-02 -3.12732249e-01 2.71515906e-01
1.12680590e+00 -4.39745747e-02 -1.31879807e+00 2.95190066e-01
1.22645319e-01 -6.34906814e-02 4.53755260e-01 -6.73965633e-01
-1.23430061e+00 9.72706378e-01 8.18947732e-01 6.20512605e-01
9.57779706e-01 -6.20698072e-02 3.79431725e-01 1.42277688e-01
2.00629130e-01 -9.97845054e-01 -3.99582624e-01 2.82200396e-01
7.81163931e-01 -9.98069644e-01 -1.26902536e-01 -4.55673933e-01
-1.92105353e-01 1.30535984e+00 1.21504039e-01 -6.33809268e-01
8.10989678e-01 4.50902134e-01 -1.41815748e-02 -2.44502351e-01
-9.35684144e-02 -3.57251853e-01 2.02701762e-01 2.42383838e-01
3.99479151e-01 7.53223430e-03 -8.61757278e-01 2.44727314e-01
9.77660343e-02 1.95311978e-01 7.17835248e-01 7.53728926e-01
-5.81672370e-01 -1.20692873e+00 -3.17920148e-01 1.67827457e-01
-7.49612391e-01 2.68914513e-02 -3.48574251e-01 1.03631568e+00
3.84583235e-01 5.14069557e-01 6.41327500e-02 3.83390486e-01
2.54976332e-01 1.11123994e-01 8.35893095e-01 -4.14726824e-01
-8.38970721e-01 3.58922750e-01 -1.15122192e-01 -3.41219127e-01
-6.15729630e-01 -5.85828125e-01 -1.41407788e+00 -8.91457964e-03
-2.40318149e-01 3.88462245e-01 8.18194985e-01 1.14088726e+00
-2.80587167e-01 6.75642788e-01 2.48819038e-01 -8.67407382e-01
-1.93855733e-01 -6.17399752e-01 -8.47977042e-01 3.06483746e-01
4.24361795e-01 -4.77199316e-01 -1.98146701e-01 2.34639142e-02] | [14.416716575622559, -2.574636220932007] |
46323bb7-b298-4f03-9183-42bb25b83839 | the-starcraft-multi-agent-challenge | 1902.04043 | null | https://arxiv.org/abs/1902.04043v5 | https://arxiv.org/pdf/1902.04043v5.pdf | The StarCraft Multi-Agent Challenge | In the last few years, deep multi-agent reinforcement learning (RL) has become a highly active area of research. A particularly challenging class of problems in this area is partially observable, cooperative, multi-agent learning, in which teams of agents must learn to coordinate their behaviour while conditioning only on their private observations. This is an attractive research area since such problems are relevant to a large number of real-world systems and are also more amenable to evaluation than general-sum problems. Standardised environments such as the ALE and MuJoCo have allowed single-agent RL to move beyond toy domains, such as grid worlds. However, there is no comparable benchmark for cooperative multi-agent RL. As a result, most papers in this field use one-off toy problems, making it difficult to measure real progress. In this paper, we propose the StarCraft Multi-Agent Challenge (SMAC) as a benchmark problem to fill this gap. SMAC is based on the popular real-time strategy game StarCraft II and focuses on micromanagement challenges where each unit is controlled by an independent agent that must act based on local observations. We offer a diverse set of challenge maps and recommendations for best practices in benchmarking and evaluations. We also open-source a deep multi-agent RL learning framework including state-of-the-art algorithms. We believe that SMAC can provide a standard benchmark environment for years to come. Videos of our best agents for several SMAC scenarios are available at: https://youtu.be/VZ7zmQ_obZ0. | ['Chia-Man Hung', 'Tim G. J. Rudner', 'Gregory Farquhar', 'Shimon Whiteson', 'Nantas Nardelli', 'Jakob Foerster', 'Tabish Rashid', 'Philip H. S. Torr', 'Mikayel Samvelyan', 'Christian Schroeder de Witt'] | 2019-02-11 | null | null | null | null | ['smac-1', 'real-time-strategy-games', 'smac'] | ['playing-games', 'playing-games', 'playing-games'] | [-4.97886240e-01 -1.17511123e-01 -2.27309048e-01 4.57483195e-02
-9.07070875e-01 -6.54845297e-01 9.72789824e-01 1.56298652e-01
-8.70118737e-01 1.29281962e+00 -1.44964522e-02 -1.72030181e-01
-3.14357460e-01 -6.47413194e-01 -6.84097946e-01 -9.32540298e-01
-7.39623904e-01 1.12708092e+00 2.99457639e-01 -7.59315312e-01
-1.11245595e-01 1.67722061e-01 -1.37702966e+00 1.80797920e-01
4.51067835e-01 5.18209934e-01 1.36236414e-01 9.51602101e-01
6.77537382e-01 1.11633861e+00 -8.93886089e-01 -1.59872428e-01
4.72387403e-01 -4.67371732e-01 -8.48347783e-01 -9.89874080e-02
-1.96222022e-01 -3.78146619e-01 -1.48397118e-01 7.42810547e-01
9.77741957e-01 3.36470395e-01 3.16248298e-01 -1.86649346e+00
-4.39296290e-02 6.69644177e-01 -6.40034616e-01 2.13467497e-02
3.71547908e-01 6.97016120e-01 1.31474817e+00 1.13862352e-02
6.11947298e-01 1.34698856e+00 2.48246133e-01 5.67569971e-01
-1.00913751e+00 -6.42828524e-01 2.69119591e-01 4.19376194e-01
-9.50468838e-01 -7.28335157e-02 3.57002884e-01 4.31428105e-02
1.18780994e+00 2.24386498e-01 7.01849580e-01 1.41843987e+00
4.01927233e-01 1.15545022e+00 1.46037221e+00 -2.99403101e-01
7.02424824e-01 -2.99799025e-01 -5.57112575e-01 8.13730478e-01
1.25169724e-01 5.17105401e-01 -3.73386353e-01 -4.16744828e-01
7.69170403e-01 -1.04752310e-01 8.93269256e-02 -6.19484663e-01
-1.44969940e+00 1.21865964e+00 3.13017607e-01 1.40245155e-01
-5.27275980e-01 6.80344880e-01 4.67161059e-01 8.27902138e-01
2.76186854e-01 7.29714930e-01 -5.04189193e-01 -4.16554481e-01
-2.82932997e-01 9.93759036e-01 1.14363372e+00 5.51485777e-01
6.26304030e-01 6.87814355e-02 2.47501880e-01 5.63472390e-01
4.04162467e-01 3.66883010e-01 3.43253434e-01 -1.64785552e+00
3.77424359e-01 2.21839994e-01 3.32661748e-01 -4.83254254e-01
-6.65199399e-01 -2.86691874e-01 -6.68950260e-01 1.12054873e+00
4.15234923e-01 -8.14535439e-01 -3.42632681e-01 1.68410468e+00
4.88369823e-01 4.13167179e-01 5.50883532e-01 1.01145673e+00
5.58863878e-01 6.71016216e-01 -2.14541838e-01 -1.32847339e-01
1.07292163e+00 -1.36968017e+00 -3.07921112e-01 -3.17253649e-01
7.32379436e-01 -4.75085855e-01 7.14897275e-01 5.06607234e-01
-1.22786903e+00 1.35493455e-02 -9.82665837e-01 5.99194527e-01
-3.15684050e-01 -5.60043931e-01 9.56767797e-01 2.81685889e-01
-1.34976637e+00 5.36750913e-01 -1.22480452e+00 -3.94185066e-01
1.76322475e-01 5.99815905e-01 -3.18321794e-01 -2.09317170e-02
-1.29357958e+00 1.16696584e+00 2.28184342e-01 -3.68989915e-01
-1.76818752e+00 -2.46079832e-01 -6.42972827e-01 -1.26131341e-01
9.26364899e-01 -5.89716375e-01 1.84783208e+00 -8.56223702e-01
-1.87172902e+00 5.25011003e-01 5.51989019e-01 -7.84887850e-01
7.02468574e-01 1.15339002e-02 -1.83816016e-01 -5.43087907e-02
1.89015806e-01 6.23020113e-01 5.36918581e-01 -1.35794818e+00
-1.16956425e+00 -3.36126164e-02 8.13500941e-01 7.69593656e-01
2.33415186e-01 1.59156844e-01 2.97708325e-02 -1.83104947e-01
-8.30155373e-01 -1.18620801e+00 -6.79928303e-01 -5.74868619e-01
1.18154116e-01 -4.77218151e-01 7.27126241e-01 1.56579420e-01
4.93903488e-01 -1.74624801e+00 4.58981693e-01 -2.42801085e-01
3.45516771e-01 6.96399882e-02 -5.59194803e-01 9.47281957e-01
3.79973739e-01 5.56456670e-02 1.69599310e-01 -5.83047211e-01
5.00155449e-01 4.94702458e-01 3.44145373e-02 6.83956265e-01
-9.13344547e-02 9.02208805e-01 -1.24172974e+00 -2.64580339e-01
1.56516328e-01 -5.71339428e-02 -5.56448400e-01 2.92130947e-01
-8.42694640e-01 5.12114823e-01 -5.50715327e-01 4.59647715e-01
1.78065971e-01 -2.33919591e-01 3.75326395e-01 6.80325270e-01
-1.97484031e-01 -1.12901077e-01 -1.41394281e+00 1.65167773e+00
-4.00737911e-01 4.28136677e-01 4.28514391e-01 -9.94010031e-01
4.91211265e-01 5.92373669e-01 8.02520931e-01 -7.16010869e-01
1.27609968e-01 2.46561587e-01 4.67659801e-01 -1.77212968e-01
3.83545935e-01 4.23094817e-02 -4.56971765e-01 9.07725513e-01
1.52774647e-01 -5.23298919e-01 6.34289563e-01 2.15380207e-01
1.67928135e+00 5.41807339e-02 5.09851158e-01 -7.95733482e-02
1.53342575e-01 2.05572501e-01 5.62486947e-01 1.18174911e+00
-4.90434766e-01 1.58993840e-01 6.07565522e-01 -6.92997277e-01
-7.75371313e-01 -9.25822914e-01 6.14257336e-01 1.30506921e+00
1.89941138e-01 -5.28255641e-01 -5.11955738e-01 -6.93101823e-01
-7.24974833e-03 4.43116575e-01 -6.02625847e-01 2.01266378e-01
-6.55199528e-01 -8.91675472e-01 4.56611216e-01 4.10597026e-02
5.85738301e-01 -1.66754222e+00 -9.90333438e-01 4.14525062e-01
6.03095591e-02 -9.26777363e-01 -8.29716772e-02 1.90911010e-01
-2.32968003e-01 -1.30869377e+00 -6.89794481e-01 -5.90212524e-01
8.04898702e-03 2.23123640e-01 1.38047361e+00 2.33062983e-01
-7.13566020e-02 8.03696334e-01 -6.31009221e-01 -5.79956710e-01
-6.34788513e-01 3.22605729e-01 3.12154531e-01 -2.11446345e-01
-1.10942610e-01 -4.88164455e-01 -5.53154588e-01 4.49525744e-01
-7.43853390e-01 -4.59520295e-02 5.77589691e-01 8.76028776e-01
1.97581038e-01 1.85616314e-01 6.06594086e-01 -5.53184211e-01
1.01420724e+00 -7.45586514e-01 -9.90761995e-01 7.43785501e-02
-2.06028342e-01 -1.61888093e-01 7.38662720e-01 -3.62030953e-01
-6.44877791e-01 -2.02522904e-01 1.38209864e-01 -1.26128644e-01
-2.88986892e-01 5.12389660e-01 2.65528738e-01 -1.10622667e-01
6.11985624e-01 6.90185875e-02 2.46047020e-01 6.29763231e-02
2.12996662e-01 3.81776571e-01 4.29105945e-02 -8.40632975e-01
6.11957550e-01 3.97072077e-01 8.06720778e-02 -5.86580336e-01
-3.59994799e-01 -2.29389980e-01 2.41629109e-02 -3.27049017e-01
7.53820479e-01 -1.15532887e+00 -1.46241915e+00 5.16375184e-01
-1.01409173e+00 -1.24889040e+00 -2.48361126e-01 5.23842573e-01
-1.00898468e+00 5.58416843e-02 -7.00576842e-01 -7.23237216e-01
-6.51727617e-03 -1.49732006e+00 8.79761338e-01 4.04698223e-01
1.54383346e-01 -1.31609690e+00 8.08796167e-01 2.72923082e-01
5.24812818e-01 4.16431308e-01 2.08792016e-01 -7.49383628e-01
-7.53989458e-01 1.18606232e-01 3.99487853e-01 -3.12269013e-02
-4.48603556e-02 -1.71311453e-01 -5.91283202e-01 -9.97882783e-01
-3.38425517e-01 -1.12108350e+00 5.60247004e-01 3.45786899e-01
4.97630656e-01 -1.02665454e-01 -1.41907141e-01 3.16264182e-01
1.34899044e+00 2.66353577e-01 2.75962949e-01 8.41153920e-01
2.92095423e-01 2.09138453e-01 8.11203122e-01 7.46877909e-01
8.71255577e-01 8.10343802e-01 1.06126070e+00 -1.36956170e-01
3.15354019e-01 2.00740114e-01 7.52617538e-01 4.64269400e-01
-5.15809238e-01 -5.84958076e-01 -1.00668776e+00 2.86646396e-01
-2.37406564e+00 -1.10721242e+00 2.95085847e-01 1.87455356e+00
7.08905995e-01 1.10541157e-01 4.68255877e-01 -3.07599872e-01
3.26107949e-01 4.11402911e-01 -6.31439805e-01 -3.09690267e-01
-2.75976658e-01 2.31156975e-01 4.69277054e-01 7.31803477e-01
-1.16549587e+00 1.13956344e+00 5.37378311e+00 8.71271312e-01
-8.17849874e-01 4.56266016e-01 4.68258202e-01 -4.47243929e-01
3.26619476e-01 2.23872787e-03 -6.67238295e-01 3.32156330e-01
1.01961684e+00 -2.63554811e-01 9.82649148e-01 7.27124810e-01
3.77344251e-01 -5.58243513e-01 -1.03289723e+00 7.77597606e-01
-1.14912994e-01 -1.52234042e+00 -5.89080513e-01 4.33401346e-01
1.12445366e+00 8.77764821e-01 -2.53484175e-02 8.30279648e-01
1.64931393e+00 -1.14366281e+00 4.71001059e-01 2.57724244e-02
3.41490239e-01 -8.80263209e-01 8.68727028e-01 5.66460073e-01
-1.06275070e+00 -3.37147325e-01 -3.33149225e-01 -5.60194552e-01
1.54505908e-01 -2.68408179e-01 -7.61386871e-01 6.23925567e-01
7.89959669e-01 6.18715584e-01 -2.25915506e-01 1.11195552e+00
-3.02062809e-01 3.60843897e-01 -3.52924556e-01 -4.84830320e-01
8.55132401e-01 -2.30852589e-01 4.63749826e-01 6.91655874e-01
6.65598363e-02 8.08208361e-02 8.34153831e-01 3.12080443e-01
-1.00596532e-01 -1.34218588e-01 -6.40180409e-01 1.65387079e-01
4.38109189e-01 1.46944869e+00 -6.49349570e-01 -1.77954853e-01
-5.64919293e-01 8.16909313e-01 6.96519494e-01 3.03463966e-01
-9.55247581e-01 1.60217345e-01 1.03120840e+00 -5.08891046e-01
1.97631568e-01 -3.70037347e-01 5.31218231e-01 -1.10873127e+00
-4.33992386e-01 -1.55840302e+00 5.24288833e-01 -3.74113649e-01
-1.17007136e+00 6.01120412e-01 -1.31820261e-01 -1.09186482e+00
-6.78165257e-01 -4.69512850e-01 -7.28710175e-01 2.97031701e-01
-1.57158649e+00 -1.01395810e+00 -3.01726907e-02 6.95868671e-01
6.57899320e-01 -7.22099423e-01 1.13514340e+00 -4.75509278e-02
-6.13708913e-01 1.92642674e-01 5.14150739e-01 -1.14702247e-01
7.13426173e-01 -1.54465044e+00 4.26318198e-01 3.33868355e-01
2.73590684e-01 -2.58402675e-01 7.53707051e-01 -3.69224310e-01
-1.59348297e+00 -8.26169789e-01 -1.03798822e-01 -5.41911006e-01
1.08873188e+00 -4.97488827e-01 -2.51287788e-01 7.91786253e-01
7.67275095e-01 2.11968973e-01 3.21029425e-01 1.39125884e-01
1.18863158e-01 -2.80472133e-02 -7.66027689e-01 8.09164643e-01
6.87570512e-01 4.87734680e-04 -1.57752201e-01 6.61423564e-01
5.64953744e-01 -6.07509375e-01 -7.57792413e-01 7.15904012e-02
1.50885329e-01 -1.19618547e+00 7.41374910e-01 -7.08137751e-01
3.16426396e-01 -2.57718503e-01 -1.58636823e-01 -2.11886930e+00
-1.97344378e-01 -1.06944895e+00 -1.33788675e-01 7.34050870e-01
4.69495535e-01 -8.53019297e-01 9.37376976e-01 7.57738873e-02
4.16725352e-02 -7.34636724e-01 -1.05943263e+00 -9.28079069e-01
3.92474234e-01 -4.51715514e-02 4.52574909e-01 8.41958284e-01
1.20254926e-01 3.86123717e-01 -6.65014863e-01 1.88707754e-01
7.41894782e-01 6.88592419e-02 1.19930291e+00 -8.85327697e-01
-9.76362884e-01 -4.67860967e-01 -1.51170552e-01 -6.82465196e-01
3.80417317e-01 -6.73138678e-01 -3.02489591e-03 -1.49682593e+00
5.26485816e-02 -5.16039789e-01 -1.95651293e-01 5.31372488e-01
1.07029870e-01 6.12309836e-02 6.81616604e-01 1.44886911e-01
-1.53245437e+00 6.69428110e-01 1.21820140e+00 -1.92893773e-01
-1.42732427e-01 2.62892246e-01 -3.04583430e-01 6.26444101e-01
1.38033438e+00 -3.71406943e-01 -3.48865151e-01 -5.41672707e-01
1.98343575e-01 4.09402966e-01 4.00389224e-01 -1.03095734e+00
4.75006789e-01 -6.62904978e-01 -2.72928923e-01 1.04460515e-01
6.46011174e-01 -5.56124985e-01 -1.58281811e-02 7.75356591e-01
-2.19727710e-01 5.58742225e-01 -3.23624834e-02 3.66743743e-01
-2.21544713e-01 -1.54900417e-01 5.96962035e-01 -6.63102090e-01
-8.75714600e-01 3.35338652e-01 -6.21542096e-01 4.71529990e-01
1.54094946e+00 4.33388770e-01 -6.57730758e-01 -8.75333011e-01
-4.74708736e-01 1.02223003e+00 4.81253654e-01 1.98915571e-01
3.81560087e-01 -9.48478580e-01 -1.24407852e+00 -1.95995077e-01
-1.54572874e-01 8.90590902e-03 1.50921538e-01 6.30684495e-01
-5.17162323e-01 1.10469095e-01 -4.90019411e-01 -3.27099085e-01
-1.26785350e+00 3.34122270e-01 6.74162686e-01 -8.71677637e-01
-4.55955446e-01 5.37604332e-01 -5.56930639e-02 -7.28189290e-01
3.38893712e-01 -1.10732485e-02 -6.83531165e-02 -2.27991283e-01
5.20296872e-01 3.58408213e-01 -3.02163213e-01 -3.13311309e-01
-2.18509644e-01 9.88816656e-03 -1.27210140e-01 -4.40265089e-01
1.72020137e+00 1.21429920e-01 9.08034444e-02 3.21475327e-01
6.32053494e-01 -2.99388319e-01 -1.64875495e+00 -1.44589737e-01
-4.19459119e-02 -1.29255736e-02 -1.38460338e-01 -1.01498008e+00
-9.94333923e-01 4.13840622e-01 2.97887444e-01 5.76883852e-01
7.12172806e-01 1.32186413e-01 2.41616800e-01 6.99117541e-01
9.30477679e-01 -1.27220678e+00 4.28886324e-01 8.91560495e-01
1.04987431e+00 -1.68124831e+00 3.76153141e-02 3.31112951e-01
-9.74827409e-01 7.66293287e-01 8.21421683e-01 -5.25394857e-01
2.33265549e-01 5.44633985e-01 2.06523493e-01 -3.38251412e-01
-1.54353344e+00 -5.32627523e-01 -5.61989844e-01 7.27868021e-01
-1.37465656e-01 3.23655844e-01 1.31745130e-01 1.00046046e-01
-1.60313979e-01 -2.29486525e-01 9.49114799e-01 1.10870588e+00
-3.84705544e-01 -1.40093291e+00 -4.31006849e-01 1.95180967e-01
-3.37719709e-01 2.63686091e-01 -2.88675696e-01 1.17800677e+00
-6.87862262e-02 1.12930512e+00 -1.01544335e-01 -9.73233134e-02
2.05953136e-01 -6.06655002e-01 5.39155662e-01 -5.90129673e-01
-7.79254556e-01 -2.47915611e-02 2.67767131e-01 -8.04737329e-01
-5.69810212e-01 -7.79956877e-01 -1.22000194e+00 -6.44090414e-01
1.55298293e-01 4.09039944e-01 4.99294460e-01 8.56539190e-01
1.22833759e-01 5.05715013e-01 6.83354616e-01 -1.34946227e+00
-8.74894023e-01 -8.24350774e-01 -6.35683417e-01 1.18927255e-01
4.35627013e-01 -8.30400586e-01 -3.08330476e-01 -7.43987381e-01] | [3.7609143257141113, 1.888580560684204] |
96aea135-97f5-43df-8aaf-57c09bdb3bfd | ddgk-learning-graph-representations-for-deep | 1904.09671 | null | http://arxiv.org/abs/1904.09671v1 | http://arxiv.org/pdf/1904.09671v1.pdf | DDGK: Learning Graph Representations for Deep Divergence Graph Kernels | Can neural networks learn to compare graphs without feature engineering? In
this paper, we show that it is possible to learn representations for graph
similarity with neither domain knowledge nor supervision (i.e.\ feature
engineering or labeled graphs). We propose Deep Divergence Graph Kernels, an
unsupervised method for learning representations over graphs that encodes a
relaxed notion of graph isomorphism. Our method consists of three parts. First,
we learn an encoder for each anchor graph to capture its structure. Second, for
each pair of graphs, we train a cross-graph attention network which uses the
node representations of an anchor graph to reconstruct another graph. This
approach, which we call isomorphism attention, captures how well the
representations of one graph can encode another. We use the attention-augmented
encoder's predictions to define a divergence score for each pair of graphs.
Finally, we construct an embedding space for all graphs using these pair-wise
divergence scores.
Unlike previous work, much of which relies on 1) supervision, 2) domain
specific knowledge (e.g. a reliance on Weisfeiler-Lehman kernels), and 3) known
node alignment, our unsupervised method jointly learns node representations,
graph representations, and an attention-based alignment between graphs.
Our experimental results show that Deep Divergence Graph Kernels can learn an
unsupervised alignment between graphs, and that the learned representations
achieve competitive results when used as features on a number of challenging
graph classification tasks. Furthermore, we illustrate how the learned
attention allows insight into the the alignment of sub-structures across
graphs. | ['Rami Al-Rfou', 'Bryan Perozzi', 'Dustin Zelle'] | 2019-04-21 | null | null | null | null | ['graph-similarity'] | ['graphs'] | [ 1.36181101e-01 6.63042307e-01 -3.14644665e-01 -5.30198812e-01
-3.72777551e-01 -6.22442484e-01 5.94611287e-01 5.78658164e-01
1.24706894e-01 3.03410023e-01 2.93223202e-01 -3.51065129e-01
-1.79375872e-01 -1.10819256e+00 -8.87135148e-01 -4.26933140e-01
-3.45889211e-01 4.32193488e-01 3.95850837e-02 -1.97487772e-01
3.69472522e-03 4.46768820e-01 -1.03088188e+00 4.81680967e-03
9.28614020e-01 7.39959717e-01 6.45845234e-02 7.48554766e-01
-1.40045106e-01 7.37348795e-01 -1.86332732e-01 -5.70704639e-01
2.59865105e-01 -6.37800813e-01 -1.14556623e+00 2.03578770e-01
5.72837353e-01 -9.30402577e-02 -7.40407228e-01 1.16242206e+00
-6.83626756e-02 8.80457684e-02 1.00171542e+00 -1.48070610e+00
-1.37552917e+00 6.38999581e-01 -4.16518986e-01 1.40540302e-01
3.04929346e-01 -8.50624032e-03 1.62494481e+00 -4.82549965e-01
5.23970306e-01 1.01092505e+00 9.13272619e-01 2.97583342e-01
-1.62658787e+00 -2.06945837e-01 1.37837380e-01 -5.49338460e-02
-1.22481024e+00 -1.27670541e-01 9.88904953e-01 -7.13816047e-01
9.71805573e-01 -5.22691198e-02 7.20434129e-01 8.33200276e-01
1.64274007e-01 4.46699947e-01 5.92171431e-01 -4.28937316e-01
6.94869682e-02 -1.16754793e-01 4.49853390e-01 1.18939531e+00
3.96231294e-01 9.85633656e-02 2.03277003e-02 -2.37435341e-01
8.24898422e-01 2.76845574e-01 -2.71483421e-01 -8.14801574e-01
-9.84382093e-01 1.11599278e+00 1.15640545e+00 4.28444654e-01
-1.48229524e-01 5.40041089e-01 3.80846798e-01 5.39900362e-01
4.11560059e-01 6.35860860e-01 -2.92041749e-01 4.66513753e-01
-2.63918072e-01 -2.23486781e-01 8.21876049e-01 1.01164389e+00
1.32395792e+00 1.03793889e-01 8.29745755e-02 5.69067240e-01
3.50178957e-01 1.07227534e-01 2.17278346e-01 -5.71529210e-01
3.22049707e-01 7.82660365e-01 -4.17394161e-01 -1.32716894e+00
-2.83824384e-01 -2.33149007e-01 -7.93138623e-01 -9.63456780e-02
3.02026898e-01 1.09249666e-01 -1.06263578e+00 2.12538934e+00
-6.07683398e-02 4.90684152e-01 1.24609582e-01 5.79572856e-01
8.00610065e-01 2.57555604e-01 -1.35339573e-01 2.46843249e-01
1.03222787e+00 -9.76646781e-01 -3.03417653e-01 -3.77031624e-01
1.02494943e+00 -2.26645276e-01 1.01840997e+00 -3.71692091e-01
-9.26939011e-01 -4.07237232e-01 -1.09149754e+00 -1.85667485e-01
-5.18028736e-01 -2.89162815e-01 9.22975242e-01 4.04923052e-01
-1.49150968e+00 9.96159673e-01 -8.72342169e-01 -8.30091715e-01
3.48388582e-01 3.58560115e-01 -6.89476788e-01 -1.24589033e-01
-1.02265656e+00 7.07475245e-01 3.44925314e-01 -2.35208601e-01
-7.71929801e-01 -5.45806766e-01 -1.42556024e+00 4.06651407e-01
2.24827439e-01 -7.98015296e-01 7.43250549e-01 -1.39147365e+00
-1.14276516e+00 1.03585815e+00 1.42641574e-01 -5.41056812e-01
-2.00233310e-01 2.57546365e-01 -2.15693876e-01 2.08757535e-01
2.25733086e-01 4.69928175e-01 7.91295946e-01 -1.10165000e+00
-5.69248497e-02 -4.12281752e-01 3.13871592e-01 -2.61452254e-02
-3.87961596e-01 -2.43726864e-01 -3.74799043e-01 -6.44564569e-01
9.01133716e-02 -9.60320890e-01 -2.45176524e-01 6.80745840e-02
-5.83382964e-01 -1.69541076e-01 5.01226485e-01 -6.89706624e-01
9.22134519e-01 -2.22688985e+00 4.28063840e-01 5.68525910e-01
7.84023106e-01 -6.75539523e-02 -4.56725985e-01 6.86384797e-01
-4.74412918e-01 4.70784903e-01 -4.46409643e-01 -9.85486060e-02
1.35917924e-02 4.28263843e-01 -1.21304408e-01 5.87727785e-01
6.38277292e-01 1.23692536e+00 -1.07841754e+00 -4.25176919e-02
-1.04548164e-01 4.15956408e-01 -6.90181971e-01 4.36150044e-01
-1.30960971e-01 1.98914751e-01 -3.07002902e-01 3.15184355e-01
3.94903332e-01 -7.93845773e-01 6.13572955e-01 -2.53442764e-01
5.51174581e-01 3.96263450e-01 -7.07969844e-01 1.83565509e+00
-3.04932743e-01 5.50064385e-01 -1.74789339e-01 -1.54500711e+00
9.83385682e-01 1.01879023e-01 2.32748613e-01 -3.10130924e-01
-1.73245948e-02 4.97722030e-02 8.26875493e-02 -4.05230820e-02
-4.72279079e-02 5.05419895e-02 -1.67064115e-01 6.53826773e-01
5.90224683e-01 -9.97665431e-03 1.07534222e-01 6.80016100e-01
1.51906157e+00 -1.42007470e-01 4.37454432e-01 -4.29349273e-01
2.07383320e-01 -2.86429524e-01 3.67541045e-01 5.33982635e-01
9.32612196e-02 4.62455958e-01 9.41913307e-01 -6.49050534e-01
-1.08801103e+00 -1.37682164e+00 2.81844109e-01 9.83032703e-01
1.59251139e-01 -7.96003342e-01 -5.41985810e-01 -1.10747099e+00
3.72278094e-01 4.40455854e-01 -9.38895047e-01 -6.83253646e-01
-4.31427151e-01 -2.50305504e-01 4.24930453e-01 8.75486493e-01
-8.11540522e-03 -7.50645995e-01 2.50648987e-03 -1.71574622e-01
3.31096113e-01 -9.63283479e-01 -8.04353178e-01 4.38301325e-01
-9.27693963e-01 -1.50491476e+00 -2.67360836e-01 -1.26724589e+00
1.16260767e+00 3.89956504e-01 1.37896585e+00 6.12771153e-01
-1.19720943e-01 6.88406527e-01 -2.60850519e-01 1.72896668e-01
-4.19888258e-01 1.22288510e-01 -1.57939255e-01 -9.94454026e-02
1.55191720e-01 -1.02445769e+00 -2.78854907e-01 6.64732978e-02
-7.05375075e-01 -5.00210486e-02 4.91481900e-01 1.11033916e+00
4.79470640e-01 -2.11420149e-01 4.22433436e-01 -1.22087288e+00
7.85316288e-01 -7.07727194e-01 -5.69622755e-01 4.42025185e-01
-6.87527180e-01 6.59805298e-01 8.00776839e-01 -2.57087916e-01
-4.28286791e-01 5.90621028e-03 3.27737898e-01 -6.77167118e-01
3.65463458e-02 8.51445615e-01 -1.93720028e-01 -9.85197648e-02
7.19526291e-01 -5.64526096e-02 2.20817670e-01 -3.93498182e-01
7.42073536e-01 9.50301066e-02 5.25543988e-01 -5.98325253e-01
1.08875990e+00 2.48619676e-01 4.69640419e-02 -5.47408581e-01
-6.96998358e-01 -2.24886298e-01 -8.83364439e-01 3.55124891e-01
1.08154655e+00 -6.82770550e-01 -3.99714291e-01 3.14058959e-02
-1.02378500e+00 -4.06120598e-01 -4.53330934e-01 3.78523469e-01
-5.61172485e-01 5.07075071e-01 -7.97072589e-01 -3.28134865e-01
-1.18615642e-01 -9.03281093e-01 8.94897640e-01 -4.33243290e-02
-1.68084100e-01 -1.58852291e+00 2.60074496e-01 -1.53106883e-01
1.74418628e-01 3.88050139e-01 1.44792140e+00 -1.10830164e+00
-5.20748556e-01 -2.84960717e-01 -4.84928608e-01 3.25302780e-01
4.41152245e-01 -7.25893229e-02 -6.50179267e-01 -6.05808794e-01
-4.21271741e-01 -4.19136196e-01 8.79289508e-01 8.53494853e-02
1.07267487e+00 -4.75068688e-01 -5.46177804e-01 9.21072960e-01
1.33893776e+00 -2.11390555e-01 4.69146281e-01 -2.07492948e-01
1.15858638e+00 4.69903350e-01 -8.55722725e-02 -6.75619170e-02
4.50425595e-01 4.26096261e-01 4.34350520e-01 -1.54911965e-01
-8.42252970e-02 -6.81618392e-01 2.52783120e-01 1.05459690e+00
-7.29510048e-03 -1.44119203e-01 -9.64687049e-01 5.81141949e-01
-1.90248811e+00 -6.75993681e-01 7.64133260e-02 2.20391679e+00
4.22039658e-01 1.33499689e-02 2.27642171e-02 -2.43386239e-01
9.15573597e-01 2.93925166e-01 -5.62657833e-01 -5.84792912e-01
1.65103868e-01 5.50931454e-01 4.29678023e-01 6.74343109e-01
-9.89365816e-01 1.01301265e+00 5.91606808e+00 1.19957253e-01
-8.71907532e-01 -5.60811684e-02 4.63477790e-01 5.30084848e-01
-7.90265381e-01 5.08085489e-01 -4.13931087e-02 1.57661989e-01
9.89606798e-01 -3.80959898e-01 7.46197462e-01 8.70085061e-01
-6.62565768e-01 6.27979577e-01 -1.58022463e+00 6.96490526e-01
2.39676863e-01 -1.36719906e+00 2.90104765e-02 2.29619488e-01
6.20436072e-01 7.08830133e-02 -1.77313760e-01 4.24789041e-01
1.04077327e+00 -1.37371743e+00 2.31958777e-01 4.39248264e-01
7.82058775e-01 -6.00822091e-01 5.49873292e-01 -1.96018275e-02
-1.53517759e+00 2.08465308e-01 -4.88381237e-01 -5.73968217e-02
-2.75099337e-01 4.17987734e-01 -9.31286395e-01 7.56311178e-01
2.91163564e-01 1.17501664e+00 -5.62000096e-01 6.14640296e-01
-6.35722637e-01 4.40975726e-01 -4.58591096e-02 2.70193249e-01
2.25107476e-01 -4.00412679e-01 2.78654307e-01 8.88467610e-01
1.14240907e-01 -1.97231278e-01 5.02175152e-01 1.21571350e+00
-4.70770180e-01 -1.02470234e-01 -1.13320470e+00 -5.66466510e-01
3.55185151e-01 1.14397538e+00 -5.76684773e-01 -2.70827591e-01
-6.22452855e-01 1.36094809e+00 1.13830125e+00 4.35961753e-01
-6.83363378e-01 -5.36820531e-01 8.60752881e-01 1.43468201e-01
4.83976930e-01 -2.51501352e-01 1.67215273e-01 -1.28046048e+00
-1.01368472e-01 -4.32871491e-01 6.05586410e-01 -7.00828969e-01
-1.76215732e+00 6.38000488e-01 -1.59996256e-01 -7.32226431e-01
-3.89906138e-01 -6.78646803e-01 -1.01686108e+00 9.63967443e-01
-1.30515385e+00 -1.30879974e+00 -2.67165333e-01 5.67147136e-01
-4.93386537e-02 -8.52716491e-02 1.09710932e+00 -2.45872773e-02
-4.34936911e-01 7.28698552e-01 1.71260908e-02 6.63342714e-01
4.71422791e-01 -1.61107743e+00 9.16205525e-01 6.24263406e-01
6.46522999e-01 7.10529625e-01 1.84609920e-01 -7.08346784e-01
-1.51890969e+00 -1.24192905e+00 6.78431809e-01 -3.74950498e-01
9.60800290e-01 -6.51442647e-01 -1.19355214e+00 1.33721185e+00
2.03371778e-01 7.52345860e-01 8.51163149e-01 4.57141310e-01
-9.96670067e-01 5.39689958e-02 -9.14893925e-01 3.68153930e-01
1.41135955e+00 -9.85334218e-01 -6.28847122e-01 4.14435506e-01
1.00358999e+00 -6.91900551e-02 -9.90182221e-01 1.74013704e-01
2.57614076e-01 -7.57035077e-01 8.28361332e-01 -1.28586006e+00
2.95623124e-01 -6.55845180e-02 -1.96699187e-01 -1.64165032e+00
-7.24243581e-01 -4.54578966e-01 -7.38852769e-02 1.00159800e+00
4.91276801e-01 -7.61895359e-01 6.89940095e-01 5.32990158e-01
-2.40709111e-01 -7.16194749e-01 -4.38342929e-01 -8.22745562e-01
1.97325364e-01 -4.45977673e-02 6.79388225e-01 1.46416104e+00
2.01033160e-01 7.85558343e-01 1.46721723e-02 3.86870921e-01
3.97029310e-01 3.29194725e-01 8.03411961e-01 -1.50236464e+00
-5.60514688e-01 -4.55518425e-01 -1.08843505e+00 -7.60995269e-01
7.66236961e-01 -1.72603667e+00 -2.96457201e-01 -1.62626576e+00
3.27821851e-01 -2.25619152e-01 -4.15389121e-01 6.70052588e-01
-1.76795185e-01 -2.07555383e-01 3.30813788e-02 1.23293869e-01
-5.48717201e-01 6.15448475e-01 8.62710416e-01 -2.88492531e-01
1.95520800e-02 -4.75784898e-01 -9.85091865e-01 6.39282644e-01
7.22691298e-01 -4.45132524e-01 -6.99671268e-01 -4.94332194e-01
1.14595525e-01 -8.96169841e-02 4.88798559e-01 -7.15068579e-01
1.49326488e-01 -1.52251599e-02 2.47730955e-01 1.15932018e-01
-3.94114889e-02 -7.16884553e-01 1.50961459e-01 5.10565341e-01
-4.14643556e-01 1.44752562e-01 -1.33242890e-01 9.69903886e-01
-1.72356799e-01 -6.80570304e-02 7.56992042e-01 -1.44685432e-01
-4.93472934e-01 5.44119537e-01 1.31214187e-01 3.59016359e-01
9.97047067e-01 -2.19712645e-01 -3.58957767e-01 -4.82742757e-01
-8.38442147e-01 2.72968978e-01 8.46651554e-01 2.98485756e-01
6.62460327e-01 -1.52890229e+00 -5.86376905e-01 3.58629405e-01
3.36462229e-01 -7.95007870e-02 -2.50080585e-01 5.98426342e-01
-3.21146548e-01 2.06083413e-02 -2.39535764e-01 -5.12443244e-01
-9.30717707e-01 8.60527217e-01 4.28122133e-01 -4.28181380e-01
-7.18835533e-01 8.24011743e-01 7.03847408e-01 -7.60017633e-01
-1.65245876e-01 -4.21161532e-01 1.99175075e-01 -3.69384557e-01
9.13450792e-02 -1.63833380e-01 -8.17476064e-02 -6.14200652e-01
-4.21723366e-01 5.46520948e-01 -2.96121776e-01 3.75799149e-01
1.34107542e+00 2.86017209e-01 -2.73060322e-01 2.96668172e-01
1.60502064e+00 -6.23880327e-02 -1.15810204e+00 -2.95019925e-01
3.24675649e-01 -4.88470644e-01 -1.57638997e-01 -3.22980583e-01
-1.30952466e+00 8.19528878e-01 1.07017029e-02 2.88267016e-01
8.84771824e-01 4.96029675e-01 5.59291363e-01 4.03759241e-01
1.52786911e-01 -4.11427587e-01 3.81308317e-01 5.81798255e-01
7.93753982e-01 -1.24712121e+00 -1.43266603e-01 -6.06424689e-01
-5.28528333e-01 1.09285092e+00 6.53492272e-01 -6.53601229e-01
7.79378295e-01 7.49758705e-02 -5.07255733e-01 -5.58296263e-01
-7.55084813e-01 -3.29275638e-01 4.79326934e-01 9.51654792e-01
4.57669288e-01 7.50898942e-02 1.70427009e-01 6.20036066e-01
-8.71926844e-02 -4.74890530e-01 3.23975921e-01 7.92341352e-01
-3.39701831e-01 -1.15005434e+00 2.62618452e-01 7.53641784e-01
6.85606077e-02 -2.37511531e-01 -9.57162619e-01 8.51317286e-01
-3.39676887e-01 5.15268981e-01 3.06217164e-01 -7.10445106e-01
1.63340852e-01 -1.23065254e-02 5.58223546e-01 -1.15990317e+00
-3.79526615e-01 -4.55014855e-01 8.27470049e-02 -5.20275772e-01
-1.33490831e-01 -8.78257528e-02 -1.35106444e+00 -3.36303949e-01
-3.93283695e-01 3.48035514e-01 1.71395421e-01 6.67261958e-01
6.86255336e-01 4.14818168e-01 6.08074725e-01 -4.87530738e-01
-3.95598114e-01 -6.90702379e-01 -8.93555105e-01 8.72956991e-01
2.16971278e-01 -6.33841097e-01 -5.33613801e-01 -1.11930899e-01] | [7.043728828430176, 6.293851852416992] |
fe03e5ed-a5fe-4c9b-8c75-163f69197c14 | gaitvibe-enhancing-structural-vibration-based | 2212.03377 | null | https://arxiv.org/abs/2212.03377v1 | https://arxiv.org/pdf/2212.03377v1.pdf | GaitVibe+: Enhancing Structural Vibration-based Footstep Localization Using Temporary Cameras for In-home Gait Analysis | In-home gait analysis is important for providing early diagnosis and adaptive treatments for individuals with gait disorders. Existing systems include wearables and pressure mats, but they have limited scalability. Recent studies have developed vision-based systems to enable scalable, accurate in-home gait analysis, but it faces privacy concerns due to the exposure of people's appearances. Our prior work developed footstep-induced structural vibration sensing for gait monitoring, which is device-free, wide-ranged, and perceived as more privacy-friendly. Although it has succeeded in temporal gait event extraction, it shows limited performance for spatial gait parameter estimation due to imprecise footstep localization. In particular, the localization error mainly comes from the estimation error of the wave arrival time at the vibration sensors and its error propagation to wave velocity estimations. Therefore, we present GaitVibe+, a vibration-based footstep localization method fused with temporarily installed cameras for in-home gait analysis. Our method has two stages: fusion and operating. In the fusion stage, both cameras and vibration sensors are installed to record only a few trials of the subject's footstep data, through which we characterize the uncertainty in wave arrival time and model the wave velocity profiles for the given structure. In the operating stage, we remove the camera to preserve privacy at home. The footstep localization is conducted by estimating the time difference of arrival (TDoA) over multiple vibration sensors, whose accuracy is improved through the reduced uncertainty and velocity modeling during the fusion stage. We evaluate GaitVibe+ through a real-world experiment with 50 walking trials. With only 3 trials of multi-modal fusion, our approach has an average localization error of 0.22 meters, which reduces the spatial gait parameter error from 111% to 27%. | ['Hae Young Noh', 'Jingxiao Liu', 'Yiwen Dong'] | 2022-12-07 | null | null | null | null | ['event-extraction'] | ['natural-language-processing'] | [-6.24170080e-02 -5.60976505e-01 1.08975112e-01 6.01433404e-02
-8.56832266e-01 -2.20214456e-01 -4.76616800e-01 9.06111896e-02
-5.13280988e-01 6.34041190e-01 2.49880970e-01 2.52693355e-01
1.91667363e-01 -8.14278424e-01 -4.13741946e-01 -6.85435891e-01
-2.81382620e-01 -1.22916982e-01 4.37077135e-01 -1.92021169e-02
-2.10266560e-01 -6.41050190e-02 -1.49316573e+00 -1.34498402e-01
8.28335702e-01 1.03429580e+00 -2.30128840e-01 7.87334681e-01
6.73110843e-01 8.10908228e-02 -7.61322558e-01 -2.10650668e-01
1.81434639e-02 -2.28309885e-01 -1.33958146e-01 -7.83095807e-02
1.00715861e-01 -7.90687382e-01 -3.77737164e-01 7.15802312e-01
1.15491390e+00 -3.10744322e-03 3.19752455e-01 -1.45924330e+00
-3.52381110e-01 -4.76941578e-02 -7.35575974e-01 3.67060527e-02
1.03000069e+00 3.46618861e-01 4.37398404e-01 -5.67496717e-01
2.27185920e-01 7.41745532e-01 1.37060142e+00 5.08302987e-01
-1.40128529e+00 -5.29962838e-01 -3.97107512e-01 4.61622179e-01
-1.89744711e+00 -5.68205953e-01 8.47350717e-01 -3.52131814e-01
9.47518826e-01 3.93879145e-01 1.13764572e+00 1.26837420e+00
3.43418002e-01 2.22774804e-01 6.85452342e-01 -2.65339434e-01
4.75070924e-01 -3.05797756e-01 2.46297777e-01 5.54767907e-01
7.85175800e-01 1.98249906e-01 -7.47888207e-01 -4.04001474e-01
8.50330830e-01 7.80250505e-02 -5.81453860e-01 5.01545556e-02
-8.63407969e-01 3.16666961e-01 3.29364508e-01 -5.40667288e-02
-4.85112965e-01 3.99362892e-01 3.91097754e-01 -3.94333713e-02
2.22604513e-01 -4.24819976e-01 6.70820847e-02 -6.55321896e-01
-9.87188876e-01 1.82764053e-01 6.34334385e-01 7.43642986e-01
3.04910004e-01 4.71187383e-02 -1.65687650e-01 6.33961916e-01
5.05514503e-01 1.10811937e+00 2.72960484e-01 -8.78113568e-01
6.04269803e-01 2.79623747e-01 2.23478764e-01 -1.35891986e+00
-6.12167835e-01 3.83486366e-03 -8.00795555e-01 1.83874276e-02
4.86418903e-01 -5.70010126e-01 -5.81404865e-01 1.61217487e+00
3.00356060e-01 4.17518020e-01 -3.19654197e-01 1.12147141e+00
6.39105201e-01 2.63256192e-01 4.01193425e-02 -3.93231779e-01
1.52439284e+00 -2.23988995e-01 -8.72787118e-01 -4.10827160e-01
3.97029966e-01 -3.44711751e-01 9.54271495e-01 1.53728455e-01
-8.28784823e-01 -3.01652461e-01 -1.08931839e+00 2.57433087e-01
1.19974777e-01 2.29168758e-01 1.01436414e-01 1.16729426e+00
-1.03669202e+00 3.90979648e-01 -1.30049431e+00 -6.24110639e-01
2.41253242e-01 3.36708933e-01 -2.63644636e-01 -1.19332923e-03
-1.30269241e+00 5.72407186e-01 -3.18248481e-01 3.49915594e-01
-9.80274472e-03 -4.90535080e-01 -9.70627546e-01 -5.18091395e-02
1.78443357e-01 -1.00457120e+00 7.68075824e-01 1.84071297e-03
-1.52198398e+00 3.76254261e-01 -4.38998967e-01 -2.97052532e-01
5.63837230e-01 -2.83511430e-01 -5.93715787e-01 3.29120070e-01
3.85856599e-01 -1.39689997e-01 9.22113299e-01 -7.53041983e-01
-2.89356321e-01 -5.62010288e-01 -6.50281727e-01 5.96085973e-02
-4.17144775e-01 -2.47664124e-01 -3.97836745e-01 -4.36189473e-01
2.89886147e-01 -8.46045136e-01 -5.14972992e-02 1.60539776e-01
-3.25333834e-01 5.00681221e-01 6.52532160e-01 -9.72050786e-01
1.62907767e+00 -2.23956490e+00 -5.11973977e-01 3.77232283e-01
2.37142891e-01 2.58454345e-02 3.76206636e-01 4.36110467e-01
3.18303198e-01 -1.91248469e-02 -2.23276958e-01 -5.25631487e-01
-1.83150351e-01 5.12893833e-02 3.54392752e-02 7.49834359e-01
-2.94789910e-01 6.25226736e-01 -6.41088605e-01 -4.79514003e-01
5.67802966e-01 5.87415040e-01 -4.70083773e-01 -6.99310973e-02
6.51973188e-01 3.68803829e-01 -4.45625126e-01 1.19153059e+00
7.64722347e-01 1.58434436e-01 -8.51985142e-02 -4.03833717e-01
-8.03613756e-03 -2.79859900e-01 -1.55255842e+00 1.39383638e+00
-4.71708104e-02 3.92518252e-01 1.70546964e-01 -6.58995211e-01
7.42847323e-01 5.86452961e-01 9.32175100e-01 -5.30931771e-01
2.05878481e-01 1.87248483e-01 -4.05292004e-01 -1.00090134e+00
2.45266482e-01 2.46762648e-01 -2.46768773e-01 1.92139402e-01
-4.14514095e-01 3.46794993e-01 -1.69921473e-01 -2.78902739e-01
1.40089917e+00 6.32425621e-02 2.43195206e-01 1.14730127e-01
6.94598779e-02 -6.13230057e-02 7.93633878e-01 5.85479796e-01
-8.24387610e-01 8.65184724e-01 -2.40965903e-01 -1.71414226e-01
-4.79100317e-01 -1.42902994e+00 4.03726771e-02 4.55692589e-01
3.40775311e-01 -8.19868088e-01 -8.06569040e-01 2.51679346e-02
1.38898984e-01 1.52659342e-01 -2.46160105e-01 -4.62569416e-01
-5.89662075e-01 -9.15713370e-01 1.00667953e+00 1.00662148e+00
9.19721365e-01 -4.35470611e-01 -9.97367084e-01 5.24338126e-01
-8.49481285e-01 -1.07832992e+00 -7.10468650e-01 -3.83273780e-01
-6.68379724e-01 -1.06426835e+00 -7.90055692e-01 -3.56142551e-01
3.58156204e-01 2.42473990e-01 5.04570782e-01 -1.02954403e-01
-5.81607580e-01 9.22888160e-01 -2.53203273e-01 -3.21293354e-01
6.10536397e-01 -4.71465588e-01 5.16202688e-01 5.55718653e-02
4.99823064e-01 -8.90250385e-01 -9.23153460e-01 3.18868101e-01
5.84320016e-02 -6.53674543e-01 -1.22931726e-01 6.73540890e-01
4.96359587e-01 2.36325085e-01 2.22049356e-01 1.88974932e-01
7.40771353e-01 -3.64543051e-01 -2.13504016e-01 -1.52412191e-01
-4.31728840e-01 -6.45896554e-01 1.98845953e-01 -4.85448658e-01
-7.18397677e-01 1.82590872e-01 -1.41345292e-01 -2.38849297e-01
-1.67079344e-01 5.58587849e-01 -1.46013439e-01 -1.63331598e-01
7.81052828e-01 1.37805402e-01 1.70731395e-01 -2.17311606e-01
-1.52419835e-01 8.89955580e-01 8.83472145e-01 -4.85036105e-01
5.53064048e-01 5.60542345e-01 7.06829578e-02 -1.41951370e+00
2.74217337e-01 -5.93000293e-01 -2.86525309e-01 -7.29139864e-01
8.32828999e-01 -1.11915672e+00 -1.33345902e+00 9.80945945e-01
-8.70275080e-01 -1.83346719e-02 -7.61106834e-02 7.92736948e-01
-5.13919592e-01 6.29951417e-01 -5.96369088e-01 -1.20028734e+00
-5.50391555e-01 -7.55653620e-01 1.26590014e+00 3.49592566e-01
-6.52131140e-01 -6.77450478e-01 9.70849544e-02 4.04431790e-01
3.70974422e-01 7.27289677e-01 1.19771808e-01 2.41636455e-01
-1.94574878e-01 -6.81648910e-01 2.78263181e-01 -1.75765738e-01
3.22342962e-01 -8.44165683e-02 -1.03583086e+00 -3.72315317e-01
3.09827514e-02 1.90668508e-01 4.47327614e-01 1.00636756e+00
5.07556200e-01 -9.91412923e-02 -6.74051940e-01 6.50775015e-01
1.30903387e+00 1.29013479e-01 9.12708759e-01 2.81780422e-01
8.19028854e-01 3.29182029e-01 6.68035328e-01 6.72664344e-01
5.24459481e-01 8.80594134e-01 1.87408268e-01 1.03192031e-01
3.58313173e-02 -4.35171761e-02 7.18328178e-01 4.61081177e-01
-6.85329795e-01 -2.43726283e-01 -7.92470157e-01 5.37250459e-01
-1.90002859e+00 -1.13127446e+00 -5.67580998e-01 2.63706398e+00
3.21646571e-01 -9.63843241e-02 6.41729355e-01 5.63862324e-01
9.23759699e-01 -1.30943388e-01 -4.61872697e-01 -5.49781360e-02
2.44611725e-01 1.20447844e-01 7.97449946e-01 2.63405889e-01
-1.09284854e+00 1.51468486e-01 6.55913830e+00 2.96968281e-01
-1.05992079e+00 2.95767598e-02 -2.04520062e-01 -2.23952994e-01
2.88559735e-01 -3.01016420e-01 -5.28745651e-01 7.72650123e-01
8.91876221e-01 -1.37809470e-01 8.93966928e-02 6.58327281e-01
6.86900437e-01 -5.19516230e-01 -7.19671011e-01 1.32349300e+00
-6.49956837e-02 -8.30329657e-01 -7.20826566e-01 2.87655860e-01
-1.77486107e-01 -3.08560908e-01 -1.85562521e-01 -2.53361464e-01
-3.33600819e-01 -5.22705019e-01 6.16818488e-01 5.54870427e-01
9.97170091e-01 -6.56385779e-01 6.94597661e-01 2.25378588e-01
-1.94483089e+00 -9.82257128e-02 -7.77442902e-02 -4.07978863e-01
6.55039072e-01 7.28191257e-01 -4.01779979e-01 5.73338568e-01
1.20577288e+00 7.15649366e-01 -2.68969327e-01 1.16502798e+00
-3.96248102e-02 9.15839732e-01 -8.87740254e-01 -6.73048347e-02
-7.24125266e-01 -2.40704253e-01 9.35078204e-01 7.46689200e-01
8.55103254e-01 3.29372972e-01 3.19493562e-01 6.45473123e-01
5.76427042e-01 -2.79957026e-01 -6.66317105e-01 3.19504589e-01
8.69509399e-01 7.21536040e-01 -4.08442974e-01 1.44575477e-01
-3.77445430e-01 1.03070545e+00 -4.03300941e-01 3.76394212e-01
-9.32475567e-01 -6.21192217e-01 8.79996479e-01 5.47737122e-01
-5.35585172e-03 -4.29794669e-01 -5.33428431e-01 -1.15905368e+00
6.67809308e-01 -1.98834538e-01 4.53964949e-01 -7.31878579e-01
-1.18596625e+00 9.09555182e-02 -4.68213707e-02 -1.66787648e+00
-4.29856151e-01 -1.77904949e-01 -8.82783532e-01 8.41907978e-01
-5.79099476e-01 -1.06702137e+00 -5.65405011e-01 9.00814295e-01
-2.53512990e-02 3.67043406e-01 9.64037597e-01 6.19659662e-01
-7.95799255e-01 9.05826807e-01 -4.57378402e-02 3.32783341e-01
8.18550646e-01 -8.50927830e-01 3.23099494e-01 1.06385696e+00
-5.20334244e-01 6.36345744e-01 8.38497221e-01 -1.11090624e+00
-1.50466418e+00 -9.52112257e-01 7.42344201e-01 -4.58142996e-01
4.04944867e-01 -2.50273347e-01 -7.48566449e-01 4.71560568e-01
-4.89297897e-01 2.12782487e-01 7.52835751e-01 -1.28509030e-01
2.71992415e-01 -3.21121186e-01 -1.53188801e+00 6.84133530e-01
1.14596355e+00 -4.79946017e-01 -4.41452891e-01 -2.52722889e-01
3.11204731e-01 -4.96499836e-01 -1.10776377e+00 2.37640768e-01
1.06490612e+00 -6.93682551e-01 1.24043858e+00 3.69454145e-01
-2.62108117e-01 -5.30189633e-01 -2.32046902e-01 -1.14813983e+00
-4.81435448e-01 -5.39961457e-01 -2.72156805e-01 1.51698589e+00
-1.41139060e-01 -9.22781765e-01 7.82037377e-01 9.99448955e-01
1.04994014e-01 -2.65872270e-01 -1.27351594e+00 -8.64716411e-01
-7.33332932e-01 -6.47060096e-01 3.77170175e-01 5.01779199e-01
3.50712270e-01 -2.58167833e-02 -6.15056634e-01 5.67078531e-01
1.07933319e+00 -4.11624879e-01 5.81463099e-01 -1.20412827e+00
-8.62968937e-02 2.56836623e-01 -9.75199163e-01 -3.90697509e-01
-6.28187120e-01 -1.27535418e-01 2.30893806e-01 -1.45047784e+00
-2.54324675e-01 1.66154087e-01 1.40816256e-01 4.58416879e-01
-9.21824723e-02 4.13661957e-01 -1.78845391e-01 5.31040840e-02
-2.07572728e-02 3.56705666e-01 6.39821410e-01 -1.29962221e-01
-6.58693254e-01 3.22649717e-01 -2.82020956e-01 7.75571227e-01
6.13306224e-01 -3.44110668e-01 -3.72482866e-01 -2.13405356e-01
-1.90205440e-01 2.30984718e-01 8.99854958e-01 -1.55282664e+00
4.09924537e-01 7.70999044e-02 6.04705453e-01 -4.87982661e-01
6.04144990e-01 -9.28138971e-01 5.42135715e-01 6.98656142e-01
5.73442459e-01 -3.45055610e-02 2.33065814e-01 6.87282324e-01
1.42556146e-01 3.47040057e-01 3.73082668e-01 1.19872734e-01
-5.57733834e-01 2.28564575e-01 -9.90190744e-01 -1.84610888e-01
9.67361867e-01 -9.76732492e-01 -3.78738046e-01 -5.09303510e-01
-9.93510187e-01 1.93324104e-01 4.97073740e-01 2.58679092e-02
9.11832213e-01 -1.54496336e+00 -4.06162471e-01 4.32575941e-01
1.84699029e-01 -2.79756516e-01 6.01560593e-01 1.14197981e+00
-4.67136115e-01 -1.26688942e-01 -1.52329981e-01 -9.71563816e-01
-1.52529836e+00 3.05587277e-02 2.77481467e-01 3.14136386e-01
-8.60134602e-01 4.49445873e-01 -7.32278049e-01 3.41914356e-01
1.98319167e-01 -4.65573847e-01 -2.61418633e-02 -9.96068586e-04
6.74585164e-01 1.08595717e+00 1.39730006e-01 -6.81124330e-01
-8.54936421e-01 1.12281609e+00 5.51895678e-01 -3.51550013e-01
8.51575613e-01 -8.27644765e-01 2.39222780e-01 2.92138040e-01
8.30429077e-01 5.08365482e-02 -1.09520006e+00 2.33135849e-01
-4.24098611e-01 -4.60086465e-01 -5.88089377e-02 -4.23093647e-01
-8.35255682e-01 5.51442087e-01 1.13222671e+00 1.17744297e-01
1.42466187e+00 -5.56155503e-01 1.30887532e+00 4.68695015e-02
9.10915911e-01 -1.12241316e+00 -2.96547025e-01 9.82506573e-02
3.95967126e-01 -8.39437485e-01 -2.04145182e-02 -6.60423994e-01
-4.00241047e-01 8.12401056e-01 5.40797353e-01 -1.15380064e-01
7.41105914e-01 5.62019408e-01 5.94638400e-02 5.52011654e-02
-1.58749118e-01 -2.32245699e-01 5.07808942e-03 1.30884826e+00
-6.76997080e-02 3.09062064e-01 -3.13139856e-01 1.07626724e+00
-1.24044612e-01 4.69767064e-01 4.38690543e-01 1.35359430e+00
-3.85439843e-01 -7.15718627e-01 -9.86295879e-01 4.93360698e-01
-2.09676757e-01 3.02394837e-01 -1.03417560e-01 5.20958781e-01
8.89132097e-02 1.46089566e+00 -5.87750077e-02 -8.79074454e-01
8.14709961e-01 -5.11351936e-02 4.34088200e-01 -2.44111657e-01
-2.99216717e-01 2.67336309e-01 3.08654934e-01 -1.04032457e+00
-2.53324509e-01 -9.02307749e-01 -1.30440342e+00 -6.23304129e-01
-1.99038833e-01 -1.16541959e-01 3.63017142e-01 8.16456497e-01
5.59266269e-01 4.72427487e-01 4.44756836e-01 -9.41071868e-01
-2.46040136e-01 -5.46402693e-01 -1.02502453e+00 9.08635929e-02
4.57671076e-01 -7.91083157e-01 -2.96830952e-01 2.25842744e-01] | [6.893762588500977, 0.47452932596206665] |
c244d46e-2c2f-46b7-9403-7ed31e2c2bdf | fully-convolutional-variational-autoencoder | null | null | https://www.researchgate.net/publication/340049776_Fully_Convolutional_Variational_Autoencoder_For_Feature_Extraction_Of_Fire_Detection_System | https://www.researchgate.net/profile/Herminarto-Nugroho/publication/340049776_Fully_Convolutional_Variational_Autoencoder_For_Feature_Extraction_Of_Fire_Detection_System/links/5e7437ad92851c3587599b32/Fully-Convolutional-Variational-Autoencoder-For-Feature-Extraction-Of-Fire-Detection-System.pdf | Fully Convolutional Variational Autoencoder For Feature Extraction Of Fire Detection System | This paper proposes a fully convolutional variational autoencoder (VAE) for features extraction from a large-scale dataset of fire images. The dataset will be used to train the deep learning algorithm to detect fire and smoke. The features extraction is used to tackle the curse of dimensionality, which is the common issue in training deep learning with huge datasets. Features extraction aims to reduce the dimension of the dataset significantly without losing too much essential information. Variational autoencoders (VAEs) are powerfull generative model, which can be used for dimension reduction. VAEs work better than any other methods available for this purpose because they can explore variations on the data in a specific direction. | ['Ariana Yunita', 'Muhammad Koyimatu', 'Ade Irawan', 'Meredita Susanty', 'Herminarto Nugroho'] | 2020-03-01 | null | null | null | jurnal-ilmu-komputer-dan-informasi-2020-3 | ['fire-detection'] | ['time-series'] | [-3.25809896e-01 -3.71426314e-01 2.26285696e-01 4.70026582e-02
-1.47996128e-01 -2.86173254e-01 7.44548142e-01 -4.79644001e-01
-3.65326673e-01 6.43904388e-01 2.09271058e-01 8.83565173e-02
-4.37651873e-01 -1.45798445e+00 -5.28216779e-01 -1.15233970e+00
1.26395643e-01 3.10794979e-01 2.45776385e-01 -3.91336530e-01
1.08201176e-01 7.75399446e-01 -1.99923480e+00 3.87519658e-01
2.91575432e-01 8.85013103e-01 4.92598534e-01 5.94692588e-01
-4.35185492e-01 7.18289793e-01 -3.17734838e-01 2.02320531e-01
2.06941366e-01 -3.36651891e-01 -5.99657059e-01 2.90465485e-02
-4.48108427e-02 -2.80840218e-01 -5.93819857e-01 9.43812907e-01
4.30447996e-01 3.28994751e-01 1.29618359e+00 -1.15248406e+00
-4.99802411e-01 4.80236471e-01 -2.82863200e-01 5.64542592e-01
-4.35275286e-01 1.26911104e-02 6.64931238e-01 -9.85931933e-01
6.53280914e-01 1.23541236e+00 4.82053041e-01 7.10698843e-01
-7.97646821e-01 -4.08599138e-01 -5.00839233e-01 5.65741241e-01
-1.38746965e+00 -1.28692403e-01 1.15790355e+00 -6.47832930e-01
8.76835048e-01 3.81544292e-01 9.65350509e-01 1.45715070e+00
2.75657386e-01 5.27636349e-01 8.97612393e-01 -7.62488246e-02
3.45878482e-01 1.95391193e-01 8.48411843e-02 5.13003767e-01
1.79984733e-01 3.82361740e-01 -2.33175620e-01 2.61603557e-02
9.21868801e-01 4.93099511e-01 -1.55919552e-01 3.05375224e-03
-6.34952962e-01 1.39814353e+00 5.33900201e-01 6.10418200e-01
-7.72136152e-01 6.16018772e-02 3.31167072e-01 1.79611351e-02
2.79477477e-01 3.42583328e-01 -4.29030001e-01 -1.14704818e-01
-9.28441226e-01 4.39913213e-01 4.87732202e-01 4.13134843e-01
8.01973104e-01 4.13102090e-01 -1.70065835e-01 6.67276740e-01
4.66330856e-01 6.83077276e-01 5.34025669e-01 -8.77228200e-01
-6.22697063e-02 1.02696013e+00 -4.19828504e-01 -9.16501760e-01
-4.34781760e-01 -4.00255740e-01 -1.29110789e+00 5.64264059e-01
-3.77044156e-02 -3.09371531e-01 -1.02239192e+00 1.23949504e+00
5.88607013e-01 1.31058209e-02 1.18479609e-01 7.95571327e-01
1.23431039e+00 1.05128515e+00 -8.93617868e-02 -9.68731344e-02
1.33709252e+00 -3.92573148e-01 -7.26022005e-01 6.89025000e-02
7.70692304e-02 -4.26614046e-01 7.21293747e-01 4.14231420e-01
-3.82724673e-01 -6.08927608e-01 -8.86886775e-01 -3.15978527e-02
-8.65920246e-01 -4.38058265e-02 7.17193246e-01 4.28666711e-01
-6.88506305e-01 8.00127923e-01 -7.42445707e-01 -7.83149675e-02
8.69319737e-01 4.57030050e-02 -1.59646586e-01 8.06658119e-02
-1.23253393e+00 7.10718989e-01 8.23042393e-01 2.94278622e-01
-1.24874353e+00 -6.17791295e-01 -6.42299771e-01 1.96215585e-01
2.21987039e-01 -5.16077638e-01 5.79079032e-01 -5.46355069e-01
-1.13200319e+00 4.47122753e-01 2.70806104e-01 -3.38064611e-01
4.23960716e-01 -1.79694846e-01 -2.24624649e-01 -5.69797531e-02
-2.49233380e-01 4.38716799e-01 1.23457253e+00 -1.08550596e+00
-2.57887125e-01 -4.76181984e-01 -2.52928555e-01 -1.55344054e-01
-5.62608957e-01 -3.34794760e-01 1.31477296e-01 -5.30006886e-01
-8.18966255e-02 -8.56619537e-01 -2.25898713e-01 -3.39475155e-01
-2.11249381e-01 -5.10084629e-01 1.66331983e+00 -5.73524773e-01
9.84327972e-01 -2.21376491e+00 5.00697076e-01 -1.83919052e-04
3.14921707e-01 5.38793325e-01 1.36039287e-01 5.39576650e-01
1.33888617e-01 1.60063863e-01 -3.38944703e-01 9.41607952e-02
-2.19037592e-01 6.27211690e-01 -1.74884364e-01 1.37878880e-01
3.60870242e-01 8.74341726e-01 -6.40655398e-01 -7.11982071e-01
5.59387743e-01 9.39346433e-01 -4.50719565e-01 2.62824178e-01
-4.55508441e-01 4.38018233e-01 -5.81838906e-01 2.38851279e-01
7.48991191e-01 8.08328018e-02 -3.20495754e-01 -2.81994015e-01
-2.38609925e-01 -5.16458571e-01 -1.19918001e+00 1.33604145e+00
-3.69656831e-01 9.10132408e-01 -2.84319609e-01 -9.40701008e-01
1.05296409e+00 3.00380111e-01 6.93981886e-01 -3.91713619e-01
5.34626126e-01 -2.56253958e-01 -8.29113349e-02 -9.03886974e-01
9.01723579e-02 -3.37807655e-01 3.08098644e-01 2.91749537e-01
2.96709239e-01 -6.39929250e-02 3.31724048e-01 -8.00818801e-02
7.29652405e-01 -4.07613553e-02 6.76692352e-02 -2.90455341e-01
4.54470068e-01 9.04008597e-02 5.35718799e-01 3.05808842e-01
1.70948610e-01 3.46846879e-01 2.72016644e-01 -9.32486415e-01
-1.36874425e+00 -9.25084233e-01 -3.45434308e-01 6.09814167e-01
-3.81733298e-01 -3.38323712e-01 -5.80817461e-01 -5.77310503e-01
-4.35197651e-02 7.19773293e-01 -8.39224696e-01 -2.43496224e-01
-2.56486863e-01 -8.93605709e-01 3.58836919e-01 5.89229167e-01
9.08443034e-01 -1.31990194e+00 -1.06752849e+00 3.05928271e-02
1.09706521e-02 -6.86325490e-01 4.61895674e-01 1.83177978e-01
-1.03690732e+00 -1.27908242e+00 -6.45296454e-01 -3.42202783e-01
2.52936542e-01 -3.87460552e-02 7.79744804e-01 -1.05828516e-01
-7.09531188e-01 5.85688017e-02 -6.28452957e-01 -8.37249100e-01
-4.89346981e-01 1.18767232e-01 -2.51213163e-02 -8.70483220e-02
7.37422645e-01 -7.89463997e-01 -4.09370929e-01 -3.25710058e-01
-1.10830760e+00 -1.94306433e-01 4.85706866e-01 7.41472304e-01
4.58663613e-01 6.79038763e-01 1.90808982e-01 -7.04926372e-01
7.28782356e-01 -6.17073774e-01 -6.27123058e-01 -1.05776601e-01
-3.74695987e-01 4.50007379e-01 7.74322391e-01 -1.93108603e-01
-1.00895476e+00 -3.42487544e-02 -2.87454754e-01 -8.74666631e-01
-5.28861523e-01 4.43901181e-01 1.22026093e-01 2.64793992e-01
8.54016840e-01 4.17028219e-01 -1.02026775e-01 -7.38297343e-01
2.35536978e-01 7.71541655e-01 5.26609011e-02 1.01396829e-01
8.67875218e-01 4.25844610e-01 5.29748499e-01 -1.32297623e+00
-6.31400764e-01 -2.12501943e-01 -8.80436897e-01 -3.92681867e-01
1.21770012e+00 -4.81653035e-01 -7.75116861e-01 3.27116847e-01
-1.02475321e+00 -6.11138307e-02 -4.78790730e-01 5.15362382e-01
-1.93599284e-01 1.28483921e-01 -1.43394440e-01 -1.10156643e+00
-5.91584444e-01 -8.80692542e-01 7.37887979e-01 4.68509465e-01
3.17347556e-01 -1.02693474e+00 4.74213302e-01 -9.20844227e-02
4.40149575e-01 5.49565434e-01 7.89490163e-01 -4.01918560e-01
-4.27053273e-01 -3.33181731e-02 4.21512201e-02 7.31578052e-01
-2.28713155e-02 5.46803057e-01 -1.18643546e+00 9.72250104e-03
2.47434661e-01 -6.46851435e-02 1.41609609e+00 6.08611047e-01
1.25858128e+00 -2.38556802e-01 -7.76918232e-02 7.72583425e-01
1.58520436e+00 2.03149930e-01 7.73125887e-01 3.61420184e-01
8.14064562e-01 2.29305133e-01 1.38081297e-01 7.40563691e-01
-7.93977305e-02 1.52948678e-01 9.59214687e-01 9.84561592e-02
-1.02958255e-01 5.41032339e-03 1.26632228e-01 6.72911346e-01
-5.66676795e-01 -1.21308818e-01 -9.05918300e-01 3.96819055e-01
-1.67524183e+00 -1.34031928e+00 -4.46223825e-01 1.52559936e+00
2.90751338e-01 -2.83227026e-01 4.95837629e-02 7.37061977e-01
3.74784201e-01 3.63609701e-01 -3.40871394e-01 -3.68891746e-01
8.86841565e-02 4.11541700e-01 2.93987513e-01 7.63797089e-02
-1.44897544e+00 8.76004279e-01 6.42822266e+00 6.56826496e-01
-1.19927824e+00 6.17175214e-02 -9.61059481e-02 5.25795445e-02
-1.66610107e-01 -2.76269555e-01 -6.93323076e-01 4.17693466e-01
8.56317818e-01 3.38716716e-01 5.84318042e-01 1.17996752e+00
6.63800240e-02 1.80477966e-02 -6.90388381e-01 1.17200708e+00
-2.49368653e-01 -1.48363578e+00 2.24234909e-01 2.61868417e-01
6.24130785e-01 1.76491797e-01 3.63750570e-02 3.50631893e-01
2.02388451e-01 -1.11414957e+00 4.75304238e-02 9.20711994e-01
4.58777159e-01 -1.22785223e+00 8.77850831e-01 6.48724258e-01
-1.02740276e+00 -3.61401856e-01 -1.08949304e+00 -1.70027539e-01
-7.03235641e-02 8.05223584e-01 -7.00829864e-01 3.52346659e-01
8.84379506e-01 6.92826986e-01 -4.66441631e-01 8.31261456e-01
-1.70560762e-01 5.86920977e-01 -4.16762054e-01 -2.44923860e-01
4.66923028e-01 -4.71643597e-01 7.38288522e-01 1.00633943e+00
4.05718178e-01 8.23801011e-02 -9.61677656e-02 1.21743262e+00
1.27750307e-01 5.64569868e-02 -1.07527781e+00 -4.91745502e-01
1.49635732e-01 1.29159546e+00 -4.30878580e-01 -2.87143081e-01
4.23310995e-02 8.17538321e-01 -4.82507907e-02 1.67210996e-01
-6.92916989e-01 -4.31227475e-01 6.34873569e-01 -1.48025066e-01
5.31424761e-01 -2.89159775e-01 3.65250595e-02 -1.06520653e+00
-4.58601952e-01 -4.98846292e-01 4.21981066e-01 -6.56173229e-01
-1.14620352e+00 7.24574566e-01 4.61248420e-02 -1.10659385e+00
-4.78384703e-01 -8.17108810e-01 -6.78295255e-01 7.33985066e-01
-1.30820596e+00 -1.08443511e+00 -6.89673066e-01 8.43455732e-01
7.90382326e-01 -5.38884282e-01 1.09498918e+00 1.42343372e-01
-6.29363596e-01 -1.49876073e-01 3.07835996e-01 3.61823469e-01
-1.20349228e-01 -1.02011979e+00 -6.15424216e-02 8.10950637e-01
5.37970901e-01 2.04660237e-01 7.48916209e-01 -5.37450373e-01
-1.51594996e+00 -1.05129898e+00 4.39198405e-01 -4.04669374e-01
3.99234369e-02 -2.85258204e-01 -8.42575908e-01 4.14265692e-01
1.62310064e-01 3.29838097e-02 7.11410403e-01 2.46584173e-02
-1.29045816e-02 -7.09817698e-03 -1.11446500e+00 1.63839906e-01
7.34700918e-01 -4.25032705e-01 -7.02798843e-01 2.99435288e-01
3.54390800e-01 -1.78010315e-02 -1.02301514e+00 2.41234884e-01
6.09863222e-01 -1.07765651e+00 1.00432122e+00 -8.63772810e-01
8.23012829e-01 4.61301059e-02 -1.61589593e-01 -1.43817401e+00
-7.10295558e-01 -1.16863996e-02 -5.14896989e-01 1.08988631e+00
-2.62400173e-02 -1.81610003e-01 6.56909108e-01 1.21832378e-01
2.23869607e-01 -5.04028559e-01 -7.95907438e-01 -6.70621216e-01
1.02602363e-01 -5.12962282e-01 7.51855552e-01 9.18382525e-01
-4.32648659e-01 3.51300716e-01 -4.98214930e-01 1.58513606e-01
8.29357326e-01 6.93240091e-02 6.54720545e-01 -1.69537210e+00
2.38991454e-02 -3.44733119e-01 -6.65013552e-01 -1.19115256e-01
3.06724589e-02 -8.95581245e-01 -3.98225069e-01 -1.75221372e+00
2.27984816e-01 6.93549588e-02 -2.86752760e-01 3.41645777e-01
1.08168691e-01 1.20376669e-01 1.96214885e-01 -4.72160019e-02
2.04783350e-01 9.84814525e-01 1.23117876e+00 -2.77263820e-01
-2.65848428e-01 1.03573494e-01 -2.29956195e-01 7.53052294e-01
1.00386596e+00 -7.86252439e-01 -5.64683795e-01 -3.38401318e-01
2.28790179e-01 -2.61584610e-01 5.82616210e-01 -1.24311221e+00
-1.14867210e-01 -4.51736718e-01 9.16600764e-01 -9.42614913e-01
2.64680237e-01 -1.13758028e+00 3.62515956e-01 3.97893876e-01
8.07861090e-02 -2.37182781e-01 1.33599326e-01 3.73405904e-01
-2.55118161e-01 -4.77060139e-01 7.79142261e-01 -5.64297736e-01
-9.53298748e-01 5.68312943e-01 -4.07066643e-01 -1.66314006e-01
1.05656397e+00 -2.31335638e-03 2.96846237e-02 -1.06288470e-01
-8.70698094e-01 -1.39769480e-01 7.74898306e-02 5.01795173e-01
8.24012578e-01 -1.50046027e+00 -7.61861622e-01 4.60524619e-01
-2.21185178e-01 2.28603676e-01 6.77028000e-01 3.99761319e-01
-6.63646042e-01 1.55128747e-01 -6.85619950e-01 -6.39739871e-01
-1.05873632e+00 8.29132855e-01 3.94730866e-01 -1.38992339e-01
-9.53127146e-01 8.89756382e-01 -1.70037642e-01 -1.17107473e-01
-2.11290643e-01 -6.65359870e-02 -8.29981148e-01 4.77752805e-01
6.27912343e-01 6.61941767e-01 -2.26280943e-01 -5.64635456e-01
-4.02251273e-01 5.03303289e-01 4.23348248e-01 -1.25669660e-02
2.09174657e+00 3.54669511e-01 -1.22014873e-01 6.56626582e-01
1.29495788e+00 -4.36027408e-01 -1.30150259e+00 7.32557997e-02
-3.92788380e-01 -4.48686361e-01 6.84136152e-01 -3.26877356e-01
-1.43348992e+00 1.45167279e+00 9.85223949e-01 4.17914063e-01
9.00684237e-01 -4.64360453e-02 6.38347447e-01 4.79921550e-01
-9.58803594e-02 -1.34416032e+00 3.57077159e-02 6.10641360e-01
1.15657699e+00 -1.24973798e+00 -1.46353124e-02 2.86433935e-01
-6.54504359e-01 1.55990613e+00 2.57468551e-01 -3.96168321e-01
1.14677632e+00 3.09516847e-01 -1.72505304e-01 -7.11627007e-01
-4.87618834e-01 -5.78612149e-01 3.60395253e-01 7.62077749e-01
9.08786505e-02 7.51591250e-02 -7.98166618e-02 5.42217076e-01
-2.38305137e-01 6.50869235e-02 1.86074167e-01 6.86839640e-01
-7.85282969e-01 -8.19185019e-01 -4.84987468e-01 6.22555912e-01
-1.29284695e-01 5.99177554e-02 -4.32536334e-01 7.04804480e-01
5.39939404e-01 6.89830720e-01 6.90864213e-03 -6.72784984e-01
1.54243991e-01 4.04286146e-01 3.96484554e-01 -1.82022601e-01
-2.68942475e-01 -1.19206507e-03 -4.00125921e-01 -3.57935876e-01
-4.12867099e-01 -5.71144402e-01 -9.95883942e-01 -2.30759442e-01
-1.13205306e-01 -6.89523369e-02 8.66051197e-01 1.01035810e+00
3.62579040e-02 8.72465134e-01 7.38660812e-01 -8.29368651e-01
-4.24218029e-01 -1.16412497e+00 -9.31558073e-01 4.41946715e-01
3.13356310e-01 -9.63801503e-01 -4.39105153e-01 -8.80204216e-02] | [9.117972373962402, 2.932912588119507] |
ea3561ea-5030-4dd8-8b58-a753808172ce | very-large-language-model-as-a-unified | 2212.09271 | null | https://arxiv.org/abs/2212.09271v2 | https://arxiv.org/pdf/2212.09271v2.pdf | Very Large Language Model as a Unified Methodology of Text Mining | Text data mining is the process of deriving essential information from language text. Typical text mining tasks include text categorization, text clustering, topic modeling, information extraction, and text summarization. Various data sets are collected and various algorithms are designed for the different types of tasks. In this paper, I present a blue sky idea that very large language model (VLLM) will become an effective unified methodology of text mining. I discuss at least three advantages of this new methodology against conventional methods. Finally I discuss the challenges in the design and development of VLLM techniques for text mining. | ['Meng Jiang'] | 2022-12-19 | null | null | null | null | ['text-clustering', 'text-categorization'] | ['natural-language-processing', 'natural-language-processing'] | [-1.9613930e-03 3.3787642e-02 -5.7306117e-01 -4.7384465e-01
-5.5840224e-01 -2.9538092e-01 8.3661985e-01 8.6085701e-01
-4.4187078e-01 7.1046758e-01 7.3811972e-01 -5.2809346e-01
-1.8076986e-01 -7.2211313e-01 2.9246667e-01 -3.2988578e-01
-1.2440496e-03 7.6977420e-01 -6.7850649e-02 -1.8271147e-01
9.0577352e-01 1.5040815e-01 -1.7554904e+00 6.0061908e-01
9.5275170e-01 5.2392548e-01 3.3359262e-01 7.9074746e-01
-1.4226940e+00 9.6963084e-01 -9.6591967e-01 2.4797814e-02
-2.9019204e-01 -3.4971261e-01 -1.1666836e+00 2.7026406e-01
5.2706983e-02 9.3493529e-02 7.3030777e-02 8.9441895e-01
3.8327438e-01 3.1951648e-01 9.6979547e-01 -1.3804460e+00
-1.4118148e-01 1.1192806e+00 -9.9231613e-01 3.3322108e-01
6.2381983e-01 -9.1798353e-01 8.7652403e-01 -9.4853914e-01
6.8555331e-01 1.6324254e+00 2.8431535e-01 3.7139025e-01
-5.8749568e-01 -6.4759010e-01 2.3292622e-01 -6.3793160e-02
-1.1382886e+00 -2.8954875e-01 6.2701225e-01 -5.7765716e-01
1.2111157e+00 3.5492808e-01 2.5282344e-01 6.0879266e-01
7.2610325e-01 1.1856986e+00 9.2933655e-01 -8.9258945e-01
2.2133271e-01 7.1736538e-01 1.2753388e+00 4.3538222e-01
6.4363897e-01 -7.0967144e-01 -9.7248685e-01 -5.6230533e-01
-2.1514285e-01 -1.2031496e-02 2.6465502e-01 1.3286781e-01
-8.2946587e-01 1.2432103e+00 -7.8853291e-01 5.2903861e-01
-1.8121891e-01 -3.6135811e-01 9.5950484e-01 5.5830610e-01
8.0255377e-01 1.9875023e-01 -5.1273328e-01 -5.5833332e-02
-1.1894014e+00 1.4471038e-01 1.1649148e+00 1.2579440e+00
5.8717638e-01 -5.7398840e-03 -5.0010033e-02 9.2744172e-01
5.5164033e-01 2.5189683e-01 1.2445879e+00 -3.6702472e-01
6.9373846e-01 1.1008333e+00 -1.2917320e-01 -7.1575189e-01
-7.7378076e-01 3.1323530e-02 -9.0616697e-01 -2.2389334e-01
-2.1231472e-01 -5.6999654e-01 -7.7021968e-01 7.8980005e-01
3.7420833e-01 -9.7886384e-01 2.6719606e-01 -2.5838229e-01
1.2737824e+00 1.0655713e+00 2.9608333e-01 -8.2209963e-01
1.4085854e+00 -6.3324964e-01 -1.1800416e+00 -1.3398813e-01
1.1474302e+00 -9.9122488e-01 7.8008133e-01 6.3406122e-01
-8.9693785e-01 -4.7869155e-01 -6.1550266e-01 -2.3490830e-01
-9.0090430e-01 7.6517865e-02 8.5446525e-01 9.2720580e-01
-8.1403178e-01 -2.7459666e-02 -3.1221485e-01 -8.1487894e-01
1.6621748e-01 3.2424027e-01 -1.1353504e-01 3.6199963e-01
-9.5235747e-01 4.0237612e-01 8.8953650e-01 -6.1718643e-01
-1.6384628e-02 -2.9487947e-01 -7.3230058e-01 -1.0967629e-01
3.0853501e-01 -4.6655643e-01 1.1592983e+00 -5.2998430e-01
-1.0082479e+00 1.0089501e+00 -7.3080999e-01 -5.6960446e-01
4.5371756e-02 -3.1608805e-01 -5.1424646e-01 -1.4638906e-02
3.8540611e-01 2.1627821e-01 7.3008752e-01 -1.1203096e+00
-1.2626455e+00 -5.7347447e-01 -7.6833278e-01 2.1079417e-01
-8.3474338e-01 6.3170141e-01 -2.6828662e-01 -7.7949536e-01
-1.2598501e-01 -3.4732443e-01 -2.9849550e-01 -7.1551371e-01
-5.4991138e-01 -1.1039523e+00 1.3574870e+00 -3.4499878e-01
1.7791953e+00 -1.7435913e+00 -4.5033330e-01 1.8882258e-01
5.2522886e-01 -7.5117655e-02 5.0441903e-01 1.0785471e+00
1.8593682e-01 5.7287294e-01 2.1886350e-01 -1.8591578e-01
-9.3243711e-02 -3.1345796e-02 -6.5212435e-01 -1.8259961e-02
-5.7096809e-01 7.6731175e-01 -3.5811448e-01 -1.0761120e+00
3.2008874e-01 -4.4400774e-02 -3.7360474e-02 -2.2267139e-01
-2.7814350e-01 -2.4301055e-01 -9.3147129e-01 4.9729988e-01
3.4331638e-01 -8.8373378e-02 1.0514802e-01 3.8943827e-01
-5.9231251e-01 3.7937281e-01 -1.2348831e+00 1.4304507e+00
-1.3117819e-01 1.0019308e+00 1.2206303e-02 -1.1428494e+00
9.9533659e-01 3.9970011e-01 8.7265158e-01 -2.5337654e-01
3.4883913e-01 -2.0516318e-01 -2.8179169e-01 -6.5635389e-01
9.2761868e-01 7.4191885e-03 -4.0049720e-01 1.2083075e+00
-5.9585083e-02 -8.3061725e-02 7.2093374e-01 7.6025069e-01
6.3646460e-01 -5.3814232e-01 9.4103646e-01 -7.6692373e-01
6.9492382e-01 7.2392642e-01 4.1375533e-02 1.0266303e+00
1.2879431e-01 -2.0926709e-01 3.4506136e-01 -4.9546984e-01
-7.0629936e-01 -2.9228389e-01 -3.0013242e-01 1.5576015e+00
-1.9456333e-01 -1.2243234e+00 -5.9261554e-01 -5.2582848e-01
1.2098995e-01 9.8110819e-01 -5.2712780e-01 2.0122479e-01
-3.6036032e-01 -1.1059570e+00 3.9173132e-01 1.2860906e-01
4.0625075e-01 -1.0221200e+00 -4.2131555e-01 2.8646189e-01
-1.5381159e-01 -8.5656673e-01 -1.8282536e-01 4.0195906e-01
-1.0605505e+00 -6.5335870e-01 -1.0342918e-01 -1.1312430e+00
6.4022368e-01 7.5795066e-01 9.6272534e-01 -1.6660821e-01
-3.3294049e-01 3.5782012e-01 -8.1531596e-01 -1.1683218e+00
-8.4007800e-01 5.0687295e-01 2.4513896e-01 -4.1392624e-01
1.1262859e+00 -9.0347946e-02 1.1629905e-01 -1.2929687e-01
-1.0768279e+00 1.2931503e-01 3.4555775e-01 3.4925899e-01
2.3345885e-01 9.0863240e-01 8.6498708e-01 -1.5144424e+00
1.5690625e+00 -5.5410314e-01 -7.9272173e-02 3.5038060e-01
-1.1486390e+00 2.4350455e-01 5.2626097e-01 -2.5307181e-01
-1.3651491e+00 -2.7678585e-01 -5.8478530e-02 6.5131634e-01
-3.5935974e-01 8.7359911e-01 -2.2476830e-03 4.5098302e-01
6.3238078e-01 2.8241089e-01 -2.3196985e-01 -8.1558597e-01
2.0444009e-01 1.6289895e+00 -1.8815109e-01 -2.8487164e-01
4.3403494e-01 5.4878473e-01 -3.7025338e-01 -1.6024646e+00
-9.4420433e-01 -1.1915966e+00 -9.2814451e-01 -1.5413392e-01
5.2391893e-01 -7.0348603e-01 -2.8418362e-01 3.3241799e-01
-8.6329752e-01 7.9730123e-02 -3.8251132e-01 3.2179382e-01
-8.3700068e-02 6.4146745e-01 -3.8212460e-01 -8.2346761e-01
-1.0960681e+00 -3.9471099e-01 9.2685652e-01 9.3066394e-02
-7.0519400e-01 -1.3329115e+00 4.3451160e-02 4.7746524e-01
-4.1316345e-02 -1.0943233e-01 1.1422267e+00 -1.2316436e+00
4.8930129e-01 -5.0048125e-01 1.4622977e-01 -5.3832568e-02
4.7775850e-01 8.7646827e-02 -6.6340876e-01 -3.3379069e-01
3.5305056e-01 -3.0658334e-01 9.8743463e-01 5.6545299e-01
1.1698418e+00 -3.8814485e-01 -8.0181962e-01 1.2265935e-01
1.2246873e+00 4.3529773e-01 7.6250853e-03 5.2864307e-01
6.0576105e-01 1.0785756e+00 8.2092118e-01 6.4700675e-01
3.3187866e-01 -8.5254267e-02 -5.3128052e-01 1.8893281e-01
1.9064458e-01 -5.8109146e-03 5.3768605e-01 1.1959021e+00
6.6259456e-01 -5.4543734e-01 -1.2126470e+00 3.5099360e-01
-1.8632820e+00 -9.5192057e-01 -7.1527189e-01 1.7615882e+00
8.2136655e-01 4.3668038e-01 2.4383420e-01 4.0316156e-01
5.8502197e-01 -1.1966142e-02 -3.6023337e-01 -8.0972981e-01
-2.3730712e-01 -1.8640485e-01 2.9105693e-01 5.0187391e-01
-1.1064079e+00 1.2064182e+00 7.1910248e+00 9.3836284e-01
-6.3666207e-01 -1.3465665e-01 2.9248741e-01 -4.8311003e-02
-1.9303539e-01 2.6466880e-02 -1.4612548e+00 1.7797631e-01
1.1291336e+00 -1.1198785e+00 -5.4510510e-01 8.7482506e-01
6.0369051e-01 -6.1711138e-01 -6.3398290e-01 1.0741571e+00
3.3154574e-01 -1.3085395e+00 9.4756544e-01 2.1104483e-01
6.7458540e-01 -1.4156582e-02 -4.2487830e-01 2.3275046e-01
5.6039137e-01 -7.5126213e-01 2.7976614e-01 -5.1481291e-03
5.1497519e-01 -8.8100028e-01 6.3111240e-01 8.8261908e-01
-1.0836596e+00 8.0094924e-03 -5.9440374e-01 -1.3233635e-01
6.6842161e-02 7.6254594e-01 -7.9555458e-01 5.0106990e-01
7.3039895e-01 7.7951801e-01 -6.7739409e-01 6.5106416e-01
3.6657798e-01 7.2294611e-01 -2.1649458e-01 -5.0707555e-01
2.4156074e-01 -2.0652570e-01 5.9948158e-01 1.5863981e+00
-9.9854663e-02 -1.5954331e-01 4.4446191e-01 1.1115815e-01
2.6080403e-02 8.5215646e-01 -8.0734277e-01 -1.7930047e-01
3.3855027e-01 1.2497029e+00 -1.1790614e+00 -7.5151455e-01
-5.6045282e-01 4.8629481e-01 -2.1051568e-01 2.5518690e-03
1.2917513e-01 -8.6592442e-01 1.2017867e-01 -1.4581888e-02
-3.1381667e-01 -2.6990312e-01 -6.5183997e-01 -1.1448303e+00
-2.1296972e-01 -8.8586313e-01 9.2882961e-01 -3.7279969e-01
-9.4324929e-01 5.0045699e-01 4.5349813e-01 -9.1986036e-01
-5.4427397e-01 -5.6731874e-01 -6.4393681e-01 4.4944996e-01
-1.0274025e+00 -7.7666700e-01 -7.2102159e-02 6.9740373e-01
1.4595660e+00 -7.3605281e-01 7.5881380e-01 -2.6367927e-01
-5.5620772e-01 1.8998908e-01 6.6958356e-01 -3.5196114e-02
7.1986181e-01 -1.2977595e+00 4.0530282e-01 7.2291291e-01
2.4806570e-01 5.7879120e-01 7.7914721e-01 -9.0998334e-01
-1.4711573e+00 -9.6963888e-01 1.2119133e+00 -5.5854666e-01
7.9695737e-01 -6.0006398e-01 -9.0787530e-01 6.1351538e-01
4.3173927e-01 -1.2524922e+00 1.4444208e+00 1.9288109e-01
1.9519216e-01 1.6102643e-01 -7.9393899e-01 4.6456930e-01
4.2175674e-01 -1.2605724e-01 -9.8210156e-01 5.8984447e-01
6.8659419e-01 3.7990531e-01 -6.1387992e-01 -2.8873056e-01
3.6419040e-01 -3.5617855e-01 4.3244922e-01 -7.3038077e-01
5.8380529e-02 1.2796125e-01 1.4139861e-01 -9.0290225e-01
6.7010395e-02 -9.4015098e-01 -8.1426449e-02 1.6123681e+00
4.3361974e-01 -5.3518081e-01 8.2063246e-01 4.4853106e-01
2.5140670e-01 -2.7701205e-01 -5.4532701e-01 -5.0034922e-01
5.4730624e-01 -8.1203985e-01 1.7670012e-01 9.8448747e-01
8.6083364e-01 1.0708861e+00 -2.4956493e-01 -5.5925763e-01
7.8402609e-01 2.7715164e-01 9.0279573e-01 -1.9668226e+00
6.4260429e-01 -5.9644902e-01 1.4205240e-01 -9.4329244e-01
2.0622425e-01 -9.6208841e-01 -4.7536552e-01 -2.0263402e+00
4.3795875e-01 -9.4046101e-02 2.0136848e-01 1.7646235e-01
-1.1351805e-01 -6.4175969e-01 -2.3932391e-01 6.4520460e-01
-7.8216273e-01 2.0322528e-01 6.7420924e-01 -1.9451143e-01
-7.2143006e-01 2.3471291e-01 -1.2702994e+00 9.9612039e-01
1.4244261e+00 -7.6950336e-01 -6.9930726e-01 -1.4266153e-01
5.5013514e-01 -1.3369863e-01 -8.1674463e-01 -4.7107348e-01
8.2608962e-01 -4.2258981e-01 2.3728788e-01 -1.3158518e+00
-4.2614055e-01 -5.9302920e-01 -5.3520411e-01 3.7765706e-01
-7.0921034e-01 8.0033369e-02 2.7547914e-01 4.7942862e-01
-3.4267715e-01 -6.3966686e-01 4.7876063e-01 -3.1431413e-01
-8.3148885e-01 2.3013961e-02 -1.3361884e+00 1.7377795e-01
9.0579116e-01 -3.7475181e-01 1.7341597e-02 -2.7574646e-01
-3.9418134e-01 6.9008625e-01 -4.6457443e-02 8.3802259e-01
6.5077919e-01 -7.6506370e-01 -9.1689801e-01 1.0016694e-01
1.6881715e-01 7.5789895e-03 -3.4664750e-01 2.5878614e-01
-2.5720572e-01 9.0466142e-01 1.1849405e-01 -2.0246394e-01
-1.7894763e+00 5.7957959e-01 -2.8315005e-01 -5.1621038e-01
-8.1775075e-01 3.2367364e-01 1.7695236e-01 -3.6416319e-01
4.4663388e-01 -7.0567787e-02 -9.4374639e-01 6.3808048e-01
1.0179565e+00 5.5874425e-01 1.1008784e-01 -5.4237461e-01
-1.7995259e-01 3.9758885e-01 -6.9487321e-01 -1.3104168e-01
1.1599298e+00 -7.1476007e-01 -5.9558660e-01 1.1344868e+00
9.2136502e-01 1.3823338e-01 1.3411709e-02 -4.4736382e-01
8.0133134e-01 1.4642148e-01 3.5573533e-01 -4.3863428e-01
-2.0681743e-01 7.2209913e-01 5.4918677e-02 9.3007302e-01
9.2369127e-01 1.6948743e-01 5.6131375e-01 9.4596088e-01
1.7428769e-01 -1.9216501e+00 -2.6334676e-01 7.3299265e-01
6.5576053e-01 -1.4452449e+00 5.9071851e-01 -2.0298772e-01
-6.6575545e-01 1.3717182e+00 4.0702450e-01 3.9279252e-01
1.3339846e+00 7.4237287e-01 1.2888215e-01 -6.8681508e-01
-1.0784316e+00 -2.7653009e-01 2.0056140e-01 4.6211410e-01
1.0272309e+00 -2.7804080e-01 -8.7091935e-01 5.5653322e-01
-7.3162961e-01 -2.8789389e-01 7.2686875e-01 1.4162135e+00
-1.2379622e+00 -1.2610326e+00 -6.2828749e-01 1.1131421e+00
-9.0400994e-01 1.4651908e-02 -1.1272966e+00 9.4533145e-01
-4.3409806e-01 1.5485795e+00 -1.6661348e-04 -2.6250106e-01
-7.4689768e-02 3.9043432e-01 -3.7469515e-01 -1.1234491e+00
-6.6361290e-01 2.9358709e-01 4.1584648e-02 2.4725467e-01
-4.7147217e-01 -7.1981865e-01 -1.6309930e+00 -4.6060273e-01
-5.2438354e-01 9.6195996e-01 9.1585493e-01 9.2368966e-01
1.7032051e-01 2.4243322e-01 5.6948596e-01 -9.9612847e-02
-9.5392622e-02 -1.1811163e+00 -8.6833209e-01 7.1132660e-02
1.8283673e-01 -1.1036862e-01 -3.7555906e-01 4.0592134e-01] | [10.521321296691895, 8.312297821044922] |
1bc30d4b-998a-466a-a3d1-58433ed5a969 | discriminative-feature-encoding-for-intrinsic | 2209.12155 | null | https://arxiv.org/abs/2209.12155v1 | https://arxiv.org/pdf/2209.12155v1.pdf | Discriminative feature encoding for intrinsic image decomposition | Intrinsic image decomposition is an important and long-standing computer vision problem. Given an input image, recovering the physical scene properties is ill-posed. Several physically motivated priors have been used to restrict the solution space of the optimization problem for intrinsic image decomposition. This work takes advantage of deep learning, and shows that it can solve this challenging computer vision problem with high efficiency. The focus lies in the feature encoding phase to extract discriminative features for different intrinsic layers from an input image. To achieve this goal, we explore the distinctive characteristics of different intrinsic components in the high dimensional feature embedding space. We define feature distribution divergence to efficiently separate the feature vectors of different intrinsic components. The feature distributions are also constrained to fit the real ones through a feature distribution consistency. In addition, a data refinement approach is provided to remove data inconsistency from the Sintel dataset, making it more suitable for intrinsic image decomposition. Our method is also extended to intrinsic video decomposition based on pixel-wise correspondences between adjacent frames. Experimental results indicate that our proposed network structure can outperform the existing state-of-the-art. | ['Feng Lu', 'Yunfei Liu', 'Zongji Wang'] | 2022-09-25 | null | null | null | null | ['intrinsic-image-decomposition'] | ['computer-vision'] | [ 1.42256260e-01 -1.09470867e-01 -1.04737073e-01 -2.33773485e-01
-4.93173480e-01 -1.31841049e-01 4.09935415e-01 -5.96827865e-01
-4.16984707e-01 4.31007862e-01 2.30436936e-01 3.74606073e-01
-5.16296625e-01 -5.02845466e-01 -6.90464616e-01 -1.23561478e+00
2.19036832e-01 8.56325701e-02 -1.01269707e-01 1.31915621e-02
2.82158941e-01 4.71283376e-01 -1.34051144e+00 8.31392109e-02
7.94039667e-01 1.00867128e+00 5.28487325e-01 3.47139418e-01
6.13553114e-02 4.70990658e-01 -3.28641161e-02 1.74175754e-01
4.75254655e-01 -4.26711112e-01 -6.70097113e-01 4.44673777e-01
5.32592118e-01 -4.54525739e-01 -6.85037553e-01 1.25174427e+00
1.71467662e-01 1.89655766e-01 7.82689214e-01 -1.22994518e+00
-6.98345423e-01 2.57104952e-02 -6.22973442e-01 9.00728479e-02
-1.49281947e-02 1.72839090e-02 1.20857990e+00 -1.03862262e+00
5.34784138e-01 1.08471453e+00 3.51506501e-01 3.79686028e-01
-1.33769083e+00 -3.73793721e-01 1.51998028e-01 4.78906542e-01
-1.39672577e+00 -4.23459232e-01 1.31417191e+00 -6.25198066e-01
6.76799476e-01 -4.25668359e-02 5.69354117e-01 1.00387990e+00
2.73061663e-01 7.20018864e-01 8.37828398e-01 -4.77221698e-01
1.60163149e-01 1.50704496e-02 3.33048373e-01 6.48677468e-01
2.99649835e-01 6.65590316e-02 -5.81106484e-01 4.36809883e-02
9.88505244e-01 1.26260996e-01 -8.51594687e-01 -7.40283906e-01
-1.33759832e+00 9.18006837e-01 4.41600055e-01 2.84141332e-01
-3.76598597e-01 4.95585874e-02 -5.10396026e-02 4.80588600e-02
2.12314427e-01 2.57700324e-01 -3.66217375e-01 -4.70734201e-03
-6.44840360e-01 7.15682209e-02 6.01175010e-01 7.11827576e-01
1.04387844e+00 1.84239239e-01 2.42471188e-01 7.30982661e-01
5.00786781e-01 4.06508058e-01 3.24762881e-01 -1.41154623e+00
4.61313725e-01 4.95955378e-01 1.84833825e-01 -1.47392142e+00
-3.56146276e-01 -3.88713509e-01 -1.27311361e+00 3.38211477e-01
3.99169803e-01 1.89945742e-01 -5.72754204e-01 1.76909602e+00
2.77945548e-01 2.83255339e-01 1.52934790e-01 1.17889512e+00
5.83027422e-01 7.37581015e-01 -6.55793130e-01 -2.44290799e-01
1.25122809e+00 -7.31679738e-01 -6.87711060e-01 -1.22305378e-01
1.84748933e-01 -5.61931729e-01 1.00009286e+00 4.80000526e-01
-8.75542045e-01 -8.59682977e-01 -1.19047713e+00 -2.46462449e-01
6.27358481e-02 3.32970500e-01 5.13091505e-01 4.27326441e-01
-6.85770810e-01 6.48591459e-01 -1.05819929e+00 -1.97796337e-02
2.57538199e-01 3.94147635e-01 -6.10203803e-01 -6.29595891e-02
-1.01040661e+00 4.75653470e-01 3.20789546e-01 4.50045049e-01
-6.25420690e-01 -6.18823111e-01 -1.08466792e+00 7.20984712e-02
2.72198111e-01 -7.80171394e-01 4.94046479e-01 -9.29716766e-01
-1.42780125e+00 6.78696215e-01 -2.19227582e-01 -1.64199933e-01
1.98539972e-01 -1.16505861e-01 -1.23937286e-01 4.99083817e-01
5.09834737e-02 3.79279882e-01 1.22641075e+00 -1.34706426e+00
-3.17110986e-01 -3.80611092e-01 1.77547365e-01 1.89915672e-01
-5.71972847e-01 -4.13057446e-01 -5.55498362e-01 -5.79127967e-01
5.62784255e-01 -9.16768491e-01 -1.41110241e-01 8.60235691e-02
-1.63299099e-01 1.22953184e-01 7.23544478e-01 -7.50661790e-01
6.71990931e-01 -2.33717084e+00 8.71432900e-01 4.03990261e-02
4.74690348e-01 -1.36025995e-01 -2.53403485e-01 1.03928268e-01
-1.42366230e-01 -1.65075034e-01 -2.70918787e-01 -2.87133306e-01
-1.28428593e-01 2.43147120e-01 -1.69769704e-01 8.86811674e-01
1.70700699e-01 5.22158682e-01 -5.57817638e-01 -3.13038737e-01
4.22404319e-01 8.93862307e-01 -7.38592327e-01 2.82345176e-01
1.17103457e-01 7.37053156e-01 -4.95691568e-01 9.43048298e-02
9.57818270e-01 -2.65390962e-01 -1.07890785e-01 -7.05768824e-01
5.69176190e-02 5.08913994e-02 -1.51094484e+00 2.05751801e+00
-4.24638808e-01 5.65387368e-01 4.64860648e-01 -1.48559153e+00
8.59796941e-01 7.59007111e-02 8.96611214e-01 -4.71976161e-01
1.22776225e-01 4.63806540e-02 1.25635132e-01 -6.28531992e-01
2.72888392e-01 -2.64065638e-02 2.55277097e-01 1.52539730e-01
1.97568923e-01 2.98122969e-03 8.92820880e-02 5.04478179e-02
5.78313291e-01 2.62065560e-01 7.23353550e-02 -5.11226475e-01
1.05918062e+00 -3.34528297e-01 1.05053866e+00 4.48839933e-01
1.25280870e-02 9.42136168e-01 3.76759857e-01 -6.47272229e-01
-9.45120990e-01 -9.81173158e-01 -2.39197373e-01 1.46366134e-01
4.57120568e-01 -3.91688347e-01 -7.84340739e-01 -4.53549653e-01
-2.98172474e-01 3.29828918e-01 -5.24940193e-01 -2.98154563e-01
-5.85728347e-01 -6.27464592e-01 -1.20384462e-01 3.52617234e-01
7.17540622e-01 -7.47714698e-01 -6.69695675e-01 1.31848708e-01
-5.44513166e-01 -1.35213923e+00 -4.77393627e-01 8.94422159e-02
-8.26501071e-01 -1.15433085e+00 -6.89551115e-01 -7.27619529e-01
7.86754370e-01 6.65337682e-01 7.92830110e-01 -3.12748775e-02
-4.45684880e-01 6.57173514e-01 -2.04346791e-01 3.32764417e-01
-9.07858610e-02 -8.96504596e-02 2.78720081e-01 5.31414807e-01
3.13730657e-01 -8.27638209e-01 -6.77270114e-01 4.12046909e-01
-9.95646894e-01 3.00260276e-01 4.10321325e-01 1.16737545e+00
6.47101462e-01 4.13759857e-01 1.71637461e-01 -2.96240300e-01
1.76020652e-01 -1.81712508e-01 -6.46317303e-01 9.34676677e-02
-1.66764215e-01 3.81987840e-01 7.92008281e-01 -3.28928530e-01
-1.11107779e+00 3.36611539e-01 -4.17430252e-02 -6.72555625e-01
-1.66387230e-01 5.22753298e-01 -6.52953267e-01 -9.96937156e-02
2.26035058e-01 5.84334791e-01 3.42725575e-01 -6.43422186e-01
2.42324084e-01 3.23243678e-01 4.16532457e-01 -7.06750929e-01
9.14088845e-01 8.73294532e-01 2.51886994e-01 -1.29224813e+00
-8.90849411e-01 -6.38063610e-01 -1.01174760e+00 -1.12093113e-01
9.97137725e-01 -9.94456291e-01 -7.45665669e-01 5.40468574e-01
-1.22123337e+00 -1.56311784e-02 -2.88959652e-01 7.34212220e-01
-7.39146471e-01 9.00094390e-01 -4.40972716e-01 -4.93976712e-01
-9.21451021e-03 -1.45975292e+00 1.01866984e+00 1.04719944e-01
3.09202313e-01 -1.08339381e+00 2.06341103e-01 4.33677912e-01
-3.01322900e-02 1.56816468e-01 6.76621318e-01 1.04350097e-01
-8.13939571e-01 1.93893269e-01 -2.98059553e-01 6.53456390e-01
4.20738071e-01 -1.97170638e-02 -8.10644805e-01 -5.56189001e-01
8.34607601e-01 -2.02911094e-01 1.19738352e+00 7.41746664e-01
1.16359627e+00 -2.37068072e-01 -1.11902822e-02 1.19342792e+00
1.53834236e+00 -7.08048567e-02 7.08686948e-01 4.07373399e-01
1.01703537e+00 8.84915471e-01 4.27188009e-01 3.07202816e-01
3.08061033e-01 7.04211891e-01 5.70690215e-01 -1.61922932e-01
-1.01775512e-01 7.02243224e-02 4.51544881e-01 9.29518700e-01
-1.78550422e-01 1.90114349e-01 -5.65053999e-01 4.60818887e-01
-2.00999498e+00 -9.93668854e-01 -1.81425989e-01 2.21150637e+00
4.48835254e-01 -2.22534519e-02 -2.26840243e-01 2.71362543e-01
4.71763760e-01 4.01712298e-01 -5.72095871e-01 1.96232930e-01
-2.20931262e-01 -1.78995028e-01 2.20344737e-01 7.24711299e-01
-1.15799963e+00 5.01557589e-01 5.19517040e+00 8.29122484e-01
-1.08164406e+00 -1.01908587e-01 4.80197906e-01 2.20804587e-01
-1.65376827e-01 1.14680484e-01 -8.08717787e-01 3.56586069e-01
3.79741102e-01 1.44657224e-01 4.85104889e-01 6.65111721e-01
2.05072522e-01 -6.32266477e-02 -1.11573851e+00 1.44275832e+00
2.74895936e-01 -1.43002880e+00 6.95605204e-02 4.56930459e-01
6.43316150e-01 -1.65957630e-01 -7.94616714e-03 -2.10863441e-01
-3.74062717e-01 -8.52116525e-01 5.97971976e-01 6.55053735e-01
5.55298984e-01 -7.12858558e-01 5.51404297e-01 3.67033899e-01
-1.28569305e+00 1.74265690e-02 -7.92686403e-01 -1.53714195e-01
1.07533589e-01 8.23746979e-01 -1.08015463e-01 7.01542735e-01
7.43583918e-01 1.24091220e+00 -4.18952346e-01 6.88387871e-01
-4.08254489e-02 2.19268516e-01 -3.56959105e-01 6.32564425e-01
1.69639766e-01 -9.07001197e-01 5.98368108e-01 8.21859002e-01
1.76196009e-01 1.37152761e-01 2.65784651e-01 1.23959804e+00
2.28713498e-01 -1.81100100e-01 -6.25041425e-01 1.86845407e-01
-2.52467424e-01 1.48069465e+00 -6.44033432e-01 1.15678813e-02
-6.00908875e-01 1.10589457e+00 2.37467498e-01 6.05743349e-01
-7.26721048e-01 -1.20170332e-01 9.28681910e-01 -1.42647535e-01
4.26418126e-01 -7.80114830e-01 -1.09846674e-01 -1.71764350e+00
3.09792697e-01 -7.48357654e-01 7.94847459e-02 -4.73486662e-01
-1.23612738e+00 4.60868359e-01 3.55297662e-02 -1.47184896e+00
-1.14088811e-01 -9.39127862e-01 -5.76859891e-01 8.73530984e-01
-1.71364796e+00 -1.04463947e+00 -5.66936970e-01 9.13228393e-01
5.22990048e-01 -2.25936607e-01 5.82358479e-01 1.66299388e-01
-6.46714211e-01 1.96838692e-01 4.06499922e-01 2.70393908e-01
3.08064312e-01 -1.03065324e+00 1.97537187e-02 9.49075401e-01
3.84081304e-01 6.80500150e-01 5.53944170e-01 -3.38780314e-01
-1.91683030e+00 -7.20945716e-01 3.14412326e-01 -1.03386685e-01
5.41629672e-01 -4.96739924e-01 -1.02505267e+00 3.60994846e-01
1.91249564e-01 2.00931624e-01 5.45683920e-01 -1.44105002e-01
-3.46087337e-01 -3.41498315e-01 -7.87114024e-01 3.75479668e-01
9.51702476e-01 -5.80487669e-01 -5.16153336e-01 1.68846726e-01
4.86130118e-01 -8.23689103e-02 -7.78433442e-01 3.29755813e-01
5.18562138e-01 -1.24085748e+00 1.31946588e+00 -3.68994117e-01
4.87268120e-01 -4.93161201e-01 -3.23806584e-01 -1.09911430e+00
-6.06361926e-01 -5.40995061e-01 -1.75423712e-01 1.23193574e+00
-7.71515369e-02 -5.85030556e-01 7.55600810e-01 6.10977829e-01
1.05855331e-01 -5.53054869e-01 -1.01810706e+00 -9.05929148e-01
1.24646723e-02 -2.94679165e-01 2.87892204e-02 8.75511825e-01
-2.80814320e-01 4.08916146e-01 -5.65634370e-01 4.73810285e-01
1.15096033e+00 4.71670061e-01 7.40959883e-01 -1.27384639e+00
-5.51005661e-01 -3.52963448e-01 -4.91251945e-01 -1.38763845e+00
4.35279846e-01 -8.27692688e-01 -6.26242235e-02 -1.36279750e+00
3.67171198e-01 -2.37114921e-01 -3.37961107e-01 1.06366955e-01
9.97939482e-02 1.05410203e-01 3.05991292e-01 3.88881505e-01
-1.56502113e-01 1.17480099e+00 1.26039505e+00 -3.31378609e-01
-1.53846353e-01 -2.31001332e-01 -4.53823626e-01 8.64855349e-01
7.70135701e-01 -2.77794302e-01 -4.92848098e-01 -5.81384420e-01
1.23270929e-01 8.78474035e-04 4.85571682e-01 -9.87866580e-01
1.59583062e-01 -3.62834811e-01 3.42422217e-01 -5.36735475e-01
5.60026348e-01 -1.24105179e+00 8.57168958e-02 3.30047756e-01
-7.49211758e-02 -3.38402271e-01 -8.52652267e-02 6.80033565e-01
-4.30351257e-01 -4.35796201e-01 8.84696901e-01 -9.47825611e-02
-6.04423642e-01 4.28398162e-01 -1.13328449e-01 2.53792349e-02
7.16590941e-01 -3.96475375e-01 8.26500729e-02 -1.96546897e-01
-5.73776305e-01 6.48532882e-02 5.04412472e-01 2.90639818e-01
9.91794527e-01 -1.43931150e+00 -6.70160830e-01 5.90367436e-01
9.03901085e-02 1.11618824e-01 3.80234778e-01 9.61296976e-01
-4.53138053e-01 2.62882888e-01 -5.15710115e-01 -1.04532719e+00
-1.06263530e+00 5.71863115e-01 4.31162834e-01 -5.10830656e-02
-1.02696323e+00 5.49013734e-01 7.79984057e-01 -2.76342511e-01
2.15866223e-01 -4.63295937e-01 -1.47616506e-01 -7.30947703e-02
5.36043584e-01 1.78201497e-01 -2.35320210e-01 -9.12788391e-01
-2.78404087e-01 1.20125842e+00 -3.38021591e-02 -8.80146921e-02
1.55697906e+00 -3.92641157e-01 -2.98525900e-01 2.44142801e-01
1.66122842e+00 -1.33687332e-01 -1.74950445e+00 -3.49561572e-01
-2.57953465e-01 -6.81308925e-01 3.79920959e-01 1.14499293e-01
-1.52600849e+00 1.08059216e+00 4.32006508e-01 1.73265897e-02
1.20767212e+00 -2.03461677e-01 6.35138690e-01 3.97432774e-01
2.85771757e-01 -9.85983849e-01 1.17505223e-01 4.01504695e-01
1.13750088e+00 -1.45481002e+00 1.89262524e-01 -5.29418707e-01
-2.73002893e-01 1.40981519e+00 5.87880969e-01 -4.82345372e-01
8.06242406e-01 -3.13187130e-02 -2.64681250e-01 -2.71957427e-01
-3.21037024e-01 5.45450812e-03 5.13290823e-01 6.11603081e-01
1.64785609e-01 -3.45441520e-01 -2.38841549e-01 4.84716058e-01
1.66193873e-01 -3.84140760e-01 5.99143267e-01 4.46537375e-01
-2.06508741e-01 -1.06927478e+00 -4.01671946e-01 7.44720846e-02
-1.43810779e-01 8.62338245e-02 -1.68284122e-02 7.10637927e-01
5.64012751e-02 7.30955780e-01 -8.70580748e-02 -1.65441677e-01
2.94370521e-02 -1.98087931e-01 6.39159024e-01 -3.24321628e-01
8.76002684e-02 4.60710883e-01 -3.95080507e-01 -6.54157281e-01
-8.21261048e-01 -6.92523599e-01 -1.16207004e+00 1.63288787e-01
-1.98609307e-01 5.06343581e-02 5.48835635e-01 8.48565876e-01
2.84921259e-01 4.21406329e-01 8.54926348e-01 -1.29090941e+00
-5.59004605e-01 -4.83712435e-01 -7.54518211e-01 5.25493920e-01
7.64283299e-01 -9.48188245e-01 -7.10459173e-01 3.47683758e-01] | [9.394131660461426, -2.5944108963012695] |
e5eb5bef-6994-4aef-9357-36c7e76d7716 | ceil-a-general-classification-enhanced | 2304.11061 | null | https://arxiv.org/abs/2304.11061v1 | https://arxiv.org/pdf/2304.11061v1.pdf | CEIL: A General Classification-Enhanced Iterative Learning Framework for Text Clustering | Text clustering, as one of the most fundamental challenges in unsupervised learning, aims at grouping semantically similar text segments without relying on human annotations. With the rapid development of deep learning, deep clustering has achieved significant advantages over traditional clustering methods. Despite the effectiveness, most existing deep text clustering methods rely heavily on representations pre-trained in general domains, which may not be the most suitable solution for clustering in specific target domains. To address this issue, we propose CEIL, a novel Classification-Enhanced Iterative Learning framework for short text clustering, which aims at generally promoting the clustering performance by introducing a classification objective to iteratively improve feature representations. In each iteration, we first adopt a language model to retrieve the initial text representations, from which the clustering results are collected using our proposed Category Disentangled Contrastive Clustering (CDCC) algorithm. After strict data filtering and aggregation processes, samples with clean category labels are retrieved, which serve as supervision information to update the language model with the classification objective via a prompt learning approach. Finally, the updated language model with improved representation ability is used to enhance clustering in the next iteration. Extensive experiments demonstrate that the CEIL framework significantly improves the clustering performance over iterations, and is generally effective on various clustering algorithms. Moreover, by incorporating CEIL on CDCC, we achieve the state-of-the-art clustering performance on a wide range of short text clustering benchmarks outperforming other strong baseline methods. | ['Haijiang Wu', 'Di Niu', 'Yinglong Ma', 'Mengzhen Wang', 'Mingjun Zhao'] | 2023-04-20 | null | null | null | null | ['classification', 'deep-clustering', 'text-clustering', 'deep-clustering', 'short-text-clustering'] | ['methodology', 'miscellaneous', 'natural-language-processing', 'natural-language-processing', 'natural-language-processing'] | [-8.27938393e-02 -4.10155892e-01 -1.28885165e-01 -3.72985691e-01
-7.88981855e-01 -4.05772507e-01 7.37841964e-01 4.50448513e-01
-4.08012360e-01 1.54240668e-01 3.63663316e-01 2.64176279e-02
-3.08171034e-01 -4.82334614e-01 -2.71531135e-01 -1.06802011e+00
3.02433282e-01 8.38794708e-01 -2.38422915e-01 2.67745018e-01
2.83957839e-01 -1.06083117e-02 -1.50330806e+00 3.00814629e-01
1.21594822e+00 6.00424349e-01 3.81399959e-01 1.51324704e-01
-4.70663726e-01 6.50293052e-01 -5.09203374e-01 -2.43396953e-01
-1.21364608e-01 -4.53307360e-01 -9.09053206e-01 4.37934935e-01
-1.76803663e-01 -6.99338764e-02 -2.94113457e-01 1.01081216e+00
3.72671843e-01 5.59412122e-01 9.13786650e-01 -1.11963940e+00
-7.05965042e-01 1.20442069e+00 -8.60984743e-01 -2.13071957e-01
5.54923527e-02 -2.75130361e-01 1.20759606e+00 -1.02186191e+00
3.78229350e-01 1.25222707e+00 5.05599320e-01 5.99741697e-01
-1.42689216e+00 -8.08612287e-01 6.20951355e-01 1.33864179e-01
-1.67103004e+00 -2.94205993e-01 9.22755182e-01 -3.45058799e-01
4.94636506e-01 1.39864627e-02 1.76816911e-01 9.11756873e-01
-4.75779116e-01 1.19518042e+00 6.37156606e-01 -3.22175503e-01
3.68311048e-01 7.23520666e-02 6.47527516e-01 4.40590471e-01
2.40967169e-01 -4.97836560e-01 -2.49197170e-01 3.92044289e-03
1.52331918e-01 4.36817378e-01 -2.71171838e-01 -5.01710474e-01
-1.37937927e+00 9.48799431e-01 7.92055309e-01 5.51439166e-01
-2.68252730e-01 5.71468025e-02 5.63128591e-01 -9.20496359e-02
5.51316619e-01 4.28284705e-01 -3.27593416e-01 5.21824621e-02
-1.20251739e+00 -2.49894708e-02 4.43727732e-01 8.26953471e-01
8.02568495e-01 -3.93906832e-01 -1.59294859e-01 1.07699323e+00
4.57201838e-01 1.37567803e-01 7.14006782e-01 -8.39268327e-01
6.37338758e-01 1.08574069e+00 -2.44702771e-01 -1.01948738e+00
-4.21654940e-01 -7.65777469e-01 -1.34973824e+00 -3.47317398e-01
1.65496394e-01 -1.01955449e-02 -8.23758006e-01 1.58864617e+00
2.19744533e-01 1.14005454e-01 2.41203651e-01 7.69821227e-01
8.10745418e-01 8.22573125e-01 1.38014197e-01 -2.92843461e-01
1.19404042e+00 -9.50053990e-01 -8.84121060e-01 5.16135804e-02
8.21963847e-01 -6.24526203e-01 1.01554763e+00 4.41458464e-01
-5.15909910e-01 -5.46119571e-01 -8.60145986e-01 -9.77963731e-02
-5.22978008e-01 3.72576773e-01 5.62893748e-01 4.93999600e-01
-9.99005258e-01 3.23216319e-01 -1.01506782e+00 -3.43280673e-01
6.47956848e-01 3.97916168e-01 -4.44170423e-02 -3.12533945e-01
-9.10959661e-01 1.41947806e-01 7.37875640e-01 8.81885737e-02
-6.50301993e-01 -5.53577423e-01 -7.77147293e-01 4.02862102e-01
4.83129233e-01 -4.03999984e-01 8.28300238e-01 -7.70361364e-01
-1.33559179e+00 7.57255018e-01 -4.15259004e-01 -2.38514230e-01
2.74771929e-01 -3.01037639e-01 -2.57957667e-01 2.12008297e-01
3.71757925e-01 9.12713945e-01 6.81626439e-01 -1.82123804e+00
-6.63555443e-01 -4.23096806e-01 -4.23599213e-01 4.96874958e-01
-7.45928764e-01 -2.03685567e-01 -1.12269855e+00 -7.37658918e-01
3.92888248e-01 -8.14745426e-01 -3.86918396e-01 -5.50667882e-01
-5.79132199e-01 -7.80407727e-01 1.03554463e+00 -4.07503366e-01
1.45802045e+00 -2.32166004e+00 4.49641913e-01 3.23001146e-01
6.81966245e-01 1.35192811e-01 -2.20496561e-02 2.08313927e-01
-7.33202919e-02 3.20212275e-01 -4.34488446e-01 -9.15454745e-01
1.97736055e-01 -9.54108834e-02 -2.19831660e-01 4.23340917e-01
-4.72699180e-02 8.14046562e-01 -9.85327363e-01 -7.28862882e-01
3.83277714e-01 3.01075518e-01 -5.71500301e-01 2.18016341e-01
-2.52971560e-01 3.73482078e-01 -3.45425546e-01 2.49484524e-01
7.32629418e-01 -6.63243771e-01 3.88633072e-01 -8.07908699e-02
1.09032102e-01 6.20947368e-02 -1.14242005e+00 1.97827530e+00
-2.47384861e-01 5.70229173e-01 5.32498658e-02 -1.48903418e+00
8.23699415e-01 1.76809102e-01 8.13967288e-01 -3.38061303e-01
2.01320365e-01 -1.12096272e-01 -1.57311067e-01 -1.47914439e-01
4.24722373e-01 1.89265251e-01 -2.92212665e-01 8.60982716e-01
-1.63710415e-02 1.29490972e-01 3.18264186e-01 8.42470109e-01
7.58846462e-01 -2.40373418e-01 -1.21031620e-01 -3.56428772e-01
6.70546055e-01 4.39463928e-02 4.85823184e-01 5.50842702e-01
-8.81325975e-02 6.40650153e-01 3.58688682e-01 -1.41891064e-02
-5.85548759e-01 -1.00186586e+00 -1.72735125e-01 1.28093719e+00
2.72510827e-01 -7.04870403e-01 -9.65856493e-01 -8.97852123e-01
-2.19557673e-01 5.45687377e-01 -6.07644379e-01 -3.58480036e-01
-2.87048399e-01 -1.11977410e+00 4.89400327e-01 4.86562848e-01
7.54532218e-01 -7.98523366e-01 1.56555146e-01 1.15096085e-01
-5.38949609e-01 -8.01486254e-01 -5.40372729e-01 3.70063961e-01
-8.47756088e-01 -1.03106821e+00 -6.59654796e-01 -1.12447727e+00
9.84240294e-01 7.07592428e-01 8.94160211e-01 3.58130485e-01
8.58531520e-02 3.22473794e-01 -7.04193771e-01 1.86617523e-01
-2.47931927e-01 5.33449650e-01 1.47774341e-02 2.03313947e-01
7.57361472e-01 -2.63610214e-01 -5.72029352e-01 2.14348510e-01
-1.04848659e+00 1.18981294e-01 4.44588959e-01 8.37002933e-01
4.54854429e-01 7.50022113e-01 6.83550775e-01 -1.05046403e+00
6.43382370e-01 -6.08135641e-01 -2.73701280e-01 1.83968872e-01
-7.05069363e-01 1.43387735e-01 9.18213964e-01 -3.95263404e-01
-1.20392454e+00 1.72462463e-01 1.27634227e-01 -3.83122146e-01
-2.63793886e-01 8.80345762e-01 -4.89894331e-01 7.07918167e-01
5.04347503e-01 3.31883341e-01 -6.98112622e-02 -6.36235237e-01
5.86740673e-01 1.04363859e+00 5.66332817e-01 -7.16256022e-01
7.13296115e-01 5.96539259e-01 -5.57805657e-01 -5.65669596e-01
-9.58604038e-01 -9.65345204e-01 -1.13726246e+00 -3.34944800e-02
1.06936657e+00 -1.15406907e+00 -6.42964482e-01 5.76833844e-01
-7.66278207e-01 -4.10999238e-01 2.32055396e-01 4.31421608e-01
-6.70512393e-02 6.46662891e-01 -6.55567706e-01 -4.80378747e-01
-1.71513960e-01 -1.11653113e+00 1.15461338e+00 2.09271595e-01
-1.13727435e-01 -1.30711102e+00 -2.04149127e-01 5.59655786e-01
-6.58619702e-02 -2.68425532e-02 1.16136301e+00 -8.32933009e-01
-4.08915311e-01 -1.50488123e-01 -3.04759145e-01 1.41963229e-01
4.12258536e-01 -5.47234453e-02 -8.86227548e-01 -5.43588817e-01
-2.32910901e-01 -2.61466444e-01 1.33003402e+00 3.16515148e-01
1.70470381e+00 -1.86969526e-03 -7.59964049e-01 5.44873595e-01
1.25002635e+00 7.65194967e-02 3.65563691e-01 2.94061191e-02
1.16255784e+00 5.94776809e-01 4.17270660e-01 4.12996531e-01
5.79480827e-01 3.78064990e-01 1.28148526e-01 -9.57519859e-02
-1.26344124e-02 -2.26649389e-01 2.44580775e-01 1.28470874e+00
3.38085562e-01 -2.95589715e-01 -1.15382075e+00 5.85452139e-01
-2.09894204e+00 -8.15247238e-01 -3.20352107e-01 2.01351309e+00
9.51945543e-01 -4.91423942e-02 5.21615520e-02 3.71274829e-01
1.08764267e+00 -2.94061489e-02 -6.80401742e-01 3.92563611e-01
1.41802356e-01 -4.99513522e-02 -9.59876180e-02 2.90669918e-01
-1.44591880e+00 1.18293774e+00 5.45903921e+00 1.04038739e+00
-8.63498390e-01 6.13152236e-02 6.69338763e-01 2.67595071e-02
-2.13957757e-01 -1.02350481e-01 -6.91561699e-01 6.56956017e-01
7.08269477e-01 -1.06733449e-01 4.66362298e-01 6.81042910e-01
3.05621207e-01 7.33778849e-02 -1.15922809e+00 1.08332264e+00
1.61375836e-01 -1.23932278e+00 2.55922109e-01 1.80674791e-01
9.63771224e-01 -1.96237147e-01 1.78186730e-01 6.11781001e-01
7.95454204e-01 -9.38802838e-01 3.23410034e-01 2.29363054e-01
6.32155240e-01 -1.10320568e+00 7.10678279e-01 4.33573037e-01
-1.33843946e+00 -1.19554244e-01 -4.83267486e-01 1.94655776e-01
-3.08202922e-01 8.55029762e-01 -5.48173368e-01 6.40411794e-01
7.91901827e-01 1.34803247e+00 -8.86457026e-01 6.80088699e-01
-5.87804690e-02 9.02252197e-01 -1.11693405e-01 -1.45134166e-01
3.81641388e-01 -4.38026667e-01 5.57854250e-02 1.32758546e+00
-4.00476605e-02 7.76958689e-02 5.01665175e-01 9.41738069e-01
-4.80895191e-01 1.59891561e-01 -2.94852585e-01 -5.28340712e-02
6.86238706e-01 1.36036420e+00 -1.31480229e+00 -6.14121079e-01
-2.27004841e-01 9.48546946e-01 5.38401186e-01 5.57192385e-01
-7.37454355e-01 -5.72776258e-01 4.23205018e-01 -4.25822347e-01
2.45827973e-01 -1.95061848e-01 -5.33469677e-01 -1.34965897e+00
-2.24044427e-01 -8.54165912e-01 6.96453035e-01 -4.04967010e-01
-1.53194356e+00 2.88489252e-01 -1.86338171e-01 -1.18066359e+00
3.58487889e-02 -3.10157001e-01 -5.72696388e-01 4.28614795e-01
-1.11468613e+00 -9.84400690e-01 -4.31215107e-01 8.14548016e-01
7.16169417e-01 -3.16638082e-01 6.56925857e-01 4.16866422e-01
-1.11178982e+00 6.60021305e-01 7.86960125e-01 4.47130710e-01
7.88178205e-01 -1.54903471e+00 -8.58802944e-02 9.35333371e-01
1.78150192e-01 9.30282652e-01 1.37927383e-01 -6.66300714e-01
-1.02437341e+00 -1.54786718e+00 5.09794056e-01 -4.99338418e-01
4.36035305e-01 -7.14668572e-01 -1.20096993e+00 5.42557538e-01
2.43532389e-01 -4.43783253e-01 1.01118338e+00 4.42400008e-01
-3.70651186e-01 -9.14819166e-02 -7.10489035e-01 6.10045135e-01
8.78522158e-01 -5.38339078e-01 -7.18700826e-01 3.59575450e-01
9.46671784e-01 5.13520464e-02 -7.20598936e-01 4.54137959e-02
1.63855050e-02 -5.94637573e-01 8.51481795e-01 -3.05260211e-01
4.74726081e-01 -4.96796727e-01 -8.42003971e-02 -1.38931894e+00
-5.41159213e-01 -4.16224957e-01 3.21501680e-02 1.74878478e+00
2.28977084e-01 -2.71172464e-01 7.80446470e-01 4.20212477e-01
-2.07271367e-01 -3.67154092e-01 -4.83413309e-01 -4.32004869e-01
4.43345428e-01 -4.07107651e-01 6.39852345e-01 1.37044501e+00
2.45853409e-01 6.41684055e-01 -2.39656661e-02 1.23381473e-01
8.33511591e-01 3.52597713e-01 7.96141088e-01 -1.60209548e+00
2.08093151e-01 -7.83899009e-01 6.56642616e-02 -1.26775539e+00
6.08120799e-01 -1.44903541e+00 3.46388966e-01 -1.78412449e+00
6.56102240e-01 -6.29492700e-01 -4.11805123e-01 3.44033390e-01
-7.42618918e-01 1.04052108e-02 7.59527907e-02 6.42392635e-01
-1.27496600e+00 8.54946494e-01 8.52509499e-01 -3.62814218e-01
-3.91360432e-01 -1.34770563e-02 -1.13199949e+00 5.52524507e-01
7.18776464e-01 -4.91991431e-01 -4.24489498e-01 -4.40628171e-01
-1.14569096e-02 -5.14869511e-01 -9.50196944e-03 -9.37613904e-01
5.42208612e-01 2.19358772e-01 5.08180380e-01 -9.24207807e-01
-5.13913743e-02 -8.19409907e-01 -2.68807918e-01 3.86405736e-01
-6.89550459e-01 -3.73532742e-01 -1.70911834e-01 8.70249748e-01
-3.56606990e-01 -1.13879770e-01 7.45640337e-01 1.48362145e-01
-6.38800502e-01 3.71404171e-01 -6.23790443e-01 3.97105552e-02
8.20432305e-01 1.33145601e-01 -6.36794344e-02 -1.67499095e-01
-7.43478894e-01 8.74335170e-01 5.55050790e-01 4.38718349e-01
4.71533626e-01 -1.38171840e+00 -6.19724631e-01 -3.89783159e-02
1.63054675e-01 5.13611794e-01 1.25397056e-01 6.73284888e-01
-2.03032851e-01 4.26217794e-01 4.60171789e-01 -8.90742600e-01
-9.91623402e-01 9.58572030e-01 9.01020020e-02 -5.03430128e-01
-6.56331003e-01 5.71710408e-01 4.36178416e-01 -7.99111903e-01
6.33480608e-01 -2.04506084e-01 -4.73546296e-01 2.99963593e-01
3.91526967e-01 2.62818158e-01 3.26023623e-02 -4.95950043e-01
-3.50925744e-01 5.31361938e-01 -4.27254885e-01 5.28885499e-02
1.33618307e+00 -5.24159491e-01 -2.78711915e-01 4.54171479e-01
1.34290826e+00 -1.90322742e-01 -1.18334877e+00 -5.35665572e-01
2.98946887e-01 -1.18904598e-01 2.22659245e-01 -6.32422924e-01
-1.25398803e+00 1.11799204e+00 3.99452776e-01 2.26105675e-01
1.17956901e+00 2.17456967e-01 6.81478322e-01 5.99660039e-01
-9.83110145e-02 -1.27141201e+00 5.23093939e-01 4.81633544e-01
3.71745646e-01 -1.39294302e+00 4.16730382e-02 -2.87637830e-01
-7.72264540e-01 9.29003716e-01 6.55710936e-01 5.98715134e-02
8.15950096e-01 -4.57076542e-02 1.02566950e-01 -2.85585463e-01
-5.51580429e-01 -4.92748380e-01 1.75896227e-01 6.19041860e-01
5.81304610e-01 1.71347931e-01 -1.27781630e-02 8.59748065e-01
4.30846177e-02 -5.51203549e-01 2.43168741e-01 4.45111066e-01
-3.96041483e-01 -1.00172102e+00 -4.73916084e-01 6.49184883e-01
-2.35584587e-01 -5.71393361e-03 -6.53862894e-01 5.82679749e-01
3.09464168e-02 1.41492212e+00 2.62228668e-01 -4.36094582e-01
-1.78990841e-01 9.42084566e-02 -1.63838729e-01 -8.30927253e-01
-5.03608465e-01 3.64534229e-01 -5.19623876e-01 -1.66370586e-01
-5.51355004e-01 -8.35230291e-01 -1.70851219e+00 -3.69830787e-01
-5.52296460e-01 5.75520337e-01 3.42237294e-01 1.08064330e+00
5.02593040e-01 6.07030392e-01 9.43530917e-01 -8.00897241e-01
-1.18253611e-01 -9.84953225e-01 -5.49208939e-01 8.64695489e-01
7.52398893e-02 -6.69262588e-01 -5.00250578e-01 2.97280341e-01] | [10.414748191833496, 6.712684154510498] |
902e5aec-246b-419b-a031-2fd4195b96ef | partial-domain-adaptation-without-domain | 2108.12867 | null | https://arxiv.org/abs/2108.12867v2 | https://arxiv.org/pdf/2108.12867v2.pdf | Partial Domain Adaptation without Domain Alignment | Unsupervised domain adaptation (UDA) aims to transfer knowledge from a well-labeled source domain to a different but related unlabeled target domain with identical label space. Currently, the main workhorse for solving UDA is domain alignment, which has proven successful. However, it is often difficult to find an appropriate source domain with identical label space. A more practical scenario is so-called partial domain adaptation (PDA) in which the source label set or space subsumes the target one. Unfortunately, in PDA, due to the existence of the irrelevant categories in the source domain, it is quite hard to obtain a perfect alignment, thus resulting in mode collapse and negative transfer. Although several efforts have been made by down-weighting the irrelevant source categories, the strategies used tend to be burdensome and risky since exactly which irrelevant categories are unknown. These challenges motivate us to find a relatively simpler alternative to solve PDA. To achieve this, we first provide a thorough theoretical analysis, which illustrates that the target risk is bounded by both model smoothness and between-domain discrepancy. Considering the difficulty of perfect alignment in solving PDA, we turn to focus on the model smoothness while discard the riskier domain alignment to enhance the adaptability of the model. Specifically, we instantiate the model smoothness as a quite simple intra-domain structure preserving (IDSP). To our best knowledge, this is the first naive attempt to address the PDA without domain alignment. Finally, our empirical results on multiple benchmark datasets demonstrate that IDSP is not only superior to the PDA SOTAs by a significant margin on some benchmarks (e.g., +10% on Cl->Rw and +8% on Ar->Rw ), but also complementary to domain alignment in the standard UDA | ['Songcan Chen', 'Weikai Li'] | 2021-08-29 | null | null | null | null | ['partial-domain-adaptation'] | ['methodology'] | [ 5.23346484e-01 2.21380293e-01 -3.22185934e-01 -2.27164268e-01
-8.45020890e-01 -7.75625706e-01 3.84962648e-01 1.16272300e-01
-2.33147651e-01 8.28822792e-01 -1.58903748e-01 -2.84500420e-01
-2.38431886e-01 -6.04038835e-01 -6.50294542e-01 -8.71112108e-01
2.46521756e-01 6.05682313e-01 2.85546452e-01 -2.86296517e-01
1.37007356e-01 3.12236309e-01 -1.31069279e+00 -1.52865216e-01
1.19128346e+00 8.31190825e-01 2.18359917e-01 2.17331760e-02
-2.39425197e-01 3.63550097e-01 -4.29652542e-01 -5.46851337e-01
5.21492302e-01 -6.59632623e-01 -1.11120951e+00 2.87338704e-01
2.51495659e-01 -9.70977172e-02 2.23738074e-01 1.28397608e+00
3.49195272e-01 1.41918063e-01 8.21513236e-01 -1.34562731e+00
-4.24664736e-01 4.39956278e-01 -6.77897632e-01 -8.92433450e-02
2.32499033e-01 -1.54919073e-01 1.11430073e+00 -7.11645901e-01
6.56715155e-01 8.88832390e-01 6.20401561e-01 6.71320975e-01
-1.39633000e+00 -6.68983161e-01 3.86102647e-01 -6.63560331e-02
-1.39343190e+00 -2.42005393e-01 9.40033555e-01 -4.94328439e-01
5.21278560e-01 2.06402004e-01 8.51158947e-02 1.06384659e+00
-1.86232135e-01 6.12946093e-01 1.33077860e+00 -6.00541532e-01
4.65984106e-01 4.77397561e-01 4.13320094e-01 2.85247773e-01
2.13324308e-01 -3.32058147e-02 -1.02334023e-01 -2.78042316e-01
5.66848814e-01 -1.87083751e-01 -2.38100275e-01 -1.03732061e+00
-1.02285457e+00 8.50624859e-01 2.60918170e-01 3.04182589e-01
-1.73533991e-01 -5.30938804e-01 2.78934389e-01 5.95545888e-01
4.13745731e-01 6.83398128e-01 -6.48349404e-01 -5.49355373e-02
-6.23311460e-01 2.70546019e-01 7.41823554e-01 1.06358755e+00
9.67144847e-01 -1.80717453e-01 2.43415594e-01 9.43095386e-01
1.27638131e-01 4.12636995e-01 4.29301560e-01 -8.89682114e-01
6.09778583e-01 5.90042353e-01 2.98206002e-01 -7.80022860e-01
-2.99959779e-01 -3.83671552e-01 -8.34990501e-01 2.27269158e-01
1.02800179e+00 -8.02797750e-02 -7.11888015e-01 2.19214988e+00
4.06611443e-01 4.32726145e-02 2.65183330e-01 1.00872719e+00
2.21226528e-01 4.06020254e-01 1.21437289e-01 -4.11405563e-01
1.27913713e+00 -8.75029624e-01 -4.67551291e-01 -4.58249509e-01
8.64544749e-01 -7.07214773e-01 1.24337065e+00 3.60762626e-01
-8.55774999e-01 -4.88384962e-01 -1.04170072e+00 1.06546253e-01
-2.61850268e-01 -8.91193897e-02 4.56986427e-01 7.45875895e-01
-7.08426178e-01 5.10060668e-01 -5.74906647e-01 -6.96001768e-01
2.36077920e-01 4.75933403e-01 -6.05729818e-01 -1.98339820e-01
-1.27383602e+00 9.12669837e-01 4.68098968e-01 -4.41745847e-01
-4.06732976e-01 -7.19696283e-01 -6.48901761e-01 -4.47059348e-02
6.41068876e-01 -5.01593232e-01 1.17567015e+00 -1.26420331e+00
-1.59086275e+00 9.75574434e-01 -2.42327392e-01 -4.88173783e-01
6.32402480e-01 -1.03655562e-01 -2.82852173e-01 -2.26007074e-01
1.74238324e-01 5.04056573e-01 7.38551974e-01 -1.29598081e+00
-7.48457432e-01 -4.15057182e-01 2.84353018e-01 3.98116678e-01
-5.71040809e-01 -2.77734362e-02 -3.39394093e-01 -6.22519493e-01
2.07194403e-01 -1.13720751e+00 -2.12017417e-01 -2.17248917e-01
-2.40355223e-01 -2.78380424e-01 5.40554643e-01 -5.04261851e-01
1.26841605e+00 -2.29217434e+00 3.27859133e-01 2.46150061e-01
1.38477549e-01 2.96605021e-01 -1.16050266e-01 2.00088203e-01
-4.28785533e-01 -8.83802306e-03 -6.43402100e-01 -1.65451437e-01
-9.59109887e-03 2.16446534e-01 -5.35239995e-01 4.04411554e-01
1.42541930e-01 4.73438591e-01 -9.41211998e-01 -3.70041728e-01
-4.44632843e-02 -4.08217777e-03 -6.27558112e-01 8.96688029e-02
-1.67833313e-01 5.38958788e-01 -4.72352028e-01 4.83656913e-01
8.21983635e-01 -4.25420612e-01 5.29130220e-01 3.46714281e-03
7.95249641e-02 2.61387616e-01 -1.44250309e+00 1.64745247e+00
-2.39286378e-01 1.71083733e-01 4.41749170e-02 -1.36896515e+00
1.02849054e+00 8.75134021e-02 6.70704067e-01 -6.07173860e-01
-2.91070212e-02 4.26223367e-01 3.83091252e-03 -1.81060031e-01
3.78421187e-01 -4.77872312e-01 -2.53654748e-01 3.02123576e-01
-1.19909965e-01 1.10497214e-01 1.06892157e-02 -7.71888569e-02
9.70140934e-01 2.43340239e-01 6.55155718e-01 -4.04913396e-01
6.67234778e-01 2.25484863e-01 8.84325683e-01 5.38328886e-01
-4.31508303e-01 6.42713428e-01 5.79398990e-01 -1.12181403e-01
-1.00543070e+00 -1.17850208e+00 -1.79238498e-01 1.06384277e+00
4.49070364e-01 -1.11488536e-01 -8.10550690e-01 -1.10621178e+00
-1.48715734e-01 6.06415689e-01 -3.63940299e-01 -1.97044939e-01
-6.04043424e-01 -7.47329772e-01 3.76116276e-01 4.44797188e-01
4.96396750e-01 -7.37878025e-01 -1.90390453e-01 2.41926029e-01
-3.35054785e-01 -1.03948665e+00 -4.19867963e-01 4.00070637e-01
-9.32805359e-01 -1.00395286e+00 -9.73911226e-01 -9.30042863e-01
7.95885026e-01 2.98386008e-01 9.76826489e-01 -4.02962089e-01
3.33866090e-01 8.06536451e-02 -4.33093250e-01 -2.79749334e-01
-4.82652962e-01 4.02871758e-01 2.12387502e-01 -2.83914065e-04
5.29264390e-01 -6.04678333e-01 -2.87191629e-01 7.20563591e-01
-7.98369765e-01 -4.83782962e-02 5.48099935e-01 9.11308110e-01
6.20832026e-01 1.96550593e-01 8.10632229e-01 -1.15298545e+00
5.34876049e-01 -6.35782540e-01 -6.83473945e-01 2.84501284e-01
-8.43218744e-01 2.24839728e-02 9.28818226e-01 -6.65295482e-01
-9.88280714e-01 4.05167222e-01 4.01947089e-03 -3.75048637e-01
-3.90677005e-01 3.40109199e-01 -5.49711049e-01 1.23254687e-01
8.78235757e-01 1.23700395e-01 1.17319137e-01 -5.22907913e-01
3.26172948e-01 6.29000485e-01 4.40378994e-01 -6.75452888e-01
9.53059077e-01 4.50612903e-01 -1.89740255e-01 -5.68456709e-01
-8.76373887e-01 -5.89664400e-01 -6.79110289e-01 2.45388061e-01
6.45933807e-01 -7.37582743e-01 -1.78237811e-01 3.15426618e-01
-8.63396883e-01 -3.29908967e-01 -4.26017970e-01 3.00501615e-01
-6.52874112e-01 7.98483014e-01 -1.78907260e-01 -4.76797462e-01
-5.66178039e-02 -1.15024590e+00 6.88695729e-01 5.67645766e-02
-3.67924958e-01 -9.79546726e-01 9.40869451e-02 3.23669344e-01
1.79273710e-01 9.30622220e-02 1.09820867e+00 -1.00009525e+00
-2.40111083e-01 1.43538211e-02 -2.17653796e-01 4.09359485e-01
4.78476852e-01 -4.71473157e-01 -8.21637273e-01 -4.94652778e-01
1.22248709e-01 -1.60788462e-01 5.15944421e-01 1.72049448e-01
8.51519883e-01 -4.45830524e-02 -3.82684052e-01 3.75163019e-01
1.34512329e+00 3.42681557e-01 4.72024173e-01 5.45351803e-01
5.40223598e-01 8.10055435e-01 1.07013154e+00 2.92525887e-01
3.37500751e-01 1.01846874e+00 1.95818737e-01 -1.65969029e-01
-5.71564361e-02 -1.16921924e-01 3.86212200e-01 7.06777871e-01
9.29946229e-02 -1.92283005e-01 -1.00354850e+00 6.58688903e-01
-1.87508798e+00 -6.73723459e-01 8.31890199e-03 2.48687625e+00
9.36709702e-01 1.55340672e-01 4.32834417e-01 1.80151120e-01
8.60608339e-01 -1.51382774e-01 -6.69653535e-01 -2.94948369e-01
-1.57104641e-01 3.54766995e-02 5.09618819e-01 4.36445713e-01
-1.28623164e+00 9.12790179e-01 5.90611792e+00 9.83283997e-01
-1.10414302e+00 3.20891105e-02 4.28432375e-01 2.36611962e-01
-2.02785656e-01 2.34687045e-01 -8.27298582e-01 6.41739786e-01
7.40363479e-01 -2.67309695e-01 4.76262540e-01 1.09800172e+00
-5.88882901e-02 1.61073118e-01 -1.27957559e+00 7.95923471e-01
-1.61023632e-01 -7.83390939e-01 -1.71664849e-01 2.19271868e-01
7.59660602e-01 -2.67118007e-01 -3.17687877e-02 5.79713941e-01
3.81551713e-01 -6.93232715e-01 3.66242021e-01 -9.73084718e-02
8.23100150e-01 -8.31133187e-01 6.78606212e-01 5.79199970e-01
-9.37201977e-01 -4.47315983e-02 -5.47027826e-01 -5.80511056e-02
-5.15635833e-02 5.39089680e-01 -7.69424736e-01 8.27261448e-01
5.04536688e-01 5.47993898e-01 -2.55524337e-01 8.45444739e-01
2.33527888e-02 4.18149233e-01 -2.99590886e-01 4.24697340e-01
7.51563534e-02 -3.18376094e-01 5.37882388e-01 9.72371221e-01
3.48576784e-01 4.29703183e-02 2.51924664e-01 6.46094620e-01
-9.82434005e-02 3.32617134e-01 -7.55524457e-01 1.87067926e-01
4.21367586e-01 9.70295846e-01 -5.98817587e-01 -2.29802117e-01
-6.35459483e-01 1.00285089e+00 4.11095977e-01 3.39955837e-01
-9.83248532e-01 -2.44892135e-01 8.16701889e-01 1.76478863e-01
2.43144974e-01 4.96847108e-02 -4.44500953e-01 -1.21822011e+00
1.27324224e-01 -1.15795362e+00 6.47174418e-01 -2.50776500e-01
-1.67101407e+00 4.83595729e-01 1.19839750e-01 -1.64335310e+00
-3.00952345e-01 -3.99016559e-01 -1.32511124e-01 8.74251068e-01
-1.72901225e+00 -7.90924489e-01 -1.74703822e-01 7.41897881e-01
5.00039458e-01 -7.24060759e-02 8.75959933e-01 4.73175585e-01
-4.50487196e-01 8.65840197e-01 3.69085073e-01 -6.90772161e-02
1.15886748e+00 -1.26319408e+00 1.54081225e-01 8.18131745e-01
-1.53636485e-01 6.07751727e-01 7.11032689e-01 -5.10281801e-01
-9.77725148e-01 -1.01969421e+00 9.19801533e-01 -4.13245440e-01
6.64283752e-01 -2.91187108e-01 -1.31493819e+00 6.50467038e-01
-1.56239673e-01 -1.20951727e-01 6.13961577e-01 1.82061672e-01
-4.33814406e-01 -1.43827826e-01 -1.29234946e+00 6.98663712e-01
1.05576432e+00 -3.51298541e-01 -8.25854182e-01 2.10771367e-01
5.72884679e-01 -2.05569580e-01 -9.01233315e-01 5.99359751e-01
2.30138093e-01 -8.29936504e-01 9.45626736e-01 -5.74166059e-01
3.16613615e-01 -5.18283844e-01 -1.81420475e-01 -1.23268294e+00
-3.81722987e-01 -4.22991186e-01 1.16869301e-01 1.52791893e+00
3.33195060e-01 -8.26384783e-01 9.59624171e-01 7.87886858e-01
1.00681037e-01 -4.34520245e-01 -9.72227097e-01 -1.25671566e+00
5.25155604e-01 -2.87361145e-01 5.53922892e-01 1.46471632e+00
3.50098498e-02 3.68943959e-01 -3.68008077e-01 3.92421275e-01
4.70674425e-01 3.19974184e-01 8.45018685e-01 -1.48728788e+00
-3.43332499e-01 -4.36403722e-01 -1.27654731e-01 -1.24186766e+00
2.41915122e-01 -8.16405356e-01 3.90992872e-02 -1.13821423e+00
1.57071382e-01 -8.45919609e-01 -5.31069160e-01 5.75423360e-01
-1.91432014e-01 -1.93108320e-02 2.08086044e-01 5.06656289e-01
-4.57195610e-01 3.30597967e-01 1.07576323e+00 -1.92638137e-04
-4.36397463e-01 7.68013671e-02 -9.27010298e-01 7.15761483e-01
9.16187942e-01 -5.90384960e-01 -6.15354836e-01 -2.52129674e-01
-7.64907226e-02 7.92801827e-02 1.46816447e-02 -8.32623005e-01
2.77538933e-02 -3.79854977e-01 -1.94897041e-01 -1.73826084e-01
8.93569738e-02 -1.01913917e+00 1.68515027e-01 2.64687985e-01
-2.18264222e-01 -3.10632825e-01 9.14883986e-02 5.58954835e-01
-2.83879697e-01 -3.64288986e-01 1.07298386e+00 1.43833026e-01
-9.56806064e-01 -3.29974890e-02 -5.81445992e-02 1.55990988e-01
1.19402659e+00 -4.64614481e-01 -2.01274380e-01 -1.73285216e-01
-6.94351256e-01 1.38599381e-01 8.07395637e-01 3.90446246e-01
6.87248781e-02 -1.25220442e+00 -5.12818098e-01 1.70276105e-01
3.33836228e-01 1.21676736e-01 2.18806475e-01 7.89029360e-01
-6.61895052e-02 3.61509651e-01 -2.95740068e-01 -5.81633270e-01
-1.26394737e+00 8.73641491e-01 1.75765052e-01 -5.85418940e-01
-5.45517206e-01 5.71823895e-01 7.16106117e-01 -5.79541504e-01
2.12456688e-01 -1.67139411e-01 -1.63080975e-01 -9.54563823e-03
2.25149408e-01 2.56747723e-01 3.12517248e-02 -5.30819297e-01
-4.83421534e-01 7.13267505e-01 -2.65802026e-01 1.38061076e-01
1.02408361e+00 -3.76614809e-01 2.08167002e-01 1.27479687e-01
9.67182755e-01 1.31503373e-01 -1.40537608e+00 -5.25363743e-01
3.45449239e-01 -3.25382650e-01 -3.88580769e-01 -8.13265979e-01
-7.48213470e-01 7.46569574e-01 6.03547037e-01 2.72762954e-01
1.39763069e+00 -1.65431798e-02 5.77796996e-01 3.17914873e-01
4.93888140e-01 -1.12142146e+00 -6.04766235e-02 5.10157883e-01
6.19417965e-01 -1.36026680e+00 -1.19724564e-01 -6.62014782e-01
-8.81073952e-01 7.54932344e-01 7.30325460e-01 -4.70012873e-02
2.72728890e-01 -4.67312103e-03 6.85976297e-02 2.16716945e-01
-2.87836909e-01 -2.67522663e-01 1.13356732e-01 7.24990308e-01
2.29821160e-01 -7.84434825e-02 -3.65697563e-01 7.59366989e-01
-7.98612610e-02 -3.66292149e-02 3.20919186e-01 7.70127892e-01
-2.50013769e-01 -1.54413891e+00 -4.82800335e-01 8.33321139e-02
-5.11869192e-01 9.70807076e-02 -3.50990653e-01 1.05420804e+00
3.54357623e-02 9.17106271e-01 -2.17748478e-01 -2.02607632e-01
4.71214801e-01 3.31739545e-01 3.03738832e-01 -5.85686982e-01
-2.96330154e-01 1.10365324e-01 -7.02650473e-02 -2.34451726e-01
-4.30566162e-01 -6.22041345e-01 -1.30395150e+00 -2.02776566e-01
-3.14824849e-01 1.67828873e-01 3.57673854e-01 9.61535156e-01
3.44986141e-01 1.73780829e-01 7.43879974e-01 -2.89230615e-01
-8.33823204e-01 -7.09418833e-01 -6.32111311e-01 6.74432635e-01
1.68982685e-01 -8.64165485e-01 -3.72172654e-01 6.59632310e-02] | [10.326617240905762, 3.1414012908935547] |
d8f4bd1a-9efb-4111-9dbf-75cb48a1648f | transfer-language-selection-for-zero-shot | 2206.00962 | null | https://arxiv.org/abs/2206.00962v1 | https://arxiv.org/pdf/2206.00962v1.pdf | Transfer Language Selection for Zero-Shot Cross-Lingual Abusive Language Detection | We study the selection of transfer languages for automatic abusive language detection. Instead of preparing a dataset for every language, we demonstrate the effectiveness of cross-lingual transfer learning for zero-shot abusive language detection. This way we can use existing data from higher-resource languages to build better detection systems for low-resource languages. Our datasets are from seven different languages from three language families. We measure the distance between the languages using several language similarity measures, especially by quantifying the World Atlas of Language Structures. We show that there is a correlation between linguistic similarity and classifier performance. This discovery allows us to choose an optimal transfer language for zero shot abusive language detection. | ['Michal Wroczynski', 'Gniewosz Leliwa', 'Masaki Arata', 'Fumito Masui', 'Michal Ptaszynski', 'Juuso Eronen'] | 2022-06-02 | null | null | null | null | ['abusive-language'] | ['natural-language-processing'] | [-4.98681754e-01 -4.69241828e-01 -8.06519568e-01 -3.14654887e-01
-9.73594964e-01 -8.28818262e-01 5.68251431e-01 1.75049454e-01
-6.69593692e-01 6.61364138e-01 3.41490746e-01 -2.21404538e-01
3.38627160e-01 -6.49035692e-01 -1.44266486e-01 -2.59917766e-01
-7.89518431e-02 5.79591870e-01 3.76528829e-01 -6.75354540e-01
3.92488718e-01 6.74824119e-01 -6.07705235e-01 4.54107821e-01
9.16333616e-01 8.22492540e-02 -2.92385459e-01 3.79938364e-01
-4.85173702e-01 1.07233679e+00 -6.97302341e-01 -9.39778626e-01
1.65070474e-01 -5.34856260e-01 -1.06035399e+00 -1.29262313e-01
6.30995929e-01 -2.46458039e-01 -9.77622122e-02 1.32579863e+00
4.09353703e-01 -3.08821082e-01 8.34922254e-01 -1.12852764e+00
-7.56312251e-01 9.17000055e-01 -7.14171708e-01 1.00750458e+00
6.26308203e-01 2.25475460e-01 9.35017467e-01 -7.52566695e-01
1.03333759e+00 1.83555996e+00 5.92749119e-01 6.64056480e-01
-1.24877620e+00 -1.05421162e+00 -2.09081888e-01 1.72769815e-01
-1.69993734e+00 -5.40141940e-01 9.84320045e-01 -9.50999856e-01
1.05087757e+00 -2.08246782e-01 2.42277533e-01 1.41486204e+00
2.96885464e-02 3.95735562e-01 1.04804170e+00 -6.79123461e-01
-2.66809374e-01 4.94661570e-01 4.55990106e-01 9.89336133e-01
4.36256617e-01 -1.75670505e-01 -7.02448130e-01 -5.76905906e-01
1.75671890e-01 -4.53635842e-01 1.04301892e-01 -2.99729072e-02
-7.02842832e-01 1.46031857e+00 2.01757997e-01 1.14712942e+00
1.12812154e-01 -1.66776076e-01 1.09770703e+00 5.33441722e-01
7.94456065e-01 7.48855710e-01 -1.50835598e-02 -1.33948820e-02
-7.70340204e-01 -1.15285493e-01 8.68655324e-01 6.49620354e-01
7.74565041e-01 1.35053813e-01 -3.50654200e-02 1.28380966e+00
7.83055425e-02 3.50236535e-01 7.34293401e-01 -6.94733202e-01
4.83503163e-01 5.23796141e-01 -2.39493474e-01 -9.52981353e-01
-1.57392293e-01 2.18226269e-01 -2.67233789e-01 -1.55666977e-01
5.41422665e-01 -3.90505679e-02 -5.41414380e-01 1.91085029e+00
1.27110943e-01 -2.82205015e-01 -9.46468711e-02 4.87177879e-01
3.03751528e-01 3.76077354e-01 4.26348358e-01 -3.71015370e-01
1.44219005e+00 -4.48427111e-01 -7.26961792e-01 -1.97886735e-01
1.34609663e+00 -8.53499830e-01 1.43384850e+00 3.78925174e-01
-8.31447303e-01 2.54779309e-02 -1.04947877e+00 -4.28170621e-01
-7.67463386e-01 -4.25797522e-01 5.14593065e-01 1.03462994e+00
-7.41946101e-01 3.97000343e-01 -5.20421028e-01 -6.13448858e-01
3.66136879e-01 6.60736300e-03 -4.81821686e-01 9.85860601e-02
-1.48447168e+00 1.39022148e+00 4.02046680e-01 -8.57774615e-01
-7.84213722e-01 -5.83344042e-01 -7.93570936e-01 -4.88288999e-01
2.24781975e-01 -8.42852071e-02 9.96845841e-01 -1.27402997e+00
-9.47497129e-01 1.77829039e+00 -9.55902226e-03 -3.22925866e-01
4.01462078e-01 -1.82924956e-01 -6.60797060e-01 6.21008687e-02
6.26281857e-01 1.34310156e-01 7.33418941e-01 -9.08249259e-01
-4.44039524e-01 -3.71686816e-01 -2.21819758e-01 -2.33235225e-01
-9.45973039e-01 1.21895409e+00 -3.49883316e-03 -7.06437290e-01
-4.72996116e-01 -7.18920112e-01 3.77023667e-01 -1.18132643e-01
-3.53067786e-01 -4.77305561e-01 6.40860379e-01 -1.05141807e+00
1.41640031e+00 -2.16946864e+00 1.66766584e-01 1.15453802e-01
2.64647037e-01 2.30771467e-01 1.32200092e-01 2.90382117e-01
-9.01171118e-02 6.08314157e-01 -2.35192403e-01 -4.21887755e-01
-1.86930135e-01 3.55492532e-01 -4.23955113e-01 8.69635820e-01
1.80399001e-01 4.16096628e-01 -9.30312395e-01 -1.04276407e+00
-7.97906071e-02 1.85739577e-01 -5.86389720e-01 1.39548600e-01
2.85000652e-01 1.53320223e-01 -2.13031113e-01 6.60386980e-01
3.23775560e-01 5.15364826e-01 6.16481490e-02 2.84047276e-01
-1.68474585e-01 8.00255179e-01 -4.04530734e-01 1.37485170e+00
-5.15191555e-01 5.95508575e-01 -3.58650432e-04 -6.39180362e-01
1.07006311e+00 1.22210845e-01 1.78788766e-01 -5.73588431e-01
3.34771991e-01 4.33260828e-01 4.81645554e-01 -3.99020344e-01
2.47182012e-01 -6.03426814e-01 -5.45454264e-01 5.92769027e-01
3.96635443e-01 -2.29510590e-01 5.47845483e-01 4.53837544e-01
8.91900718e-01 -4.02043372e-01 8.43538523e-01 -8.52065802e-01
8.25879693e-01 1.49881229e-01 5.05202115e-01 5.13771534e-01
-6.55874431e-01 -5.59264347e-02 7.24237978e-01 -4.78056967e-01
-1.07305932e+00 -1.16734052e+00 -2.99893886e-01 1.78605819e+00
-3.12622935e-01 -5.34735680e-01 -6.76892698e-01 -8.10999632e-01
-6.31803721e-02 1.01742315e+00 -5.40595055e-01 -6.90437138e-01
-8.13976943e-01 -5.75857460e-01 1.31135857e+00 1.37829304e-01
1.56621456e-01 -1.02800429e+00 -1.24997228e-01 -2.00102508e-01
-9.75839049e-02 -1.15036094e+00 -6.78497851e-01 6.21184185e-02
-3.26061308e-01 -7.66340494e-01 -1.87665269e-01 -7.57734358e-01
-2.89514363e-02 -3.78430672e-02 1.39882195e+00 3.37614805e-01
-4.34715271e-01 -1.35390845e-04 -2.29142368e-01 -3.83243561e-01
-1.30139363e+00 4.10887301e-01 5.77012837e-01 -3.38922173e-01
1.02499962e+00 -4.40135688e-01 2.95751393e-01 -6.07902668e-02
-5.67289770e-01 -6.58689439e-01 -1.61047757e-01 3.70621175e-01
1.29446341e-02 -6.40443444e-01 2.51499206e-01 -8.64455342e-01
8.37362170e-01 -7.92326808e-01 -4.08295572e-01 1.86002061e-01
-2.74774283e-01 5.13893832e-03 6.70254111e-01 -7.59951353e-01
-8.64319503e-01 -3.45294923e-01 -9.11236182e-02 -3.91852826e-01
-1.49041668e-01 -1.42593822e-02 -1.45437136e-01 5.44338115e-02
9.93521571e-01 -1.92538828e-01 -4.18260843e-01 -5.95636666e-01
4.52353895e-01 8.23911309e-01 3.59061360e-01 -5.99783659e-01
7.33288944e-01 4.19431001e-01 -5.75627685e-01 -1.15813458e+00
-9.77105796e-01 -6.28475964e-01 -1.04359007e+00 9.64708701e-02
1.08108592e+00 -8.22799206e-01 -3.54620904e-01 2.10127607e-01
-1.36806035e+00 9.10916133e-04 1.85151264e-01 1.64149538e-01
-2.54484564e-01 5.66476226e-01 -1.09008121e+00 -7.77143478e-01
-4.60546076e-01 -8.76109242e-01 8.38266909e-01 -6.10922456e-01
-7.59561837e-01 -1.14638197e+00 7.02986419e-01 2.04883888e-01
9.30915251e-02 -3.07436027e-02 1.23160410e+00 -1.08022010e+00
3.05828512e-01 7.82776549e-02 -1.43628959e-02 3.68482977e-01
3.50366682e-01 2.12532803e-01 -8.09295177e-01 -3.14666301e-01
-4.22002971e-02 -6.76158249e-01 6.63455188e-01 -3.09637487e-01
6.65142298e-01 -3.32477659e-01 -3.77946824e-01 4.14472610e-01
1.20629287e+00 1.58646330e-01 3.21617365e-01 3.94497007e-01
1.07996595e+00 7.88864911e-01 3.01954150e-01 1.35048777e-01
-7.87434354e-02 8.56922507e-01 -2.83400387e-01 1.45114496e-01
-1.10891618e-01 -3.56208354e-01 8.82736742e-01 9.94951963e-01
2.95459956e-01 -2.65772566e-02 -1.57525301e+00 8.26086044e-01
-1.21213853e+00 -1.08614349e+00 -3.74411955e-03 2.02046728e+00
1.11114275e+00 2.10593760e-01 8.09868693e-01 -1.10725187e-01
7.78430462e-01 -4.47482988e-02 -1.55045718e-01 -1.20221448e+00
-2.15279952e-01 2.35041708e-01 4.06910717e-01 9.92645741e-01
-1.04189634e+00 1.79345095e+00 7.21926022e+00 9.82289732e-01
-1.20716369e+00 6.21148109e-01 4.27940428e-01 -2.48034775e-01
-3.93485203e-02 -2.54263014e-01 -9.55122411e-01 5.39749384e-01
1.13637948e+00 -6.17591798e-01 2.58251101e-01 9.66809213e-01
-8.14095587e-02 3.28231901e-01 -9.71647263e-01 7.56392896e-01
4.90028709e-01 -7.10023224e-01 2.21831545e-01 1.26308175e-02
3.05468798e-01 2.38034993e-01 -2.21997768e-01 4.80940640e-01
7.23748565e-01 -1.02334297e+00 5.29407322e-01 -6.24004789e-02
7.17316329e-01 -1.16943383e+00 2.96072394e-01 3.30139756e-01
-6.64527416e-01 1.71040893e-02 -5.37925661e-01 -8.41548666e-02
6.78957030e-02 4.04166728e-01 -9.60011899e-01 -4.30983379e-02
8.42488408e-01 5.98384142e-01 -7.57901013e-01 1.84363410e-01
-2.68655390e-01 7.46221900e-01 -2.20309362e-01 -4.14811112e-02
1.34195343e-01 -3.36963952e-01 7.24913657e-01 1.75563264e+00
3.92042212e-02 -3.02564502e-01 5.14666319e-01 9.23410177e-01
-1.97986200e-01 6.39778316e-01 -1.28755403e+00 -3.18447471e-01
3.92739594e-01 1.08863580e+00 -6.40773594e-01 -5.30610025e-01
-3.88407946e-01 1.12313998e+00 9.75745559e-01 -4.47034955e-01
-6.28758788e-01 -1.64452806e-01 1.00589097e+00 2.79491454e-01
-1.36838302e-01 -4.16525275e-01 -2.02128485e-01 -1.22024810e+00
-4.66307759e-01 -1.12069261e+00 8.55722547e-01 -3.56025636e-01
-1.90503156e+00 6.13901854e-01 3.42308372e-01 -7.61738241e-01
-7.07948208e-01 -7.37742007e-01 -4.64804292e-01 7.87158787e-01
-7.97478497e-01 -1.20203876e+00 3.72693777e-01 8.22206497e-01
3.38075608e-01 -4.86869186e-01 8.81595552e-01 4.14047360e-01
-7.71609187e-01 7.96071231e-01 -5.16700208e-01 5.17024398e-01
1.05646658e+00 -1.03757775e+00 2.77826995e-01 9.85102654e-01
3.83906662e-01 7.44994462e-01 7.96901584e-01 -7.87137628e-01
-7.40404129e-01 -7.30407059e-01 1.16135192e+00 -7.19575763e-01
1.54329967e+00 -8.59548509e-01 -1.27202642e+00 7.88118541e-01
3.58928025e-01 -2.15773895e-01 1.09369826e+00 3.83403957e-01
-1.12318432e+00 3.09051961e-01 -1.34579718e+00 6.75764382e-01
1.34444988e+00 -1.03962648e+00 -9.65523839e-01 5.28840184e-01
7.51375973e-01 3.99900436e-01 -6.33392334e-01 -1.52284220e-01
1.58307195e-01 -7.99716830e-01 7.18206704e-01 -1.11853266e+00
5.64411759e-01 1.40776768e-01 -1.83760226e-01 -1.29705989e+00
-4.27964836e-01 -5.20304918e-01 3.66728157e-01 1.55261624e+00
4.09144312e-01 -6.47904754e-01 5.60238063e-02 5.93160279e-02
2.70579010e-01 5.15086390e-02 -1.15323186e+00 -9.61206377e-01
1.00230265e+00 -3.87261808e-01 8.19945335e-02 1.64845979e+00
3.08789790e-01 8.20440948e-01 -3.89933586e-01 -1.14473417e-01
4.09384221e-01 -2.26950929e-01 5.61364651e-01 -9.81850863e-01
-1.89432532e-01 -5.56892812e-01 -5.93440115e-01 -8.35229531e-02
9.02237236e-01 -1.28790665e+00 -2.43247852e-01 -5.43064594e-01
6.10743403e-01 -8.97379965e-02 -1.80761188e-01 6.02257311e-01
-6.46836981e-02 6.24318659e-01 7.05990791e-02 2.29960576e-01
-3.38976264e-01 5.62509596e-02 4.90944743e-01 -2.39355653e-03
-2.59088069e-01 -7.69989908e-01 -6.50496781e-01 1.15223455e+00
9.54059720e-01 -8.82716596e-01 3.51758525e-02 -2.00659707e-01
7.27548748e-02 -5.52472770e-01 -5.75545169e-02 -5.67163765e-01
-4.26352888e-01 -2.74867296e-01 -9.61500928e-02 -8.04244727e-02
1.67346016e-01 -3.29169989e-01 -6.00570560e-01 8.24513614e-01
-2.22253397e-01 2.20173359e-01 2.03291535e-01 -1.77752391e-01
7.22216535e-03 -5.21970749e-01 1.39141190e+00 -2.36226514e-01
-6.05190635e-01 1.12685919e-01 -7.44014025e-01 4.51222569e-01
9.35983300e-01 2.76828974e-01 -3.45540196e-01 -2.52945065e-01
-3.46095383e-01 -2.55950600e-01 7.94959366e-01 6.12775683e-01
6.83388561e-02 -1.19645202e+00 -9.48723674e-01 -1.07254190e-02
5.10890365e-01 -1.16692436e+00 -5.74121177e-01 6.66805327e-01
-4.82621372e-01 5.55858165e-02 -4.92071599e-01 -3.59168768e-01
-1.63656688e+00 1.10000634e+00 5.05153298e-01 -2.55672395e-01
-2.13299781e-01 6.06816530e-01 1.02200076e-01 -4.06485170e-01
-3.17341387e-01 3.83953065e-01 -1.25474840e-01 2.09444880e-01
6.62174344e-01 3.18427771e-01 -2.47750565e-01 -1.26942813e+00
-7.15211809e-01 2.66930252e-01 -4.47036296e-01 -3.28735858e-01
1.00492036e+00 -3.13170301e-03 -6.30491614e-01 9.69257057e-01
1.47158539e+00 7.00663328e-01 -6.25738949e-02 -9.98757109e-02
7.19188213e-01 -6.31149054e-01 -1.43753424e-01 -4.09817398e-01
-6.44329071e-01 8.48926127e-01 5.00747085e-01 1.56446725e-01
6.60272419e-01 3.86759996e-01 5.78748286e-01 3.27533692e-01
4.82582986e-01 -9.97003615e-01 2.85706758e-01 8.15971792e-01
9.84225810e-01 -1.14190340e+00 5.38650341e-02 -6.45066679e-01
-6.53544903e-01 7.38961339e-01 6.62617505e-01 -4.81649786e-01
4.58950520e-01 4.69662517e-01 3.42933953e-01 -3.77156526e-01
-3.33194166e-01 -2.91787773e-01 2.63843060e-01 5.15294075e-01
9.71220791e-01 1.59309939e-01 -8.49316418e-01 2.95601755e-01
-7.69287944e-01 -5.77472270e-01 4.28840965e-01 5.99801421e-01
-4.96950507e-01 -1.34135163e+00 -4.22992438e-01 1.07811481e-01
-9.04128313e-01 -2.39031330e-01 -1.40015507e+00 1.14521146e+00
2.96070695e-01 8.09282005e-01 1.88275814e-01 -2.58441716e-01
2.55895257e-02 5.96683204e-01 6.64246619e-01 -9.14706051e-01
-7.42496729e-01 -9.62769240e-02 5.04713118e-01 -3.86834323e-01
-2.33033985e-01 -5.50229132e-01 -8.84534061e-01 -7.31557786e-01
-6.13734648e-02 -1.05349198e-01 1.90151408e-01 9.10269439e-01
-1.01606458e-01 -2.00439259e-01 5.11657834e-01 -3.69177401e-01
-3.71312201e-01 -1.22784495e+00 -5.73168159e-01 9.26510036e-01
1.39017120e-01 -8.31390858e-01 -5.02949715e-01 -2.48512179e-01] | [8.806977272033691, 10.560308456420898] |
28b8fad1-e618-4c59-b807-1c6ec346c36b | rmdl-random-multimodel-deep-learning-for | 1805.01890 | null | http://arxiv.org/abs/1805.01890v2 | http://arxiv.org/pdf/1805.01890v2.pdf | RMDL: Random Multimodel Deep Learning for Classification | The continually increasing number of complex datasets each year necessitates
ever improving machine learning methods for robust and accurate categorization
of these data. This paper introduces Random Multimodel Deep Learning (RMDL): a
new ensemble, deep learning approach for classification. Deep learning models
have achieved state-of-the-art results across many domains. RMDL solves the
problem of finding the best deep learning structure and architecture while
simultaneously improving robustness and accuracy through ensembles of deep
learning architectures. RDML can accept as input a variety data to include
text, video, images, and symbolic. This paper describes RMDL and shows test
results for image and text data including MNIST, CIFAR-10, WOS, Reuters, IMDB,
and 20newsgroup. These test results show that RDML produces consistently better
performance than standard methods over a broad range of data types and
classification problems. | ['Laura E. Barnes', 'Kiana Jafari Meimandi', 'Donald E. Brown', 'Mojtaba Heidarysafa', 'Kamran Kowsari'] | 2018-05-03 | null | null | null | null | ['hierarchical-text-classification-of-blurbs'] | ['natural-language-processing'] | [-4.09516037e-01 -5.30736387e-01 -2.23348677e-01 -4.71941531e-01
-7.91327357e-01 -4.36664134e-01 9.05855060e-01 9.02559087e-02
-5.30632675e-01 6.96844757e-01 1.45742401e-01 -3.50118428e-01
-1.55549824e-01 -5.61176658e-01 -4.18758601e-01 -3.94367099e-01
-9.95540395e-02 6.61522388e-01 -1.73825964e-01 -8.42240453e-02
3.23269635e-01 5.08710682e-01 -1.55973613e+00 8.90913427e-01
5.00007987e-01 1.32855248e+00 -2.18510002e-01 8.28776717e-01
-1.05827741e-01 1.22301745e+00 -8.50405216e-01 -4.19132829e-01
1.68328688e-01 -3.11170127e-02 -9.34911549e-01 -2.70787906e-02
6.57890022e-01 -3.59952986e-01 -3.77184391e-01 4.49383914e-01
1.01705420e+00 1.85136527e-01 9.47479844e-01 -1.33184898e+00
-8.34968150e-01 4.91814852e-01 -6.31440401e-01 3.90234232e-01
1.43448114e-01 5.67586124e-02 1.06196415e+00 -1.11954737e+00
4.27169532e-01 1.53308904e+00 8.28831732e-01 5.27679503e-01
-1.26780224e+00 -8.76015544e-01 8.76544490e-02 3.66841018e-01
-1.34888220e+00 -2.96333790e-01 3.30172747e-01 -7.19905913e-01
1.19148862e+00 1.24945670e-01 -1.27780572e-01 1.64001465e+00
6.69341445e-01 1.08160198e+00 9.67619658e-01 -1.66569129e-01
1.55587301e-01 9.31583568e-02 5.25336564e-01 5.92217147e-01
1.09398209e-01 -1.41181275e-01 -4.34838235e-01 -7.29850456e-02
2.08433554e-01 2.84260008e-02 1.13692276e-01 1.28442168e-01
-1.03064394e+00 8.75792444e-01 3.05499226e-01 3.40912998e-01
-2.73615599e-01 7.23448873e-04 6.70225620e-01 6.46603703e-01
7.65098274e-01 5.77621043e-01 -7.63799310e-01 4.24652100e-02
-6.61183596e-01 3.89305681e-01 7.48878956e-01 5.62747180e-01
3.05898935e-01 3.27484041e-01 -4.80179349e-03 1.20355916e+00
2.99583554e-01 2.11983740e-01 9.96252716e-01 -6.93243444e-01
6.14935756e-01 7.00468659e-01 -1.28184691e-01 -1.20239830e+00
-7.20535755e-01 -7.18676090e-01 -1.33023810e+00 3.24081838e-01
1.35959044e-01 -1.62088260e-01 -1.29264188e+00 1.37521756e+00
-1.30489260e-01 -1.09908447e-01 2.50621438e-01 4.66617703e-01
1.44309354e+00 7.92349100e-01 1.66027322e-01 2.55671054e-01
8.94570291e-01 -9.38651919e-01 -5.09700119e-01 -3.21850330e-01
5.75170338e-01 -4.59393948e-01 8.04839551e-01 8.94607484e-01
-7.01969862e-01 -7.98396826e-01 -9.58238304e-01 -7.90589303e-02
-6.71960711e-01 3.28835398e-01 2.68863708e-01 1.89533517e-01
-9.75715220e-01 6.15890086e-01 -6.34045064e-01 -3.54751676e-01
5.23535192e-01 4.70554024e-01 -6.22223616e-01 -1.97979972e-01
-1.08988154e+00 1.03273344e+00 5.28790951e-01 -9.03427824e-02
-1.08520961e+00 -4.48511839e-01 -5.13271809e-01 1.99699134e-04
-2.38774925e-01 -3.86632830e-01 1.39193642e+00 -1.16254783e+00
-1.08124208e+00 1.00317585e+00 2.01461554e-01 -6.83667481e-01
6.73510432e-01 -3.05346102e-01 -7.56187856e-01 -3.13134402e-01
-1.84851110e-01 6.77667797e-01 8.26459646e-01 -1.29710996e+00
-4.82517898e-01 -3.94702017e-01 -2.56061822e-01 1.43252850e-01
-4.27395761e-01 6.98084310e-02 -8.16173293e-03 -6.28206551e-01
3.61075960e-02 -7.41013706e-01 1.32501125e-02 -4.04694021e-01
-5.85227907e-01 -7.14255750e-01 1.05806184e+00 -6.45723999e-01
1.10296929e+00 -2.08613467e+00 3.38563442e-01 -1.60268962e-01
2.72538185e-01 4.31846410e-01 -4.71438050e-01 5.31572044e-01
-3.95030737e-01 3.90051037e-01 3.01531255e-01 -5.78797698e-01
8.71675462e-02 1.91945896e-01 -2.02851370e-01 2.51287520e-01
-9.66616496e-02 7.66279995e-01 -3.40523422e-01 -1.84180245e-01
2.29459077e-01 3.54873955e-01 -1.45239323e-01 2.26102233e-01
-2.04661727e-01 1.75940484e-01 -9.23776552e-02 6.52007699e-01
3.65084499e-01 -5.00159502e-01 -1.43210933e-01 -2.80792594e-01
2.29634732e-01 3.87527756e-02 -1.05355513e+00 1.31119895e+00
-3.64447027e-01 9.88018513e-01 -1.84057787e-01 -1.07642794e+00
1.04864609e+00 2.26046070e-01 4.44020540e-01 -6.33149981e-01
3.28150779e-01 1.48685560e-01 1.03409797e-01 -5.24192572e-01
4.13490951e-01 2.14376718e-01 -2.07180783e-01 5.20229757e-01
4.10787463e-01 3.19173872e-01 1.62358969e-01 1.08678266e-01
1.07660711e+00 -4.37951118e-01 1.80574596e-01 -1.90653265e-01
3.39551538e-01 -2.07922533e-01 3.64957601e-01 9.39819157e-01
-2.14563459e-02 5.46902061e-01 9.67044085e-02 -1.11337554e+00
-6.72242820e-01 -1.01209688e+00 -1.81135669e-01 1.54193914e+00
-2.56857932e-01 -2.27309078e-01 -3.72278750e-01 -8.23717475e-01
2.88413644e-01 7.38070130e-01 -7.51422107e-01 -2.36844376e-01
-2.00189099e-01 -1.21477973e+00 5.82269788e-01 5.93924642e-01
8.01964819e-01 -1.05530715e+00 -2.97925062e-02 2.45452926e-01
-2.76206493e-01 -1.05491042e+00 1.95471883e-01 2.23307639e-01
-7.07496166e-01 -1.14492810e+00 -3.18376392e-01 -7.12709606e-01
3.21698248e-01 -3.46115744e-03 1.44789600e+00 -4.25379835e-02
-4.12871540e-01 1.80893973e-01 -2.84748733e-01 -7.66155839e-01
-5.91586888e-01 3.17606896e-01 2.21824780e-01 7.28719905e-02
4.68698978e-01 -1.53850600e-01 -2.50571668e-01 3.58922809e-01
-8.18915784e-01 6.41551986e-02 4.77031112e-01 8.95169437e-01
3.62878323e-01 2.72785783e-01 8.35164547e-01 -5.93718231e-01
9.68193769e-01 -9.46880102e-01 -2.05740854e-01 2.67101705e-01
-6.37935579e-01 -7.78439268e-02 6.88341379e-01 -4.27272171e-01
-6.62228584e-01 -3.01523983e-01 -3.40379596e-01 -2.44089738e-01
-5.16995430e-01 7.36965895e-01 5.30203804e-02 2.16505885e-01
1.07021892e+00 1.89168081e-01 -8.20783079e-02 -8.45621467e-01
2.96649747e-02 1.17557967e+00 4.25260544e-01 -3.19500804e-01
2.15730846e-01 1.43590182e-01 -3.75265867e-01 -7.56558537e-01
-9.51026022e-01 -1.41445905e-01 -6.16345108e-01 -2.44646922e-01
7.66454160e-01 -9.98482287e-01 -4.36709940e-01 1.00599885e+00
-1.12455523e+00 -4.52065855e-01 1.74587190e-01 3.57988954e-01
-2.29270488e-01 -1.67497069e-01 -7.89986312e-01 -4.33463693e-01
-6.39462233e-01 -1.20472610e+00 8.59126985e-01 -5.17254956e-02
-4.11546439e-01 -1.11735678e+00 3.10629643e-02 2.84774840e-01
5.47246933e-01 4.79693472e-01 9.48794961e-01 -1.28037739e+00
-2.65269190e-01 -5.48502803e-01 -2.20700711e-01 7.21809685e-01
9.22206864e-02 1.68988720e-01 -1.07628858e+00 -5.29017627e-01
-5.39870441e-01 -8.15149009e-01 1.18945360e+00 3.62466097e-01
1.86242902e+00 -3.95166814e-01 -2.39157081e-01 5.73257744e-01
1.30234838e+00 3.11402023e-01 4.66036260e-01 6.31173968e-01
6.56274498e-01 3.41831774e-01 1.38460502e-01 3.56847048e-01
5.89697838e-01 3.47113490e-01 6.00151956e-01 -1.22413956e-01
1.49549812e-01 2.15287909e-01 2.03942418e-01 7.27118552e-01
8.62905905e-02 -8.88806880e-01 -1.44829810e+00 2.93771684e-01
-1.88005614e+00 -1.15376592e+00 5.15614636e-02 1.71199429e+00
5.16162097e-01 6.66817576e-02 8.68684649e-02 3.02842259e-01
3.88966799e-01 1.35415345e-01 -9.37770009e-01 -4.21409994e-01
-2.82947838e-01 -9.54243690e-02 2.21729174e-01 6.43068552e-02
-1.48949766e+00 7.06796408e-01 7.02536583e+00 7.60941148e-01
-1.33566952e+00 4.03903574e-02 1.10285807e+00 -1.03650972e-01
9.44681093e-02 -1.07646477e+00 -9.84588444e-01 5.22525072e-01
1.29626548e+00 -1.67040750e-01 1.78852722e-01 7.98393905e-01
-8.06390867e-02 1.50711864e-01 -1.16468978e+00 1.28356194e+00
2.72365898e-01 -1.60653174e+00 2.10447013e-01 -1.02166794e-01
7.61824250e-01 8.93663645e-01 3.50024343e-01 6.65774822e-01
8.92860711e-01 -1.39094961e+00 5.14249742e-01 4.18585747e-01
6.03083014e-01 -8.49291086e-01 9.68974054e-01 5.28793931e-01
-5.74054003e-01 -6.26838446e-01 -1.81165397e-01 1.66990101e-01
-5.16987920e-01 4.14377242e-01 -7.08752990e-01 4.95121509e-01
1.13397825e+00 1.12522495e+00 -8.32601249e-01 8.86360824e-01
2.88691044e-01 5.55810928e-01 -1.55495316e-01 5.30242696e-02
3.09041739e-01 4.42171097e-01 1.26819029e-01 1.46804070e+00
1.60525411e-01 -1.52356148e-01 3.38146329e-01 1.68251529e-01
-5.86531758e-01 6.48916885e-02 -7.53242373e-01 -3.41574810e-02
4.06411290e-01 1.05529952e+00 -4.66337174e-01 -4.34170961e-01
-2.46985272e-01 6.32767558e-01 4.06890184e-01 4.31628168e-01
-6.78430915e-01 -1.83157191e-01 7.93350637e-01 -1.44960746e-01
-5.96441962e-02 -2.35443413e-01 -2.80280471e-01 -1.18505478e+00
-4.05513018e-01 -1.38735735e+00 6.95145190e-01 -7.73373902e-01
-1.71446097e+00 1.11137259e+00 -2.20546741e-02 -1.29781616e+00
-4.46364969e-01 -8.57538581e-01 -4.49764758e-01 5.45700729e-01
-1.18817914e+00 -8.93485546e-01 -5.52196324e-01 6.28994346e-01
8.32243860e-01 -9.50818598e-01 1.06649315e+00 3.46769214e-01
-8.30599308e-01 6.19995058e-01 6.68052554e-01 5.27295411e-01
7.77949333e-01 -1.13696265e+00 6.72249377e-01 3.98528546e-01
2.24861875e-01 8.35667551e-02 4.76800770e-01 -1.98880643e-01
-1.11688805e+00 -1.44025898e+00 5.17845631e-01 -6.54622555e-01
4.56776410e-01 -2.21040010e-01 -8.18676531e-01 7.97082484e-01
4.98312920e-01 -4.93317954e-02 8.88853669e-01 1.53628334e-01
-7.43451118e-01 -4.21130151e-01 -1.25296462e+00 3.14713955e-01
6.08294487e-01 -4.39429849e-01 -4.32342023e-01 5.35509944e-01
2.77666181e-01 -3.95921141e-01 -9.27722633e-01 6.56856418e-01
6.55871034e-01 -9.75146770e-01 9.50445890e-01 -1.06214404e+00
6.94407105e-01 2.19456002e-01 -4.89031762e-01 -1.80741775e+00
-3.67501646e-01 -1.85832724e-01 -4.04970646e-01 9.26746011e-01
4.21919912e-01 -6.41477585e-01 5.54722488e-01 5.63959360e-01
-1.12132303e-01 -9.82005000e-01 -7.53808498e-01 -7.92049110e-01
3.64049524e-01 -5.82281768e-01 6.40802860e-01 1.34205925e+00
-4.92724746e-01 6.02484226e-01 -3.45219761e-01 -2.33616635e-01
7.07469106e-01 -4.06527445e-02 8.74551892e-01 -1.71421754e+00
-1.37844428e-01 -5.65227807e-01 -6.68313682e-01 -6.62095904e-01
3.77559036e-01 -1.06412911e+00 -2.97703922e-01 -1.86574364e+00
4.08792607e-02 -4.25077528e-01 -6.25222206e-01 7.71582842e-01
1.60664871e-01 2.17328623e-01 1.64081872e-01 2.09182873e-01
-7.59289086e-01 2.87430376e-01 7.81249762e-01 -5.03945947e-01
9.70410705e-02 3.02740578e-02 -6.77916527e-01 7.55363345e-01
1.24132574e+00 -2.80936539e-01 -2.86941826e-01 -1.02056992e+00
1.75977331e-02 -2.22285420e-01 2.17610285e-01 -1.15542674e+00
1.05600245e-02 3.54428850e-02 9.44823205e-01 -8.38807523e-01
2.72688061e-01 -5.83446801e-01 1.50121227e-01 3.08504313e-01
-8.08551073e-01 4.45090592e-01 4.82467771e-01 4.67549026e-01
-3.05836171e-01 2.04181433e-01 1.09441590e+00 -1.70038313e-01
-9.72834945e-01 5.15016019e-01 -5.07565737e-01 -5.05810156e-02
8.48929048e-01 9.39529017e-02 -7.11015344e-01 -4.04308945e-01
-1.05098975e+00 3.80762607e-01 -6.81706965e-02 1.16552162e+00
7.07659721e-01 -1.36174619e+00 -1.05829048e+00 3.89683574e-01
1.50894463e-01 -1.71635762e-01 9.41455141e-02 3.82176101e-01
-3.20348233e-01 2.48952463e-01 -3.59342784e-01 -7.21596658e-01
-1.41456413e+00 1.51282802e-01 7.20705986e-01 -3.92446041e-01
-2.00328290e-01 1.03560078e+00 -1.27196670e-01 -8.32082629e-01
6.61340594e-01 -1.19488060e-01 -3.31686586e-01 2.29365095e-01
7.21814632e-01 4.82727319e-01 4.59224254e-01 -6.61462665e-01
-3.09827536e-01 7.98022598e-02 -4.60644603e-01 2.87454814e-01
1.43473089e+00 1.46517605e-01 1.19856216e-01 6.45891845e-01
1.65994346e+00 -8.50601375e-01 -8.09904814e-01 -1.51200414e-01
2.25074038e-01 -3.27490829e-03 2.87307143e-01 -1.24753237e+00
-1.04535580e+00 1.03963268e+00 8.63183677e-01 3.19744319e-01
9.55952108e-01 -2.61649430e-01 4.52090502e-01 7.89270580e-01
2.96042025e-01 -1.18802500e+00 3.89037877e-01 8.27860415e-01
1.08124232e+00 -1.70562577e+00 4.60975664e-03 6.40696049e-01
-5.83648145e-01 1.24394822e+00 8.91027927e-01 -1.05497055e-03
8.53864789e-01 2.57602036e-01 1.45593092e-01 -4.25238647e-02
-1.28423297e+00 1.25602007e-01 5.28635740e-01 3.28655183e-01
6.54225826e-01 -1.32162338e-02 2.43401393e-01 4.47998941e-01
6.58676550e-02 1.74483005e-02 3.49713624e-01 6.93153620e-01
-4.86114323e-01 -9.32421505e-01 -2.89137274e-01 9.67398345e-01
-8.32495451e-01 8.98693055e-02 -6.15917563e-01 8.68000865e-01
-2.83218045e-02 9.82613504e-01 3.26474607e-01 -9.50295329e-01
2.94889301e-01 1.80072218e-01 7.41654485e-02 -4.97486472e-01
-7.67558634e-01 -3.31993133e-01 1.88651934e-01 -3.82027060e-01
-2.77241737e-01 -4.00474638e-01 -9.32904065e-01 -5.72112918e-01
-1.56059153e-02 4.56174985e-02 8.57130408e-01 9.22114134e-01
6.79600596e-01 4.06926602e-01 6.88734770e-01 -9.71157968e-01
-7.49395609e-01 -1.20771849e+00 -2.49794871e-01 4.13105249e-01
5.45463324e-01 -5.94282329e-01 -3.89475763e-01 -3.25909667e-02] | [9.6412935256958, 2.7974863052368164] |
39d9552c-2d75-4153-a9df-c2392ea04283 | improving-and-benchmarking-offline | 2306.00972 | null | https://arxiv.org/abs/2306.00972v1 | https://arxiv.org/pdf/2306.00972v1.pdf | Improving and Benchmarking Offline Reinforcement Learning Algorithms | Recently, Offline Reinforcement Learning (RL) has achieved remarkable progress with the emergence of various algorithms and datasets. However, these methods usually focus on algorithmic advancements, ignoring that many low-level implementation choices considerably influence or even drive the final performance. As a result, it becomes hard to attribute the progress in Offline RL as these choices are not sufficiently discussed and aligned in the literature. In addition, papers focusing on a dataset (e.g., D4RL) often ignore algorithms proposed on another dataset (e.g., RL Unplugged), causing isolation among the algorithms, which might slow down the overall progress. Therefore, this work aims to bridge the gaps caused by low-level choices and datasets. To this end, we empirically investigate 20 implementation choices using three representative algorithms (i.e., CQL, CRR, and IQL) and present a guidebook for choosing implementations. Following the guidebook, we find two variants CRR+ and CQL+ , achieving new state-of-the-art on D4RL. Moreover, we benchmark eight popular offline RL algorithms across datasets under unified training and evaluation framework. The findings are inspiring: the success of a learning paradigm severely depends on the data distribution, and some previous conclusions are biased by the dataset used. Our code is available at https://github.com/sail-sg/offbench. | ['Shuicheng Yan', 'Yang Yue', 'Yirui Wang', 'Xiao Ma', 'Bingyi Kang'] | 2023-06-01 | null | null | null | null | ['offline-rl', 'd4rl'] | ['playing-games', 'robots'] | [-4.19878095e-01 -4.89272714e-01 -6.47769809e-01 -1.07406594e-01
-6.59403145e-01 -9.00713146e-01 5.18068492e-01 1.16585955e-01
-5.73622465e-01 7.89261758e-01 7.01738149e-02 -5.53635240e-01
-1.19686402e-01 -6.58396542e-01 -7.23950207e-01 -7.24077284e-01
5.87876840e-03 3.13799322e-01 8.24862123e-02 -3.74124587e-01
4.08904344e-01 3.65637690e-01 -1.68819571e+00 9.57775339e-02
7.07499743e-01 6.95224881e-01 3.87869030e-01 3.57455879e-01
-2.45069399e-01 1.01444650e+00 -7.79975891e-01 -2.32424468e-01
2.86735922e-01 -5.68033397e-01 -6.71721339e-01 -3.21554691e-01
-9.33514833e-02 -5.65618277e-01 -3.66744459e-01 7.75831521e-01
8.26617479e-01 -1.88158937e-02 2.07812145e-01 -1.37396240e+00
-5.40358424e-01 8.27333570e-01 -6.11158431e-01 -8.85514356e-03
4.11020726e-01 5.67746103e-01 1.04160631e+00 -6.67605519e-01
5.56016624e-01 1.04313385e+00 4.58511204e-01 5.97124338e-01
-1.02365589e+00 -8.23137283e-01 3.34717363e-01 3.37421685e-01
-1.28577125e+00 -4.14250672e-01 9.08178926e-01 -1.07305065e-01
8.18684161e-01 1.70872375e-01 6.94140077e-01 1.46635902e+00
3.60581391e-02 1.36982763e+00 1.44861472e+00 -3.80444139e-01
4.54794377e-01 -6.76120073e-02 6.60772920e-02 4.95931327e-01
3.56986970e-01 4.02798951e-01 -5.56360900e-01 2.08867006e-02
6.57684088e-01 -1.70341909e-01 -1.50308311e-01 -4.38378453e-01
-1.07337832e+00 9.09003317e-01 1.62653521e-01 2.80371636e-01
-5.15408516e-02 -6.82837740e-02 6.02715254e-01 6.31905198e-01
5.45058958e-02 5.93695939e-01 -5.99858820e-01 -6.17694199e-01
-7.37077951e-01 4.81678307e-01 7.83209443e-01 9.40956116e-01
8.18902254e-01 -1.50364377e-02 -1.56375140e-01 8.75168741e-01
8.32304209e-02 2.46055946e-01 6.17556453e-01 -9.20030653e-01
3.41354668e-01 4.25556600e-01 1.62338838e-01 -6.81845129e-01
-6.53673530e-01 -4.24795091e-01 -6.88094497e-01 1.41916409e-01
6.86429977e-01 -2.97437757e-01 -3.54506433e-01 1.86049116e+00
1.73950493e-01 -9.51109082e-02 9.30178314e-02 1.03596854e+00
8.57330561e-01 3.80188406e-01 -5.65252192e-02 -2.86722898e-01
9.54165995e-01 -1.30039763e+00 -6.66210234e-01 -1.90250307e-01
9.59571302e-01 -6.42099261e-01 1.52779317e+00 8.23479652e-01
-9.86118615e-01 -6.87647581e-01 -1.09363723e+00 1.67848766e-01
-3.66513789e-01 2.30281100e-01 8.70732129e-01 5.04826427e-01
-9.18575406e-01 6.88231289e-01 -8.92519414e-01 -2.46706396e-01
1.57987475e-01 1.85918078e-01 1.49274364e-01 -1.14525504e-01
-1.25411510e+00 8.27763021e-01 4.92211252e-01 -4.01114114e-02
-1.00796652e+00 -5.41567564e-01 -3.32500935e-01 -4.63313133e-01
7.15278506e-01 -4.07949626e-01 1.63153183e+00 -9.73436832e-01
-1.93827927e+00 6.13025188e-01 2.33998790e-01 -5.09889424e-01
8.52402210e-01 -3.55212569e-01 -3.93451989e-01 -2.07658574e-01
-8.12270492e-02 5.59024692e-01 7.16452479e-01 -1.26704872e+00
-8.28251123e-01 -2.17894495e-01 3.83742809e-01 3.43830109e-01
-1.53880060e-01 -1.36668295e-01 -5.69076955e-01 -5.96458912e-01
-3.47136021e-01 -8.93227756e-01 -6.84365928e-02 -3.76955539e-01
1.10142315e-02 -5.67355871e-01 7.61753440e-01 -2.46869937e-01
1.64553130e+00 -2.38274145e+00 5.00147380e-02 -3.10783207e-01
7.62490258e-02 1.38618276e-01 -3.63295674e-01 8.38024139e-01
1.80394486e-01 1.51512221e-01 2.64688339e-02 -1.51472732e-01
2.89428383e-01 4.48830009e-01 -4.13166195e-01 5.49412489e-01
-8.42099711e-02 8.31914902e-01 -1.19170237e+00 -4.36736256e-01
2.33537555e-01 -2.02457011e-02 -6.66337490e-01 3.35669875e-01
-4.30722535e-01 5.23440897e-01 -5.49490809e-01 7.25921094e-01
4.91744518e-01 -1.54274479e-01 3.56089264e-01 -1.26672819e-01
-4.65577215e-01 4.97797132e-01 -1.17111218e+00 2.00543284e+00
-5.09644210e-01 3.47175628e-01 -2.72481650e-01 -9.12724793e-01
1.00829554e+00 8.03854764e-02 6.34318531e-01 -1.11154962e+00
6.82071745e-02 3.61545444e-01 2.58802295e-01 -2.93729901e-01
6.04720891e-01 4.05569375e-01 -1.18744582e-01 7.19226003e-01
-9.58073512e-02 2.42209025e-02 5.28406143e-01 -3.38667654e-03
1.11826646e+00 5.56453109e-01 4.31565970e-01 -1.29178643e-01
2.37371907e-01 3.46248597e-02 5.84941030e-01 1.01824486e+00
-4.89330530e-01 2.26681873e-01 6.19281709e-01 -4.74414706e-01
-8.96539807e-01 -1.00642920e+00 -8.18333998e-02 1.39109695e+00
1.76881894e-01 -5.68938971e-01 -6.10204279e-01 -8.55960608e-01
9.08234045e-02 8.12199056e-01 -4.36452568e-01 -1.52109057e-01
-6.35891616e-01 -7.79700935e-01 7.48731494e-01 3.23836058e-01
6.26527250e-01 -1.37006688e+00 -8.65122259e-01 3.00289392e-01
-5.92000112e-02 -8.97525966e-01 -1.13512874e-01 2.79226601e-01
-8.52233291e-01 -1.07599676e+00 -3.98284554e-01 -5.20556092e-01
2.40508750e-01 3.94013554e-01 1.35928297e+00 2.10795313e-01
1.45913944e-01 3.34209710e-01 -8.02708626e-01 -3.08810562e-01
-4.06899840e-01 4.28894013e-01 1.40687138e-01 -3.58093649e-01
2.83589303e-01 -4.18860883e-01 -6.64997339e-01 4.19717073e-01
-7.20916033e-01 4.13342826e-02 7.40907907e-01 7.54162431e-01
4.09975678e-01 2.36565974e-02 6.80817664e-01 -7.64554739e-01
8.12015176e-01 -5.30731320e-01 -6.25593483e-01 2.40378514e-01
-8.63337636e-01 2.05079868e-01 9.00030434e-01 -5.86107433e-01
-6.84531987e-01 -3.33716840e-01 -2.53657639e-01 -3.80176067e-01
-2.17561990e-01 4.71808523e-01 -2.41437741e-02 2.19479546e-01
6.01212323e-01 4.88589585e-01 2.98034083e-02 -3.90539736e-01
3.48634541e-01 6.06196821e-01 2.71784086e-02 -1.04316211e+00
4.06945348e-01 3.88197973e-02 -5.51865339e-01 -6.74331963e-01
-8.81970704e-01 -7.58539960e-02 -2.35094696e-01 -2.44969293e-01
3.21612149e-01 -7.93042898e-01 -7.50117958e-01 4.79632646e-01
-6.86606944e-01 -9.69428539e-01 -3.09722483e-01 4.17241663e-01
-7.14882374e-01 1.45143211e-01 -5.60489774e-01 -6.25468433e-01
-1.41316742e-01 -1.54733109e+00 7.18340099e-01 2.33494207e-01
-2.42101118e-01 -8.98898661e-01 2.74120122e-01 1.99156046e-01
4.37123239e-01 -4.18077633e-02 6.41136885e-01 -4.73329812e-01
-3.54107827e-01 3.20522070e-01 -9.58522111e-02 2.37779051e-01
1.61751539e-01 2.49082685e-01 -8.46133947e-01 -6.63257837e-01
-1.66380137e-01 -8.02771628e-01 4.99581724e-01 2.57062972e-01
1.53519285e+00 -2.34230220e-01 -1.78699661e-02 5.56726038e-01
1.42730987e+00 3.71635944e-01 5.71597517e-01 8.74612272e-01
3.28724116e-01 3.46111745e-01 9.71688271e-01 8.00438881e-01
4.11731154e-01 5.57263672e-01 4.42210615e-01 9.23788324e-02
-1.08468075e-05 -4.58903074e-01 7.18062043e-01 1.06642592e+00
2.25216127e-03 -3.10479224e-01 -8.80388856e-01 2.28297010e-01
-1.77362168e+00 -7.36773908e-01 2.38475025e-01 2.12970090e+00
1.01240683e+00 2.98475295e-01 4.60410476e-01 1.97948501e-01
2.81902045e-01 4.56817418e-01 -8.70819628e-01 -4.58569050e-01
-1.38431087e-01 2.82013953e-01 4.66476977e-01 1.71202049e-01
-7.91530013e-01 1.09106123e+00 5.88448572e+00 1.15277517e+00
-1.29042697e+00 9.67082474e-03 5.11102915e-01 -1.78646762e-02
-1.49080679e-01 2.31292527e-02 -8.74979734e-01 5.62199950e-01
8.63393188e-01 -2.75758058e-01 9.05791819e-01 8.40133011e-01
3.25985998e-01 -1.50972679e-01 -1.09065032e+00 1.12304735e+00
-2.67444640e-01 -1.09753478e+00 1.11123603e-02 -1.98037788e-01
6.18153214e-01 1.91552714e-01 1.67487592e-01 9.06308293e-01
5.89330435e-01 -8.39838564e-01 8.68918538e-01 2.23369658e-01
5.84459245e-01 -9.29690123e-01 4.32663798e-01 5.05778134e-01
-9.61459577e-01 -2.56382495e-01 -3.35190743e-01 -2.55675316e-01
-3.87459844e-01 2.21217960e-01 -5.61823845e-01 6.81503773e-01
7.77818263e-01 9.20886397e-01 -6.38130784e-01 7.80190885e-01
-4.67255265e-01 8.63006711e-01 -6.39783144e-02 -3.31521779e-01
4.70248103e-01 -2.92909563e-01 9.93114263e-02 1.09067881e+00
1.06307723e-01 -1.84715632e-02 2.81741351e-01 5.54384112e-01
-1.23286366e-01 3.09954196e-01 -5.48176706e-01 -8.10381249e-02
5.80091417e-01 1.25752580e+00 -5.03150582e-01 1.04027009e-02
-6.28039718e-01 6.04989767e-01 6.41389668e-01 2.88538039e-01
-1.13023663e+00 -2.96743251e-02 7.78303981e-01 -1.39098123e-01
4.13899608e-02 -4.67942506e-01 -1.32275417e-01 -9.90098178e-01
-1.71209127e-01 -1.50038016e+00 5.32620251e-01 -4.85297918e-01
-1.18462586e+00 2.42486417e-01 -9.77140591e-02 -1.34958386e+00
-1.03455037e-03 -4.34233993e-01 -2.48438686e-01 1.90102041e-01
-1.53168547e+00 -4.55017626e-01 -2.37728238e-01 4.57492977e-01
7.37921298e-01 -1.65746585e-01 5.57988822e-01 4.01262641e-01
-8.83656204e-01 9.02835846e-01 3.40153158e-01 3.45705822e-02
1.01769876e+00 -1.12331915e+00 1.84177697e-01 3.94559115e-01
2.53132969e-01 5.68455338e-01 5.86540401e-01 -2.66158670e-01
-1.95434904e+00 -9.19128716e-01 2.55401254e-01 -4.53959525e-01
8.95603061e-01 -3.00442308e-01 -6.82720125e-01 4.94806200e-01
2.51961112e-01 -1.50159299e-01 4.88202006e-01 1.40282199e-01
-1.34171173e-01 -3.30439895e-01 -8.91336620e-01 1.03867698e+00
1.22013402e+00 -2.90493935e-01 -2.86201149e-01 1.47605732e-01
6.63598955e-01 -6.42692506e-01 -8.93969655e-01 2.63105124e-01
5.90696573e-01 -1.28597474e+00 7.92025685e-01 -5.00891745e-01
4.94057000e-01 -1.15632795e-01 -1.68210387e-01 -1.26377964e+00
-8.84300470e-02 -6.47077918e-01 -2.95686513e-01 1.12853074e+00
3.04247826e-01 -8.07233632e-01 7.10587680e-01 5.66506386e-02
-9.33581665e-02 -1.07915306e+00 -5.16499579e-01 -9.46497321e-01
2.99805939e-01 -5.28203726e-01 7.39376605e-01 1.00910461e+00
-1.67117819e-01 2.10403755e-01 -3.61919045e-01 -1.72244251e-01
4.24656272e-01 4.09593165e-01 1.18163884e+00 -6.36383593e-01
-4.65947360e-01 -7.28135586e-01 3.08909655e-01 -1.41541433e+00
1.53766111e-01 -8.97229493e-01 -2.04576775e-01 -1.23620009e+00
-5.17270714e-02 -9.39121962e-01 -4.88681138e-01 6.12976313e-01
-5.51078767e-02 -9.26247314e-02 2.47010127e-01 4.10533637e-01
-9.04645324e-01 7.52410352e-01 1.52838540e+00 6.44950867e-02
-5.30102789e-01 -9.84443799e-02 -6.55516088e-01 6.20553493e-01
1.55888057e+00 -4.09742653e-01 -5.26906729e-01 -5.09899020e-01
3.17708045e-01 1.37347907e-01 1.42343059e-01 -1.09946775e+00
9.40104127e-02 -3.38382453e-01 3.47347148e-02 -5.46669722e-01
-9.29550007e-02 -5.29362619e-01 -6.67935833e-02 5.97061217e-01
-3.73716474e-01 4.19771761e-01 3.06656927e-01 2.57574618e-01
-1.70235619e-01 -1.91501573e-01 6.81954980e-01 -1.53920040e-01
-8.43320847e-01 3.19880903e-01 -2.11323649e-01 5.40016174e-01
8.99960399e-01 -1.19137824e-01 -4.41984385e-01 -1.65734231e-01
-2.79948711e-01 3.85861307e-01 5.58823824e-01 5.82713187e-01
3.41797143e-01 -1.05677772e+00 -6.14464283e-01 1.41068697e-01
1.15589328e-01 -1.41625896e-01 6.74996302e-02 9.07877445e-01
-4.99722272e-01 4.04914409e-01 -2.69490272e-01 -4.88027930e-01
-8.23067963e-01 6.44926310e-01 1.95713192e-01 -5.66638768e-01
-5.70647240e-01 4.10031170e-01 -7.82022700e-02 -6.42591417e-01
4.28827584e-01 -4.20688480e-01 -1.18853800e-01 1.26356736e-01
2.25578442e-01 4.13600028e-01 -4.85167131e-02 9.74325538e-02
-3.29011738e-01 3.29109818e-01 -1.94607064e-01 7.94278532e-02
1.33749247e+00 1.38432354e-01 2.17499644e-01 6.96841955e-01
9.12863731e-01 -2.20372546e-02 -1.42335105e+00 -1.41212225e-01
6.83815405e-02 -2.77632236e-01 -1.00709140e-01 -8.69676232e-01
-1.15122950e+00 5.73564231e-01 4.63067591e-01 1.09298140e-01
1.26655209e+00 -2.11191177e-01 5.87477744e-01 4.27418500e-01
9.16126907e-01 -1.35789800e+00 1.65443853e-01 6.20113671e-01
8.44054222e-01 -1.24764240e+00 2.81729728e-01 2.10270211e-01
-7.19184577e-01 1.10551727e+00 7.33258843e-01 -2.05298513e-01
2.67238587e-01 2.77419478e-01 2.62460932e-02 1.66013330e-01
-9.96183217e-01 -2.52345204e-01 -3.64183754e-01 3.02105010e-01
5.51053822e-01 9.77077559e-02 -7.90036440e-01 6.51841104e-01
-4.36549336e-01 1.00453593e-01 3.80674690e-01 1.09136581e+00
-1.84336871e-01 -1.50354445e+00 -1.74266994e-01 2.41572812e-01
-3.72083843e-01 9.47370976e-02 -2.33936772e-01 1.31060076e+00
-2.78912438e-03 8.60615969e-01 -2.32153758e-01 -5.09868145e-01
4.01623070e-01 -2.13157699e-01 7.10436344e-01 -1.72319531e-01
-7.43096054e-01 -2.36521900e-01 1.05724514e-01 -7.13783085e-01
-3.37130576e-01 -7.21856117e-01 -1.27712691e+00 -5.65867245e-01
4.55233045e-02 3.05304706e-01 4.47307438e-01 7.10736454e-01
2.50211835e-01 4.05421168e-01 7.49362290e-01 -5.25853574e-01
-8.39517772e-01 -7.27794230e-01 -4.61211413e-01 9.44290385e-02
5.87515384e-02 -9.29848313e-01 -3.72768968e-01 -5.10416746e-01] | [3.984215021133423, 1.7580773830413818] |
03b4a9a5-229a-4af9-9fb4-ca6214c4b2c0 | random-copolymer-inverse-design-system | 2212.00023 | null | https://arxiv.org/abs/2212.00023v2 | https://arxiv.org/pdf/2212.00023v2.pdf | Random Copolymer inverse design system orienting on Accurate discovering of Antimicrobial peptide-mimetic copolymers | Antimicrobial resistance is one of the biggest health problem, especially in the current period of COVID-19 pandemic. Due to the unique membrane-destruction bactericidal mechanism, antimicrobial peptide-mimetic copolymers are paid more attention and it is urgent to find more potential candidates with broad-spectrum antibacterial efficacy and low toxicity. Artificial intelligence has shown significant performance on small molecule or biotech drugs, however, the higher-dimension of polymer space and the limited experimental data restrict the application of existing methods on copolymer design. Herein, we develop a universal random copolymer inverse design system via multi-model copolymer representation learning, knowledge distillation and reinforcement learning. Our system realize a high-precision antimicrobial activity prediction with few-shot data by extracting various chemical information from multi-modal copolymer representations. By pre-training a scaffold-decorator generative model via knowledge distillation, copolymer space are greatly contracted to the near space of existing data for exploration. Thus, our reinforcement learning algorithm can be adaptive for customized generation on specific scaffolds and requirements on property or structures. We apply our system on collected antimicrobial peptide-mimetic copolymers data, and we discover candidate copolymers with desired properties. | ['Yang Tang', 'Tianyu Wu'] | 2022-11-30 | null | null | null | null | ['activity-prediction', 'activity-prediction'] | ['computer-vision', 'time-series'] | [ 6.17589116e-01 -4.91765022e-01 -5.43978333e-01 2.75826544e-01
-5.48059046e-01 -5.85366189e-01 3.00663739e-01 3.82048368e-01
-1.43615872e-01 1.38126957e+00 1.73798099e-01 -3.00998420e-01
-1.07745498e-01 -9.95421946e-01 -8.27787220e-01 -1.06164467e+00
5.08240536e-02 5.38311779e-01 -7.94001594e-02 -3.24858904e-01
4.63449538e-01 4.88847822e-01 -1.33608103e+00 3.60229760e-01
1.17933679e+00 6.99980617e-01 7.78430700e-01 5.07116556e-01
-2.52909869e-01 3.52011591e-01 -2.01591626e-01 1.25367165e-01
1.85844749e-02 -2.77886331e-01 -3.36116105e-01 -5.28979480e-01
-2.93720722e-01 -1.18391216e-01 -7.97654912e-02 6.04843616e-01
7.92550921e-01 -2.04216525e-01 1.06973541e+00 -7.31546283e-01
-8.37085426e-01 3.68273526e-01 -2.83172220e-01 -1.28023833e-01
3.67834568e-01 3.80940050e-01 7.48440564e-01 -7.05528617e-01
6.01235449e-01 1.18973315e+00 3.98052096e-01 6.18364334e-01
-1.28068972e+00 -8.49345863e-01 1.33658841e-01 2.71966755e-01
-1.00735176e+00 1.42796382e-01 7.37507403e-01 -7.18791127e-01
1.08560169e+00 1.34930685e-01 1.02437210e+00 1.50054312e+00
7.74035990e-01 6.65382206e-01 1.09547842e+00 2.10998982e-01
3.05379331e-01 -1.11337677e-01 -5.83799839e-01 6.20578468e-01
2.68124491e-01 2.78177947e-01 -1.67891234e-01 -5.07427335e-01
8.17734718e-01 6.94207430e-01 -2.54733831e-01 -6.14496052e-01
-1.07546043e+00 1.01073635e+00 3.13438535e-01 2.94477306e-02
-5.24078131e-01 -7.48690665e-02 3.64292353e-01 9.41476449e-02
-5.16148582e-02 1.16895986e+00 -9.26465750e-01 -6.73095789e-03
-4.28165644e-01 3.02244514e-01 6.41167760e-01 7.85658419e-01
7.51841903e-01 -5.95282242e-02 1.34570912e-01 8.41687381e-01
3.08509082e-01 7.05517411e-01 5.74315012e-01 -3.71603131e-01
-2.35513244e-02 5.26492417e-01 1.63716957e-01 -7.93253660e-01
-4.91131902e-01 -3.78245264e-01 -8.10971260e-01 -2.72551626e-01
-7.29372352e-02 -7.43981153e-02 -8.19389522e-01 1.77304685e+00
4.72185075e-01 -1.26030251e-01 3.61114472e-01 5.02332687e-01
6.68473721e-01 1.04724765e+00 6.79762006e-01 -7.34151483e-01
1.49543548e+00 -6.60914063e-01 -2.69975811e-01 1.55962974e-01
4.67112929e-01 -8.08150828e-01 7.94371486e-01 5.04450023e-01
-4.15710658e-01 -3.54922801e-01 -1.19562411e+00 5.72518170e-01
-3.70449632e-01 -2.65722901e-01 9.10793841e-01 3.58936042e-01
-4.83892187e-02 9.14747000e-01 -6.04451716e-01 -1.87425867e-01
5.45960844e-01 5.57326794e-01 -2.44108826e-01 -2.65441090e-01
-1.35589230e+00 7.25849807e-01 4.96233732e-01 -2.88687021e-01
-1.14585471e+00 -7.81838715e-01 -5.68947196e-01 -2.97078639e-01
3.70191574e-01 -1.06339145e+00 6.83008730e-01 -3.89303446e-01
-1.86345518e+00 7.72026926e-02 3.41659635e-01 -4.83527370e-02
1.39319748e-01 -1.78369284e-01 -3.65775645e-01 1.52742788e-01
1.71920583e-01 6.53077304e-01 7.78133929e-01 -9.99814272e-01
-4.29718584e-01 -2.39102021e-01 -2.24717304e-01 1.38952270e-01
-1.69314325e-01 -4.62460756e-01 3.56535763e-01 -9.44973409e-01
-8.29953626e-02 -1.06549525e+00 -6.66159809e-01 -4.59176898e-01
-3.04065138e-01 -4.10339743e-01 4.74072307e-01 -4.51682627e-01
1.03126991e+00 -1.83496392e+00 4.44817930e-01 1.71281666e-01
2.05558166e-03 1.10890791e-01 -4.58250880e-01 9.58982646e-01
-7.27923810e-02 9.57134217e-02 -1.55448645e-01 9.17478502e-01
-4.97831881e-01 3.88460718e-02 -3.96470398e-01 2.22985774e-01
2.45872363e-01 7.82560289e-01 -1.23040652e+00 -4.08079535e-01
2.81398520e-02 3.66430193e-01 -7.58273661e-01 2.78170526e-01
-1.01784825e+00 9.35912311e-01 -1.25482059e+00 1.12365830e+00
6.51056528e-01 -4.75961328e-01 3.52864236e-01 -4.95550096e-01
-3.35610323e-02 -1.50660783e-01 -5.35069287e-01 1.70786619e+00
-4.12812322e-01 -1.17498569e-01 -5.29481113e-01 -7.64466763e-01
1.07775819e+00 1.93582669e-01 9.83963251e-01 -7.87128985e-01
-1.67954955e-02 4.30204004e-01 1.45140454e-01 -7.39908457e-01
7.81935155e-02 -4.79899108e-01 2.19348371e-02 2.01966718e-01
-4.89385784e-01 -7.80246332e-02 4.47538160e-02 -1.26923040e-01
1.00998509e+00 4.70871925e-01 2.64066011e-01 -2.17443541e-01
5.24922788e-01 1.58786818e-01 6.93672776e-01 4.31526899e-01
3.16391587e-01 2.09971026e-01 2.07033381e-01 -5.74247479e-01
-1.39949107e+00 -8.01128089e-01 -2.49997228e-01 1.09409547e+00
2.76099801e-01 -2.37379223e-01 -4.12248343e-01 -4.25764471e-01
1.50511533e-01 3.76327246e-01 -4.70249414e-01 -2.01277152e-01
-7.67664194e-01 -9.20611680e-01 2.77279317e-01 3.86566848e-01
1.42906785e-01 -1.05725110e+00 -1.67296842e-01 9.24288571e-01
1.10511586e-01 -4.93988425e-01 -1.84833884e-01 2.29719251e-01
-8.71046066e-01 -1.27176285e+00 -8.26768458e-01 -1.08042490e+00
3.94718736e-01 9.16475505e-02 4.47793484e-01 -2.96942770e-01
-5.88091850e-01 1.49506956e-01 -2.81101257e-01 -4.30528820e-01
-7.13230431e-01 1.57314703e-01 1.54287264e-01 -3.72349650e-01
1.49041340e-01 -7.86352873e-01 -1.21776402e+00 4.32899803e-01
-6.66664898e-01 1.61627680e-01 1.20757031e+00 1.21271157e+00
1.07316625e+00 -1.30400881e-01 1.08827722e+00 -6.96239889e-01
7.08104730e-01 -6.98306739e-01 -4.60883886e-01 3.29253882e-01
-7.11580455e-01 4.95138705e-01 9.48827386e-01 -8.82332742e-01
-8.66966307e-01 1.30371571e-01 -1.59902915e-01 -6.46440834e-02
2.64158130e-01 4.03723955e-01 -4.68950003e-01 2.19971523e-01
5.31622469e-01 5.56162596e-01 2.90583253e-01 -2.42711976e-01
3.50627929e-01 6.03109241e-01 -1.43300816e-01 -9.49656069e-01
1.74591452e-01 8.84123221e-02 2.46542633e-01 -8.88395727e-01
-3.52661788e-01 -5.25034033e-02 1.91867292e-01 1.99432567e-01
9.50872004e-01 -1.02170455e+00 -1.05420995e+00 4.00115848e-01
-9.76608813e-01 -5.61475346e-04 5.02355136e-02 5.91597438e-01
-8.81878912e-01 5.80987692e-01 -5.37811339e-01 -2.54057616e-01
-6.80374205e-01 -1.53498518e+00 6.44355536e-01 7.99002424e-02
-2.58879751e-01 -5.03875077e-01 5.80187321e-01 3.60628635e-01
3.14892888e-01 4.59082365e-01 1.58589816e+00 -4.96868163e-01
-8.97617102e-01 7.76750669e-02 8.67970660e-02 2.59236634e-01
4.75997269e-01 -1.94867909e-01 -3.99204373e-01 -4.95375127e-01
-1.54290035e-01 -3.83350760e-01 7.90084362e-01 5.34744740e-01
1.27914941e+00 -4.61757869e-01 -8.17953110e-01 4.41661924e-01
1.41168118e+00 8.43270898e-01 6.21564627e-01 4.29301530e-01
7.70575106e-01 2.87870228e-01 7.93867409e-01 6.14944756e-01
1.65358149e-02 3.02250147e-01 4.67322350e-01 2.41501346e-01
2.28358388e-01 -7.07708001e-01 7.35636279e-02 5.33329248e-01
-3.43175411e-01 -3.02002728e-01 -5.01104355e-01 2.02182710e-01
-1.64955413e+00 -9.43235159e-01 4.37356025e-01 1.97753990e+00
1.14552319e+00 -2.00913787e-01 7.76649639e-02 -3.91124606e-01
6.05776548e-01 -9.69625190e-02 -1.14340460e+00 -1.86320096e-01
-3.16021264e-01 2.83102751e-01 5.58697164e-01 -2.92866379e-02
-9.99360561e-01 7.39664793e-01 6.05847931e+00 1.13595545e+00
-1.20151341e+00 -3.76809120e-01 5.38556576e-01 1.12228952e-01
-5.94739139e-01 6.40628636e-02 -6.16493046e-01 6.88247204e-01
5.61888278e-01 5.85955642e-02 4.30772960e-01 8.91886115e-01
4.15456444e-02 1.14112869e-01 -1.10808671e+00 1.00574577e+00
-4.21137929e-01 -1.79451168e+00 4.80894297e-01 2.00497702e-01
8.36695790e-01 -2.08282873e-01 3.58244069e-02 2.06176080e-02
2.47487739e-01 -1.11255777e+00 7.69585148e-02 5.88678598e-01
8.27162087e-01 -8.06757867e-01 3.10462207e-01 1.06128544e-01
-1.07618117e+00 -4.43146288e-01 -4.06299472e-01 3.51129413e-01
7.27731660e-02 3.02001983e-01 -1.05400407e+00 2.39207745e-01
1.26077890e-01 8.58980060e-01 1.21207938e-01 8.44173133e-01
-2.94662034e-03 1.42485484e-01 -1.91959009e-01 -7.16149807e-01
-2.81192027e-02 -4.21675116e-01 4.24104869e-01 8.17221701e-01
4.13007259e-01 3.28344315e-01 5.00803947e-01 2.99897790e-01
6.38049915e-02 5.98375320e-01 -6.39050007e-01 -6.18962586e-01
6.05128884e-01 6.92421556e-01 -4.58454490e-01 -3.36342156e-01
-2.45117024e-01 4.79355723e-01 -7.24110529e-02 3.09890717e-01
-7.34214306e-01 -1.58083588e-01 7.29417145e-01 1.27385706e-01
5.08240044e-01 -1.22167937e-01 6.69169948e-02 -6.72328830e-01
-6.18230879e-01 -1.28896081e+00 2.95986444e-01 -3.58498156e-01
-1.46329939e+00 2.61788726e-01 -2.76748985e-01 -1.40292680e+00
1.24833055e-01 -6.40565813e-01 -2.08360627e-01 6.02304935e-01
-1.29381287e+00 -1.05886972e+00 1.56495154e-01 2.10016862e-01
6.56578600e-01 -4.97192025e-01 1.03933370e+00 6.51702806e-02
-3.77576232e-01 1.31592616e-01 5.30878663e-01 -6.25892103e-01
7.93519378e-01 -6.45683348e-01 -2.80981451e-01 -1.99391052e-01
-7.54311442e-01 7.12044895e-01 8.33436847e-01 -1.11132312e+00
-1.85530543e+00 -9.89704192e-01 2.91812164e-03 -2.22672641e-01
6.56683147e-01 -1.03190675e-01 -6.80123091e-01 2.73831822e-02
3.33512053e-02 -7.53042877e-01 1.23716021e+00 -2.23341912e-01
-2.85229862e-01 -2.50460044e-03 -9.40817356e-01 7.03200102e-01
9.63519156e-01 -7.55299926e-02 -2.41087973e-01 6.91327274e-01
1.06973028e+00 -9.98777151e-02 -1.29950464e+00 7.93436706e-01
1.00468266e+00 -3.01304638e-01 1.15084207e+00 -9.94837165e-01
5.94347656e-01 -4.48462576e-01 -2.80105442e-01 -1.17990804e+00
-6.50676072e-01 -6.90957189e-01 4.18817699e-02 5.56412995e-01
5.53801239e-01 -6.54933929e-01 9.04397845e-01 -2.36275699e-02
-7.72203952e-02 -1.36442387e+00 -6.60745442e-01 -5.55844486e-01
1.58924341e-01 3.03273976e-01 9.18837965e-01 7.18162060e-01
-4.93388213e-02 6.54679000e-01 -6.53186321e-01 -1.91475183e-01
2.73119450e-01 7.10034788e-01 7.09223270e-01 -1.14662373e+00
-6.73594117e-01 -3.02405298e-01 -1.59625456e-01 -1.24275780e+00
-2.57729352e-01 -7.86313117e-01 -3.10506046e-01 -1.60622478e+00
4.40313369e-01 -9.23046529e-01 -3.98692578e-01 2.05376327e-01
1.40058640e-02 -4.39263165e-01 -3.00175250e-01 2.77653754e-01
-2.93412149e-01 9.39524889e-01 1.89152455e+00 -6.59720838e-01
-4.18712497e-01 7.27404356e-02 -9.75961983e-01 2.26917058e-01
7.84071326e-01 -4.03226674e-01 -5.62522948e-01 1.52217269e-01
6.13230169e-01 3.45761418e-01 -3.22738647e-01 -6.24969184e-01
-3.54764163e-01 -8.53724778e-01 5.87028146e-01 -6.14884138e-01
2.88124710e-01 -6.27535760e-01 8.08808565e-01 1.10110450e+00
-7.32515007e-03 -1.12563908e-01 1.58858374e-01 1.03349411e+00
1.99239179e-01 1.16020501e-01 5.02269030e-01 -3.60975534e-01
-5.16948283e-01 6.80005908e-01 -6.75797343e-01 -2.81801403e-01
1.12505603e+00 -4.46119487e-01 -2.43588194e-01 2.34745726e-01
-6.24739766e-01 1.13991834e-01 6.07975423e-01 4.76537824e-01
8.25000882e-01 -1.12283731e+00 -5.89574099e-01 2.93395042e-01
2.56792128e-01 -1.44376889e-01 6.65076911e-01 4.07060623e-01
-6.11122310e-01 4.47800785e-01 -4.74044412e-01 -7.35019922e-01
-9.68941152e-01 1.08910036e+00 3.43818255e-02 -2.34399229e-01
-2.62020469e-01 5.89717209e-01 6.23576820e-01 -8.90385360e-02
-3.67978096e-01 -6.14051372e-02 -4.22238708e-01 4.13294770e-02
2.72967398e-01 2.39508152e-01 -3.30939174e-01 2.02065501e-02
-3.71944159e-01 7.67279744e-01 -4.25839871e-01 6.99340820e-01
1.66722739e+00 4.67061460e-01 -1.81990415e-02 -1.86685264e-01
1.15455711e+00 4.74385284e-02 -1.29572403e+00 -2.57596951e-02
-5.15096664e-01 -2.42299557e-01 -5.73012054e-01 -7.68537164e-01
-3.75567704e-01 4.36811149e-01 7.45334744e-01 -2.50169247e-01
8.23826075e-01 1.32420272e-01 9.30069149e-01 5.72193742e-01
4.08791840e-01 -1.10046232e+00 5.37799716e-01 1.40433177e-01
9.43901837e-01 -1.04431188e+00 3.50649059e-01 -3.46099526e-01
-4.35507268e-01 1.03340495e+00 4.12836879e-01 1.99894324e-01
4.99789834e-01 -7.43886828e-02 -2.91103750e-01 -1.31796226e-01
-7.19641089e-01 5.31302869e-01 -2.58270979e-01 7.88169265e-01
2.44332820e-01 4.10462081e-01 -6.24186218e-01 5.27377307e-01
-9.30352602e-03 -9.77714434e-02 5.13937287e-02 1.11111093e+00
-8.19462836e-01 -1.66919518e+00 -1.13355994e-01 6.06445968e-01
-1.47996783e-01 -2.71211445e-01 -7.67614990e-02 3.98230553e-01
1.16430469e-01 5.81760705e-01 -3.36611629e-01 -3.90314460e-01
2.27693781e-01 -2.24753633e-01 8.25788379e-01 -3.10346931e-01
6.93008602e-02 3.68667006e-01 8.31123814e-02 -9.78603736e-02
-1.81175992e-01 -6.43298090e-01 -1.42531693e+00 3.65434475e-02
-5.13847768e-01 3.36927205e-01 8.29639375e-01 6.51791930e-01
8.34534764e-01 4.25798059e-01 9.60974514e-01 -5.18397331e-01
-5.82901239e-01 -7.04386055e-01 -4.43012774e-01 9.33820009e-02
-7.03724660e-03 -8.87634933e-01 2.57475555e-01 -1.22066423e-01] | [4.979572296142578, 5.719258785247803] |
8584178e-dbeb-42bb-942a-2979a746dadc | behavior-from-the-void-unsupervised-active | 2103.04551 | null | https://arxiv.org/abs/2103.04551v4 | https://arxiv.org/pdf/2103.04551v4.pdf | Behavior From the Void: Unsupervised Active Pre-Training | We introduce a new unsupervised pre-training method for reinforcement learning called APT, which stands for Active Pre-Training. APT learns behaviors and representations by actively searching for novel states in reward-free environments. The key novel idea is to explore the environment by maximizing a non-parametric entropy computed in an abstract representation space, which avoids challenging density modeling and consequently allows our approach to scale much better in environments that have high-dimensional observations (e.g., image observations). We empirically evaluate APT by exposing task-specific reward after a long unsupervised pre-training phase. In Atari games, APT achieves human-level performance on 12 games and obtains highly competitive performance compared to canonical fully supervised RL algorithms. On DMControl suite, APT beats all baselines in terms of asymptotic performance and data efficiency and dramatically improves performance on tasks that are extremely difficult to train from scratch. | ['Pieter Abbeel', 'Hao liu'] | 2021-03-08 | null | http://proceedings.neurips.cc/paper/2021/hash/99bf3d153d4bf67d640051a1af322505-Abstract.html | http://proceedings.neurips.cc/paper/2021/file/99bf3d153d4bf67d640051a1af322505-Paper.pdf | neurips-2021-12 | ['unsupervised-pre-training'] | ['methodology'] | [-2.11455151e-02 1.36053503e-01 -4.55646694e-01 -1.02912858e-01
-9.26969707e-01 -5.27625144e-01 8.87923837e-01 -6.32969141e-02
-9.87872839e-01 1.01534164e+00 1.71744809e-01 -1.26674160e-01
-5.03621437e-02 -6.49951160e-01 -7.98243761e-01 -7.46711731e-01
-5.09786308e-01 8.99564028e-01 4.64728698e-02 -2.54857630e-01
1.42787740e-01 2.59470731e-01 -1.56627166e+00 -2.05071032e-01
7.06850290e-01 6.91091001e-01 3.50914359e-01 7.22331643e-01
3.21722627e-01 9.88368988e-01 -3.73120040e-01 9.72261000e-03
3.19512367e-01 -5.37461042e-01 -7.83843637e-01 1.45251065e-01
-2.15651125e-01 -6.66521311e-01 -5.91025412e-01 9.45042968e-01
2.99066067e-01 7.27896452e-01 7.53930032e-01 -9.74545538e-01
-5.55878222e-01 6.90510213e-01 -4.73040104e-01 3.29893470e-01
2.75775999e-01 5.80976009e-01 9.28379834e-01 -5.29030740e-01
5.16571462e-01 1.12878537e+00 1.04281470e-01 8.96590233e-01
-1.77912521e+00 -5.33071697e-01 1.94897354e-01 -7.22605921e-03
-9.57596719e-01 -4.73165482e-01 2.33843938e-01 -1.25463486e-01
1.29603529e+00 -2.18616739e-01 6.70672357e-01 1.53231382e+00
1.18472144e-01 1.19582510e+00 1.25697684e+00 -8.68939087e-02
9.06323016e-01 -1.94646731e-01 -2.97863454e-01 5.20736158e-01
2.29613204e-02 7.99841821e-01 -5.75559914e-01 -1.32360920e-01
9.82508242e-01 -2.83835884e-02 1.81705907e-01 -9.05811846e-01
-1.18775284e+00 1.01208615e+00 3.61529291e-01 2.91507021e-02
-5.41029513e-01 6.39418840e-01 2.67678708e-01 6.45628095e-01
1.43624805e-02 8.39838922e-01 -4.30986226e-01 -9.23253000e-01
-5.36322355e-01 5.49549282e-01 5.73910773e-01 8.20931196e-01
9.29333329e-01 4.34413821e-01 -1.35010853e-01 6.32221401e-01
8.69664475e-02 5.95888078e-01 9.44606960e-01 -1.38917768e+00
2.89315790e-01 1.39273494e-01 2.82722354e-01 -1.49625763e-01
-2.54700214e-01 -4.99698132e-01 -4.20226783e-01 6.24707937e-01
2.72111386e-01 -5.75367689e-01 -9.62158263e-01 1.94765997e+00
1.52810678e-01 1.24128453e-01 4.96965796e-01 6.64824128e-01
1.94189921e-01 6.21443570e-01 1.28814518e-01 -2.38799229e-01
6.99662149e-01 -1.00549924e+00 -3.43388587e-01 -5.95221877e-01
6.62224054e-01 1.06836088e-01 1.40392303e+00 6.49014533e-01
-1.15989661e+00 -2.96771049e-01 -8.18219781e-01 2.84875304e-01
-1.13752276e-01 -3.99343580e-01 1.01214993e+00 4.47573066e-01
-1.11797607e+00 8.72864783e-01 -1.21465313e+00 -1.87327132e-01
6.38178885e-01 5.18594563e-01 -3.67016107e-01 9.03327465e-02
-9.21830237e-01 8.56908619e-01 5.74705064e-01 -5.49550474e-01
-1.94054782e+00 -3.48507881e-01 -1.08430505e+00 1.00677989e-01
7.52121329e-01 -3.73416126e-01 1.83065724e+00 -8.16079557e-01
-2.07051921e+00 4.52042013e-01 2.41780758e-01 -1.01362121e+00
3.10110778e-01 -5.31034231e-01 -4.65320684e-02 1.37946472e-01
3.79710458e-02 9.82655585e-01 9.80596185e-01 -1.09449089e+00
-3.82173538e-01 -1.32253751e-01 1.90149784e-01 7.61051178e-01
-2.44910061e-01 -3.63779038e-01 -1.24642178e-01 -4.87373322e-01
-4.18465108e-01 -1.11042011e+00 -8.00601184e-01 -4.24217314e-01
5.44929281e-02 -2.89099097e-01 5.56582630e-01 -3.66492197e-02
6.56785607e-01 -2.06668115e+00 3.74749273e-01 8.71256143e-02
2.21122697e-01 1.29170179e-01 -3.45372200e-01 4.00227755e-01
5.46047352e-02 -1.62440732e-01 -1.09013684e-01 -4.22660738e-01
2.29551211e-01 5.91602445e-01 -4.24959868e-01 3.11626107e-01
1.99008554e-01 1.24175036e+00 -1.35688829e+00 -2.61964291e-01
2.22959369e-01 -1.38441652e-01 -9.78525162e-01 5.35226703e-01
-7.22785532e-01 6.76493227e-01 -5.61317325e-01 3.78054112e-01
7.98551291e-02 -3.58873457e-01 2.18918979e-01 8.70453894e-01
2.19361261e-01 3.54120433e-01 -9.40351665e-01 2.21762633e+00
-4.45546240e-01 3.09479117e-01 -3.28348547e-01 -1.09354222e+00
8.31883669e-01 4.90583517e-02 5.05199432e-01 -8.28246176e-01
5.36006726e-02 -1.49465173e-01 6.72059879e-02 -8.17455873e-02
6.67117059e-01 -1.60561457e-01 -3.57427478e-01 7.15073347e-01
4.89954829e-01 -3.91883492e-01 1.02023512e-01 3.95046592e-01
1.43774176e+00 4.70354646e-01 3.82185429e-01 -2.32894033e-01
-2.16773331e-01 -1.39086872e-01 2.91093707e-01 1.18349063e+00
-2.45862007e-01 1.91173464e-01 6.52207613e-01 -2.64647931e-01
-7.05148339e-01 -1.57246053e+00 1.97887197e-01 1.45615613e+00
5.44668585e-02 -5.14563799e-01 -4.83538181e-01 -8.93286467e-01
-3.00207250e-02 8.47388208e-01 -8.60126138e-01 -6.15370810e-01
-2.32188791e-01 -5.29542267e-01 3.16070557e-01 5.74613750e-01
5.98186731e-01 -1.51904380e+00 -9.58207190e-01 2.05361754e-01
2.45467246e-01 -8.09101641e-01 -1.83846280e-01 8.83344829e-01
-1.14814413e+00 -5.37748277e-01 -6.55820966e-01 -5.00651300e-01
4.17295963e-01 -1.20438049e-02 1.17502487e+00 -2.49743283e-01
-1.43427372e-01 5.96784532e-01 -3.68218333e-01 -1.67255148e-01
-2.71197557e-01 2.66542822e-01 4.13316458e-01 -5.50589979e-01
2.55333155e-01 -8.76416445e-01 -4.72568870e-01 1.85308810e-02
-7.25645006e-01 -2.32912317e-01 8.21608186e-01 1.12592638e+00
5.71863353e-01 -3.49210599e-03 6.52623892e-01 -7.28104413e-01
8.71681035e-01 -6.26471102e-01 -9.12317336e-01 -1.32727012e-01
-6.53498352e-01 6.59765124e-01 6.64252937e-01 -6.34267926e-01
-1.00423884e+00 1.34829506e-01 1.26091421e-01 -4.97510910e-01
-3.83036792e-01 3.61284733e-01 2.98915982e-01 3.22989970e-01
1.15650499e+00 5.46216726e-01 2.37662017e-01 -3.13443780e-01
6.19251609e-01 1.22131974e-01 5.41283250e-01 -1.01265132e+00
9.44075584e-01 4.69615348e-02 -2.30892271e-01 -5.32402754e-01
-6.56714320e-01 -1.51491031e-01 -2.22803980e-01 6.34855926e-02
6.30603075e-01 -9.93740618e-01 -1.03857243e+00 2.23761708e-01
-2.46189341e-01 -1.28547883e+00 -1.03219116e+00 6.85763359e-01
-1.30116093e+00 1.28335968e-01 -5.76926887e-01 -9.39310610e-01
6.08888417e-02 -1.09469461e+00 8.53610098e-01 4.45509046e-01
-2.76016355e-01 -8.90301466e-01 5.80567777e-01 -1.34938806e-01
5.01936495e-01 -1.33142620e-01 6.30841494e-01 -6.82011247e-01
-5.88647902e-01 2.81599045e-01 2.80257672e-01 2.92021185e-01
-1.38889756e-02 -6.14422441e-01 -7.93047488e-01 -6.06085241e-01
-2.12279707e-01 -1.42550564e+00 9.46266234e-01 2.54431516e-01
1.42186201e+00 -1.01952791e-01 -9.38581154e-02 5.31718075e-01
1.05242682e+00 2.44100615e-01 6.47043765e-01 3.71590167e-01
5.36631607e-02 1.20954402e-01 6.76282883e-01 8.46820831e-01
1.89312935e-01 5.31277835e-01 6.52570009e-01 2.32443035e-01
4.87896949e-01 -5.51788747e-01 7.80667901e-01 2.80359089e-01
-7.48170242e-02 -1.15807578e-01 -6.01328969e-01 4.35281485e-01
-1.98049366e+00 -1.04467952e+00 9.20576513e-01 2.24660945e+00
1.05841923e+00 4.35680389e-01 5.43567896e-01 -3.63875031e-01
7.92459697e-02 1.39090970e-01 -1.21603346e+00 -4.08019066e-01
1.14100739e-01 7.36634195e-01 4.02912706e-01 4.47487175e-01
-1.06654668e+00 1.36504328e+00 7.48768473e+00 7.89784849e-01
-7.21043348e-01 -1.74223080e-01 6.48492932e-01 -4.73344117e-01
-1.01288207e-01 -2.10361648e-02 -5.41552007e-01 1.41614094e-01
1.16051400e+00 -2.66335666e-01 1.06286013e+00 1.32253492e+00
-2.16034129e-01 -4.31801617e-01 -1.26119721e+00 9.94680405e-01
-2.93398976e-01 -1.19110668e+00 -2.78921008e-01 4.64439869e-01
7.56041110e-01 5.86191893e-01 5.91635764e-01 1.14455104e+00
1.40000677e+00 -1.34657812e+00 3.25962633e-01 2.04388842e-01
7.71097243e-01 -8.94353509e-01 2.45808512e-01 7.48321950e-01
-6.22262716e-01 -2.81269103e-01 -5.93886912e-01 -3.29516232e-01
-1.91935256e-01 -1.87646046e-01 -7.97587812e-01 -2.90295258e-02
6.80169344e-01 9.30122614e-01 -4.72924590e-01 8.13666403e-01
-4.59271163e-01 6.89743340e-01 -3.42207164e-01 -3.35127652e-01
6.61639631e-01 -1.89573392e-01 3.80356520e-01 8.28850508e-01
1.08410984e-01 9.91267934e-02 3.97082120e-01 9.73134100e-01
-2.10020021e-01 -2.46305600e-01 -9.96990025e-01 -3.52110237e-01
2.86569774e-01 1.15122676e+00 -5.23233056e-01 -3.22665364e-01
2.58576926e-02 1.08225167e+00 8.64924431e-01 4.41888034e-01
-8.06267500e-01 -8.02117512e-02 7.18548656e-01 -2.73452759e-01
4.99948204e-01 -4.06538457e-01 3.13413888e-01 -1.37310541e+00
-4.63541031e-01 -1.13458180e+00 4.33593303e-01 -5.96596360e-01
-1.02018845e+00 4.51882809e-01 2.34595314e-01 -1.03272760e+00
-1.06917763e+00 -4.67422128e-01 -5.00829041e-01 3.66118878e-01
-1.29812229e+00 -4.14848506e-01 1.84593976e-01 9.21217322e-01
6.08595133e-01 -5.25473416e-01 1.11861193e+00 -4.02340204e-01
-3.84650737e-01 6.27746165e-01 3.43997687e-01 -8.00474286e-02
3.22919041e-01 -1.64844406e+00 5.09594738e-01 5.73952258e-01
6.16984963e-01 5.99585295e-01 6.02710903e-01 -5.24509549e-01
-1.44898236e+00 -7.27920294e-01 -1.61703900e-01 -5.78515351e-01
6.64689422e-01 -6.44410014e-01 -5.92384338e-01 9.04726744e-01
2.78210253e-01 1.07016612e-03 5.30998170e-01 3.67878914e-01
-2.54069120e-01 2.62299716e-01 -1.01608729e+00 8.86854768e-01
1.16717243e+00 -5.13205111e-01 -8.50965917e-01 2.07705587e-01
6.83346629e-01 -4.62792277e-01 -6.05897546e-01 3.55345458e-02
2.10605398e-01 -8.85014355e-01 9.10053790e-01 -9.95012879e-01
3.93063366e-01 1.42935261e-01 -1.34364858e-01 -1.66824758e+00
-4.20429021e-01 -1.23691952e+00 -5.82222760e-01 4.06116575e-01
3.49551171e-01 -5.02145886e-01 1.17539322e+00 3.77973735e-01
3.46300937e-02 -7.33785450e-01 -6.54300749e-01 -1.06038249e+00
3.72179806e-01 -3.75973225e-01 5.48887610e-01 5.86406648e-01
4.09030885e-01 4.12138432e-01 -4.84635919e-01 -3.59620541e-01
6.05498493e-01 6.66454509e-02 1.03847849e+00 -9.25606489e-01
-8.65896285e-01 -2.74362087e-01 -2.79472262e-01 -1.55806804e+00
4.00701135e-01 -7.63606310e-01 3.05857092e-01 -1.09858561e+00
1.95212319e-01 -3.49792898e-01 -5.49522996e-01 5.69006026e-01
6.67961091e-02 -9.64117050e-02 7.48515725e-02 8.95824507e-02
-1.29752719e+00 1.22442019e+00 1.18820715e+00 1.64145961e-01
-4.60958093e-01 -1.36095479e-01 -8.16007078e-01 6.98571801e-01
1.03544021e+00 -5.42237043e-01 -8.97553861e-01 -2.66826868e-01
1.58442289e-01 2.53178596e-01 2.11366355e-01 -1.18072474e+00
-4.69427146e-02 -6.08239174e-01 4.72816169e-01 -3.25315356e-01
6.14375174e-01 -5.09615660e-01 -4.12517637e-01 5.01060486e-01
-7.67805815e-01 1.17924623e-01 2.13298231e-01 8.80809069e-01
8.13423395e-02 -9.80573595e-02 7.94587493e-01 -3.80032629e-01
-7.62743175e-01 5.24650812e-01 -9.32198107e-01 4.85967129e-01
1.13126397e+00 -1.16294235e-01 -2.51397401e-01 -8.25726151e-01
-1.00565970e+00 3.88851911e-01 5.71604908e-01 3.24845880e-01
6.94992006e-01 -1.28042686e+00 -4.22063440e-01 2.42157310e-01
2.19011217e-01 1.08788304e-01 8.58126208e-02 4.13753718e-01
-1.84721932e-01 9.06528831e-02 -4.36232477e-01 -4.66644734e-01
-6.28275633e-01 5.97935438e-01 3.52805763e-01 -6.92207396e-01
-8.17294061e-01 8.80163431e-01 3.14706355e-01 -5.02305269e-01
3.96808803e-01 -3.48703861e-01 -1.92512617e-01 -5.36102653e-01
5.93268931e-01 -3.43844667e-02 -3.65955174e-01 -1.46942243e-01
-2.12787441e-03 -1.57776594e-01 -4.03045744e-01 -6.48381472e-01
1.46760106e+00 1.96516171e-01 5.79625010e-01 5.60844421e-01
9.38281119e-01 -3.97416204e-01 -1.91342545e+00 -4.06704903e-01
5.26909605e-02 -4.96967226e-01 6.86250813e-03 -7.49784648e-01
-8.21839273e-01 7.87427008e-01 5.95075846e-01 -8.17125812e-02
7.05292523e-01 1.66303203e-01 4.42759693e-01 1.29040909e+00
6.22081816e-01 -1.38585258e+00 9.36354697e-01 8.50238740e-01
6.19651556e-01 -1.24908948e+00 -4.17716093e-02 6.13009691e-01
-1.07557070e+00 7.28565395e-01 9.08677816e-01 -6.02864802e-01
4.66311842e-01 2.29906410e-01 -3.68475437e-01 -1.52194083e-01
-1.18624580e+00 -3.57885629e-01 -4.49060462e-02 9.81209695e-01
-1.80256087e-02 4.77912538e-02 5.24522603e-01 4.09853905e-01
-3.93710226e-01 -6.02707304e-02 5.03329217e-01 1.17280626e+00
-6.24341071e-01 -1.10492325e+00 1.53898373e-01 6.03395283e-01
-2.35399723e-01 -3.46763581e-02 -1.73110425e-01 7.59817064e-01
-4.72333819e-01 7.46633351e-01 9.38530713e-02 -3.97856146e-01
-7.65479356e-02 -7.26483911e-02 7.81093419e-01 -8.85565162e-01
-4.38733876e-01 2.13215183e-02 -6.01169840e-02 -9.97538924e-01
-1.00284405e-01 -8.15549314e-01 -1.48535609e+00 -1.41559541e-01
-2.50390600e-02 3.73641521e-01 1.76613241e-01 9.72415924e-01
2.76715398e-01 2.97436535e-01 6.69529736e-01 -8.57309699e-01
-1.10059249e+00 -7.56598532e-01 -6.87041700e-01 3.36172372e-01
3.60950470e-01 -1.04268730e+00 -1.44148275e-01 -2.82422364e-01] | [4.007068634033203, 1.5225600004196167] |
c6dcf410-7cb6-463b-8c5c-2bbd4c79ce65 | what-is-learned-in-knowledge-graph-embeddings | 2110.09978 | null | https://arxiv.org/abs/2110.09978v1 | https://arxiv.org/pdf/2110.09978v1.pdf | What is Learned in Knowledge Graph Embeddings? | A knowledge graph (KG) is a data structure which represents entities and relations as the vertices and edges of a directed graph with edge types. KGs are an important primitive in modern machine learning and artificial intelligence. Embedding-based models, such as the seminal TransE [Bordes et al., 2013] and the recent PairRE [Chao et al., 2020] are among the most popular and successful approaches for representing KGs and inferring missing edges (link completion). Their relative success is often credited in the literature to their ability to learn logical rules between the relations. In this work, we investigate whether learning rules between relations is indeed what drives the performance of embedding-based methods. We define motif learning and two alternative mechanisms, network learning (based only on the connectivity of the KG, ignoring the relation types), and unstructured statistical learning (ignoring the connectivity of the graph). Using experiments on synthetic KGs, we show that KG models can learn motifs and how this ability is degraded by non-motif (noise) edges. We propose tests to distinguish the contributions of the three mechanisms to performance, and apply them to popular KG benchmarks. We also discuss an issue with the standard performance testing protocol and suggest an improvement. To appear in the proceedings of Complex Networks 2021. | ['Andrew Wood', 'Trung V. Dang', 'Peter Chin', 'Tianqi Wu', 'Omri Ben-Eliezer', 'Michael Simkin', 'Michael R. Douglas'] | 2021-10-19 | null | null | null | null | ['knowledge-graph-embeddings', 'knowledge-graph-embeddings'] | ['graphs', 'methodology'] | [-1.47680286e-03 6.55215740e-01 -5.37649989e-01 -7.08376169e-02
9.57794338e-02 -5.53620815e-01 7.42884874e-01 4.95683044e-01
5.32731675e-02 6.27000272e-01 2.11229309e-01 -5.57375550e-01
-6.30980968e-01 -1.29659557e+00 -1.05827248e+00 -2.57707238e-01
-9.45620239e-01 6.35748923e-01 3.34010303e-01 -2.67591000e-01
-1.10856630e-03 2.79273570e-01 -1.46822965e+00 2.56600529e-01
6.31515563e-01 6.67284429e-01 -3.35808903e-01 6.55039549e-01
-3.07302177e-01 9.98494983e-01 -3.03213269e-01 -6.09288275e-01
1.65723264e-01 -2.36845165e-01 -9.85537708e-01 -2.30033666e-01
2.68360525e-01 1.07469194e-01 -6.75725400e-01 8.47031891e-01
1.60830542e-01 -2.35138655e-01 7.50422478e-01 -1.77211034e+00
-4.09106702e-01 1.22778618e+00 -4.48676378e-01 1.24806203e-02
6.36919916e-01 -2.81823665e-01 1.54460526e+00 -8.22502732e-01
9.81816888e-01 1.19261432e+00 8.81480455e-01 1.83975533e-01
-1.63211143e+00 -2.95561999e-01 2.36196220e-02 7.12879121e-01
-1.40938890e+00 -3.34282190e-01 8.02275002e-01 -4.64001536e-01
1.03039050e+00 2.40868196e-01 6.59254193e-01 9.03586090e-01
3.99402194e-02 5.53948700e-01 9.26221728e-01 -6.99380875e-01
1.91421747e-01 -7.65571604e-03 4.51871157e-01 1.05278087e+00
7.38112211e-01 1.41741693e-01 -7.50033081e-01 -5.37548184e-01
4.89984423e-01 -3.09562445e-01 -1.76879525e-01 -7.75620162e-01
-1.13967276e+00 8.45672965e-01 5.60613930e-01 1.90683693e-01
-5.40073477e-02 2.09402159e-01 4.94552672e-01 6.27260029e-01
1.85876310e-01 4.34810907e-01 -4.53159451e-01 8.78938753e-03
-5.42736709e-01 1.16501234e-01 1.37075102e+00 9.34149504e-01
8.33655417e-01 -1.97351620e-01 3.35444272e-01 5.95360637e-01
2.72480816e-01 -1.14460714e-01 -1.97280571e-02 -6.71784043e-01
3.87110770e-01 9.14129615e-01 -3.24828506e-01 -1.50019681e+00
-4.75646287e-01 -2.75605887e-01 -7.46020377e-01 -2.03850403e-01
5.23949265e-01 1.76135488e-02 -5.39586723e-01 1.66795647e+00
1.99440181e-01 5.66288829e-01 -6.54801279e-02 3.24239284e-01
9.25769210e-01 2.71165192e-01 -2.22925246e-01 -9.71371755e-02
9.58614111e-01 -7.33967483e-01 -4.34128046e-01 -1.16403098e-05
9.80202496e-01 -2.90010750e-01 6.04469597e-01 2.31444970e-01
-7.98519611e-01 -2.48914585e-01 -1.18583345e+00 2.99307615e-01
-7.52559304e-01 -3.17451388e-01 1.00005817e+00 4.46310073e-01
-1.10184300e+00 9.43945169e-01 -6.90929294e-01 -4.94459420e-01
1.91301093e-01 4.60985243e-01 -6.44972146e-01 -1.52268887e-01
-1.48351121e+00 9.06095386e-01 6.27063096e-01 -8.10689584e-04
-4.10926282e-01 -5.48242867e-01 -9.68342364e-01 6.06347732e-02
7.25516081e-01 -6.84882104e-01 5.39976537e-01 -5.91681182e-01
-8.30234528e-01 7.71912694e-01 8.89001712e-02 -6.08717263e-01
2.45156184e-01 1.12881698e-01 -6.65552974e-01 5.95500655e-02
-1.21844351e-01 3.09225738e-01 6.20146811e-01 -1.25250530e+00
-3.73713225e-01 -2.48507023e-01 2.99358100e-01 -3.28071177e-01
-2.29262367e-01 -3.06863695e-01 -1.95630804e-01 -4.45849776e-01
3.21032494e-01 -9.75374162e-01 5.62190339e-02 -1.78085268e-01
-8.31361115e-01 -4.42745596e-01 6.18583202e-01 -4.82305229e-01
1.50870943e+00 -1.95122528e+00 4.17666644e-01 8.66432726e-01
6.29985094e-01 -3.57719623e-02 -1.46393940e-01 1.01581967e+00
-2.91589528e-01 4.10076499e-01 -1.16215989e-01 5.07494360e-02
2.20966488e-01 6.22348607e-01 -7.39964247e-02 3.78886193e-01
2.57278621e-01 1.16775930e+00 -9.76397693e-01 -4.49263245e-01
3.70620191e-02 3.41506273e-01 -3.45283836e-01 -1.30841032e-01
-3.81778926e-01 -8.25177804e-02 -1.04508087e-01 6.03592038e-01
1.91852689e-01 -4.38509613e-01 9.07282889e-01 -5.66806495e-01
3.30049187e-01 4.81843412e-01 -1.59510756e+00 1.18930495e+00
-5.44607304e-02 6.63583994e-01 -1.06510811e-01 -1.41312981e+00
7.51054764e-01 2.30859637e-01 4.93897766e-01 -3.02929759e-01
-1.81888700e-01 1.60605788e-01 3.51334810e-01 -3.92447561e-01
2.97940314e-01 2.36369431e-01 2.50638928e-02 4.59905505e-01
9.53928530e-02 1.58928826e-01 5.27787447e-01 6.69624627e-01
1.53341115e+00 -3.51634808e-02 4.21454132e-01 -2.85866410e-01
2.89105535e-01 -3.90030555e-02 4.28493440e-01 7.96952665e-01
1.09727673e-01 6.77428842e-02 1.06511188e+00 -6.24118924e-01
-1.06521094e+00 -1.15184033e+00 -7.27607086e-02 7.61467040e-01
-5.89165874e-02 -1.23329830e+00 -1.79579496e-01 -8.20953548e-01
4.78405714e-01 3.33665401e-01 -8.61033261e-01 -3.94474804e-01
-4.66597766e-01 -5.53183556e-01 7.00696886e-01 5.62695086e-01
1.53118029e-01 -8.41832280e-01 7.08036944e-02 2.07040519e-01
-8.23033452e-02 -1.13822687e+00 1.22071683e-01 2.74620682e-01
-8.99594605e-01 -1.56761599e+00 1.72101408e-01 -7.73964345e-01
7.39867389e-01 -2.18903318e-01 1.49183619e+00 4.07368839e-01
-3.23773861e-01 5.15629709e-01 -5.07690787e-01 2.59537250e-02
-5.30892074e-01 1.99049190e-01 2.70499498e-01 -2.32838601e-01
3.48498642e-01 -9.86428201e-01 -1.63455456e-01 2.36641571e-01
-8.56992662e-01 3.42577207e-03 6.91547573e-01 9.17221844e-01
3.51730466e-01 3.58354449e-01 4.58472431e-01 -1.40667403e+00
5.98624408e-01 -7.34652936e-01 -2.45443240e-01 4.05622870e-01
-9.76890743e-01 4.18629736e-01 4.92466062e-01 -3.54710668e-01
-4.49556597e-02 -1.52613550e-01 1.96721658e-01 -1.32973880e-01
1.72223449e-01 1.20395339e+00 -2.28551939e-01 -3.79098207e-01
5.89998901e-01 8.05853233e-02 -7.27193058e-02 -3.50330979e-01
4.84357029e-01 1.23133130e-01 3.62696707e-01 -1.06023657e+00
9.64788675e-01 2.04443917e-01 4.78216588e-01 -7.44856477e-01
-4.41199630e-01 -3.16240847e-01 -7.47241378e-01 -1.64805174e-01
2.34515563e-01 -5.29914677e-01 -7.86363006e-01 -1.46989405e-01
-9.95483160e-01 -2.12766498e-01 -2.80686945e-01 2.78345078e-01
-3.75412047e-01 4.48341787e-01 -7.09240735e-01 -4.63322669e-01
5.25098778e-02 -5.44261456e-01 4.68650013e-01 -1.59112185e-01
-3.89602274e-01 -1.29296100e+00 2.61280507e-01 6.05662726e-03
1.67151213e-01 6.35883331e-01 1.44635284e+00 -7.04048216e-01
-5.15387237e-01 -1.77201219e-02 -2.01943263e-01 1.12386532e-01
1.43134326e-01 3.26596498e-01 -5.15917003e-01 -1.41533509e-01
-8.88271391e-01 -1.58682212e-01 9.33645129e-01 -4.03702073e-02
7.06169307e-01 -4.37838018e-01 -6.16477907e-01 3.94400805e-01
1.60438609e+00 -2.58685678e-01 6.86329305e-01 3.40579152e-01
8.57428968e-01 7.07272232e-01 1.39182573e-02 1.60871744e-01
5.24886787e-01 6.49532318e-01 4.70956445e-01 2.28600979e-01
2.77962927e-02 -5.79691768e-01 3.80741030e-01 1.14202571e+00
-3.03428233e-01 -4.31505032e-02 -1.12814200e+00 5.62521756e-01
-2.12540030e+00 -9.81491804e-01 -4.72051144e-01 1.99524629e+00
9.41367209e-01 4.69138056e-01 3.25845450e-01 5.56186199e-01
6.11286759e-01 8.75815377e-02 -1.69892907e-01 -4.65987414e-01
-3.93891424e-01 3.84870738e-01 5.04113734e-01 6.59708619e-01
-8.42154443e-01 6.59079194e-01 6.43414640e+00 5.21095634e-01
-5.24491906e-01 -2.78419077e-01 1.85777992e-01 4.29653555e-01
-4.13206190e-01 3.31562698e-01 -5.49765766e-01 3.57010812e-01
1.06841457e+00 -1.75696298e-01 5.54049313e-01 7.05107570e-01
-3.15538049e-01 -3.49007435e-02 -1.48314774e+00 6.99666202e-01
-3.49716209e-02 -1.61964369e+00 5.68642579e-02 6.00559078e-02
7.12697208e-01 -8.92881602e-02 -2.72733688e-01 3.37886363e-01
6.28829837e-01 -1.23886037e+00 3.96330714e-01 6.24965966e-01
5.29642701e-01 -5.93159795e-01 7.58705497e-01 1.00962080e-01
-1.50682509e+00 5.29518053e-02 -6.93315864e-02 -2.87598193e-01
-1.26542598e-01 7.70550311e-01 -9.43673313e-01 9.87385035e-01
5.40214837e-01 9.74707782e-01 -7.33220994e-01 9.27478611e-01
-4.27544057e-01 9.49147582e-01 -4.49622542e-01 -3.72145288e-02
-9.67668369e-02 -1.43469810e-01 6.58967674e-01 1.17314279e+00
-1.87790677e-01 -1.08335041e-01 2.88917899e-01 7.77032495e-01
-2.17488393e-01 -1.42589748e-01 -8.90750706e-01 -3.10720354e-01
6.52735114e-01 1.03441799e+00 -8.52479279e-01 -2.00771883e-01
-5.71501970e-01 4.86770809e-01 5.66140473e-01 3.60835135e-01
-4.02107835e-01 -2.79402047e-01 4.84997153e-01 4.64743584e-01
2.99384713e-01 -3.26701939e-01 -5.27613722e-02 -1.03703249e+00
1.03278354e-01 -9.06253338e-01 5.65817833e-01 -3.54440838e-01
-1.51823723e+00 1.33221015e-01 1.32110298e-01 -7.20166385e-01
-2.32846901e-01 -7.42280662e-01 -4.86724526e-01 4.72684026e-01
-1.20705783e+00 -1.09445703e+00 -6.67101592e-02 5.15163839e-01
-2.96720117e-01 1.08506225e-01 9.85253036e-01 3.69861305e-01
-4.43607420e-01 5.01504898e-01 5.31503633e-02 5.69294453e-01
3.83669794e-01 -1.49232543e+00 3.70135933e-01 4.08862054e-01
6.46676540e-01 8.49059463e-01 7.58439839e-01 -7.72781372e-01
-1.68021703e+00 -7.98361838e-01 1.01819682e+00 -5.43483317e-01
1.12800896e+00 -5.56123018e-01 -8.90312850e-01 1.01782942e+00
-1.16528571e-01 3.16582978e-01 6.61993802e-01 6.34206414e-01
-7.24277616e-01 -7.32816011e-02 -7.49042869e-01 5.75839102e-01
1.36490548e+00 -6.93712652e-01 -5.28172135e-01 1.63610265e-01
6.15673304e-01 -3.53593454e-02 -1.21563435e+00 7.12997019e-01
6.74738884e-01 -1.00853574e+00 1.06913483e+00 -9.87552583e-01
3.94385010e-01 -3.22731107e-01 -1.87714875e-01 -1.25388849e+00
-2.65486389e-01 -5.12573600e-01 -8.14170122e-01 1.12193334e+00
6.29434228e-01 -7.30772972e-01 9.96127546e-01 1.85150936e-01
2.90082335e-01 -9.52743649e-01 -7.03933895e-01 -9.24692154e-01
-1.01171650e-01 -3.26351762e-01 4.53915000e-01 1.40384054e+00
4.77801442e-01 4.84236151e-01 -2.17816457e-01 1.88027099e-01
6.72823071e-01 1.00455441e-01 7.82821536e-01 -1.68568361e+00
-5.07792771e-01 -4.10330623e-01 -1.02820897e+00 -4.57910419e-01
3.42825890e-01 -1.21972334e+00 -5.30725360e-01 -1.67730021e+00
1.40232995e-01 -6.21335804e-01 -2.47101009e-01 5.92486441e-01
4.60909642e-02 4.41395771e-03 -1.33978575e-01 9.66693684e-02
-5.61244428e-01 2.07015038e-01 6.93213642e-01 -3.89276296e-01
-8.47723335e-02 -2.24231154e-01 -3.94652247e-01 5.45136452e-01
6.72779143e-01 -4.81101632e-01 -4.55661297e-01 -6.59279749e-02
1.04451394e+00 -1.63947180e-01 6.00222886e-01 -6.39481068e-01
5.34313500e-01 2.05947846e-01 7.67547404e-03 -2.13518351e-01
3.94896343e-02 -7.84860849e-01 5.42978168e-01 4.58493322e-01
-1.77652121e-01 1.09273970e-01 1.52146012e-01 7.99662828e-01
-3.13096374e-01 -7.87666589e-02 7.19277635e-02 -1.17259743e-02
-7.80806601e-01 1.59745291e-01 8.93223956e-02 2.56367564e-01
8.70000362e-01 -2.59921163e-01 -5.12655258e-01 -3.86272997e-01
-1.11163330e+00 2.58639157e-01 3.58097851e-01 1.98529363e-01
6.08494341e-01 -1.33300030e+00 -7.07567990e-01 1.09808303e-01
1.88228130e-01 -2.01880947e-01 -3.40308934e-01 9.77232695e-01
-4.85906363e-01 1.85675412e-01 1.61863677e-02 -3.25326651e-01
-1.21996236e+00 4.97138113e-01 2.15552151e-01 -4.22983468e-01
-5.63421845e-01 6.06799304e-01 -5.24353385e-01 -5.14813781e-01
2.98440129e-01 -1.91321805e-01 -8.65155458e-02 1.36975059e-02
7.85051882e-02 5.45946062e-01 5.57030551e-02 -3.66798490e-01
-4.15241688e-01 3.81395131e-01 -8.93989056e-02 2.10093915e-01
1.46732223e+00 3.32706362e-01 -5.35946786e-01 6.31641388e-01
9.73204195e-01 2.16836840e-01 -3.70472640e-01 -5.22673845e-01
6.71976686e-01 -1.82636723e-01 -3.77409548e-01 -6.12592041e-01
-7.78056860e-01 4.76427078e-01 -1.40077874e-01 7.76744902e-01
6.26086235e-01 2.77396500e-01 3.59329641e-01 5.19950449e-01
5.39635956e-01 -8.24197650e-01 -9.58372876e-02 3.53319079e-01
5.48281074e-01 -1.05554283e+00 2.34991446e-01 -8.58824134e-01
-2.95777954e-02 1.19932067e+00 3.61611098e-01 -2.70524710e-01
9.43742931e-01 4.22474563e-01 -6.08118057e-01 -4.22750264e-01
-9.58724678e-01 -1.86171442e-01 3.11937064e-01 6.42365396e-01
2.54987121e-01 2.60677367e-01 -3.28578919e-01 4.60777760e-01
-2.03724548e-01 -1.56229913e-01 3.20033699e-01 9.06499147e-01
-2.08684340e-01 -1.46699238e+00 -3.79070006e-02 8.75781655e-01
-1.37168020e-01 -2.76611447e-01 -9.57559884e-01 1.03110993e+00
2.93493241e-01 8.06978762e-01 -1.81946680e-01 -7.60477960e-01
3.60596180e-01 2.14174464e-01 6.42752230e-01 -7.30897963e-01
-2.77925760e-01 -6.38639510e-01 6.74726665e-01 -5.88273048e-01
-4.75857347e-01 -5.16770780e-01 -1.12412798e+00 -8.22438598e-01
-5.42702556e-01 4.49927300e-01 2.60518014e-01 7.70973086e-01
5.32255948e-01 4.40700680e-01 3.49103302e-01 -2.55042672e-01
-2.67215073e-01 -8.44199777e-01 -8.07249665e-01 3.37927073e-01
1.99299734e-02 -8.68293047e-01 -6.76523864e-01 -2.35092230e-02] | [8.695473670959473, 7.587416172027588] |
576e8823-fa72-46ef-ba50-bcd89a16c463 | sneakyprompt-evaluating-robustness-of-text-to | 2305.12082 | null | https://arxiv.org/abs/2305.12082v2 | https://arxiv.org/pdf/2305.12082v2.pdf | SneakyPrompt: Evaluating Robustness of Text-to-image Generative Models' Safety Filters | Text-to-image generative models such as Stable Diffusion and DALL$\cdot$E 2 have attracted much attention since their publication due to their wide application in the real world. One challenging problem of text-to-image generative models is the generation of Not-Safe-for-Work (NSFW) content, e.g., those related to violence and adult. Therefore, a common practice is to deploy a so-called safety filter, which blocks NSFW content based on either text or image features. Prior works have studied the possible bypass of such safety filters. However, existing works are largely manual and specific to Stable Diffusion's official safety filter. Moreover, the bypass ratio of Stable Diffusion's safety filter is as low as 23.51% based on our evaluation. In this paper, we propose the first automated attack framework, called SneakyPrompt, to evaluate the robustness of real-world safety filters in state-of-the-art text-to-image generative models. Our key insight is to search for alternative tokens in a prompt that generates NSFW images so that the generated prompt (called an adversarial prompt) bypasses existing safety filters. Specifically, SneakyPrompt utilizes reinforcement learning (RL) to guide an agent with positive rewards on semantic similarity and bypass success. Our evaluation shows that SneakyPrompt successfully generated NSFW content using an online model DALL$\cdot$E 2 with its default, closed-box safety filter enabled. At the same time, we also deploy several open-source state-of-the-art safety filters on a Stable Diffusion model and show that SneakyPrompt not only successfully generates NSFW content, but also outperforms existing adversarial attacks in terms of the number of queries and image qualities. | ['Yinzhi Cao', 'Neil Gong', 'Haolin Yuan', 'Bo Hui', 'Yuchen Yang'] | 2023-05-20 | null | null | null | null | ['semantic-textual-similarity', 'semantic-similarity'] | ['natural-language-processing', 'natural-language-processing'] | [ 1.68405786e-01 8.08651745e-02 -6.23065233e-02 -3.15387212e-02
-8.50368977e-01 -9.59044099e-01 9.37330723e-01 -1.34011552e-01
-3.93420994e-01 3.80417526e-01 -6.54559955e-02 -4.92975652e-01
-4.75759655e-02 -1.12602496e+00 -8.24322999e-01 -4.19498384e-01
7.92673901e-02 4.11331713e-01 5.18110037e-01 -3.85736674e-01
1.91782489e-02 2.97150671e-01 -1.21416652e+00 1.64591148e-01
7.64416277e-01 7.06232965e-01 3.37354466e-03 8.03799748e-01
1.90930247e-01 7.72009611e-01 -1.08755219e+00 -1.13821840e+00
4.14036870e-01 -5.01372933e-01 -6.43555999e-01 -2.95017332e-01
3.89812738e-01 -7.90241539e-01 -5.69714129e-01 1.16150808e+00
7.72520483e-01 -2.16162056e-01 5.47390163e-01 -1.89027214e+00
-8.42514932e-01 8.27672720e-01 -3.19784313e-01 4.74933609e-02
6.18130028e-01 7.42067516e-01 7.13387728e-01 -4.61232245e-01
8.04645956e-01 1.40139925e+00 4.10500795e-01 8.01399112e-01
-1.20902550e+00 -1.22864020e+00 -5.16802669e-02 1.48166969e-01
-1.41771293e+00 -1.26035869e-01 6.33561194e-01 -3.14220846e-01
9.10108030e-01 3.63892555e-01 4.20870125e-01 1.70725870e+00
3.80603194e-01 6.52198672e-01 1.16266966e+00 -1.60553381e-01
3.57703865e-01 5.35237417e-02 -3.30307722e-01 6.89080834e-01
1.15886264e-01 4.15838361e-01 -4.66919184e-01 -4.74922627e-01
6.54539764e-01 -1.45447418e-01 4.42774221e-02 7.99375623e-02
-6.60978734e-01 1.22751498e+00 2.11175963e-01 4.78586294e-02
-1.53614163e-01 2.27243304e-01 2.50828922e-01 1.43705383e-01
2.94574231e-01 3.61945242e-01 2.93073744e-01 -2.66597509e-01
-7.72252500e-01 5.72514415e-01 6.96258485e-01 8.73707175e-01
5.21256089e-01 1.67141885e-01 -3.41002077e-01 5.03054738e-01
1.44286528e-01 9.98704255e-01 8.63171890e-02 -1.07607734e+00
4.75588202e-01 3.59100342e-01 -7.81890191e-03 -1.17469597e+00
1.64432339e-02 -2.21860901e-01 -7.55958378e-01 2.57658809e-01
1.38696775e-01 -3.97012442e-01 -7.90830612e-01 1.95289791e+00
4.31661457e-01 2.59460956e-01 4.15669270e-02 6.61484003e-01
7.27749169e-01 6.86130941e-01 2.37159312e-01 6.89310282e-02
1.25157022e+00 -5.57954967e-01 -4.51518655e-01 -2.29776457e-01
3.78291219e-01 -8.02387118e-01 1.19194651e+00 3.47172111e-01
-1.01642275e+00 -3.45287800e-01 -8.60683560e-01 5.60455859e-01
-3.14897954e-01 -2.37424195e-01 3.59559536e-01 1.13916230e+00
-1.05188167e+00 3.63871336e-01 -5.73878109e-01 -3.14851463e-01
3.21413666e-01 2.78326005e-01 -1.73184887e-01 -3.23793702e-02
-1.52018499e+00 7.06497788e-01 2.67979115e-01 -5.29197276e-01
-1.48089969e+00 -5.35978317e-01 -7.90422618e-01 -2.63726544e-02
7.94790030e-01 -6.38081133e-01 1.19895005e+00 -8.01797152e-01
-1.39368999e+00 6.06678426e-01 3.70033890e-01 -6.93282008e-01
7.55149662e-01 -2.06117138e-01 -4.97797936e-01 6.48001671e-01
1.93950668e-01 7.87836969e-01 1.37408876e+00 -1.28854132e+00
-3.77230048e-01 -1.27517162e-02 4.89810228e-01 -7.24789128e-02
-6.72323823e-01 3.32241267e-01 -4.58238959e-01 -9.80023980e-01
-7.68940568e-01 -1.05751264e+00 -6.39603063e-02 -2.36312404e-01
-7.15881586e-01 -3.36410969e-01 9.56622839e-01 -4.25352126e-01
1.33315122e+00 -2.11279774e+00 -3.49093705e-01 3.03273290e-01
1.50533870e-01 4.65731680e-01 -5.39440691e-01 7.20979631e-01
1.13492437e-01 5.20917952e-01 4.58788686e-02 -2.30990753e-01
8.72733295e-02 1.93978384e-01 -8.05533171e-01 2.28853077e-01
2.07874805e-01 8.92024815e-01 -9.13590729e-01 -4.32158351e-01
1.57009006e-01 3.99505824e-01 -6.68570280e-01 3.61199647e-01
-2.93161660e-01 1.20319575e-01 -4.21226114e-01 5.03591597e-01
6.29111409e-01 -6.55953726e-03 -4.52149957e-02 1.05380602e-01
2.45332628e-01 -1.73369780e-01 -9.11975622e-01 1.26442361e+00
-2.42423430e-01 1.31100178e-01 -1.11816742e-01 -5.81645191e-01
8.44456553e-01 2.15150967e-01 2.77308822e-01 -8.49518895e-01
1.96902201e-01 5.43009266e-02 -1.62322164e-01 -3.52313489e-01
5.68784356e-01 1.34988084e-01 -3.41977298e-01 6.70086861e-01
1.77972298e-02 -3.81311715e-01 2.26715460e-01 7.93508172e-01
1.56583059e+00 -2.94507910e-02 -1.52242228e-01 8.21909010e-02
2.93132067e-01 -2.03381434e-01 2.98489511e-01 1.32798159e+00
-1.63708344e-01 5.48539639e-01 6.29712760e-01 -1.02653481e-01
-1.00199044e+00 -1.36306584e+00 4.24268216e-01 8.62780988e-01
2.88595051e-01 -8.08260977e-01 -1.26885498e+00 -1.13537896e+00
-1.65354028e-01 8.50763023e-01 -4.15690303e-01 -5.53489089e-01
-3.89825791e-01 -3.53137314e-01 1.29166520e+00 3.17732900e-01
6.69118345e-01 -1.32039654e+00 -7.30927706e-01 1.57185912e-01
-2.19467640e-01 -1.24016178e+00 -6.81904137e-01 -4.66512501e-01
-2.29132086e-01 -1.16794896e+00 -5.80972135e-01 -1.80477917e-01
6.11282766e-01 1.29713982e-01 8.42713714e-01 1.92443728e-01
-3.12976182e-01 7.60061860e-01 -6.29543185e-01 -3.29302877e-01
-9.20512199e-01 -2.14878619e-02 -9.67320651e-02 -2.16926560e-02
5.69885969e-02 -2.33852923e-01 -6.90386772e-01 6.68361425e-01
-1.40470743e+00 -2.40196332e-01 3.36637139e-01 7.15909839e-01
2.59696960e-01 3.05399895e-01 5.80749214e-01 -6.77121580e-01
9.89161730e-01 -4.51483816e-01 -7.36340821e-01 3.04621160e-01
-6.29360199e-01 -6.45039901e-02 9.05923486e-01 -9.04755473e-01
-8.45058739e-01 -2.80216724e-01 -4.03194129e-01 -8.91037405e-01
-9.39874053e-02 1.01509519e-01 -6.37189299e-02 6.20631948e-02
9.04040754e-01 3.47826779e-01 -1.34993106e-01 6.36774674e-02
4.50804323e-01 5.20599544e-01 6.93299770e-01 -7.80052483e-01
1.26509106e+00 4.77098554e-01 -2.52722234e-01 -4.35942560e-01
-5.10725617e-01 4.51159850e-02 4.08189863e-01 -2.92509139e-01
7.57301390e-01 -6.63235247e-01 -1.12683332e+00 6.85151160e-01
-1.11486864e+00 -4.44796950e-01 -2.13517115e-01 1.55592099e-01
-5.46763122e-01 5.22112668e-01 -6.40486896e-01 -9.74541068e-01
-6.21533751e-01 -1.31615245e+00 1.10311818e+00 1.56495169e-01
-4.32211488e-01 -5.28707266e-01 -8.98322761e-02 4.41709250e-01
4.53831583e-01 9.77713391e-02 8.21720064e-01 -8.29789639e-01
-5.80901325e-01 -2.38505006e-01 -3.71143594e-02 3.94086242e-01
-2.13077396e-01 1.44119099e-01 -6.89897478e-01 -4.77385938e-01
-4.30601165e-02 -5.08403838e-01 4.59774077e-01 3.43680009e-02
1.07916760e+00 -7.29408205e-01 -6.46363795e-02 4.58715051e-01
1.12594175e+00 4.16566432e-01 8.50216329e-01 3.63718957e-01
2.67004430e-01 4.81663644e-01 6.24000430e-01 6.17616475e-01
1.85383677e-01 6.98987961e-01 7.08098054e-01 5.25407754e-02
-9.91643406e-03 -7.22108126e-01 6.95415974e-01 4.60613556e-02
1.61941037e-01 -5.80333114e-01 -7.24164784e-01 3.55936944e-01
-1.59378397e+00 -1.25121391e+00 3.49993676e-01 2.13308024e+00
8.43969703e-01 5.31458795e-01 2.07065910e-01 -7.05639869e-02
7.13320434e-01 2.23386794e-01 -3.62177461e-01 -5.32774031e-01
-4.90660854e-02 4.49534982e-01 4.20952588e-01 3.68243933e-01
-9.95520234e-01 1.17411864e+00 5.62148523e+00 1.59138060e+00
-1.01093435e+00 2.32630417e-01 6.30992770e-01 -1.68910704e-03
-5.09949446e-01 1.16482243e-01 -9.73502994e-01 7.58090138e-01
7.35933006e-01 -2.70672351e-01 6.29672825e-01 9.56768692e-01
1.64395958e-01 -1.03537969e-01 -7.85629511e-01 8.17391753e-01
2.91828394e-01 -1.15568960e+00 1.46344930e-01 3.88935730e-02
5.43621957e-01 -2.99705565e-01 4.23440069e-01 3.34594429e-01
7.95810223e-01 -8.75006080e-01 1.02209127e+00 -1.75723771e-03
9.99104977e-01 -9.27260339e-01 4.20246094e-01 5.15610158e-01
-9.61698413e-01 -5.06287962e-02 -1.45436585e-01 4.64548409e-01
1.81630492e-01 2.91017830e-01 -9.97120321e-01 4.55400109e-01
6.97968602e-01 1.37510419e-01 -5.95799387e-01 5.46139538e-01
-7.23118007e-01 8.12065423e-01 -4.52367306e-01 -2.34356504e-02
3.13742220e-01 2.92337894e-01 6.18469238e-01 1.09242404e+00
5.82172930e-01 1.00975513e-01 3.74350548e-01 9.97482538e-01
-2.20958546e-01 -1.11285016e-01 -8.83277118e-01 -8.75757784e-02
7.67684698e-01 1.21595049e+00 -5.94304740e-01 -3.75258893e-01
-4.93488424e-02 9.72290635e-01 -4.21940982e-02 2.96680689e-01
-1.33022642e+00 -3.54463756e-01 5.09097815e-01 3.80804926e-01
2.57485598e-01 2.64913235e-02 1.73077911e-01 -8.79111052e-01
-2.01805860e-01 -1.29964721e+00 5.66091359e-01 -8.12688768e-01
-1.42919457e+00 8.35977852e-01 3.73330742e-01 -1.00760555e+00
-4.66868669e-01 -3.23014334e-02 -8.37432861e-01 6.20353997e-01
-1.12748146e+00 -1.31870723e+00 -1.09571762e-01 1.10835922e+00
6.11595213e-01 -2.68269628e-01 6.58086836e-01 2.18455214e-02
-5.37350118e-01 1.05178344e+00 -3.60925674e-01 9.49027240e-02
6.82720363e-01 -7.82943666e-01 6.06897891e-01 1.19899809e+00
1.33107677e-01 6.41032636e-01 7.93487370e-01 -1.13380527e+00
-1.21713543e+00 -1.05885768e+00 4.65707153e-01 -2.80113071e-01
6.91914082e-01 -4.62503314e-01 -6.35703385e-01 3.59393477e-01
3.98876667e-01 -2.11691394e-01 1.81052282e-01 -6.13984764e-01
-6.51453674e-01 -9.79539827e-02 -1.36926758e+00 1.01000834e+00
9.37383294e-01 -5.61069191e-01 -2.69135177e-01 3.07659447e-01
8.49937081e-01 -3.00728589e-01 -5.66898525e-01 3.80919486e-01
3.02034676e-01 -1.14075291e+00 1.13507998e+00 -2.89185137e-01
5.64942598e-01 -5.59247695e-02 5.40187024e-02 -1.09729910e+00
4.43179347e-02 -1.13416183e+00 -9.04130191e-02 1.42547596e+00
7.96428099e-02 -7.78679013e-01 6.83431566e-01 6.84832752e-01
1.47716120e-01 -5.98737776e-01 -8.56282830e-01 -1.13343585e+00
-2.36060079e-02 -6.09890580e-01 6.43408835e-01 6.61546290e-01
-3.45876783e-01 -3.76488715e-02 -6.66122377e-01 1.29905790e-01
6.83735847e-01 -2.95744151e-01 1.03008044e+00 -5.33508062e-01
-5.46819329e-01 -2.81976610e-01 -1.99397087e-01 -7.06900001e-01
2.94790894e-01 -5.28907180e-01 -1.16214782e-01 -1.10243118e+00
2.50366718e-01 -3.24865162e-01 4.15117703e-02 7.98093855e-01
-1.83615685e-01 3.52869660e-01 6.12946868e-01 8.28547254e-02
-4.40569699e-01 4.35148925e-01 9.53099012e-01 -3.71526092e-01
1.57146249e-02 -7.08410218e-02 -5.95046759e-01 7.10848629e-01
8.71670425e-01 -6.67348564e-01 -6.31476462e-01 -1.91694036e-01
2.93516964e-01 -2.45550442e-02 7.39314616e-01 -7.77749002e-01
1.65813670e-01 -3.65092844e-01 -6.18607774e-02 -4.41247523e-01
3.16794634e-01 -6.03155851e-01 3.44899774e-01 6.62431479e-01
-2.35022828e-01 2.50734717e-01 2.18504909e-02 4.01943356e-01
7.76101276e-02 -4.88875479e-01 5.46601176e-01 -3.08500640e-02
-4.64778125e-01 2.74801105e-01 -5.02292335e-01 2.61188745e-01
1.29702568e+00 -1.05897769e-01 -9.67051029e-01 -8.83724451e-01
-3.36234450e-01 3.49110477e-02 5.00144184e-01 6.04274333e-01
9.58280981e-01 -1.05721080e+00 -7.09811091e-01 2.34996319e-01
1.85190216e-02 -4.77024525e-01 3.66335481e-01 4.09484684e-01
-3.47421259e-01 -3.40915658e-02 -5.18215224e-02 -3.37742865e-01
-1.46457124e+00 9.00302052e-01 -3.04113496e-02 -5.44908345e-01
-4.66119736e-01 6.72815800e-01 3.81646574e-01 -1.31676970e-02
2.23992378e-01 3.09861302e-01 2.18866780e-01 -2.79948503e-01
4.62687850e-01 3.73825401e-01 -2.88250864e-01 -4.70724642e-01
-3.78015667e-01 3.79927546e-01 -7.09036961e-02 -4.48939979e-01
9.98038054e-01 2.07220539e-01 1.82967186e-01 -5.36787927e-01
9.01137710e-01 2.04691991e-01 -1.16593719e+00 3.91964428e-02
-5.29687405e-01 -7.82468855e-01 -5.14368594e-01 -7.96884060e-01
-1.09536695e+00 6.92431569e-01 6.36199355e-01 4.70902860e-01
1.19836092e+00 9.23679546e-02 1.02157056e+00 2.16378927e-01
5.32822430e-01 -9.62444842e-01 6.85182631e-01 2.43097648e-01
9.52012718e-01 -7.87008166e-01 -1.80813506e-01 -4.72910702e-01
-9.45676446e-01 6.14106953e-01 8.30810070e-01 -1.17132142e-01
1.69342190e-01 4.76849675e-01 -4.22930084e-02 -4.81754690e-02
-6.25931799e-01 9.04196352e-02 -1.47381350e-01 8.39295864e-01
-4.03324932e-01 -7.25844577e-02 -2.95039594e-01 5.89100242e-01
-2.84621119e-01 -2.43473247e-01 5.56469798e-01 8.62029970e-01
-1.10136792e-01 -1.44579875e+00 -5.94127595e-01 2.19123736e-01
-7.30117142e-01 -1.63907990e-01 -4.78719413e-01 6.06559813e-01
2.06483722e-01 1.27088296e+00 -3.84629130e-01 -6.38863921e-01
2.75863588e-01 -2.44068250e-01 2.88503140e-01 -3.62826079e-01
-1.09269011e+00 1.95426837e-01 8.88750888e-03 -6.20282352e-01
-7.80559406e-02 -2.52502382e-01 -1.16961634e+00 -5.19673944e-01
-3.11913371e-01 -2.36314964e-02 5.27772605e-01 6.35046959e-01
3.70927900e-01 1.79823846e-01 8.98373127e-01 -3.70755881e-01
-8.15935671e-01 -5.51578343e-01 -2.38090917e-01 7.52360046e-01
-2.77773470e-01 -5.38446903e-01 -1.03432037e-01 -8.42291489e-02] | [5.701298236846924, 7.821197032928467] |
3abc30a1-ab3f-435f-9f3f-2fe0399e3d77 | rpn-a-word-vector-level-data-augmentation | 2212.05961 | null | https://arxiv.org/abs/2212.05961v3 | https://arxiv.org/pdf/2212.05961v3.pdf | RPN: A Word Vector Level Data Augmentation Algorithm in Deep Learning for Language Understanding | Data augmentation is a widely used technique in machine learning to improve model performance. However, existing data augmentation techniques in natural language understanding (NLU) may not fully capture the complexity of natural language variations, and they can be challenging to apply to large datasets. This paper proposes the Random Position Noise (RPN) algorithm, a novel data augmentation technique that operates at the word vector level. RPN modifies the word embeddings of the original text by introducing noise based on the existing values of selected word vectors, allowing for more fine-grained modifications and better capturing natural language variations. Unlike traditional data augmentation methods, RPN does not require gradients in the computational graph during virtual sample updates, making it simpler to apply to large datasets. Experimental results demonstrate that RPN consistently outperforms existing data augmentation techniques across various NLU tasks, including sentiment analysis, natural language inference, and paraphrase detection. Moreover, RPN performs well in low-resource settings and is applicable to any model featuring a word embeddings layer. The proposed RPN algorithm is a promising approach for enhancing NLU performance and addressing the challenges associated with traditional data augmentation techniques in large-scale NLU tasks. Our experimental results demonstrated that the RPN algorithm achieved state-of-the-art performance in all seven NLU tasks, thereby highlighting its effectiveness and potential for real-world NLU applications. | ['Huiwen Xue', 'Xuecong Hou', 'Yue Wang', 'Xiaolong Zhang', 'Yongming Liu', 'Zhuanzhe Zhao', 'Zhengqing Yuan'] | 2022-12-12 | null | null | null | null | ['text-augmentation'] | ['natural-language-processing'] | [ 4.17344153e-01 -2.33311534e-01 -6.57599747e-01 -1.07285753e-01
-3.85568082e-01 -4.53417867e-01 7.13551641e-01 5.75990975e-01
-6.23985708e-01 5.08696854e-01 4.97049809e-01 -4.59337234e-01
2.69101322e-01 -9.75148201e-01 -7.40507662e-01 -2.97429711e-01
1.82962060e-01 4.80270833e-01 -2.84643948e-01 -4.07576889e-01
8.18904862e-02 3.03839892e-01 -1.37693679e+00 -4.02729772e-02
9.70993578e-01 7.64899075e-01 2.70374678e-03 4.95814800e-01
-8.50943685e-01 5.31298161e-01 -5.28643847e-01 -2.78671920e-01
3.09287965e-01 -2.30872601e-01 -5.85866332e-01 -1.59812063e-01
4.61736858e-01 -1.95621714e-01 -5.56127310e-01 8.47164333e-01
5.72150528e-01 5.62725902e-01 4.37291056e-01 -1.13143492e+00
-1.18563437e+00 7.38928616e-01 -6.78393066e-01 4.41701055e-01
4.58190203e-01 -6.69438988e-02 1.37941563e+00 -1.17817533e+00
4.68590558e-01 1.44371450e+00 6.19628966e-01 7.84741461e-01
-1.35468936e+00 -8.13754797e-01 4.69551533e-01 -1.10441074e-02
-8.90894532e-01 -5.36224693e-02 8.99994910e-01 -2.12445959e-01
1.17290068e+00 6.92145452e-02 3.81025136e-01 1.35889161e+00
-2.28442833e-01 1.30716372e+00 8.95278335e-01 -6.60677195e-01
4.67567071e-02 2.78080311e-02 8.65469515e-01 3.91913295e-01
3.58069301e-01 -2.42523775e-01 -5.51884294e-01 -3.31688881e-01
5.93508780e-01 3.41438085e-01 -3.24522555e-01 -4.64540064e-01
-1.37611842e+00 1.06123948e+00 5.63291788e-01 3.04367840e-01
-2.05194503e-01 9.73275006e-02 7.56341338e-01 1.98867261e-01
7.86596179e-01 8.32663417e-01 -8.33635867e-01 -2.74148107e-01
-2.76003569e-01 1.48547173e-01 2.87060887e-01 8.22392166e-01
7.20612764e-01 2.01239049e-01 -3.41009885e-01 1.21799147e+00
-4.70086485e-02 3.91211092e-01 1.18422818e+00 -6.82724342e-02
7.80378103e-01 1.09601486e+00 -1.44748196e-01 -8.67523730e-01
-4.93170917e-01 -4.48735267e-01 -9.84782219e-01 -2.44113505e-01
1.41054690e-01 -1.80128053e-01 -1.11718976e+00 1.79106617e+00
4.15994167e-01 3.74089897e-01 2.36018434e-01 5.23939848e-01
8.99011672e-01 8.45215499e-01 3.11456136e-02 3.61733325e-02
1.31507671e+00 -1.01229036e+00 -1.10851550e+00 -7.39355385e-01
1.03470373e+00 -6.94039226e-01 1.89978874e+00 9.54054147e-02
-4.99383301e-01 -6.50555313e-01 -1.14451659e+00 -3.49033564e-01
-6.34116054e-01 3.26506272e-02 9.19020176e-01 6.16191626e-01
-5.55628300e-01 3.85815412e-01 -5.07206798e-01 -2.14679986e-01
4.53637123e-01 1.61887944e-01 -4.16386634e-01 -4.72370178e-01
-1.63525200e+00 7.77102232e-01 6.35245204e-01 -2.23036408e-02
-1.59856066e-01 -1.09719491e+00 -1.42816389e+00 1.20621830e-01
4.63696152e-01 -4.16066468e-01 1.10524035e+00 -2.76307046e-01
-1.02486253e+00 4.35508490e-01 -3.76116604e-01 -6.15955770e-01
2.96201110e-01 -6.62165761e-01 -3.20587486e-01 -4.93383825e-01
-1.47913218e-01 5.54774344e-01 6.79070473e-01 -9.53878045e-01
-2.64983505e-01 -3.85001034e-01 -7.69018456e-02 2.01296180e-01
-1.15876710e+00 -4.80996072e-01 -4.70707417e-01 -1.10606027e+00
-7.41624534e-02 -6.16506994e-01 -3.04255456e-01 -2.85914898e-01
-2.44133219e-01 -5.13757467e-01 1.15746891e+00 -4.61476147e-01
1.67662776e+00 -1.89316535e+00 -1.62605830e-02 1.46611452e-01
1.44574165e-01 8.40303957e-01 -5.18846035e-01 3.66872698e-01
-7.22788945e-02 1.42265797e-01 -3.36755872e-01 -5.29766560e-01
-5.24177812e-02 5.49063563e-01 -2.74440289e-01 9.11387615e-03
2.46115834e-01 1.29054952e+00 -1.22387254e+00 3.96779776e-02
2.91754156e-01 3.68756622e-01 -5.95333219e-01 1.79653510e-01
-3.73922259e-01 6.16317056e-02 -3.01669598e-01 5.18366218e-01
6.15059614e-01 -7.93506056e-02 -2.00299527e-02 -9.70050916e-02
3.51560473e-01 3.09467912e-01 -1.16757357e+00 1.59552169e+00
-8.68464410e-01 6.85449958e-01 -4.30217862e-01 -8.55002046e-01
1.21744335e+00 1.69398077e-02 2.16083556e-01 -7.75216997e-01
2.53459990e-01 -7.90726207e-03 4.55619805e-02 -2.72464663e-01
6.25495970e-01 8.23669210e-02 -2.14405343e-01 6.36892259e-01
4.05120710e-03 3.22945565e-02 5.10901988e-01 4.23635393e-01
1.04099798e+00 -3.66449356e-01 6.20542645e-01 -1.22476548e-01
5.33830762e-01 -2.68857628e-01 4.67409074e-01 8.68858278e-01
-1.75993875e-01 2.71583974e-01 3.58939052e-01 -4.71019894e-01
-1.11949074e+00 -8.78614664e-01 -1.81861401e-01 1.29244232e+00
-2.26009652e-01 -4.61619318e-01 -5.02746820e-01 -9.04009104e-01
2.11800784e-01 8.93332481e-01 -9.36879873e-01 -4.25268799e-01
-3.76562864e-01 -1.13508213e+00 2.96648800e-01 7.67156541e-01
4.89814818e-01 -1.16047680e+00 2.74824291e-01 3.11637759e-01
-1.34628341e-01 -1.36333275e+00 -8.14563155e-01 1.18456911e-02
-1.05593896e+00 -1.13600767e+00 -4.51730371e-01 -9.01186645e-01
8.99700165e-01 5.58902681e-01 9.38119948e-01 -1.83645412e-02
-2.41530314e-01 3.01436156e-01 -7.77723074e-01 -6.32840574e-01
-5.76825023e-01 2.83438236e-01 5.08623660e-01 5.53496368e-02
9.04515862e-01 -3.44206452e-01 -3.01981747e-01 -9.73988976e-03
-1.38517058e+00 -1.73671648e-01 5.48493445e-01 1.25226939e+00
6.43086553e-01 -3.41587543e-01 8.76546383e-01 -1.33616662e+00
1.23981512e+00 -3.02132457e-01 -2.82170296e-01 2.26925641e-01
-8.30338538e-01 1.38372406e-01 8.00801992e-01 -9.49940383e-01
-7.82806396e-01 -1.79166272e-01 -2.84114718e-01 -3.53561968e-01
1.37777701e-01 6.22355461e-01 -3.03720683e-01 -1.93502642e-02
7.32846797e-01 3.02859783e-01 1.10671684e-01 -6.30639851e-01
7.50535429e-01 6.59631431e-01 3.21038693e-01 -3.44898313e-01
8.92671943e-01 1.59473926e-01 -2.70624518e-01 -1.15371144e+00
-1.10011637e+00 -7.48973072e-01 -7.99004018e-01 3.06336612e-01
4.05853480e-01 -7.71249294e-01 -2.37336129e-01 4.07153100e-01
-9.55922842e-01 -1.50635958e-01 -5.10409713e-01 3.96324009e-01
8.55596364e-03 6.60182655e-01 -4.49785262e-01 -5.72196960e-01
-8.13944101e-01 -8.33918810e-01 5.79877019e-01 1.77773252e-01
-3.26142341e-01 -1.27793288e+00 2.19096363e-01 4.76408839e-01
2.79369295e-01 -6.62421063e-02 1.23057771e+00 -1.13729036e+00
1.23698406e-01 -6.61187291e-01 -2.78387785e-01 7.32220948e-01
4.97074753e-01 -3.44428450e-01 -9.71614063e-01 -3.60543221e-01
-1.30368203e-01 -5.04314065e-01 8.60642135e-01 9.04176831e-02
1.31080890e+00 -4.45425928e-01 -8.71654451e-02 3.78365338e-01
1.11740053e+00 -1.76394358e-02 4.44384336e-01 3.60397696e-01
1.02627409e+00 1.74683467e-01 6.48036182e-01 4.37908322e-01
1.29638478e-01 4.10787761e-01 3.67490113e-01 -3.48107100e-01
-1.05790645e-01 -4.63083416e-01 2.00399399e-01 9.52262461e-01
5.11154950e-01 -2.82459915e-01 -9.58605886e-01 8.49101901e-01
-1.85677588e+00 -5.07852316e-01 -1.49671048e-01 2.05788493e+00
8.15546989e-01 4.10815388e-01 -2.52410650e-01 3.48412395e-01
4.73766476e-01 3.82904023e-01 -7.63580859e-01 -7.54582882e-01
-2.25109547e-01 3.02156329e-01 3.17386985e-01 4.07815933e-01
-1.06583738e+00 1.20229053e+00 5.90076113e+00 8.44740212e-01
-6.28243089e-01 1.98832527e-01 3.89174759e-01 -9.17692408e-02
-5.69487810e-01 -4.53988284e-01 -9.24105823e-01 3.08882296e-01
5.36593139e-01 -2.02032894e-01 2.33238146e-01 9.26291168e-01
2.06927449e-01 1.92282766e-01 -1.13298893e+00 8.63166988e-01
2.96653688e-01 -1.43600500e+00 7.27953911e-01 -1.98824584e-01
1.04399896e+00 2.68359303e-01 1.48534412e-02 6.58272624e-01
2.78806657e-01 -8.48194301e-01 -2.23740906e-01 -1.11629970e-01
5.90036333e-01 -8.79465699e-01 1.00775504e+00 3.70739520e-01
-1.01306260e+00 -6.57881796e-02 -5.20004213e-01 -2.55155683e-01
5.21171317e-02 6.12978637e-01 -9.79557455e-01 7.86611363e-02
3.41223896e-01 6.28562689e-01 -5.61644852e-01 4.92694438e-01
-3.29954565e-01 5.40998578e-01 -2.28761718e-01 -4.91691530e-01
5.86482227e-01 -2.30454832e-01 4.68542904e-01 1.36570799e+00
1.46817113e-03 -1.65012404e-01 2.19999418e-01 3.88516337e-01
-8.01679373e-01 5.88140011e-01 -8.96903515e-01 -4.19799954e-01
5.60989022e-01 1.06799090e+00 -2.53197223e-01 -3.71127814e-01
-7.46759593e-01 9.94997144e-01 6.36047363e-01 2.28675827e-01
-4.75186139e-01 -4.83561486e-01 1.07570648e+00 -1.13725290e-01
5.17481491e-02 -2.77642637e-01 -3.92495155e-01 -1.40395796e+00
1.23969473e-01 -8.90705168e-01 5.23401141e-01 -4.04218137e-01
-1.49152410e+00 5.72649896e-01 -3.13721091e-01 -1.17054987e+00
-7.51170143e-02 -7.87093222e-01 -6.18793786e-01 8.05821300e-01
-1.76468122e+00 -1.15805304e+00 -1.14277221e-01 4.51467305e-01
8.93157601e-01 -2.82090247e-01 1.00464845e+00 2.20878273e-01
-8.90376985e-01 9.03516829e-01 5.17623365e-01 3.18585306e-01
6.41590893e-01 -1.21225488e+00 1.02833974e+00 1.14949811e+00
5.07507980e-01 8.55688870e-01 5.68217158e-01 -6.98556185e-01
-1.36555636e+00 -1.20798922e+00 9.28832352e-01 -3.32118154e-01
1.18174267e+00 -7.09474802e-01 -1.28157341e+00 6.70289040e-01
4.80241841e-03 1.43668726e-01 9.16402161e-01 3.76440197e-01
-5.05471945e-01 5.82739003e-02 -9.94916677e-01 7.98599482e-01
9.28435206e-01 -5.15416384e-01 -7.46730566e-01 5.34158885e-01
9.91908193e-01 -3.63902897e-01 -7.29084849e-01 5.24775267e-01
2.36981243e-01 -1.63442656e-01 1.03195238e+00 -1.23233378e+00
5.07849157e-01 1.04443952e-01 5.20522380e-03 -1.63581681e+00
-2.21196830e-01 -3.50381643e-01 -6.85185671e-01 1.45296860e+00
6.64196253e-01 -7.96614051e-01 8.33003938e-01 5.12114942e-01
2.34559104e-01 -1.09297943e+00 -7.97564745e-01 -7.16328979e-01
5.65519109e-02 -7.29905427e-01 4.17398930e-01 1.26199234e+00
-4.69145253e-02 6.98699713e-01 -5.83889008e-01 -8.03452823e-03
3.49788606e-01 -1.62535310e-01 9.69186068e-01 -1.17983413e+00
1.18894894e-02 -4.24455971e-01 -3.52553040e-01 -1.16083121e+00
3.80538315e-01 -1.00915134e+00 -2.92831361e-01 -1.78640902e+00
9.82460231e-02 -2.80057818e-01 -4.05350298e-01 4.46664035e-01
-8.81249130e-01 3.77064764e-01 1.56229168e-01 1.15511209e-01
-1.09551661e-02 9.83493686e-01 1.25730467e+00 -4.01718348e-01
-4.42223668e-01 1.17414683e-01 -7.44355023e-01 6.96994424e-01
9.58087981e-01 -1.30545825e-01 -6.59592092e-01 -5.48692048e-01
1.58488691e-01 -9.40305173e-01 -1.89729974e-01 -6.19750857e-01
-9.48114097e-02 1.60784453e-01 3.56400609e-01 -6.15014732e-01
1.91376314e-01 -8.40701580e-01 -9.35773969e-01 4.71769691e-01
-3.23201656e-01 2.17303917e-01 5.80515385e-01 7.44152665e-01
-1.99887484e-01 -3.94905031e-01 6.56085849e-01 9.40192938e-02
-9.32095408e-01 5.32252252e-01 -1.85454115e-01 2.28397399e-01
9.50855136e-01 -8.15418959e-02 -2.04605177e-01 -1.82841092e-01
-4.06201214e-01 6.16910517e-01 7.20526651e-02 9.83947515e-01
7.89991140e-01 -1.45960355e+00 -4.73545820e-01 4.29451257e-01
5.10574222e-01 1.45834014e-01 2.75372148e-01 3.19274396e-01
-3.29749793e-01 4.32990313e-01 1.55158937e-01 -1.58577085e-01
-1.28873038e+00 8.23362052e-01 -2.98082922e-02 -6.40756547e-01
-6.07032299e-01 9.76057649e-01 2.18926266e-01 -1.01382422e+00
3.92885238e-01 -4.79402035e-01 -5.05866170e-01 3.97375047e-01
8.84510159e-01 2.32093319e-01 2.19602734e-01 -3.40411991e-01
-7.00105801e-02 3.55833113e-01 -6.21371090e-01 3.87151152e-01
1.24810684e+00 -5.52039072e-02 5.21518216e-02 5.24362564e-01
1.34836781e+00 -8.23468938e-02 -7.84449279e-01 -9.82550859e-01
-7.27403611e-02 -3.88572901e-01 2.02797234e-01 -5.86307406e-01
-8.32940519e-01 9.97626841e-01 3.39718074e-01 -2.01571174e-02
8.70366573e-01 -3.26007575e-01 1.22281146e+00 7.59714007e-01
1.64636411e-02 -1.11275232e+00 2.18943521e-01 8.47845614e-01
8.46937358e-01 -1.56096292e+00 8.81177261e-02 -3.25494528e-01
-7.23749578e-01 9.65718508e-01 9.56021845e-01 9.35789198e-02
5.58230817e-01 -3.66542302e-02 3.16460669e-01 1.62997097e-01
-4.44457442e-01 -1.33936450e-01 4.90648270e-01 5.66835821e-01
4.14691389e-01 -1.34588674e-01 -4.38578635e-01 3.90157253e-01
-7.06716850e-02 -3.74578446e-01 5.55643022e-01 7.95050502e-01
-2.23838419e-01 -1.39389658e+00 -2.74636805e-01 9.35759187e-01
-1.85306534e-01 -4.09943789e-01 -4.92691159e-01 9.36599076e-01
-1.97958738e-01 5.97251892e-01 9.19968858e-02 -3.20682108e-01
5.81700444e-01 4.14197147e-01 9.96310487e-02 -7.49770463e-01
-4.86380965e-01 -3.81512880e-01 -9.39972848e-02 -3.69409978e-01
-1.47481803e-02 -4.95210648e-01 -1.17416358e+00 -3.07638049e-01
-3.58298302e-01 8.42780098e-02 6.36469007e-01 1.06256127e+00
3.72420728e-01 7.60902762e-01 5.79541147e-01 -5.61832309e-01
-4.74724889e-01 -1.34929681e+00 -2.30710745e-01 7.16106594e-01
3.24660599e-01 -5.96703470e-01 -2.81910628e-01 -4.39961404e-01] | [10.663989067077637, 8.309526443481445] |
3402e557-e29d-46ce-82b7-be616f69120c | self-meta-pseudo-labels-meta-pseudo-labels | 2212.13420 | null | https://arxiv.org/abs/2212.13420v1 | https://arxiv.org/pdf/2212.13420v1.pdf | Self Meta Pseudo Labels: Meta Pseudo Labels Without The Teacher | We present Self Meta Pseudo Labels, a novel semi-supervised learning method similar to Meta Pseudo Labels but without the teacher model. We introduce a novel way to use a single model for both generating pseudo labels and classification, allowing us to store only one model in memory instead of two. Our method attains similar performance to the Meta Pseudo Labels method while drastically reducing memory usage. | ['Qingchen Wang', 'Kei-Sing Ng'] | 2022-12-27 | null | null | null | null | ['semi-supervised-image-classification'] | ['computer-vision'] | [ 7.49038577e-01 8.42513323e-01 -4.39237684e-01 -8.33223343e-01
-9.84746218e-01 -6.77557468e-01 1.07285845e+00 4.33835268e-01
-4.83984083e-01 1.12586021e+00 -1.05967157e-01 -2.31058225e-01
3.20669889e-01 -8.12925041e-01 -6.79601192e-01 -5.18816710e-01
4.35680985e-01 9.46778357e-01 2.07314998e-01 2.92797804e-01
3.10014933e-01 1.11840673e-01 -2.05047917e+00 7.20610857e-01
6.90365076e-01 3.99625272e-01 -1.12979189e-01 6.13626659e-01
-6.17206991e-01 1.23309791e+00 -8.54044855e-01 -3.30147743e-01
1.58334300e-01 -6.77938819e-01 -1.31056476e+00 1.72566995e-01
6.17497683e-01 1.61930442e-01 -9.85075533e-02 1.04412162e+00
2.74622768e-01 8.54233801e-02 1.16672719e+00 -1.37991154e+00
-5.32531500e-01 1.34815478e+00 -2.21174687e-01 -3.19428474e-01
5.26435435e-01 -4.85983402e-01 6.53456211e-01 -6.05173826e-01
4.28329080e-01 1.30899429e+00 5.93310833e-01 8.85673702e-01
-1.59829938e+00 -7.84890175e-01 -3.48034292e-01 5.21390736e-02
-1.43139255e+00 -5.11152864e-01 5.20353377e-01 -3.48282754e-01
8.12178135e-01 2.23787904e-01 2.12748230e-01 9.86989558e-01
-2.02448651e-01 6.60206616e-01 1.96084297e+00 -1.15545332e+00
2.92031378e-01 6.06038451e-01 7.17595339e-01 1.09764457e+00
-3.27364132e-02 -7.92332366e-03 -4.50470358e-01 -6.77487493e-01
2.00761825e-01 -1.61644518e-01 3.50113809e-01 -1.37144908e-01
-1.34899580e+00 7.50705540e-01 -7.64611512e-02 1.47685453e-01
3.27087760e-01 5.32089233e-01 3.29055458e-01 3.95760924e-01
7.99525261e-01 3.61022055e-01 -5.70255935e-01 -2.91372299e-01
-8.14890504e-01 -2.05162987e-01 1.06372333e+00 1.33204448e+00
1.25320590e+00 -6.08807988e-02 -9.04048160e-02 9.31181431e-01
1.19095109e-01 5.30103862e-01 8.18031132e-01 -1.37513971e+00
-5.43085895e-02 6.76550567e-01 1.76568851e-01 -2.79582411e-01
-4.97551262e-01 -2.08492160e-01 -5.24961650e-01 1.09995343e-01
1.45428106e-01 6.00291044e-02 -1.18671465e+00 1.76014793e+00
2.63055056e-01 2.88794637e-01 1.11319527e-01 -1.31950736e-01
9.82141972e-01 6.60024762e-01 1.47233531e-01 -4.26477790e-01
1.04518330e+00 -1.61366189e+00 -4.88510191e-01 -9.00543928e-02
1.43746734e+00 -5.89548230e-01 9.41286087e-01 3.40252012e-01
-1.06730413e+00 -6.80897355e-01 -1.10581446e+00 -8.85164216e-02
-8.48789811e-01 1.14656776e-01 7.94212520e-01 1.02605987e+00
-1.38379765e+00 9.09886539e-01 -6.11764550e-01 -1.03491381e-01
2.75715776e-02 5.48505127e-01 -4.51661974e-01 2.93706805e-01
-9.58183706e-01 9.54939187e-01 9.51904714e-01 -6.99415803e-01
-7.01873183e-01 -2.77150840e-01 -1.05577028e+00 -2.37415507e-01
2.86580380e-02 -3.80959332e-01 1.58414304e+00 -9.56816614e-01
-1.59933376e+00 1.39650702e+00 -5.32618880e-01 -4.46887881e-01
3.64497989e-01 1.95743188e-01 -4.93762165e-01 -2.22852286e-02
2.14468956e-01 1.23009956e+00 1.04046023e+00 -1.58343589e+00
-7.24595129e-01 7.27456957e-02 -1.73736177e-02 1.29739508e-01
-4.94302660e-01 -1.92674920e-01 1.37152776e-01 -5.28423488e-01
1.18978277e-01 -1.17506039e+00 -6.93863407e-02 -4.64336395e-01
-3.88292760e-01 -5.15881598e-01 6.64614081e-01 3.40059966e-01
9.59249794e-01 -1.85376096e+00 -2.47656465e-01 3.23085040e-02
4.81454849e-01 4.64440703e-01 -2.14810222e-01 4.30064499e-01
-4.31591094e-01 3.29787821e-01 -4.44854528e-01 -7.39615560e-01
-3.79297435e-02 6.16151333e-01 -4.72100705e-01 1.76663131e-01
-3.00387561e-01 8.89593422e-01 -1.45863438e+00 -9.95463014e-01
1.44365087e-01 7.54533708e-02 8.45176280e-02 2.82271683e-01
-2.36231908e-01 1.14421293e-01 -4.85042445e-02 3.26038212e-01
6.57005310e-01 -5.23843348e-01 2.63241500e-01 1.68561533e-01
1.47681996e-01 5.79421222e-01 -1.06179333e+00 1.53684318e+00
-7.96342015e-01 4.34588075e-01 -6.06781781e-01 -7.91760385e-01
9.99539554e-01 4.37373102e-01 3.12855333e-01 -1.51715323e-01
9.74932089e-02 2.75245249e-01 -7.07061589e-01 1.18911909e-02
3.86343628e-01 -2.91903555e-01 -1.29849836e-01 1.43873250e+00
4.41018313e-01 -4.07296002e-01 4.70382601e-01 2.70962715e-01
8.61759961e-01 2.81927168e-01 4.05183554e-01 -1.80293888e-01
4.33022559e-01 3.50229561e-01 1.62149251e-01 9.17897761e-01
2.32445434e-01 2.99313098e-01 1.67191610e-01 -5.45034528e-01
-8.28869998e-01 -1.11335611e+00 -2.11649239e-01 1.22044671e+00
2.31525935e-02 -8.51147592e-01 -8.64429474e-01 -1.32011104e+00
-5.68053834e-02 9.92301345e-01 -8.97766292e-01 -2.78563559e-01
-5.20630717e-01 -5.97204208e-01 8.61983061e-01 4.68566686e-01
3.88664007e-01 -1.07060850e+00 -2.92934179e-01 5.14440909e-02
-2.69326717e-02 -8.44180465e-01 -3.09075594e-01 8.49893451e-01
-1.21417844e+00 -9.54936981e-01 -2.41619557e-01 -1.11022544e+00
1.03325319e+00 3.07744801e-01 1.28202522e+00 -1.80866029e-02
1.26296850e-02 1.42288074e-01 -4.39653993e-01 -1.16965145e-01
-1.51277959e+00 3.17340881e-01 1.87528208e-01 -4.23711479e-01
5.04660785e-01 -5.51740348e-01 2.49372125e-01 2.88632303e-01
-9.35633302e-01 6.25010848e-01 3.27028364e-01 1.13543904e+00
4.78924900e-01 1.65255934e-01 3.71434271e-01 -1.98553026e+00
3.54903519e-01 -3.75718623e-01 -3.53713155e-01 3.44068468e-01
-1.21833158e+00 5.69690406e-01 8.38784277e-01 -6.67723179e-01
-8.90027523e-01 5.83449721e-01 7.77845085e-02 -7.17207566e-02
-5.29152155e-01 -6.01592809e-02 2.70451844e-01 -2.67004043e-01
9.25164461e-01 1.54414177e-01 -8.28626156e-02 -6.41073525e-01
8.79182518e-01 1.17642152e+00 4.28050339e-01 -5.72406650e-01
7.61271238e-01 4.24244016e-01 1.26954943e-01 -4.27249342e-01
-1.42178965e+00 -2.76536882e-01 -9.73646164e-01 6.47371188e-02
3.26673269e-01 -6.93638325e-01 -2.49516606e-01 3.57960671e-01
-1.11792374e+00 -6.47526264e-01 -7.19028294e-01 1.77638710e-01
-8.83686841e-01 4.14698660e-01 -7.59337246e-01 -4.33261573e-01
-2.68232107e-01 -6.86958849e-01 1.12735128e+00 -2.52547339e-02
-2.18674779e-01 -1.23009455e+00 2.66990364e-01 1.35095969e-01
1.70356706e-01 1.01465844e-02 9.59886074e-01 -9.85757947e-01
1.17754005e-01 -1.64519683e-01 -3.64847392e-01 2.94957668e-01
4.95764583e-01 -4.04138356e-01 -1.34133613e+00 -8.23749043e-03
-1.38922259e-01 -7.94436574e-01 8.54432344e-01 -3.77481222e-01
1.08672047e+00 -2.52731085e-01 -5.06363094e-01 4.19097900e-01
1.05081677e+00 1.07194327e-01 7.95896426e-02 3.59148495e-02
8.17077637e-01 5.07913172e-01 5.67021430e-01 1.55529097e-01
5.39961755e-01 4.30799425e-01 -1.00003943e-01 -4.98015359e-02
-3.77054304e-01 -6.15760624e-01 3.15903157e-01 1.27134395e+00
6.05477870e-01 -6.67835847e-02 -8.67876172e-01 4.13209289e-01
-1.80517459e+00 -6.94784820e-01 -2.53306538e-01 2.11872196e+00
1.41626585e+00 2.10047200e-01 -1.83510005e-01 4.62858140e-01
8.13768804e-01 3.77694070e-02 -1.88023493e-01 -7.00795233e-01
3.47206965e-02 5.80250323e-01 5.85386753e-01 6.85872674e-01
-1.20664692e+00 1.19743848e+00 8.64809704e+00 9.85010445e-01
-7.69946754e-01 5.43477237e-01 4.45512861e-01 3.49972606e-01
-3.47726524e-01 4.04653609e-01 -1.02008474e+00 2.70431966e-01
1.50414181e+00 -1.28455713e-01 4.11077648e-01 9.71718431e-01
-4.79918331e-01 -2.12635085e-01 -1.55126655e+00 1.09522259e+00
5.17862797e-01 -1.15040886e+00 3.81739467e-01 -2.75898516e-01
9.91319180e-01 -1.43726453e-01 -2.81814963e-01 3.39226633e-01
8.05874169e-01 -7.80643761e-01 8.10782611e-01 3.09920877e-01
1.29313958e+00 -5.69577098e-01 4.67928231e-01 5.70897877e-01
-1.04237819e+00 1.43171057e-01 -3.83503288e-01 -2.08652452e-01
-7.36443400e-02 5.74402750e-01 -1.05930340e+00 4.33686487e-02
9.49325338e-02 5.67617297e-01 -1.06502914e+00 4.24673647e-01
-6.49792910e-01 6.97997808e-01 -2.06513435e-01 -1.66796800e-02
-8.22163001e-02 2.90851593e-01 1.02167986e-01 1.53480220e+00
3.04039214e-02 -1.21668592e-01 4.91768092e-01 6.25020504e-01
-8.34049061e-02 5.34720868e-02 -7.82562077e-01 -6.20683506e-02
6.35713339e-01 1.19157827e+00 -8.52443695e-01 -1.11190188e+00
-3.12581356e-03 1.10991347e+00 4.95870501e-01 -1.66016564e-01
-4.48580593e-01 -5.45902610e-01 -3.12757105e-01 1.90516189e-02
-4.22302753e-01 -2.30647042e-01 -2.29468048e-01 -1.16758955e+00
-5.87906361e-01 -4.11498040e-01 5.36125004e-01 -9.30214822e-01
-9.59815800e-01 8.94781232e-01 5.31556904e-01 -1.21799886e+00
-8.22592616e-01 -3.96544427e-01 -9.30855647e-02 5.70887506e-01
-1.33932781e+00 -1.23962629e+00 -2.72369862e-01 3.58884901e-01
4.06480730e-01 -7.20454985e-03 1.54777646e+00 -9.78806019e-02
-1.36020541e-01 8.74779642e-01 7.79709443e-02 -2.39995807e-01
1.11610591e+00 -1.78108096e+00 5.20870984e-01 1.88391522e-01
5.06948948e-01 5.97653031e-01 5.39076865e-01 -5.83062530e-01
-8.70663106e-01 -1.19164371e+00 1.36870742e+00 -6.21533871e-01
3.26238394e-01 -4.96826977e-01 -4.80363488e-01 7.74853885e-01
2.74253339e-01 -5.51416986e-02 1.09611988e+00 -1.29549280e-01
-6.75007284e-01 9.44011062e-02 -1.33852339e+00 4.70998257e-01
1.08428311e+00 -7.00241387e-01 -8.92601192e-01 7.86588669e-01
9.69042003e-01 -3.48849654e-01 -6.41668975e-01 2.82122225e-01
2.00927392e-01 -5.28964043e-01 4.81673539e-01 -2.51792222e-01
1.18950076e-01 -4.01830882e-01 1.92311749e-01 -1.31244040e+00
-1.96166128e-01 -5.94033778e-01 -5.95858395e-01 1.30893135e+00
7.49244213e-01 -9.70772803e-01 1.15312433e+00 4.17558283e-01
8.51849392e-02 -3.78938049e-01 -6.34365559e-01 -1.01595068e+00
-1.83174059e-01 -2.53813297e-01 6.75708055e-01 1.22668719e+00
2.15524793e-01 5.58237016e-01 -2.73278445e-01 -4.00086969e-01
8.97326648e-01 4.67987150e-01 6.33753777e-01 -1.27367401e+00
-5.14264882e-01 -2.11149063e-02 -1.58875749e-01 -1.00926661e+00
7.71722317e-01 -1.48981047e+00 5.87895103e-02 -1.18238568e+00
4.13949490e-01 -9.84271407e-01 -4.61158663e-01 1.06297708e+00
-2.22605225e-02 9.66297746e-01 -1.95428923e-01 3.03748757e-01
-6.22865379e-01 1.91659883e-01 6.32554710e-01 -3.42377692e-01
-2.09385425e-01 -4.41822298e-02 -5.42318165e-01 7.56243169e-01
8.65712702e-01 -1.23368609e+00 -6.05433524e-01 -4.25372034e-01
1.10093102e-01 -2.56840914e-01 -1.42886207e-01 -1.12192154e+00
2.29548156e-01 -5.08386791e-02 1.56213403e-01 -5.42457461e-01
4.02570903e-01 -4.77468491e-01 1.37315646e-01 3.67800653e-01
-7.92171896e-01 1.02825224e-01 -1.33539677e-01 2.68761486e-01
-2.82040648e-02 -1.02560079e+00 8.99916410e-01 -4.21208173e-01
-4.37533021e-01 -1.66038319e-01 -4.37018961e-01 8.95113945e-02
8.99066150e-01 -2.04979599e-01 -3.70810002e-01 -1.68682769e-01
-9.24769461e-01 -9.44432691e-02 8.05521548e-01 2.81021833e-01
3.20014954e-01 -1.30567670e+00 -4.80100036e-01 2.10731655e-01
3.09369475e-01 -2.22011060e-01 -3.17127377e-01 -2.31793746e-02
-4.73810852e-01 3.80254805e-01 -1.31142768e-03 -5.52265048e-01
-1.14380217e+00 8.78225803e-01 2.30781380e-02 -2.42518723e-01
-4.87180054e-01 7.00952888e-01 -2.84796715e-01 -7.50099897e-01
1.50842801e-01 1.15071312e-01 -2.29969382e-01 1.53581247e-01
6.61597610e-01 6.12210333e-01 6.42484799e-02 -7.32042730e-01
4.06827126e-03 6.89916790e-01 -2.10810557e-01 -5.35073340e-01
8.91397774e-01 9.80764907e-03 -4.30211127e-01 1.15987253e+00
1.23537529e+00 1.44275380e-02 -6.41823947e-01 -4.73554313e-01
2.20430478e-01 -2.81633437e-01 -1.70069188e-01 -7.65796185e-01
-5.74759066e-01 7.35103011e-01 4.75016743e-01 9.94591936e-02
8.67539763e-01 1.53608799e-01 6.23273730e-01 6.55438602e-01
9.06165302e-01 -1.14286399e+00 5.87997064e-02 4.00781184e-01
1.50153160e-01 -1.03420317e+00 2.58534163e-01 -5.69450200e-01
-3.43150973e-01 1.11812711e+00 5.09960949e-01 3.64284180e-02
8.29493701e-01 3.53654116e-01 3.82651508e-01 -5.92113435e-02
-1.09240317e+00 -1.20422289e-01 -3.66299786e-03 6.10153437e-01
4.33373243e-01 3.33641738e-01 -5.32274723e-01 1.29401414e-02
-1.72220945e-01 -6.82285726e-02 7.87785769e-01 1.50318813e+00
-5.46407878e-01 -2.03654933e+00 -1.52070954e-01 7.97248363e-01
-1.76312014e-01 -8.33065361e-02 -5.96268713e-01 3.00088227e-01
3.64323556e-01 1.10887372e+00 -6.90261722e-02 -6.67848885e-01
-2.11135417e-01 6.75237536e-01 5.13305962e-01 -1.39073670e+00
-6.92689419e-01 -4.32347089e-01 2.66972512e-01 -1.18762091e-01
-8.54421794e-01 -2.06828997e-01 -1.30864656e+00 -1.10833518e-01
-7.39871025e-01 6.67892039e-01 8.58837843e-01 8.43953371e-01
1.87107459e-01 -7.87265450e-02 1.10934818e+00 -7.26674855e-01
-5.18085539e-01 -1.10842752e+00 -6.32893085e-01 3.28061610e-01
4.45851050e-02 -8.25364590e-01 -3.71470153e-01 2.70083278e-01] | [9.61387825012207, 3.9717977046966553] |
9d5aa2c0-0bdd-431c-8f3a-9dd062e03b16 | motility-at-the-origin-of-life-its | 1311.2531 | null | http://arxiv.org/abs/1311.2531v1 | http://arxiv.org/pdf/1311.2531v1.pdf | Motility at the origin of life: Its characterization and a model | Due to recent advances in synthetic biology and artificial life, the origin
of life is currently a hot topic of research. We review the literature and
argue that the two traditionally competing "replicator-first" and
"metabolism-first" approaches are merging into one integrated theory of
individuation and evolution. We contribute to the maturation of this more
inclusive approach by highlighting some problematic assumptions that still lead
to an impoverished conception of the phenomenon of life. In particular, we
argue that the new consensus has so far failed to consider the relevance of
intermediate timescales. We propose that an adequate theory of life must
account for the fact that all living beings are situated in at least four
distinct timescales, which are typically associated with metabolism, motility,
development, and evolution. On this view, self-movement, adaptive behavior and
morphological changes could have already been present at the origin of life. In
order to illustrate this possibility we analyze a minimal model of life-like
phenomena, namely of precarious, individuated, dissipative structures that can
be found in simple reaction-diffusion systems. Based on our analysis we suggest
that processes in intermediate timescales could have already been operative in
prebiotic systems. They may have facilitated and constrained changes occurring
in the faster- and slower-paced timescales of chemical self-individuation and
evolution by natural selection, respectively. | ['Nathaniel Virgo', 'Tom Froese', 'Takashi Ikegami'] | 2013-11-11 | null | null | null | null | ['artificial-life'] | ['miscellaneous'] | [ 2.39274681e-01 1.71650574e-01 2.27298677e-01 2.51714498e-01
6.39413178e-01 -6.62353635e-01 1.01229191e+00 4.41319287e-01
-4.27782178e-01 9.17964935e-01 -1.01550438e-01 -3.70592713e-01
-2.52589643e-01 -7.60751963e-01 -4.43387270e-01 -1.08844543e+00
-1.48888811e-01 3.70599568e-01 2.96638340e-01 -6.60896242e-01
3.21130335e-01 5.47657073e-01 -1.77614200e+00 -3.82198006e-01
8.62922728e-01 1.62066564e-01 2.86578327e-01 7.39514947e-01
-7.01358020e-02 1.38759732e-01 -4.38340008e-01 -2.61588961e-01
-1.10200852e-01 -1.04666829e+00 -5.85852325e-01 -1.24388868e-02
-6.29907846e-01 3.20216417e-01 -3.03933490e-02 6.81396782e-01
3.19167376e-01 -1.53541461e-01 9.57390785e-01 -6.44020915e-01
-7.95307100e-01 4.94087219e-01 -2.51103878e-01 1.43149018e-01
1.28298551e-01 3.91899735e-01 5.60497046e-01 -6.30661428e-01
7.89765954e-01 1.17692411e+00 4.14672464e-01 7.44521320e-01
-1.21883225e+00 2.29243383e-01 -1.77647829e-01 -9.55652222e-02
-1.21176732e+00 -4.43664819e-01 4.85655516e-01 -7.00180948e-01
7.94483602e-01 3.70797485e-01 1.31452048e+00 9.71536577e-01
9.42924559e-01 9.28487033e-02 1.30568647e+00 -5.87049842e-01
5.12262404e-01 6.36536721e-03 -3.81761998e-01 4.40264642e-01
9.38811362e-01 3.54707301e-01 -4.15627331e-01 -9.04419646e-02
8.23959649e-01 -3.59674007e-01 -2.45599180e-01 -1.94585487e-01
-1.27732635e+00 4.60867167e-01 -1.01557031e-01 8.35650325e-01
-3.84755433e-01 1.78624183e-01 2.22999215e-01 2.05882922e-01
3.82985413e-01 6.31874442e-01 -5.43018341e-01 -1.89786285e-01
-4.57755715e-01 -2.74011139e-02 9.91065681e-01 1.17530964e-01
5.02165496e-01 -1.32260680e-01 6.65624082e-01 2.88684011e-01
3.69482279e-01 3.33273172e-01 6.99967980e-01 -6.18045032e-01
-5.51052213e-01 6.85633123e-01 5.44958450e-02 -6.53327465e-01
-3.68155867e-01 -5.15343666e-01 -7.43450940e-01 3.12786192e-01
5.34073889e-01 -1.47715911e-01 -4.86090779e-01 1.73150682e+00
6.23624563e-01 -4.61237282e-02 3.78954411e-01 5.93720436e-01
1.89590663e-01 7.13845670e-01 -8.32771603e-03 -7.01860309e-01
1.14644134e+00 -4.16563869e-01 -5.82625091e-01 1.90430880e-01
3.55037481e-01 -5.64424574e-01 7.80762911e-01 2.84940422e-01
-1.14728558e+00 -1.89603433e-01 -1.22630370e+00 4.16243374e-01
-7.23547518e-01 -7.06724703e-01 6.83487058e-01 1.02268171e+00
-9.15751874e-01 1.12963104e+00 -9.77955043e-01 -1.08324564e+00
-4.08699572e-01 3.36965397e-02 1.87566988e-02 6.24520302e-01
-1.08820641e+00 1.14119458e+00 2.18879193e-01 2.70078659e-01
-8.09229732e-01 -4.16452140e-01 -1.06682092e-01 -2.89585859e-01
2.32198194e-01 -1.07118571e+00 7.21123576e-01 -9.93299961e-01
-1.70966661e+00 1.15953517e+00 2.76041888e-02 -2.10210770e-01
6.14938021e-01 3.46018255e-01 -2.62650788e-01 1.08938769e-01
-3.05721134e-01 1.49233729e-01 2.24890575e-01 -1.42514527e+00
-8.62283483e-02 -4.15853620e-01 -2.71980345e-01 1.09291270e-01
2.95551885e-02 -3.45523916e-02 4.01883543e-01 -3.46834660e-01
1.85840577e-01 -9.72226858e-01 -3.26326251e-01 2.28654337e-03
7.18664303e-02 -3.00666720e-01 2.97534734e-01 -1.14601105e-01
8.06406736e-01 -1.91414356e+00 6.13163471e-01 -1.45698011e-01
6.43270761e-02 1.42548069e-01 1.59160078e-01 1.15751779e+00
-3.28283086e-02 3.64207774e-01 -3.18261236e-01 1.15100287e-01
-1.43423840e-01 3.53594512e-01 3.21128070e-02 7.93740571e-01
1.64705161e-02 7.98089385e-01 -1.10254514e+00 -2.81701386e-01
1.43183500e-01 6.52870595e-01 2.73224153e-02 -1.55727223e-01
-3.21479440e-01 7.70126760e-01 -2.59100080e-01 6.55891836e-01
2.77895451e-01 6.20411225e-02 4.00864869e-01 4.53768849e-01
-8.63177657e-01 -7.68874511e-02 -8.09275031e-01 1.32232332e+00
6.23100027e-02 3.85792851e-01 4.75193448e-02 -9.78377283e-01
8.26410532e-01 4.30878580e-01 6.37606740e-01 -4.77124006e-01
2.55430251e-01 8.20121288e-01 6.08593702e-01 -5.34402847e-01
2.97250420e-01 -4.91992801e-01 2.26792514e-01 4.80131388e-01
-1.37673646e-01 -3.32860380e-01 1.39261767e-01 -2.78715879e-01
8.18845630e-01 4.06622767e-01 5.94433069e-01 -8.40319455e-01
7.33213902e-01 -1.65809467e-01 4.90672439e-01 3.59624654e-01
-5.20866990e-01 2.88151711e-01 4.72308904e-01 -3.91977280e-01
-1.33063436e+00 -9.46202278e-01 -3.84141564e-01 6.40299499e-01
4.46982622e-01 -2.33342364e-01 -8.90843749e-01 2.35244080e-01
-2.34595641e-01 4.69033003e-01 -8.26378703e-01 -4.26050216e-01
-7.03145921e-01 -1.27898479e+00 3.40499669e-01 -3.18186730e-01
-5.36621921e-02 -1.08434463e+00 -1.13764942e+00 4.91210163e-01
3.69121432e-01 -3.83365422e-01 2.74843246e-01 4.01857644e-01
-9.44523931e-01 -9.57028270e-01 -7.94030488e-01 -2.69272506e-01
6.62445724e-01 1.84532806e-01 9.08864319e-01 6.39706194e-01
-5.60856462e-01 3.38087052e-01 -4.07501161e-01 -3.77939761e-01
-1.04618573e+00 -1.01504833e-01 4.29511696e-01 -2.75849015e-01
-1.44863263e-01 -9.99497771e-01 -8.38797748e-01 2.46121645e-01
-1.12229586e+00 -7.75759295e-02 3.75333369e-01 5.52789748e-01
2.57438481e-01 -6.73745871e-02 8.29520226e-01 -2.93413699e-01
4.17946875e-01 -6.98324084e-01 -2.07337350e-01 4.49419439e-01
-7.97385812e-01 1.25112996e-01 7.30382740e-01 -5.09029388e-01
-9.68473136e-01 -2.26810277e-01 -1.46844208e-01 6.71056151e-01
-1.97919890e-01 4.25583005e-01 -1.47000521e-01 -9.29400027e-02
5.98638773e-01 5.27977049e-01 2.86564529e-01 -2.30871245e-01
3.33427429e-01 4.74870235e-01 4.13135365e-02 -7.47807920e-01
6.04353011e-01 6.82967484e-01 4.33589667e-01 -1.21484971e+00
7.61917308e-02 2.51786739e-01 -6.01226687e-01 -5.38228452e-01
8.16198468e-01 -3.57392371e-01 -7.64344811e-01 6.67127967e-01
-9.18135345e-01 -4.55979556e-01 -7.36173987e-01 2.86161721e-01
-7.48319626e-01 4.86249924e-01 -4.04683709e-01 -1.21275222e+00
-2.51051486e-01 -6.96963847e-01 4.89257604e-01 5.59739649e-01
-2.57674664e-01 -1.24871647e+00 7.04783678e-01 -2.29095027e-01
6.37042284e-01 7.64540374e-01 8.73745203e-01 -3.80357474e-01
-3.89498085e-01 2.47319296e-01 7.27691829e-01 -2.21133411e-01
2.85169899e-01 8.84329319e-01 -6.20741665e-01 -1.45927653e-01
3.40770751e-01 1.19410567e-01 6.79955065e-01 1.43312871e-01
-6.72671059e-03 -2.65526902e-02 -4.40850645e-01 3.43931645e-01
1.65072203e+00 7.31936812e-01 5.81983447e-01 4.53049123e-01
8.11405480e-02 1.35442257e+00 3.32755417e-01 3.15263510e-01
1.86929628e-01 3.99898946e-01 4.38184112e-01 4.72510681e-02
1.27407806e-02 6.62768036e-02 4.47219640e-01 1.14142942e+00
-4.23154175e-01 -2.86353171e-01 -8.70050251e-01 6.76310420e-01
-1.73887897e+00 -9.59271967e-01 -4.90446895e-01 2.27450633e+00
7.10234880e-01 9.66511890e-02 3.72250468e-01 4.27322648e-02
8.94426703e-01 -2.82731116e-01 -6.57081783e-01 -7.37598300e-01
-5.94330609e-01 1.43473461e-01 3.83469045e-01 5.96967518e-01
-3.02898437e-01 7.51917839e-01 7.40120363e+00 2.10613564e-01
-1.32284844e+00 4.81221005e-02 4.53537524e-01 5.55699989e-02
-5.62088192e-01 4.05040413e-01 -3.77487749e-01 6.17212474e-01
1.22833443e+00 -6.72327101e-01 2.02246115e-01 1.44032866e-01
5.63219845e-01 -4.76402342e-01 -8.80605161e-01 1.58853620e-01
-2.26687387e-01 -1.03468752e+00 -2.17957377e-01 4.20980960e-01
6.32466435e-01 -2.28067562e-01 -2.87479192e-01 -3.01352680e-01
5.30901738e-02 -8.34394932e-01 7.99281240e-01 7.09854126e-01
4.32657659e-01 -3.78711313e-01 2.80966550e-01 5.81643760e-01
-9.49337840e-01 6.58146963e-02 -2.85058349e-01 -3.85025412e-01
4.97178674e-01 7.92718470e-01 -3.58013839e-01 5.55078447e-01
8.74987245e-02 2.35494509e-01 -4.83410478e-01 9.29422319e-01
-3.12888715e-03 2.70092160e-01 -4.67503130e-01 -4.63762462e-01
-1.03139214e-01 -6.06112540e-01 6.43677115e-01 7.40932345e-01
5.05758345e-01 -3.53389382e-02 -7.16287911e-01 1.03972447e+00
7.63894618e-01 1.21986546e-01 -5.53694546e-01 -2.53166854e-01
3.49044234e-01 1.17308557e+00 -1.43384886e+00 -2.47557372e-01
2.06616279e-02 8.37812185e-01 -2.48135343e-01 -1.22807272e-01
-7.79787958e-01 2.50596590e-02 6.10475242e-01 3.13091099e-01
2.92802025e-02 -6.52283490e-01 -1.96886629e-01 -1.16071200e+00
-2.93473393e-01 -4.43055212e-01 -1.64989457e-01 -1.07609436e-01
-8.22196662e-01 3.75131875e-01 -8.61992687e-02 -4.11999255e-01
-7.92144910e-02 -4.19565946e-01 -7.41418362e-01 5.45088887e-01
-1.16937900e+00 -8.38043451e-01 1.58237979e-01 8.12136158e-02
2.66935676e-01 1.66017368e-01 6.77870870e-01 -9.34767351e-02
-8.07724178e-01 -1.04121141e-01 6.81882620e-01 -8.20866942e-01
4.25421178e-01 -1.13659048e+00 5.42497873e-01 8.30947578e-01
-3.08462083e-01 8.03424835e-01 1.25093544e+00 -9.47356761e-01
-1.42368829e+00 -2.88656980e-01 9.81117189e-01 -2.24032357e-01
7.23321736e-01 -4.77401853e-01 -7.26413369e-01 8.65069926e-02
4.33012366e-01 -6.14318728e-01 7.42498040e-01 -2.36707032e-01
2.70888835e-01 5.94645180e-02 -1.03600228e+00 9.03986216e-01
1.21695614e+00 -1.60774887e-01 -6.06121063e-01 3.72866064e-01
4.36599195e-01 2.70930082e-01 -8.65554452e-01 1.77240014e-01
9.38080728e-01 -1.16523230e+00 7.61399746e-01 -3.16439033e-01
1.90541700e-01 -3.89041007e-01 3.36978316e-01 -9.03409362e-01
-2.57753313e-01 -1.04807937e+00 1.56986624e-01 1.29499900e+00
1.85837358e-01 -1.17516768e+00 1.41643360e-01 3.55766565e-01
-9.17314831e-03 -8.33489835e-01 -1.19197035e+00 -9.06367481e-01
7.45081186e-01 5.63296139e-01 4.27761197e-01 9.18374300e-01
3.02254885e-01 1.11911833e-01 -9.52605798e-04 -5.41438401e-01
5.05778074e-01 -8.47252682e-02 3.88066858e-01 -1.46463943e+00
-3.89503658e-01 -6.17133617e-01 -1.99753672e-01 -1.51718840e-01
-1.99352548e-01 -3.50879043e-01 9.70555916e-02 -1.29722214e+00
5.65244704e-02 -2.38816559e-01 -8.28599408e-02 -3.66656989e-01
3.61640863e-02 -9.69850197e-02 3.82210687e-02 6.07433975e-01
-1.43430512e-02 4.04964715e-01 1.11991847e+00 6.18408620e-01
-3.11802059e-01 -5.44800401e-01 -7.32812822e-01 5.94928563e-01
9.34680104e-01 -4.39560056e-01 -3.01015794e-01 1.49789482e-01
7.67853737e-01 8.50856379e-02 8.04478824e-02 -1.01836300e+00
4.26755436e-02 -4.65033025e-01 -1.87716573e-01 8.66407529e-03
1.53642267e-01 -5.16648412e-01 8.10058415e-01 1.26428425e+00
-2.63698008e-02 6.74356446e-02 -2.73916930e-01 4.80697811e-01
3.98706287e-01 -3.25001895e-01 9.28159833e-01 -5.09758949e-01
-1.27786785e-01 -1.42136544e-01 -1.07828140e+00 -4.52097118e-01
1.57408679e+00 -6.92966998e-01 -5.65975964e-01 1.42358482e-01
-6.65666699e-01 -3.00441086e-01 1.15404177e+00 1.28539652e-01
1.27701312e-01 -7.95990884e-01 -6.23759747e-01 -2.43128762e-01
-2.70242244e-01 -5.21861255e-01 2.37256512e-01 9.96943891e-01
-1.19835317e+00 2.79353827e-01 -6.23245716e-01 -3.13779205e-01
-8.69305551e-01 8.57415020e-01 5.97046673e-01 5.08905873e-02
-3.26925218e-01 5.53723991e-01 2.28024468e-01 2.46350914e-02
-5.15258431e-01 2.64550652e-03 -1.88225433e-01 1.18445210e-01
1.33331105e-01 5.69945037e-01 -2.76415646e-01 -7.43567050e-01
-5.41539907e-01 8.69661391e-01 4.50294316e-01 -2.42195487e-01
1.33355701e+00 -6.38901889e-01 -7.37336338e-01 1.03608561e+00
4.11855698e-01 1.69441193e-01 -9.84504104e-01 5.49865305e-01
8.91466364e-02 1.05284166e-03 -7.13271141e-01 -4.53756064e-01
-4.11013931e-01 6.69876158e-01 3.13403517e-01 8.49897444e-01
9.31861043e-01 1.04843140e-01 4.52844828e-01 -1.35678519e-02
2.99092501e-01 -1.11516798e+00 -2.84913126e-02 1.96162835e-01
8.07093501e-01 -5.58614910e-01 -3.56401168e-02 -3.76569927e-01
1.23265304e-01 1.31968415e+00 3.51740360e-01 -3.24098349e-01
4.71840531e-01 2.67104536e-01 -2.62934059e-01 5.84127605e-02
-1.20440447e+00 -3.32707077e-01 -3.65225077e-01 6.34852886e-01
8.80226433e-01 3.26511413e-02 -1.52006674e+00 5.84423654e-02
4.55964208e-02 -2.75851786e-01 9.37313199e-01 9.89292324e-01
-8.12339962e-01 -1.49984872e+00 -5.87779164e-01 -3.80007505e-01
-4.17322308e-01 2.59444326e-01 -9.11171675e-01 7.76381135e-01
6.44449949e-01 8.07711720e-01 -1.68082029e-01 -4.46671359e-02
-2.17681542e-01 1.24392420e-01 7.70779610e-01 -3.28386486e-01
-7.69889653e-01 1.50072664e-01 -7.43896142e-02 -3.34703014e-03
-6.23647094e-01 -9.80751991e-01 -1.17416871e+00 -6.27345622e-01
-3.37545216e-01 4.11342978e-01 9.31943774e-01 8.46334875e-01
2.24035665e-01 4.19779360e-01 4.27220732e-01 -7.51555085e-01
-3.32598060e-01 -5.97116411e-01 -7.35177815e-01 2.59702392e-02
1.11987397e-01 -5.16191781e-01 -6.76966846e-01 1.40764579e-01] | [5.5889201164245605, 4.1747307777404785] |
c8bd4860-1f88-4655-8a30-9306bd87595d | a-more-fine-grained-aspect-sentiment-opinion | 2103.15255 | null | https://arxiv.org/abs/2103.15255v5 | https://arxiv.org/pdf/2103.15255v5.pdf | A More Fine-Grained Aspect-Sentiment-Opinion Triplet Extraction Task | Aspect Sentiment Triplet Extraction (ASTE) aims to extract aspect term, sentiment and opinion term triplets from sentences and tries to provide a complete solution for aspect-based sentiment analysis (ABSA). However, some triplets extracted by ASTE are confusing, since the sentiment in a triplet extracted by ASTE is the sentiment that the sentence expresses toward the aspect term rather than the sentiment of the aspect term and opinion term pair. In this paper, we introduce a more fine-grained Aspect-Sentiment-Opinion Triplet Extraction (ASOTE) Task. ASOTE also extracts aspect term, sentiment and opinion term triplets. However, the sentiment in a triplet extracted by ASOTE is the sentiment of the aspect term and opinion term pair. We build four datasets for ASOTE based on several popular ABSA benchmarks. We propose a Position-aware BERT-based Framework (PBF) to address this task. PBF first extracts aspect terms from sentences. For each extracted aspect term, PBF first generates aspect term-specific sentence representations considering both the meaning and the position of the aspect term, then extracts associated opinion terms and predicts the sentiments of the aspect term and opinion term pairs based on the sentence representations. Experimental results on the four datasets show the effectiveness of PBF. | ['Yancheng He', 'Cunxiang Yin', 'Fang Wang', 'Yuncong Li', 'Sheng-hua Zhong', 'Wenjun Zhang'] | 2021-03-29 | null | null | null | null | ['aspect-sentiment-opinion-triplet-extraction'] | ['natural-language-processing'] | [ 2.03186944e-01 -1.11516751e-01 -6.68343157e-02 -7.67435133e-01
-8.05223048e-01 -6.70845032e-01 6.29524708e-01 4.09894317e-01
1.13914767e-02 2.00823605e-01 6.31732941e-01 -1.54676706e-01
4.82144654e-02 -9.48705614e-01 -3.13744009e-01 -6.35236025e-01
3.38334024e-01 2.51957059e-01 -1.35423228e-01 -8.16909492e-01
4.46227163e-01 -7.95968994e-02 -1.52660894e+00 9.24388409e-01
5.81220806e-01 1.56227684e+00 -2.07160100e-01 4.48263317e-01
-8.33063304e-01 6.90498054e-01 -1.07367969e+00 -6.70884907e-01
1.41007856e-01 -3.86899382e-01 -7.99804270e-01 3.34577471e-01
2.04858050e-01 4.24179852e-01 5.73588312e-01 8.61392796e-01
2.40289435e-01 -1.12566039e-01 7.88234055e-01 -1.18939209e+00
-5.02224088e-01 5.87898195e-01 -6.81423366e-01 -1.22755259e-01
5.06893218e-01 -2.27535293e-01 1.68941891e+00 -1.21953428e+00
4.35134947e-01 1.21348774e+00 5.09370923e-01 1.73488215e-01
-3.45457435e-01 -2.52059817e-01 6.66873515e-01 -1.42498612e-01
-7.60568261e-01 -1.06263645e-01 1.03382540e+00 -2.58996993e-01
1.36103332e+00 5.43480575e-01 1.09008694e+00 7.35910833e-01
5.18603563e-01 1.10777843e+00 1.18319869e+00 -3.04464042e-01
2.08861664e-01 3.77997935e-01 8.60450149e-01 2.62848973e-01
6.83852136e-02 -5.55911422e-01 -8.57476056e-01 -1.84907064e-01
-2.92697191e-01 -9.64741930e-02 -1.70418937e-02 2.97433417e-02
-9.67555344e-01 7.39799678e-01 3.03613454e-01 3.77744973e-01
-6.85459793e-01 -3.33084613e-01 6.07294977e-01 3.64102215e-01
7.07596481e-01 4.13279742e-01 -9.90143895e-01 -2.62461230e-02
-5.41719019e-01 3.13183039e-01 1.07885146e+00 9.29307997e-01
9.94350731e-01 -7.74671808e-02 -5.47590077e-01 8.93313110e-01
5.97331882e-01 8.23769987e-01 6.92948282e-01 -2.38723412e-01
4.62781042e-01 1.44808447e+00 -9.94306430e-02 -1.36454356e+00
-4.69026476e-01 -4.17786330e-01 -5.39809406e-01 -1.19439043e-01
-4.17478412e-01 -1.23011485e-01 -9.37428594e-01 1.20102167e+00
5.48086286e-01 -6.51251733e-01 4.05920833e-01 6.33731544e-01
1.41028488e+00 7.80616939e-01 -2.88666695e-01 -2.38803580e-01
1.98933792e+00 -1.16216338e+00 -7.73327470e-01 -7.97321558e-01
5.52409351e-01 -1.14854825e+00 9.27940547e-01 2.57927686e-01
-6.97741687e-01 -2.15508148e-01 -1.15887320e+00 -3.69154811e-02
-7.45921493e-01 1.25770420e-01 6.16734505e-01 3.54712218e-01
-7.64306903e-01 2.57012271e-03 -3.64067882e-01 1.49074448e-02
1.53529182e-01 2.93670774e-01 -3.14973831e-01 8.22892934e-02
-1.18591583e+00 7.30845213e-01 3.09529877e-03 3.33159119e-01
-2.94396542e-02 -5.36946118e-01 -1.44521439e+00 6.12161532e-02
2.58295953e-01 -9.22105730e-01 1.15991795e+00 -1.21694899e+00
-1.22622418e+00 6.72738731e-01 -7.42762983e-01 -2.30593397e-03
-4.05851662e-01 -2.69214004e-01 -6.71548784e-01 -6.19264394e-02
6.08780384e-01 2.05820382e-01 7.80575454e-01 -1.27274585e+00
-7.28504062e-01 -6.70717895e-01 3.68968457e-01 4.50880647e-01
-4.69956636e-01 1.98606923e-01 -4.48467553e-01 -5.90726852e-01
2.24584877e-01 -8.12322915e-01 -1.74336329e-01 -5.32244384e-01
-5.98056018e-01 -5.09956062e-01 7.81449199e-01 -2.17484251e-01
1.36058700e+00 -2.11224174e+00 -1.25874951e-01 2.25459293e-01
9.37709436e-02 2.60513365e-01 -4.03046936e-01 5.21153510e-01
-2.09092826e-01 -5.09104878e-02 -2.49876514e-01 -4.21468228e-01
1.40979424e-01 1.79593161e-01 -6.14405930e-01 -4.07401353e-01
5.30062675e-01 9.38963056e-01 -8.40609729e-01 -4.71823215e-01
-2.15143755e-01 5.72582483e-01 -4.35952902e-01 1.14482664e-01
-3.01118463e-01 -4.21028659e-02 -7.93184996e-01 9.55254614e-01
7.16495216e-01 -1.46059558e-01 -7.49474168e-02 -6.66871905e-01
-6.89876527e-02 6.99436069e-01 -8.59451711e-01 1.05930352e+00
-8.51046860e-01 3.65791529e-01 -3.25454950e-01 -5.80813348e-01
1.24814188e+00 1.97191715e-01 4.66041803e-01 -6.91860318e-01
3.38303268e-01 3.01907033e-01 -3.29639226e-01 -5.64017594e-01
1.01305425e+00 -4.52255189e-01 -4.73209798e-01 5.32502890e-01
3.26046459e-02 -6.60297155e-01 7.42443562e-01 3.22688520e-01
8.74486744e-01 6.39499398e-03 5.45746684e-01 -1.72911316e-01
9.57253695e-01 7.37558678e-02 5.21092236e-01 8.84370282e-02
2.09104847e-02 7.02022076e-01 8.62891734e-01 -7.28869796e-01
-4.62392837e-01 -4.98859525e-01 5.62119074e-02 9.57633018e-01
1.09644346e-01 -1.18279135e+00 -2.17451453e-01 -1.12817287e+00
-2.62168676e-01 5.84994137e-01 -7.83546031e-01 -6.69497699e-02
-3.53052020e-01 -8.68186951e-01 -2.36043647e-01 4.24771339e-01
4.16683584e-01 -1.17797589e+00 -1.09281637e-01 1.21991420e-02
-5.17200351e-01 -1.15261996e+00 -5.99002659e-01 1.46806896e-01
-3.86299670e-01 -9.11883056e-01 -4.23415631e-01 -7.20074892e-01
7.26569951e-01 4.34539318e-01 1.49674988e+00 -2.04534400e-02
3.24839592e-01 1.15260996e-01 -7.90404022e-01 -7.10704267e-01
1.34982844e-03 -1.19707316e-01 -2.50181288e-01 4.44378108e-01
8.17393184e-01 -3.33980262e-01 -6.47034943e-01 1.00759484e-01
-9.68594193e-01 -1.68490186e-01 6.19646609e-01 6.34109557e-01
8.21909189e-01 1.06904348e-02 2.87643790e-01 -1.21998394e+00
9.62714434e-01 -5.15581310e-01 -1.89899608e-01 1.59063384e-01
-7.37569809e-01 -1.25348300e-01 6.12232208e-01 4.45470475e-02
-9.20942843e-01 -3.82834643e-01 -4.92180854e-01 1.29811823e-01
2.76676029e-01 1.13213801e+00 -2.56256014e-01 5.52196622e-01
2.16519564e-01 3.52972269e-01 -4.85790253e-01 -6.89786896e-02
1.46522135e-01 9.64881897e-01 1.77907497e-02 -3.68365824e-01
4.95087445e-01 4.81109321e-01 -3.28214802e-02 -6.66198909e-01
-1.67090380e+00 -7.36237884e-01 -2.28363916e-01 -2.84725189e-01
4.78899211e-01 -9.64374900e-01 -2.52333999e-01 4.48814362e-01
-1.26043677e+00 7.08742380e-01 -4.95223582e-01 7.82370046e-02
-2.74558604e-01 1.28449738e-01 -8.83810073e-02 -8.30623150e-01
-1.02761006e+00 -1.27778637e+00 1.65879345e+00 3.63917649e-01
-6.60461187e-01 -9.59354579e-01 2.75683790e-01 6.00051582e-01
3.65709931e-01 1.38991192e-01 8.15859497e-01 -7.72716880e-01
-1.28349036e-01 -6.51209176e-01 -1.93225089e-02 5.82149982e-01
5.83275020e-01 2.04561859e-01 -9.92031276e-01 9.43794101e-02
3.78961533e-01 -1.43086001e-01 8.90033126e-01 2.65899718e-01
3.54733706e-01 -5.11269271e-01 1.97317645e-01 2.51914710e-01
1.28302050e+00 -4.71120626e-02 2.52544969e-01 5.45713484e-01
6.71709359e-01 7.35673487e-01 1.00104439e+00 3.47456247e-01
7.71991014e-01 5.51738858e-01 1.83145419e-01 1.56248435e-01
4.88970913e-02 7.00894073e-02 8.77035618e-01 1.44383144e+00
2.51405209e-01 -2.00024962e-01 -6.13145709e-01 8.06774855e-01
-1.57784009e+00 -5.37782133e-01 -4.53291327e-01 1.49374735e+00
7.52984643e-01 3.16275239e-01 -1.01169348e-01 3.70422035e-01
1.78700715e-01 6.60792053e-01 -3.27178240e-01 -9.85379338e-01
-4.55051005e-01 1.24775298e-01 -4.04610246e-01 3.53978574e-01
-1.05864573e+00 8.41161728e-01 4.87111044e+00 7.85717726e-01
-1.04428768e+00 -1.26902848e-01 4.92492467e-01 1.35012642e-02
-8.96037459e-01 2.04586491e-01 -9.19174850e-01 1.41677633e-01
5.83943665e-01 -4.42168951e-01 -2.44172096e-01 1.07509470e+00
1.70552594e-04 -1.72640324e-01 -8.88723016e-01 6.13204181e-01
5.63355803e-01 -9.31084037e-01 6.05741262e-01 -3.51884186e-01
1.00458658e+00 -1.25783458e-01 2.21236825e-01 4.68982399e-01
-2.41157472e-01 -5.82163870e-01 6.55280113e-01 2.21130684e-01
2.68263489e-01 -8.19851100e-01 1.37342536e+00 -1.83400661e-01
-1.67837131e+00 1.62352666e-01 -1.46198377e-01 -1.97404236e-01
2.03516781e-01 1.26988876e+00 -4.52127218e-01 9.33482766e-01
8.45786691e-01 1.17819655e+00 -6.31933033e-01 4.63308871e-01
-5.65747917e-01 2.84518987e-01 -4.40354906e-02 -3.96494031e-01
5.69861472e-01 -3.68832082e-01 7.76024401e-01 1.23168087e+00
1.98014989e-01 -2.72621661e-01 -1.16803586e-01 5.27590930e-01
-1.14934137e-02 6.86522067e-01 -6.34064734e-01 -4.83958811e-01
-4.21074964e-02 1.84889805e+00 -6.92694008e-01 -4.73801345e-01
-5.62836289e-01 7.60513127e-01 4.81438674e-02 2.24987403e-01
-1.58769831e-01 -5.63443363e-01 8.56373906e-01 -4.15378064e-01
6.36908829e-01 3.31371069e-01 -6.10455096e-01 -1.37324631e+00
7.17389584e-01 -1.07787848e+00 3.70954335e-01 -8.97745490e-01
-1.41138375e+00 1.30145240e+00 -3.56826603e-01 -1.66528821e+00
-3.79976183e-01 -7.37168729e-01 -1.01260209e+00 8.22299421e-01
-1.75775647e+00 -1.45063186e+00 -9.62678641e-02 2.24555403e-01
8.27584147e-01 -1.59283131e-01 9.07431781e-01 -9.76976901e-02
-4.26385254e-01 3.07068855e-01 -5.25284231e-01 8.72507766e-02
3.63339305e-01 -1.31102097e+00 4.89059150e-01 6.61490440e-01
2.05785587e-01 9.97303128e-01 7.29153812e-01 -4.69041467e-01
-1.34565270e+00 -9.93527234e-01 1.69720256e+00 -6.06730759e-01
8.11414540e-01 -1.23615235e-01 -5.33386230e-01 5.12241423e-01
4.48430926e-01 -3.64521623e-01 1.03870666e+00 5.20876527e-01
-6.21286035e-01 -2.83237159e-01 -7.47426748e-01 5.61858773e-01
2.37041220e-01 -6.14705622e-01 -7.19936073e-01 3.27752829e-01
8.99544835e-01 -1.08537316e-01 -7.49026775e-01 8.31886113e-01
6.37274265e-01 -1.08735681e+00 6.43357575e-01 -4.14507687e-01
9.59081948e-01 -5.13725162e-01 -3.77612352e-01 -1.53326082e+00
2.42906958e-01 -5.84854670e-02 -1.59385711e-01 1.64219570e+00
9.63072538e-01 -4.12746876e-01 4.57391113e-01 4.07755911e-01
-6.03380240e-02 -1.40723300e+00 -5.49036920e-01 -3.20481628e-01
-6.12534359e-02 -6.03924036e-01 9.99612331e-01 5.60376942e-01
2.74406701e-01 1.07046616e+00 4.49342430e-02 -2.62207445e-02
9.49340034e-03 1.02356088e+00 5.48690856e-01 -7.82733977e-01
-1.05560683e-01 -5.44549584e-01 -3.72741669e-01 -8.41849327e-01
1.21659771e-01 -7.62781322e-01 4.02269624e-02 -1.87346876e+00
4.75932837e-01 1.46440282e-01 -3.74074876e-01 4.36549962e-01
-6.09875441e-01 2.77131647e-01 2.15983599e-01 -1.27358958e-01
-7.28398144e-01 8.76284182e-01 1.40968347e+00 -5.84219098e-01
1.86207518e-02 3.40764344e-01 -1.31264317e+00 1.09302533e+00
6.35285258e-01 -4.61541772e-01 -3.59270990e-01 -2.74273992e-01
1.13980341e+00 -3.58716160e-01 -3.36348593e-01 -4.89439577e-01
5.19279987e-02 9.16186720e-02 1.59490466e-01 -1.08308768e+00
4.52369630e-01 -7.72871077e-01 -5.87053359e-01 7.67192841e-02
-1.31229773e-01 3.27859610e-01 9.72192958e-02 2.16446832e-01
-8.73756766e-01 -2.15049744e-01 2.22159103e-01 -5.36914952e-02
-4.05051351e-01 4.81366552e-02 -2.99552917e-01 1.35539293e-01
5.16389728e-01 5.98921478e-02 -4.53587890e-01 -4.32081491e-01
-3.27299237e-01 3.94436866e-01 1.24929361e-01 6.58773661e-01
9.31984901e-01 -1.34035480e+00 -6.03763878e-01 3.70120198e-01
7.07784295e-01 1.74763337e-01 2.18402550e-01 8.37199330e-01
5.10735027e-02 3.67501110e-01 2.57124454e-01 -2.81414539e-01
-1.36334813e+00 3.14497679e-01 6.27750680e-02 -7.88673639e-01
2.15829574e-02 9.41370904e-01 2.87299782e-01 -8.92150879e-01
-4.23411667e-01 -3.87259454e-01 -1.00394130e+00 5.33704758e-01
7.79350162e-01 -2.52635181e-01 3.29887658e-01 -1.18662548e+00
-4.84270662e-01 1.00770259e+00 -3.71675104e-01 -1.32479399e-01
1.30671144e+00 -1.64568350e-01 -7.13836133e-01 7.20119774e-01
1.36756897e+00 4.17367429e-01 -2.38345638e-01 -1.54316410e-01
3.75912152e-02 -2.87600070e-01 -7.42425695e-02 -8.43431771e-01
-1.26864052e+00 6.34246111e-01 -1.13068230e-01 3.55300754e-01
1.36205184e+00 6.53108880e-02 1.09403419e+00 3.36935967e-01
7.55719766e-02 -9.63825107e-01 6.55840784e-02 1.00194132e+00
1.15472245e+00 -1.27040386e+00 7.89450109e-02 -5.22070587e-01
-1.07042336e+00 9.99839067e-01 6.15113795e-01 -1.01564955e-02
9.10908580e-01 9.39871594e-02 6.36730909e-01 -6.88575685e-01
-9.61743772e-01 -3.63567799e-01 6.88362539e-01 2.26891682e-01
6.04594350e-01 -3.60643454e-02 -6.42312288e-01 1.15697527e+00
-7.74702609e-01 -3.53625089e-01 3.92947763e-01 1.06625879e+00
-3.05074811e-01 -1.31114590e+00 -8.69490132e-02 5.28275430e-01
-4.50051665e-01 -5.17637372e-01 -9.11814809e-01 9.68337357e-02
5.48368543e-02 1.35567939e+00 -1.87183842e-01 -6.39747620e-01
5.88643610e-01 7.03328326e-02 -1.97020695e-01 -7.01035857e-01
-1.03731155e+00 1.67205781e-01 4.83153939e-01 -6.20786011e-01
-6.83603644e-01 -4.46828902e-01 -1.15887046e+00 1.84110746e-01
-3.81570816e-01 5.60547709e-01 1.04628170e+00 1.35455084e+00
4.52636659e-01 6.93166614e-01 1.11884403e+00 -4.22294587e-01
4.13980102e-03 -1.14254749e+00 -5.37385225e-01 5.55802405e-01
4.54328060e-01 -1.55381635e-01 -4.83191490e-01 -2.97305971e-01] | [11.463924407958984, 6.652829647064209] |
a7972026-fafe-4940-842c-4536d29aa4c6 | boundary-aware-self-supervised-learning-for | 2201.05277 | null | https://arxiv.org/abs/2201.05277v1 | https://arxiv.org/pdf/2201.05277v1.pdf | Boundary-aware Self-supervised Learning for Video Scene Segmentation | Self-supervised learning has drawn attention through its effectiveness in learning in-domain representations with no ground-truth annotations; in particular, it is shown that properly designed pretext tasks (e.g., contrastive prediction task) bring significant performance gains for downstream tasks (e.g., classification task). Inspired from this, we tackle video scene segmentation, which is a task of temporally localizing scene boundaries in a video, with a self-supervised learning framework where we mainly focus on designing effective pretext tasks. In our framework, we discover a pseudo-boundary from a sequence of shots by splitting it into two continuous, non-overlapping sub-sequences and leverage the pseudo-boundary to facilitate the pre-training. Based on this, we introduce three novel boundary-aware pretext tasks: 1) Shot-Scene Matching (SSM), 2) Contextual Group Matching (CGM) and 3) Pseudo-boundary Prediction (PP); SSM and CGM guide the model to maximize intra-scene similarity and inter-scene discrimination while PP encourages the model to identify transitional moments. Through comprehensive analysis, we empirically show that pre-training and transferring contextual representation are both critical to improving the video scene segmentation performance. Lastly, we achieve the new state-of-the-art on the MovieNet-SSeg benchmark. The code is available at https://github.com/kakaobrain/bassl. | ['Eun-Sol Kim', 'Joonseok Lee', 'Seongsu Ha', 'Sangho Lee', 'Gunsoo Han', 'Minchul Shin', 'Jonghwan Mun'] | 2022-01-14 | null | null | null | null | ['scene-segmentation'] | ['computer-vision'] | [ 6.13922358e-01 -1.24017419e-02 -6.46014214e-01 -3.55295509e-01
-8.09760928e-01 -5.10474443e-01 5.91591537e-01 1.48628339e-01
-2.24806398e-01 1.26286656e-01 3.56368184e-01 -1.67910293e-01
-1.57727879e-02 -4.70608681e-01 -9.20094132e-01 -5.63858330e-01
-3.52385151e-03 6.18979409e-02 5.78526497e-01 -9.33110062e-03
2.65748382e-01 -3.91564518e-03 -1.43964422e+00 5.93551934e-01
9.10963714e-01 1.19500840e+00 4.82991338e-01 6.69732094e-01
-1.12186214e-02 1.00159025e+00 -8.92461166e-02 -6.33261055e-02
3.64769071e-01 -6.58060312e-01 -1.18331313e+00 4.10670519e-01
4.11121309e-01 -3.25578630e-01 -4.56081688e-01 9.41602051e-01
1.44857332e-01 6.15503192e-01 5.85317850e-01 -1.20548439e+00
-2.18310028e-01 5.00018179e-01 -7.49690473e-01 4.61879104e-01
2.65615880e-01 2.50398278e-01 1.21439445e+00 -8.89456868e-01
7.58378863e-01 8.77297759e-01 6.38005257e-01 3.43898118e-01
-1.12819803e+00 -4.24210429e-01 4.18547958e-01 5.46075583e-01
-1.20901370e+00 -5.03779829e-01 1.04983664e+00 -5.88587880e-01
6.05913341e-01 1.22906506e-01 6.00947320e-01 1.16455734e+00
-5.56649640e-02 1.21157920e+00 7.94842660e-01 -4.18204963e-01
3.69792312e-01 -3.29074651e-01 1.41127229e-01 6.30460918e-01
-2.14258045e-01 -5.87965623e-02 -5.44131160e-01 2.54401445e-01
8.49778235e-01 2.07390875e-01 -3.17372710e-01 -4.34521437e-01
-1.02121615e+00 6.57182872e-01 3.20658445e-01 2.40154579e-01
-3.43074441e-01 4.12420975e-03 5.91692150e-01 1.48062436e-02
5.28092086e-01 2.72573948e-01 -4.02252078e-01 -1.73081473e-01
-1.26937294e+00 2.67567094e-02 5.14690399e-01 9.80634928e-01
9.29693401e-01 -1.21794157e-01 -3.67717832e-01 9.86743629e-01
8.53854418e-02 5.72478957e-02 4.76250887e-01 -1.15173483e+00
4.10562575e-01 4.94289041e-01 -1.24639228e-01 -8.38652551e-01
-2.77046829e-01 -2.13326782e-01 -7.19060242e-01 -3.05806547e-01
5.23760319e-01 -1.12818278e-01 -1.11344087e+00 1.71112919e+00
4.67940032e-01 1.01195812e+00 -1.32362008e-01 1.07415092e+00
9.12107527e-01 7.74776340e-01 3.12063098e-01 -2.51221329e-01
1.25880992e+00 -1.53584099e+00 -4.13283229e-01 -3.85882497e-01
7.28551209e-01 -6.04920685e-01 1.35237575e+00 2.20533863e-01
-9.07026350e-01 -8.13151598e-01 -8.42005551e-01 -2.73432191e-02
-5.36545888e-02 -1.58773400e-02 4.13838416e-01 6.99541997e-03
-7.36416817e-01 7.68782020e-01 -8.06489885e-01 -5.02268195e-01
6.69284403e-01 1.80008803e-02 -1.98014498e-01 -8.95913020e-02
-1.05703974e+00 2.60863274e-01 3.84194285e-01 -8.46880674e-02
-1.29410899e+00 -8.77942085e-01 -9.53820944e-01 -8.10616314e-02
8.64799798e-01 -6.12033129e-01 1.32902563e+00 -1.37840152e+00
-1.44973099e+00 1.05016828e+00 -2.61253864e-01 -5.62409580e-01
4.76450831e-01 -4.09856170e-01 -2.01807156e-01 5.97487092e-01
2.86419451e-01 8.13392639e-01 9.63955641e-01 -1.37450039e+00
-8.06437850e-01 1.50740345e-03 5.93466386e-02 3.76430899e-01
-2.71943629e-01 -2.53158971e-03 -8.88947964e-01 -9.03515816e-01
1.28897876e-01 -7.34030426e-01 -2.96288610e-01 -3.09493601e-01
-6.67079747e-01 -1.43468142e-01 8.37829411e-01 -7.88216889e-01
1.36845243e+00 -2.20645332e+00 1.03461305e-02 -1.81877557e-02
1.92837358e-01 2.93117493e-01 -1.97246775e-01 2.71577924e-01
-8.82692188e-02 9.18382499e-03 -4.60570991e-01 -5.18499196e-01
-2.04997048e-01 7.02847540e-02 -4.09626484e-01 3.64270508e-01
1.30456254e-01 1.02201390e+00 -1.06288850e+00 -7.05129385e-01
3.82911295e-01 7.67864659e-02 -7.07667768e-01 4.56517875e-01
-4.33265269e-01 6.76210642e-01 -3.82954955e-01 6.37285233e-01
3.69822413e-01 -4.58350092e-01 1.18044786e-01 -2.34404415e-01
-4.77762595e-02 2.21409947e-01 -9.23467696e-01 2.03121495e+00
-2.12500840e-01 6.80945694e-01 -1.28603145e-01 -1.29769611e+00
6.47702992e-01 1.23971321e-01 7.51630664e-01 -7.20313370e-01
2.60983706e-01 -2.29697868e-01 -3.23799759e-01 -7.05345035e-01
4.86651123e-01 1.11309409e-01 5.07704318e-02 3.61261845e-01
2.06416383e-01 1.25253916e-01 2.78960198e-01 2.13353157e-01
1.02462089e+00 4.60704297e-01 2.23772615e-01 -2.48689905e-01
3.55175823e-01 9.89371017e-02 8.15472960e-01 5.91503859e-01
-5.12348890e-01 9.23156857e-01 4.85901803e-01 -7.13984743e-02
-1.01775336e+00 -9.69476461e-01 1.69944078e-01 1.42034233e+00
6.82998836e-01 -5.31943321e-01 -1.04811442e+00 -8.19809496e-01
-2.19315678e-01 5.77314854e-01 -5.87378740e-01 -1.55199379e-01
-6.01272047e-01 -3.50761920e-01 2.72163391e-01 7.31638253e-01
6.43449426e-01 -9.77373183e-01 -7.22985208e-01 4.38284986e-02
-3.25038284e-01 -1.46081221e+00 -8.28523278e-01 1.20449118e-01
-8.76136243e-01 -1.26749003e+00 -6.52670145e-01 -1.04000425e+00
6.46228909e-01 6.47788465e-01 9.26773071e-01 -1.27229085e-02
-2.24099129e-01 6.12248480e-01 -6.40804410e-01 2.02491328e-01
-1.10723339e-01 2.85084154e-02 -1.86004028e-01 2.64047503e-01
1.64254427e-01 -6.63495660e-01 -9.13804770e-01 5.77171862e-01
-7.66850650e-01 6.12191379e-01 3.08999538e-01 7.23987162e-01
9.02048707e-01 -1.03470013e-01 4.96602148e-01 -1.05618584e+00
1.15213655e-01 -6.65674865e-01 -3.36859405e-01 2.30379060e-01
-3.20104003e-01 -3.82777601e-01 7.02996433e-01 -4.50413465e-01
-1.22988594e+00 4.95939776e-02 -2.96306284e-03 -8.73039782e-01
-3.94924819e-01 3.78595024e-01 -2.09542140e-01 2.39964873e-01
5.58407784e-01 2.57979304e-01 -2.80755132e-01 -4.66992766e-01
5.10140717e-01 4.85960841e-01 7.17678785e-01 -6.38739944e-01
5.13154030e-01 5.75301051e-01 -3.78987253e-01 -8.37426901e-01
-1.07140219e+00 -9.03517365e-01 -9.50522959e-01 -5.10605454e-01
1.03373098e+00 -1.01953638e+00 -3.14644843e-01 4.35827821e-01
-7.63992906e-01 -1.10278654e+00 -3.46417904e-01 2.76617527e-01
-8.76375556e-01 6.36993408e-01 -7.77984977e-01 -6.03639543e-01
-2.69115537e-01 -9.85376120e-01 9.91895616e-01 4.19967949e-01
-2.44098917e-01 -1.07180357e+00 -2.52157208e-02 6.19682193e-01
-7.04453960e-02 2.46286184e-01 7.07882702e-01 -7.56690741e-01
-5.31820774e-01 2.52696723e-01 -2.93618381e-01 3.71591061e-01
1.43113986e-01 -7.99250752e-02 -1.08888423e+00 -1.94620728e-01
-6.69723973e-02 -3.04448605e-01 1.09467256e+00 5.39728403e-01
1.38302803e+00 -2.24296540e-01 -2.45388284e-01 9.87663448e-01
1.16749120e+00 2.16487885e-01 4.95759189e-01 3.98499042e-01
9.62112606e-01 6.24380350e-01 9.94246840e-01 5.52867711e-01
3.86524051e-01 7.14379191e-01 2.35529199e-01 -1.90549552e-01
-3.57122481e-01 -6.69893622e-01 2.61209965e-01 6.69761837e-01
-4.40304726e-02 -1.04155704e-01 -9.95344818e-01 5.28260946e-01
-2.16006351e+00 -8.93333018e-01 8.48210137e-03 2.06935453e+00
8.47715199e-01 2.61630714e-01 3.18609715e-01 -6.96972758e-03
9.09972966e-01 5.28946161e-01 -6.85304165e-01 9.84031856e-02
-5.84600605e-02 -4.25668992e-02 3.62025350e-01 3.36200714e-01
-1.57973635e+00 1.45120621e+00 4.85937643e+00 1.10184109e+00
-1.04036582e+00 3.51543993e-01 1.03186917e+00 8.07831064e-02
-1.09148078e-01 1.94641262e-01 -5.35754859e-01 5.74125886e-01
6.22482121e-01 -5.82252592e-02 3.78566265e-01 9.08494294e-01
5.19439518e-01 -2.83664048e-01 -1.16201103e+00 9.65136766e-01
7.28291720e-02 -1.43401003e+00 -7.14941025e-02 -4.20647919e-01
1.02177691e+00 -1.09550804e-02 -1.70680255e-01 3.77938211e-01
-1.72171816e-02 -6.63119256e-01 9.16351855e-01 3.27757180e-01
7.96550155e-01 -4.83498752e-01 3.21788937e-01 2.10147649e-01
-1.48282957e+00 -1.21141590e-01 -1.56336784e-01 6.45370856e-02
2.52763897e-01 4.66344267e-01 -4.77942169e-01 6.17100298e-01
6.67102635e-01 1.09301472e+00 -4.23801839e-01 1.26445758e+00
-3.84881586e-01 1.05641735e+00 -1.32340519e-02 5.15150070e-01
3.95467311e-01 -3.54591995e-01 4.80911553e-01 1.50341201e+00
-6.76134974e-02 2.46769577e-01 5.03111541e-01 8.05410743e-01
-6.27319962e-02 1.04312137e-01 -2.62317955e-01 1.18415006e-01
4.56112206e-01 1.13917434e+00 -1.21603584e+00 -4.80132550e-01
-3.23636562e-01 1.13359964e+00 1.46744713e-01 6.75046921e-01
-1.03308868e+00 -1.27331063e-01 7.21459389e-01 2.05622390e-01
4.77250963e-01 -6.19892441e-02 -3.71986032e-01 -1.12856722e+00
-2.08998159e-01 -7.47406602e-01 6.46050513e-01 -7.23741472e-01
-1.16165578e+00 3.34509134e-01 1.30873680e-01 -1.38817620e+00
-1.80575341e-01 -2.19667956e-01 -9.94114101e-01 2.79265523e-01
-1.46460438e+00 -1.12467492e+00 -5.69294691e-01 6.84949696e-01
1.09525526e+00 1.12973690e-01 1.82447955e-01 3.64669412e-01
-9.15688396e-01 6.10250294e-01 -8.46032947e-02 3.48119378e-01
6.35791481e-01 -1.04872692e+00 3.51562560e-01 1.20472097e+00
2.24208474e-01 2.79119015e-01 4.77675557e-01 -7.68021762e-01
-1.23339057e+00 -1.44032311e+00 3.68811250e-01 -2.21203938e-01
7.23110735e-01 -4.46111530e-01 -9.57757592e-01 6.81509018e-01
3.46341468e-02 1.18950203e-01 5.68780363e-01 -1.25276998e-01
-3.24382126e-01 5.64816706e-02 -6.65826619e-01 6.94815993e-01
1.44565761e+00 -6.37751281e-01 -4.89886403e-01 3.48216504e-01
9.78935361e-01 -4.73141223e-01 -5.88181555e-01 4.33298111e-01
2.88526684e-01 -1.03735662e+00 1.00694311e+00 -6.88276410e-01
8.65784287e-01 -2.08074242e-01 -8.09569582e-02 -9.42683458e-01
-2.36970589e-01 -8.49110186e-01 -2.30478778e-01 1.35388172e+00
1.13411531e-01 -1.63351685e-01 9.95289564e-01 4.30543214e-01
-5.63621223e-01 -1.03069139e+00 -6.28128886e-01 -7.50596821e-01
-2.91520596e-01 -6.88403308e-01 1.06669500e-01 9.99416232e-01
1.17127918e-01 2.90558189e-01 -4.18457121e-01 8.95787030e-02
5.34603119e-01 3.93053889e-01 7.83535242e-01 -7.65803158e-01
-3.98768246e-01 -5.36372721e-01 -1.40266716e-01 -1.59469759e+00
2.09985867e-01 -8.92815769e-01 2.98166782e-01 -1.55528879e+00
3.97249430e-01 -4.48358059e-01 -4.30330426e-01 4.24542516e-01
-3.25925440e-01 2.51804292e-01 3.74449283e-01 4.54723865e-01
-1.30383861e+00 5.10478079e-01 1.26157522e+00 5.15399575e-02
-4.58383083e-01 2.44207438e-02 -6.18347287e-01 8.96534801e-01
6.55202270e-01 -2.81495720e-01 -6.19194627e-01 -2.01005891e-01
-3.75441939e-01 1.26774803e-01 3.78344268e-01 -9.83931780e-01
3.43534946e-01 -2.94745028e-01 1.87112659e-01 -3.44937116e-01
2.49607906e-01 -4.31931615e-01 -1.92748651e-01 1.59334987e-01
-5.12267232e-01 -3.94391656e-01 1.05679706e-01 7.21859932e-01
-3.23091447e-01 -2.60802537e-01 7.99943209e-01 2.64220107e-02
-1.43103194e+00 5.65474868e-01 -1.35661006e-01 4.76744562e-01
1.12434721e+00 -4.04484272e-01 -2.80990630e-01 -3.73571694e-01
-7.52448499e-01 3.77171278e-01 4.86595005e-01 3.31880778e-01
6.33345187e-01 -1.10041296e+00 -3.12271357e-01 7.62186274e-02
1.31900072e-01 2.83456594e-01 6.60686255e-01 1.09778273e+00
-4.18162704e-01 6.38303012e-02 -1.93518959e-03 -7.98997819e-01
-1.24549270e+00 5.32607317e-01 1.26984686e-01 -5.91604374e-02
-8.55127692e-01 1.04037118e+00 7.42320895e-01 1.16061702e-01
4.34998393e-01 -4.31442350e-01 -2.90468663e-01 1.34902507e-01
3.96279752e-01 3.59974742e-01 -2.14326814e-01 -5.93843699e-01
-1.85809091e-01 6.59493625e-01 -4.67349067e-02 1.25628695e-01
1.22287714e+00 -2.08578125e-01 2.50014395e-01 4.74449664e-01
1.33797145e+00 -3.21716160e-01 -2.00090098e+00 -4.37969506e-01
1.84296742e-01 -5.49419999e-01 3.39699127e-02 -3.52514058e-01
-1.09738135e+00 8.05577517e-01 3.65560800e-01 -5.41859772e-03
1.39871478e+00 1.76031575e-01 1.12763059e+00 1.27511352e-01
1.99674577e-01 -1.25847208e+00 4.99740601e-01 5.45597494e-01
4.87705231e-01 -1.25823522e+00 -1.68650880e-01 -6.37646258e-01
-1.00968134e+00 8.32897067e-01 6.62759066e-01 -1.96247876e-01
6.09074354e-01 2.66785268e-02 -1.27398282e-01 -4.39215936e-02
-5.98616123e-01 -5.52777886e-01 5.16163290e-01 4.19538021e-01
1.49563298e-01 -7.89991990e-02 -1.63730606e-02 9.49223876e-01
5.92532754e-02 -3.56605574e-02 2.31612444e-01 9.50845242e-01
-5.78236938e-01 -7.29788959e-01 -4.99377623e-02 5.06102860e-01
-2.53153265e-01 -1.34118855e-01 -2.31644481e-01 5.27183175e-01
1.90203741e-01 9.93452132e-01 1.89066768e-01 -6.72651947e-01
2.27432296e-01 -3.17616276e-02 2.75128067e-01 -7.09626913e-01
-4.05770838e-01 4.04433489e-01 1.65077150e-02 -8.14483047e-01
-4.31594461e-01 -6.92925036e-01 -1.41575432e+00 -1.48916999e-02
-7.98647851e-02 2.70878691e-02 1.83511108e-01 1.01121998e+00
3.69781017e-01 5.64953029e-01 7.04466343e-01 -1.03065133e+00
-1.21197909e-01 -7.21301854e-01 -3.85001183e-01 7.93072045e-01
1.01896025e-01 -7.26547956e-01 -2.63838053e-01 5.39582968e-01] | [9.255255699157715, 0.5724532008171082] |
c54532bb-13fd-482b-a93a-fb481b38b402 | hlt-fbk-a-complete-temporal-processing-system | null | null | https://aclanthology.org/S15-2135 | https://aclanthology.org/S15-2135.pdf | HLT-FBK: a Complete Temporal Processing System for QA TempEval | null | ['Anne-Lyse Minard', 'Paramita Mirza'] | 2015-06-01 | null | null | null | semeval-2015-6 | ['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] | [-7.234249591827393, 3.82053279876709] |
847a50bd-9586-4c56-bfd0-a867d475c20e | deep-graph-learning-for-spatially-varying | 2202.06300 | null | https://arxiv.org/abs/2202.06300v1 | https://arxiv.org/pdf/2202.06300v1.pdf | Deep Graph Learning for Spatially-Varying Indoor Lighting Prediction | Lighting prediction from a single image is becoming increasingly important in many vision and augmented reality (AR) applications in which shading and shadow consistency between virtual and real objects should be guaranteed. However, this is a notoriously ill-posed problem, especially for indoor scenarios, because of the complexity of indoor luminaires and the limited information involved in 2D images. In this paper, we propose a graph learning-based framework for indoor lighting estimation. At its core is a new lighting model (dubbed DSGLight) based on depth-augmented Spherical Gaussians (SG) and a Graph Convolutional Network (GCN) that infers the new lighting representation from a single LDR image of limited field-of-view. Our lighting model builds 128 evenly distributed SGs over the indoor panorama, where each SG encoding the lighting and the depth around that node. The proposed GCN then learns the mapping from the input image to DSGLight. Compared with existing lighting models, our DSGLight encodes both direct lighting and indirect environmental lighting more faithfully and compactly. It also makes network training and inference more stable. The estimated depth distribution enables temporally stable shading and shadows under spatially-varying lighting. Through thorough experiments, we show that our method obviously outperforms existing methods both qualitatively and quantitatively. | ['Yanwen Guo', 'Yan Zhang', 'Piaopiao Yu', 'Shan Yang', 'Zhen He', 'Zhenyu Chen', 'Chenchen Wan', 'Jie Guo', 'Jiayang Bai'] | 2022-02-13 | null | null | null | null | ['lighting-estimation'] | ['computer-vision'] | [ 2.40644619e-01 -9.97194350e-02 4.64762568e-01 -5.01705706e-01
2.34287102e-02 -4.65576589e-01 4.19164449e-01 -4.57395732e-01
1.57036364e-01 7.08753228e-01 4.10072058e-02 -4.20575023e-01
3.35212201e-01 -1.00222993e+00 -7.91272223e-01 -8.84215355e-01
2.87718654e-01 1.00629412e-01 2.15347320e-01 8.10215324e-02
-1.97318688e-01 6.72537923e-01 -1.52940476e+00 -2.11409792e-01
8.51245761e-01 1.16933692e+00 7.43008196e-01 1.02894950e+00
-2.01922610e-01 6.82362974e-01 -2.56352603e-01 -1.62369087e-01
4.35288697e-01 -2.88363367e-01 -1.34749472e-01 3.63835752e-01
8.64323974e-01 -5.37118256e-01 -6.07075334e-01 9.29459333e-01
4.25530642e-01 3.97384346e-01 3.27382922e-01 -1.14012325e+00
-7.62281716e-01 -3.72077793e-01 -7.84569561e-01 -2.59677500e-01
3.13417614e-01 7.43471980e-02 6.04071796e-01 -6.92142606e-01
2.84113020e-01 1.14753735e+00 6.37799561e-01 4.08228159e-01
-9.50945139e-01 -5.57105839e-01 5.92440367e-01 -1.17737614e-01
-1.24608564e+00 -2.21828610e-01 1.04997766e+00 -1.26082554e-01
5.39029002e-01 3.63889277e-01 9.94795918e-01 7.48557627e-01
3.39278013e-01 4.06094879e-01 1.39274299e+00 -4.66854215e-01
3.33095580e-01 2.29796290e-01 -3.52757514e-01 1.07676899e+00
5.30854054e-02 1.19143479e-01 -4.56076831e-01 -5.79473078e-02
1.13816702e+00 2.82355785e-01 -7.20053673e-01 -6.08072698e-01
-8.30168426e-01 4.45110112e-01 8.14209521e-01 -2.98030078e-01
-1.52840331e-01 4.44517404e-01 -2.37193182e-01 -2.16664150e-01
6.46669328e-01 -2.55329788e-01 -3.42224777e-01 4.45718259e-01
-6.71573102e-01 -1.14260606e-01 6.32857442e-01 9.02522206e-01
1.03727686e+00 1.64911434e-01 2.44501829e-01 7.75356054e-01
9.49776232e-01 8.62224579e-01 -1.97371662e-01 -1.13297069e+00
1.72361717e-01 4.02959168e-01 4.67129052e-02 -1.12799263e+00
-2.02246666e-01 -4.11925197e-01 -9.54520047e-01 4.49522465e-01
4.98052202e-02 -1.26412392e-01 -1.06815612e+00 1.58792806e+00
6.38094544e-01 6.93684697e-01 -2.78397024e-01 8.91338408e-01
8.80743325e-01 7.97367930e-01 -4.50668037e-01 -2.28082776e-01
9.45732176e-01 -1.11585987e+00 -7.49701440e-01 -5.03765166e-01
-3.37785110e-02 -7.33971596e-01 1.28051615e+00 4.92104381e-01
-8.92490208e-01 -5.60636938e-01 -1.00052762e+00 -4.85665888e-01
-1.86307341e-01 2.71828882e-02 8.40255857e-01 7.96711147e-01
-1.48414528e+00 -1.84007846e-02 -6.63687527e-01 -2.83144444e-01
1.98454559e-01 1.67560890e-01 -1.88632533e-02 -5.89436412e-01
-7.55354345e-01 5.10382295e-01 -2.74837762e-01 5.74241519e-01
-8.84593666e-01 -4.75219756e-01 -1.09374392e+00 -1.16541214e-01
2.95018792e-01 -8.54509473e-01 8.75908971e-01 -5.86061060e-01
-1.77653027e+00 5.79043925e-01 -5.95250010e-01 4.86632623e-02
3.34338754e-01 -1.28866121e-01 -1.68764919e-01 -1.48026749e-01
-2.94195741e-01 3.00584495e-01 9.05586183e-01 -2.04450631e+00
-4.05113578e-01 -6.42109513e-01 2.47737616e-01 5.45787573e-01
-1.20721146e-01 -4.86280739e-01 -7.59416282e-01 -1.42203301e-01
3.75776768e-01 -8.40209007e-01 -4.34718698e-01 4.57638502e-01
-5.57415307e-01 3.17967176e-01 7.95993268e-01 -7.30232835e-01
9.06306267e-01 -1.95033205e+00 -1.56203389e-01 1.95589110e-01
2.92557418e-01 -1.20035872e-01 1.85181841e-01 9.66328457e-02
2.33767763e-01 -4.72190499e-01 -1.29933015e-01 -8.86343658e-01
-9.01684612e-02 5.93466878e-01 -4.37742710e-01 7.37573862e-01
-5.71179152e-01 8.23019087e-01 -9.86581326e-01 -4.27921802e-01
8.39576662e-01 1.04868758e+00 -2.96462536e-01 4.89840209e-01
-3.62148404e-01 7.74720192e-01 -1.71281502e-01 4.79345828e-01
1.03416574e+00 -2.26559594e-01 1.62223130e-01 -1.73371628e-01
-1.62256196e-01 -6.39132783e-02 -1.28584218e+00 1.88813972e+00
-1.00284302e+00 8.18547428e-01 1.17902972e-01 -3.10536265e-01
1.14324701e+00 -7.79254586e-02 7.49844238e-02 -7.12416708e-01
3.52813266e-02 -2.31538773e-01 -8.11407566e-01 -2.41337419e-01
4.55258876e-01 5.44389710e-02 4.48000133e-01 2.45121092e-01
-4.12493706e-01 -6.13708615e-01 -4.98979002e-01 1.05078094e-01
7.09605038e-01 4.56728935e-01 1.08840838e-01 1.56176034e-02
5.50899386e-01 -6.44350588e-01 5.51147044e-01 4.17457163e-01
1.41007170e-01 8.09687674e-01 -1.86205134e-01 -4.95588243e-01
-6.90825462e-01 -1.25473917e+00 4.36943099e-02 8.28993917e-01
4.61227924e-01 -1.19610235e-01 -5.78450799e-01 -4.50163692e-01
-1.47419974e-01 8.56260657e-01 -3.74430716e-01 2.94238091e-01
-4.33014750e-01 -3.59429866e-01 -2.61484444e-01 1.97288185e-01
7.79529929e-01 -5.02416372e-01 -5.04856706e-01 -3.20895314e-01
-1.14380337e-01 -1.27608931e+00 -4.04090345e-01 2.39621401e-02
-5.39983273e-01 -8.61831546e-01 -5.65375924e-01 -6.73138082e-01
8.91248345e-01 1.04672956e+00 1.24401474e+00 -5.54819219e-03
-3.81573439e-01 7.02096820e-01 1.05385669e-01 -4.90700305e-01
1.27419218e-01 -6.40628755e-01 -1.51287839e-01 2.01585546e-01
-8.59649479e-02 -6.89543962e-01 -9.82572854e-01 2.71344811e-01
-6.30613685e-01 5.16695440e-01 6.57092780e-02 3.43716860e-01
8.83487284e-01 4.26660866e-01 -2.64360636e-01 -8.18592191e-01
1.01672476e-02 -1.98027357e-01 -1.08493650e+00 3.07896733e-01
-5.63592911e-01 -4.79303420e-01 5.94124556e-01 4.85033654e-02
-1.50064337e+00 2.61144876e-01 6.78960308e-02 -6.28407836e-01
-1.66056246e-01 -2.79597402e-01 -5.14283955e-01 -4.39702302e-01
2.70270824e-01 2.35926583e-01 -3.45220447e-01 -2.70103455e-01
5.79888940e-01 5.14143050e-01 4.91629571e-01 -4.26728636e-01
9.18925941e-01 9.84461665e-01 3.33063483e-01 -1.15003371e+00
-9.95678365e-01 -3.86615694e-01 -5.01408756e-01 -6.07284009e-01
8.40040147e-01 -1.05795848e+00 -9.22915041e-01 5.58777690e-01
-1.16013944e+00 -8.41743290e-01 -1.71869084e-01 2.74021775e-01
-4.33632225e-01 3.81544799e-01 -3.98430288e-01 -1.22075510e+00
2.53157541e-02 -1.07186866e+00 1.39792061e+00 4.69194144e-01
4.06498551e-01 -1.40887403e+00 1.38688102e-01 4.35221732e-01
1.97913200e-01 5.10346293e-01 7.15674639e-01 6.97976649e-01
-1.05421507e+00 1.41474575e-01 -5.18938601e-01 5.75827599e-01
4.16068673e-01 -3.64972977e-03 -1.41596019e+00 -2.68521935e-01
2.27548480e-01 -4.34940355e-03 6.43831432e-01 7.12565660e-01
1.45661283e+00 -6.81786165e-02 -2.10596785e-01 1.11533868e+00
1.86173809e+00 1.03546277e-01 5.50340235e-01 3.42579111e-02
1.36600101e+00 5.88418543e-01 3.42572272e-01 3.40634227e-01
8.47408175e-01 5.51808596e-01 9.58374858e-01 -6.01732075e-01
-5.42691648e-01 -2.65247911e-01 1.34684190e-01 6.74080789e-01
-8.58752429e-02 -5.85555196e-01 -6.94987774e-01 1.31345525e-01
-1.66119385e+00 -4.10121709e-01 -3.74062091e-01 2.41450143e+00
5.71649492e-01 -1.58394709e-01 -5.46115875e-01 -1.91644773e-01
4.66623276e-01 4.63114083e-01 -6.98617697e-01 -3.51760060e-01
-2.00671300e-01 1.01315752e-01 5.79704463e-01 1.01178598e+00
-5.82502604e-01 6.85300529e-01 5.68468094e+00 2.95535833e-01
-9.74970579e-01 8.06583539e-02 8.20049822e-01 3.01244501e-02
-6.41975999e-01 -1.26139089e-01 -6.95256233e-01 4.67420906e-01
3.95086735e-01 3.82430315e-01 8.91395509e-01 7.80250609e-01
3.61963421e-01 -4.60464001e-01 -8.40045512e-01 1.18097651e+00
4.22580153e-01 -9.97763813e-01 -1.40024155e-01 2.34262049e-01
1.12195432e+00 1.64582446e-01 1.41616121e-01 -3.19886178e-01
5.66381752e-01 -9.76541519e-01 4.10644948e-01 7.02857196e-01
9.59041774e-01 -4.81789172e-01 3.63817692e-01 2.97778130e-01
-1.34092450e+00 1.52562529e-01 -5.46233177e-01 -9.29768011e-02
2.25603774e-01 8.56336415e-01 -8.06184411e-01 5.60017467e-01
7.12523639e-01 6.04333460e-01 -3.67059082e-01 8.20990503e-01
-7.47980237e-01 2.68624634e-01 -3.42653275e-01 1.59941077e-01
-1.06209047e-01 -6.12739027e-01 1.18389525e-01 9.03933167e-01
3.56472462e-01 8.39746371e-02 3.12797904e-01 7.78120577e-01
-8.50310922e-03 -3.48277450e-01 -7.75422394e-01 7.09922850e-01
3.14267069e-01 1.42702472e+00 -7.86336660e-01 -6.65895119e-02
-5.74789166e-01 1.24247336e+00 1.88425809e-01 9.23607826e-01
-7.63553143e-01 2.82751687e-04 6.76950336e-01 2.19609648e-01
7.82698542e-02 -5.69500625e-01 -3.62460971e-01 -1.06384468e+00
-1.27504364e-01 -2.30176196e-01 -2.01233819e-01 -1.29594064e+00
-1.04787433e+00 4.95302498e-01 -3.84905994e-01 -8.85592282e-01
3.08861285e-01 -5.68753183e-01 -6.45767927e-01 1.10112512e+00
-2.10972738e+00 -1.40132511e+00 -1.06325305e+00 8.87034118e-01
5.35488129e-01 4.77408022e-01 8.48616719e-01 1.51849732e-01
-4.12865609e-01 5.38548306e-02 2.35060677e-01 -2.25908816e-01
5.43388903e-01 -1.45656037e+00 4.78562981e-01 1.00398397e+00
1.99092403e-01 4.79285151e-01 7.48390794e-01 -6.28349721e-01
-1.59385049e+00 -1.27844775e+00 4.38396454e-01 -3.92402083e-01
3.29147846e-01 -7.31514692e-01 -6.44490182e-01 6.99698150e-01
2.30186656e-01 4.29185867e-01 4.14866030e-01 -1.24839902e-01
-1.91997647e-01 -4.12117749e-01 -9.82339859e-01 6.58039451e-01
1.18236220e+00 -5.82156658e-01 5.73915131e-02 7.67666638e-01
9.45122898e-01 -8.44373524e-01 -4.59016860e-01 1.07049070e-01
4.80714500e-01 -1.38259804e+00 1.15139914e+00 4.55808789e-01
1.61713347e-01 -6.08120978e-01 -5.75381458e-01 -1.32585490e+00
-1.30364776e-01 -5.61709940e-01 -3.71405929e-01 1.05857980e+00
-1.58802748e-01 -8.17177653e-01 8.80046129e-01 6.83465838e-01
-2.63548076e-01 -8.22171986e-01 -5.99801660e-01 -3.65587234e-01
-7.27755249e-01 -5.39103508e-01 7.38440692e-01 7.18989134e-01
-9.66325760e-01 2.81200945e-01 -4.34133530e-01 7.84803629e-01
1.19818020e+00 3.30119371e-01 1.08208621e+00 -1.08533049e+00
-4.64534134e-01 1.57099694e-01 -1.17294766e-01 -1.39616060e+00
7.13931844e-02 -4.12497014e-01 3.55308682e-01 -2.12253213e+00
3.11558489e-02 -6.46106720e-01 -2.51040682e-02 1.17253706e-01
-2.50555456e-01 4.05572146e-01 -1.23034820e-01 -1.10229522e-01
-5.08191526e-01 6.26266241e-01 1.52231538e+00 1.65025815e-01
-2.53598154e-01 1.89090550e-01 -3.21329027e-01 9.20837045e-01
5.94492733e-01 9.60141122e-02 -9.16484237e-01 -8.45504761e-01
4.75200027e-01 -1.06743686e-01 5.55431426e-01 -8.39982748e-01
2.08127901e-01 -2.69838005e-01 6.91582739e-01 -8.05911839e-01
7.79621959e-01 -1.14608276e+00 4.28418875e-01 9.47910026e-02
2.27519110e-01 -2.80963063e-01 -6.41686097e-02 8.78559589e-01
2.52772212e-01 2.13533178e-01 6.00360215e-01 -2.82570809e-01
-6.68302298e-01 6.79012477e-01 3.86429846e-01 -4.92139399e-01
9.77897227e-01 -4.60844308e-01 -3.51299912e-01 -5.80254674e-01
-2.72413075e-01 1.60257235e-01 9.22018111e-01 5.46069965e-02
9.43126857e-01 -1.20952845e+00 -2.02464163e-01 5.77610970e-01
8.15058779e-03 6.78831875e-01 4.61367428e-01 4.06104952e-01
-7.21412182e-01 2.62681961e-01 3.70524198e-01 -7.23702371e-01
-1.29730928e+00 3.89130950e-01 2.73804843e-01 8.34037140e-02
-7.59912014e-01 1.11309111e+00 8.59855771e-01 -6.33721828e-01
4.25933778e-01 -4.70769882e-01 1.13444775e-01 -5.39242566e-01
4.80075359e-01 4.02179867e-01 -6.29446730e-02 -6.34044468e-01
-3.06076016e-02 8.45306039e-01 4.71960098e-01 1.44208804e-01
1.32522261e+00 -8.54439557e-01 -4.91431326e-01 6.94943547e-01
1.08795929e+00 2.61545271e-01 -1.80226755e+00 -3.08702081e-01
-9.37677920e-01 -1.02097976e+00 5.17596006e-01 -6.74985290e-01
-1.20446539e+00 9.52318609e-01 5.68637311e-01 1.49429873e-01
1.36684108e+00 -1.54196903e-01 9.07109201e-01 1.04827583e-01
6.92822814e-01 -7.91709483e-01 5.24837375e-02 3.11684996e-01
6.03797376e-01 -1.18093216e+00 1.48794621e-01 -6.95410073e-01
-3.07476401e-01 1.03097415e+00 6.50645375e-01 4.41774279e-02
6.95872068e-01 2.79391617e-01 1.32232547e-01 -2.23014370e-01
-3.51746172e-01 -2.14418508e-02 2.75762707e-01 8.63405764e-01
1.05924979e-01 1.64104834e-01 6.10909104e-01 -1.43806338e-01
-2.19048977e-01 -2.24988356e-01 4.20836598e-01 5.65665364e-01
-4.28595275e-01 -6.78538382e-01 -5.39152682e-01 2.27020174e-01
1.17959440e-01 -1.16125308e-01 -2.37339782e-03 4.25369501e-01
3.54548365e-01 9.85513926e-01 6.53815828e-03 -1.87442750e-01
4.58981842e-02 -5.60954094e-01 6.60042405e-01 -6.87844634e-01
1.59916744e-01 1.56503022e-01 -3.05510670e-01 -8.38199973e-01
-4.68568206e-01 -3.61622602e-01 -1.17164874e+00 -2.99505979e-01
-4.23086971e-01 -3.03144723e-01 1.24775827e+00 6.28969371e-01
1.00788668e-01 7.32567072e-01 1.03806162e+00 -1.09500384e+00
3.49904835e-01 -2.75844187e-01 -9.27089095e-01 -2.32389793e-01
6.86341107e-01 -5.48103511e-01 -5.04021704e-01 3.14414278e-02] | [9.790523529052734, -2.9688525199890137] |
14374aba-1952-4097-8ef3-5b30a2f4216d | high-dimensional-mr-reconstruction | 2306.08630 | null | https://arxiv.org/abs/2306.08630v2 | https://arxiv.org/pdf/2306.08630v2.pdf | High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models | We present a novel method that integrates subspace modeling with an adaptive generative image prior for high-dimensional MR image reconstruction. The subspace model imposes an explicit low-dimensional representation of the high-dimensional images, while the generative image prior serves as a spatial constraint on the "contrast-weighted" images or the spatial coefficients of the subspace model. A formulation was introduced to synergize these two components with complimentary regularization such as joint sparsity. A special pretraining plus subject-specific network adaptation strategy was proposed to construct an accurate generative-model-based representation for images with varying contrasts, validated by experimental data. An iterative algorithm was introduced to jointly update the subspace coefficients and the multiresolution latent space of the generative image model that leveraged a recently developed intermediate layer optimization technique for network inversion. We evaluated the utility of the proposed method in two high-dimensional imaging applications: accelerated MR parameter mapping and high-resolution MRSI. Improved performance over state-of-the-art subspace-based methods was demonstrated in both cases. Our work demonstrated the potential of integrating data-driven and adaptive generative models with low-dimensional representation for high-dimensional imaging problems. | ['Fan Lam', 'Mark A. Anastasio', 'Varun A. Kelkar', 'Xi Peng', 'Ruiyang Zhao'] | 2023-06-14 | null | null | null | null | ['image-reconstruction'] | ['computer-vision'] | [ 4.94135559e-01 -3.00186984e-02 8.37088749e-02 -5.42473733e-01
-9.85077322e-01 -2.11251587e-01 5.17332017e-01 -5.75878084e-01
-5.49761593e-01 6.60843015e-01 4.96137142e-01 2.40069535e-02
-4.46520954e-01 -2.10328013e-01 -4.83977139e-01 -1.12165701e+00
-9.78881046e-02 5.59996367e-01 6.98855985e-03 6.19830340e-02
9.77432281e-02 7.08664417e-01 -1.05653775e+00 2.84907281e-01
8.97665143e-01 5.86909533e-01 5.47299147e-01 4.57693875e-01
2.85709798e-01 4.60516691e-01 1.86959337e-02 4.12153751e-01
2.29739890e-01 -4.95842546e-01 -5.04649520e-01 2.83391207e-01
2.92683601e-01 -4.03512746e-01 -5.69729209e-01 9.76936638e-01
8.97385657e-01 2.51993656e-01 8.36590111e-01 -5.93969941e-01
-4.81964082e-01 3.54866207e-01 -4.96970117e-01 5.16517639e-01
-4.84222025e-02 1.07784167e-01 3.59555304e-01 -1.05178165e+00
1.00283003e+00 8.12096357e-01 4.86060500e-01 3.53683501e-01
-1.85499024e+00 -4.51688349e-01 -5.11283390e-02 1.23210311e-01
-1.40086114e+00 -5.47488332e-01 1.15025723e+00 -8.08818817e-01
1.00315654e+00 1.58126861e-01 6.45017445e-01 9.73176122e-01
4.60392356e-01 4.42624450e-01 1.55280662e+00 -3.56444389e-01
1.61254540e-01 -1.16097480e-02 8.93453956e-02 5.88688970e-01
-4.90551032e-02 2.59857655e-01 -5.39217114e-01 -4.64475095e-01
1.27641654e+00 -1.46969333e-01 -5.22444844e-01 -1.04385412e+00
-1.34624970e+00 9.39820290e-01 4.17675793e-01 5.24958134e-01
-8.44814181e-01 -7.54147619e-02 2.06366435e-01 -1.43692419e-01
5.90531230e-01 3.79971325e-01 2.51326174e-01 3.42620790e-01
-1.41336107e+00 8.13040897e-05 4.97985631e-01 5.25834620e-01
3.89188170e-01 4.17931348e-01 -3.97413969e-01 9.13427114e-01
5.91949046e-01 3.82539958e-01 6.81730509e-01 -1.14147508e+00
6.25806376e-02 7.32509419e-02 -9.34648365e-02 -8.63965511e-01
-5.87905526e-01 -1.03638995e+00 -1.14116132e+00 3.70315537e-02
3.99585627e-02 8.28651562e-02 -1.16305578e+00 1.96940291e+00
4.13874775e-01 5.22557735e-01 -1.35041013e-01 1.26998782e+00
5.22410631e-01 4.25560504e-01 -1.21372916e-01 -5.52261412e-01
1.04045451e+00 -5.85042119e-01 -8.90104592e-01 1.97393335e-02
3.01903993e-01 -6.18031681e-01 6.97660744e-01 7.18723536e-02
-1.45551729e+00 -2.72660255e-01 -1.14580476e+00 1.53357804e-01
1.84583738e-01 2.92506069e-01 4.98250932e-01 5.32362878e-01
-1.34152663e+00 4.17608291e-01 -1.20482004e+00 -9.14351940e-02
2.31937453e-01 6.01250708e-01 -2.60706306e-01 -1.57840580e-01
-9.89481390e-01 9.14061844e-01 2.00504914e-01 2.62039423e-01
-1.22704732e+00 -9.34471607e-01 -8.08721364e-01 -1.32885039e-01
-6.79665282e-02 -1.12661159e+00 6.08197987e-01 -4.31546986e-01
-1.53416121e+00 8.84041011e-01 -2.26665899e-01 -4.02319580e-01
4.75926101e-01 -9.68919322e-02 -2.95353144e-01 6.59724891e-01
1.20684654e-01 5.77873468e-01 1.19040430e+00 -1.35816622e+00
3.81928653e-01 -5.04185081e-01 -6.64639056e-01 5.36342859e-01
-9.19420198e-02 -1.56772584e-01 -3.52301806e-01 -7.67529726e-01
8.54228079e-01 -1.05005670e+00 -5.22456110e-01 -3.26108038e-01
-2.09276080e-01 7.96835780e-01 5.53867996e-01 -9.87224281e-01
1.04057467e+00 -2.03981519e+00 6.51530683e-01 5.40355563e-01
4.82499421e-01 4.99420054e-03 -7.05405399e-02 9.61934030e-02
-5.64056635e-01 -5.40329635e-01 -5.47489643e-01 -2.98193783e-01
-3.57042462e-01 1.75951272e-01 -1.32770643e-01 8.48351955e-01
-8.32249522e-02 7.33247280e-01 -8.04803610e-01 -2.95880169e-01
3.41491759e-01 1.16523850e+00 -9.09506500e-01 3.71360749e-01
2.22882271e-01 1.14032769e+00 -3.39739114e-01 7.33208656e-03
7.07748592e-01 -4.96919245e-01 5.11710286e-01 -8.20600808e-01
-1.36636779e-01 -2.69160923e-02 -1.21430552e+00 2.30405760e+00
-2.37150759e-01 8.83414447e-02 5.15636146e-01 -1.15016603e+00
6.70668542e-01 4.65735734e-01 1.01616919e+00 -5.07804096e-01
1.13717532e-02 3.14119071e-01 1.23853840e-01 -4.90408212e-01
2.91049063e-01 -4.41849768e-01 3.52688223e-01 4.09610301e-01
3.49455923e-01 -1.15558863e-01 -9.76010635e-02 2.38273889e-01
7.43062615e-01 5.14144957e-01 2.69363225e-02 -6.82819426e-01
6.83700979e-01 -2.62570679e-01 3.11240315e-01 7.14668989e-01
-4.46507484e-02 7.66777396e-01 1.83724374e-01 -2.17965141e-01
-1.23242378e+00 -1.04667282e+00 -4.71030891e-01 6.58949673e-01
-2.15175569e-01 4.03604209e-02 -8.30809116e-01 -1.20884813e-01
-4.13721949e-01 6.27323389e-01 -5.44861913e-01 -1.57817185e-01
-7.83869088e-01 -1.32154143e+00 1.02870315e-01 1.65359586e-01
3.18157107e-01 -5.31838775e-01 -3.58793259e-01 5.10020256e-01
-2.87095934e-01 -1.17222750e+00 -4.80048805e-01 3.47555518e-01
-1.23082757e+00 -7.30033398e-01 -1.11988163e+00 -6.54283047e-01
9.87681448e-01 1.49573296e-01 8.33731472e-01 -4.29562330e-01
-3.78612757e-01 6.53222024e-01 2.16423661e-01 3.68283302e-01
-4.74630713e-01 -1.75091341e-01 2.11165577e-01 1.71908662e-01
-3.08405042e-01 -1.16686010e+00 -8.63535762e-01 2.36130804e-01
-1.06020463e+00 3.36269021e-01 7.93033600e-01 1.23216403e+00
9.00080681e-01 -3.90476912e-01 5.08717656e-01 -8.00459504e-01
4.69149113e-01 -4.96094167e-01 -4.06916171e-01 7.75594041e-02
-6.01408303e-01 4.80841637e-01 1.84828162e-01 -5.66521943e-01
-1.22646654e+00 2.88751006e-01 -1.90649152e-01 -6.20652437e-01
3.75394002e-02 6.16636753e-01 1.75677761e-02 -3.87401700e-01
5.94613194e-01 7.04416335e-01 3.80412966e-01 -4.64823544e-01
3.69311035e-01 1.93964601e-01 8.04703832e-01 -7.59160221e-01
6.32093370e-01 7.08442748e-01 2.71400869e-01 -8.98401260e-01
-5.20907938e-01 -5.28784633e-01 -1.02343285e+00 -9.79768410e-02
1.05719995e+00 -1.08640981e+00 -1.86735511e-01 4.33171064e-01
-9.17823315e-01 -1.31167307e-01 -2.03985140e-01 1.07372725e+00
-9.34891880e-01 6.41765773e-01 -7.30203986e-01 -4.06912148e-01
-4.57767665e-01 -1.56512320e+00 8.72423708e-01 -3.69337738e-01
-5.40152527e-02 -1.04819000e+00 3.10242206e-01 3.86788577e-01
7.29806483e-01 1.96654037e-01 1.18665671e+00 -4.10052925e-01
-6.94588244e-01 5.51395826e-02 -1.60324082e-01 2.97237307e-01
-1.94741815e-01 -7.86236227e-01 -7.83062398e-01 -4.97423142e-01
5.84231794e-01 -5.75597696e-02 7.85785139e-01 1.05817497e+00
8.94601405e-01 6.42190799e-02 -1.40291229e-01 1.08506846e+00
1.47758424e+00 -4.41929363e-02 6.83412254e-01 6.66479096e-02
7.60667264e-01 2.22587436e-01 -1.58805656e-03 3.21097046e-01
1.55995950e-01 1.02756691e+00 2.11971235e-02 -3.09385449e-01
-4.31689441e-01 -7.35491663e-02 9.26642716e-02 1.26315117e+00
-2.16678753e-01 4.95223790e-01 -7.98376679e-01 3.61019909e-01
-1.73351550e+00 -8.34300995e-01 1.33087426e-01 2.10957289e+00
6.96624339e-01 -1.99648306e-01 -4.98277321e-02 -2.88688958e-01
6.44326866e-01 1.77639589e-01 -7.50723958e-01 2.64251530e-01
-1.01865113e-01 4.67674956e-02 2.63114691e-01 6.03206038e-01
-9.28716898e-01 5.90697587e-01 7.29211712e+00 6.61975265e-01
-1.15489852e+00 5.60156226e-01 4.81312126e-01 -1.36840314e-01
-5.44974566e-01 -6.12127297e-02 -5.57429254e-01 2.01116949e-01
8.36425841e-01 7.45850801e-02 4.98430669e-01 3.88697505e-01
4.99126613e-01 6.18623495e-02 -8.61174345e-01 1.03880847e+00
2.92181045e-01 -1.56108916e+00 5.61320744e-02 1.81366518e-01
8.05624306e-01 2.52597183e-01 2.38442197e-01 -1.00789055e-01
-1.76497430e-01 -8.42982113e-01 4.74986345e-01 7.95093358e-01
9.87489104e-01 -3.31784397e-01 3.81446004e-01 2.64019698e-01
-7.27470338e-01 2.78204113e-01 -1.48873851e-01 4.92860943e-01
4.23343420e-01 4.93301183e-01 -6.87472284e-01 4.31017250e-01
2.94688642e-01 6.04680419e-01 -1.94923833e-01 8.39259803e-01
4.69256639e-02 3.24140817e-01 -2.98246443e-01 8.05440128e-01
2.33442888e-01 -6.05304480e-01 1.02969122e+00 1.14106560e+00
3.31893981e-01 4.18018073e-01 1.52426079e-01 1.24267161e+00
3.65726739e-01 2.13910714e-02 -4.54538137e-01 2.48724088e-01
-4.76932124e-04 1.41976690e+00 -6.81282461e-01 -2.03430548e-01
-1.73304468e-01 8.18809807e-01 1.16117455e-01 8.85872781e-01
-6.91694140e-01 4.66403723e-01 8.42287168e-02 5.03547013e-01
4.36098009e-01 -6.75492048e-01 -1.81212649e-01 -1.46301842e+00
-2.89400846e-01 -6.99673831e-01 1.94089055e-01 -8.55536103e-01
-9.24128294e-01 7.43692100e-01 3.66855383e-01 -1.05383754e+00
-6.13323927e-01 -2.48175874e-01 -2.93125719e-01 1.29437399e+00
-1.58702397e+00 -1.24836409e+00 -9.73696634e-02 7.98298359e-01
1.08362868e-01 -3.89582336e-01 9.26525056e-01 4.48564470e-01
-4.75537688e-01 1.86751112e-01 3.93922031e-01 -3.71433884e-01
4.73010182e-01 -9.14073348e-01 -3.91166717e-01 9.72778738e-01
-1.78815365e-01 9.00932372e-01 6.98519766e-01 -7.07182646e-01
-1.46063709e+00 -6.61258757e-01 2.19701990e-01 7.80751705e-02
5.76294482e-01 -2.53620476e-01 -9.60229456e-01 6.51577890e-01
7.87154511e-02 1.49534091e-01 9.15555060e-01 -2.09563687e-01
2.07003821e-02 1.59531161e-01 -1.23381174e+00 3.61503273e-01
8.68452489e-01 -6.87936425e-01 -4.62655813e-01 3.80674303e-01
2.96282589e-01 -6.79606974e-01 -1.19876456e+00 3.58175486e-01
4.30716783e-01 -8.52120519e-01 1.33000076e+00 -4.35122252e-01
1.80976734e-01 -3.53072017e-01 -3.17059726e-01 -1.32403266e+00
-7.36065626e-01 -6.59410894e-01 -4.20457184e-01 5.42128563e-01
1.69855535e-01 -4.10158962e-01 7.58659065e-01 6.77360773e-01
-5.12346208e-01 -6.42767072e-01 -1.10269237e+00 -4.73156333e-01
-2.60427035e-02 -3.11328053e-01 7.68695772e-03 9.10352170e-01
-3.47546905e-01 3.58309358e-01 -5.21447778e-01 4.40107852e-01
1.15695262e+00 1.41065670e-02 1.76495329e-01 -6.34233236e-01
-5.24693668e-01 -1.68851867e-01 -3.57331604e-01 -8.83453906e-01
2.91544914e-01 -1.29880095e+00 -2.75558650e-01 -1.32148087e+00
6.00416303e-01 -3.57855737e-01 -5.43581247e-01 1.05592117e-01
1.29736692e-01 2.00787500e-01 -9.72338673e-03 6.08864188e-01
-1.53470784e-01 6.99831426e-01 1.47083497e+00 2.12517738e-01
-2.82424271e-01 -2.91118354e-01 -4.85609770e-01 4.31254506e-01
2.67342955e-01 -4.14808333e-01 -7.07136929e-01 -3.82421464e-01
-6.22603446e-02 4.06254232e-01 5.90540290e-01 -1.01269579e+00
3.28005910e-01 2.73628473e-01 6.37443602e-01 -4.80049491e-01
6.12291038e-01 -8.21769536e-01 6.02546573e-01 4.52719897e-01
-4.20152456e-01 -3.39576960e-01 1.08571038e-01 4.83335942e-01
-1.31113708e-01 2.77287252e-02 1.18560433e+00 -1.33637100e-01
-4.63890702e-01 3.12859863e-01 -1.50401339e-01 -2.56570160e-01
6.18497431e-01 -2.39682019e-01 2.49008283e-01 -3.55300337e-01
-1.47156441e+00 -2.32463524e-01 2.18711257e-01 -8.97638202e-02
9.48681831e-01 -1.44322431e+00 -8.60771060e-01 6.72714293e-01
-3.42087626e-01 -3.31038564e-01 7.81534016e-01 1.57299054e+00
-2.77038693e-01 4.71956879e-01 -5.85641980e-01 -1.03081012e+00
-8.52981746e-01 3.88409644e-01 7.15027630e-01 -7.07712173e-01
-9.32256401e-01 5.26440442e-01 4.43086296e-01 -4.31843668e-01
-6.57769293e-02 -9.24393535e-03 -1.88340291e-01 -2.08980456e-01
2.96872497e-01 1.81949705e-01 3.75464186e-02 -9.92652237e-01
-2.81620830e-01 6.03855729e-01 -1.90051094e-01 -4.86223966e-01
1.78442430e+00 -3.84532779e-01 -9.17363614e-02 2.55063891e-01
1.26497555e+00 -4.60723221e-01 -1.48486233e+00 -5.23908913e-01
-4.33616340e-01 -2.25541234e-01 8.12728226e-01 -7.72525907e-01
-9.54930842e-01 7.71853507e-01 1.02507150e+00 -5.25654197e-01
1.15467930e+00 -2.76690960e-01 4.89241034e-01 -1.87808033e-02
4.21586901e-01 -8.53939950e-01 -4.26463000e-02 3.00048769e-01
1.23208177e+00 -1.03181267e+00 3.79679054e-01 -4.71216530e-01
-5.62967122e-01 8.49239886e-01 1.75176486e-02 -1.87851816e-01
7.08199322e-01 2.45307311e-01 -1.05044015e-01 -5.39717376e-01
-3.66287887e-01 2.55220175e-01 8.99652898e-01 6.14199936e-01
6.35344267e-01 -1.59294173e-01 -3.44488710e-01 2.86240637e-01
2.98354626e-01 1.56798750e-01 1.96614683e-01 7.01814055e-01
-2.73716860e-02 -1.02853429e+00 -5.53707063e-01 3.27175975e-01
-2.72364229e-01 -2.14330733e-01 3.78498763e-01 5.42951226e-01
-2.48076409e-01 1.52475923e-01 -1.55004695e-01 1.63657293e-01
1.77226868e-02 2.20088363e-01 9.46944356e-01 -5.18071294e-01
-2.32909858e-01 8.97139907e-01 -8.67294446e-02 -6.92202747e-01
-6.41317546e-01 -8.79382670e-01 -1.10104215e+00 3.55969250e-01
-4.97329757e-02 -2.17297785e-02 9.55118239e-01 7.63005376e-01
5.20936251e-01 5.88468790e-01 4.92274493e-01 -1.27437282e+00
-5.08741021e-01 -8.53927553e-01 -7.87651420e-01 3.08499157e-01
1.23456605e-01 -7.52944589e-01 -1.71652883e-01 -2.67746784e-02] | [13.50711441040039, -2.388105630874634] |
c49b3094-3dd7-4b77-9da0-39f0a1b6224c | estimating-mutual-information-for-discrete | 1709.06212 | null | http://arxiv.org/abs/1709.06212v3 | http://arxiv.org/pdf/1709.06212v3.pdf | Estimating Mutual Information for Discrete-Continuous Mixtures | Estimating mutual information from observed samples is a basic primitive,
useful in several machine learning tasks including correlation mining,
information bottleneck clustering, learning a Chow-Liu tree, and conditional
independence testing in (causal) graphical models. While mutual information is
a well-defined quantity in general probability spaces, existing estimators can
only handle two special cases of purely discrete or purely continuous pairs of
random variables. The main challenge is that these methods first estimate the
(differential) entropies of X, Y and the pair (X;Y) and add them up with
appropriate signs to get an estimate of the mutual information. These
3H-estimators cannot be applied in general mixture spaces, where entropy is not
well-defined. In this paper, we design a novel estimator for mutual information
of discrete-continuous mixtures. We prove that the proposed estimator is
consistent. We provide numerical experiments suggesting superiority of the
proposed estimator compared to other heuristics of adding small continuous
noise to all the samples and applying standard estimators tailored for purely
continuous variables, and quantizing the samples and applying standard
estimators tailored for purely discrete variables. This significantly widens
the applicability of mutual information estimation in real-world applications,
where some variables are discrete, some continuous, and others are a mixture
between continuous and discrete components. | ['Sreeram Kannan', 'Sewoong Oh', 'Pramod Viswanath', 'Weihao Gao'] | 2017-09-19 | estimating-mutual-information-for-discrete-1 | http://papers.nips.cc/paper/7180-estimating-mutual-information-for-discrete-continuous-mixtures | http://papers.nips.cc/paper/7180-estimating-mutual-information-for-discrete-continuous-mixtures.pdf | neurips-2017-12 | ['mutual-information-estimation'] | ['methodology'] | [ 1.33348271e-01 -8.67889747e-02 -3.59577328e-01 -3.13615829e-01
-6.53646469e-01 -3.27988416e-01 5.43087900e-01 3.22748482e-01
-2.65531898e-01 1.10219204e+00 -2.02837989e-01 -4.10085827e-01
-7.13345528e-01 -7.77625382e-01 -4.20400977e-01 -9.94658351e-01
-5.74579298e-01 8.03163767e-01 7.88013265e-02 3.75614077e-01
1.05740957e-01 4.02403772e-01 -1.48301983e+00 -6.74817383e-01
1.17279112e+00 7.51142383e-01 -7.81601574e-03 8.99138093e-01
-9.52268671e-03 5.46893835e-01 -5.67161143e-01 -3.52732480e-01
7.27037564e-02 -9.23984230e-01 -6.10426784e-01 2.40972731e-02
-1.50557443e-01 3.20485272e-02 1.02668263e-01 1.30261540e+00
2.14661226e-01 1.45843774e-01 1.41820323e+00 -1.65164959e+00
-3.96767080e-01 9.35766578e-01 -1.12021208e+00 -1.20501049e-01
2.75636911e-01 -3.94061834e-01 1.15647030e+00 -3.31436068e-01
1.84001148e-01 1.24297857e+00 6.31728649e-01 1.10797718e-01
-1.28324234e+00 -7.97501564e-01 -8.51242244e-02 1.68368518e-01
-1.52736473e+00 -1.89473256e-01 6.43066406e-01 -4.33751464e-01
3.06006730e-01 6.02159023e-01 4.91611689e-01 6.47425890e-01
1.02413416e-01 7.66782045e-01 1.22043884e+00 -5.15179455e-01
4.63098377e-01 3.48897249e-01 2.72020608e-01 3.39645982e-01
6.66321695e-01 1.05093420e-02 -7.74497837e-02 -5.79215467e-01
6.58862710e-01 2.55659193e-01 -2.15490282e-01 -6.03607357e-01
-9.63318944e-01 8.80852044e-01 -1.04044348e-01 4.80712354e-01
-2.45444894e-01 3.66839692e-02 -8.12972635e-02 3.50975543e-01
3.06204379e-01 2.90686227e-02 -3.90277356e-01 -1.29821762e-01
-9.59998548e-01 1.56235009e-01 1.37169337e+00 1.14946043e+00
7.19172418e-01 -3.49951208e-01 9.78557244e-02 7.01797783e-01
5.61295450e-01 7.56236732e-01 1.81618631e-01 -7.29408205e-01
3.59325975e-01 2.54366606e-01 1.35276034e-01 -8.95209610e-01
-3.11512560e-01 -3.46351206e-01 -1.23163271e+00 -4.37293313e-02
7.73267269e-01 -3.91110629e-01 -4.94867444e-01 1.91390574e+00
3.29673350e-01 2.26878256e-01 -1.09551184e-01 5.73526502e-01
3.17649543e-01 4.59065855e-01 -1.19404860e-01 -6.45618498e-01
1.07028699e+00 -4.32982445e-01 -7.44234443e-01 -4.55477014e-02
3.65912676e-01 -7.32391953e-01 3.86175454e-01 2.58120924e-01
-9.40273166e-01 -2.44789831e-02 -9.23404038e-01 5.19487381e-01
-1.94840044e-01 -7.93165267e-02 7.30582416e-01 8.81317735e-01
-7.16566205e-01 6.79840446e-01 -7.19346762e-01 -2.51768053e-01
7.87865967e-02 4.03881967e-01 -3.31690937e-01 -1.51875447e-02
-1.14650309e+00 5.01240253e-01 1.67249098e-01 -7.38609657e-02
-2.90531546e-01 -3.62940997e-01 -7.72995651e-01 1.67503625e-01
3.59103471e-01 -6.04632258e-01 9.53299344e-01 -5.98161578e-01
-1.32159007e+00 3.20987284e-01 -1.31695896e-01 -3.29487711e-01
6.29811943e-01 8.38401541e-02 -4.01361674e-01 -2.17774600e-01
1.68531194e-01 -5.23349121e-02 6.61542535e-01 -1.09953296e+00
-5.41189611e-01 -5.26112974e-01 -3.66033345e-01 1.79130107e-01
-4.72228089e-03 -1.97173506e-01 -2.91551471e-01 -4.01114166e-01
3.63150597e-01 -6.89088583e-01 -4.93882060e-01 -2.20584244e-01
-6.93114400e-01 -5.99678904e-02 5.98779023e-01 -3.79462898e-01
1.07169545e+00 -2.14267278e+00 -1.02451012e-01 5.67702413e-01
2.14488178e-01 -4.24961150e-01 2.03386232e-01 4.93028849e-01
-1.38683885e-01 1.99694261e-01 -6.26397073e-01 -1.36847615e-01
9.94861647e-02 9.30623803e-03 3.69914502e-01 9.00845885e-01
1.02892451e-01 2.04001054e-01 -1.06535518e+00 -7.04132557e-01
2.61559635e-01 2.92608172e-01 -4.35731709e-01 2.06760392e-01
6.23115264e-02 4.38071907e-01 -3.68046314e-01 3.37755829e-01
9.71864641e-01 -3.75223309e-01 3.81229132e-01 3.18353504e-01
6.24546669e-02 -2.05215588e-02 -1.80678201e+00 9.05519426e-01
-3.32123816e-01 6.72122896e-01 6.26863837e-02 -1.20817113e+00
8.82828116e-01 2.60859162e-01 7.61086881e-01 2.89182924e-02
3.76308233e-01 6.71274364e-02 2.73839384e-01 -2.43652612e-01
9.96693894e-02 -5.19651055e-01 -2.07813323e-01 4.54314739e-01
-3.60519439e-02 -2.10325137e-01 3.24576378e-01 2.45184451e-01
1.20918548e+00 -5.52432418e-01 9.05263722e-01 -3.01814705e-01
4.45559502e-01 -7.78288484e-01 4.65858459e-01 1.05051696e+00
-4.91753444e-02 4.88975286e-01 9.66629624e-01 6.28871202e-01
-7.63330519e-01 -1.27251697e+00 -3.85268033e-01 5.50392866e-01
3.24935615e-01 -2.76257902e-01 -5.46257436e-01 -4.49072987e-01
4.01088372e-02 7.43213832e-01 -6.05156362e-01 -3.24722230e-02
2.14381725e-01 -1.02524495e+00 2.03311518e-01 1.56771153e-01
4.57771182e-01 -3.54478300e-01 -1.91095442e-01 1.03695050e-01
-1.40615270e-01 -7.16398954e-01 -3.14726889e-01 5.46932697e-01
-8.05103183e-01 -1.32298446e+00 -7.42975414e-01 -4.61258709e-01
4.70856905e-01 1.50744483e-01 9.18272913e-01 -2.24354923e-01
-8.11805576e-02 2.03742102e-01 -1.42618790e-01 -2.11526155e-01
-4.46921766e-01 -1.91963136e-01 -6.93624169e-02 7.55035430e-02
3.40477884e-01 -6.74856365e-01 -3.99077117e-01 6.54372036e-01
-7.84244955e-01 -3.24532032e-01 7.16347754e-01 9.45545256e-01
2.69157946e-01 6.41212523e-01 4.89272267e-01 -8.95696402e-01
5.59206963e-01 -9.31653857e-01 -6.06167138e-01 2.09628254e-01
-5.02189398e-01 3.18533480e-01 4.30333406e-01 -5.34545660e-01
-9.97203350e-01 7.42368354e-03 1.84790969e-01 -3.93454470e-02
-2.71137685e-01 5.64637303e-01 -5.11189580e-01 2.77614176e-01
1.69254541e-01 -1.26493797e-01 -2.75354311e-02 -4.68479514e-01
3.77020478e-01 8.54066432e-01 4.34211344e-01 -4.13373053e-01
5.64932168e-01 2.30302989e-01 4.49660838e-01 -9.91166115e-01
-4.03722942e-01 -7.99078047e-01 -6.09386802e-01 5.75803705e-02
6.39438927e-01 -4.49229866e-01 -9.61350679e-01 3.78321290e-01
-8.03767920e-01 -5.08919396e-02 -1.78658977e-01 8.78127515e-01
-5.66682100e-01 5.93869865e-01 -3.91216218e-01 -1.48361778e+00
2.20053986e-01 -9.16550636e-01 8.03784609e-01 2.89348692e-01
-3.18572372e-01 -1.36742270e+00 2.53427386e-01 -3.42817269e-02
7.12265223e-02 1.14989214e-01 8.32412004e-01 -1.00047493e+00
-2.14796096e-01 -6.03511274e-01 -1.97595671e-01 9.96422619e-02
3.00097883e-01 3.61173511e-01 -4.30129230e-01 -1.52154816e-02
1.13220677e-01 1.07153296e-01 8.45358729e-01 7.80224919e-01
9.99985576e-01 -4.66825455e-01 -6.75653458e-01 1.64574757e-01
1.24060977e+00 2.28712648e-01 4.34771270e-01 -1.67303935e-01
3.19394261e-01 5.12929320e-01 6.01007640e-01 8.97831917e-01
3.00950140e-01 3.86936516e-01 2.40470991e-01 -4.01298096e-03
5.36329985e-01 -3.19428630e-02 2.49023616e-01 8.57274950e-01
1.06875354e-03 -4.16791975e-01 -6.15276575e-01 4.73252207e-01
-1.87411356e+00 -1.21091616e+00 -5.96508384e-01 2.74427891e+00
1.12167466e+00 7.59323612e-02 2.80863255e-01 3.85088116e-01
1.22188425e+00 -2.54302859e-01 -4.11757201e-01 -7.50250462e-03
-2.34474912e-02 1.71274588e-01 8.73604476e-01 6.01317763e-01
-1.21877193e+00 2.11688548e-01 6.90547895e+00 1.01241791e+00
-6.14654958e-01 5.68126403e-02 5.76663613e-01 1.19155228e-01
-1.43116981e-01 3.19691747e-01 -5.81843197e-01 6.20521963e-01
9.57952201e-01 -3.13822091e-01 1.08379170e-01 8.23673606e-01
7.97383487e-02 -5.73612392e-01 -1.17883909e+00 8.55078578e-01
-3.16894948e-01 -5.32415330e-01 -5.96613348e-01 2.98087418e-01
8.65098715e-01 -4.51815814e-01 -2.34459098e-02 4.74558622e-02
7.41381049e-01 -9.20420229e-01 1.17345795e-01 6.90593839e-01
4.05329555e-01 -8.22497070e-01 9.37766135e-01 5.20066738e-01
-1.07843792e+00 2.00912267e-01 -3.10350299e-01 -2.11339667e-01
7.71470591e-02 1.36454558e+00 -7.31331348e-01 5.54141045e-01
4.04941708e-01 5.65217793e-01 -2.51898766e-01 1.38443458e+00
-5.57663068e-02 6.26994312e-01 -6.93050623e-01 -3.24036062e-01
-1.27732068e-01 -6.20906413e-01 6.62134409e-01 1.10287964e+00
5.36936820e-01 -1.00669563e-01 -7.79223219e-02 7.46606886e-01
1.90601021e-01 2.11900219e-01 -6.63936138e-01 -5.36518432e-02
6.92669749e-01 1.10532701e+00 -9.77949321e-01 -4.11886126e-01
-5.19014060e-01 6.96288884e-01 -7.61549622e-02 3.65451485e-01
-9.57641840e-01 -5.83318651e-01 4.77122039e-01 -1.00193128e-01
3.38107198e-01 -1.19760945e-01 -3.56148541e-01 -1.02413630e+00
-1.69432297e-01 -5.17482340e-01 5.11693180e-01 -1.17678992e-01
-1.57394242e+00 1.01377167e-01 3.41801494e-01 -1.26579285e+00
-5.90323269e-01 -2.84858316e-01 -6.16282403e-01 8.54056478e-01
-7.46682346e-01 -4.32871073e-01 -6.66570477e-03 5.09135962e-01
-9.39204767e-02 7.38332570e-02 5.51384568e-01 1.50611043e-01
-6.46470368e-01 5.30310988e-01 8.20268869e-01 -4.39710245e-02
5.82941771e-01 -1.63077497e+00 -1.18708216e-01 7.05109477e-01
1.17140628e-01 6.07348680e-01 1.04353487e+00 -7.33647585e-01
-1.11792445e+00 -5.87101579e-01 6.77084327e-01 -9.30023119e-02
8.82224619e-01 -3.09156775e-01 -7.42451966e-01 4.23911154e-01
2.00675447e-02 -1.48723185e-01 8.48054767e-01 3.54561508e-01
1.32126324e-02 1.42839924e-01 -1.31875539e+00 5.78098714e-01
6.98133349e-01 -1.06966563e-01 -1.47152096e-01 3.46299142e-01
2.33193561e-01 1.29034474e-01 -1.11979938e+00 4.09640998e-01
6.16504252e-01 -1.31114173e+00 7.77062297e-01 -3.38901371e-01
1.55586630e-01 -2.32758805e-01 -1.27758130e-01 -1.29890621e+00
-1.36495844e-01 -5.89745343e-01 -6.48142695e-02 1.34564090e+00
3.94610882e-01 -8.74840736e-01 5.79104364e-01 6.52817726e-01
6.05428517e-01 -4.56103712e-01 -1.02714694e+00 -9.34646666e-01
-4.28973623e-02 -5.17846704e-01 4.49302495e-01 1.03345716e+00
3.53090644e-01 4.64981198e-01 -5.49157441e-01 8.42441916e-02
1.03291428e+00 1.38359934e-01 8.20631742e-01 -1.66978991e+00
-7.97903717e-01 -7.41850555e-01 -7.07243621e-01 -9.97528970e-01
6.45759702e-02 -5.82334697e-01 2.37633020e-01 -1.24639392e+00
6.21397376e-01 -7.25041449e-01 -7.29934201e-02 -8.23015273e-02
-2.81407207e-01 -2.65372097e-01 -1.66473135e-01 -6.43249974e-02
-4.49892491e-01 5.30873001e-01 1.04081392e+00 -4.68269289e-02
-2.13616058e-01 7.17837155e-01 -6.36201501e-01 8.28674436e-01
7.25876331e-01 -6.53414011e-01 -4.14713562e-01 5.43528318e-01
-9.66921076e-02 5.52063227e-01 2.31593043e-01 -9.91476357e-01
2.32159719e-01 -4.55780387e-01 3.36216092e-01 -8.12625527e-01
1.14255302e-01 -9.28732693e-01 5.34079492e-01 2.86756098e-01
-3.19868773e-01 -5.36875188e-01 -2.55257517e-01 7.98153639e-01
-1.89335704e-01 -6.97112560e-01 8.12728941e-01 7.29185417e-02
6.19445182e-02 1.75391912e-01 -3.96606773e-01 -4.99186553e-02
1.14892507e+00 -2.79627531e-03 -2.21087541e-02 -9.27460015e-01
-8.36039841e-01 1.31670699e-01 3.94596666e-01 -2.25376695e-01
2.92761445e-01 -1.33647192e+00 -5.79954684e-01 7.30077624e-02
-2.23353952e-01 -1.44205168e-01 9.27285329e-02 1.29711914e+00
-1.91099923e-02 3.13200951e-01 1.24469727e-01 -6.19673371e-01
-1.22104430e+00 5.57313800e-01 3.69889624e-02 -4.14240271e-01
-5.58382906e-02 5.66073537e-01 2.60767967e-01 -2.16122940e-01
2.20224649e-01 -2.47252569e-01 -1.04258321e-01 8.18193406e-02
2.59008139e-01 6.50276959e-01 -3.16348404e-01 -3.54393125e-01
-4.01357502e-01 3.77257466e-01 9.65877324e-02 -4.56030130e-01
1.04114032e+00 -2.81841338e-01 -3.27736706e-01 9.70260680e-01
1.42771471e+00 2.70350635e-01 -8.23827803e-01 -2.64299780e-01
1.98039979e-01 -4.30114806e-01 -2.11407214e-01 -3.13442886e-01
-9.43677366e-01 7.88540661e-01 3.48378360e-01 8.41932833e-01
1.06294477e+00 3.20520222e-01 2.01651722e-01 1.70174420e-01
2.67509639e-01 -8.61569226e-01 -2.48249844e-01 3.12225997e-01
4.72594649e-01 -1.07149887e+00 9.79349911e-02 -6.04509175e-01
-4.14857507e-01 9.56559777e-01 1.96377158e-01 -1.08525716e-02
1.12206399e+00 4.75936115e-01 -5.24044394e-01 9.58438516e-02
-6.75519586e-01 -4.87464309e-01 4.03237343e-01 5.92360020e-01
7.74152219e-01 4.51059103e-01 -4.92354751e-01 5.75313032e-01
-1.77375332e-01 -3.63662183e-01 5.75640023e-01 7.04835415e-01
-3.46202105e-01 -1.08073866e+00 -6.14054978e-01 9.89834607e-01
-4.17675555e-01 -7.96182901e-02 -3.25160027e-01 9.38022375e-01
-1.25968009e-01 1.16274881e+00 1.41406745e-01 -1.22474618e-01
-1.72054589e-01 -1.22304842e-01 4.51767266e-01 -2.59686321e-01
2.03856573e-01 3.31871867e-01 -6.08351938e-02 6.49723634e-02
-5.48171043e-01 -1.12335300e+00 -9.28185523e-01 -5.98831654e-01
-9.54474151e-01 4.76349622e-01 6.09763861e-01 1.02744460e+00
-2.60516733e-01 3.41759264e-01 8.18263054e-01 -6.12484932e-01
-5.98655283e-01 -1.14806855e+00 -1.22148407e+00 1.24570936e-01
2.22551793e-01 -9.52794850e-01 -8.55083525e-01 -2.09074050e-01] | [7.356607437133789, 4.3609418869018555] |
081be829-6170-40ce-8ede-1ee0f2035359 | neuro-symbolic-spatio-temporal-reasoning | 2211.15566 | null | https://arxiv.org/abs/2211.15566v2 | https://arxiv.org/pdf/2211.15566v2.pdf | Neuro-Symbolic Spatio-Temporal Reasoning | Knowledge about space and time is necessary to solve problems in the physical world: An AI agent situated in the physical world and interacting with objects often needs to reason about positions of and relations between objects; and as soon as the agent plans its actions to solve a task, it needs to consider the temporal aspect (e.g., what actions to perform over time). Spatio-temporal knowledge, however, is required beyond interacting with the physical world, and is also often transferred to the abstract world of concepts through analogies and metaphors (e.g., "a threat that is hanging over our heads"). As spatial and temporal reasoning is ubiquitous, different attempts have been made to integrate this into AI systems. In the area of knowledge representation, spatial and temporal reasoning has been largely limited to modeling objects and relations and developing reasoning methods to verify statements about objects and relations. On the other hand, neural network researchers have tried to teach models to learn spatial relations from data with limited reasoning capabilities. Bridging the gap between these two approaches in a mutually beneficial way could allow us to tackle many complex real-world problems, such as natural language processing, visual question answering, and semantic image segmentation. In this chapter, we view this integration problem from the perspective of Neuro-Symbolic AI. Specifically, we propose a synergy between logical reasoning and machine learning that will be grounded on spatial and temporal knowledge. Describing some successful applications, remaining challenges, and evaluation datasets pertaining to this direction is the main topic of this contribution. | ['Stefan Wermter', 'Matthias Kerzel', 'Marjan Alirezaie', 'Kyra Ahrens', 'Michael Sioutis', 'Jae Hee Lee'] | 2022-11-28 | null | null | null | null | ['logical-reasoning'] | ['reasoning'] | [ 1.18253298e-01 7.37271309e-02 -1.79711014e-01 -2.04347342e-01
1.78180575e-01 -7.66822696e-01 7.51850188e-01 4.78362590e-01
-3.70492518e-01 4.96421963e-01 -1.81194156e-01 -4.94295150e-01
-6.45496547e-01 -1.21342874e+00 -4.08604771e-01 -5.54334462e-01
-1.51325122e-01 5.62324762e-01 5.35806119e-01 -3.31038028e-01
4.62877274e-01 8.87934685e-01 -1.55549896e+00 3.09783697e-01
6.81108475e-01 8.94405067e-01 2.61538446e-01 3.63273561e-01
-4.75171149e-01 1.21374178e+00 -4.84468639e-01 1.40033517e-04
-1.62998214e-01 -5.13542652e-01 -1.53147614e+00 -7.80347809e-02
-1.16768107e-01 -8.39626119e-02 -3.42409164e-01 1.08093357e+00
-2.58979410e-01 5.32474399e-01 4.68483120e-01 -1.40356266e+00
-8.29689205e-01 5.09147286e-01 -1.99580982e-01 3.41651767e-01
5.56210220e-01 5.32842167e-02 7.51766801e-01 -2.28220373e-01
6.30145133e-01 1.25661612e+00 3.30780745e-01 4.04677808e-01
-1.07593298e+00 -5.32084182e-02 6.41886234e-01 9.52544868e-01
-1.42265713e+00 9.74054933e-02 9.43946004e-01 -4.96369898e-01
1.02774596e+00 2.96429932e-01 9.55903590e-01 7.33045280e-01
4.10009474e-02 8.89718235e-01 1.09146559e+00 -5.66364050e-01
6.41541839e-01 4.02144715e-02 2.05569446e-01 4.08416241e-01
-2.08397865e-01 1.49230942e-01 -6.25623345e-01 2.77901947e-01
8.82806540e-01 -7.02700093e-02 -7.52015114e-02 -3.97782743e-01
-1.39676130e+00 4.88119900e-01 7.46670127e-01 1.00922108e+00
-4.16651696e-01 2.26712450e-01 1.97140634e-01 4.70259115e-02
-2.83651408e-02 7.63950944e-01 -2.48649195e-01 -1.10719979e-01
-7.85500884e-01 2.96595395e-01 7.05466688e-01 6.20131969e-01
6.09548867e-01 -2.20434502e-01 6.60208687e-02 2.71617234e-01
2.78815031e-01 3.66970688e-01 3.06762755e-01 -1.22556567e+00
1.35234982e-01 8.66520703e-01 1.98991656e-01 -1.17132962e+00
-4.89314258e-01 1.09584287e-01 -5.09165764e-01 3.77774954e-01
6.60383821e-01 3.99087697e-01 -7.46921360e-01 1.73068297e+00
4.91089374e-01 3.65754157e-01 1.16665237e-01 1.09068489e+00
5.37510514e-01 6.51677370e-01 2.20650524e-01 -9.36093181e-02
1.52670813e+00 -6.30864859e-01 -8.52351248e-01 -4.20280308e-01
6.01670980e-01 -5.22032827e-02 9.83933091e-01 3.47947508e-01
-1.19261444e+00 -3.44869435e-01 -8.61706316e-01 -3.40898007e-01
-1.05588603e+00 -3.99232566e-01 8.68061960e-01 7.61971846e-02
-1.01990902e+00 6.82638407e-01 -9.55278754e-01 -6.02082431e-01
3.60495836e-01 1.91776201e-01 -2.53270388e-01 8.77763703e-02
-1.41318750e+00 1.45896065e+00 7.31950641e-01 3.46077502e-01
-4.76742566e-01 -3.93982351e-01 -8.81159484e-01 3.33848968e-03
6.23997092e-01 -6.39167368e-01 1.20720816e+00 -9.92075801e-01
-1.26836073e+00 7.99265623e-01 -2.03949839e-01 -5.55258632e-01
1.89025775e-01 -1.32043391e-01 -4.80089188e-01 3.73992532e-01
5.51942065e-02 7.25146770e-01 2.16761440e-01 -1.15369451e+00
-5.65436661e-01 -6.99714899e-01 6.13021374e-01 2.68466175e-01
-1.08837178e-02 1.31733306e-02 -3.27719957e-01 -3.14085692e-01
6.86219275e-01 -8.71294200e-01 -7.67827779e-02 2.67722458e-01
-2.96952110e-02 -3.94788474e-01 8.13134372e-01 -4.27157938e-01
1.05767977e+00 -2.13298583e+00 5.12038112e-01 2.56372780e-01
1.01771176e-01 1.43661991e-01 1.24099381e-01 3.61138701e-01
-1.87848017e-01 2.95441411e-02 -2.55247712e-01 4.25480157e-01
1.65808767e-01 5.21160424e-01 -6.53186619e-01 2.75173783e-01
-1.77731700e-02 1.05752587e+00 -1.24978507e+00 -5.75480461e-01
4.80632395e-01 3.98203224e-01 -1.53072968e-01 -1.44909143e-01
-5.31645775e-01 6.04726672e-01 -6.84829831e-01 4.36947495e-01
2.51719564e-01 -2.62787014e-01 3.46269548e-01 5.45976162e-02
-3.16052467e-01 4.19851571e-01 -1.20335150e+00 1.75918698e+00
-4.32691097e-01 7.37989724e-01 -3.05536062e-01 -1.18136799e+00
4.81287003e-01 4.90694135e-01 4.23533708e-01 -1.18281424e+00
1.07254550e-01 -1.01665519e-02 6.44565001e-02 -8.39518011e-01
2.26349607e-01 -2.99909800e-01 1.72675923e-02 4.65482235e-01
-3.25277179e-01 -4.79882896e-01 3.50116491e-01 1.46299317e-01
1.00303388e+00 6.70867443e-01 5.26190758e-01 -3.60173322e-02
6.72389328e-01 4.18700278e-01 3.56132299e-01 3.92804027e-01
-2.77260661e-01 -6.01083077e-02 4.95220453e-01 -7.55952597e-01
-5.59968948e-01 -1.33907616e+00 7.60766044e-02 9.71440852e-01
6.51413858e-01 -1.59555942e-01 -6.63922310e-01 -3.44220340e-01
-2.56622076e-01 1.09123361e+00 -7.14153409e-01 -2.18162686e-01
-7.26675153e-01 -6.26804456e-02 4.24615294e-01 7.85705507e-01
5.51093400e-01 -1.57298410e+00 -1.37346303e+00 1.47817656e-01
-1.68264180e-01 -1.08018172e+00 3.08056980e-01 1.17019750e-01
-9.40680504e-01 -1.20486307e+00 -1.06599137e-01 -5.73537588e-01
6.20993793e-01 2.11901888e-01 9.90103126e-01 2.10474893e-01
-1.90609187e-01 5.96705198e-01 -3.95300210e-01 -4.34867859e-01
-1.08557250e-02 -4.31280106e-01 -5.55554926e-02 -1.89169884e-01
4.17739123e-01 -7.78581679e-01 -3.61708134e-01 2.80923635e-01
-1.12029922e+00 3.05871516e-01 1.58731550e-01 4.14499044e-01
4.48847741e-01 4.55876410e-01 2.06458375e-01 -4.42217261e-01
4.01276827e-01 -3.80972713e-01 -6.26188338e-01 5.86460412e-01
-2.22648054e-01 2.37263903e-01 4.61584538e-01 -6.63839519e-01
-1.22718298e+00 -2.47265682e-01 3.60161185e-01 -2.92708904e-01
-5.37324309e-01 7.46497035e-01 -1.74581915e-01 2.35147685e-01
5.98889530e-01 3.52400601e-01 -2.35004976e-01 -1.31872267e-01
6.68412209e-01 -1.94705017e-02 6.27799451e-01 -9.87155080e-01
6.35732293e-01 7.43325233e-01 2.69773155e-01 -6.45863533e-01
-8.97176683e-01 -2.15367258e-01 -1.05996680e+00 -3.43308955e-01
1.16009521e+00 -1.63388148e-01 -1.12314761e+00 2.67985016e-01
-1.29565954e+00 -5.12852788e-01 -5.98896503e-01 4.85822201e-01
-8.27190936e-01 1.44155443e-01 -3.51889938e-01 -8.81884634e-01
4.53977585e-01 -8.93243730e-01 6.75316393e-01 2.79494673e-01
-6.47565663e-01 -1.27186859e+00 -5.53055108e-02 3.56358379e-01
1.76193103e-01 2.31515601e-01 1.16992629e+00 -3.59888047e-01
-7.26749122e-01 8.77640694e-02 -1.79494649e-01 -1.82367340e-01
2.51190364e-01 -2.10496292e-01 -7.94108987e-01 3.81100684e-01
2.76551485e-01 -8.83134827e-02 2.96432555e-01 2.47789264e-01
1.33277464e+00 -2.60512382e-01 -4.75606084e-01 1.67965487e-01
1.08287954e+00 8.42285573e-01 7.52520621e-01 4.63887274e-01
4.18711245e-01 1.08526886e+00 8.39782298e-01 1.33766249e-01
6.36849821e-01 9.14837003e-01 3.25284958e-01 1.93208292e-01
4.05456647e-02 -1.35365203e-01 -9.96875316e-02 3.22367340e-01
-3.02850455e-01 1.52935404e-02 -1.37942505e+00 5.86642087e-01
-2.16416383e+00 -1.37632227e+00 -8.36603791e-02 1.77933955e+00
8.67887735e-01 -5.29395714e-02 -2.72861898e-01 4.01268840e-01
3.51836443e-01 2.51911376e-02 -6.53856099e-01 -3.56799304e-01
8.46576616e-02 -4.37499955e-02 -1.75417706e-01 5.32441199e-01
-9.09159124e-01 1.24315631e+00 6.01753855e+00 4.92997110e-01
-1.16284537e+00 -7.96016231e-02 2.37782896e-01 1.26671061e-01
-1.97404549e-01 3.14921796e-01 -1.35642961e-01 8.05473253e-02
6.15087926e-01 -4.28169519e-02 8.95358801e-01 4.43522036e-01
2.00619504e-01 -6.53726816e-01 -1.57138586e+00 8.93245697e-01
-3.62733193e-02 -1.18880343e+00 -1.53421059e-01 -1.28030539e-01
3.16588670e-01 -6.07252717e-01 2.62977090e-02 9.34301391e-02
2.39777982e-01 -1.24322569e+00 1.06148195e+00 7.99390256e-01
1.07288146e-02 -3.21703136e-01 3.74572635e-01 6.84542716e-01
-1.25902581e+00 -1.06715031e-01 1.66671544e-01 -6.65233135e-01
2.88631201e-01 1.98716745e-01 -6.17337584e-01 5.93731165e-01
7.68084168e-01 4.46031570e-01 -3.30532938e-01 8.37862790e-01
-6.66172206e-01 -3.91105190e-03 -2.76554942e-01 -1.07413150e-01
2.27777019e-01 -4.33140367e-01 2.99034357e-01 5.61634958e-01
1.32630587e-01 6.93633854e-01 -1.20999053e-01 1.45965636e+00
6.75977945e-01 -2.97211438e-01 -8.08301449e-01 -1.06115177e-01
4.10616994e-01 7.68975079e-01 -1.16005671e+00 -3.49934459e-01
-2.35108122e-01 7.28578031e-01 3.32004786e-01 6.33402586e-01
-1.03908312e+00 -9.17247236e-02 5.87048173e-01 1.11112818e-01
-1.15619831e-01 -6.87794507e-01 -5.51083803e-01 -7.87429750e-01
1.26251712e-01 -5.67210495e-01 3.64409566e-01 -1.31067133e+00
-7.81598449e-01 3.71375382e-01 5.82771122e-01 -1.08828342e+00
-3.13818753e-01 -8.56620133e-01 -5.03928483e-01 7.51146019e-01
-1.28093231e+00 -1.10057020e+00 -1.94882989e-01 7.37904072e-01
2.81697869e-01 3.80848169e-01 7.87030280e-01 -6.35610223e-02
-1.16620682e-01 -2.74622083e-01 -6.70834124e-01 6.80847242e-02
1.52586922e-02 -1.13986945e+00 -8.13862833e-04 7.53136754e-01
4.52711821e-01 8.64007115e-01 6.83432460e-01 -5.27777076e-01
-1.37617493e+00 -5.42778969e-01 1.08038568e+00 -5.30569613e-01
7.90784836e-01 -1.00231051e-01 -1.19980872e+00 8.79321754e-01
7.53943324e-02 2.49754749e-02 4.60683197e-01 8.60154256e-02
-4.36849147e-01 -2.61279698e-02 -1.06140733e+00 1.03738666e+00
1.16857791e+00 -8.33998621e-01 -1.14503288e+00 2.65051991e-01
5.75356901e-01 -4.57545549e-01 -7.06920207e-01 2.69461036e-01
3.31913978e-01 -9.14946198e-01 1.16216755e+00 -8.56960118e-01
1.01747960e-02 -8.50256622e-01 -8.53913873e-02 -9.95221078e-01
-3.01558107e-01 -1.22354306e-01 -5.38661443e-02 9.06218112e-01
1.69860944e-01 -5.95054865e-01 5.43448329e-01 9.13091242e-01
4.98628877e-02 -5.06744087e-01 -1.05229855e+00 -7.73721337e-01
1.04495361e-01 -9.33874667e-01 7.09059358e-01 1.17649567e+00
5.21070421e-01 6.79625496e-02 2.19824255e-01 4.50195402e-01
1.09440573e-01 3.83587718e-01 2.15807453e-01 -1.32723117e+00
1.87635180e-02 -6.40569866e-01 -5.21650255e-01 -9.12606537e-01
4.81058300e-01 -7.73348033e-01 1.00963891e-01 -2.00160217e+00
-2.28547931e-01 -3.45330149e-01 -1.31513879e-01 8.13030839e-01
3.37114394e-01 -2.79187262e-01 3.51044387e-01 6.83782250e-02
-5.94118834e-01 2.56706595e-01 1.43375969e+00 -1.95031062e-01
-2.27250889e-01 -2.48877108e-01 -3.12519044e-01 1.10028100e+00
7.83899367e-01 -1.33019239e-01 -7.39227295e-01 -5.21079719e-01
6.68074787e-01 4.42794561e-01 8.66780996e-01 -1.14245188e+00
7.99123228e-01 -9.02758837e-01 1.25712156e-01 -4.89837438e-01
5.76099336e-01 -1.24075258e+00 2.56653696e-01 4.31641430e-01
-3.32232714e-01 1.38046980e-01 2.65428126e-01 2.46634632e-01
-4.07144248e-01 -1.99768394e-01 5.85310221e-01 -2.86445320e-01
-1.28971469e+00 -1.90818980e-01 -4.89347309e-01 4.51758271e-03
1.44177449e+00 -4.50717300e-01 -4.39118326e-01 -1.50108293e-01
-1.14615345e+00 3.75510782e-01 2.34897435e-01 4.91853744e-01
7.70374775e-01 -1.22014511e+00 7.82191381e-02 -7.12245107e-02
9.04568806e-02 1.06084086e-01 3.69648516e-01 9.97036517e-01
-5.76553464e-01 6.78498507e-01 -2.99854696e-01 -4.81308222e-01
-9.09794629e-01 1.03263569e+00 6.03368044e-01 5.93208186e-02
-5.88988841e-01 5.55845201e-01 3.49049896e-01 -2.82535046e-01
2.86901891e-01 -7.73950458e-01 -4.52741921e-01 3.07754260e-02
5.14763117e-01 3.07771176e-01 -3.05360019e-01 -5.40715933e-01
-6.87177598e-01 7.16531992e-01 5.76153278e-01 -3.77782375e-01
1.00907826e+00 -8.06818977e-02 -6.39139950e-01 8.78514707e-01
5.78650653e-01 -4.37132299e-01 -9.39211249e-01 -3.11658770e-01
3.67838502e-01 -3.36687237e-01 -1.95525393e-01 -9.67183948e-01
-7.13510871e-01 1.05479550e+00 3.00831735e-01 6.57123327e-01
1.14674902e+00 4.68331337e-01 2.72131532e-01 4.70235497e-01
6.45453572e-01 -1.17142642e+00 2.87290871e-01 7.64751315e-01
9.01766121e-01 -9.06167030e-01 -5.34518622e-02 -3.92947912e-01
-6.48768723e-01 1.15136576e+00 7.11989522e-01 2.95784861e-01
6.69043839e-01 1.54818833e-01 -1.64407328e-01 -5.31913757e-01
-4.96595293e-01 -2.66770303e-01 3.71434867e-01 6.21829152e-01
2.46523619e-01 1.32603705e-01 -6.59987852e-02 2.01108545e-01
-2.02620164e-01 1.49565920e-01 1.26226306e-01 1.19762421e+00
-3.97470295e-01 -9.75510538e-01 -5.99797785e-01 -2.53281653e-01
4.54093441e-02 1.03305854e-01 -3.94741029e-01 8.41797352e-01
5.45742929e-01 9.60399032e-01 2.37330720e-01 7.73677453e-02
2.69851297e-01 2.06205994e-01 6.89605117e-01 -4.16373789e-01
-2.29093418e-01 -4.62339997e-01 -2.47955278e-01 -7.50487626e-01
-7.92552888e-01 -7.26892948e-01 -2.08089757e+00 -2.18055576e-01
2.55062014e-01 8.24406967e-02 6.28613353e-01 1.40907085e+00
-8.47667456e-02 8.07379007e-01 -6.32265955e-02 -5.48881650e-01
1.27832098e-02 -3.43065262e-01 -4.36493367e-01 3.11730415e-01
1.62622139e-01 -7.55284727e-01 1.45701617e-02 1.61467940e-01] | [10.386296272277832, 1.944320559501648] |
dc2ff790-6aa9-4946-9f2d-a195c8d1174f | semi-supervised-3d-hand-object-pose | 2107.07676 | null | https://arxiv.org/abs/2107.07676v1 | https://arxiv.org/pdf/2107.07676v1.pdf | Semi-supervised 3D Hand-Object Pose Estimation via Pose Dictionary Learning | 3D hand-object pose estimation is an important issue to understand the interaction between human and environment. Current hand-object pose estimation methods require detailed 3D labels, which are expensive and labor-intensive. To tackle the problem of data collection, we propose a semi-supervised 3D hand-object pose estimation method with two key techniques: pose dictionary learning and an object-oriented coordinate system. The proposed pose dictionary learning module can distinguish infeasible poses by reconstruction error, enabling unlabeled data to provide supervision signals. The proposed object-oriented coordinate system can make 3D estimations equivariant to the camera perspective. Experiments are conducted on FPHA and HO-3D datasets. Our method reduces estimation error by 19.5% / 24.9% for hands/objects compared to straightforward use of labeled data on FPHA and outperforms several baseline methods. Extensive experiments also validate the robustness of the proposed method. | ['Ya zhang', 'Siheng Chen', 'Zida Cheng'] | 2021-07-16 | null | null | null | null | ['hand-object-pose'] | ['computer-vision'] | [-2.87584871e-01 -3.63921016e-01 -2.88549721e-01 -2.38276839e-01
-5.48244059e-01 -5.87099612e-01 2.21257970e-01 -5.04812479e-01
-3.69715452e-01 4.59244668e-01 2.55155742e-01 1.86471298e-01
1.06097415e-01 -2.87631541e-01 -4.52261895e-01 -5.09480834e-01
8.59386697e-02 1.02409720e+00 9.66897383e-02 -3.32992077e-02
2.54196823e-01 9.31586325e-01 -1.29546511e+00 -2.60051906e-01
2.57848829e-01 9.35529530e-01 4.04326200e-01 5.33948064e-01
2.54365176e-01 2.84776390e-01 -6.25620663e-01 2.00072974e-01
7.45440722e-01 5.87778576e-02 -6.48559749e-01 6.22424901e-01
5.70724964e-01 -7.98895001e-01 -3.89106989e-01 8.43939662e-01
9.42917883e-01 1.17642313e-01 5.69499195e-01 -1.32548153e+00
-1.62258416e-01 7.98166096e-02 -7.34004736e-01 -4.23861258e-02
8.22268307e-01 2.17430145e-02 7.61512876e-01 -1.27483833e+00
9.05620873e-01 1.45132780e+00 5.70424736e-01 4.04921144e-01
-9.80581701e-01 -6.03060305e-01 1.60250574e-01 1.16851851e-01
-1.94278646e+00 -8.37698951e-02 9.84852135e-01 -6.59682751e-01
7.61112273e-01 2.55400002e-01 6.79731309e-01 1.26103544e+00
-1.70893356e-01 9.99012828e-01 1.26056087e+00 -5.93568861e-01
-1.61249399e-01 2.36237183e-01 1.90302387e-01 8.08291674e-01
3.30483109e-01 4.27623838e-02 -5.79586506e-01 -2.63414513e-02
1.23326731e+00 3.40585440e-01 -1.83892608e-01 -8.17594409e-01
-1.37826252e+00 4.27396327e-01 3.95024747e-01 -5.43492939e-03
-2.77724177e-01 -1.64986119e-01 7.70090818e-02 -3.58885862e-02
1.11341506e-01 1.37260988e-01 -4.36939120e-01 -6.81845397e-02
-4.63688135e-01 4.88651842e-01 6.78791523e-01 1.66164875e+00
4.94003892e-01 -1.54901043e-01 -1.30056307e-01 5.73650301e-01
6.69989288e-01 1.07543373e+00 -1.03817068e-01 -7.95063853e-01
7.14032948e-01 6.97620869e-01 3.73378068e-01 -1.02428234e+00
-6.15624964e-01 -2.37258449e-01 -4.30233955e-01 5.12463599e-02
7.02722430e-01 9.27793607e-02 -8.58440936e-01 1.25968111e+00
7.33034670e-01 -5.03572404e-01 -5.36102891e-01 1.43799770e+00
6.81122959e-01 2.24695578e-01 -2.41420224e-01 -1.55628115e-01
1.30541015e+00 -9.26817834e-01 -8.01594019e-01 -6.94021136e-02
3.55830997e-01 -9.21493292e-01 1.02875531e+00 3.85050952e-01
-7.32885718e-01 -7.78774381e-01 -7.46215165e-01 -1.95657417e-01
-8.83759931e-02 6.55820787e-01 4.48036283e-01 5.62660098e-01
-2.79587537e-01 1.42136678e-01 -9.11664248e-01 -3.25067967e-01
2.46986687e-01 6.50185525e-01 -5.37904620e-01 2.42171183e-01
-7.12047577e-01 1.03844714e+00 5.26177168e-01 3.53757739e-01
-8.98353696e-01 -3.25562567e-01 -8.95684659e-01 -4.29310888e-01
6.95804417e-01 -3.74027818e-01 1.08266842e+00 -1.22662701e-01
-1.52547967e+00 8.91103983e-01 -1.40519872e-01 1.81486219e-01
7.90930569e-01 -8.42268646e-01 -6.78525046e-02 1.34456962e-01
9.92440209e-02 4.21651483e-01 9.78463113e-01 -1.48516607e+00
-4.84329700e-01 -9.51075792e-01 -6.20530918e-02 3.91817808e-01
-8.70649517e-02 -1.64002925e-01 -7.31371522e-01 -7.80079722e-01
6.15950167e-01 -1.36447597e+00 1.88985337e-02 2.44300961e-01
-6.14415348e-01 -3.92723054e-01 1.00085032e+00 -9.57058728e-01
1.01628208e+00 -1.81588793e+00 4.09951270e-01 5.46473384e-01
2.14614913e-01 1.41573012e-01 1.07223719e-01 1.51928544e-01
1.30261734e-01 -4.66748565e-01 2.75676340e-01 -2.96897829e-01
1.02071300e-01 9.00261775e-02 -2.50583161e-02 6.96237028e-01
-3.76606546e-02 7.06839085e-01 -7.58430183e-01 -8.16116750e-01
4.85249102e-01 6.50849462e-01 -6.15738213e-01 5.97938776e-01
-5.71581796e-02 7.45620131e-01 -6.07343912e-01 1.13975477e+00
5.89584768e-01 -8.53978768e-02 1.50915310e-01 -6.40595376e-01
-1.53357657e-02 1.82895556e-01 -1.70061755e+00 1.99753463e+00
-2.97837108e-01 3.12046438e-01 -1.77259535e-01 -4.28919405e-01
8.63438308e-01 4.17548448e-01 4.87348437e-01 -1.00784019e-01
7.00332165e-01 1.87580600e-01 -2.35461324e-01 -5.91165721e-01
2.15098321e-01 1.66010067e-01 -2.18320470e-02 4.52317685e-01
1.78593278e-01 -1.26363099e-01 -1.37375578e-01 -2.54872054e-01
4.70147878e-01 5.67196727e-01 4.20189112e-01 -1.68162435e-01
5.69225907e-01 -1.63757518e-01 3.99525017e-01 3.05073828e-01
-3.41883004e-01 5.36060214e-01 -1.29351467e-01 -5.51674783e-01
-1.02132297e+00 -1.01159573e+00 -1.09132901e-01 9.23119128e-01
3.16175610e-01 -3.24714869e-01 -6.60762370e-01 -9.39444840e-01
2.68381536e-01 1.01023175e-01 -3.38812351e-01 2.95483619e-01
-8.60745609e-01 -1.24738976e-01 1.89247970e-02 8.79975140e-01
3.91258061e-01 -7.54075289e-01 -6.07135177e-01 -9.13343877e-02
-2.94943571e-01 -1.24794400e+00 -8.69520068e-01 -1.09791540e-01
-7.54587054e-01 -1.17293954e+00 -8.84645581e-01 -9.17001963e-01
1.03008699e+00 4.08303708e-01 5.88897109e-01 -1.12871476e-01
-4.22487468e-01 6.32021487e-01 -3.17984611e-01 -4.62813646e-01
2.84786918e-03 2.62781590e-01 7.15590239e-01 -6.57571256e-02
4.65568244e-01 -4.32293385e-01 -6.10308409e-01 7.97486961e-01
-5.69994263e-02 -2.89820462e-01 6.89701080e-01 7.27416515e-01
7.72132814e-01 -2.98480421e-01 2.42268797e-02 -5.20131886e-01
2.07538337e-01 2.21410722e-01 -6.63645029e-01 2.06636488e-01
-4.28875923e-01 6.63357303e-02 1.37861604e-02 -6.54139698e-01
-1.10776162e+00 8.05503964e-01 1.34196311e-01 -6.92947209e-01
-3.62323403e-01 -1.17456093e-02 -6.32588804e-01 -2.96275198e-01
5.92615724e-01 -1.13970814e-02 1.14791058e-01 -8.79374325e-01
2.74579793e-01 9.37353313e-01 5.18810928e-01 -7.17365086e-01
1.18385458e+00 5.94279110e-01 7.20752403e-02 -7.46614814e-01
-8.86500895e-01 -7.11252034e-01 -1.46393013e+00 -3.92981470e-01
8.04151475e-01 -9.04967010e-01 -1.01111615e+00 3.47814173e-01
-1.33103418e+00 1.65145382e-01 2.60442263e-03 7.97865212e-01
-5.84123194e-01 5.68933666e-01 -3.27322841e-01 -9.45488334e-01
-3.25742692e-01 -1.24590468e+00 1.52581632e+00 -2.60596395e-01
-4.19554234e-01 -5.53635120e-01 -8.35820809e-02 6.71239078e-01
-3.13165307e-01 2.33771771e-01 3.11834037e-01 -3.89356822e-01
-5.82046151e-01 -5.99181890e-01 -6.26977757e-02 1.45888656e-01
3.64524722e-01 -4.23612386e-01 -8.22829604e-01 -6.37514949e-01
-1.80050991e-02 -4.09005523e-01 1.01174772e-01 7.23839030e-02
9.39275324e-01 -1.80611417e-01 -3.65058213e-01 3.81975532e-01
1.00281453e+00 8.45906213e-02 4.29026634e-02 2.02402025e-01
1.13811767e+00 5.64920902e-01 1.04455853e+00 8.15949678e-01
3.53527546e-01 9.61167991e-01 2.48527333e-01 1.76561147e-01
-1.21502869e-01 -5.04381478e-01 1.30430743e-01 9.04940248e-01
-7.03031480e-01 2.26963818e-01 -8.60999525e-01 2.33870700e-01
-1.58382988e+00 -6.39487207e-01 8.25173259e-02 2.07125735e+00
7.14185834e-01 1.48768201e-01 5.17241120e-01 5.38833380e-01
6.64013028e-01 -9.18050185e-02 -5.57614088e-01 5.73892236e-01
4.10773188e-01 5.04513159e-02 3.87689322e-01 4.67339814e-01
-1.20189989e+00 9.81219232e-01 5.95856285e+00 3.22929889e-01
-9.01694715e-01 3.28499749e-02 -3.89691949e-01 -1.03191331e-01
4.35142994e-01 -2.62037486e-01 -1.19346464e+00 7.39652961e-02
-6.12629987e-02 3.28866363e-01 3.50494713e-01 1.23503804e+00
1.57790184e-01 5.07578775e-02 -1.53238201e+00 1.59741735e+00
3.66389483e-01 -6.66091263e-01 1.25864595e-01 1.76056355e-01
4.18192655e-01 -5.44254959e-01 -1.49825782e-01 -1.21668680e-02
-2.04542294e-01 -6.46883607e-01 1.02954733e+00 3.40506077e-01
7.58422434e-01 -5.09846032e-01 6.45243704e-01 5.55930793e-01
-1.53363335e+00 1.13335192e-01 -6.76779523e-02 -1.24700703e-01
2.60880500e-01 -7.00856838e-03 -1.12798047e+00 2.59170502e-01
8.07614207e-01 6.02628350e-01 -4.24601436e-01 6.24833524e-01
-3.09711307e-01 1.49696454e-01 -4.65810776e-01 -4.65712249e-02
-2.38850161e-01 1.75075140e-02 8.91733587e-01 9.49245751e-01
-3.35255601e-02 3.17076683e-01 6.78358614e-01 6.86055243e-01
2.71693945e-01 -6.00762963e-02 -4.35040683e-01 1.16044335e-01
5.55299222e-01 9.07084584e-01 -6.93031967e-01 -1.02926128e-01
-1.50858417e-01 1.10557532e+00 6.00225963e-02 1.13766715e-01
-6.99615002e-01 -3.48269135e-01 3.27264994e-01 2.19096512e-01
2.64174581e-01 -7.62935758e-01 -9.59354453e-03 -1.20632112e+00
4.95413005e-01 -9.34532881e-01 1.94200993e-01 -6.29530370e-01
-1.04888868e+00 3.92856419e-01 2.51319736e-01 -1.52360356e+00
-1.64051920e-01 -9.87183988e-01 2.92589992e-01 5.86728990e-01
-1.06123912e+00 -1.38088059e+00 -7.24217474e-01 8.58567297e-01
7.04166651e-01 -2.67197132e-01 7.79100120e-01 2.80170977e-01
-3.35157603e-01 7.19734907e-01 -3.87915522e-01 5.16677082e-01
7.12027788e-01 -1.11666000e+00 1.08933851e-01 4.09884453e-01
4.25773621e-01 9.17700946e-01 5.61541259e-01 -6.10333741e-01
-2.02452946e+00 -7.44562924e-01 6.10911191e-01 -1.05623758e+00
1.36400819e-01 -6.21113956e-01 -3.70637685e-01 8.56850326e-01
-4.45341915e-01 1.56130522e-01 5.59463620e-01 1.23243235e-01
-5.26011407e-01 -1.07638404e-01 -1.08141303e+00 3.70103955e-01
1.56253839e+00 -5.71077526e-01 -9.87240672e-01 5.42309642e-01
2.94921488e-01 -9.26682472e-01 -9.93419945e-01 3.63223672e-01
1.09018683e+00 -4.60364252e-01 1.21570885e+00 -5.88260233e-01
-2.78337836e-01 -5.21053493e-01 -3.18367690e-01 -7.92788029e-01
-3.09504479e-01 -5.80894530e-01 -4.13786024e-01 7.78157592e-01
-1.67081863e-01 -2.53357530e-01 9.93299365e-01 3.45887482e-01
2.77733624e-01 -4.75939244e-01 -7.55971014e-01 -1.00977242e+00
-5.09796143e-01 -3.67813021e-01 4.40309435e-01 5.92403293e-01
-1.15687259e-01 4.24154878e-01 -5.26996493e-01 4.70119953e-01
1.07522595e+00 2.94998169e-01 1.27462411e+00 -1.38515449e+00
-5.03327698e-02 -9.35158208e-02 -7.15569794e-01 -1.51800334e+00
1.88551500e-01 -6.85958803e-01 9.72060859e-02 -1.11562264e+00
2.65892237e-01 -4.04970109e-01 -9.51304659e-03 5.23101211e-01
3.20050865e-03 2.91303128e-01 2.29482830e-01 4.41780090e-01
-5.52294374e-01 4.54010427e-01 1.39945519e+00 -2.17755675e-01
-3.81632179e-01 1.47705168e-01 4.65240795e-03 8.97402167e-01
4.87316996e-01 -3.21026117e-01 -3.47699910e-01 -5.36989689e-01
-3.22828650e-01 -7.20657408e-02 5.68975568e-01 -8.42365742e-01
-1.02093285e-02 -2.10279688e-01 5.73258281e-01 -1.19082761e+00
5.02381086e-01 -1.31020033e+00 1.25460133e-01 4.78082448e-01
-1.30760849e-01 -5.96398562e-02 -1.00719959e-01 5.04068494e-01
1.91710502e-01 1.14585236e-01 5.03543139e-01 -2.49168903e-01
-6.74146771e-01 4.43599731e-01 5.89317977e-02 -4.90092859e-02
1.13832271e+00 -3.81859332e-01 5.21121323e-01 -2.41804719e-01
-9.02020037e-01 1.28541708e-01 1.82258978e-01 5.87024689e-01
7.02857316e-01 -1.62271643e+00 -3.91300261e-01 4.05893654e-01
1.80457816e-01 3.70964766e-01 -1.95302173e-01 6.86891437e-01
-5.35020769e-01 7.52426565e-01 -2.49805182e-01 -1.09183729e+00
-1.61971140e+00 5.19703150e-01 7.21545145e-02 2.13222995e-01
-6.16889179e-01 7.88824201e-01 -2.20716909e-01 -6.91044629e-01
8.08063924e-01 -4.28164154e-01 8.64751860e-02 -4.13973164e-03
3.96861464e-01 7.89730191e-01 -7.20667839e-02 -8.98006856e-01
-5.55916846e-01 1.03527498e+00 2.19381340e-02 -3.59905809e-02
1.26468682e+00 -6.35140240e-02 1.03746057e-01 3.02804530e-01
1.18917918e+00 -1.56906731e-02 -1.23826587e+00 -5.17000079e-01
-2.27450877e-02 -8.98368716e-01 -1.60341904e-01 -6.36556029e-01
-9.07161117e-01 9.92068291e-01 9.31452692e-01 -4.49943870e-01
6.75539553e-01 1.97573379e-01 7.09384322e-01 9.19875681e-01
8.91313910e-01 -1.17355192e+00 3.64390671e-01 2.77100265e-01
1.41618156e+00 -1.41756594e+00 3.65043163e-01 -7.42067099e-01
-3.95421237e-01 1.00519526e+00 7.57417560e-01 3.34551968e-02
7.99169719e-01 6.90238252e-02 1.58410341e-01 -2.68389910e-01
1.33869126e-01 -1.70077711e-01 6.43776476e-01 6.12736583e-01
2.07893744e-01 1.65248483e-01 -8.87793899e-02 5.54238021e-01
-2.12860271e-01 -4.84760031e-02 -2.28644103e-01 1.36403656e+00
-2.07360119e-01 -1.12325430e+00 -8.58111501e-01 6.57929406e-02
8.90415255e-03 4.75990593e-01 -3.93399745e-01 1.07302296e+00
9.52599421e-02 6.21909022e-01 -1.94524691e-01 -5.72378159e-01
7.88851559e-01 1.14617489e-01 1.08480024e+00 -7.76694953e-01
-8.30752552e-02 5.66357017e-01 -2.40337610e-01 -6.11591578e-01
-6.85044765e-01 -7.53998458e-01 -1.14480352e+00 -8.13669637e-02
-7.99664736e-01 -1.93034723e-01 5.02127469e-01 9.25157070e-01
2.27766767e-01 1.76096838e-02 6.52184784e-01 -1.39405477e+00
-1.03124070e+00 -9.98581886e-01 -7.08265603e-01 4.91349965e-01
3.27162206e-01 -1.46849573e+00 -1.69698328e-01 2.54415572e-01] | [6.672255992889404, -0.753339409828186] |
06df7148-e7d1-4039-99ea-8be535a1802d | exploring-temporal-context-and-human-movement | 2106.13967 | null | https://arxiv.org/abs/2106.13967v1 | https://arxiv.org/pdf/2106.13967v1.pdf | Exploring Temporal Context and Human Movement Dynamics for Online Action Detection in Videos | Nowadays, the interaction between humans and robots is constantly expanding, requiring more and more human motion recognition applications to operate in real time. However, most works on temporal action detection and recognition perform these tasks in offline manner, i.e. temporally segmented videos are classified as a whole. In this paper, based on the recently proposed framework of Temporal Recurrent Networks, we explore how temporal context and human movement dynamics can be effectively employed for online action detection. Our approach uses various state-of-the-art architectures and appropriately combines the extracted features in order to improve action detection. We evaluate our method on a challenging but widely used dataset for temporal action localization, THUMOS'14. Our experiments show significant improvement over the baseline method, achieving state-of-the art results on THUMOS'14. | ['Petros Maragos', 'Nikolaos Kardaris', 'Vasiliki I. Vasileiou'] | 2021-06-26 | null | null | null | null | ['online-action-detection'] | ['computer-vision'] | [ 4.16938692e-01 -3.36894274e-01 -5.70287466e-01 2.12647066e-01
-4.83150452e-01 -3.23940843e-01 7.79056370e-01 -3.33899975e-01
-7.55493283e-01 4.81932223e-01 3.36409688e-01 2.33554542e-01
1.57551289e-01 -3.00974727e-01 -3.59517097e-01 -7.79384375e-01
-4.34973955e-01 1.22720204e-01 7.55558491e-01 -1.00270519e-02
1.25690669e-01 4.22302157e-01 -1.53748453e+00 4.98811215e-01
4.03693020e-01 1.00876832e+00 1.85984120e-01 8.84599566e-01
3.51923376e-01 1.44391990e+00 -4.27847356e-01 1.80184677e-01
2.95802563e-01 -6.61869943e-01 -9.07571614e-01 3.47577184e-01
1.73443079e-01 -5.56121171e-01 -9.25859869e-01 7.45729685e-01
2.76168019e-01 5.57261765e-01 4.57554072e-01 -1.18533647e+00
-2.13982746e-01 3.83924574e-01 -2.57632762e-01 4.14184064e-01
5.90534866e-01 4.16184723e-01 7.93456852e-01 -6.44156218e-01
8.74449730e-01 1.20347750e+00 5.49633682e-01 4.80952531e-01
-8.60037565e-01 -3.75181228e-01 3.62792403e-01 8.89782846e-01
-1.07149029e+00 -4.67208683e-01 6.42333627e-01 -4.47779983e-01
1.36160469e+00 -7.69409239e-02 1.00445259e+00 1.45359039e+00
2.52549678e-01 1.46600449e+00 7.33449101e-01 -4.16645736e-01
4.77769375e-02 -6.06564462e-01 -1.26132578e-01 6.26454294e-01
-3.72248083e-01 6.39186949e-02 -5.86676002e-01 4.28411245e-01
8.72378469e-01 2.55087376e-01 -1.52416229e-01 -4.93336499e-01
-1.67731571e+00 4.82481211e-01 3.34169209e-01 7.46485353e-01
-7.77205110e-01 4.51421827e-01 7.66253650e-01 1.85766682e-01
3.25437963e-01 7.41261914e-02 -3.54546756e-01 -8.77454698e-01
-7.18086898e-01 1.26779690e-01 5.26767433e-01 6.76167428e-01
1.47629619e-01 -4.41410169e-02 -4.12402570e-01 7.03571320e-01
2.57248525e-02 2.21909881e-01 7.87707925e-01 -1.25040913e+00
3.81593496e-01 6.40858471e-01 3.79622608e-01 -8.50512266e-01
-5.64977288e-01 2.90130198e-01 -5.84279180e-01 5.85137457e-02
5.83628178e-01 3.09364051e-02 -1.12007511e+00 1.56928611e+00
2.45128930e-01 4.88551050e-01 1.62475511e-01 9.99700725e-01
3.78066391e-01 4.79798943e-01 3.82473856e-01 -2.28113279e-01
1.29820895e+00 -1.50079954e+00 -8.97154629e-01 -4.06125784e-01
9.46830034e-01 -4.11828667e-01 6.82975590e-01 4.61149067e-01
-8.94687653e-01 -6.37901604e-01 -8.88995290e-01 6.96012452e-02
-3.79516780e-01 6.29356384e-01 6.38409853e-01 1.57769203e-01
-8.72461438e-01 8.52054536e-01 -1.46966875e+00 -8.46519768e-01
4.86658096e-01 3.12365562e-01 -6.14120245e-01 6.20783716e-02
-1.05568635e+00 8.83122921e-01 6.19974732e-01 2.44987130e-01
-1.08830822e+00 2.02254832e-01 -9.30904448e-01 -2.94433594e-01
7.93522537e-01 -4.37732637e-01 1.70054996e+00 -9.20908630e-01
-1.81622124e+00 6.16269231e-01 -1.98136240e-01 -9.59713042e-01
7.54335523e-01 -7.03654706e-01 -3.97970945e-01 5.79398870e-01
9.96793956e-02 6.83562279e-01 6.92092538e-01 -4.42505449e-01
-9.59589303e-01 -1.71061143e-01 6.47890270e-02 1.85448661e-01
-3.95480901e-01 2.35267356e-01 -6.19835973e-01 -7.46914744e-01
8.17012116e-02 -1.26153827e+00 -3.39728922e-01 1.35127520e-02
-6.57342747e-02 -5.62021852e-01 1.16412783e+00 -6.40709937e-01
1.24513388e+00 -2.07932258e+00 4.26342785e-01 -4.75085109e-01
-1.25998989e-01 5.36678076e-01 -1.97813585e-01 5.69132447e-01
1.02211677e-01 -3.00391346e-01 -1.73449352e-01 -4.68331844e-01
8.13236013e-02 2.97972202e-01 -7.93546811e-02 7.01055229e-01
7.84644410e-02 1.10963738e+00 -1.09471965e+00 -5.29065371e-01
7.15244591e-01 4.23959643e-01 -8.52310210e-02 1.34005427e-01
-2.28992715e-01 6.72111154e-01 -5.62228799e-01 7.52678156e-01
-1.15314528e-01 -1.87102705e-01 2.87507147e-01 1.08930491e-01
-2.08799750e-01 1.98863328e-01 -8.98845673e-01 1.97583497e+00
-2.09849581e-01 8.67976189e-01 -3.24975789e-01 -1.05902064e+00
3.96696121e-01 6.24423265e-01 1.05304027e+00 -7.45568097e-01
2.50806510e-01 1.01995289e-01 6.72216266e-02 -7.47840405e-01
4.61419851e-01 2.32669100e-01 -1.23955663e-02 3.77020240e-01
1.13188505e-01 5.31455576e-01 6.54130638e-01 -1.06725328e-01
1.54725432e+00 8.65489185e-01 5.97647190e-01 3.80835176e-01
5.63084543e-01 1.39204204e-01 5.82370758e-01 6.45755291e-01
-8.92043948e-01 3.43389660e-01 3.31454188e-01 -5.31327069e-01
-7.94399798e-01 -6.50622666e-01 4.77319062e-01 1.20169008e+00
9.97051895e-02 -3.74419779e-01 -7.14077353e-01 -1.05689287e+00
-3.51355106e-01 3.90966207e-01 -7.82378674e-01 -4.82155010e-02
-1.07496965e+00 -3.23956817e-01 4.95152235e-01 1.08197904e+00
8.34158242e-01 -1.86458278e+00 -1.33493125e+00 5.58305740e-01
-2.36393794e-01 -1.64882874e+00 -3.26239169e-01 -1.31810620e-01
-8.58814061e-01 -1.16946137e+00 -8.60462666e-01 -5.98180175e-01
1.25040412e-01 5.08670211e-01 7.96654701e-01 -3.02381635e-01
-2.89953381e-01 6.23457491e-01 -7.54333615e-01 -3.97553593e-02
-2.05364108e-01 -6.50976300e-02 2.82856878e-02 1.71213448e-01
3.29822093e-01 -5.95209181e-01 -7.81913221e-01 5.45322418e-01
-7.13601053e-01 -1.53375641e-01 8.17077637e-01 7.02959299e-01
2.99337178e-01 -2.79764812e-02 2.81130731e-01 -2.83179522e-01
-7.53564835e-02 -1.90866500e-01 -2.98986763e-01 1.85638666e-01
-9.73953232e-02 -1.59130260e-01 4.21368659e-01 -7.99038470e-01
-9.54344392e-01 4.70006824e-01 5.10007925e-02 -7.16316640e-01
-3.38533908e-01 3.91351908e-01 1.05977297e-01 -9.87807438e-02
3.38520408e-01 2.92353332e-01 -2.21818417e-01 -3.95915449e-01
3.58779132e-01 4.24060196e-01 6.87001526e-01 1.77384317e-01
3.17793697e-01 7.67718315e-01 -7.55938888e-02 -8.47237527e-01
-5.89663923e-01 -8.33931744e-01 -1.19842458e+00 -6.10945344e-01
1.21299124e+00 -8.34539950e-01 -8.63863170e-01 9.10059452e-01
-1.08520484e+00 -6.68780684e-01 -4.31692451e-02 8.43093514e-01
-9.13352251e-01 5.50457358e-01 -8.19342852e-01 -1.07468832e+00
1.20268203e-03 -9.63407755e-01 1.30195248e+00 -1.23698553e-02
-3.89144391e-01 -7.49191821e-01 2.38403365e-01 3.10209125e-01
5.27874306e-02 3.97800058e-01 9.11816210e-02 -4.95969802e-01
-7.38759637e-01 -4.69937950e-01 5.69165237e-02 2.45247021e-01
2.34861061e-01 -2.52729505e-01 -6.65309191e-01 -1.36915609e-01
-1.22155339e-01 -4.58646804e-01 1.15620780e+00 4.54763412e-01
7.31782973e-01 -1.05188802e-01 -5.74642181e-01 4.91514280e-02
8.21780503e-01 4.99205410e-01 8.76124084e-01 4.94206846e-01
7.67672598e-01 6.44231439e-01 1.18494332e+00 4.78381425e-01
1.62245989e-01 1.00613165e+00 3.33758086e-01 3.54184240e-01
-3.15393582e-02 -8.28509778e-02 8.84935260e-01 6.03733897e-01
-4.32049155e-01 -2.85429001e-01 -9.11490619e-01 7.07941592e-01
-2.58281898e+00 -1.32968950e+00 1.24550052e-01 1.89968669e+00
2.79569536e-01 1.41050041e-01 5.20172715e-01 2.24609792e-01
5.30305266e-01 5.52068532e-01 -5.08895814e-01 1.24208987e-01
5.19431047e-02 -7.31732994e-02 3.58424515e-01 -4.75423075e-02
-1.89940989e+00 1.26286066e+00 6.32802677e+00 6.20715380e-01
-1.06354702e+00 1.98213816e-01 1.23976722e-01 -1.32793829e-01
8.97166610e-01 -2.23843396e-01 -3.54500324e-01 2.15901151e-01
8.95770133e-01 1.25593886e-01 1.72806635e-01 8.13439310e-01
6.20611012e-01 -4.24323112e-01 -1.00526845e+00 1.05199087e+00
5.33434451e-02 -8.19043100e-01 -4.66746509e-01 -5.37022538e-02
5.35750747e-01 5.49739301e-02 -2.53369689e-01 5.28659999e-01
1.69700950e-01 -9.01061833e-01 7.00907350e-01 6.26470268e-01
3.11387032e-01 -4.69478220e-01 6.33282125e-01 3.33134949e-01
-1.66712582e+00 -5.30589998e-01 2.38869414e-01 -2.14169368e-01
5.57370007e-01 -8.96914527e-02 -6.59308970e-01 6.21075749e-01
7.58522332e-01 1.51477766e+00 -5.38667262e-01 9.32621658e-01
-4.04029340e-01 4.16221112e-01 -2.20069751e-01 -8.33324566e-02
6.09975636e-01 -5.46401441e-02 6.25779688e-01 1.16634405e+00
3.47004145e-01 1.36371478e-01 6.05857730e-01 2.03615367e-01
2.05983073e-01 -1.39657229e-01 -7.43633032e-01 -5.93735278e-01
-5.60854040e-02 1.05854297e+00 -1.03083253e+00 -5.30964971e-01
-4.67384100e-01 1.35185063e+00 1.49643183e-01 2.92702079e-01
-9.97658670e-01 7.46771544e-02 5.60355365e-01 -3.22578013e-01
6.85923636e-01 -7.05971837e-01 4.05462146e-01 -1.23602450e+00
2.33484402e-01 -8.96192372e-01 5.48337162e-01 -7.40553379e-01
-7.59153664e-01 3.91400546e-01 1.90896243e-02 -1.70506930e+00
-8.25918198e-01 -6.72264814e-01 -3.23734730e-01 -9.91654582e-03
-8.82753313e-01 -1.33997130e+00 -1.65198401e-01 4.85706955e-01
1.00965834e+00 3.86931822e-02 6.62506878e-01 2.94881254e-01
-6.43962085e-01 5.46767563e-02 -1.67168066e-01 3.63035202e-01
5.51700413e-01 -9.80083644e-01 4.25006926e-01 1.11788809e+00
5.06983876e-01 1.76927567e-01 5.32089591e-01 -7.21044898e-01
-1.37106824e+00 -1.00310147e+00 7.14754701e-01 -4.97675329e-01
9.33584034e-01 -2.10149199e-01 -6.61957383e-01 9.07894492e-01
2.91415602e-01 3.16430852e-02 1.68468401e-01 -2.53823668e-01
-3.92083824e-02 3.14082831e-01 -6.91453874e-01 8.33537400e-01
1.62575114e+00 -5.81022859e-01 -5.87436020e-01 4.14955854e-01
4.02725875e-01 -2.30748504e-01 -6.40045822e-01 6.99661851e-01
8.25528681e-01 -9.57392037e-01 7.75278449e-01 -5.56800902e-01
2.96491712e-01 -4.47588950e-01 -1.57537628e-02 -9.01766181e-01
-1.07285351e-01 -8.02811861e-01 -5.81678271e-01 5.83698928e-01
-1.90850481e-01 -3.43479425e-01 8.47185969e-01 5.67562357e-02
-1.37910664e-01 -6.83519244e-01 -1.07134080e+00 -8.89800251e-01
-6.00515425e-01 -5.49457312e-01 -1.63213596e-01 6.30030811e-01
1.30349681e-01 2.28678092e-01 -7.59600222e-01 -1.83145896e-01
2.42677048e-01 2.59834155e-02 7.87817955e-01 -8.37452054e-01
-2.37232655e-01 -5.52807093e-01 -9.07924891e-01 -1.34371352e+00
3.41335773e-01 -3.46302062e-01 3.01817864e-01 -1.51664281e+00
6.98834881e-02 4.90312546e-01 -4.04640853e-01 6.49113476e-01
8.69854167e-02 4.32305634e-01 3.97641003e-01 2.57791400e-01
-1.24027741e+00 8.60083640e-01 1.12331963e+00 -1.39261991e-01
-1.94171339e-01 -4.26682495e-02 3.20716709e-01 8.91312301e-01
6.12015545e-01 -2.45310456e-01 -2.35364363e-01 -5.38648814e-02
-4.07940626e-01 1.61144793e-01 6.65352166e-01 -1.53183448e+00
3.77659887e-01 -8.44170153e-02 2.79821813e-01 -7.90484488e-01
6.78883135e-01 -6.77107275e-01 -8.58080015e-02 6.78065836e-01
-1.93275943e-01 3.50605845e-02 7.31844082e-02 8.14405084e-01
-4.48867708e-01 1.04544029e-01 5.44004917e-01 -2.35038266e-01
-1.49046493e+00 2.38775119e-01 -7.78347671e-01 -3.41178298e-01
1.29895914e+00 -2.75077403e-01 -3.43099348e-02 -5.02801359e-01
-9.41158175e-01 1.39796466e-01 2.29884282e-01 6.31625235e-01
5.73762059e-01 -1.41114533e+00 -3.97558570e-01 -2.46050894e-01
1.50093973e-01 -5.99080443e-01 4.51814383e-01 1.33323681e+00
-3.38288426e-01 7.38702893e-01 -3.54935914e-01 -6.40768707e-01
-1.36707854e+00 6.46444321e-01 2.90536553e-01 -5.14347196e-01
-1.00660920e+00 4.09970582e-01 -7.94760324e-03 1.44161442e-02
3.21999371e-01 -3.03353935e-01 -5.38847387e-01 2.09084898e-01
5.44580936e-01 6.04950070e-01 -3.70185137e-01 -9.02313530e-01
-4.16697115e-01 4.34743315e-01 1.55982882e-01 -3.54049742e-01
1.15906549e+00 -4.36439440e-02 7.14076906e-02 7.37778008e-01
1.07251656e+00 -5.86737156e-01 -1.56567085e+00 -1.06638774e-01
4.07039344e-01 -4.29005682e-01 -3.26137900e-01 -5.72126687e-01
-8.85707736e-01 7.09155202e-01 8.42822313e-01 1.48936123e-01
1.21040630e+00 -4.82777786e-03 1.00506961e+00 6.79311454e-01
6.84201181e-01 -1.27230024e+00 4.44694251e-01 7.20417261e-01
7.75066972e-01 -1.34893429e+00 -1.03191003e-01 -2.80452341e-01
-8.19223225e-01 1.05350900e+00 5.22605300e-01 -1.54010370e-01
3.48051041e-01 -2.56033361e-01 4.12734784e-02 -1.00359415e-04
-7.10359752e-01 -6.09876454e-01 2.84544736e-01 2.45919049e-01
3.02995354e-01 -3.68517675e-02 -4.38647091e-01 1.92174882e-01
3.98298115e-01 3.38120073e-01 2.55913496e-01 1.36858749e+00
-2.59594917e-01 -1.06023920e+00 -1.16310917e-01 1.84482545e-01
-4.48788047e-01 3.19636256e-01 -4.99659956e-01 1.00569892e+00
-7.74808079e-02 9.65017319e-01 -1.34566426e-01 -4.81818646e-01
4.11582023e-01 2.45463461e-01 5.27630746e-01 -3.76918823e-01
-3.69472951e-01 2.52095044e-01 3.46880406e-01 -1.26484573e+00
-1.10828781e+00 -1.12061381e+00 -1.30931103e+00 1.77795380e-01
6.93512633e-02 -3.63366753e-01 2.22882509e-01 1.16496432e+00
3.79595935e-01 6.51390851e-01 3.26778680e-01 -1.35465682e+00
-3.16236049e-01 -1.33887744e+00 -3.84886146e-01 4.99778926e-01
2.62696713e-01 -1.10334480e+00 -1.62450060e-01 1.72460899e-01] | [8.209405899047852, 0.5016278028488159] |
e539a276-b8e7-4ce3-8c2c-712aa68a8d71 | iiit-dwd-lt-edi-eacl2021-hope-speech | null | null | https://aclanthology.org/2021.ltedi-1.14 | https://aclanthology.org/2021.ltedi-1.14.pdf | IIIT_DWD@LT-EDI-EACL2021: Hope Speech Detection in YouTube multilingual comments | Language as a significant part of communication should be inclusive of equality and diversity. The internet user’s language has a huge influence on peer users all over the world. People express their views through language on virtual platforms like Facebook, Twitter, YouTube etc. People admire the success of others, pray for their well-being, and encourage on their failure. Such inspirational comments are hope speech comments. At the same time, a group of users promotes discrimination based on gender, racial, sexual orientation, persons with disability, and other minorities. The current paper aims to identify hope speech comments which are very important to move on in life. Various machine learning and deep learning based models (such as support vector machine, logistics regression, convolutional neural network, recurrent neural network) are employed to identify the hope speech in the given YouTube comments. The YouTube comments are available in English, Tamil and Malayalam languages and are part of the task “EACL-2021:Hope Speech Detection for Equality, Diversity and Inclusion”. | ['Ankit Kumar Mishra', 'Sunil Saumya'] | null | null | null | null | eacl-ltedi-2021-4 | ['hope-speech-detection'] | ['natural-language-processing'] | [-5.91521680e-01 1.44311085e-01 -7.56266952e-01 -2.31454208e-01
-3.17407250e-01 -2.69703306e-02 8.86226356e-01 4.36950177e-01
-3.42046589e-01 8.97508800e-01 1.28598034e+00 -4.08655256e-01
8.76889899e-02 -6.64415121e-01 3.00558537e-01 -1.06213003e-01
3.62967551e-01 1.73817173e-01 -3.23263168e-01 -9.85606432e-01
7.69705117e-01 1.81462109e-01 -1.27284229e+00 1.41121119e-01
9.56631184e-01 2.95238286e-01 -4.83699501e-01 7.90888906e-01
-6.17448211e-01 1.25638092e+00 -5.33761978e-01 -8.67275596e-01
-3.70252877e-01 -4.81282949e-01 -8.75787437e-01 -3.11494976e-01
2.27586761e-01 -4.89574790e-01 -2.89600670e-01 1.28931653e+00
9.86796021e-01 -9.98036340e-02 5.16207576e-01 -1.24673271e+00
-1.02432537e+00 9.81014669e-01 -4.30461496e-01 2.45923802e-01
7.42398977e-01 -4.01531339e-01 6.15313649e-01 -8.18312943e-01
6.57944083e-01 1.50394750e+00 6.33684278e-01 5.14809608e-01
-4.21433717e-01 -7.80904889e-01 -4.06918854e-01 4.07270640e-02
-1.12111318e+00 -8.29457521e-01 8.70293200e-01 -6.19943976e-01
7.66360462e-01 6.62892401e-01 9.78558421e-01 1.19986403e+00
1.15701333e-01 5.91671705e-01 8.28938842e-01 -3.41255844e-01
-2.20751792e-01 6.95405960e-01 -8.46911818e-02 6.05620623e-01
-3.22994649e-01 -4.24945235e-01 -6.11117005e-01 -3.41593981e-01
-1.61547381e-02 2.26379991e-01 2.09288802e-02 5.59747100e-01
-9.30346012e-01 1.30253911e+00 3.81210864e-01 4.84574318e-01
-5.57231531e-02 -4.10784930e-01 8.59424293e-01 3.33332717e-01
8.10863316e-01 -6.59579635e-02 2.65913159e-01 -9.29346979e-01
-8.96759748e-01 5.23641668e-02 9.22226608e-01 3.18531305e-01
1.80673033e-01 1.40875569e-02 1.34709524e-02 1.44116902e+00
5.62208593e-01 5.25907695e-01 9.32058334e-01 -6.84401035e-01
2.91789651e-01 8.78564179e-01 -2.59455889e-01 -1.33315575e+00
-4.96850193e-01 -4.46522325e-01 -1.02964485e+00 -1.53909959e-02
-2.15160456e-02 -3.96020383e-01 -2.38015220e-01 1.41408908e+00
2.40999669e-01 -3.79434556e-01 1.84388399e-01 6.01519048e-01
1.55687547e+00 7.61869729e-01 9.10503641e-02 -3.07227254e-01
9.87153888e-01 -7.63386071e-01 -9.25940633e-01 2.58147746e-01
7.67680228e-01 -1.31081903e+00 7.51582921e-01 1.40392557e-01
-1.07415807e+00 -2.42167428e-01 -7.03890085e-01 -3.74522507e-01
-6.79290831e-01 6.64836243e-02 5.20357072e-01 1.14558136e+00
-9.11615670e-01 6.01030231e-01 -1.28330544e-01 -8.52275610e-01
5.66380382e-01 1.83653757e-01 -2.70364761e-01 3.86376232e-01
-1.28142905e+00 7.53464699e-01 -1.53058171e-01 -6.00757338e-02
-4.96838503e-02 -2.48095304e-01 -9.03025389e-01 -3.71978700e-01
-2.72712439e-01 -1.24228865e-01 7.26361454e-01 -1.23042595e+00
-1.26801407e+00 1.40052569e+00 -1.35922536e-01 -2.91018724e-01
6.53990269e-01 -2.38286018e-01 -8.11656356e-01 -4.39547092e-01
1.73378021e-01 6.17604196e-01 5.18800080e-01 -4.18411404e-01
-4.92016912e-01 -5.28524697e-01 -1.54159460e-02 1.38430789e-01
-8.82025480e-01 8.54892552e-01 3.90160561e-01 -4.46690500e-01
-2.66711920e-01 -6.38488889e-01 1.85049340e-01 -1.56365976e-01
-8.29389572e-01 -5.18379271e-01 1.24593925e+00 -1.11594605e+00
1.57657564e+00 -2.18028831e+00 -1.59864992e-01 -1.64452970e-01
3.87986958e-01 3.45070243e-01 4.71003532e-01 9.53103721e-01
2.25779384e-01 7.03803957e-01 4.56408113e-01 -5.00150882e-02
1.86161068e-03 1.34194607e-03 7.99867809e-02 5.58245838e-01
-2.47257963e-01 5.24040401e-01 -7.29524612e-01 -5.29127419e-01
4.75228764e-02 7.04664886e-01 -5.67505956e-01 -3.81158367e-02
5.49583018e-01 3.20530385e-01 -2.62700617e-01 4.85018581e-01
6.06697619e-01 -1.12113200e-01 1.50391832e-02 3.46136361e-01
-8.73586237e-01 4.40621972e-01 -6.02184653e-01 8.77067804e-01
-2.97581524e-01 1.12077963e+00 -1.86914746e-02 -8.69932652e-01
1.30888593e+00 2.90982932e-01 2.27124080e-01 -8.27434599e-01
5.07146239e-01 4.55565214e-01 3.30599099e-01 -8.11660528e-01
8.84542882e-01 5.41209914e-02 4.93796775e-03 2.93996483e-01
-4.03589189e-01 2.47190252e-01 -7.71786496e-02 4.06553477e-01
1.60177201e-01 -4.22191173e-01 6.41465962e-01 -2.83877462e-01
7.97822177e-01 -7.01482534e-01 3.21514338e-01 1.00020982e-01
-5.92334092e-01 3.69623035e-01 6.80987000e-01 -5.06655633e-01
-1.17267144e+00 -6.64574087e-01 -2.85585016e-01 1.22046256e+00
-2.00533718e-01 -2.90477425e-01 -3.45226437e-01 -4.06759121e-02
-1.59693599e-01 6.09509230e-01 -3.31179082e-01 -1.49830788e-01
-2.31231153e-01 -2.66771555e-01 3.64719838e-01 -1.50875822e-01
9.45640683e-01 -9.49824452e-01 -3.05796415e-01 8.99448246e-02
-1.05666466e-01 -7.49606192e-01 -3.12811673e-01 -5.85849464e-01
-4.29854631e-01 -7.62170076e-01 -1.11755013e+00 -8.08414698e-01
2.92917490e-01 -1.74901858e-02 6.32529438e-01 3.52028906e-01
-1.86945096e-01 1.38778716e-01 -4.38045621e-01 -4.77991343e-01
-6.61863089e-01 1.45475641e-01 -3.65310274e-02 -9.64261889e-02
4.44038570e-01 -5.93478322e-01 -3.33289713e-01 -2.08761573e-01
-2.36957893e-01 2.01588243e-01 -1.88816562e-01 6.32773459e-01
-4.42785501e-01 -4.33898807e-01 7.73367345e-01 -1.05676723e+00
1.11285806e+00 -9.81971562e-01 2.53148109e-01 -1.60536453e-01
-3.36500674e-01 -6.59604490e-01 2.82407522e-01 -1.14767924e-01
-6.80121541e-01 -5.83193898e-01 -7.31309950e-01 3.59311789e-01
1.33399814e-01 5.29191911e-01 2.27925271e-01 5.82149699e-02
5.43291926e-01 1.92404360e-01 1.33196324e-01 -3.50761592e-01
-7.77636655e-04 1.48653722e+00 1.19170539e-01 1.42359138e-01
1.48462147e-01 1.85356036e-01 -5.01154840e-01 -1.46609175e+00
-4.69056040e-01 -4.73835886e-01 -2.54934907e-01 -7.12189317e-01
8.82649004e-01 -7.81399667e-01 -8.30443919e-01 6.44591331e-01
-1.10106325e+00 3.53749573e-01 1.99728802e-01 5.94594896e-01
1.30333394e-01 2.54490554e-01 -6.07237756e-01 -1.43219662e+00
-6.87103987e-01 -6.71084285e-01 6.34087741e-01 8.14188778e-01
-5.94978929e-01 -1.27397382e+00 -1.26218408e-01 6.96404636e-01
7.75754213e-01 4.68147755e-01 7.26352632e-01 -1.01377726e+00
4.01588649e-01 -1.37874201e-01 -3.54230911e-01 3.47844243e-01
2.46871352e-01 4.47966784e-01 -6.12202704e-01 1.71675041e-01
-2.52100945e-01 -6.13841712e-01 5.63091397e-01 3.28474432e-01
7.44190216e-01 -9.18324888e-01 1.12825617e-01 -2.29762793e-02
1.09923100e+00 1.39218360e-01 6.61763966e-01 3.20197105e-01
5.60333014e-01 7.05893695e-01 7.15813460e-03 1.06855333e+00
7.02023089e-01 3.13306630e-01 5.20223022e-01 2.42282986e-03
-3.12763150e-03 -3.55293065e-01 4.70303565e-01 1.41820419e+00
-2.41875738e-01 4.81098145e-02 -1.07377601e+00 5.90889156e-01
-1.53214133e+00 -1.28368127e+00 -5.59561193e-01 2.25824022e+00
5.92960596e-01 2.00137898e-01 6.62476063e-01 4.52751696e-01
7.66274989e-01 4.38619882e-01 -1.33444875e-01 -1.30115819e+00
-2.27783740e-01 -1.68571323e-01 8.20807517e-02 8.18352878e-01
-9.08207953e-01 7.14506328e-01 5.15407181e+00 6.86486602e-01
-1.64149857e+00 2.95628220e-01 1.11161780e+00 -5.21971621e-02
-5.59176981e-01 -3.11786413e-01 -8.63684475e-01 4.78868484e-01
9.70638692e-01 -7.30044961e-01 2.33787462e-01 7.57213652e-01
5.75036585e-01 -1.49593130e-02 -2.86953598e-01 1.16149783e+00
3.76598477e-01 -1.43728626e+00 -3.96396071e-01 1.86054081e-01
7.91697145e-01 1.66467771e-01 4.76103008e-01 2.78157622e-01
-5.22345901e-02 -1.18659389e+00 4.62842196e-01 2.83485979e-01
6.51296437e-01 -8.68256032e-01 7.25443602e-01 4.66230601e-01
-4.83973563e-01 -1.18913762e-01 -3.72751415e-01 -7.05701649e-01
2.22022176e-01 5.50184131e-01 -5.36040843e-01 -6.43374398e-02
3.64717394e-01 1.09726691e+00 -4.30025399e-01 8.57511401e-01
4.82466519e-02 5.49340248e-01 -1.72876656e-01 -8.04647565e-01
3.65658909e-01 -8.04777220e-02 6.44286394e-01 1.28111351e+00
5.16965091e-01 -2.62123942e-01 2.10589096e-02 4.03465569e-01
-3.53496432e-01 9.53829944e-01 -9.19900537e-01 -7.08192945e-01
3.28335166e-01 1.06756186e+00 -4.10431027e-01 -1.40302524e-01
-3.65156859e-01 6.68398917e-01 8.70228261e-02 -2.28602607e-02
-4.78856415e-01 -4.42482382e-01 5.31707704e-01 5.71864307e-01
-6.82645202e-01 -3.72188762e-02 -6.02822416e-02 -9.21932697e-01
-4.96818542e-01 -8.86480808e-01 8.24969858e-02 -3.99411321e-01
-1.09350157e+00 3.32969278e-01 -6.97810829e-01 -8.73967588e-01
-2.39886612e-01 -3.36651325e-01 -9.79352057e-01 8.18829060e-01
-1.14177966e+00 -9.14091587e-01 -1.98841058e-02 5.58297992e-01
6.58100069e-01 -6.11375272e-01 7.59497106e-01 7.01349199e-01
-5.36279380e-01 5.07932186e-01 1.30058512e-01 3.47068578e-01
5.75307369e-01 -7.13554263e-01 -7.29719624e-02 2.26298600e-01
-8.90299901e-02 4.48185414e-01 6.45395458e-01 -5.94855666e-01
-9.64510322e-01 -5.20817876e-01 2.02576518e+00 1.79219395e-01
7.87224114e-01 -1.78371519e-01 -2.16607824e-01 2.80432791e-01
7.22234070e-01 -5.31892121e-01 1.10736263e+00 4.45060760e-01
-6.06491640e-02 1.72984853e-01 -1.23643076e+00 7.70133436e-01
9.01237905e-01 -7.71525204e-01 -1.83558539e-01 9.25519407e-01
4.15750086e-01 -2.56185800e-01 -6.33583665e-01 -1.65585309e-01
7.47021556e-01 -1.54358768e+00 7.58689582e-01 -9.94971156e-01
1.09232342e+00 6.92124188e-01 -1.63882673e-01 -1.01617026e+00
-2.42007170e-02 -7.66739547e-01 3.91122401e-01 1.81728709e+00
5.15883267e-01 -8.40301633e-01 7.58319676e-01 6.97392523e-01
1.61437705e-01 -7.77851045e-01 -1.09729433e+00 -3.54149863e-02
2.31014982e-01 -1.37584791e-01 1.99254915e-01 1.43286419e+00
4.30554658e-01 6.51017964e-01 -9.75819945e-01 -6.37418032e-01
3.78341973e-02 -3.58547270e-01 7.56604373e-01 -1.22681248e+00
2.31730744e-01 -8.29472899e-01 -5.94689310e-01 -5.22440970e-01
-1.75917119e-01 -8.91268611e-01 -9.64590430e-01 -1.55085969e+00
3.93486142e-01 -2.24495500e-01 3.17797333e-01 5.89102358e-02
3.08142930e-01 1.07777096e-01 3.82028133e-01 1.27795577e-01
-4.07862633e-01 6.09223068e-01 1.27975512e+00 -3.02977175e-01
-2.23071352e-01 2.38826320e-01 -1.16157484e+00 7.25257456e-01
1.00721359e+00 -1.98782548e-01 -1.69142380e-01 -3.38627063e-02
9.22477245e-01 1.76658198e-01 5.89747056e-02 -6.72385693e-01
2.17116654e-01 -1.08196810e-01 2.48545259e-01 -4.61996436e-01
4.28038210e-01 -2.52736241e-01 -9.19100791e-02 9.15734768e-01
-5.75075924e-01 6.31264895e-02 -3.05009604e-01 -2.15558022e-01
-4.13686931e-01 -3.18313956e-01 7.14589357e-01 2.55931932e-02
-1.29629031e-01 1.26785114e-01 -3.76063138e-01 2.61983693e-01
6.82211876e-01 -2.52116263e-01 -7.18343198e-01 -1.24213850e+00
-6.95639610e-01 9.47567374e-02 1.19853176e-01 7.55035102e-01
6.10347927e-01 -1.51959085e+00 -1.30800021e+00 5.02386689e-02
-1.90707907e-01 -9.63199794e-01 1.98365957e-01 1.01193309e+00
-4.72969443e-01 1.49662346e-01 -4.22949910e-01 -1.70590520e-01
-1.69872499e+00 -4.34186459e-02 1.52067924e-02 7.80789554e-02
-4.15197819e-01 1.13063180e+00 -5.42024016e-01 -6.74261868e-01
2.04865336e-01 4.59394693e-01 -1.01280260e+00 3.98816794e-01
7.40987957e-01 8.02326679e-01 -6.74552739e-01 -1.43617427e+00
-2.81818688e-01 4.13520634e-01 -4.37108278e-02 8.67825523e-02
1.29022551e+00 -1.52169913e-01 -5.68400681e-01 6.18710935e-01
1.73216677e+00 6.15220904e-01 1.29963085e-02 2.72907495e-01
-1.45675898e-01 -8.01923752e-01 -6.69063628e-02 -4.93235499e-01
-9.14329350e-01 1.15281379e+00 5.75290918e-01 7.62409687e-01
6.08856320e-01 -1.85314178e-01 8.50103080e-01 -2.01140881e-01
-2.03747377e-01 -1.39774716e+00 -5.38444286e-03 5.70054173e-01
1.19477928e+00 -1.68083143e+00 4.89936909e-03 -1.48663953e-01
-6.17088437e-01 1.40664673e+00 2.84137309e-01 1.36369422e-01
1.02931142e+00 -1.92789257e-01 2.05496877e-01 1.63340345e-01
-4.04105306e-01 1.29715726e-01 -9.71746370e-02 6.50858819e-01
1.24632514e+00 2.47115940e-01 -1.20000017e+00 3.76001209e-01
-7.50154495e-01 5.78322895e-02 6.60712957e-01 2.55788058e-01
-9.82730985e-01 -1.09284234e+00 -9.65062901e-02 5.91362417e-01
-1.08962381e+00 -1.84558004e-01 -7.37144709e-01 3.64732504e-01
2.49462068e-01 1.10805833e+00 -8.93708840e-02 -4.40873563e-01
-3.14076543e-01 -9.31444392e-02 -2.81375885e-01 -1.83942825e-01
-8.44138563e-01 -5.85374795e-02 7.75204599e-01 4.99016084e-02
-4.62982923e-01 -6.70389831e-01 -1.15886533e+00 -1.18089819e+00
1.49122179e-01 2.00430781e-01 1.07112098e+00 7.45318353e-01
6.60650209e-02 1.12218849e-01 8.29569936e-01 -3.38243634e-01
-2.21549973e-01 -9.47557211e-01 -5.25608242e-01 9.40560773e-02
2.41339400e-01 -7.38221705e-02 -2.46768430e-01 -5.46416640e-01] | [8.932292938232422, 10.702166557312012] |
e5731280-f904-4f8a-97cb-52ef29f01d72 | analysis-of-climate-campaigns-on-social-media | 2305.06174 | null | https://arxiv.org/abs/2305.06174v2 | https://arxiv.org/pdf/2305.06174v2.pdf | Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging | Climate change is the defining issue of our time, and we are at a defining moment. Various interest groups, social movement organizations, and individuals engage in collective action on this issue on social media. In addition, issue advocacy campaigns on social media often arise in response to ongoing societal concerns, especially those faced by energy industries. Our goal in this paper is to analyze how those industries, their advocacy group, and climate advocacy group use social media to influence the narrative on climate change. In this work, we propose a minimally supervised model soup [57] approach combined with messaging themes to identify the stances of climate ads on Facebook. Finally, we release our stance dataset, model, and set of themes related to climate campaigns for future work on opinion mining and the automatic detection of climate change stances. | ['Dan Goldwasser', 'Ruqi Zhang', 'Tunazzina Islam'] | 2023-05-06 | null | null | null | null | ['opinion-mining'] | ['natural-language-processing'] | [ 5.46494603e-01 4.50603217e-01 -5.45479953e-01 -2.18801051e-01
-5.09749055e-01 -7.85558701e-01 9.33148921e-01 9.75392938e-01
-2.75106072e-01 6.18384659e-01 1.07366550e+00 -8.40684652e-01
2.18165442e-01 -1.14126480e+00 -6.28023624e-01 -5.20574510e-01
3.39286804e-01 -3.23778361e-01 -5.73644228e-02 -4.36694235e-01
8.47604811e-01 -2.13225439e-01 -1.03092277e+00 2.89563686e-01
7.51739383e-01 4.63053197e-01 -3.33796181e-02 2.70652622e-01
-4.97384876e-01 9.52037573e-01 -4.84758675e-01 -1.35998830e-01
-4.39579934e-02 -5.30897498e-01 -5.57478309e-01 1.63706969e-02
4.97217625e-01 2.04691112e-01 5.04343688e-01 1.13849998e+00
3.69687200e-01 -2.56414622e-01 5.78153551e-01 -9.82320130e-01
-4.13467973e-01 1.13448048e+00 -8.15913975e-01 3.77309442e-01
2.35358387e-01 -1.20163158e-01 1.02229416e+00 -3.49161208e-01
9.19578135e-01 1.25992835e+00 6.39652312e-01 -9.39274728e-02
-7.97888577e-01 -8.79470825e-01 6.98989928e-01 -9.62205827e-02
-5.44571042e-01 -3.40018153e-01 1.16367185e+00 -9.32216406e-01
5.78684747e-01 6.36926055e-01 9.01930630e-01 1.09523463e+00
4.26800340e-01 7.78476596e-02 1.77641988e+00 -3.84137660e-01
4.51584220e-01 3.27718347e-01 4.98631924e-01 1.41926765e-01
4.83340561e-01 -3.81036431e-01 -3.70740473e-01 -7.85402775e-01
-2.16467291e-01 4.91685532e-02 1.31908745e-01 4.64281112e-01
-1.01710773e+00 1.30016756e+00 4.59472239e-01 4.24938589e-01
-4.74789977e-01 1.42401069e-01 1.93906948e-01 1.98636159e-01
1.43674719e+00 3.64157975e-01 -2.98283458e-01 -1.09884247e-01
-3.30006719e-01 1.98893458e-01 1.09325242e+00 2.89306283e-01
7.87340939e-01 -6.49585903e-01 3.49060416e-01 6.32617474e-01
6.55675828e-01 6.55379534e-01 -2.50579864e-01 -8.29887629e-01
4.27780420e-01 9.72250938e-01 5.61704859e-02 -1.55844092e+00
-4.32329774e-01 -3.39311630e-01 -4.27995682e-01 7.82866217e-03
8.11469927e-02 -8.27005208e-01 -1.90271303e-01 1.44163156e+00
8.78213048e-01 -9.84675288e-02 -1.28023639e-01 4.73183662e-01
5.97387731e-01 8.11147213e-01 6.81428850e-01 -6.11874640e-01
1.46260214e+00 -2.95676857e-01 -9.64997828e-01 -3.08822364e-01
5.50081372e-01 -1.07820106e+00 6.57321811e-01 -1.98503718e-01
-6.19036794e-01 -4.07915749e-03 -8.01355362e-01 3.12601537e-01
-8.83854449e-01 -5.56736708e-01 6.05269074e-01 6.19198143e-01
-4.50189799e-01 4.05383587e-01 -1.77250549e-01 -8.19349825e-01
4.07694817e-01 -3.69955301e-01 3.23938519e-01 5.93930602e-01
-1.24075699e+00 9.25447762e-01 -1.68541804e-01 -3.44714463e-01
-2.56517739e-03 -9.00077283e-01 -5.59868693e-01 -7.64382005e-01
5.00532687e-01 -4.02096152e-01 9.63039160e-01 -1.01162279e+00
-8.13724935e-01 1.14636290e+00 -2.05086768e-01 -3.26819390e-01
3.26615632e-01 -1.02909341e-01 -8.48300636e-01 -2.67463446e-01
3.83785814e-01 2.53372431e-01 6.29017293e-01 -1.11509943e+00
-9.56634223e-01 -5.23789406e-01 4.06294376e-01 -5.95546030e-02
-6.46038234e-01 6.46093309e-01 6.35213852e-01 -3.33946556e-01
-2.20063835e-01 -1.33427107e+00 -4.69078243e-01 -4.40074712e-01
-5.35401464e-01 -5.45523703e-01 1.21232426e+00 -5.39198101e-01
1.51892328e+00 -2.07520890e+00 -2.49188691e-01 9.12288353e-02
2.06252292e-01 -2.49046609e-01 4.35126275e-01 9.21006918e-01
1.52499899e-01 9.52387393e-01 -5.02208136e-02 2.47414842e-01
9.39526856e-02 -1.57061458e-01 -6.21952891e-01 5.41298985e-01
-2.75768247e-02 3.40503931e-01 -1.14031327e+00 -3.91421705e-01
-1.98526397e-01 2.69292276e-02 -3.93780798e-01 -4.43744361e-01
-6.01771712e-01 5.35131752e-01 -8.58614445e-01 3.32452714e-01
5.51250041e-01 -4.69802797e-01 5.33261180e-01 -1.92955405e-01
-1.10890198e+00 6.76414192e-01 -5.71896076e-01 7.15378761e-01
-2.45866999e-01 8.41372669e-01 1.28863588e-01 -2.52425134e-01
7.23585010e-01 1.07853524e-01 8.02762747e-01 -3.43560636e-01
3.17778677e-01 4.67870645e-02 -1.02552541e-01 -4.17193919e-01
6.22687995e-01 -1.05690569e-01 -4.43673164e-01 1.01154375e+00
-1.13819206e+00 -1.29461229e-01 -7.06494078e-02 2.30795056e-01
7.35716522e-01 -1.52162239e-01 6.31072044e-01 -5.39365709e-01
3.79257709e-01 4.68886971e-01 3.44379216e-01 1.99367389e-01
-3.00759047e-01 -1.41446590e-02 5.67322910e-01 -5.61517954e-01
-8.50635350e-01 -1.04419433e-01 -3.07248741e-01 1.12389457e+00
1.36125401e-01 -4.93773013e-01 -3.96903515e-01 -7.32865214e-01
4.29921709e-02 1.01316094e+00 -6.55169964e-01 3.52349520e-01
-7.22346187e-01 -1.11474466e+00 -1.78829938e-01 -2.30197474e-01
7.87528872e-01 -7.48097599e-01 -4.44047093e-01 3.88757914e-01
-4.89804178e-01 -9.64170337e-01 -3.49141777e-01 -1.25970513e-01
-4.68679249e-01 -1.44150567e+00 -1.32161275e-01 -5.19344389e-01
6.32335305e-01 4.28737372e-01 8.35721016e-01 -3.24762225e-01
2.69535363e-01 3.71050388e-01 -3.09465498e-01 -1.41088390e+00
-9.03915226e-01 3.24836612e-01 -2.73893535e-01 -3.96994762e-02
4.63621438e-01 -5.87613523e-01 -6.89352512e-01 2.53822803e-01
-7.20839679e-01 1.26635090e-01 -4.37393524e-02 -3.94322723e-01
1.81372657e-01 -1.15313187e-01 9.28382635e-01 -1.41325092e+00
7.31373727e-01 -1.27678704e+00 -2.52024740e-01 -2.14770302e-01
-7.08493590e-01 -6.63114071e-01 -2.28030816e-01 -2.86247939e-01
-1.02781129e+00 -3.13378036e-01 -1.37922261e-02 8.15792203e-01
-1.85570508e-01 9.64515805e-01 3.50264519e-01 1.22057647e-01
9.79573965e-01 -6.01864874e-01 1.35387629e-01 -3.54003221e-01
3.41486841e-01 9.95195210e-01 -5.50532758e-01 -8.84306729e-02
9.35509980e-01 8.87488186e-01 -2.92548478e-01 -9.42242622e-01
-1.37146056e+00 -5.77366769e-01 2.99450643e-02 -1.01328444e+00
1.09842396e+00 -1.22096646e+00 -5.44845521e-01 4.11096096e-01
-1.16122377e+00 -9.30365846e-02 9.55292210e-02 1.13550186e-01
1.13544606e-01 4.52195555e-02 -2.98161626e-01 -8.98116887e-01
-4.97957766e-01 -9.63791087e-02 4.01023000e-01 2.70008236e-01
-8.21434259e-01 -1.30607212e+00 5.54707229e-01 7.60784984e-01
8.97255480e-01 1.05316651e+00 7.31464744e-01 -2.61638135e-01
-3.86019021e-01 3.26839834e-01 -1.05375685e-02 1.94092514e-03
8.42847049e-01 2.57060975e-02 -8.37695897e-01 -6.62412345e-02
1.44910589e-01 5.34445979e-02 5.92112422e-01 2.60155082e-01
4.06712294e-01 -7.09230244e-01 -5.05381167e-01 -5.97771227e-01
1.29862809e+00 1.07138827e-01 1.89939737e-01 7.91927814e-01
5.55710554e-01 1.08844817e+00 5.62257528e-01 4.80857909e-01
6.31598294e-01 1.38555676e-01 4.00019228e-01 -2.85353124e-01
1.17629297e-01 -1.13127701e-01 8.05585563e-01 8.36632013e-01
-1.34520262e-01 8.66599306e-02 -1.01657248e+00 7.17265129e-01
-1.76630604e+00 -1.10931027e+00 -8.72882426e-01 1.34124625e+00
1.02471638e+00 2.30989814e-01 2.00378180e-01 -1.10719800e-01
8.76835287e-01 8.58984172e-01 -3.07931066e-01 -4.28216517e-01
-2.49783117e-02 -4.54460710e-01 7.30568469e-01 5.18535256e-01
-1.20215380e+00 5.40618777e-01 6.07048512e+00 1.18365824e-01
-1.18288946e+00 4.13776129e-01 9.26690102e-01 1.54410675e-01
-8.37579370e-01 3.27942401e-01 -1.01358318e+00 3.62093389e-01
9.84651148e-01 -5.48724651e-01 -2.18527317e-01 5.28753936e-01
1.01470888e+00 -3.93772691e-01 -3.12821925e-01 -1.07668098e-02
-3.33408751e-02 -1.63096631e+00 -5.28432190e-01 4.61262286e-01
1.15664089e+00 2.20988482e-01 7.88624883e-02 -1.25306463e-02
4.70700175e-01 -6.62101507e-02 7.32224762e-01 3.08771849e-01
1.50180727e-01 -3.98925602e-01 1.69808209e-01 2.81175256e-01
-7.80260682e-01 -3.09687871e-02 -1.44533947e-01 -6.20669901e-01
4.81871456e-01 1.38467693e+00 -5.77043831e-01 1.20698944e-01
5.94988823e-01 8.72849345e-01 -3.95610750e-01 2.62063354e-01
-1.77463770e-01 1.30355203e+00 -1.18640780e-01 -5.96339405e-01
4.51200068e-01 -3.42962980e-01 9.30175781e-01 1.10490477e+00
1.28347009e-01 1.65717587e-01 2.38435477e-01 5.74572682e-01
-1.30771315e-02 3.73122483e-01 -9.92861271e-01 -5.88705838e-01
2.33846858e-01 1.46867394e+00 -8.15200329e-01 -1.24826096e-01
-3.65188390e-01 -9.71664786e-02 -5.51417395e-02 1.48145750e-01
-8.00493658e-01 2.94776052e-01 9.65411305e-01 6.86864972e-01
-1.26283750e-01 -1.35791823e-01 -2.88526326e-01 -5.41606188e-01
-3.23656529e-01 -9.21145380e-01 2.04525247e-01 -2.49562025e-01
-1.33739889e+00 -5.09523973e-02 1.04264682e-02 -9.95632291e-01
9.35671255e-02 1.33954927e-01 -1.00375748e+00 4.95462418e-01
-1.72756624e+00 -1.17425704e+00 -5.49647920e-02 -4.48555872e-02
2.96161383e-01 3.80039066e-01 6.35154128e-01 2.32635200e-01
-2.89333463e-01 -5.74147463e-01 -2.61074096e-01 -2.31442168e-01
8.37687910e-01 -8.79663169e-01 5.04395247e-01 1.94295943e-01
-5.52258313e-01 5.99920869e-01 1.02461457e+00 -1.18396497e+00
-1.22624660e+00 -1.48701894e+00 1.30658519e+00 -5.02818048e-01
1.31603003e+00 -1.66728407e-01 -4.04567093e-01 5.00057995e-01
9.37708080e-01 -9.37724531e-01 1.36302078e+00 6.05515838e-01
-2.81121433e-02 1.87854633e-01 -1.03299749e+00 9.04882252e-01
1.00549662e+00 -4.26968753e-01 -5.69025576e-01 1.03272736e+00
9.65001881e-01 -9.24102440e-02 -9.22289789e-01 -3.94678004e-02
2.24245965e-01 -4.31298971e-01 4.32096720e-01 -6.20638788e-01
7.31716931e-01 -3.18423450e-01 -8.00990611e-02 -1.37179017e+00
-4.32919353e-01 -8.47343683e-01 3.24381500e-01 1.46072316e+00
6.87926948e-01 -8.41826022e-01 4.92402405e-01 5.44852674e-01
5.95493205e-02 -1.69274867e-01 -4.16444719e-01 2.34983433e-02
2.53716201e-01 -4.16706204e-01 4.37710106e-01 1.63920140e+00
1.08792506e-01 5.30513942e-01 -2.90560633e-01 8.01283494e-02
6.66911125e-01 6.23958528e-01 7.38806725e-01 -1.29127204e+00
1.34038731e-01 -2.04556093e-01 3.59502763e-01 -2.84117848e-01
-1.39663726e-01 -7.26432085e-01 -4.34402823e-01 -1.65535855e+00
2.11063728e-01 -4.27993953e-01 -5.62283136e-02 2.29428396e-01
-4.77342270e-02 -5.01227640e-02 1.54087707e-01 1.68091536e-01
-3.38230580e-01 -1.48180211e-02 1.24211347e+00 -4.22347188e-01
-4.39261138e-01 -9.52924117e-02 -1.65273452e+00 9.36454177e-01
1.14099467e+00 -6.75751865e-01 -5.81939630e-02 2.84853488e-01
1.49095941e+00 -5.40398359e-01 2.00875252e-01 -6.14429653e-01
1.52822778e-01 -7.87012637e-01 -1.75211117e-01 -7.73872912e-01
-4.54260081e-01 -7.46629357e-01 6.92162871e-01 5.90081751e-01
-6.01568997e-01 -4.89607267e-02 -1.15336357e-02 7.09804118e-01
-1.93780176e-02 1.47466794e-01 4.20800120e-01 -1.00308619e-01
-2.38902703e-01 -1.28670126e-01 -9.07217145e-01 7.04813153e-02
1.07770741e+00 3.95674646e-01 -9.80576575e-01 -6.41660213e-01
-6.93284750e-01 2.01593935e-01 3.56134027e-01 7.11387932e-01
-1.48756713e-01 -1.12487209e+00 -1.22071218e+00 -6.42945826e-01
1.07923485e-01 -5.36278546e-01 6.69944435e-02 1.03999019e+00
1.14832684e-01 -2.84179114e-03 2.41609246e-01 -2.04259723e-01
-1.28242683e+00 1.05943970e-01 8.42841640e-02 -7.29880109e-02
-2.87264794e-01 1.45726457e-01 -1.51463583e-01 -4.21556145e-01
-2.70537347e-01 -3.05440605e-01 -7.41513193e-01 9.79973972e-01
6.54903769e-01 5.54329634e-01 -2.89231539e-01 -6.45692050e-01
-2.26415247e-01 4.62158293e-01 2.39355832e-01 -4.37439419e-03
1.51822829e+00 -2.53923982e-01 -5.32322526e-01 9.67373192e-01
1.25422251e+00 5.64699888e-01 -4.81142640e-01 -3.48922946e-02
1.79139942e-01 -1.14700459e-01 7.27085397e-02 -7.74464071e-01
-6.50033951e-01 6.45924881e-02 4.53854263e-01 9.77510035e-01
4.72499222e-01 2.43644282e-01 6.94758177e-01 1.30152166e-01
5.68279326e-02 -1.49289882e+00 -1.82841972e-01 4.09112632e-01
1.16766047e+00 -1.21494997e+00 4.20369834e-01 -8.22944403e-01
-2.53321946e-01 7.45576978e-01 2.85934687e-01 2.15688676e-01
1.28538001e+00 2.02835619e-01 4.39730883e-01 -5.56397796e-01
-7.39814043e-01 -1.11609757e-01 -1.46200702e-01 5.62234260e-02
7.73193061e-01 3.18198740e-01 -1.18666410e+00 5.53571582e-02
-6.23165369e-02 -3.20760876e-01 6.36864424e-01 1.15576136e+00
-9.02525306e-01 -1.01111245e+00 -6.20079637e-01 4.00306016e-01
-8.07133079e-01 1.02686532e-01 -1.24606836e+00 5.68637252e-01
3.66698027e-01 1.35809708e+00 7.01182662e-03 -3.44772577e-01
2.33194083e-01 2.60995515e-03 -4.05917406e-01 -4.84221727e-01
-1.23667562e+00 1.02911703e-01 1.14613736e+00 -2.45779693e-01
-1.21034527e+00 -1.24441087e+00 -1.12703884e+00 -6.47852302e-01
-1.99515834e-01 1.55619904e-01 1.16229558e+00 8.96255970e-01
5.06990790e-01 3.43377769e-01 9.93807614e-01 -1.17418639e-01
-1.33369099e-02 -1.07036078e+00 -1.59193501e-01 2.98336655e-01
1.47164121e-01 -2.34932024e-02 -7.03310192e-01 1.19878083e-01] | [8.768917083740234, 9.871844291687012] |
d63f5ac4-df86-4b69-85b5-4e557918759a | fast-convergence-in-learning-two-layer-neural | 2305.13471 | null | https://arxiv.org/abs/2305.13471v2 | https://arxiv.org/pdf/2305.13471v2.pdf | Fast Convergence in Learning Two-Layer Neural Networks with Separable Data | Normalized gradient descent has shown substantial success in speeding up the convergence of exponentially-tailed loss functions (which includes exponential and logistic losses) on linear classifiers with separable data. In this paper, we go beyond linear models by studying normalized GD on two-layer neural nets. We prove for exponentially-tailed losses that using normalized GD leads to linear rate of convergence of the training loss to the global optimum if the iterates find an interpolating model. This is made possible by showing certain gradient self-boundedness conditions and a log-Lipschitzness property. We also study generalization of normalized GD for convex objectives via an algorithmic-stability analysis. In particular, we show that normalized GD does not overfit during training by establishing finite-time generalization bounds. | ['Christos Thrampoulidis', 'Hossein Taheri'] | 2023-05-22 | null | null | null | null | ['generalization-bounds'] | ['methodology'] | [-2.45751232e-01 2.07182035e-01 -2.20909223e-01 -8.56542051e-01
-8.26872766e-01 -2.52074748e-01 -1.20789997e-01 4.12012845e-01
-9.84475136e-01 1.03418744e+00 -3.73715580e-01 -4.83577251e-01
-3.57305229e-01 -6.47328615e-01 -1.02296937e+00 -8.05565059e-01
-5.11304975e-01 3.46949458e-01 1.00943185e-01 2.78405305e-02
-1.53628923e-02 6.25472903e-01 -1.08168852e+00 -1.17343619e-01
9.13530409e-01 1.15128350e+00 -3.33272278e-01 8.80784750e-01
6.54474050e-02 6.00525856e-01 -2.73855835e-01 -3.94257784e-01
3.88363004e-01 -2.83829927e-01 -6.53312743e-01 -3.00511718e-01
6.46550119e-01 -3.56592745e-01 -6.54586032e-02 1.28448939e+00
4.69709754e-01 4.31675524e-01 7.00846136e-01 -1.44185686e+00
-5.68246603e-01 4.24460322e-01 -2.90217221e-01 1.46151766e-01
-3.41475457e-01 -4.26455736e-01 1.09921849e+00 -8.61471355e-01
1.87860072e-01 1.05795527e+00 1.24866855e+00 7.32290983e-01
-1.32031846e+00 -5.84021747e-01 1.80623293e-01 -1.62650511e-01
-1.08905196e+00 -2.13705972e-01 3.26593727e-01 -3.11768383e-01
7.84241796e-01 4.24422175e-02 4.26783264e-02 3.67113441e-01
1.61906272e-01 8.59319746e-01 7.33311772e-01 -5.90893984e-01
1.53219536e-01 4.29334551e-01 5.17442942e-01 1.11766517e+00
4.51421797e-01 8.17308109e-03 -4.90751229e-02 1.66353211e-02
4.14615601e-01 -1.27875790e-01 -2.73697257e-01 -3.31146240e-01
-3.55739862e-01 1.07015467e+00 5.79964817e-01 3.13483596e-01
-2.04987645e-01 3.60904992e-01 5.18484354e-01 6.39202058e-01
9.33753788e-01 1.71429887e-01 -4.54195499e-01 -2.28086719e-04
-8.01122010e-01 2.88652271e-01 1.00493932e+00 8.21542263e-01
5.82018256e-01 7.05870241e-02 -7.79084489e-02 7.99492717e-01
5.31728081e-02 4.39683616e-01 2.98583984e-01 -7.16787577e-01
5.31697571e-01 1.72868997e-01 1.51677102e-01 -7.58949816e-01
-6.32800519e-01 -7.86132812e-01 -6.85291946e-01 4.96216625e-01
8.16028893e-01 -3.34179401e-01 -5.44749856e-01 2.24092364e+00
3.75040323e-02 -3.12238902e-01 -1.04420260e-01 6.61820531e-01
7.57347941e-02 4.57511961e-01 1.78765446e-01 -3.34385931e-01
5.71927309e-01 -7.76023090e-01 -5.34073532e-01 6.63117021e-02
9.66935992e-01 6.79632053e-02 1.48860991e+00 3.87101263e-01
-1.35822785e+00 -2.92092979e-01 -1.12780333e+00 -2.68569320e-01
-1.93479881e-01 7.71840662e-02 1.61372721e-01 7.46786475e-01
-9.08305049e-01 1.11966991e+00 -9.67416406e-01 3.59292515e-02
5.60824335e-01 5.78251243e-01 -3.83209676e-01 -1.93842407e-03
-1.04511380e+00 7.58792877e-01 3.88830304e-01 9.89554301e-02
-6.13050878e-01 -1.02920222e+00 -7.73701370e-01 1.99597627e-01
-7.45704249e-02 -3.92645031e-01 1.28498089e+00 -1.17683697e+00
-1.27535295e+00 9.17433321e-01 -2.78855674e-02 -9.53188002e-01
1.08071792e+00 -3.55154842e-01 1.17767781e-01 -8.24434161e-02
-1.48231804e-01 3.39375228e-01 5.80080032e-01 -8.15292299e-01
-8.03792536e-01 -6.14642382e-01 2.11042285e-01 9.69214067e-02
-8.43772709e-01 -9.91970450e-02 2.39936173e-01 -3.16050798e-01
-2.14973330e-01 -5.66317976e-01 -2.00205669e-01 6.21002495e-01
-6.87372163e-02 -3.19907188e-01 5.02539635e-01 -5.97248077e-01
1.23128617e+00 -2.07230783e+00 -2.31563300e-01 1.27858773e-01
2.69166023e-01 2.49792755e-01 -8.93006567e-03 -2.90157348e-02
-8.15361142e-02 6.98430538e-02 -4.72403884e-01 -8.11199784e-01
4.06701118e-01 2.28042111e-01 -2.55450815e-01 9.20440495e-01
7.17718378e-02 5.68397045e-01 -7.38210917e-01 -2.52072066e-01
-2.47162834e-01 3.55092019e-01 -6.78867936e-01 -6.80902749e-02
-7.04790233e-03 -2.59524643e-01 -1.04810789e-01 1.18042953e-01
8.30357790e-01 -4.84510809e-02 -3.53369534e-01 2.52569914e-01
2.51747109e-02 1.05898038e-01 -9.06362712e-01 1.04385817e+00
-8.76203537e-01 7.33549654e-01 5.06391644e-01 -1.53510678e+00
8.18902373e-01 -1.24408774e-01 3.25012088e-01 -3.44301164e-01
3.16154093e-01 5.16242027e-01 -3.76991391e-01 -1.05360195e-01
8.06034878e-02 -9.35566425e-01 1.91334426e-01 3.55594248e-01
-2.66580633e-03 3.47852170e-01 1.83380455e-01 -2.17392817e-01
5.99727035e-01 -2.82888174e-01 -1.63121790e-01 -6.36227787e-01
6.05735719e-01 -1.40428424e-01 4.22944605e-01 6.88824415e-01
-2.41918921e-01 2.39435762e-01 7.85444260e-01 -1.54465348e-01
-1.01197481e+00 -1.15803111e+00 -5.24268031e-01 1.28585577e+00
-2.63520330e-01 2.04207227e-01 -7.18975425e-01 -8.06979775e-01
3.65557432e-01 8.04904699e-01 -7.98460424e-01 -4.55343008e-01
-3.81503820e-01 -1.00211334e+00 6.79343700e-01 7.41798818e-01
5.27085781e-01 -5.41972220e-01 -4.03701216e-01 1.32204711e-01
3.79403293e-01 -6.58848405e-01 -6.85441613e-01 6.80398464e-01
-1.14002955e+00 -1.01664102e+00 -1.03950346e+00 -1.10447764e+00
8.42007875e-01 -2.48401299e-01 8.73640895e-01 -2.86437750e-01
-1.07290857e-01 2.89626241e-01 2.37656087e-01 -5.65620959e-01
-2.72834271e-01 1.41994566e-01 2.94152856e-01 -5.62973283e-02
2.99216241e-01 -3.96810085e-01 -3.12941968e-01 3.43585491e-01
-7.95616448e-01 -4.13011014e-01 -1.21683325e-03 9.43475962e-01
7.15696275e-01 4.59630877e-01 7.26863801e-01 -7.22587943e-01
1.01827192e+00 -4.68309551e-01 -9.89366114e-01 3.11863959e-01
-9.82681096e-01 3.73648852e-01 1.02900076e+00 -5.42396784e-01
-8.82232547e-01 -2.06972688e-01 -1.09984726e-01 -4.57772285e-01
4.59474951e-01 4.65009540e-01 6.88856319e-02 -2.94369757e-01
8.77575755e-01 -6.86748046e-03 1.81429699e-01 -5.34975767e-01
2.46841207e-01 5.38451314e-01 5.14036000e-01 -8.58035207e-01
5.48044026e-01 4.41620469e-01 3.05486083e-01 -6.59552932e-01
-1.19096649e+00 -1.80293590e-01 -3.76173019e-01 2.34893374e-02
4.64668334e-01 -4.24818307e-01 -9.78246450e-01 4.34085816e-01
-8.17194641e-01 -6.84446454e-01 -7.14378893e-01 7.11869657e-01
-6.62523806e-01 1.58397093e-01 -8.50803852e-01 -1.19323277e+00
-3.21644753e-01 -5.78959584e-01 3.75037909e-01 2.23752353e-02
3.47743779e-01 -1.63934302e+00 1.54100806e-01 -2.05298424e-01
5.15380442e-01 1.87439382e-01 8.35594237e-01 -7.95555413e-01
3.20382416e-01 -6.14765406e-01 -3.54910493e-01 1.16378939e+00
-2.06908882e-01 -1.50627330e-01 -6.97130382e-01 -4.51356083e-01
3.28347236e-01 -4.50383663e-01 1.16995037e+00 8.21644425e-01
1.07884932e+00 -6.28424704e-01 -1.77408513e-02 9.37347531e-01
1.51259637e+00 -1.14545800e-01 9.18300077e-02 5.15785098e-01
3.09178710e-01 6.31835461e-01 4.00091082e-01 4.27343041e-01
-5.43328188e-03 7.63749182e-02 3.26502770e-01 -5.85396662e-02
3.02404910e-01 -1.86391637e-01 2.73279488e-01 3.42602462e-01
2.25244209e-01 1.29797962e-02 -6.10079587e-01 5.96365929e-01
-1.78571713e+00 -7.24775434e-01 -2.99247801e-01 2.63461566e+00
1.08360064e+00 4.85448241e-01 4.76441115e-01 2.47769326e-01
7.77891874e-01 -4.65828896e-01 -9.16060805e-01 -7.84460247e-01
-2.26026371e-01 2.10079089e-01 1.02811015e+00 1.12143981e+00
-1.24154007e+00 5.65559149e-01 6.48397541e+00 9.07082856e-01
-1.03497994e+00 2.06352577e-01 8.86210322e-01 -2.46367678e-01
2.01867204e-02 -5.50857663e-01 -1.01040053e+00 3.26288491e-01
8.91654015e-01 -4.43172336e-01 2.44326323e-01 1.31375921e+00
9.01006460e-02 2.33066559e-01 -1.13373625e+00 7.04776764e-01
-3.26477736e-01 -1.01767027e+00 -4.76223618e-01 1.67912290e-01
8.30507100e-01 7.53511861e-02 3.05305421e-01 4.03996110e-01
3.28426272e-01 -1.00148356e+00 6.95315480e-01 2.20168218e-01
7.93522775e-01 -1.14026713e+00 7.83994317e-01 3.90471697e-01
-8.49337518e-01 -4.36070770e-01 -7.29641199e-01 -1.12210192e-01
5.68823665e-02 7.76739955e-01 -6.52611315e-01 3.00168376e-02
2.72573918e-01 4.29305136e-01 -1.30118430e-01 1.25128710e+00
-8.64559412e-03 5.95853746e-01 -7.69269943e-01 -1.15360960e-01
5.71659267e-01 -2.73807824e-01 3.03570300e-01 1.44744897e+00
6.98190108e-02 -3.00618142e-01 -7.51092359e-02 7.13490784e-01
-3.64751130e-01 2.84744352e-01 -3.63357902e-01 2.12497935e-01
8.73515476e-03 7.91786432e-01 -3.78454268e-01 -5.86080924e-02
-2.48297989e-01 7.96539605e-01 5.54740429e-01 1.83722928e-01
-8.00971150e-01 -9.54522252e-01 6.88462675e-01 1.16999708e-01
3.08561325e-01 -2.68204838e-01 -4.95589405e-01 -8.21077108e-01
3.96200985e-01 -1.47531912e-01 6.60828114e-01 -1.28574759e-01
-1.36225426e+00 5.01621842e-01 -4.33414280e-02 -4.93774652e-01
-1.10576302e-01 -1.05147922e+00 -5.95593274e-01 9.17493045e-01
-1.46837640e+00 -5.84017098e-01 1.26427814e-01 6.00591600e-01
6.24183081e-02 1.17164560e-01 4.36648548e-01 6.86007917e-01
-4.84531373e-01 1.18444610e+00 6.92561924e-01 1.43609583e-01
4.17365879e-01 -1.58265460e+00 -6.37112558e-03 6.87442839e-01
-2.81557471e-01 4.54148173e-01 8.94168258e-01 -1.58325687e-01
-7.68981099e-01 -1.04607618e+00 1.00768661e+00 1.10524595e-01
9.04016256e-01 -2.64657378e-01 -1.08839428e+00 5.99718869e-01
-5.61234295e-01 2.94068694e-01 3.97684127e-01 2.00387076e-01
-3.80536854e-01 -4.12290394e-01 -1.60832429e+00 1.44328475e-01
8.26085329e-01 -4.74120885e-01 -2.08445847e-01 5.37458420e-01
6.11354232e-01 -1.15507387e-01 -7.15433419e-01 2.24548087e-01
6.42481983e-01 -7.21830726e-01 7.30474710e-01 -1.28712296e+00
1.27199292e-01 3.14262539e-01 -2.89326251e-01 -1.13923335e+00
-7.23735616e-02 -6.17627800e-01 -9.13112685e-02 8.23396385e-01
5.35720527e-01 -1.02213657e+00 9.58665609e-01 9.05769289e-01
-2.28742719e-01 -1.24448836e+00 -9.55837846e-01 -1.44754934e+00
7.89566040e-01 -5.08430839e-01 -1.56761661e-01 5.53890228e-01
2.20665082e-01 -1.85631793e-02 -8.51986855e-02 -1.70914814e-01
8.41515839e-01 -4.59396571e-01 1.30017728e-01 -1.18051004e+00
-3.93045723e-01 -8.98236752e-01 -4.48740453e-01 -1.13837206e+00
5.54321170e-01 -9.51032937e-01 1.69471040e-01 -1.12837386e+00
-1.21882558e-01 -6.65508389e-01 -6.52930319e-01 5.12566745e-01
3.95950302e-02 1.26546592e-01 -1.02284163e-01 -1.59736291e-01
-5.07939577e-01 6.21237457e-01 8.28234732e-01 3.99097577e-02
-3.65072638e-01 5.19144475e-01 -5.06751835e-01 7.35242784e-01
1.00426006e+00 -5.54321647e-01 -5.02102256e-01 -3.52918148e-01
3.35835218e-01 -2.84274399e-01 2.10890055e-01 -1.07135713e+00
1.75940663e-01 2.56579816e-01 -4.57386114e-02 -1.36814341e-01
1.32812917e-01 -6.13167465e-01 -5.47472894e-01 7.80492723e-01
-1.01435041e+00 -1.71373352e-01 2.45136142e-01 5.72259009e-01
3.51451263e-02 -6.78903759e-01 1.30262947e+00 3.33272487e-01
9.22438800e-02 4.78779554e-01 -1.86415184e-02 5.59363186e-01
7.87975669e-01 -6.80140033e-02 1.23775236e-01 -4.48467076e-01
-8.99981141e-01 4.16749060e-01 1.61860853e-01 -1.93089709e-01
3.38428766e-01 -1.16321659e+00 -7.21917152e-01 1.64590627e-01
-3.05621028e-01 -3.48373540e-02 -8.83588791e-02 1.06323493e+00
-5.49054563e-01 4.65620250e-01 1.02944583e-01 -1.46180615e-01
-1.25526488e+00 5.06824315e-01 8.97050142e-01 -3.28149080e-01
-4.20381993e-01 1.27720428e+00 2.29565546e-01 -2.93253899e-01
9.44729269e-01 -7.41813898e-01 5.27887702e-01 -7.27696940e-02
6.13133252e-01 6.57352328e-01 2.55131751e-01 -5.47437370e-02
-2.74757594e-01 3.95826548e-01 -9.21894461e-02 -3.30982983e-01
1.47049642e+00 4.09092288e-03 1.72261178e-01 6.63774729e-01
2.03725863e+00 -4.00155604e-01 -1.74607801e+00 -3.20875436e-01
1.39750779e-01 -1.74000666e-01 1.48061633e-01 -5.45829892e-01
-1.05006063e+00 1.19248915e+00 7.16903806e-01 3.07257384e-01
1.02741814e+00 -8.70362818e-02 7.38341570e-01 7.44942367e-01
8.95478874e-02 -1.18389165e+00 -3.24963689e-01 5.20490110e-01
6.31985009e-01 -1.09471619e+00 -2.30631530e-01 1.95774421e-01
-2.45890051e-01 1.28272247e+00 3.02576810e-01 -4.58843619e-01
1.09753561e+00 2.64834493e-01 -3.41188163e-01 2.41949946e-01
-5.82862377e-01 -4.74191941e-02 2.27581248e-01 4.81702328e-01
3.17736655e-01 -4.49603535e-02 -4.70544219e-01 6.13831758e-01
-1.82936847e-01 -2.81313504e-03 1.51021689e-01 6.50959849e-01
-8.66192579e-01 -7.60558307e-01 1.18488811e-01 4.15968329e-01
-7.89757490e-01 -1.16074868e-01 -1.25673842e-02 7.85549581e-01
-3.02513361e-01 5.90696990e-01 8.72910470e-02 4.74150181e-02
2.59258509e-01 2.07327977e-01 7.71078646e-01 -2.34325975e-01
-2.46247292e-01 -4.44638312e-01 -8.32351744e-02 -2.86970496e-01
5.65590821e-02 -5.07102311e-01 -1.37464476e+00 -5.09145379e-01
-4.95991826e-01 3.24360281e-01 8.97385955e-01 7.75532246e-01
-3.72265913e-02 2.17593625e-01 7.22946346e-01 -4.17382598e-01
-1.42040336e+00 -8.01785350e-01 -7.96773970e-01 8.15201923e-02
8.12006176e-01 -4.44554061e-01 -1.13262296e+00 -2.68232614e-01] | [7.78222131729126, 3.9349617958068848] |
fbe8ca7e-6f7e-4db6-804d-a3b8a58fd094 | cscd-ime-correcting-spelling-errors-generated | 2211.08788 | null | https://arxiv.org/abs/2211.08788v2 | https://arxiv.org/pdf/2211.08788v2.pdf | CSCD-IME: Correcting Spelling Errors Generated by Pinyin IME | Chinese Spelling Correction (CSC) is a task to detect and correct spelling mistakes in texts. In fact, most of Chinese input is based on pinyin input method, so the study of spelling errors in this process is more practical and valuable. However, there is still no research dedicated to this essential scenario. In this paper, we first present a Chinese Spelling Correction Dataset for errors generated by pinyin IME (CSCD-IME), including 40,000 annotated sentences from real posts of official media on Sina Weibo. Furthermore, we propose a novel method to automatically construct large-scale and high-quality pseudo data by simulating the input through pinyin IME. A series of analyses and experiments on CSCD-IME show that spelling errors produced by pinyin IME hold a particular distribution at pinyin level and semantic level and are challenging enough. Meanwhile, our proposed pseudo-data construction method can better fit this error distribution and improve the performance of CSC systems. Finally, we provide a useful guide to using pseudo data, including the data scale, the data source, and the training strategy. | ['Jie zhou', 'Fandong Meng', 'Yong Hu'] | 2022-11-16 | null | null | null | null | ['spelling-correction'] | ['natural-language-processing'] | [ 9.25575010e-03 -6.12311780e-01 3.84720474e-01 -2.06885591e-01
-6.65240228e-01 -5.07268012e-01 3.01411420e-01 2.39907354e-01
-7.93524623e-01 8.17975104e-01 4.12163794e-01 -4.39000309e-01
3.57838646e-02 -7.17908621e-01 -5.96547961e-01 -2.85843790e-01
6.90519094e-01 5.01600683e-01 4.20617670e-01 -5.23504794e-01
9.93170738e-01 9.84351858e-02 -1.03345931e+00 6.25151575e-01
1.63084674e+00 2.05094472e-01 9.84826148e-01 7.59308517e-01
-4.29146111e-01 6.92214847e-01 -1.32728803e+00 -5.35826504e-01
-1.31491020e-01 -5.85829318e-01 -8.50904107e-01 -2.56527454e-01
-6.28085360e-02 2.84542814e-02 -8.89207348e-02 1.42939985e+00
6.32542491e-01 -4.17828560e-02 6.36059821e-01 -9.18777168e-01
-1.08153737e+00 9.20171797e-01 9.25089791e-02 3.27053338e-01
4.60911065e-01 -2.51548886e-01 6.54743910e-01 -1.17351151e+00
7.55686343e-01 7.93364465e-01 8.45799267e-01 7.64333487e-01
-1.25876009e-01 -7.11511970e-01 -2.58906096e-01 3.49785805e-01
-1.37516510e+00 7.11388979e-03 3.70047629e-01 -2.31550440e-01
6.68094099e-01 4.31679666e-01 4.45571244e-01 9.97461081e-01
3.66100222e-02 1.26689649e+00 1.08097100e+00 -9.42425013e-01
1.76858958e-02 2.66563743e-01 2.76608795e-01 1.33744434e-01
3.66642445e-01 -4.24172729e-01 -5.25920510e-01 3.54521364e-01
3.81639481e-01 2.52639413e-01 -4.25253242e-01 6.90903127e-01
-1.03255522e+00 5.10213673e-01 -1.10194683e-02 7.89063632e-01
2.71661639e-01 -3.37764323e-01 4.49313700e-01 2.66825527e-01
3.65924925e-01 6.07094824e-01 -7.90298164e-01 -7.37271488e-01
-9.92168605e-01 4.19217229e-01 5.42384923e-01 1.68094301e+00
2.87328035e-01 -3.44890147e-01 -2.19573811e-01 8.57519507e-01
1.45933658e-01 8.47077250e-01 1.00791216e+00 -3.02942455e-01
1.23803127e+00 6.94940925e-01 4.97619241e-01 -1.19123018e+00
-3.78205478e-01 -2.14564323e-01 -7.05245137e-01 -4.53964919e-01
6.69416428e-01 -2.33245850e-01 -5.57539105e-01 8.90426278e-01
-2.90111065e-01 -3.12331378e-01 -3.23916227e-02 8.23128998e-01
6.81972861e-01 6.92992270e-01 -1.68245405e-01 -1.90514892e-01
1.12788665e+00 -1.15012026e+00 -1.29798508e+00 -1.55987203e-01
1.30815303e+00 -1.25199354e+00 1.66379333e+00 5.03446817e-01
-8.58631670e-01 -5.17398000e-01 -7.04192221e-01 -2.04751432e-01
-5.20337999e-01 7.19701350e-01 4.22754064e-02 8.13269258e-01
-4.76939887e-01 7.89892375e-01 -4.06902432e-01 -2.19269305e-01
1.63943157e-01 -4.12290901e-01 -1.58886582e-01 -3.06070238e-01
-1.62299097e+00 9.21263516e-01 6.49618864e-01 1.87032640e-01
-1.88470200e-01 -6.38369977e-01 -5.94800293e-01 -6.31508976e-02
2.70946681e-01 1.90999016e-01 1.50509596e+00 -8.64533365e-01
-1.09135973e+00 5.66798031e-01 -4.04725581e-01 -1.26440749e-01
6.70400918e-01 -5.69992125e-01 -1.05812037e+00 -1.06725112e-01
2.26073235e-01 -2.35725820e-01 2.21360162e-01 -7.94904828e-01
-8.75032067e-01 -1.42936245e-01 -7.38108039e-01 2.55712569e-01
-4.79774356e-01 7.64646947e-01 -5.50828934e-01 -1.08358490e+00
3.24906670e-02 -6.88773811e-01 -8.88285786e-02 -6.68507159e-01
-4.49918360e-01 -3.77431810e-01 4.78850991e-01 -1.20085144e+00
2.20738387e+00 -2.15613461e+00 -4.57235962e-01 2.38654420e-01
-6.02290817e-02 9.92686570e-01 -1.64357312e-02 7.70926416e-01
2.63826638e-01 5.46515048e-01 -2.69038200e-01 -3.11033338e-01
-4.01224457e-02 5.52219786e-02 -2.10762218e-01 1.28734391e-02
-2.12675035e-01 9.12736237e-01 -1.29530966e+00 -5.05427003e-01
-1.86970189e-01 -2.18930528e-01 -4.50015396e-01 2.72928923e-01
9.56843141e-03 2.81675845e-01 -4.07398224e-01 5.59440732e-01
8.10844302e-01 -6.13213442e-02 -7.59837553e-02 3.55814397e-01
-4.22368169e-01 5.77385008e-01 -1.25261307e+00 1.40558088e+00
-2.75225818e-01 6.90922022e-01 -6.30239606e-01 -3.21731299e-01
1.18590617e+00 1.13871321e-01 -2.56232768e-01 -8.69643271e-01
8.83672386e-02 7.88145423e-01 -2.66543746e-01 -9.52132046e-01
1.32191718e+00 2.56186575e-01 -3.35089236e-01 3.68238568e-01
-3.35045129e-01 -2.58734852e-01 5.26128411e-01 3.34140033e-01
8.68640065e-01 -4.50716168e-02 2.10838407e-01 -2.30440751e-01
6.17600083e-01 2.99263179e-01 7.81670392e-01 8.47029924e-01
-2.24034503e-01 1.02102208e+00 2.83861458e-01 -6.51461184e-02
-1.35853159e+00 -5.14406860e-01 -9.10789147e-02 6.16069973e-01
1.54175714e-01 -8.84498298e-01 -1.26809537e+00 -7.47737110e-01
-3.52984041e-01 9.59497988e-01 -3.63481075e-01 5.47142737e-02
-7.60127604e-01 -4.96594876e-01 8.95107269e-01 6.01351798e-01
7.12589085e-01 -1.31327665e+00 1.28238738e-01 3.24051350e-01
-5.84801137e-01 -9.10067439e-01 -1.08011055e+00 -2.91712582e-01
-7.40390122e-01 -1.15264022e+00 -8.67289841e-01 -9.79894638e-01
8.02983046e-01 4.55524802e-01 8.63793075e-01 6.26977563e-01
2.51404226e-01 -4.43012863e-01 -1.19393420e+00 -7.45159864e-01
-7.35796332e-01 1.80917680e-01 -3.78853567e-02 -5.65936685e-01
9.83141720e-01 1.61307767e-01 -1.12801522e-01 4.58082765e-01
-9.46813405e-01 7.12796226e-02 3.81638259e-01 6.65916383e-01
1.61233261e-01 2.52564311e-01 4.41707075e-01 -1.38679385e+00
1.02072108e+00 -4.00064081e-01 -4.09395248e-01 4.56758976e-01
-7.22220600e-01 -2.93124378e-01 1.04327893e+00 -1.63351730e-01
-1.25606680e+00 -4.60175067e-01 -4.29541528e-01 2.48303160e-01
-1.94586813e-01 6.87352300e-01 -3.38753670e-01 2.58028507e-01
6.92295074e-01 5.53009152e-01 -4.19858813e-01 -1.05870497e+00
-3.83465849e-02 1.46995234e+00 6.19983435e-01 -2.79908210e-01
5.92449427e-01 -2.56005228e-01 -6.92933738e-01 -7.29645073e-01
-9.20263946e-01 -5.76506853e-01 -7.42045045e-01 -4.97350357e-02
6.75963581e-01 -5.91283679e-01 -4.61160451e-01 1.08105350e+00
-1.42670476e+00 -1.66108698e-01 1.37073770e-01 5.70132852e-01
5.48706502e-02 7.90189028e-01 -8.67064834e-01 -6.43661797e-01
-2.80425012e-01 -8.81118536e-01 7.14166462e-01 4.45911884e-01
-2.58579403e-01 -8.74280155e-01 2.54898276e-02 4.69030708e-01
2.84432143e-01 -5.35374403e-01 6.38960779e-01 -8.66809785e-01
-1.46718100e-01 -2.02482745e-01 -2.70641387e-01 6.90566242e-01
-1.55934840e-02 3.23184997e-01 -4.22448725e-01 3.39810364e-02
-3.17186378e-02 9.09470841e-02 3.19508433e-01 -3.25735249e-02
1.37207460e+00 -4.94153619e-01 -1.02186203e-02 3.23352158e-01
1.34090960e+00 3.79194438e-01 1.02733910e+00 5.88660657e-01
6.68242157e-01 3.01734805e-01 1.08051097e+00 6.00987613e-01
4.61012334e-01 3.60216409e-01 -1.18944012e-01 3.66668820e-01
-2.15686068e-01 -7.41032541e-01 3.64023298e-01 1.70092070e+00
-1.83216289e-01 -5.21190405e-01 -1.01610386e+00 6.13672197e-01
-1.63911307e+00 -9.63011563e-01 -1.07491982e+00 1.97222674e+00
1.17345750e+00 1.73368141e-01 -3.18750381e-01 5.43431938e-01
9.43754137e-01 -4.23720986e-01 2.59777009e-01 -3.15976202e-01
-5.17920136e-01 4.50335769e-03 5.62695444e-01 4.14853990e-01
-7.87292480e-01 1.24456477e+00 5.75301600e+00 1.34189832e+00
-8.04688215e-01 5.99054508e-02 8.00924674e-02 4.77833003e-01
-5.37834466e-01 -8.54523405e-02 -1.27347720e+00 1.32967830e+00
8.31211329e-01 -2.09203377e-01 3.68127793e-01 6.47529721e-01
5.32598078e-01 -1.68802574e-01 -5.19307494e-01 9.51616228e-01
2.74705529e-01 -1.35599673e+00 -1.70246035e-01 -3.88492078e-01
1.15838420e+00 -1.79815486e-01 -3.83874059e-01 2.88528591e-01
1.53711259e-01 -8.02866220e-01 1.11969697e+00 6.53877378e-01
6.61007047e-01 -6.42216980e-01 1.09057724e+00 8.09823096e-01
-6.28170013e-01 8.16871002e-02 -6.36345446e-01 -3.33528370e-01
6.51273429e-02 7.98812509e-01 -6.25121295e-01 6.27686441e-01
7.69243240e-01 8.73640716e-01 -1.11839318e+00 1.39786208e+00
-8.61378253e-01 9.35765624e-01 1.37099937e-01 -8.12366068e-01
8.42657611e-02 -2.19464868e-01 2.43043035e-01 1.68442345e+00
7.71954536e-01 6.83714375e-02 -4.00984794e-01 5.08125305e-01
-1.01078793e-01 4.96188611e-01 -2.44367570e-01 -7.37878829e-02
1.14914596e+00 6.88863814e-01 -4.39176172e-01 -4.32872117e-01
-3.36087823e-01 1.15995657e+00 3.27648103e-01 2.43959367e-01
-5.39538920e-01 -1.04563797e+00 2.21249714e-01 -2.04284251e-01
4.27065603e-02 -3.13033700e-01 -7.98815548e-01 -1.52811027e+00
2.33762190e-01 -1.09600675e+00 1.67270496e-01 -9.96810794e-01
-1.20178223e+00 4.67077076e-01 -3.91693890e-01 -1.51366758e+00
2.85852492e-01 -8.21903825e-01 -6.72944009e-01 1.12405467e+00
-1.33462954e+00 -5.61930597e-01 -3.23583215e-01 3.97724181e-01
7.89129615e-01 -1.73295796e-01 5.65011621e-01 8.03403676e-01
-6.66782081e-01 7.31680632e-01 6.97701812e-01 5.95178843e-01
9.90857422e-01 -1.32034791e+00 6.30957723e-01 1.46544576e+00
-1.11310497e-01 9.19269800e-01 8.23719144e-01 -1.08473730e+00
-6.72167420e-01 -1.20021212e+00 1.98089290e+00 -7.83400834e-01
4.87518370e-01 -3.04546028e-01 -9.90742564e-01 4.88838643e-01
-3.87214646e-02 -4.41621125e-01 4.69709545e-01 -2.01741174e-01
2.69752502e-01 2.46275872e-01 -9.61463571e-01 7.02473819e-01
1.00754905e+00 -5.36987960e-01 -9.51059699e-01 4.80013460e-01
9.02462304e-01 -7.18896866e-01 -4.39157903e-01 -1.34203747e-01
-8.79699066e-02 -7.07368076e-01 2.23142281e-01 -6.76929474e-01
8.42137516e-01 -5.96484065e-01 7.01235235e-02 -1.66699040e+00
-3.51986289e-01 -6.12365484e-01 3.33234787e-01 1.57769656e+00
5.66797018e-01 -1.56249791e-01 6.22967422e-01 5.51071703e-01
-7.95105517e-01 -1.61629155e-01 -3.79386544e-01 -8.22634816e-01
2.06268698e-01 -7.80134857e-01 1.02387023e+00 1.02003825e+00
2.18301043e-01 -2.04019085e-01 -4.73880887e-01 1.35435890e-02
1.04179904e-01 -4.31349963e-01 6.33368075e-01 -6.86069369e-01
1.93350643e-01 -3.68619233e-01 1.36683419e-01 -1.28820372e+00
-3.38187575e-01 -8.41782033e-01 1.77364260e-01 -1.30799305e+00
4.48720157e-03 -8.16491961e-01 2.21155643e-01 6.00072704e-02
-7.54445910e-01 1.53642716e-02 3.46629798e-01 5.78092456e-01
-4.98795033e-01 3.78204554e-01 1.54741538e+00 2.44760528e-01
-4.65696976e-02 2.07102716e-01 -6.02071643e-01 7.31603503e-01
7.13411212e-01 -6.94266021e-01 8.16488490e-02 -8.78637671e-01
6.90850198e-01 -2.73067445e-01 -1.94781750e-01 -8.98454487e-01
4.70358849e-01 -4.59123611e-01 1.54396445e-01 -7.60053635e-01
-5.82047522e-01 -6.62324786e-01 -1.84503973e-01 3.78487319e-01
-4.28480536e-01 4.46908802e-01 -2.93672949e-01 1.93103895e-01
-2.56595761e-01 -1.13801706e+00 4.65585142e-01 -3.22391897e-01
-8.07515502e-01 -9.60241854e-02 -7.16198981e-01 5.18550932e-01
7.21842825e-01 -2.20310271e-01 -5.58934391e-01 1.72166992e-02
-3.25034596e-02 1.41159981e-01 5.20579040e-01 3.30447882e-01
6.08526766e-01 -1.36825478e+00 -8.74499261e-01 3.74190927e-01
2.44869843e-01 3.01816408e-02 3.15563470e-01 5.30443788e-01
-1.27893269e+00 4.86914635e-01 -9.77191851e-02 7.22021796e-03
-1.10559916e+00 4.59893346e-01 4.31287885e-02 -2.16384023e-01
-4.58662212e-01 8.28826547e-01 -6.40545905e-01 -9.05385435e-01
9.56645831e-02 -4.62205052e-01 -5.67671478e-01 -1.08451962e-01
1.03772378e+00 7.53631711e-01 4.97493804e-01 -4.26562369e-01
-1.04348890e-01 2.49504656e-01 -3.90875340e-02 1.05876237e-01
9.48643148e-01 -4.31510538e-01 -2.27175340e-01 2.93440312e-01
9.44384396e-01 6.20434225e-01 -6.29307687e-01 -3.11823457e-01
4.16675508e-01 -9.35394406e-01 -4.73411828e-01 -9.57859099e-01
-5.77545881e-01 9.16702807e-01 -5.13764145e-03 1.32685592e-02
8.22508872e-01 -4.76350725e-01 1.24520457e+00 4.97175246e-01
5.02361596e-01 -1.91665256e+00 -1.20891176e-01 1.18103099e+00
7.25264966e-01 -1.11863708e+00 -4.53608960e-01 -3.77332062e-01
-9.21810567e-01 1.27237630e+00 7.29790092e-01 2.52613798e-02
4.76208866e-01 4.16527409e-03 2.78842866e-01 2.89784402e-01
-2.32965559e-01 2.18436614e-01 5.94630465e-02 7.22722292e-01
6.43126369e-01 1.73559487e-01 -1.09979069e+00 1.32481205e+00
-6.08041525e-01 2.00624794e-01 1.12377894e+00 8.84791791e-01
-6.57318413e-01 -1.36195958e+00 -5.45089304e-01 4.49246228e-01
-5.12468457e-01 -5.41244268e-01 -1.37464553e-01 4.65354443e-01
1.83385864e-01 1.08831894e+00 -1.52076215e-01 -4.36226368e-01
4.45507169e-01 -2.21075803e-01 2.72359513e-02 -7.56395459e-01
-7.67307043e-01 -2.61441171e-01 3.19126807e-02 -1.18123420e-01
-7.99411163e-02 -8.57956052e-01 -1.35780513e+00 -5.96011817e-01
-5.69632351e-01 6.65432990e-01 7.14133859e-01 1.24324417e+00
1.24015890e-01 2.53817499e-01 6.33930981e-01 -1.12508133e-01
-5.55474520e-01 -1.36364770e+00 -9.26940560e-01 7.52186775e-01
-1.43331334e-01 4.35532257e-02 -2.72534847e-01 7.43899047e-02] | [10.982450485229492, 10.759657859802246] |
aa010301-e174-4087-ac6a-5b4984273065 | universal-learned-image-compression-with-low | 2206.11599 | null | https://arxiv.org/abs/2206.11599v1 | https://arxiv.org/pdf/2206.11599v1.pdf | Universal Learned Image Compression With Low Computational Cost | Recently, learned image compression methods have developed rapidly and exhibited excellent rate-distortion performance when compared to traditional standards, such as JPEG, JPEG2000 and BPG. However, the learning-based methods suffer from high computational costs, which is not beneficial for deployment on devices with limited resources. To this end, we propose shift-addition parallel modules (SAPMs), including SAPM-E for the encoder and SAPM-D for the decoder, to largely reduce the energy consumption. To be specific, they can be taken as plug-and-play components to upgrade existing CNN-based architectures, where the shift branch is used to extract large-grained features as compared to small-grained features learned by the addition branch. Furthermore, we thoroughly analyze the probability distribution of latent representations and propose to use Laplace Mixture Likelihoods for more accurate entropy estimation. Experimental results demonstrate that the proposed methods can achieve comparable or even better performance on both PSNR and MS-SSIM metrics to that of the convolutional counterpart with an about 2x energy reduction. | ['Wen Tan', 'Yongsheng Liang', 'Fanyang Meng', 'Youneng Bao', 'Yao Xin', 'Bowen Li'] | 2022-06-23 | null | null | null | null | ['ms-ssim'] | ['computer-vision'] | [ 1.70638874e-01 -1.06367081e-01 -2.57015198e-01 -3.80277574e-01
-7.05669940e-01 2.81033590e-02 3.67591172e-01 1.37280494e-01
-4.24342811e-01 4.86227572e-01 6.86472952e-02 -2.65488297e-01
-4.91718799e-02 -7.41260052e-01 -7.47073293e-01 -7.77242005e-01
-1.94483206e-01 -2.71879762e-01 2.00906932e-01 4.56577092e-02
3.14082533e-01 1.24748573e-01 -1.51006269e+00 2.59680420e-01
9.52155828e-01 1.41788471e+00 5.59420347e-01 4.51239318e-01
1.71250310e-02 1.08650124e+00 -3.18546325e-01 -6.61234260e-01
1.12371154e-01 -3.71709377e-01 -4.25630152e-01 -1.18910424e-01
-3.34415287e-02 -9.88150775e-01 -9.01514649e-01 1.09142470e+00
4.20290947e-01 -1.99461624e-01 4.60271746e-01 -1.01869559e+00
-3.46185267e-01 5.82895875e-01 -6.73533738e-01 1.86489806e-01
-3.85588296e-02 -2.47385055e-02 8.81980121e-01 -8.18275750e-01
2.25596756e-01 9.72858012e-01 5.04797995e-01 2.56393641e-01
-6.47431314e-01 -8.07166100e-01 -1.27422228e-01 9.04582679e-01
-1.57568705e+00 -6.89554214e-01 8.16998065e-01 1.08257785e-01
1.18172503e+00 1.36171296e-01 5.96695662e-01 8.38459969e-01
3.79472017e-01 9.46616232e-01 6.95159614e-01 -3.17822427e-01
3.20491493e-01 4.88574095e-02 -4.67355967e-01 7.77628958e-01
4.24182236e-01 -2.29380965e-01 -6.14522576e-01 2.16415435e-01
8.43122303e-01 -7.64327273e-02 -4.13816154e-01 -1.43151671e-01
-8.41143727e-01 6.95591331e-01 4.76264775e-01 1.47320971e-01
-3.84592891e-01 5.23956597e-01 5.72875559e-01 1.73020400e-02
4.29699928e-01 -2.09005892e-01 -4.18846756e-01 -5.74861944e-01
-1.43081367e+00 -5.82241304e-02 6.28243685e-01 1.24548483e+00
7.07067847e-01 1.98956609e-01 1.59433112e-02 8.79697978e-01
4.96688128e-01 1.08038209e-01 6.24584377e-01 -1.07953870e+00
7.19416082e-01 4.83854890e-01 -3.00685346e-01 -1.04614341e+00
-1.02603726e-01 -6.78449512e-01 -1.28846002e+00 -1.28826499e-01
-3.22898626e-01 3.16835225e-01 -5.81831515e-01 1.37867510e+00
-1.67627916e-01 3.76635402e-01 7.27997813e-03 6.50442123e-01
5.26973605e-01 8.65945756e-01 -7.99386650e-02 -2.95936108e-01
1.23990405e+00 -1.17092037e+00 -8.35930705e-01 -3.01159918e-01
4.55363363e-01 -6.43925309e-01 6.82389259e-01 4.42926973e-01
-1.41662860e+00 -6.55125201e-01 -1.52328336e+00 -3.66239488e-01
7.90939704e-02 4.54768986e-01 3.64284068e-01 7.90447056e-01
-9.83310819e-01 1.11852872e+00 -1.13075042e+00 2.30870005e-02
7.68859863e-01 3.70060503e-01 9.81360674e-02 -1.27815351e-01
-1.00006461e+00 6.51182950e-01 4.23099786e-01 1.10665560e-01
-9.51611400e-01 -5.49504340e-01 -7.83078909e-01 7.23475695e-01
8.88414681e-02 -4.51509148e-01 1.08502686e+00 -5.60148478e-01
-1.72177863e+00 3.16695213e-01 5.15830442e-02 -7.71434307e-01
3.28019142e-01 -4.11014438e-01 -3.04970860e-01 5.39529622e-01
-4.08422709e-01 6.53366506e-01 1.02544498e+00 -8.83051157e-01
-6.65301561e-01 1.40232658e-02 4.14138287e-03 7.81053677e-02
-9.31400120e-01 -6.74194470e-02 -7.67147720e-01 -8.75483274e-01
1.41473383e-01 -6.51294827e-01 -8.07515383e-02 2.49525264e-01
-2.13780329e-01 1.59163669e-01 9.93253529e-01 -1.04085982e+00
1.58518076e+00 -2.39188623e+00 -9.16875303e-02 -7.62873664e-02
1.73333511e-01 4.55571681e-01 1.20092079e-01 2.70054251e-01
5.59638739e-02 1.33492112e-01 -2.32795641e-01 -4.54780698e-01
2.02408656e-02 1.28591612e-01 1.85250696e-02 4.13879037e-01
3.35477591e-01 6.70729816e-01 -5.54089487e-01 -5.89463592e-01
4.36615437e-01 6.77962363e-01 -8.12769353e-01 2.70607471e-01
8.87087062e-02 3.48532349e-02 -2.77572662e-01 4.98381406e-01
9.01983321e-01 -4.83520478e-01 4.52975780e-01 -5.60713410e-01
7.35188946e-02 5.64599693e-01 -8.89065862e-01 1.80703044e+00
-6.42430365e-01 7.02753484e-01 8.87312293e-02 -1.13221395e+00
8.37135792e-01 3.50440502e-01 4.21387017e-01 -6.84327424e-01
2.95730472e-01 4.22535539e-01 -7.30316043e-02 -3.19524497e-01
6.34118080e-01 2.47522801e-01 2.60995060e-01 -4.80044000e-02
3.52771819e-01 1.52770638e-01 1.05060183e-01 1.34430155e-01
9.99281466e-01 1.06948288e-02 4.93662000e-01 -2.14636415e-01
5.99984944e-01 -6.83543146e-01 7.36246705e-01 3.07759553e-01
4.79095429e-02 4.87449884e-01 3.27242821e-01 -1.53329968e-01
-1.20299935e+00 -8.40469420e-01 -2.80336421e-02 5.23957074e-01
3.20777774e-01 -9.36534584e-01 -9.66985345e-01 -3.61418962e-01
-5.41936815e-01 6.28152549e-01 1.62186071e-01 -4.52615470e-01
-6.25137687e-01 -7.18379617e-01 4.96656358e-01 6.57304108e-01
1.16847742e+00 -5.05355000e-01 -1.05645895e+00 4.37704921e-01
-3.64819050e-01 -1.23635030e+00 -3.82278502e-01 2.87903130e-01
-1.19927251e+00 -6.93935871e-01 -6.81719840e-01 -5.83206654e-01
3.01778823e-01 9.61203203e-02 8.35231543e-01 3.95826809e-02
-2.41553068e-01 -1.69716626e-02 -5.80609739e-01 -4.68343906e-02
-2.61194259e-01 1.07183337e-01 -2.47063160e-01 -7.29151443e-02
1.58953086e-01 -1.01077557e+00 -1.10519648e+00 1.74914792e-01
-9.72972393e-01 3.21069181e-01 9.60255861e-01 6.92279279e-01
4.71173912e-01 3.67249489e-01 2.92760104e-01 -2.45149150e-01
1.82417586e-01 -3.80867064e-01 -4.27927524e-01 1.63004965e-01
-1.00741363e+00 1.56966716e-01 7.67434955e-01 -1.47973031e-01
-9.94616687e-01 -1.09476924e-01 -3.21613520e-01 -4.59253311e-01
3.94377321e-01 4.84657317e-01 -2.56986737e-01 -7.09326491e-02
-5.95632289e-03 5.85740864e-01 -1.22269541e-01 -6.19182050e-01
-3.44060883e-02 7.88179934e-01 5.19498944e-01 -2.89765418e-01
6.92717016e-01 3.30130488e-01 3.42165679e-03 -6.46301270e-01
-1.92184806e-01 -1.09714650e-01 -2.09718823e-01 -1.16529875e-01
6.42477751e-01 -1.48585522e+00 -4.41255331e-01 5.57250679e-01
-1.10353911e+00 2.98370086e-02 -1.36350185e-01 6.78626418e-01
-6.44424379e-01 6.40162468e-01 -9.19769526e-01 -6.24382079e-01
-6.03747308e-01 -1.45166218e+00 9.00983095e-01 4.33229566e-01
1.94017634e-01 -7.23301530e-01 -5.72070956e-01 2.48086497e-01
8.16185117e-01 -2.59334922e-01 1.16880453e+00 -2.82883227e-01
-9.87756550e-01 -6.96253255e-02 -4.08165872e-01 8.04410875e-01
-1.04497403e-01 -1.04036048e-01 -1.09941161e+00 -6.17793500e-01
2.77370304e-01 -2.89669186e-01 1.06160808e+00 4.48836446e-01
1.85224938e+00 -4.68810081e-01 -1.35857388e-01 1.06456840e+00
1.59380376e+00 3.62332523e-01 1.18252349e+00 2.57567406e-01
2.65905976e-01 -4.45254706e-02 4.05380815e-01 1.02836227e+00
3.56062263e-01 6.60232663e-01 5.50652266e-01 1.18418075e-01
-2.31709614e-01 -3.09401065e-01 5.33225954e-01 1.61205351e+00
-1.93679079e-01 -3.88814420e-01 -3.71457130e-01 2.35886618e-01
-1.57829845e+00 -7.02791095e-01 2.32918814e-01 2.06120896e+00
8.10597062e-01 3.15295458e-01 -4.13999468e-01 5.29224217e-01
5.67043841e-01 5.42004168e-01 -5.03271759e-01 -2.07729831e-01
1.57598600e-01 5.19751906e-01 7.10448921e-01 -4.19684462e-02
-9.88595665e-01 3.71701360e-01 5.86898899e+00 1.39979577e+00
-1.09172308e+00 3.17180276e-01 7.51742303e-01 -9.61254388e-02
-1.88338146e-01 8.58994350e-02 -6.45494223e-01 6.19426429e-01
1.31082606e+00 -1.37598053e-01 4.33283687e-01 1.12745118e+00
9.32968855e-02 1.03141123e-03 -1.04142439e+00 1.33737683e+00
-6.78581968e-02 -1.36405790e+00 2.19956543e-02 1.65027782e-01
4.17648971e-01 -8.59442726e-02 6.22146390e-02 1.96839824e-01
-3.22167844e-01 -7.39506781e-01 9.40686285e-01 2.58786112e-01
9.46840703e-01 -9.09438729e-01 7.68079698e-01 2.73467183e-01
-1.41707289e+00 -2.01733515e-01 -7.54096150e-01 3.97019573e-02
2.03858286e-01 8.79703462e-01 -4.24243808e-01 7.36656666e-01
9.51844990e-01 7.76241302e-01 -4.50998366e-01 1.07997763e+00
-8.32301527e-02 7.19882786e-01 -1.99639916e-01 1.24412522e-01
3.61818597e-02 -7.69981965e-02 1.35343224e-01 1.16787732e+00
9.39985394e-01 -9.92916152e-02 -3.18022162e-01 6.55382931e-01
-4.36043113e-01 -4.25890870e-02 8.61725397e-03 -2.83656083e-02
5.70058823e-01 1.21412337e+00 -6.34668171e-01 -3.74796033e-01
-5.99424124e-01 1.31061482e+00 -9.37242643e-04 1.18837185e-01
-1.19245410e+00 -6.46678925e-01 6.70075595e-01 9.46539268e-02
7.59872377e-01 -2.67579615e-01 -4.49188910e-02 -1.28832424e+00
2.30887085e-01 -7.44398773e-01 -9.80808660e-02 -5.83686888e-01
-7.19414890e-01 4.61858243e-01 -1.10918812e-01 -1.52040064e+00
-1.53869063e-01 -4.80254322e-01 -3.98786217e-01 5.28240323e-01
-1.98327816e+00 -7.17547834e-01 -5.64272344e-01 4.78875250e-01
7.01686025e-01 -1.99105144e-01 7.41069496e-01 7.36212254e-01
-5.73722482e-01 8.68831038e-01 5.48527122e-01 8.29984099e-02
4.06452984e-01 -6.84435964e-01 3.61949533e-01 8.06020558e-01
3.30603234e-02 4.42430794e-01 3.65832359e-01 -3.32456917e-01
-1.60566401e+00 -1.11381555e+00 5.77280223e-01 6.56798601e-01
1.44284964e-01 -3.44838440e-01 -7.06836343e-01 3.20939571e-01
4.13368702e-01 1.31486490e-01 5.62545776e-01 -4.70070362e-01
-3.40494454e-01 -4.36027825e-01 -1.14166534e+00 3.24221462e-01
8.73293757e-01 -5.32629788e-01 -4.15638313e-02 2.34396867e-02
6.32547796e-01 -2.84065276e-01 -9.75993633e-01 5.05093932e-01
5.97916543e-01 -1.31163323e+00 9.17433321e-01 2.55673647e-01
9.51863825e-01 -1.69081181e-01 -5.55177152e-01 -1.00086582e+00
-4.43938643e-01 -4.64408994e-01 -7.03087807e-01 1.34910154e+00
9.56677794e-02 -2.47639328e-01 7.39479542e-01 1.43542871e-01
-2.30471462e-01 -9.99158323e-01 -1.14608371e+00 -8.70058179e-01
-2.68570453e-01 -3.94207984e-01 6.13081574e-01 3.03940207e-01
-2.86950599e-02 -5.99536672e-02 -6.12801075e-01 4.11891714e-02
5.83411932e-01 -2.04089120e-01 3.09514582e-01 -7.73581266e-01
-5.91188192e-01 -3.37480962e-01 -5.84972024e-01 -1.56940877e+00
-1.85633034e-01 -6.73515022e-01 1.63484365e-02 -1.31963241e+00
4.27037567e-01 -2.66600847e-01 -4.55636919e-01 9.48666036e-02
-4.31010826e-03 2.07804427e-01 2.15717077e-01 2.88961530e-01
-5.35494030e-01 1.01166511e+00 8.83242488e-01 -2.77688324e-01
2.19356164e-01 -3.13088834e-01 -5.68325043e-01 6.76707506e-01
6.57424450e-01 -4.32741016e-01 -5.64991295e-01 -6.34346962e-01
1.39860868e-01 1.06001593e-01 1.76116496e-01 -1.58123457e+00
2.32178718e-01 2.50029564e-01 4.39654440e-01 -5.44241190e-01
5.30841768e-01 -8.66139352e-01 2.50562578e-01 5.32273114e-01
-2.00588241e-01 -1.70428813e-01 3.27746384e-02 5.63373983e-01
-5.40069163e-01 -4.24520910e-01 9.02544796e-01 4.46687676e-02
-6.41843021e-01 2.86197722e-01 -4.02325302e-01 -2.65367180e-01
9.24753726e-01 -1.53642759e-01 -2.25577682e-01 -6.36858821e-01
-5.40942587e-02 -2.43482620e-01 3.48678738e-01 9.75228995e-02
1.05169761e+00 -1.29987073e+00 -5.95167398e-01 2.37228319e-01
-1.23192012e-01 -6.41890382e-03 5.26763201e-01 8.01468492e-01
-8.56991231e-01 5.11413813e-01 -1.70554355e-01 -4.17143971e-01
-1.08158791e+00 3.83195937e-01 -2.75921868e-03 -4.48540479e-01
-5.83360910e-01 8.53486836e-01 -7.46441912e-03 2.99139887e-01
3.61505121e-01 -5.10808527e-01 1.07097454e-01 -2.59743929e-01
6.44966304e-01 5.27572989e-01 2.12685645e-01 -2.86894441e-01
-3.19561452e-01 3.07560861e-01 -1.49210289e-01 2.82554358e-01
1.61936128e+00 -3.65521699e-01 -8.33535790e-02 -1.70140024e-02
1.53441167e+00 -3.77543330e-01 -1.52862561e+00 -8.56844187e-02
-1.45103619e-01 -5.62893033e-01 4.56048399e-01 -3.63824278e-01
-1.56586826e+00 1.10478997e+00 9.42001581e-01 -1.42420053e-01
1.73488820e+00 -2.11651444e-01 1.14854741e+00 1.94367200e-01
5.08495331e-01 -1.25210965e+00 1.22487709e-01 9.93000865e-02
5.62491417e-01 -7.99155593e-01 2.84798056e-01 -4.78740662e-01
-1.99908137e-01 1.40241635e+00 3.64642531e-01 -6.55741468e-02
7.87064910e-01 5.06746829e-01 -6.14264190e-01 2.88677961e-01
-8.73258829e-01 3.71578097e-01 1.09373510e-01 2.92590976e-01
4.85605836e-01 -1.55686930e-01 -4.77296829e-01 7.16643393e-01
-2.58253217e-02 2.39265338e-01 4.87662017e-01 1.00581849e+00
-4.18989003e-01 -1.02562320e+00 4.57938537e-02 6.41416728e-01
-5.79519331e-01 -3.84577036e-01 4.93383557e-01 4.22989339e-01
2.22420856e-01 8.03817987e-01 1.30026072e-01 -8.19096923e-01
-1.44402906e-01 -5.93612902e-02 4.69204009e-01 -9.21787545e-02
-2.49099374e-01 1.12431094e-01 -2.57406030e-02 -7.01251149e-01
-5.18815339e-01 -3.93880397e-01 -1.01812863e+00 -4.37054068e-01
-3.96245271e-01 -1.64422855e-01 9.86571252e-01 8.09548259e-01
5.10338902e-01 8.38421583e-01 7.23924696e-01 -9.26833034e-01
-7.87298024e-01 -1.01528358e+00 -6.10257983e-01 -9.41881388e-02
1.15097627e-01 -4.16366011e-01 -1.91770241e-01 2.22952679e-01] | [11.31792163848877, -1.637199878692627] |
2db6b8dc-22d1-48bb-98b4-cf42a78ae5ac | an-empirical-and-comparative-analysis-of-data | null | null | https://openreview.net/forum?id=SygBIxSFDS | https://openreview.net/pdf?id=SygBIxSFDS | An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms | This paper focuses on valuating training data for supervised learning tasks and studies the Shapley value, a data value notion originated in cooperative game theory. The Shapley value defines a unique value distribution scheme that satisfies a set of appealing properties desired by a data value notion. However, the Shapley value requires exponential complexity to calculate exactly. Existing approximation algorithms, although achieving great improvement over the exact algorithm, relies on retraining models for multiple times, thus remaining limited when applied to larger-scale learning tasks and real-world datasets.
In this work, we develop a simple and efficient algorithm to estimate the Shapley value with complexity independent with the model size. The key idea is to approximate the model via a $K$-nearest neighbor ($K$NN) classifier, which has a locality structure that can lead to efficient Shapley value calculation. We evaluate the utility of the values produced by the $K$NN proxies in various settings, including label noise correction, watermark detection, data summarization, active data acquisition, and domain adaption. Extensive experiments demonstrate that our algorithm achieves at least comparable utility to the values produced by existing algorithms while significant efficiency improvement. Moreover, we theoretically analyze the Shapley value and justify its advantage over the leave-one-out error as a data value measure. | ['Dawn Song', 'Bo Li', 'Ce Zhang', 'Jiacen Xu', 'Xuehui Sun', 'Ruoxi Jia'] | 2019-09-25 | null | null | null | null | ['data-summarization'] | ['miscellaneous'] | [ 3.15405369e-01 3.08112085e-01 -7.32141018e-01 -1.34351656e-01
-9.95632350e-01 -6.90361857e-01 5.42766750e-02 6.52162910e-01
-7.79448628e-01 1.03662825e+00 -7.63929030e-03 -1.17908768e-01
-6.25841260e-01 -8.29181612e-01 -5.33540547e-01 -8.97297025e-01
-3.28339726e-01 3.08634698e-01 1.89519495e-01 -1.61709428e-01
5.03189385e-01 -3.48961093e-02 -1.47783792e+00 -7.72159323e-02
9.61252689e-01 1.14549828e+00 -7.66269714e-02 6.02311313e-01
1.73518360e-02 1.02766824e+00 -8.73914957e-01 -7.43400455e-01
5.99008501e-01 -7.01064408e-01 -8.98583233e-01 -1.19039923e-01
-1.47349566e-01 -4.17519033e-01 -4.53962199e-02 1.28367233e+00
6.32106721e-01 1.27485767e-01 7.78625131e-01 -1.81827593e+00
-8.77369881e-01 1.11891210e+00 -6.75357461e-01 2.92926040e-02
1.68629393e-01 -2.36395061e-01 1.49482858e+00 -2.78045058e-01
6.63884878e-01 5.50594747e-01 7.77146876e-01 6.40381277e-01
-1.29021561e+00 -7.20645964e-01 -2.23420590e-01 4.82834220e-01
-1.36055851e+00 -3.69117633e-02 9.79821086e-01 -5.14651909e-02
5.89030206e-01 2.88966238e-01 6.83921397e-01 5.74711978e-01
8.74419231e-03 9.47958052e-01 1.07100010e+00 -5.75378656e-01
9.01200116e-01 3.79791737e-01 4.58979048e-02 5.98366678e-01
6.66176319e-01 -5.30665889e-02 -6.86289847e-01 -4.92142946e-01
3.91271949e-01 -1.90740824e-01 -3.92392784e-01 -9.17410195e-01
-1.04385054e+00 9.46281433e-01 3.91812742e-01 1.80163592e-01
-3.44138503e-01 3.31418097e-01 5.27281165e-01 8.17185104e-01
3.77832055e-01 4.87188131e-01 -5.13694465e-01 -1.24491766e-01
-8.93893600e-01 1.18927933e-01 8.42142582e-01 9.78698015e-01
6.77632749e-01 -3.44548076e-01 3.01709343e-02 6.24743462e-01
3.53221293e-03 4.25058305e-02 6.09620512e-01 -1.48978913e+00
2.65982568e-01 7.30264544e-01 1.16673939e-01 -8.01360071e-01
-1.42503783e-01 -4.12797123e-01 -8.79150450e-01 2.98246533e-01
5.66374183e-01 -3.61331180e-02 -2.37853024e-02 2.08871007e+00
4.45601195e-01 3.25229615e-02 4.88857508e-01 6.13361895e-01
3.44416022e-01 3.36225301e-01 -2.00494123e-03 -7.67310023e-01
1.17797470e+00 -7.34783888e-01 -6.84945524e-01 2.45315373e-01
1.19588828e+00 -2.84413248e-01 1.14693308e+00 4.50414896e-01
-9.81365085e-01 -4.82084416e-02 -1.27062118e+00 5.67066371e-02
-2.77168721e-01 -6.50122046e-01 4.70407486e-01 1.09135437e+00
-1.15401077e+00 7.03151286e-01 -1.46305887e-04 -3.06577623e-01
7.40381420e-01 4.25815612e-01 -4.49743807e-01 2.22189222e-02
-1.30324316e+00 5.68223298e-01 6.86494529e-01 -7.32637644e-01
-5.42666376e-01 -7.51661777e-01 -4.85242963e-01 2.74505049e-01
7.13284492e-01 -5.58038414e-01 1.14598227e+00 -9.14686561e-01
-1.19939947e+00 9.81311083e-01 4.99713987e-01 -7.96127677e-01
6.45943701e-01 5.06285071e-01 1.78643733e-01 1.96041137e-01
-7.51418769e-02 3.71732086e-01 4.10115808e-01 -1.29140878e+00
-8.55113626e-01 -3.46046776e-01 4.50171053e-01 3.60167742e-01
-9.77614820e-01 -3.03045958e-01 1.39723971e-01 -7.63554275e-01
-1.00455388e-01 -5.65952301e-01 -4.10242468e-01 4.94456917e-01
1.92084745e-01 -3.82733226e-01 5.37337899e-01 -2.20589653e-01
1.30719912e+00 -2.14287782e+00 -1.97765417e-02 2.10604474e-01
5.41494071e-01 8.32469389e-02 -2.22624391e-01 3.81982416e-01
3.81692380e-01 3.00809383e-01 -5.13869703e-01 1.19193867e-01
2.04139426e-01 2.15015814e-01 2.80381311e-02 5.54351270e-01
-4.18358088e-01 9.13759649e-01 -9.88634706e-01 -7.40034938e-01
-2.18672335e-01 -1.57389522e-01 -8.27951491e-01 4.48327027e-02
-5.09442426e-02 -3.97252530e-01 -2.52669901e-01 4.12841201e-01
7.90092170e-01 -4.17429358e-01 5.76632321e-01 1.61693782e-01
5.31811297e-01 -3.95472258e-01 -1.40305626e+00 1.61545575e+00
6.75523058e-02 3.82854939e-01 7.66169187e-03 -1.44205749e+00
1.00825846e+00 1.48757339e-01 8.32926750e-01 -5.92724800e-01
4.79660630e-01 2.97204077e-01 -3.59769315e-01 -2.51368314e-01
6.12739325e-01 -3.10448319e-01 -4.53278005e-01 9.67294216e-01
3.95830162e-02 7.06455037e-02 1.72302071e-02 4.77994055e-01
1.32942843e+00 -5.09965658e-01 1.09983397e+00 -3.79130185e-01
4.24055934e-01 1.47153273e-01 6.36591971e-01 7.43536115e-01
-9.34856653e-01 9.47869122e-02 9.24206793e-01 -1.93310797e-01
-8.90113890e-01 -9.91247416e-01 5.58947325e-02 1.19995522e+00
6.97556436e-01 -3.61333251e-01 -1.02615416e+00 -9.64688778e-01
2.90012717e-01 6.27954543e-01 -7.80451834e-01 -6.17044747e-01
4.45421748e-02 -6.91293597e-01 7.07948208e-01 4.97041196e-01
6.76815510e-01 -7.92845607e-01 -8.45171869e-01 1.43457562e-01
-3.71625930e-01 -7.87105560e-01 -4.53572154e-01 4.23179656e-01
-8.96494925e-01 -1.24276423e+00 -6.62550628e-01 -8.33381951e-01
4.76179302e-01 4.40834612e-01 8.12899530e-01 1.18450195e-01
2.30847731e-01 5.63921928e-01 -6.00309193e-01 -4.97732460e-01
-3.69434953e-01 1.34404927e-01 6.79012462e-02 -2.21526116e-01
6.19189382e-01 -3.45876694e-01 -5.47922432e-01 2.18032449e-01
-9.23547029e-01 -3.61441672e-01 4.76076394e-01 9.25502062e-01
6.76936269e-01 4.36010599e-01 1.00662124e+00 -1.00526750e+00
9.27004099e-01 -5.46187222e-01 -4.12058800e-01 5.01419365e-01
-1.19210052e+00 1.59945577e-01 7.51714945e-01 -4.61096168e-01
-6.29432678e-01 -4.52559479e-02 3.87768596e-01 -1.08261913e-01
3.53507221e-01 4.60447043e-01 -2.75900543e-01 -1.87977597e-01
9.07180488e-01 1.60671368e-01 2.96920657e-01 -2.26395186e-02
5.11024356e-01 8.78852367e-01 4.03076291e-01 -4.49260563e-01
6.74635947e-01 3.00922483e-01 1.83953438e-02 -2.92939991e-01
-5.99238694e-01 -3.41317147e-01 -4.46944207e-01 -2.50044018e-01
3.28856558e-01 -7.52803266e-01 -1.18915188e+00 3.25104415e-01
-6.75702333e-01 -1.74197763e-01 -9.89682019e-01 2.67298311e-01
-9.88246620e-01 5.19959688e-01 -3.23440999e-01 -9.63808835e-01
-4.07950044e-01 -5.74710310e-01 2.90027201e-01 1.19892590e-01
3.14361565e-02 -8.34886849e-01 8.51344466e-02 6.57787561e-01
2.11756095e-01 3.62016678e-01 1.06164575e+00 -7.78464794e-01
-4.05573130e-01 -4.18784708e-01 -1.05328485e-01 3.45426172e-01
-1.05222814e-01 -5.56940198e-01 -8.61141264e-01 -5.88056743e-01
9.98621956e-02 -5.01476943e-01 7.55942464e-01 3.42204154e-01
1.22505343e+00 -6.06578112e-01 4.26523611e-02 3.03647727e-01
1.72582281e+00 3.28319311e-01 4.88729477e-01 3.41751873e-01
1.24150053e-01 6.46536052e-01 8.08992088e-01 9.37150538e-01
5.26861191e-01 2.93827146e-01 5.36290050e-01 2.48758867e-01
3.26509386e-01 -2.46193662e-01 2.35665888e-01 7.16505229e-01
-5.82784368e-03 -3.59815419e-01 -6.24815226e-01 4.96262372e-01
-2.00695610e+00 -1.11668825e+00 2.33338192e-01 2.39530778e+00
1.00578105e+00 1.47644639e-01 4.68666941e-01 8.15608144e-01
7.17131674e-01 8.63569155e-02 -8.64634395e-01 -3.86345297e-01
-2.24369362e-01 -6.97572762e-03 7.81548738e-01 1.99480265e-01
-7.15408146e-01 5.74894071e-01 6.77252531e+00 1.19897842e+00
-5.96810102e-01 3.31630617e-01 5.55539727e-01 -3.76061738e-01
-4.67169791e-01 -1.25717714e-01 -7.93723762e-02 4.25621599e-01
7.41273463e-01 -1.16689968e+00 5.66268504e-01 1.12167907e+00
-2.14518428e-01 -1.53670564e-01 -9.28594887e-01 1.13941562e+00
1.31238997e-01 -1.37678969e+00 -1.04707800e-01 2.66062349e-01
7.57098854e-01 -4.21919614e-01 -6.31591007e-02 1.64344504e-01
7.00990081e-01 -5.14636040e-01 7.82335341e-01 -1.47428503e-03
8.29794109e-01 -1.03603160e+00 8.63478601e-01 6.10826135e-01
-1.11030436e+00 -6.15545869e-01 -6.96015954e-01 -1.03935152e-01
-3.21458787e-01 4.95022297e-01 -5.89199007e-01 5.14780045e-01
5.50934136e-01 3.63827437e-01 -4.97968286e-01 8.27166617e-01
2.64683247e-01 3.50535959e-01 -1.18692897e-01 -4.66491342e-01
-7.31129646e-02 3.64777669e-02 1.65566400e-01 6.38816416e-01
2.92419434e-01 3.13676476e-01 -2.14967221e-01 4.16790545e-01
-7.31281519e-01 5.52535236e-01 -7.13690639e-01 -3.48677710e-02
9.13081586e-01 9.73153889e-01 -8.38046849e-01 -1.70152649e-01
-2.20533207e-01 8.51611137e-01 3.95853788e-01 -2.63309069e-02
-8.58084738e-01 -7.13764906e-01 5.61192513e-01 1.98588241e-02
6.42683953e-02 1.04521066e-01 -6.01416886e-01 -9.39033806e-01
5.07750586e-02 -6.65758610e-01 8.42996776e-01 -3.55094761e-01
-1.33321822e+00 1.51091799e-01 -2.24076565e-02 -1.54201412e+00
-6.04567379e-02 -3.40274960e-01 -1.99113995e-01 1.04883149e-01
-1.33775687e+00 -6.44937932e-01 -2.18246102e-01 7.99750090e-01
1.88188292e-02 -3.23931575e-01 7.40600586e-01 7.08345994e-02
-2.40248963e-01 1.15941894e+00 6.94698513e-01 -3.44559327e-02
6.62963629e-01 -1.29510176e+00 -1.06014125e-01 4.87499624e-01
1.18408076e-01 1.85959153e-02 5.54987192e-01 -1.59366325e-01
-1.13868058e+00 -7.16213167e-01 8.58815849e-01 -2.14363337e-01
4.68977034e-01 -2.19781891e-01 -6.67383015e-01 2.36884370e-01
-7.00819641e-02 7.18024373e-02 1.21785522e+00 -1.24327384e-01
-5.58396995e-01 -4.71317112e-01 -1.89981973e+00 4.04456943e-01
1.30573869e+00 -4.50401485e-01 -4.05771434e-01 -4.75262813e-02
8.20599318e-01 1.61930591e-01 -1.01029813e+00 1.65115520e-01
6.50561273e-01 -1.02648151e+00 8.39219153e-01 -5.73821545e-01
3.32498163e-01 -8.27138424e-02 -6.08040392e-01 -1.08753800e+00
-4.30823117e-01 -5.76382101e-01 -1.69802323e-01 1.09104669e+00
2.26182669e-01 -7.20700324e-01 1.23373210e+00 6.78214729e-01
5.61303616e-01 -7.81257808e-01 -1.30026174e+00 -1.05877054e+00
3.45333219e-01 -3.23178560e-01 9.16031182e-01 1.36990643e+00
6.33843541e-01 4.38831970e-02 -4.85217869e-01 -4.30685937e-01
1.30383837e+00 -1.13897435e-01 5.05940735e-01 -1.54319918e+00
-1.88333422e-01 -4.17556226e-01 -7.28990734e-01 -6.32999480e-01
1.33126512e-01 -1.04665458e+00 -2.85127699e-01 -1.45141995e+00
4.66976345e-01 -4.53005612e-01 -7.89454222e-01 6.19547665e-01
1.59905925e-02 3.62097025e-01 4.77332950e-01 4.11849260e-01
-9.37236190e-01 5.43907166e-01 9.91068542e-01 -2.52993464e-01
-2.21816197e-01 -2.58878559e-01 -1.30480504e+00 4.37153250e-01
1.05143368e+00 -7.64249146e-01 -7.32758522e-01 5.18630520e-02
3.20526302e-01 7.61654377e-02 1.05032086e-01 -9.73157167e-01
5.49975932e-01 -4.38316405e-01 2.29834300e-02 -1.19709238e-01
-1.94170967e-01 -1.16914105e+00 3.78126651e-02 7.54912019e-01
-8.51130366e-01 -3.47615689e-01 -4.59403604e-01 8.99179280e-01
-2.19136607e-02 -6.36255980e-01 1.11752093e+00 -3.61241661e-02
-7.25278497e-01 1.63351715e-01 -2.41715282e-01 3.47742081e-01
1.74858499e+00 -5.91127098e-01 -4.87838030e-01 -4.40047801e-01
-3.37884516e-01 2.20802858e-01 6.15286052e-01 8.75864178e-02
5.25948465e-01 -1.63805449e+00 -6.30925715e-01 -7.36476248e-03
3.88204426e-01 -2.91267842e-01 1.99562773e-01 4.33145195e-01
-4.07330334e-01 -1.66700780e-01 -4.39338654e-01 -2.44207919e-01
-1.34612548e+00 8.40859592e-01 1.56478897e-01 -4.46143031e-01
-2.35261470e-01 6.42646074e-01 -3.12665403e-01 -2.74797708e-01
4.16797936e-01 9.81464088e-02 -1.03648216e-01 4.54172283e-01
4.71378714e-01 6.83297694e-01 -2.22113416e-01 -2.18093291e-01
-2.08454296e-01 4.09616500e-01 -4.04850289e-04 -1.62391961e-02
1.13768804e+00 -2.83741236e-01 1.19486317e-01 1.13628037e-01
1.20865393e+00 -3.18575263e-01 -1.05782855e+00 -6.79668665e-01
1.30109787e-01 -5.95328569e-01 5.30482456e-02 -5.85268199e-01
-1.06310117e+00 3.68775010e-01 6.86479449e-01 4.68079954e-01
1.49028146e+00 -4.86097485e-03 7.49429703e-01 6.87767386e-01
9.47377861e-01 -1.61444044e+00 2.80602127e-01 -4.51714173e-02
4.25833583e-01 -1.12184417e+00 1.10025026e-01 -1.80543333e-01
-9.57905233e-01 7.70302176e-01 3.70133966e-01 2.53688693e-02
8.36774945e-01 4.15084094e-01 6.13149209e-03 1.99002668e-01
-7.89449096e-01 -1.03314705e-01 -4.71085697e-01 9.56707001e-01
-1.33478686e-01 2.77075976e-01 -6.51286721e-01 1.06647050e+00
-2.09025055e-01 4.43426609e-01 9.01039898e-01 1.05527949e+00
-8.22686672e-01 -9.75283086e-01 -2.12386459e-01 6.64901793e-01
-3.03444803e-01 2.35554904e-01 -5.58427334e-01 5.59635103e-01
1.19196801e-02 1.07700491e+00 -8.35217163e-02 -7.41359890e-01
3.37044537e-01 -6.44115135e-02 4.15389061e-01 -4.08333763e-02
-5.94190359e-01 -4.71167833e-01 -3.69051367e-01 -2.74944454e-01
-6.93870127e-01 -4.04313117e-01 -1.37676513e+00 -1.02982605e+00
-4.92816091e-01 4.39902872e-01 2.45677143e-01 5.84296107e-01
2.19764411e-01 2.08464707e-03 9.61487114e-01 -6.27875030e-02
-1.08894062e+00 -3.99348319e-01 -1.37924719e+00 4.87277895e-01
-3.21314856e-02 -4.63383943e-01 -6.19307458e-01 6.92617223e-02] | [8.70521068572998, 5.025423049926758] |
93c957ee-a4fa-42ff-bf47-10e34f582ce3 | track-anything-segment-anything-meets-videos | 2304.11968 | null | https://arxiv.org/abs/2304.11968v2 | https://arxiv.org/pdf/2304.11968v2.pdf | Track Anything: Segment Anything Meets Videos | Recently, the Segment Anything Model (SAM) gains lots of attention rapidly due to its impressive segmentation performance on images. Regarding its strong ability on image segmentation and high interactivity with different prompts, we found that it performs poorly on consistent segmentation in videos. Therefore, in this report, we propose Track Anything Model (TAM), which achieves high-performance interactive tracking and segmentation in videos. To be detailed, given a video sequence, only with very little human participation, i.e., several clicks, people can track anything they are interested in, and get satisfactory results in one-pass inference. Without additional training, such an interactive design performs impressively on video object tracking and segmentation. All resources are available on {https://github.com/gaomingqi/Track-Anything}. We hope this work can facilitate related research. | ['Feng Zheng', 'Fangjing Wang', 'Shang Gao', 'Zhe Li', 'Mingqi Gao', 'Jinyu Yang'] | 2023-04-24 | null | null | null | null | ['video-object-tracking'] | ['computer-vision'] | [-1.71029940e-01 -9.21162069e-02 -7.04436243e-01 -4.01698709e-01
-7.66422987e-01 -6.85486257e-01 2.32396856e-01 -2.83823878e-01
-3.65126222e-01 4.46827531e-01 -1.96320280e-01 -4.61367965e-01
2.68693298e-01 -3.60035181e-01 -9.42093849e-01 -3.52710754e-01
1.31287575e-01 2.55091578e-01 7.22740889e-01 1.36161089e-01
1.58999220e-01 3.95404138e-02 -1.37563467e+00 2.00468242e-01
9.75158334e-01 7.18882978e-01 4.45303649e-01 7.74649680e-01
3.11317872e-02 8.17214966e-01 -3.88957471e-01 -7.10496604e-01
9.55162346e-02 -3.20435137e-01 -8.86021554e-01 2.25153103e-01
9.46014047e-01 -7.27655053e-01 -4.21277136e-01 1.24566698e+00
2.81779319e-01 4.21900861e-02 2.93456554e-01 -1.41264236e+00
-5.66070855e-01 7.76269913e-01 -6.30209804e-01 2.79170066e-01
6.36522532e-01 4.92481589e-01 8.81749392e-01 -9.02257502e-01
8.05653155e-01 9.96217728e-01 6.84188902e-01 6.99108839e-01
-9.79912817e-01 -7.89147139e-01 5.34297705e-01 1.39111027e-01
-1.30373108e+00 -3.01227391e-01 3.94370943e-01 -4.92416650e-01
3.98321748e-01 5.54623365e-01 8.25967252e-01 9.77110803e-01
-1.35026440e-01 1.47976792e+00 6.82259798e-01 -1.65494382e-02
-3.52598689e-02 1.40176192e-01 3.40064317e-01 7.91629553e-01
1.22143053e-01 -1.61259860e-01 -3.37251604e-01 3.41211677e-01
8.80310833e-01 2.46323809e-01 -3.32948804e-01 -1.03415577e-02
-1.30867469e+00 5.32962561e-01 3.79722416e-01 2.44989440e-01
-1.73295543e-01 3.40803444e-01 2.08168983e-01 7.13064000e-02
2.22148761e-01 1.30484939e-01 -4.30185676e-01 -4.60941225e-01
-1.18801773e+00 3.36532563e-01 6.09508932e-01 1.37142873e+00
5.14788449e-01 -9.33825672e-02 -4.25407529e-01 4.98370916e-01
9.17017683e-02 7.67334402e-01 -2.14777719e-02 -1.43957376e+00
3.22025508e-01 2.74631232e-01 3.42587352e-01 -9.57927704e-01
-3.66021931e-01 -2.77085725e-04 -6.50596380e-01 -7.52233043e-02
7.16163397e-01 -6.02692366e-01 -9.14723158e-01 1.60089695e+00
3.47014397e-01 4.65155333e-01 -5.16281843e-01 1.01722825e+00
1.11539447e+00 5.46547174e-01 4.76470172e-01 -1.17167063e-01
1.62654674e+00 -1.08387959e+00 -8.83428931e-01 -2.54561782e-01
3.45308244e-01 -7.92725623e-01 1.28669465e+00 4.94005471e-01
-1.38073683e+00 -8.47899079e-01 -6.09826326e-01 -2.74700765e-03
-1.38293669e-01 3.08998495e-01 8.11241925e-01 5.28104544e-01
-9.18389559e-01 4.27484065e-01 -1.13396525e+00 -4.80689555e-01
6.64469779e-01 2.33128548e-01 -7.62105919e-03 -2.16910541e-02
-9.43352103e-01 2.16676936e-01 2.85518825e-01 8.26085880e-02
-7.87531614e-01 -5.18219173e-01 -5.17946005e-01 -9.65412930e-02
1.07899106e+00 -6.25498772e-01 1.68600690e+00 -9.37187433e-01
-1.28560054e+00 7.41385877e-01 -4.19223219e-01 -3.18003953e-01
9.04027939e-01 -7.38053679e-01 -9.64138731e-02 3.85343641e-01
1.50027454e-01 1.05990827e+00 7.98123419e-01 -1.24451113e+00
-8.10459197e-01 -1.55704364e-01 2.08699405e-01 3.37762646e-02
-2.23827586e-01 3.05938989e-01 -1.43418801e+00 -7.04679072e-01
3.79843195e-03 -1.19295728e+00 -3.06517124e-01 9.84625816e-02
-6.46384120e-01 -3.99073780e-01 9.06759441e-01 -8.86480331e-01
1.56512213e+00 -2.19231296e+00 -1.06427215e-01 -1.76805537e-02
2.41766796e-01 5.53743720e-01 6.19805939e-02 1.17582016e-01
2.32629672e-01 5.70815146e-01 -1.98452994e-02 -2.83888578e-02
1.12683550e-02 -4.12665941e-02 1.48076057e-01 1.80433199e-01
-3.44351195e-02 1.34920228e+00 -9.65458274e-01 -8.45123470e-01
2.43768215e-01 3.13074976e-01 -5.77712119e-01 2.90217578e-01
-5.27813375e-01 5.94161808e-01 -6.12219453e-01 8.99866045e-01
7.59540379e-01 -7.03711510e-01 9.39563960e-02 -1.82625473e-01
-2.33606592e-01 -4.40600753e-01 -1.11172092e+00 1.64329636e+00
1.87972248e-01 8.64085555e-01 4.72848192e-02 -6.62849844e-01
2.50924408e-01 3.80149662e-01 5.55934727e-01 -7.21722066e-01
1.45960867e-01 -1.40592217e-01 -2.17214495e-01 -8.53963435e-01
5.71351886e-01 6.59587920e-01 5.78689910e-02 3.26994449e-01
-2.05650240e-01 6.55566752e-02 6.39388025e-01 5.66816866e-01
7.80642331e-01 2.43533865e-01 -7.04586431e-02 8.73392597e-02
2.90633380e-01 2.81954020e-01 5.87569952e-01 1.15746510e+00
-5.51263809e-01 7.24387646e-01 3.24482352e-01 -2.41700560e-01
-7.55209327e-01 -1.08410919e+00 2.57934798e-02 1.27819407e+00
7.29090869e-01 -4.30510432e-01 -1.16211641e+00 -5.89719534e-01
-1.56823933e-01 5.72766304e-01 -3.37292194e-01 3.97334307e-01
-7.16927588e-01 -2.41185442e-01 3.55766594e-01 6.24150634e-01
8.07297647e-01 -1.32413638e+00 -5.00839949e-01 -4.36632894e-02
-5.86580217e-01 -1.05650532e+00 -9.08824921e-01 -3.11317474e-01
-8.37582588e-01 -1.22588396e+00 -9.68454301e-01 -8.89509380e-01
6.41810060e-01 6.86320782e-01 1.11048162e+00 5.34926236e-01
-2.84958959e-01 5.65067112e-01 -4.69706357e-01 -3.19416076e-01
4.36227722e-03 1.89896617e-02 -3.43402416e-01 -3.81889910e-01
3.93084556e-01 3.63911092e-02 -8.08522642e-01 7.83432186e-01
-9.64478254e-01 3.85959446e-01 4.10565287e-01 2.74521232e-01
5.43400347e-01 -2.12801211e-02 2.17066333e-01 -1.09094107e+00
3.86589646e-01 -4.23696429e-01 -4.97399896e-01 2.86274135e-01
-3.13793153e-01 -5.71229815e-01 1.88177973e-01 -5.73224664e-01
-1.07020795e+00 6.42838851e-02 -1.99080601e-01 -3.93469810e-01
-3.12456161e-01 3.44368905e-01 1.30603667e-02 2.18482632e-02
3.54875743e-01 6.93378448e-02 -1.36662260e-01 -3.59611839e-01
4.09938127e-01 5.53054869e-01 6.48165464e-01 -4.50398713e-01
7.95263290e-01 2.64841914e-01 -6.63718641e-01 -7.52502382e-01
-9.98816848e-01 -5.95131457e-01 -6.22949600e-01 -6.23578787e-01
1.22409391e+00 -9.70242858e-01 -1.08606076e+00 6.06194913e-01
-8.88279200e-01 -7.43666708e-01 2.16341600e-01 4.17912573e-01
-4.06920940e-01 3.69937897e-01 -8.17368567e-01 -7.05500782e-01
-3.13809551e-02 -1.12898457e+00 8.31038296e-01 8.08010995e-01
-3.33949953e-01 -9.04949903e-01 -5.04406154e-01 5.96244216e-01
2.57303745e-01 1.36142820e-01 1.62139013e-01 -4.83890831e-01
-1.03977489e+00 -1.67810366e-01 -3.94043654e-01 1.31705940e-01
-1.11772241e-02 4.12449330e-01 -5.99559844e-01 -2.96821594e-01
-4.89473730e-01 -2.24702924e-01 7.46168673e-01 7.79725671e-01
1.64321518e+00 -3.43786508e-01 -6.28734529e-01 5.10331631e-01
1.16960633e+00 3.72889251e-01 5.31552255e-01 2.55993903e-01
8.53170812e-01 2.33232543e-01 1.00595903e+00 3.25064451e-01
4.43097562e-01 7.19727755e-01 3.08555752e-01 -3.05990189e-01
-2.90512443e-01 -2.97800034e-01 1.90596879e-01 5.11106670e-01
-4.83348936e-01 -4.70344454e-01 -7.39910722e-01 3.70622039e-01
-2.11734486e+00 -1.34691834e+00 -4.13597018e-01 2.04082465e+00
7.16005027e-01 2.76146322e-01 4.27019507e-01 -3.83922666e-01
9.02202427e-01 1.25922635e-01 -6.83700144e-01 4.86747362e-02
-3.84725034e-02 -2.61448801e-01 5.59780955e-01 3.87410611e-01
-1.32477808e+00 1.22856355e+00 6.33930254e+00 8.56236041e-01
-8.91160071e-01 2.21581254e-02 7.37549782e-01 -1.40782133e-01
-1.23507693e-01 -1.43619865e-01 -9.16347742e-01 7.78433800e-01
5.29406607e-01 -1.37086883e-01 3.38512152e-01 7.41274416e-01
5.22968471e-01 -3.32351685e-01 -9.26348269e-01 1.02095604e+00
-1.47371128e-01 -1.18789017e+00 -8.31597298e-02 -2.24831864e-01
7.70107210e-01 -1.99950844e-01 3.03600818e-01 2.66189516e-01
4.13393021e-01 -8.12477112e-01 8.92530084e-01 5.32059669e-01
4.47403729e-01 -4.23896968e-01 5.98805964e-01 4.68782395e-01
-1.17243087e+00 3.21983621e-02 -5.10559194e-02 1.76148385e-01
5.30161142e-01 2.35820860e-01 -4.79221910e-01 3.17678809e-01
9.15572405e-01 8.06744993e-01 -7.84679174e-01 1.44960833e+00
-4.58302230e-01 9.56110716e-01 -2.62126923e-01 -1.82470754e-02
2.70208329e-01 -2.00994253e-01 4.05387878e-01 1.51499760e+00
2.01840684e-01 4.94296163e-01 6.20875299e-01 5.66235900e-01
-1.37145847e-01 -4.61429805e-02 -2.15410233e-01 -2.33008936e-02
5.85623443e-01 1.27042663e+00 -1.07941198e+00 -6.33462250e-01
-6.32996380e-01 9.77807462e-01 -3.81800160e-02 7.18289614e-01
-1.30976486e+00 -8.89514461e-02 3.66138726e-01 3.75798911e-01
4.73480910e-01 -3.42294484e-01 -2.74153680e-01 -1.07634103e+00
-6.72703534e-02 -9.03484523e-01 4.89076316e-01 -9.63327408e-01
-9.10982907e-01 2.82577872e-01 5.23603708e-02 -1.26946628e+00
1.26964012e-02 -1.89659595e-01 -5.39885700e-01 2.18165934e-01
-1.06690180e+00 -1.12586391e+00 -5.58607638e-01 6.97301805e-01
9.04877722e-01 3.69859338e-01 6.30378425e-02 5.06743848e-01
-9.71597254e-01 6.70069456e-01 -2.50331610e-01 4.88464624e-01
7.81325400e-01 -1.11855733e+00 4.98503387e-01 9.00115788e-01
3.31335455e-01 7.55534768e-01 8.09637070e-01 -8.85809898e-01
-1.45048928e+00 -1.14669919e+00 5.07325113e-01 -5.50033987e-01
4.66859341e-01 -1.65889934e-02 -9.96188939e-01 1.10958672e+00
4.62744892e-01 -9.63788033e-02 4.21662629e-01 4.66021635e-02
7.36379921e-02 3.42689335e-01 -8.76436234e-01 8.77830327e-01
1.38686454e+00 -8.69726017e-02 -2.74867982e-01 4.63411421e-01
6.73957050e-01 -8.05994809e-01 -7.25293100e-01 2.86294252e-01
6.33479714e-01 -1.11876667e+00 1.02857733e+00 -4.66542929e-01
2.32934669e-01 -4.21664745e-01 2.06919104e-01 -6.55813932e-01
-3.40521842e-01 -8.05242717e-01 -9.26260874e-02 1.14166212e+00
3.99520963e-01 -2.30376497e-01 9.98260677e-01 9.30310488e-01
-3.83057375e-03 -5.88981390e-01 -3.24358433e-01 -7.99311459e-01
-2.98812836e-01 -5.04261017e-01 2.92875409e-01 7.74336040e-01
-1.82777017e-01 -3.64456847e-02 -6.42541766e-01 3.15621734e-01
6.29753113e-01 1.27873167e-01 1.06131625e+00 -1.03885925e+00
-1.00897200e-01 -3.32289100e-01 5.78193516e-02 -1.64164364e+00
-8.47723037e-02 -5.39949656e-01 1.23419829e-01 -1.59190094e+00
5.10159850e-01 -3.37790519e-01 -4.79098000e-02 6.13699555e-01
-6.03315294e-01 6.46311045e-01 5.40915310e-01 4.00212109e-01
-1.49166906e+00 -1.12771820e-02 1.59013188e+00 -1.48456335e-01
-2.99127489e-01 3.34659010e-01 -7.50466704e-01 8.67871523e-01
1.02141845e+00 -4.01024997e-01 -1.37766346e-01 -5.03198802e-01
1.27789918e-02 2.99184501e-01 4.46063638e-01 -9.59851027e-01
4.95525062e-01 -3.25846761e-01 5.02827883e-01 -7.77046204e-01
1.70595869e-01 -6.63442254e-01 4.23979878e-01 5.52989602e-01
-3.10689598e-01 -5.11193164e-02 2.00646728e-01 4.11984921e-01
-2.99310386e-01 -2.44874299e-01 5.42127609e-01 -3.63007218e-01
-1.16848934e+00 6.80167139e-01 -3.14965278e-01 2.05905184e-01
1.21701288e+00 -5.54171741e-01 -1.76508442e-01 -5.65104246e-01
-1.05085003e+00 6.55419946e-01 6.47303998e-01 4.77561504e-01
3.12637210e-01 -1.23092735e+00 -5.83884597e-01 -9.96908695e-02
-1.15754172e-01 -5.04673161e-02 4.11429137e-01 1.03111136e+00
-4.74107057e-01 3.78229797e-01 -2.83893235e-02 -9.22689438e-01
-1.59705806e+00 4.57842648e-01 -1.13516204e-01 2.61377841e-01
-6.43620610e-01 8.73555720e-01 1.64703920e-01 2.28759423e-02
4.81173962e-01 -9.01423618e-02 -1.31279275e-01 2.21614409e-02
6.84891284e-01 5.78251898e-01 -4.50100631e-01 -3.49058568e-01
-1.19490035e-01 7.48887122e-01 -2.84474492e-01 4.53106463e-02
8.83322775e-01 -4.73352939e-01 3.00766349e-01 3.04626763e-01
8.09823394e-01 9.19923857e-02 -1.80600619e+00 -5.41546121e-02
-4.81364094e-02 -8.36432815e-01 -2.69624501e-01 -6.71104670e-01
-1.32883298e+00 5.96274436e-01 3.90377223e-01 6.02932513e-01
9.12024736e-01 1.24225304e-01 9.83162820e-01 2.44953260e-01
3.74322385e-01 -1.01227069e+00 2.69689113e-01 3.87987018e-01
3.83659184e-01 -1.59683371e+00 2.44256426e-02 -5.68530023e-01
-8.67953897e-01 8.29760492e-01 9.37830746e-01 1.18411966e-01
5.05466342e-01 2.54826933e-01 3.18457812e-01 -2.13055238e-01
-5.18154502e-01 -3.22490603e-01 2.14669615e-01 5.68344295e-01
5.40205002e-01 6.86275363e-02 -2.55881339e-01 2.37884775e-01
2.58694421e-02 2.33528942e-01 2.71153837e-01 6.48222864e-01
-7.44606376e-01 -8.08390260e-01 -2.44987965e-01 4.42832679e-01
-6.19976401e-01 3.45420092e-03 -1.69404209e-01 9.89407301e-01
-8.88538510e-02 1.08843374e+00 4.34661657e-02 -1.47658303e-01
2.17688084e-01 -3.38875413e-01 2.04039514e-01 -3.08439791e-01
-5.51409602e-01 4.30292897e-02 -1.78852249e-02 -9.31968749e-01
-4.68498141e-01 -8.70121598e-01 -1.37493670e+00 -6.27730787e-01
-1.67864308e-01 9.11292061e-02 3.89338702e-01 6.43574297e-01
1.73221692e-01 4.19980556e-01 2.51789927e-01 -8.50935876e-01
-1.91585109e-01 -7.05645323e-01 -3.60469013e-01 5.35990000e-01
4.93000522e-02 -3.92169446e-01 -1.40265882e-01 5.36314070e-01] | [9.215188026428223, -0.14706513285636902] |
03736594-eb84-43b6-b40f-08f96d61e5e1 | benchmarking-bonus-based-exploration-methods | 1908.02388 | null | https://arxiv.org/abs/1908.02388v3 | https://arxiv.org/pdf/1908.02388v3.pdf | Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment | This paper provides an empirical evaluation of recently developed exploration algorithms within the Arcade Learning Environment (ALE). We study the use of different reward bonuses that incentives exploration in reinforcement learning. We do so by fixing the learning algorithm used and focusing only on the impact of the different exploration bonuses in the agent's performance. We use Rainbow, the state-of-the-art algorithm for value-based agents, and focus on some of the bonuses proposed in the last few years. We consider the impact these algorithms have on performance within the popular game Montezuma's Revenge which has gathered a lot of interest from the exploration community, across the the set of seven games identified by Bellemare et al. (2016) as challenging for exploration, and easier games where exploration is not an issue. We find that, in our setting, recently developed bonuses do not provide significantly improved performance on Montezuma's Revenge or hard exploration games. We also find that existing bonus-based methods may negatively impact performance on games in which exploration is not an issue and may even perform worse than $\epsilon$-greedy exploration. | ['Adrien Ali Taïga', 'William Fedus', 'Marc G. Bellemare', 'Marlos C. Machado', 'Aaron Courville'] | 2019-08-06 | null | null | null | null | ['montezumas-revenge'] | ['playing-games'] | [-4.78968203e-01 1.52153254e-01 -1.26217127e-01 2.57333547e-01
-6.43543661e-01 -7.52732992e-01 5.74502468e-01 2.22237557e-01
-1.11356819e+00 1.07499623e+00 2.09679425e-01 -5.52483976e-01
-6.46567643e-01 -7.78669238e-01 -6.09977722e-01 -7.17968762e-01
-8.35249186e-01 5.69577157e-01 1.20055161e-01 -7.47768104e-01
5.08790851e-01 1.34337381e-01 -1.45980120e+00 -2.99514055e-01
8.37830603e-01 5.81668198e-01 1.23238049e-01 5.34850955e-01
3.20477337e-01 6.91386461e-01 -7.60969162e-01 -2.98897713e-01
7.90378392e-01 -4.94228721e-01 -8.49964261e-01 -3.00184608e-01
-1.46085069e-01 -4.48888302e-01 -1.41624674e-01 9.71315801e-01
5.67838252e-01 2.91574776e-01 3.31271768e-01 -1.31806338e+00
-6.21781461e-02 1.13955045e+00 -7.67764032e-01 6.41168058e-01
1.55661032e-01 5.32091141e-01 1.15914857e+00 -1.55748546e-01
8.76747489e-01 1.14497399e+00 4.30977821e-01 4.47435200e-01
-1.28265619e+00 -9.08523560e-01 6.81072995e-02 1.14089243e-01
-8.37447464e-01 -9.66240689e-02 4.51916069e-01 -4.16388959e-01
8.30444574e-01 3.05671077e-02 1.01278210e+00 1.03054166e+00
3.55404094e-02 7.68092752e-01 1.55623722e+00 -3.49005848e-01
8.49125445e-01 -2.38481715e-01 -3.94765168e-01 4.50717539e-01
4.06735003e-01 9.23555374e-01 -5.74449837e-01 -2.73410678e-01
7.84563601e-01 -5.84293067e-01 -1.38898283e-01 -7.14034975e-01
-9.52255964e-01 1.26617718e+00 6.86655223e-01 -1.74382385e-02
-5.27903259e-01 5.19512236e-01 3.89867693e-01 6.02698207e-01
1.06594965e-01 1.22127855e+00 -3.33905876e-01 -8.15136433e-01
-6.65136814e-01 8.42001021e-01 7.15818524e-01 3.30734581e-01
6.32807374e-01 5.05052209e-02 1.59288228e-01 3.73598874e-01
1.77083567e-01 -1.28871262e-01 5.40942967e-01 -1.22521460e+00
4.61997271e-01 3.10318649e-01 4.90893126e-01 -6.50848627e-01
-6.44858301e-01 -6.32909060e-01 1.92675255e-02 1.09854519e+00
6.65739834e-01 -7.14772463e-01 -4.97567952e-01 2.02412558e+00
1.89496651e-01 -1.03894494e-01 2.24901631e-01 1.02212334e+00
2.82816857e-01 1.79841280e-01 8.02498590e-03 -8.19096491e-02
1.06391323e+00 -9.51864064e-01 -2.46687964e-01 -4.53726858e-01
9.19682741e-01 -3.47291589e-01 1.13676870e+00 6.35317385e-01
-1.21329451e+00 4.17851880e-02 -1.12389147e+00 5.56571841e-01
-3.35954368e-01 -4.77096826e-01 1.17801476e+00 8.38197589e-01
-1.11075723e+00 8.90421569e-01 -8.19927573e-01 -2.68276513e-01
6.13364041e-01 2.42768183e-01 1.64691344e-01 3.98551345e-01
-1.16626263e+00 1.20677340e+00 5.33230424e-01 -4.62918073e-01
-1.23349333e+00 -3.77605110e-01 -4.12735432e-01 2.33871073e-01
1.14078927e+00 -2.74533302e-01 1.31238663e+00 -9.61506605e-01
-1.42769372e+00 4.94579732e-01 7.14391351e-01 -9.38222229e-01
8.94251525e-01 -1.21377736e-01 2.49498636e-01 -1.30161822e-01
2.48845011e-01 9.23514009e-01 2.01246828e-01 -1.10264361e+00
-6.10549450e-01 -1.33332938e-01 7.45776951e-01 5.67160189e-01
-2.32664719e-02 -1.62865311e-01 2.90652841e-01 -6.35242045e-01
-3.86061817e-01 -1.09322166e+00 -6.20875776e-01 -3.65256548e-01
-1.02724686e-01 -3.53201419e-01 2.11371407e-01 -1.22927979e-01
1.00303185e+00 -1.75995255e+00 2.23857820e-01 2.43624970e-01
1.45058408e-01 -1.61217660e-01 -1.97505251e-01 6.39083147e-01
5.45984209e-02 2.10264325e-01 -2.39298776e-01 -3.95220444e-02
3.71162236e-01 2.39898935e-01 -1.19063683e-01 3.60474885e-01
-4.11794305e-01 9.82539773e-01 -1.11112964e+00 -1.08329788e-01
-1.23133697e-01 -3.10658365e-01 -8.19547772e-01 3.63783948e-02
-4.23371136e-01 2.60120362e-01 -2.97414541e-01 3.81204814e-01
2.07074299e-01 -2.42923573e-02 8.48698169e-02 8.47619712e-01
-4.06490415e-01 4.85644549e-01 -1.22115731e+00 1.75548208e+00
-1.33796439e-01 5.96879065e-01 6.71763346e-02 -6.43975019e-01
5.00444829e-01 -1.01710483e-01 3.62800777e-01 -6.74690723e-01
2.34194264e-01 2.69226074e-01 8.93719494e-01 -1.15848966e-01
6.64841056e-01 -1.49910539e-01 6.57256320e-02 1.07805109e+00
-2.97944665e-01 -1.24470994e-01 6.41648769e-01 2.22326413e-01
1.36941504e+00 2.80302495e-01 3.57902944e-01 -7.09897518e-01
-1.96070895e-01 2.81130910e-01 4.57955718e-01 1.07188833e+00
-3.47585589e-01 1.28385559e-01 9.34831798e-01 -1.22983567e-01
-1.01535141e+00 -1.02864552e+00 2.54241247e-02 1.42637539e+00
1.57826722e-01 -6.54267371e-01 -7.45922208e-01 -6.29896283e-01
-1.24786356e-02 7.58986354e-01 -1.00250220e+00 -5.41150011e-02
-1.76221624e-01 -9.01412785e-01 5.95925570e-01 3.71348202e-01
5.66172063e-01 -1.43775380e+00 -1.70967293e+00 -1.57466419e-02
2.49502048e-01 -2.27151990e-01 -5.72715402e-02 4.89219725e-01
-7.09317863e-01 -1.05083203e+00 -6.50207460e-01 -4.38629165e-02
1.27027139e-01 2.47838814e-02 1.17540646e+00 -5.10068703e-03
-1.80640087e-01 4.34796065e-01 -5.97305000e-01 -6.25245333e-01
-1.92901984e-01 3.03484648e-01 1.26308292e-01 -8.05397987e-01
2.76118845e-01 -7.49854445e-01 -6.70879483e-01 8.92811790e-02
-8.06079388e-01 -6.68126345e-02 4.55225468e-01 8.67950201e-01
-1.39860377e-01 2.74228901e-01 7.29407489e-01 -6.41531408e-01
1.19687116e+00 -8.63107502e-01 -1.04423761e+00 -3.08394074e-01
-9.02880609e-01 4.04634327e-01 2.30681032e-01 -3.42385024e-01
-7.95530915e-01 -5.38364172e-01 1.05790198e-01 -1.57747760e-01
1.66632921e-01 7.66380787e-01 5.00986695e-01 -3.10307592e-01
1.10541463e+00 -1.40318125e-01 5.89832030e-02 -4.13845062e-01
1.58296615e-01 1.28600135e-01 6.36485741e-02 -6.99500084e-01
7.51494646e-01 2.98138618e-01 9.77892894e-03 -3.19197774e-01
-1.92050412e-01 3.18606272e-02 5.34503050e-02 -1.48353606e-01
6.53125525e-01 -8.05591226e-01 -1.07720220e+00 2.76553363e-01
-6.90559983e-01 -9.25751746e-01 -6.51187658e-01 4.43287253e-01
-9.33440804e-01 9.82880667e-02 -4.64508951e-01 -8.23902607e-01
1.42193362e-01 -1.38341320e+00 2.59355068e-01 5.21907151e-01
-1.82783335e-01 -7.66295433e-01 5.57168007e-01 6.33576559e-03
7.15470910e-01 3.20975274e-01 5.52749336e-01 -5.12312770e-01
-7.32125819e-01 6.35816932e-01 9.60380584e-02 -4.15641963e-01
-2.55217195e-01 -4.36829001e-01 -6.65196121e-01 -5.42804062e-01
-1.89497575e-01 -7.32975185e-01 1.01430976e+00 4.57293928e-01
7.65703857e-01 -3.23541194e-01 -4.97012250e-02 4.85510081e-01
1.26905096e+00 3.91876966e-01 7.00051188e-01 1.25311303e+00
1.33821210e-02 8.58170629e-01 8.57813001e-01 8.05885017e-01
2.80128837e-01 7.57339835e-01 1.04888523e+00 2.53021061e-01
5.89404941e-01 -2.23971754e-01 3.81243259e-01 -1.31637603e-01
-2.62370884e-01 -3.88768874e-02 -8.30855966e-01 7.31353760e-01
-2.01968503e+00 -1.05569136e+00 4.14438188e-01 2.24101639e+00
1.00747633e+00 4.39467907e-01 9.83113885e-01 -2.32683435e-01
2.96903580e-01 2.24213153e-01 -7.40683138e-01 -7.01398253e-01
3.56277265e-02 3.75533998e-01 7.08679020e-01 5.83490551e-01
-6.87421381e-01 1.03619111e+00 6.57697725e+00 8.95422399e-01
-7.63167977e-01 3.10943127e-02 5.32675624e-01 -7.31807172e-01
-3.74684960e-01 3.06882560e-01 -3.00729781e-01 5.03853381e-01
8.74265075e-01 -4.77167785e-01 8.99630785e-01 1.07266319e+00
7.12554827e-02 -7.51665115e-01 -9.24373507e-01 6.20845497e-01
-3.58301252e-01 -1.25450528e+00 -7.54190922e-01 6.51868880e-01
7.27850854e-01 3.25674683e-01 2.89531797e-01 4.92878944e-01
1.17958033e+00 -1.39559758e+00 7.77031898e-01 -3.63771319e-02
1.83625728e-01 -1.07351625e+00 4.54736650e-01 3.40347737e-01
-4.60900337e-01 -4.06815469e-01 -2.51478076e-01 -7.17892289e-01
-3.03123649e-02 1.11810394e-01 -8.69549155e-01 -1.26545159e-02
8.39788258e-01 1.44479886e-01 -6.82963133e-01 1.09819412e+00
-4.01837170e-01 7.32295692e-01 -4.86755073e-01 -3.40626240e-01
9.12282228e-01 -3.66382301e-01 7.77542770e-01 6.73266768e-01
1.64873213e-01 3.89008634e-02 -5.56096318e-04 1.13327730e+00
3.60767879e-02 -4.92036715e-02 -7.01275468e-01 -2.74074733e-01
5.36548555e-01 1.07829607e+00 -8.81577849e-01 9.86778513e-02
7.05810860e-02 3.43096286e-01 4.29351121e-01 1.73493937e-01
-7.87310302e-01 -2.57813156e-01 8.65494370e-01 4.12632748e-02
3.55222940e-01 -5.86842857e-02 -3.14145416e-01 -9.04679120e-01
-1.51654407e-01 -1.00646019e+00 5.53663850e-01 -7.39235282e-01
-7.76680589e-01 3.13655049e-01 2.11482033e-01 -8.89150798e-01
-6.27459824e-01 -2.58426011e-01 -6.23316526e-01 6.73160613e-01
-1.34083974e+00 -3.23313862e-01 1.34636447e-01 2.06009716e-01
4.38136190e-01 -3.84079307e-01 4.03095692e-01 -3.38081360e-01
-2.83432454e-01 5.28753996e-01 2.93806255e-01 -2.52040327e-01
3.40562701e-01 -1.48613298e+00 4.29400861e-01 7.47870922e-01
1.86538458e-01 5.10727942e-01 1.06953847e+00 -6.62476480e-01
-9.73559320e-01 -2.93872297e-01 -1.77100807e-01 -3.58681679e-01
7.95452714e-01 -2.71066368e-01 -5.12948096e-01 8.42772126e-01
4.56548542e-01 -5.60130596e-01 3.42404604e-01 4.98596996e-01
-1.59785330e-01 4.58219230e-01 -1.13760841e+00 9.98552740e-01
1.08061182e+00 -6.42007515e-02 -6.13815963e-01 -5.19572105e-03
5.19826591e-01 -6.15359902e-01 -3.69936347e-01 6.11020960e-02
4.52119082e-01 -1.51761198e+00 8.45836580e-01 -7.95825541e-01
7.94729948e-01 6.24862723e-02 1.58073772e-02 -1.87735152e+00
-2.84058183e-01 -8.80713344e-01 3.06047708e-01 7.45831490e-01
3.53070498e-01 -7.92815983e-01 1.18341708e+00 2.54877061e-01
9.19752046e-02 -9.79287803e-01 -1.14154160e+00 -1.00165415e+00
6.49830937e-01 -1.90900847e-01 5.54973781e-01 8.50730956e-01
4.66082007e-01 -1.62167754e-03 -3.81272167e-01 -4.14689451e-01
7.08707511e-01 2.10680738e-02 9.32729781e-01 -9.67160404e-01
-8.51971805e-01 -9.12149608e-01 -1.18993297e-01 -6.22532845e-01
-1.12748168e-01 -7.01230109e-01 -1.45434856e-01 -1.11003768e+00
1.26372829e-01 -7.36885667e-01 -1.66129336e-01 5.07922947e-01
-1.00134136e-02 -6.87398538e-02 5.86753666e-01 2.16431171e-01
-6.30804777e-01 6.02148771e-01 1.14472842e+00 2.15565547e-01
-3.90098125e-01 -1.06309898e-01 -1.08228338e+00 6.81113899e-01
9.48655486e-01 -5.42864621e-01 -5.29972434e-01 -1.40936270e-01
7.20733643e-01 -2.33934466e-02 3.24945986e-01 -1.06249130e+00
9.73096415e-02 -5.42119622e-01 -3.79139669e-02 4.31428291e-02
2.59383053e-01 -4.56698447e-01 2.45344304e-02 9.33550894e-01
-6.19719326e-01 4.50110495e-01 4.18874055e-01 4.75812197e-01
3.03326339e-01 -5.26931226e-01 6.94092453e-01 -3.89494628e-01
-6.47085488e-01 -8.10833648e-02 -6.23522162e-01 4.76647228e-01
1.08358049e+00 -2.91438878e-01 -4.02645350e-01 -7.28573143e-01
-3.90205085e-01 4.87181157e-01 7.06329703e-01 1.84133962e-01
1.26974404e-01 -1.05829144e+00 -7.38863170e-01 -2.40666866e-01
5.79599030e-02 -2.68245429e-01 -3.96594964e-02 6.99901521e-01
-4.57807332e-01 2.21778542e-01 -8.13127816e-01 -5.14836386e-02
-9.59027767e-01 3.05965304e-01 5.16311944e-01 -6.42580152e-01
-3.98409754e-01 8.95108521e-01 1.55681238e-01 -3.37009549e-01
1.91892743e-01 -4.25653383e-02 -1.21344224e-01 2.18662620e-01
1.09821834e-01 7.50285983e-01 -3.80520791e-01 1.48207298e-03
-2.00480118e-01 -5.90708852e-02 -2.92293131e-01 -8.02223146e-01
1.49732172e+00 7.76686519e-02 3.96502107e-01 2.76427120e-01
4.02659237e-01 -4.67971750e-02 -1.53039110e+00 1.11847259e-01
-1.11014225e-01 -6.42207325e-01 1.39854237e-01 -1.10517919e+00
-9.79096353e-01 6.79692447e-01 6.19628131e-01 4.21086013e-01
8.52697194e-01 -1.61799759e-01 4.13396239e-01 3.70891035e-01
7.54257679e-01 -1.42114151e+00 2.31583565e-01 4.86797810e-01
8.07730079e-01 -1.21354663e+00 9.49124023e-02 4.09422725e-01
-7.49238372e-01 6.66951656e-01 8.12682509e-01 -4.04549420e-01
1.66587546e-01 1.47676528e-01 -9.85533148e-02 -5.44289827e-01
-9.71533239e-01 -4.79119241e-01 -5.16499460e-01 5.80365539e-01
-6.24488220e-02 7.86657035e-02 -6.81265652e-01 3.59948665e-01
-7.78511763e-01 -1.28257647e-01 1.01411748e+00 1.12158132e+00
-5.63780308e-01 -1.03159189e+00 -4.14958000e-01 5.05641580e-01
-3.39938372e-01 -1.37561426e-01 -5.28228879e-01 1.15077913e+00
-7.17195645e-02 7.37516105e-01 7.46683404e-02 -2.68572390e-01
-8.41849223e-02 -2.73746729e-01 5.47357857e-01 -3.37141931e-01
-8.88671994e-01 -1.80563241e-01 1.58373058e-01 -6.26948297e-01
-9.53052267e-02 -9.65173483e-01 -1.12264454e+00 -5.67234814e-01
-1.55665547e-01 5.30493081e-01 5.09097397e-01 8.93608391e-01
2.26918459e-01 3.22031736e-01 3.86270076e-01 -7.68427789e-01
-8.81486297e-01 -8.48028183e-01 -8.02838743e-01 1.55339435e-01
2.12218985e-01 -1.16014433e+00 -6.13637447e-01 -8.18249702e-01] | [3.7964119911193848, 1.7081049680709839] |
d804532c-c620-441d-b902-96ca8050c00b | scene-labeling-using-sparse-precision-matrix | null | null | http://openaccess.thecvf.com/content_cvpr_2016/html/Souly_Scene_Labeling_Using_CVPR_2016_paper.html | http://openaccess.thecvf.com/content_cvpr_2016/papers/Souly_Scene_Labeling_Using_CVPR_2016_paper.pdf | Scene Labeling Using Sparse Precision Matrix | Scene labeling task is to segment the image into meaningful regions and categorize them into classes of objects which comprised the image. Commonly used methods typically find the local features for each segment and label them using classifiers. Afterwards, labeling is smoothed in order to make sure that neighboring regions receive similar labels. However, these methods ignore expressive connections between labels and non-local dependencies among regions. In this paper, we propose to use a sparse estimation of precision matrix (also called concentration matrix), which is the inverse of covariance matrix of data obtained by graphical lasso to find interaction between labels and regions. To do this, we formulate the problem as an energy minimization over a graph, whose structure is captured by applying sparse constraint on the elements of the precision matrix. This graph encodes (or represents) only significant interactions and avoids a fully connected graph, which is typically used to reflect the long distance associations. We use local and global information to achieve better labeling. We assess our approach on three datasets and obtained promising results. | ['Nasim Souly', 'Mubarak Shah'] | 2016-06-01 | null | null | null | cvpr-2016-6 | ['scene-labeling'] | ['computer-vision'] | [ 3.66091490e-01 9.31054726e-02 -3.90030146e-01 -5.98204434e-01
-4.29682791e-01 -6.82457983e-01 5.33858359e-01 5.84591448e-01
-2.08766580e-01 3.50178361e-01 3.13215703e-01 2.45485768e-01
-3.59827280e-01 -7.78481483e-01 -7.39953101e-01 -8.27603936e-01
-1.39626354e-01 1.97411016e-01 1.90039352e-02 3.72095942e-01
3.52435440e-01 5.70213675e-01 -1.38469255e+00 2.07872733e-01
8.73464882e-01 8.30457091e-01 2.39939615e-01 1.11150937e-02
-1.86841056e-01 8.84353161e-01 -2.43082315e-01 7.66016543e-02
1.32969826e-01 -5.79593360e-01 -7.90814877e-01 6.42206192e-01
4.87199455e-01 3.08664143e-01 -6.47055954e-02 1.42889464e+00
-6.63089529e-02 3.19439292e-01 9.66273844e-01 -1.00129592e+00
-2.73867339e-01 6.50344014e-01 -1.06686318e+00 -7.41542876e-02
1.57191113e-01 -3.78486753e-01 1.35614645e+00 -8.19781065e-01
7.74650931e-01 1.07911611e+00 5.40047169e-01 8.35969392e-03
-1.51781237e+00 -4.33562040e-01 4.06760573e-01 1.35629838e-02
-1.77905679e+00 -3.05818260e-01 9.29357171e-01 -8.33494961e-01
3.67469609e-01 3.61105055e-01 4.90189135e-01 5.15159190e-01
1.90342572e-02 5.27305961e-01 9.82576549e-01 -3.90131533e-01
4.01034802e-01 1.97452486e-01 5.83938122e-01 9.54016149e-01
5.01327217e-02 -3.65997046e-01 -4.85043675e-01 -2.79387414e-01
4.75326002e-01 1.77998737e-01 -3.02013010e-01 -7.65244007e-01
-1.18151689e+00 9.09328640e-01 8.44511449e-01 4.17522192e-01
-4.43423271e-01 2.71696951e-02 1.28721356e-01 -2.16796175e-01
4.61915016e-01 2.46205002e-01 -5.75770298e-03 5.45136750e-01
-7.88369775e-01 -3.06214392e-01 5.24656296e-01 7.68668473e-01
1.38903022e+00 -5.16662717e-01 -2.08015576e-01 1.00450754e+00
4.81241375e-01 7.34273568e-02 5.74064776e-02 -9.91284728e-01
3.58127326e-01 1.04403830e+00 -1.61883026e-01 -1.58884466e+00
-6.27632022e-01 -4.98055190e-01 -1.00880587e+00 -5.17297015e-02
4.98878330e-01 5.84946051e-02 -7.80885458e-01 1.80268848e+00
4.74720985e-01 3.45659047e-01 -3.97423655e-01 1.04585111e+00
6.06546938e-01 5.85925698e-01 5.79062700e-02 -2.92610824e-01
1.29023635e+00 -9.10484791e-01 -6.83855116e-01 -3.25913370e-01
8.65173340e-01 -5.04001737e-01 9.00270820e-01 1.83448836e-01
-6.69453502e-01 -4.55398113e-01 -8.82941723e-01 4.53514494e-02
-1.88246742e-01 4.60854441e-01 4.90345627e-01 3.09398890e-01
-6.89407408e-01 5.04486501e-01 -5.87768495e-01 -3.25394124e-01
3.79166126e-01 3.62438649e-01 -4.73809004e-01 -2.08606154e-01
-7.41634250e-01 4.77644265e-01 2.05865771e-01 1.56978458e-01
-6.59883261e-01 -5.18267035e-01 -1.03134537e+00 -4.25949208e-02
5.36795497e-01 -3.19519579e-01 1.97807357e-01 -9.39691722e-01
-9.51615572e-01 1.01825738e+00 -4.57353324e-01 -9.69460607e-02
1.20099308e-03 4.38135415e-02 7.92483520e-03 7.03914464e-02
2.73958623e-01 5.43390751e-01 7.98287809e-01 -1.46459377e+00
-4.01258260e-01 -4.98324603e-01 8.03280920e-02 2.65326977e-01
-1.77815348e-01 -1.46662772e-01 -6.88005567e-01 -5.84125757e-01
7.13736832e-01 -1.08836555e+00 -4.09248829e-01 -8.48735198e-02
-7.94143081e-01 -1.10445730e-01 5.91493070e-01 -5.82458019e-01
1.27210951e+00 -2.43476653e+00 3.19855332e-01 8.78875136e-01
4.86643702e-01 -3.94735098e-01 -1.01485446e-01 2.85101861e-01
-1.38228878e-01 -1.21798962e-02 -5.84856033e-01 -2.13393822e-01
-2.63361841e-01 2.79557407e-01 -4.06953916e-02 9.91344571e-01
1.04552999e-01 6.26200974e-01 -8.64911079e-01 -6.26777470e-01
1.59422219e-01 4.41257715e-01 -4.47093040e-01 9.13017914e-02
-1.72558337e-01 8.13083887e-01 -6.90188229e-01 3.53570133e-01
7.61287272e-01 -5.16826034e-01 3.50745916e-01 -5.21499872e-01
-1.80314913e-01 6.25083968e-02 -1.44706023e+00 1.82518458e+00
-1.97300956e-01 3.20912719e-01 1.78498536e-01 -1.32031870e+00
1.08286691e+00 -1.40592247e-01 8.05179775e-01 -3.34819108e-01
1.49346203e-01 -1.08180664e-01 -1.93126172e-01 -3.16830337e-01
4.60709147e-02 1.67139754e-01 -4.81977165e-02 2.70888001e-01
-2.86759436e-01 1.12687625e-01 1.92460164e-01 3.64641339e-01
1.04069793e+00 -1.54568523e-01 3.23199749e-01 -6.28019094e-01
6.33889019e-01 -1.16648108e-01 6.74063683e-01 5.90308189e-01
1.34418592e-01 6.93450034e-01 6.81538939e-01 -2.01845869e-01
-6.44918084e-01 -8.24015260e-01 -2.13624999e-01 8.07841957e-01
5.07470250e-01 -5.36758065e-01 -7.95314908e-01 -9.04336572e-01
-2.06621915e-01 3.56143206e-01 -7.87864268e-01 -1.38075963e-01
-4.65497911e-01 -7.14432001e-01 -1.22755870e-01 2.56957650e-01
3.90332073e-01 -6.68466806e-01 -2.46798545e-01 -5.49660660e-02
-3.74815762e-01 -8.54699194e-01 -7.28298366e-01 2.54401445e-01
-5.86960614e-01 -1.10810530e+00 -4.58603948e-01 -8.27535868e-01
1.18596935e+00 3.89412224e-01 7.95455992e-01 9.71706584e-02
-2.43162751e-01 8.33744183e-02 -3.66429001e-01 2.59620249e-01
1.51018128e-01 -3.83103313e-03 -8.85997340e-02 7.08506525e-01
2.54005492e-02 -4.35835660e-01 -4.32413787e-01 5.51701784e-01
-6.03055894e-01 -3.87094878e-02 4.46485102e-01 7.47711837e-01
1.11953866e+00 2.55627722e-01 1.86124742e-01 -1.16028273e+00
1.33268371e-01 -6.04121327e-01 -6.55949831e-01 3.66100430e-01
-1.83943197e-01 1.08694255e-01 3.00055444e-01 -3.03184986e-01
-8.45892668e-01 6.56638741e-01 2.88427651e-01 -2.60407776e-01
2.31807749e-03 7.29442418e-01 -3.22001934e-01 -2.09861755e-01
3.82910371e-01 -5.64187728e-02 -3.79193723e-01 -4.72341806e-01
5.51606655e-01 4.67788666e-01 1.81190684e-01 -4.23806965e-01
5.50319374e-01 6.81012392e-01 4.12789166e-01 -9.18153822e-01
-1.24737275e+00 -8.15520883e-01 -8.47033739e-01 -2.24855110e-01
1.06654119e+00 -7.76977897e-01 -5.59141099e-01 -8.82332623e-02
-8.75523746e-01 -2.18863308e-01 -3.84527147e-01 6.43253863e-01
-3.38574916e-01 4.24778521e-01 -4.08370495e-01 -7.58239567e-01
4.80632693e-01 -9.91905153e-01 1.00460446e+00 1.22191615e-01
-2.27138758e-01 -1.05910242e+00 1.43017769e-01 2.51099169e-01
-7.50470608e-02 3.90839666e-01 9.02838171e-01 -2.96703607e-01
-5.05277872e-01 -1.18227571e-01 -4.86625761e-01 1.78139403e-01
2.36728653e-01 -1.35159954e-01 -8.52939606e-01 -2.27869377e-01
-3.01132817e-02 -1.68027077e-03 1.05927324e+00 6.03495121e-01
1.26568246e+00 -2.61062026e-01 -6.09099865e-01 6.02932096e-01
1.39638543e+00 4.05609980e-02 2.57987887e-01 -1.43845156e-01
1.20924830e+00 1.07860911e+00 5.99244833e-01 3.83087784e-01
2.90719986e-01 8.53598654e-01 3.35388780e-01 -2.07276016e-01
-1.36818081e-01 -2.69497097e-01 1.79989442e-01 8.44628394e-01
1.61207378e-01 -2.80488908e-01 -9.31878388e-01 4.09101129e-01
-2.03934193e+00 -5.26360452e-01 -5.40892541e-01 2.22284770e+00
4.22312886e-01 -1.13576427e-01 -2.93256454e-02 -1.12365842e-01
9.69378531e-01 2.48244926e-01 -3.93308938e-01 3.63263488e-02
-2.63831317e-01 -2.44753987e-01 4.96838510e-01 7.04832435e-01
-1.21125817e+00 8.41068566e-01 6.06551981e+00 8.19814146e-01
-7.96417415e-01 -2.46326178e-02 7.15594113e-01 2.75636375e-01
-3.18498015e-01 2.94611573e-01 -6.51030719e-01 3.54026020e-01
4.41374004e-01 3.12609911e-01 2.93316662e-01 5.13132811e-01
1.74552426e-01 -3.84543508e-01 -1.00125563e+00 8.13289940e-01
8.78003314e-02 -1.10733962e+00 -1.03955254e-01 2.65577674e-01
9.78194535e-01 -1.22618131e-01 -1.71034753e-01 -2.26506874e-01
3.29100549e-01 -9.75491524e-01 6.34706914e-01 7.66612411e-01
5.28291643e-01 -6.21326983e-01 5.08608639e-01 3.83785754e-01
-1.46825445e+00 -1.15711866e-02 -4.96642441e-01 1.00067280e-01
1.09527618e-01 1.10011148e+00 -3.44943225e-01 5.33752978e-01
5.61210513e-01 1.17242706e+00 -5.97948492e-01 9.25053179e-01
-1.38043717e-01 4.87762064e-01 -4.32648271e-01 2.76906073e-01
3.29033226e-01 -9.12668705e-01 4.01873052e-01 1.08346748e+00
1.80145383e-01 1.11760147e-01 7.80133426e-01 8.30911875e-01
-1.00075558e-01 4.64487433e-01 -6.19912982e-01 1.61533669e-01
2.35654220e-01 1.42695796e+00 -1.20776153e+00 -2.15708315e-01
-5.03763497e-01 9.05153871e-01 6.46011829e-01 4.71216887e-01
-6.60381138e-01 -2.45356262e-02 3.95372659e-01 1.90009326e-01
1.22593470e-01 -3.05343300e-01 -3.68779600e-01 -1.15704942e+00
-1.35509148e-02 -5.13119578e-01 4.44077522e-01 -5.32919288e-01
-1.17672920e+00 3.23892593e-01 -8.76523107e-02 -1.14903641e+00
3.34204018e-01 -1.06523335e-01 -3.91721368e-01 6.84457123e-01
-1.17093956e+00 -1.10871494e+00 -3.61261308e-01 6.23403370e-01
2.14643598e-01 2.99572468e-01 4.66968268e-01 3.40974003e-01
-9.03658688e-01 2.72478610e-01 2.03906015e-01 8.63383785e-02
4.85688210e-01 -1.02004564e+00 -3.44794273e-01 6.94607973e-01
5.04101098e-01 5.89444518e-01 4.88369763e-01 -7.97200382e-01
-9.96305466e-01 -1.28322446e+00 9.01417077e-01 -2.14646444e-01
5.92039168e-01 -5.66729903e-01 -9.53433812e-01 7.17764258e-01
-2.02294528e-01 2.83491582e-01 5.58805466e-01 1.91644043e-01
-4.55120325e-01 -2.26109009e-02 -9.07085538e-01 3.22436392e-01
1.18266189e+00 -5.30532420e-01 -5.91305085e-03 5.27768075e-01
4.41232085e-01 8.89500305e-02 -7.98583448e-01 3.23503643e-01
1.35780886e-01 -7.89030313e-01 7.96366334e-01 -2.08804652e-01
1.21540464e-01 -7.15244174e-01 -3.07708532e-01 -1.28273082e+00
-6.67267680e-01 -2.09502816e-01 2.29782298e-01 1.45628798e+00
4.25603569e-01 -4.67716694e-01 8.12321305e-01 3.50350589e-01
3.64117846e-02 -6.09682679e-01 -6.77417696e-01 -5.98670006e-01
-3.51621717e-01 -1.09927371e-01 2.85229295e-01 1.27335632e+00
1.40261343e-02 5.85995257e-01 -3.58969480e-01 3.33341062e-01
8.01494956e-01 3.46548676e-01 4.69547659e-01 -1.30603123e+00
-1.02115013e-01 -2.81480938e-01 -5.32195747e-01 -1.09655380e+00
5.10987163e-01 -1.14677644e+00 2.16582909e-01 -1.43787134e+00
5.59625804e-01 -8.49790752e-01 -1.65308014e-01 5.27592838e-01
-6.75591221e-03 5.22187710e-01 -4.29305732e-02 4.18396741e-01
-8.12216222e-01 5.51217139e-01 1.16583931e+00 -2.77212918e-01
-2.73683459e-01 -2.20951349e-01 -5.83963871e-01 9.11014676e-01
6.57044232e-01 -6.17025495e-01 -4.19919461e-01 -2.93536246e-01
2.79951096e-01 -9.90489498e-02 2.25738689e-01 -9.22187150e-01
3.18811059e-01 -2.97354192e-01 2.45686233e-01 -5.07669330e-01
2.69985616e-01 -9.26753402e-01 5.47961175e-01 1.13595374e-01
-5.54883301e-01 -4.16087031e-01 -3.32557261e-01 6.70155287e-01
-4.01698887e-01 -3.12101454e-01 9.22011197e-01 4.20906283e-02
-5.81598103e-01 2.80315280e-01 -1.33541852e-01 -1.93929136e-01
1.13419259e+00 2.39759088e-02 4.90059890e-02 -3.85961980e-01
-9.66511607e-01 2.99690545e-01 5.89401245e-01 1.54087692e-03
4.62843657e-01 -1.32825363e+00 -6.02880180e-01 2.15641946e-01
3.12287688e-01 8.84467065e-02 3.48743081e-01 1.02552199e+00
-2.42620990e-01 1.13634065e-01 1.21420912e-01 -8.55720282e-01
-1.31913781e+00 6.99739516e-01 2.18935430e-01 -2.54593074e-01
-7.18909740e-01 8.83524477e-01 7.50125885e-01 -3.60390097e-01
2.02025920e-01 -1.14371426e-01 -6.54997826e-01 3.94578010e-01
2.37390280e-01 2.39981860e-01 -1.51014209e-01 -1.19536591e+00
-5.84693193e-01 1.24719822e+00 1.71322107e-01 1.14159249e-01
1.07404304e+00 -5.59798539e-01 -5.59153855e-01 5.76818228e-01
1.61997330e+00 2.07636341e-01 -1.29124069e+00 -3.88834447e-01
1.73246577e-01 -5.47878921e-01 2.16938451e-01 -2.85281599e-01
-1.37635875e+00 6.80600822e-01 3.73509437e-01 2.33558536e-01
1.08538401e+00 4.21055287e-01 3.07115555e-01 6.00634031e-02
2.72127211e-01 -7.73524165e-01 -3.64801218e-03 4.28665012e-01
7.78089046e-01 -1.18001926e+00 2.18000442e-01 -1.07320845e+00
-5.72462201e-01 6.74735069e-01 2.66478091e-01 -3.46760631e-01
9.27480340e-01 -1.02711409e-01 -8.77596065e-02 -4.98242259e-01
-1.77102774e-01 -3.69310439e-01 5.83843291e-01 3.10291886e-01
3.41493338e-01 9.76072326e-02 -3.74658138e-01 2.03703240e-01
9.09160264e-03 -5.62143564e-01 6.30977526e-02 5.16061366e-01
-3.59136641e-01 -9.70853746e-01 -3.56144875e-01 5.18191695e-01
-2.69736141e-01 1.18575163e-01 -4.78680998e-01 3.09976637e-01
3.43538284e-01 1.12055290e+00 2.37751886e-01 -3.82155269e-01
1.88674107e-01 -3.46717864e-01 2.72180021e-01 -7.42439449e-01
-3.32827926e-01 3.11743081e-01 1.08377216e-02 -7.22854257e-01
-6.83826387e-01 -7.23886430e-01 -1.26993895e+00 1.66926786e-01
-5.92289388e-01 3.12908441e-01 5.96534669e-01 8.91147017e-01
1.69799507e-01 4.69753951e-01 8.32772374e-01 -7.42532015e-01
9.42829922e-02 -5.99319518e-01 -9.80666816e-01 6.70607448e-01
1.77111506e-01 -6.69728637e-01 -3.94946724e-01 2.52177149e-01] | [7.7956366539001465, 4.53635311126709] |
990576c7-8e95-4c40-90d6-41e6c86f04ff | tree-constrained-graph-neural-networks-for | 2110.00124 | null | https://arxiv.org/abs/2110.00124v1 | https://arxiv.org/pdf/2110.00124v1.pdf | Tree-Constrained Graph Neural Networks For Argument Mining | We propose a novel architecture for Graph Neural Networks that is inspired by the idea behind Tree Kernels of measuring similarity between trees by taking into account their common substructures, named fragments. By imposing a series of regularization constraints to the learning problem, we exploit a pooling mechanism that incorporates such notion of fragments within the node soft assignment function that produces the embeddings. We present an extensive experimental evaluation on a collection of sentence classification tasks conducted on several argument mining corpora, showing that the proposed approach performs well with respect to state-of-the-art techniques. | ['Paolo Torroni', 'Marco Lippi', 'Federico Ruggeri'] | 2021-09-02 | null | null | null | null | ['sentence-classification'] | ['natural-language-processing'] | [ 4.67718452e-01 5.84959567e-01 -3.71346414e-01 -5.14008760e-01
-2.04379350e-01 -2.91342437e-01 7.10292518e-01 9.88442361e-01
-7.02177286e-01 3.61128688e-01 2.95998961e-01 -7.12187767e-01
-3.37174088e-01 -1.05797064e+00 -7.71566570e-01 -5.03678381e-01
-4.61576998e-01 2.03246608e-01 3.63710821e-01 -1.77107483e-01
2.18724802e-01 3.58032078e-01 -1.15526605e+00 3.76244187e-01
7.79905856e-01 1.04843748e+00 -8.80322307e-02 6.23694479e-01
-3.73669654e-01 1.12692356e+00 -4.94214982e-01 -9.90969002e-01
-8.06296617e-03 -6.06973059e-02 -1.17501462e+00 -1.65888250e-01
5.47814846e-01 -3.37963328e-02 -4.24529880e-01 1.14343762e+00
7.93710724e-02 3.25051039e-01 8.02602828e-01 -7.89478719e-01
-1.31309521e+00 1.02308047e+00 -3.78042132e-01 5.43853164e-01
1.98251992e-01 -4.10855263e-01 1.72668493e+00 -7.49481320e-01
6.54670000e-01 1.18345737e+00 8.73123229e-01 1.79365382e-01
-1.43461514e+00 1.44965142e-01 2.93972373e-01 3.86376590e-01
-1.00919759e+00 -3.35586071e-02 1.08010828e+00 -1.21223971e-01
1.39200604e+00 1.69178918e-01 3.47133100e-01 1.00226521e+00
4.40606296e-01 8.49717557e-01 5.59443176e-01 -7.47219026e-01
3.18500549e-01 7.28270933e-02 8.41656685e-01 1.00354433e+00
2.59507596e-01 -3.99411798e-01 -2.83306718e-01 -5.02816975e-01
3.26573312e-01 -8.14156905e-02 -2.17646852e-01 -7.21483111e-01
-5.69571674e-01 1.46941590e+00 8.44784021e-01 7.11901128e-01
-3.48294169e-01 4.38478924e-02 7.51522243e-01 2.77969658e-01
7.65189648e-01 2.28683367e-01 -4.41075176e-01 4.24801320e-01
-5.78247488e-01 1.61590353e-02 1.10349834e+00 5.14287233e-01
5.57965338e-01 -2.58110344e-01 -2.87893891e-01 9.02092457e-01
1.83557838e-01 -4.05120492e-01 5.49327493e-01 -4.85901862e-01
6.77898765e-01 9.88055944e-01 -6.10660851e-01 -1.08927929e+00
-3.98569047e-01 -5.86010218e-01 -9.35672522e-01 4.82045375e-02
3.11405480e-01 1.23129942e-01 -7.95610309e-01 1.71389258e+00
3.97906512e-01 1.72713861e-01 1.09459542e-01 5.29388845e-01
1.02765596e+00 3.96245152e-01 2.46852800e-01 -6.08377717e-02
1.33441043e+00 -9.26130474e-01 -5.71615696e-01 -6.30427897e-02
9.09733772e-01 -2.08929330e-01 9.80385840e-01 -1.09372530e-02
-1.09256792e+00 -5.41192591e-01 -1.20307362e+00 -3.01449060e-01
-7.12222517e-01 -1.06365733e-01 9.46849227e-01 6.01813376e-01
-1.06793582e+00 1.18543303e+00 -6.50808454e-01 -6.41418159e-01
5.42991400e-01 2.98272103e-01 -4.66352373e-01 2.36761287e-01
-1.19939542e+00 9.88772690e-01 7.39702404e-01 1.78242043e-01
-3.78399760e-01 -4.29554373e-01 -1.17132759e+00 4.18777049e-01
2.32960567e-01 -8.28191996e-01 1.00156975e+00 -7.12162316e-01
-1.36746359e+00 1.05687201e+00 6.84800372e-02 -1.04395878e+00
1.26319408e-01 -2.11007193e-01 -2.14234844e-01 2.77126789e-01
-9.15036723e-02 1.91401988e-01 7.70478666e-01 -7.74879098e-01
-2.93860525e-01 -3.77762794e-01 3.46748412e-01 8.77944306e-02
-8.33294570e-01 1.02675222e-01 -4.32616509e-02 -5.40879071e-01
-5.92663363e-02 -4.22423631e-01 -4.14267898e-01 -4.11158055e-02
-6.15296721e-01 -7.93791473e-01 7.85372257e-01 -4.73020136e-01
1.37492085e+00 -1.93307996e+00 3.20867121e-01 1.44578338e-01
5.65109789e-01 4.03569192e-01 -2.61372298e-01 7.26089060e-01
-2.91016251e-01 2.12894708e-01 -6.53520882e-01 -3.37375373e-01
6.75131828e-02 3.26199293e-01 -1.83684170e-01 3.81429583e-01
3.50445151e-01 8.95398796e-01 -8.05414677e-01 -4.15537149e-01
3.30356620e-02 4.33444589e-01 -4.08872932e-01 2.32174098e-01
-3.13688338e-01 -4.62185591e-01 -6.29234374e-01 2.60806084e-01
7.21373200e-01 -3.25677693e-01 4.78611976e-01 3.25160362e-02
3.34231138e-01 7.60779560e-01 -8.53558242e-01 1.75173652e+00
-1.45592734e-01 3.57766330e-01 -9.55638364e-02 -1.57223153e+00
8.83337080e-01 1.39826670e-01 7.16714785e-02 -2.08749026e-02
2.95402050e-01 -5.60865924e-02 2.09022447e-01 -5.15570402e-01
4.10713911e-01 -5.79267181e-02 -1.19217280e-02 3.43140602e-01
4.30465072e-01 -2.50165612e-02 4.34021533e-01 4.43072408e-01
1.57869017e+00 -7.75196329e-02 5.75797975e-01 -4.02530700e-01
9.11197722e-01 -4.68179435e-01 1.57139540e-01 7.39379168e-01
-2.73783773e-01 2.63494670e-01 9.78839934e-01 -8.28516364e-01
-7.73288965e-01 -1.18242800e+00 -1.22186594e-01 1.24666584e+00
-4.60022390e-01 -5.89405775e-01 -9.43445385e-01 -1.18163431e+00
2.83579171e-01 7.25594342e-01 -1.18942511e+00 -2.31366962e-01
-6.80118382e-01 -7.37513900e-01 6.47863865e-01 8.31175685e-01
3.64408135e-01 -1.32297003e+00 -4.56569016e-01 3.18787575e-01
4.40375596e-01 -1.20019639e+00 -1.98723376e-01 8.13207388e-01
-1.04589415e+00 -1.11717463e+00 -3.51567864e-01 -1.24536312e+00
2.41392329e-01 -1.00307241e-01 1.34275663e+00 3.55607837e-01
-2.40680814e-01 -2.73660794e-02 -3.67623627e-01 -9.21909586e-02
-3.89702678e-01 3.99308950e-01 -2.62567729e-01 -1.25110090e-01
5.55239022e-01 -8.76158774e-01 -4.87601012e-02 -5.33419490e-01
-9.56591368e-01 -4.85465854e-01 4.58475143e-01 8.69879663e-01
1.55640736e-01 3.32554169e-02 4.50397015e-01 -1.22845292e+00
1.30952525e+00 -5.09512842e-01 -3.80364358e-01 4.46783930e-01
-5.51519871e-01 4.03447598e-01 9.03826058e-01 -2.94949859e-01
-8.72380912e-01 -2.26974055e-01 7.16584316e-03 -1.63382426e-01
-1.01181872e-01 6.83662295e-01 -5.61449490e-02 2.83056982e-02
6.25194132e-01 8.94917175e-02 -1.51456878e-01 -5.85689664e-01
8.61053467e-01 5.42278647e-01 4.40534860e-01 -3.93215001e-01
7.11166680e-01 3.59186381e-01 1.44685611e-01 -8.52357447e-01
-9.64973807e-01 -2.69891590e-01 -9.61751580e-01 4.06176925e-01
1.10818017e+00 -2.78236926e-01 -6.24035001e-01 2.06588820e-01
-1.44183969e+00 1.63192749e-01 -3.39503437e-01 3.05222452e-01
-3.23201180e-01 7.65595794e-01 -1.08317959e+00 -6.77209437e-01
-6.04592562e-01 -5.73930681e-01 6.09533727e-01 1.48707926e-01
-9.51993242e-02 -1.43890393e+00 3.96060973e-01 1.60815284e-01
2.47290403e-01 7.23467097e-02 1.63047779e+00 -1.31171227e+00
-1.91055596e-01 -2.86004871e-01 -3.09234470e-01 6.72246158e-01
-4.33733538e-02 -5.64181209e-02 -8.85580719e-01 -1.01484790e-01
1.04839221e-01 -3.63533646e-01 1.44299889e+00 3.39001775e-01
1.19398355e+00 -1.41323239e-01 -3.92980635e-01 5.18221557e-01
1.38109994e+00 -2.93479621e-01 3.74435693e-01 3.38851392e-01
7.28231192e-01 6.10188246e-01 -8.02552328e-02 2.08225429e-01
3.42047393e-01 2.22051769e-01 5.51012754e-01 -6.43218905e-02
2.77367592e-01 -2.64031380e-01 1.04362383e-01 8.02087963e-01
-2.04543006e-02 -3.71631175e-01 -5.29522836e-01 5.53531110e-01
-1.97936797e+00 -9.22050416e-01 -1.82207882e-01 1.83150148e+00
6.27019525e-01 5.89516580e-01 2.23090611e-02 3.19425762e-01
8.50004435e-01 7.74839520e-01 -2.46252939e-01 -1.33081937e+00
-5.32351620e-02 8.80418658e-01 3.95764589e-01 3.54793996e-01
-1.47350001e+00 1.02628469e+00 6.87834978e+00 7.39635408e-01
-6.29632473e-01 3.72071043e-02 3.05834800e-01 3.88699442e-01
-2.26154745e-01 -5.34714013e-02 -4.60194826e-01 -1.25828117e-01
1.04757130e+00 -7.20536262e-02 1.10879995e-01 9.25119877e-01
-2.01419473e-01 2.40223855e-01 -1.22703397e+00 2.49086812e-01
2.47064173e-01 -1.43565536e+00 5.73188029e-02 -2.18380511e-01
3.36227775e-01 1.14121430e-01 -1.11022778e-01 3.00167501e-01
5.18774867e-01 -1.13772571e+00 3.14861894e-01 9.43012685e-02
2.81787924e-02 -6.72137022e-01 7.54077375e-01 2.77272016e-01
-1.35101414e+00 -9.00590643e-02 -7.57413864e-01 -5.12116373e-01
-8.79288092e-02 8.11922371e-01 -9.28204894e-01 7.66896605e-01
6.03716850e-01 7.58675933e-01 -6.73741877e-01 6.61490679e-01
-7.93464661e-01 6.76842213e-01 -1.89370781e-01 -3.84947687e-01
4.94758576e-01 -2.76409328e-01 2.94129848e-01 1.40161157e+00
-2.99921393e-01 -3.36975157e-01 9.89167169e-02 1.07598531e+00
-5.05351543e-01 3.30629885e-01 -1.00012493e+00 -1.15881011e-01
2.83511460e-01 1.54249477e+00 -7.01213181e-01 -3.74141306e-01
-6.00917757e-01 9.67609286e-01 1.29112208e+00 9.65569913e-02
-6.95409954e-01 -6.93806410e-01 3.48431230e-01 -1.95195153e-01
7.74330080e-01 -6.66632652e-02 -2.32256189e-01 -9.27631557e-01
3.28968227e-01 -4.07734573e-01 7.91481793e-01 -3.53370458e-01
-1.72422040e+00 8.25676382e-01 -9.00233015e-02 -6.10597551e-01
-2.25787848e-01 -9.20030057e-01 -1.10892749e+00 8.77010465e-01
-1.54527617e+00 -1.28580916e+00 2.88488060e-01 3.87741834e-01
2.48493433e-01 -2.68315971e-02 1.15037453e+00 -1.23624161e-01
-5.63044667e-01 5.91512501e-01 -5.49291745e-02 3.18996400e-01
9.12626833e-02 -1.39833319e+00 8.81052434e-01 7.34937966e-01
6.60363257e-01 7.82680690e-01 4.02603179e-01 -3.48321378e-01
-9.83605444e-01 -9.06715453e-01 1.39343536e+00 -2.33453408e-01
1.13151968e+00 -5.89338005e-01 -1.39974737e+00 8.17118347e-01
7.03893721e-01 2.55575985e-01 7.37406135e-01 5.64552844e-01
-7.49040067e-01 1.75726190e-01 -1.08159757e+00 2.76010334e-01
1.17687953e+00 -6.91763103e-01 -1.24013710e+00 4.18580532e-01
8.31843913e-01 9.41819474e-02 -7.87453175e-01 3.41203302e-01
2.07647577e-01 -1.00084651e+00 8.78955066e-01 -1.18091214e+00
6.07159615e-01 1.60197556e-01 -1.32995844e-01 -1.30271566e+00
-6.71315253e-01 -4.57988143e-01 -3.72861564e-01 1.14100981e+00
5.83462119e-01 -6.68991506e-01 1.04299104e+00 1.59634173e-01
-9.58405435e-02 -1.14999402e+00 -1.09438252e+00 -8.42205703e-01
4.27666575e-01 -2.18940318e-01 2.74517298e-01 9.51787472e-01
4.23967898e-01 7.27674127e-01 5.58725297e-02 -6.14698194e-02
5.52452862e-01 2.35380810e-02 2.16474667e-01 -1.43929029e+00
-4.59670126e-01 -4.23428953e-01 -6.74029529e-01 -7.02016175e-01
8.49062145e-01 -1.44525969e+00 -3.92780334e-01 -1.66386116e+00
2.30082020e-01 1.53908685e-01 -7.07197249e-01 3.59800816e-01
-3.64172131e-01 -7.71501362e-02 1.08060941e-01 -2.19859108e-01
-4.85305935e-01 6.24688566e-01 8.27501059e-01 -2.51242667e-01
-8.30004923e-03 -8.96261483e-02 -7.46655822e-01 9.94127512e-01
7.38016725e-01 -5.82573712e-01 -3.07767779e-01 -5.74368715e-01
-1.18339449e-01 -3.70503783e-01 2.59838045e-01 -8.90700459e-01
1.60473287e-01 3.09025735e-01 1.18659183e-01 -5.35621643e-01
1.93512186e-01 -5.55427670e-01 -5.58103144e-01 5.82171321e-01
-7.04490185e-01 1.98500037e-01 -1.83367468e-02 6.77913904e-01
-1.79285794e-01 -5.95845520e-01 5.78897178e-01 -2.68895328e-02
-4.35931563e-01 4.43160795e-02 -2.36339018e-01 2.11338446e-01
7.67657936e-01 -6.55736476e-02 -2.49315113e-01 1.29188877e-02
-6.33246779e-01 -5.79895154e-02 5.75476885e-02 4.06064600e-01
6.93864703e-01 -1.15193892e+00 -6.85047090e-01 1.86004087e-01
1.18450716e-01 -3.99078429e-01 -3.63986105e-01 4.82120603e-01
-2.88239777e-01 3.89821708e-01 9.31343213e-02 -3.11698675e-01
-1.31656790e+00 8.25927019e-01 1.77295998e-01 -8.53434503e-01
-8.02243769e-01 1.20255864e+00 -7.01928064e-02 -6.40453279e-01
3.32224727e-01 -7.64960706e-01 -4.74971026e-01 2.35988926e-02
1.21896148e-01 4.11536843e-02 2.64347613e-01 -3.74336839e-01
-6.22183859e-01 4.38132077e-01 -2.44882986e-01 3.12508315e-01
1.55363405e+00 4.04474854e-01 -2.85151720e-01 3.51399869e-01
1.43938684e+00 -1.67223409e-01 -6.61361158e-01 -4.34502512e-01
5.35234928e-01 -2.25191228e-02 -6.42942488e-02 -4.67246801e-01
-8.56376767e-01 9.23949182e-01 2.50973165e-01 6.44700050e-01
7.23068297e-01 1.39159024e-01 7.78459728e-01 7.82233298e-01
-4.56488170e-02 -1.06305313e+00 -1.96360439e-01 7.93226242e-01
5.92035353e-01 -9.54516590e-01 6.56159669e-02 -6.36222064e-01
-2.69251615e-01 1.24027586e+00 1.65062577e-01 -6.78079963e-01
7.89724290e-01 1.61446244e-01 -1.07140489e-01 -3.03581506e-01
-8.64470243e-01 -2.46372774e-01 2.78469682e-01 6.85018241e-01
7.74732351e-01 8.90022591e-02 -8.31249356e-01 5.92472613e-01
5.96218072e-02 -1.57269582e-01 2.98608601e-01 1.03257740e+00
-6.22343063e-01 -1.34709680e+00 1.40070006e-01 5.19028068e-01
-6.31608725e-01 -4.73560512e-01 -6.91893160e-01 8.39642823e-01
-2.60708667e-02 8.65676045e-01 5.61939925e-03 -3.54931086e-01
4.43893880e-01 4.30000097e-01 5.24645925e-01 -7.51498401e-01
-1.06302488e+00 -4.52402502e-01 5.27310431e-01 -3.30290496e-01
-3.33737731e-01 -3.53719503e-01 -1.31600177e+00 -1.09898388e-01
-4.93286133e-01 2.97540009e-01 4.37377244e-01 9.15555000e-01
1.90444976e-01 6.79187238e-01 5.19650817e-01 -4.88790125e-01
-1.01596224e+00 -1.28671694e+00 -8.88572752e-01 7.61608481e-01
2.92166583e-02 -5.31095803e-01 -4.98378038e-01 -2.16538444e-01] | [10.205313682556152, 9.101496696472168] |
0f8992d3-5ae9-4d26-a1f7-949f65fd1ad0 | deff-gan-diverse-attribute-transfer-for-few | 2302.14533 | null | https://arxiv.org/abs/2302.14533v1 | https://arxiv.org/pdf/2302.14533v1.pdf | DEff-GAN: Diverse Attribute Transfer for Few-Shot Image Synthesis | Requirements of large amounts of data is a difficulty in training many GANs. Data efficient GANs involve fitting a generators continuous target distribution with a limited discrete set of data samples, which is a difficult task. Single image methods have focused on modeling the internal distribution of a single image and generating its samples. While single image methods can synthesize image samples with diversity, they do not model multiple images or capture the inherent relationship possible between two images. Given only a handful of images, we are interested in generating samples and exploiting the commonalities in the input images. In this work, we extend the single-image GAN method to model multiple images for sample synthesis. We modify the discriminator with an auxiliary classifier branch, which helps to generate a wide variety of samples and to classify the input labels. Our Data-Efficient GAN (DEff-GAN) generates excellent results when similarities and correspondences can be drawn between the input images or classes. | ['G. Sivakumar', 'Rajiv Kumar'] | 2023-02-28 | null | null | null | null | ['single-class-few-shot-image-synthesis', 'multi-class-one-shot-image-synthesis'] | ['computer-vision', 'computer-vision'] | [ 6.53167605e-01 1.16439655e-01 -4.03878301e-01 -4.64460611e-01
-8.42505574e-01 -6.64018333e-01 8.36759508e-01 -5.18022954e-01
4.94450442e-02 8.99999440e-01 -1.47465408e-01 2.39215732e-01
3.18417579e-01 -1.03283834e+00 -6.90851092e-01 -8.54298234e-01
7.36286819e-01 1.05239570e+00 -1.22507714e-01 1.88216269e-01
-5.97187653e-02 4.52472121e-01 -1.71671712e+00 3.89971137e-01
7.87878156e-01 1.00807643e+00 5.21403611e-01 8.11790049e-01
-3.89580667e-01 5.84807634e-01 -1.07297730e+00 -3.13881308e-01
4.06374186e-01 -1.30831599e+00 -4.82585937e-01 5.07307470e-01
5.82215250e-01 -2.96877652e-01 1.86616912e-01 9.49019551e-01
3.62091213e-01 -1.89261168e-01 1.08500171e+00 -1.66038644e+00
-7.39669621e-01 2.89638102e-01 -5.14847279e-01 -4.84585136e-01
1.38294622e-01 2.15476200e-01 7.27763712e-01 -3.94527465e-01
6.26760662e-01 1.08903623e+00 3.20758671e-01 1.20763767e+00
-1.45536029e+00 -4.63228196e-01 -2.38497630e-01 -2.50522196e-01
-1.01039624e+00 -3.28410894e-01 9.89895284e-01 -4.36384112e-01
2.59354383e-01 4.84452754e-01 9.70440149e-01 1.24960923e+00
-1.98536992e-01 9.17555273e-01 1.38031936e+00 -6.77692831e-01
2.82536238e-01 4.35122460e-01 -3.53175461e-01 3.92020285e-01
-3.79484557e-02 -2.03274675e-02 -3.21394116e-01 -1.15844216e-02
1.05391419e+00 2.73947567e-01 -1.78077459e-01 -2.19279349e-01
-1.03650582e+00 1.04580927e+00 3.39544594e-01 1.76346764e-01
-4.06917423e-01 2.80975491e-01 -2.73942295e-02 3.82854134e-01
2.51165032e-01 5.39240003e-01 -1.29307762e-01 -8.35386217e-02
-1.10953653e+00 2.60742217e-01 5.88256776e-01 1.27712536e+00
1.21531820e+00 3.01588148e-01 -2.37859219e-01 9.06968296e-01
-5.28316610e-02 7.08514571e-01 6.18426442e-01 -9.32626367e-01
1.85476184e-01 5.18521428e-01 -1.57744929e-01 -5.62627733e-01
3.25783581e-01 -3.22506160e-01 -1.06751847e+00 5.48102736e-01
5.17757893e-01 -2.82245446e-02 -1.30745339e+00 1.83943117e+00
2.43094519e-01 -2.49880493e-01 5.28977066e-02 4.36083853e-01
5.40474117e-01 8.13109696e-01 -2.91373253e-01 -1.15864873e-01
9.84615922e-01 -1.15749013e+00 -5.99898875e-01 -3.67690474e-01
2.35490054e-01 -7.15965986e-01 1.40093577e+00 4.25909966e-01
-1.33980072e+00 -8.87616754e-01 -8.79639804e-01 -8.56796652e-02
-3.78343999e-01 3.23854864e-01 5.11223197e-01 8.30922067e-01
-9.99557197e-01 3.54143262e-01 -4.87253845e-01 -1.14759738e-02
8.42470884e-01 4.11013186e-01 -2.58468270e-01 -3.61445069e-01
-5.34787118e-01 4.67897058e-01 3.16767603e-01 -3.56010348e-01
-1.18828166e+00 -6.78435683e-01 -7.16745257e-01 -1.04622558e-01
-8.54367837e-02 -9.46166337e-01 1.03825891e+00 -1.66697752e+00
-1.62177157e+00 8.64073098e-01 -1.38122708e-01 -1.49462879e-01
6.00148857e-01 3.91787261e-01 -1.37511820e-01 -1.02835655e-01
5.51040545e-02 1.29341030e+00 1.29706943e+00 -1.71326077e+00
-6.73422694e-01 -1.33474404e-02 -1.04640454e-01 1.05054289e-01
-1.07540317e-01 -5.17152011e-01 -1.22730657e-01 -7.53849745e-01
-1.89930618e-01 -8.60666394e-01 -7.81831518e-02 -2.19673216e-02
-5.44130862e-01 1.88824698e-01 1.09866953e+00 -2.42650777e-01
5.69472194e-01 -2.18163228e+00 1.61958963e-01 1.15938373e-01
1.23217024e-01 2.31482256e-02 -3.66436481e-01 3.21782470e-01
-6.81071833e-04 2.26102591e-01 -3.91366631e-01 -7.04940796e-01
-1.80454589e-02 6.32331431e-01 -4.56967056e-01 7.59943053e-02
3.79676342e-01 9.52910483e-01 -7.35082448e-01 -4.34890836e-01
3.76910344e-02 3.95821720e-01 -5.25694191e-01 6.45429552e-01
-5.70422709e-01 7.86966264e-01 -3.28325808e-01 5.76569080e-01
6.43381536e-01 -1.67050421e-01 -8.94250274e-02 -6.42363578e-02
5.21993995e-01 -6.65602982e-02 -9.23260152e-01 1.66837633e+00
-5.78518748e-01 5.53783238e-01 -3.03683013e-01 -9.19228077e-01
1.22207057e+00 2.66578794e-01 2.50694066e-01 -6.09768867e-01
-1.18537396e-02 3.02512079e-01 -8.74449615e-04 -6.27776384e-02
2.99034208e-01 -6.20280623e-01 -1.90361328e-02 7.82767832e-01
3.24594200e-01 -7.81759560e-01 2.48846382e-01 -1.46875903e-01
6.73727751e-01 1.35468632e-01 2.99719781e-01 -4.16682437e-02
1.08740576e-01 3.01717035e-02 4.48945224e-01 7.92900980e-01
5.01036942e-01 1.27388453e+00 5.25480568e-01 -4.32561070e-01
-1.44222498e+00 -1.09212899e+00 1.54855177e-01 4.37337011e-01
-1.56142712e-01 -1.57860704e-02 -9.64872539e-01 -9.23863351e-01
-4.00885552e-01 7.63037801e-01 -7.66247690e-01 -3.72870564e-02
-2.85284251e-01 -6.15889728e-01 3.34087849e-01 4.40327734e-01
5.68787456e-01 -1.08706129e+00 -4.93606150e-01 -1.01348691e-01
-6.19775094e-02 -8.50302756e-01 -6.27253652e-01 2.60444969e-01
-7.71108568e-01 -8.28226924e-01 -8.81350398e-01 -9.23802018e-01
1.13500714e+00 -8.05090517e-02 1.37693083e+00 -1.03092499e-01
-2.96379715e-01 2.80870497e-01 -1.93991840e-01 -5.93372285e-01
-9.72869873e-01 2.28854239e-01 -3.79621953e-01 1.56008899e-01
3.88392657e-02 -7.27201879e-01 -3.47771496e-01 2.61266768e-01
-1.18885744e+00 4.29686189e-01 6.62835896e-01 1.25384128e+00
8.80142033e-01 1.43202811e-01 7.58924782e-01 -1.29953146e+00
5.28641820e-01 -4.32201862e-01 -4.64846820e-01 3.74192744e-01
-3.24882984e-01 1.40108377e-01 9.72079575e-01 -7.81069815e-01
-1.03566241e+00 2.70805150e-01 -1.01290785e-01 -5.26028395e-01
-5.74757695e-01 2.47745849e-02 -5.48421741e-01 1.96434349e-01
6.97682023e-01 5.06223619e-01 3.52283776e-01 -2.81034946e-01
5.75287759e-01 6.42972350e-01 4.83438194e-01 -8.24360132e-01
6.57334864e-01 3.40891361e-01 1.18505642e-01 -6.73508167e-01
-6.10541582e-01 4.66909260e-02 -6.79936767e-01 -8.05971175e-02
8.89408112e-01 -7.33116448e-01 2.59059388e-02 5.04759789e-01
-1.05705285e+00 -6.75580084e-01 -1.17038608e+00 1.24368608e-01
-8.62951696e-01 -1.86352342e-01 -2.12329537e-01 -5.69292367e-01
-8.29047933e-02 -1.41571629e+00 1.25098586e+00 2.85647571e-01
-2.04060853e-01 -1.15237284e+00 8.95738006e-02 1.69045940e-01
4.65342164e-01 5.13619065e-01 9.90392089e-01 -3.99704009e-01
-7.50891149e-01 -3.49920928e-01 7.92369768e-02 6.96632087e-01
8.14485848e-01 2.57378537e-02 -1.08657563e+00 -2.48928457e-01
1.73626676e-01 -7.05425501e-01 6.03192389e-01 3.48091900e-01
1.45458174e+00 -4.71871853e-01 -1.37754828e-01 7.14080989e-01
1.44655824e+00 3.91165644e-01 9.85207260e-01 -2.47496948e-01
7.72368908e-01 5.69459319e-01 2.42860571e-01 2.22745627e-01
2.15556696e-02 5.03858864e-01 3.34644854e-01 -4.22162086e-01
-5.07659972e-01 -5.69705665e-01 1.49395600e-01 7.11190104e-01
-6.72241375e-02 -6.60819292e-01 -3.99688363e-01 4.96449113e-01
-1.40807807e+00 -1.07700145e+00 2.14235544e-01 2.06070995e+00
1.04170334e+00 -1.94020391e-01 2.53559202e-01 1.74201503e-01
7.24686742e-01 -6.76104277e-02 -6.90170765e-01 -1.67897746e-01
-2.94441313e-01 4.64542955e-01 1.61581218e-01 3.97814482e-01
-6.18142188e-01 6.29591346e-01 7.02542305e+00 1.32242775e+00
-1.32612979e+00 -4.71161865e-02 1.16349626e+00 -6.78313151e-02
-7.67686903e-01 -2.42882012e-03 -7.85336912e-01 7.24669576e-01
6.09558523e-01 1.23611996e-02 6.17929101e-01 8.59074354e-01
-3.50159466e-01 -1.43335551e-01 -1.36559069e+00 1.21734500e+00
1.93734512e-01 -1.49828935e+00 4.80995983e-01 3.28383297e-01
1.22674847e+00 -5.64453721e-01 3.45852703e-01 -1.05272681e-01
4.84745115e-01 -1.40833914e+00 7.79190063e-01 6.37925267e-01
1.22693479e+00 -6.07242525e-01 4.32175010e-01 4.81860787e-01
-6.87417805e-01 1.94939032e-01 -3.44841659e-01 1.09993897e-01
-1.17661674e-02 6.47024333e-01 -8.44254613e-01 3.89419705e-01
2.67785490e-01 5.76700091e-01 -5.79096675e-01 6.10578477e-01
-2.95083016e-01 4.72814411e-01 -3.92482281e-01 1.22242369e-01
9.09982994e-03 -5.24937749e-01 6.96107820e-02 7.04195738e-01
6.60071433e-01 -4.03815240e-01 5.05810045e-02 1.28279817e+00
-2.56751329e-01 -3.09122175e-01 -8.68394732e-01 -2.66090721e-01
3.87040943e-01 1.26102483e+00 -6.93349957e-01 -5.02373636e-01
-2.28754491e-01 1.19428635e+00 2.46097356e-01 3.04781973e-01
-6.42989635e-01 -4.55810465e-02 3.56758773e-01 2.12354451e-01
1.83302492e-01 1.10424059e-02 -4.47250485e-01 -1.03451240e+00
-2.05782093e-02 -1.19373512e+00 1.90941751e-01 -8.84225249e-01
-1.50819767e+00 7.31934488e-01 -2.52814982e-02 -1.31870663e+00
-7.47075856e-01 -3.14248830e-01 -7.09894538e-01 1.05056393e+00
-1.15929377e+00 -1.66056728e+00 -5.34993589e-01 7.31463015e-01
6.46295965e-01 -4.70541567e-01 1.03304052e+00 1.04547165e-01
-1.45600393e-01 5.98839700e-01 8.60252753e-02 -1.80861671e-02
4.26135540e-01 -1.45016026e+00 2.46619806e-01 5.48743904e-01
3.90205175e-01 3.15687150e-01 5.24121642e-01 -4.68487918e-01
-1.10002601e+00 -1.07121837e+00 5.02243578e-01 -1.84496209e-01
-3.62347849e-02 -5.30679882e-01 -5.62580407e-01 7.47739196e-01
5.18568814e-01 1.43383056e-01 8.34302843e-01 -5.00639081e-01
-1.23749837e-01 -1.97373971e-01 -1.54934692e+00 5.20853639e-01
7.86121607e-01 -3.82365525e-01 -6.65689856e-02 2.29336113e-01
2.93036371e-01 -2.90547192e-01 -6.52148128e-01 1.94353163e-02
3.53348911e-01 -9.48261857e-01 7.30584085e-01 -4.14196938e-01
6.85667753e-01 -3.39810044e-01 -2.54501820e-01 -1.71686792e+00
-7.94488415e-02 -4.47553754e-01 2.26143032e-01 1.61368561e+00
3.43265682e-01 -6.38976216e-01 1.11568451e+00 4.46290761e-01
5.92876747e-02 -5.81802309e-01 -5.21529436e-01 -7.46468067e-01
1.32380217e-01 -6.58714175e-02 1.12607193e+00 7.88085759e-01
-7.02939689e-01 3.29280496e-01 -6.29603148e-01 -2.70366997e-01
7.23032713e-01 3.84388834e-01 1.18458784e+00 -9.93635774e-01
-6.56861842e-01 -4.25376326e-01 -3.14249992e-01 -1.20661533e+00
6.05268031e-02 -8.08166504e-01 -1.09014194e-02 -1.37288654e+00
1.70361802e-01 -9.01620328e-01 4.07114059e-01 4.68837053e-01
7.28870854e-02 5.23846567e-01 7.55824968e-02 2.67504305e-01
2.02859174e-02 7.64769673e-01 1.64162040e+00 -4.16286230e-01
6.10830113e-02 3.63226607e-02 -7.15141714e-01 3.63631427e-01
9.52084005e-01 -5.83141029e-01 -9.67404783e-01 -4.88346785e-01
-3.16263214e-02 -1.79757085e-02 3.25127870e-01 -1.03169847e+00
-1.06244452e-01 -3.79243553e-01 7.13973343e-01 -4.27489489e-01
5.41895866e-01 -8.84458125e-01 8.41509402e-01 2.21027136e-01
-3.97844791e-01 -9.14064795e-02 -2.70875007e-01 3.04172486e-01
-6.00914001e-01 -6.30018055e-01 1.12412608e+00 -6.01360261e-01
-2.36159503e-01 5.53261459e-01 -2.81340852e-02 2.58428335e-01
1.04281807e+00 -4.88862216e-01 -1.83232591e-01 -5.02160609e-01
-5.24434209e-01 -2.77547240e-01 9.07310784e-01 4.91950810e-02
6.56841934e-01 -1.74704254e+00 -5.20864069e-01 7.14821935e-01
-1.00828782e-01 6.03575706e-01 3.58900018e-02 9.07382146e-02
-5.03145039e-01 -1.23096429e-01 -5.84794700e-01 -7.63742983e-01
-1.16633308e+00 4.16368186e-01 3.83587629e-01 -1.49873778e-01
-2.16008976e-01 7.49293566e-01 4.90461469e-01 -4.60704803e-01
-2.14906171e-01 -1.00603305e-01 2.07297474e-01 1.14497580e-01
3.63196522e-01 -3.70301120e-02 -2.55803198e-01 -3.63500625e-01
3.02784711e-01 5.71786940e-01 4.87156771e-02 -1.07446887e-01
1.36634326e+00 1.60376102e-01 -1.09421164e-01 6.11816823e-01
1.27127826e+00 1.99456997e-02 -1.58864450e+00 -1.15405396e-02
-5.54607153e-01 -8.09284210e-01 -3.32390428e-01 -6.26586378e-01
-1.52998185e+00 1.02714598e+00 3.38825732e-01 5.03086209e-01
1.45489228e+00 1.40553564e-01 5.93249321e-01 -1.64277315e-01
3.29984248e-01 -7.48357058e-01 4.97428566e-01 3.19345668e-02
8.78238440e-01 -1.15146494e+00 -1.49484754e-01 -4.06078994e-01
-7.55614161e-01 1.23277545e+00 6.40074134e-01 -1.62645444e-01
3.03914994e-01 4.30629581e-01 1.09404489e-01 2.86504459e-02
-5.75257838e-01 -6.51389584e-02 1.99152172e-01 1.17689526e+00
2.23815918e-01 6.28631338e-02 7.10171834e-02 2.09531322e-01
-4.53390419e-01 -6.56982958e-02 6.23275936e-01 7.39599824e-01
-8.83912519e-02 -1.73209620e+00 -1.86174110e-01 6.39030457e-01
-2.21482173e-01 6.38212860e-02 -3.64190280e-01 7.00247884e-01
3.84508580e-01 5.70735991e-01 3.31086069e-01 -2.66659558e-01
-1.13341495e-01 4.23141532e-02 8.61454248e-01 -7.58026421e-01
-2.88450539e-01 8.64987373e-02 -1.38023645e-01 -1.45305218e-02
-5.71785808e-01 -6.29915297e-01 -7.65435994e-01 -9.11866054e-02
-2.20641568e-01 8.34735632e-02 6.47368789e-01 7.16689110e-01
3.00175250e-01 4.45629448e-01 8.39293301e-01 -8.89833748e-01
-3.16821516e-01 -8.06212068e-01 -8.37857008e-01 6.22631788e-01
3.33590895e-01 -3.47771734e-01 -2.58251280e-01 5.25469303e-01] | [11.598494529724121, -0.332459032535553] |
f99ad71b-ec9a-47f0-ac7d-e233008fe688 | a-generative-model-to-synthesize-eeg-data-for | 2012.00430 | null | https://arxiv.org/abs/2012.00430v1 | https://arxiv.org/pdf/2012.00430v1.pdf | A Generative Model to Synthesize EEG Data for Epileptic Seizure Prediction | Prediction of seizure before they occur is vital for bringing normalcy to the lives of patients. Researchers employed machine learning methods using hand-crafted features for seizure prediction. However, ML methods are too complicated to select the best ML model or best features. Deep Learning methods are beneficial in the sense of automatic feature extraction. One of the roadblocks for accurate seizure prediction is scarcity of epileptic seizure data. This paper addresses this problem by proposing a deep convolutional generative adversarial network to generate synthetic EEG samples. We use two methods to validate synthesized data namely, one-class SVM and a new proposal which we refer to as convolutional epileptic seizure predictor (CESP). Another objective of our study is to evaluate performance of well-known deep learning models (e.g., VGG16, VGG19, ResNet50, and Inceptionv3) by training models on augmented data using transfer learning with average time of 10 min between true prediction and seizure onset. Our results show that CESP model achieves sensitivity of 78.11% and 88.21%, and FPR of 0.27/h and 0.14/h for training on synthesized and testing on real Epilepsyecosystem and CHB-MIT datasets, respectively. Effective results of CESP trained on synthesized data shows that synthetic data acquired the correlation between features and labels very well. We also show that employment of idea of transfer learning and data augmentation in patient-specific manner provides highest accuracy with sensitivity of 90.03% and 0.03 FPR/h which was achieved using Inceptionv3, and that augmenting data with samples generated from DCGAN increased prediction results of our CESP model and Inceptionv3 by 4-5% as compared to state-of-the-art traditional augmentation techniques. Finally, we note that prediction results of CESP achieved by using augmented data are better than chance level for both datasets. | ['Adeel Razi', 'Levin Kuhlmann', "Terence J. O'Brien", 'Junaid Qadir', 'Khansa Rasheed'] | 2020-12-01 | null | null | null | null | ['seizure-prediction'] | ['medical'] | [-4.88007665e-02 2.46615842e-01 3.30814958e-01 -2.55830139e-01
-9.30524468e-01 -3.61567557e-01 5.21888196e-01 -1.75683483e-01
-2.28967398e-01 1.28249574e+00 -1.59518681e-02 -2.49228105e-01
-1.42032743e-01 -7.24575579e-01 -6.40848339e-01 -6.51845634e-01
-5.15957117e-01 1.68975562e-01 -1.05720110e-01 -3.70260149e-01
8.55946839e-02 4.97637987e-01 -1.01738191e+00 3.86323690e-01
7.95736253e-01 9.05838013e-01 -1.01252468e-02 5.94489992e-01
4.75486964e-01 6.00819826e-01 -1.17296910e+00 3.55462953e-02
4.36724454e-01 -5.11617601e-01 -5.20783126e-01 -2.90243715e-01
-3.98120970e-01 -2.18134403e-01 -3.73537451e-01 8.11651230e-01
9.59124625e-01 -5.06016433e-01 7.86144078e-01 -1.70802224e+00
-5.18768728e-01 6.71485305e-01 -1.92389697e-01 3.38841438e-01
2.82263696e-01 3.79199535e-01 1.11661768e-02 -4.85422313e-01
2.58453429e-01 3.64469022e-01 9.48921025e-01 8.88340235e-01
-1.06364775e+00 -1.42796957e+00 -7.41730571e-01 9.43377465e-02
-1.58587956e+00 -1.89528897e-01 6.53288603e-01 -6.65606439e-01
1.18945575e+00 3.50630552e-01 9.04920995e-01 1.39620769e+00
7.29263246e-01 3.28051120e-01 1.71610415e+00 -2.41539001e-01
1.75295964e-01 3.18001032e-01 2.15336829e-02 2.86783278e-01
7.67445937e-02 6.15699351e-01 -4.67218339e-01 -7.25756735e-02
7.65583038e-01 -4.11526896e-02 -5.68274915e-01 4.41422403e-01
-1.02113354e+00 7.79236317e-01 2.49795526e-01 5.79832792e-01
-5.14776945e-01 9.17510167e-02 3.98865253e-01 6.40272558e-01
4.27803367e-01 7.58403540e-01 -8.30026865e-01 -2.59014666e-01
-1.07308376e+00 9.43374634e-02 6.15207076e-01 9.38659132e-01
2.65210211e-01 7.17219710e-01 -2.31313035e-01 5.06356299e-01
-7.65820295e-02 7.07615316e-01 1.19453311e+00 3.22069451e-02
4.42036465e-02 5.11388361e-01 -1.72769442e-01 -6.37294173e-01
-6.25101149e-01 -8.58764470e-01 -9.39359605e-01 3.00641328e-01
-4.17240821e-02 -6.97678685e-01 -1.32390869e+00 1.67806423e+00
-5.35879612e-01 6.32364929e-01 5.33802867e-01 3.89258951e-01
9.19936717e-01 5.79155803e-01 3.91656533e-02 -1.35927409e-01
9.77576137e-01 -5.18742025e-01 -5.78208804e-01 8.94195735e-02
7.61136115e-01 -6.13439202e-01 7.38240957e-01 6.78990364e-01
-7.82154858e-01 -3.53913218e-01 -1.06371605e+00 8.21599424e-01
-3.70429128e-01 3.08991104e-01 5.07644475e-01 7.64063597e-01
-1.25823224e+00 6.48217440e-01 -8.68372917e-01 -1.53105795e-01
5.16943693e-01 9.38491821e-01 -4.60870504e-01 5.84204555e-01
-1.19460166e+00 9.16124761e-01 4.39090520e-01 -3.87945801e-01
-1.33046901e+00 -7.94700444e-01 -4.03542310e-01 -6.37093335e-02
-5.11849165e-01 -1.47242665e-01 8.71334374e-01 -1.00325096e+00
-1.26948512e+00 5.76191962e-01 5.03207028e-01 -1.15287423e+00
5.51305354e-01 -2.19020788e-02 -9.78105128e-01 -3.61004807e-02
4.45387475e-02 6.86138451e-01 6.34163201e-01 -9.37584221e-01
-4.83790874e-01 -1.08435147e-01 -5.16661286e-01 -2.63418943e-01
-2.16017097e-01 -1.00043684e-01 3.76575410e-01 -7.74073422e-01
-2.20543891e-01 -8.83093715e-01 -4.74125966e-02 -8.10144305e-01
-5.70726454e-01 4.18580212e-02 8.68150890e-01 -1.04185855e+00
8.93472433e-01 -1.80363452e+00 -5.41581869e-01 3.06873441e-01
7.37669989e-02 5.48223734e-01 -1.65325664e-02 4.53166932e-01
-6.32070780e-01 1.35172531e-01 -2.91220725e-01 1.49371296e-01
-3.21321726e-01 -1.74108028e-01 -4.01271462e-01 3.85204047e-01
2.91549087e-01 1.06329036e+00 -6.36626124e-01 -2.92552523e-02
3.10014218e-01 8.50234926e-01 -3.74118209e-01 4.11323935e-01
3.64246637e-01 8.68789434e-01 -3.51604164e-01 6.03160501e-01
5.15831709e-01 1.37147114e-01 -3.95656019e-01 -6.58475757e-02
1.46458313e-01 -1.96631323e-03 -6.41352415e-01 1.15792894e+00
-4.18938786e-01 8.67003560e-01 -9.32033420e-01 -1.19887531e+00
1.36805010e+00 8.42759371e-01 5.30755162e-01 -7.00474262e-01
4.19426799e-01 3.56909573e-01 3.07627231e-01 -4.46527064e-01
-1.18399985e-01 -1.81548938e-01 -7.85207972e-02 1.85239032e-01
4.08926010e-01 -1.71067700e-01 -5.00425160e-01 -1.40336633e-01
1.44143891e+00 -1.19250365e-01 3.66740495e-01 -4.37152028e-01
3.09806317e-01 -5.20974174e-02 4.07757461e-01 6.22883737e-01
-1.51525378e-01 4.52159077e-01 3.38816941e-01 -3.82268906e-01
-1.07864833e+00 -7.97757685e-01 -4.41920519e-01 1.86305493e-02
-4.31984216e-01 -2.78079305e-02 -1.10070813e+00 -4.56082314e-01
-4.09882188e-01 7.80195653e-01 -7.58551717e-01 -4.89644051e-01
-3.10231835e-01 -1.04646111e+00 1.07410824e+00 5.67786455e-01
6.85028851e-01 -1.61247694e+00 -7.63417006e-01 3.39323163e-01
3.26058000e-01 -9.60439622e-01 1.35401160e-01 4.98714030e-01
-7.93488801e-01 -1.07457054e+00 -7.55632162e-01 -9.19265270e-01
6.33076131e-01 -8.69309783e-01 9.27516758e-01 6.00674413e-02
-3.68735284e-01 4.37642708e-02 -7.06836581e-01 -7.81327307e-01
-3.87055159e-01 -1.16747599e-02 2.96450466e-01 -1.88435957e-01
5.42195380e-01 -9.15404320e-01 -6.98106885e-01 -1.18313618e-01
-5.39992332e-01 1.19780026e-01 7.97970891e-01 1.07217145e+00
4.20848906e-01 -1.49190098e-01 1.35021305e+00 -8.24450552e-01
8.53063166e-01 -6.51118338e-01 -4.93155062e-01 8.91021565e-02
-8.85569513e-01 -5.35098948e-02 7.75504470e-01 -6.28917277e-01
-3.13911080e-01 1.41717330e-01 -3.19113463e-01 -4.09093231e-01
-1.99742734e-01 1.03877261e-01 1.83620960e-01 -3.03575695e-01
7.71062315e-01 6.47567153e-01 -2.35488221e-01 -1.32879555e-01
-4.20998871e-01 9.40016866e-01 5.11265099e-01 7.68112689e-02
6.42772496e-01 -9.37960669e-02 -6.41041324e-02 -5.49136877e-01
-3.16368826e-02 1.55616745e-01 -2.54109859e-01 3.34936567e-02
7.32971489e-01 -9.76715565e-01 -4.69469637e-01 7.72818863e-01
-8.45649898e-01 -5.13060987e-01 -2.16769293e-01 6.18742764e-01
-5.06955087e-01 -3.15040946e-01 -4.48289454e-01 -7.70856559e-01
-1.06406915e+00 -1.28886724e+00 6.92117214e-01 1.50645301e-02
-1.81813985e-01 -8.31292570e-01 -5.02367355e-02 -1.31758526e-01
6.32957995e-01 9.18307424e-01 6.31613016e-01 -1.28952372e+00
-2.47605786e-01 -5.91098905e-01 1.04972877e-01 5.93693018e-01
2.87441969e-01 -4.30502087e-01 -1.15450537e+00 -4.52429503e-01
1.99344635e-01 -2.40330815e-01 4.02838200e-01 4.81300086e-01
1.16791666e+00 -3.14610690e-01 -3.79913241e-01 8.89000237e-01
1.69364595e+00 9.91264284e-01 8.37776124e-01 3.43864709e-01
1.68302551e-01 -1.71884671e-01 2.60623246e-01 4.91074204e-01
-1.98298082e-01 3.16636443e-01 2.90538430e-01 -1.24284536e-01
-2.47817099e-01 -8.40172991e-02 2.66483516e-01 8.37082982e-01
3.86510901e-02 -1.62687257e-01 -1.11140716e+00 6.63054347e-01
-1.07199085e+00 -6.55151784e-01 -8.12715739e-02 2.18293905e+00
8.51856232e-01 2.16335714e-01 -1.23955242e-01 7.10264206e-01
4.65393901e-01 -6.14229262e-01 -3.63176703e-01 -2.90204644e-01
-2.00062469e-01 1.16094375e+00 5.38155198e-01 3.64581019e-01
-8.73665214e-01 8.95722628e-01 5.85153246e+00 7.26594269e-01
-1.60572422e+00 3.47145170e-01 8.57358098e-01 5.81662208e-02
7.92004094e-02 -2.58848071e-01 -5.04177153e-01 8.64837825e-01
1.40942883e+00 -2.82974511e-01 4.39262509e-01 6.19597733e-01
1.07506074e-01 2.09470198e-01 -1.05652511e+00 1.23970461e+00
7.38159344e-02 -1.13982666e+00 -2.85620149e-02 7.21916184e-03
9.04710889e-01 1.52882516e-01 -2.97109671e-02 5.90807736e-01
2.77044196e-02 -1.65475011e+00 2.54178196e-01 6.31011605e-01
1.17835510e+00 -1.04783392e+00 1.13546669e+00 2.41407543e-01
-8.06457043e-01 4.39954512e-02 -7.15712830e-02 1.41288927e-02
-2.65976101e-01 2.97024220e-01 -1.47423565e+00 2.94161409e-01
6.71781182e-01 4.30022210e-01 -6.32368147e-01 1.08704174e+00
-2.74014682e-01 1.09558713e+00 -1.39657304e-01 -1.10713236e-01
1.96877420e-01 2.38647953e-01 2.98726350e-01 1.14027786e+00
7.06729889e-01 3.21084082e-01 -3.42092186e-01 6.03527188e-01
-1.79381035e-02 9.99649540e-02 -7.42980003e-01 5.91523796e-02
5.50702810e-01 1.09357738e+00 -4.64501083e-01 -2.95892447e-01
-4.13836837e-02 8.51799071e-01 -1.83269694e-01 1.11598104e-01
-9.65103328e-01 -7.48888552e-01 -2.74781929e-03 1.09069474e-01
-1.74089715e-01 3.36879700e-01 -4.56115335e-01 -9.15677428e-01
-2.89949477e-01 -9.46964204e-01 -1.96032867e-01 -9.02782917e-01
-8.73614788e-01 1.51271629e+00 -2.50755727e-01 -1.57376182e+00
-5.56538045e-01 -4.45329547e-01 -8.11690271e-01 1.08480728e+00
-1.14625227e+00 -1.14908969e+00 -4.18332100e-01 9.98633623e-01
4.74966347e-01 -8.57721269e-01 1.23138905e+00 1.77419141e-01
-2.63590664e-01 8.66867602e-01 3.91424727e-03 3.21239620e-01
3.93094271e-01 -1.08328938e+00 3.39536309e-01 7.72834063e-01
-2.50949524e-02 -1.12734456e-02 6.79877520e-01 -6.56737983e-01
-9.43099737e-01 -1.38099384e+00 6.63008451e-01 -2.48233482e-01
4.57175881e-01 -2.14360744e-01 -6.88374817e-01 8.11274827e-01
4.96436447e-01 3.93864065e-02 6.70140982e-01 -5.63432097e-01
4.09978777e-01 -1.17525414e-01 -1.61993003e+00 2.69675910e-01
4.60163444e-01 -2.90984899e-01 -7.14984000e-01 4.92677242e-01
4.23015386e-01 -3.12781692e-01 -1.07963026e+00 6.43892348e-01
1.84887916e-01 -7.25006044e-01 5.63714564e-01 -4.43864286e-01
3.33229393e-01 1.35934621e-01 -1.22296184e-01 -1.75545311e+00
1.37283593e-01 -6.49587929e-01 1.25878930e-01 9.78217006e-01
7.23956287e-01 -9.53413129e-01 8.57547104e-01 2.89839178e-01
-3.76106054e-01 -1.18871820e+00 -7.52130449e-01 -7.71014690e-01
2.11252451e-01 -5.02989292e-01 8.82327735e-01 1.16231763e+00
1.22021651e-03 1.52858766e-03 -4.63131011e-01 2.77232200e-01
3.58126432e-01 -4.67759579e-01 4.73714709e-01 -1.12585974e+00
-1.42279208e-01 1.52404591e-01 -9.87154663e-01 1.69246972e-01
-4.01338413e-02 -1.00325978e+00 -3.58373344e-01 -1.24727178e+00
1.63796004e-02 -5.87592065e-01 -7.47394919e-01 9.16486919e-01
2.78628320e-01 6.14123046e-01 -1.31956413e-01 8.33463147e-02
3.96466106e-01 2.19992548e-01 9.81014013e-01 2.28569563e-02
-4.07182902e-01 -3.39825451e-02 -4.07074600e-01 5.52173376e-01
1.40214026e+00 -7.00541556e-01 -5.57568848e-01 -6.92372471e-02
-3.54621291e-01 4.01984394e-01 3.99876535e-01 -1.57485259e+00
5.70779219e-02 3.47358316e-01 8.85786653e-01 -3.29278767e-01
4.04613853e-01 -6.40883148e-01 5.35882115e-01 9.56775010e-01
-9.93669382e-04 1.20719150e-01 4.79443789e-01 -1.31887188e-02
-2.28860185e-01 -9.31595510e-04 7.46181548e-01 6.67543486e-02
-5.93623102e-01 3.26494396e-01 -2.17238873e-01 -2.72939377e-03
1.40371251e+00 -2.71171927e-01 -2.61069331e-02 -3.80263418e-01
-1.03093636e+00 -1.07487507e-01 -7.94711933e-02 3.06811810e-01
8.90207350e-01 -1.27563834e+00 -9.24936593e-01 6.89042449e-01
-3.96918170e-02 -5.84632933e-01 -1.11758590e-01 8.34118903e-01
-5.95479071e-01 6.04911506e-01 -7.59303451e-01 -4.19279367e-01
-1.22054720e+00 1.81538820e-01 7.08512127e-01 -1.33269906e-01
-7.03445971e-01 8.12193155e-01 -1.12374693e-01 -1.74534947e-01
-1.02247894e-02 -4.57978666e-01 -2.76235282e-01 -4.18193847e-01
3.53684306e-01 1.60885118e-02 4.53936577e-01 -4.02064085e-01
-4.67644453e-01 3.08419943e-01 4.46639806e-02 -3.36004794e-02
1.62432647e+00 7.99989343e-01 2.15417251e-01 -5.06664813e-02
1.08064163e+00 -2.23396942e-01 -9.44850802e-01 4.41641510e-01
-2.33146474e-01 6.03713877e-02 1.21317431e-01 -1.61544061e+00
-1.40472054e+00 7.99353898e-01 1.40286314e+00 -1.94574753e-03
1.57882893e+00 -3.82288218e-01 6.91989839e-01 1.16066545e-01
6.79075420e-01 -5.38363278e-01 -2.41139844e-01 -2.26778742e-02
9.80441272e-01 -1.07979202e+00 -5.11758864e-01 1.01442955e-01
-6.28609180e-01 9.43557322e-01 5.86255372e-01 -7.37760425e-01
7.56913900e-01 7.09988296e-01 -5.30689198e-04 -1.00485556e-01
-7.60911524e-01 4.32155639e-01 1.93889409e-01 9.05022621e-01
2.95531869e-01 4.90132421e-01 -5.31384468e-01 1.18642449e+00
-8.24863374e-01 3.67125213e-01 7.62898147e-01 8.57715309e-01
-1.07105762e-01 -1.06773293e+00 -1.68058738e-01 9.42167401e-01
-8.97151291e-01 -4.81510252e-01 -1.99766055e-01 1.20676732e+00
4.38389301e-01 8.86213541e-01 8.51552282e-03 -1.00039113e+00
1.56596482e-01 1.07819133e-01 4.04927135e-01 -3.90243024e-01
-1.03260314e+00 -1.08556867e-01 -1.85822964e-01 -1.79359600e-01
-4.72101457e-02 -2.48908833e-01 -1.25848031e+00 7.61472955e-02
-3.72253835e-01 5.67151487e-01 7.08974183e-01 8.89392376e-01
3.40429127e-01 8.97543192e-01 7.49029696e-01 -3.49476039e-01
-3.49826396e-01 -1.48988509e+00 -7.99566329e-01 2.36364543e-01
3.54143232e-01 -4.58257169e-01 -3.68586600e-01 1.68716431e-01] | [13.240281105041504, 3.533935308456421] |
9598c349-e7e3-4bf3-bd45-3a13e99aa357 | nas-fm-neural-architecture-search-for-tunable | 2305.12868 | null | https://arxiv.org/abs/2305.12868v1 | https://arxiv.org/pdf/2305.12868v1.pdf | NAS-FM: Neural Architecture Search for Tunable and Interpretable Sound Synthesis based on Frequency Modulation | Developing digital sound synthesizers is crucial to the music industry as it provides a low-cost way to produce high-quality sounds with rich timbres. Existing traditional synthesizers often require substantial expertise to determine the overall framework of a synthesizer and the parameters of submodules. Since expert knowledge is hard to acquire, it hinders the flexibility to quickly design and tune digital synthesizers for diverse sounds. In this paper, we propose ``NAS-FM'', which adopts neural architecture search (NAS) to build a differentiable frequency modulation (FM) synthesizer. Tunable synthesizers with interpretable controls can be developed automatically from sounds without any prior expert knowledge and manual operating costs. In detail, we train a supernet with a specifically designed search space, including predicting the envelopes of carriers and modulators with different frequency ratios. An evolutionary search algorithm with adaptive oscillator size is then developed to find the optimal relationship between oscillators and the frequency ratio of FM. Extensive experiments on recordings of different instrument sounds show that our algorithm can build a synthesizer fully automatically, achieving better results than handcrafted synthesizers. Audio samples are available at https://nas-fm.github.io/. | ['Yike Guo', 'Qifeng Liu', 'Xu Tan', 'Wei Xue', 'Zhen Ye'] | 2023-05-22 | null | null | null | null | ['architecture-search'] | ['methodology'] | [ 2.26250634e-01 -4.72465068e-01 -5.69458753e-02 8.02788511e-03
-6.95972204e-01 -9.04681742e-01 -1.17197379e-01 -5.32478929e-01
1.71664178e-01 5.92949808e-01 -8.51632208e-02 -2.58856595e-01
-3.11247706e-01 -6.70101583e-01 -4.49036032e-01 -6.53201342e-01
1.74964935e-01 1.54004902e-01 2.42550410e-02 -5.11236548e-01
1.18160047e-01 2.45280877e-01 -1.68159306e+00 1.71705466e-02
9.85242903e-01 1.00409567e+00 6.50346518e-01 1.10902882e+00
1.51692599e-01 2.25323379e-01 -1.11882722e+00 -4.42248881e-02
4.42673653e-01 -1.06569052e+00 -2.50684619e-01 -2.33652577e-01
1.42389566e-01 -6.75017685e-02 -3.02171148e-02 9.94228959e-01
9.93243754e-01 3.87272805e-01 5.54310143e-01 -7.57167995e-01
-5.69263041e-01 1.05492389e+00 8.35845992e-02 2.48296373e-02
3.01157832e-01 4.27126974e-01 1.18401766e+00 -5.07570088e-01
1.63203850e-01 9.08137739e-01 6.98013425e-01 6.35679185e-01
-1.31885290e+00 -9.33197021e-01 -3.18577915e-01 4.96264212e-02
-1.51443708e+00 -5.04947305e-01 1.02386737e+00 -2.56808817e-01
8.41969490e-01 4.95457143e-01 9.48734462e-01 8.55051398e-01
5.67043424e-02 3.09370935e-01 5.81941783e-01 -7.00407982e-01
2.82660633e-01 -1.23268709e-01 -6.90988839e-01 4.91535544e-01
-1.44893795e-01 2.61646479e-01 -7.35847592e-01 -4.48890403e-02
1.18306172e+00 -6.08744264e-01 -6.06049359e-01 -3.52796949e-02
-9.88925099e-01 7.63491869e-01 3.17647487e-01 4.97607201e-01
-3.26547354e-01 4.71397936e-01 2.78202184e-02 6.44677460e-01
-2.23962635e-01 1.42002249e+00 -4.45776969e-01 -3.80670726e-01
-9.61817980e-01 3.10236007e-01 8.72896135e-01 6.64760411e-01
2.79051185e-01 9.02836680e-01 1.97364062e-01 1.18906438e+00
9.92224887e-02 6.44988775e-01 7.40099013e-01 -1.18500662e+00
2.41366029e-01 8.98196250e-02 1.34017557e-01 -8.96460712e-01
-3.96975338e-01 -6.33813500e-01 -6.22872293e-01 7.18338713e-02
2.34726891e-01 -6.69427812e-01 -5.83587766e-01 1.67039216e+00
2.04104975e-01 1.26482949e-01 -2.06298292e-01 1.01671958e+00
6.33088768e-01 9.05911803e-01 -6.46767914e-01 -2.54189700e-01
1.21383715e+00 -8.90715063e-01 -9.84960318e-01 -2.28319585e-01
8.82358626e-02 -9.57965493e-01 1.34450412e+00 6.27893150e-01
-1.20895934e+00 -8.57297003e-01 -1.31207108e+00 2.72057980e-01
1.14417784e-01 3.26798856e-01 4.88955647e-01 8.31911206e-01
-9.54552591e-01 8.85589242e-01 -5.66270947e-01 3.59092504e-01
-2.47435458e-02 5.64333797e-01 3.40991318e-01 7.85539389e-01
-1.35552311e+00 6.10259533e-01 3.46285462e-01 8.15759897e-02
-6.72551036e-01 -9.42282319e-01 -4.02559996e-01 1.26593783e-01
4.04351771e-01 -7.63471067e-01 1.72865093e+00 -1.19441128e+00
-2.40956068e+00 6.32329509e-02 2.57979304e-01 -3.18774045e-01
9.26844329e-02 -1.16886966e-01 -6.90929532e-01 6.35624528e-02
-3.49319220e-01 3.72399002e-01 1.34239316e+00 -8.49980235e-01
-6.35960937e-01 3.62316012e-01 -1.23497412e-01 9.36127752e-02
-3.55467319e-01 -1.00724943e-01 -1.51030213e-01 -1.12666297e+00
-8.69597774e-03 -9.86462355e-01 -1.27293855e-01 -2.27870613e-01
-3.04709703e-01 5.79918884e-02 3.01199496e-01 -5.17277539e-01
1.82669318e+00 -2.11947870e+00 4.46131229e-01 3.05977434e-01
-1.66129634e-01 4.09336030e-01 -8.93773586e-02 3.97362202e-01
1.70084052e-02 -1.46269381e-01 -8.58117566e-02 2.68263549e-01
1.49344891e-01 -2.18024358e-01 -3.39316338e-01 -3.80620100e-02
-4.87884460e-03 5.81623137e-01 -7.79693246e-01 -6.68776929e-02
3.46102752e-02 4.31336433e-01 -9.73557353e-01 4.52379376e-01
-5.90856194e-01 5.80151916e-01 -4.61734951e-01 5.76317608e-01
-1.09420456e-02 -1.90726802e-01 2.97064960e-01 -3.93113732e-01
-2.70081192e-01 4.55688000e-01 -1.48983395e+00 1.51921952e+00
-9.24845815e-01 7.28671849e-01 3.07247669e-01 -6.09224737e-01
1.33209240e+00 5.00224590e-01 1.66415140e-01 -4.68335837e-01
4.68905002e-01 5.46919525e-01 4.69741940e-01 -4.78383422e-01
3.48049909e-01 -2.95967370e-01 -5.26750758e-02 4.90056276e-01
2.85263993e-02 -9.79969084e-01 1.18116401e-01 -6.32732272e-01
7.27725983e-01 6.71952916e-03 3.16996217e-01 5.13353385e-03
4.07874048e-01 -3.44051957e-01 4.39982533e-01 5.50906599e-01
3.31961274e-01 5.64045370e-01 7.37493187e-02 -2.04985797e-01
-9.76164818e-01 -9.59196329e-01 -6.69527501e-02 1.14995718e+00
-2.01704621e-01 -4.63641733e-01 -8.18531334e-01 2.51348376e-01
-2.34066248e-01 7.30444610e-01 -2.80101243e-02 -2.86273330e-01
-9.28253412e-01 -2.87053198e-01 6.24451995e-01 1.93544850e-01
1.48750171e-01 -1.13250399e+00 -7.26433098e-01 5.58815897e-01
-3.33114117e-01 -6.28394008e-01 -8.98524225e-01 4.60219204e-01
-6.77024782e-01 -5.27518094e-01 -5.66431463e-01 -1.04003251e+00
1.30069032e-01 -3.13226342e-01 8.63028347e-01 2.48281490e-02
-4.92602646e-01 -1.17090642e-01 -2.14097381e-01 -5.70435703e-01
-6.52516127e-01 3.50552350e-01 4.40774381e-01 -2.18787774e-01
-3.84170145e-01 -1.00379682e+00 -6.44774497e-01 4.75394517e-01
-7.17747271e-01 -2.21812094e-04 3.38076234e-01 7.40506649e-01
7.05172300e-01 4.57703024e-01 1.01257110e+00 -2.71509528e-01
1.06982076e+00 -1.00647300e-01 -9.55610156e-01 5.55837043e-02
-3.35041106e-01 1.52249992e-01 1.27645612e+00 -1.01462710e+00
-6.28215253e-01 4.58403863e-02 -2.41980135e-01 -4.02629167e-01
2.79160053e-01 2.40116552e-01 -2.42928877e-01 -9.42702368e-02
9.63059425e-01 7.21093714e-02 -2.09015980e-01 -5.50604999e-01
4.22966868e-01 8.99582684e-01 6.56592846e-01 -6.32596552e-01
8.65436673e-01 -2.85053372e-01 -1.66912466e-01 -8.21418703e-01
-6.15441263e-01 1.26311854e-01 -1.95948973e-01 -2.31585905e-01
4.34407473e-01 -5.95464587e-01 -8.96076620e-01 4.02799875e-01
-7.56189525e-01 -6.15128756e-01 -2.41410121e-01 7.35192597e-01
-9.03199494e-01 -2.79006451e-01 -3.89882445e-01 -6.75460458e-01
-5.26801944e-01 -1.14276600e+00 5.55110991e-01 5.29061794e-01
-6.61018014e-01 -6.30139649e-01 1.08495012e-01 1.73131526e-01
6.76092327e-01 1.20100208e-01 8.08444560e-01 2.34499667e-02
-5.69225609e-01 1.27246557e-02 7.18905926e-01 3.74459058e-01
5.74134469e-01 2.36347392e-01 -7.61382937e-01 -1.72984540e-01
1.55088961e-01 -8.94432068e-02 2.03984529e-01 6.29978478e-01
1.17834365e+00 -6.00771427e-01 -2.61821244e-02 8.98321033e-01
1.19040990e+00 7.62789130e-01 3.05461645e-01 2.18507171e-01
4.95550513e-01 1.66355953e-01 4.31752563e-01 6.31530881e-01
-1.57883629e-01 9.14503872e-01 -1.41669884e-02 2.21593231e-01
-1.80266485e-01 -4.34881479e-01 3.64928186e-01 1.21951771e+00
-1.97847933e-01 -3.37302029e-01 -5.05495787e-01 2.13678598e-01
-1.25777388e+00 -8.63365471e-01 4.06881094e-01 2.12687349e+00
1.41585076e+00 -2.09042635e-02 3.95726949e-01 4.88253683e-01
8.55154335e-01 -1.44777009e-02 -7.47895360e-01 -6.27046704e-01
1.77798867e-01 8.27281594e-01 2.32467771e-01 5.43882310e-01
-8.25229585e-01 9.68029737e-01 6.46534252e+00 1.00517964e+00
-1.51578104e+00 -3.93079460e-01 7.36363381e-02 -7.20305264e-01
-3.64775568e-01 -2.45922595e-01 -6.26010001e-01 5.98692119e-01
1.18888056e+00 -3.16187650e-01 1.30105734e+00 6.37896061e-01
4.12149280e-01 5.08400321e-01 -9.00385141e-01 1.12555802e+00
-3.09839964e-01 -1.40819299e+00 -7.42027387e-02 -4.53472704e-01
8.62535298e-01 -5.36163688e-01 3.64789516e-01 2.73276828e-02
8.99748653e-02 -1.18712926e+00 1.10708559e+00 5.74149191e-01
8.88489246e-01 -1.01577532e+00 7.86267072e-02 2.15628073e-01
-1.27183282e+00 -3.34072918e-01 -1.45099178e-01 -6.28525764e-02
2.67795771e-01 3.59977037e-01 -9.74655926e-01 1.58025742e-01
4.40374523e-01 1.45314857e-01 -5.90078235e-02 1.08041644e+00
-4.63897645e-01 8.83276522e-01 -4.31133717e-01 -6.36254251e-01
-6.11440763e-02 -2.07367286e-01 6.41642928e-01 7.70261288e-01
8.14628959e-01 1.55018523e-01 -2.13669375e-01 9.01619732e-01
-1.56090543e-01 6.30765557e-02 -4.90037538e-02 -4.38494653e-01
9.54237580e-01 9.60825980e-01 -5.17486095e-01 2.74665058e-01
3.15146774e-01 5.27383387e-01 -2.64387280e-01 3.77977610e-01
-1.05400956e+00 -9.09331381e-01 6.28257394e-01 6.52164668e-02
7.45647430e-01 -2.73843855e-01 -5.35139255e-02 -7.36843944e-01
-2.96561599e-01 -1.60998654e+00 -5.05612418e-02 -7.88384259e-01
-9.49637890e-01 8.00984561e-01 -4.16641623e-01 -1.53224158e+00
-7.82271802e-01 -3.81619751e-01 -4.86450940e-01 8.16940784e-01
-8.91700327e-01 -4.04943675e-01 7.30460957e-02 3.28454345e-01
6.06621265e-01 -3.49650472e-01 9.31632161e-01 1.73348874e-01
-3.74661803e-01 7.88452625e-01 5.68960160e-02 -2.50646025e-01
5.98819971e-01 -1.10854268e+00 4.06383753e-01 4.64784741e-01
3.64153951e-01 6.33452773e-01 1.14878130e+00 -2.78381348e-01
-1.54262006e+00 -7.29735911e-01 3.96930248e-01 -4.47096229e-02
8.58966112e-01 -3.99308681e-01 -6.32265508e-01 6.13591932e-02
8.84286836e-02 -5.54235876e-01 8.11412096e-01 -1.74359411e-01
-2.23661447e-03 -4.34385270e-01 -7.20926404e-01 8.94693851e-01
9.98023629e-01 -5.04674733e-01 -4.56149995e-01 1.52912512e-01
9.20162559e-01 -6.40655398e-01 -9.25594628e-01 1.17472462e-01
7.07477152e-01 -7.11051702e-01 1.05598080e+00 -7.83709809e-02
2.87275225e-01 -7.06858158e-01 -3.06274816e-02 -1.72671175e+00
-3.17830771e-01 -1.41055059e+00 -2.17431083e-01 1.07402909e+00
6.15137577e-01 -5.80235302e-01 2.92783827e-01 8.74108300e-02
-7.84781352e-02 -7.00479567e-01 -6.03020787e-01 -1.01319134e+00
-1.53064027e-01 -4.21005189e-01 1.03557265e+00 6.28990531e-01
-1.24086766e-02 5.40613472e-01 -4.81735080e-01 2.59072393e-01
1.47212580e-01 4.49863136e-01 6.96406305e-01 -9.33034003e-01
-1.09943271e+00 -7.67471313e-01 6.47016913e-02 -1.07146740e+00
-1.64855227e-01 -6.20933890e-01 2.70465165e-01 -1.04520702e+00
-7.39878833e-01 -5.44981182e-01 -7.86640942e-02 3.09999406e-01
-1.28936023e-01 1.74752265e-01 3.28747541e-01 -7.16702119e-02
6.93343207e-02 5.62698543e-01 1.55873287e+00 -1.24276988e-02
-7.52223134e-01 6.05717301e-01 -7.26268589e-01 6.98885679e-01
1.16626167e+00 -5.78242838e-01 -6.94816113e-01 -3.49316448e-01
4.45424825e-01 3.58890295e-01 -8.93655866e-02 -1.27488256e+00
8.25488120e-02 -2.00552359e-01 2.30712622e-01 -2.37611949e-01
4.11418051e-01 -5.02833962e-01 6.89178944e-01 4.32011098e-01
-4.86026347e-01 7.93448556e-03 3.00879866e-01 1.50247514e-01
-1.56114176e-01 -5.42747259e-01 8.20224345e-01 1.10340212e-02
-1.82499900e-01 -4.03961651e-02 -4.04528826e-01 7.67633021e-02
5.18111646e-01 -9.12225470e-02 1.24473579e-01 -6.82901978e-01
-6.85552955e-01 -1.02598339e-01 1.60291210e-01 4.34901267e-01
3.48630548e-01 -1.35805798e+00 -4.19526041e-01 2.45212689e-01
-3.95427585e-01 -2.17961550e-01 2.82284141e-01 1.30654141e-01
-6.22305870e-01 3.28941047e-01 -1.24746293e-01 -3.08117360e-01
-1.19277537e+00 2.50233173e-01 7.19798446e-01 1.98781922e-01
-3.74733716e-01 1.08118796e+00 -2.08739340e-01 -3.82252127e-01
1.86822444e-01 -6.17981195e-01 -5.94411865e-02 -6.42755255e-02
6.22245312e-01 3.62355918e-01 -1.07549541e-01 -2.43043825e-02
-1.40466124e-01 7.59031832e-01 5.95843315e-01 -3.72639000e-01
1.25536764e+00 9.50337723e-02 7.65177980e-02 5.23793638e-01
9.69333887e-01 2.83794284e-01 -1.18873167e+00 1.70547843e-01
-4.02341634e-01 -4.93351042e-01 1.79411858e-01 -7.92988896e-01
-1.04663455e+00 5.18734396e-01 5.41875720e-01 3.97763163e-01
1.50528526e+00 -2.73012370e-01 9.81845498e-01 5.15366077e-01
4.32180852e-01 -1.26682127e+00 3.24658006e-01 3.64148259e-01
1.10854173e+00 -3.99033129e-01 -1.86906591e-01 7.12342635e-02
-5.39655983e-01 1.34429419e+00 3.33708733e-01 -1.64580882e-01
5.29824317e-01 5.37840366e-01 3.61325026e-01 2.70040572e-01
-5.60797274e-01 1.44810274e-01 4.98726666e-01 4.54153895e-01
3.76661569e-01 1.06585771e-01 -1.40593395e-01 8.19242716e-01
-1.20180762e+00 -3.97815220e-02 3.68455768e-01 5.71134448e-01
-6.13649726e-01 -1.31770658e+00 -5.26159048e-01 2.09570348e-01
-4.66269821e-01 -1.96781129e-01 -2.33095288e-01 3.46355051e-01
2.77979404e-01 1.08162832e+00 6.21797591e-02 -5.89763761e-01
5.07380068e-01 -1.46457106e-01 6.31209612e-01 -4.61451232e-01
-8.21632087e-01 4.58034635e-01 8.66482556e-02 -2.22036675e-01
-6.38952851e-02 -4.65635031e-01 -1.38964403e+00 -1.92890480e-01
-7.04133511e-01 3.20406735e-01 6.51469707e-01 4.54013616e-01
2.14459375e-01 1.06918955e+00 1.05085385e+00 -7.51190662e-01
-6.38457298e-01 -7.53701091e-01 -5.56556880e-01 -3.35559756e-01
4.58731145e-01 -3.78857374e-01 -3.78814459e-01 1.68441266e-01] | [15.686223983764648, 5.91954231262207] |
48658b0f-052d-4649-9b7e-ab333e547bde | community-detection-in-the-stochastic-block | 2101.12336 | null | https://arxiv.org/abs/2101.12336v2 | https://arxiv.org/pdf/2101.12336v2.pdf | Community Detection in the Stochastic Block Model by Mixed Integer Programming | The Degree-Corrected Stochastic Block Model (DCSBM) is a popular model to generate random graphs with community structure given an expected degree sequence. The standard approach of community detection based on the DCSBM is to search for the model parameters that are the most likely to have produced the observed network data through maximum likelihood estimation (MLE). Current techniques for the MLE problem are heuristics, and therefore do not guarantee convergence to the optimum. We present mathematical programming formulations and exact solution methods that can provably find the model parameters and community assignments of maximum likelihood given an observed graph. We compare these exact methods with classical heuristic algorithms based on expectation-maximization (EM). The solutions given by exact methods give us a principled way of measuring the experimental performance of classical heuristics and comparing different variations thereof. | ['Thibaut Vidal', 'Breno Serrano'] | 2021-01-26 | null | null | null | null | ['stochastic-block-model'] | ['graphs'] | [ 2.75164425e-01 2.91156173e-01 -1.07205182e-01 -1.99059546e-02
-4.41193193e-01 -6.72711909e-01 5.86673021e-01 2.42331013e-01
-1.20111831e-01 1.03260946e+00 -2.95235753e-01 -4.79808748e-01
-5.92134655e-01 -1.10757709e+00 -5.61937034e-01 -7.46038139e-01
-7.52813876e-01 1.25080144e+00 3.30393761e-01 6.21572062e-02
3.06037784e-01 5.13993263e-01 -9.37547565e-01 -3.65497060e-02
8.46565843e-01 6.72380179e-02 3.32180202e-01 1.05852306e+00
-1.64852723e-01 5.92153251e-01 -5.49478352e-01 -5.53933442e-01
2.71548629e-01 -6.18490636e-01 -9.02943134e-01 5.42169631e-01
-2.04563171e-01 1.31397128e-01 -4.21273738e-01 1.17851281e+00
2.55364209e-01 -3.20368171e-01 9.45995450e-01 -1.86730480e+00
-1.62768394e-01 9.96382236e-01 -8.65663230e-01 8.43507145e-03
8.66033733e-01 -2.21930325e-01 1.07988369e+00 -4.75874573e-01
1.25748062e+00 1.43135405e+00 6.48443639e-01 3.67121071e-01
-2.04712844e+00 -4.30246830e-01 -1.55807897e-01 3.64485562e-01
-2.02507663e+00 -6.55484945e-02 6.27216101e-01 -4.34024692e-01
6.28758490e-01 2.85617411e-01 8.45796406e-01 9.14419055e-01
5.14784269e-02 7.02578425e-01 1.10418868e+00 -6.91644490e-01
3.29560280e-01 1.55791521e-01 -2.20150441e-01 6.67178512e-01
9.59504902e-01 1.94250215e-02 -2.08956078e-01 -8.52162778e-01
7.22521663e-01 -3.43581647e-01 -3.06204379e-01 -9.76921618e-01
-1.13955665e+00 1.06035292e+00 2.06637055e-01 8.73735696e-02
-4.29707408e-01 4.16949004e-01 1.19071163e-01 2.83364803e-01
6.54520914e-02 2.72042364e-01 -1.83974907e-01 3.91680449e-01
-1.07687819e+00 4.74146962e-01 1.33677554e+00 1.22968483e+00
8.93936455e-01 -3.87200922e-01 1.13041230e-01 3.77711743e-01
7.93426335e-01 5.31927049e-01 -5.08480072e-01 -9.19088244e-01
3.69133085e-01 4.82488394e-01 2.44650587e-01 -1.31517267e+00
-3.56285572e-02 -3.43783587e-01 -8.67177367e-01 -3.92401256e-02
4.38174427e-01 -3.26534450e-01 -5.89664996e-01 1.56906521e+00
2.51869589e-01 1.73616365e-01 -1.48859575e-01 3.85196686e-01
8.03562105e-02 7.48026788e-01 -3.56062442e-01 -7.98234046e-01
5.94885767e-01 -5.36530554e-01 -5.68849385e-01 1.60411336e-02
4.82115746e-01 -7.02852130e-01 2.00102508e-01 4.55109775e-01
-8.31802249e-01 2.56445736e-01 -9.79643345e-01 9.04684126e-01
8.61489177e-02 -4.37845737e-01 5.83935261e-01 1.01546705e+00
-1.57445848e+00 6.21261001e-01 -6.37801349e-01 -4.61056978e-01
-1.73428640e-01 4.07207906e-01 -2.75295079e-01 -3.07029337e-01
-7.63433039e-01 6.16377592e-01 6.89955831e-01 7.48092607e-02
-1.21248913e+00 1.13339841e-01 -5.80612957e-01 3.92666385e-02
6.23956501e-01 -6.38823271e-01 8.65280032e-01 -8.41838002e-01
-8.21807504e-01 8.36726427e-01 -4.27000403e-01 -6.69009209e-01
4.85907078e-01 7.46458948e-01 -4.93082926e-02 3.75511706e-01
-1.30864745e-02 4.88617182e-01 5.11505127e-01 -1.58626974e+00
-1.94437250e-01 2.58770883e-01 -2.23131031e-01 -9.13965181e-02
1.51681513e-01 1.11036740e-01 -2.50534981e-01 -1.90742016e-01
4.42563534e-01 -1.03343272e+00 -8.73330832e-01 -3.66912663e-01
-8.23029697e-01 -1.93162575e-01 3.88509750e-01 -4.61459428e-01
1.35209358e+00 -1.52175581e+00 3.83730054e-01 1.12733173e+00
3.44846040e-01 -2.00081766e-01 -2.21673816e-01 1.19171154e+00
5.44444367e-04 5.91308475e-01 -2.09093228e-01 -9.65537429e-02
-2.71483487e-03 2.76939720e-01 1.20017380e-01 6.50478661e-01
-1.32336035e-01 4.08368975e-01 -1.06702125e+00 -9.09072757e-01
5.52315451e-02 -7.88076073e-02 -7.18291819e-01 3.86248417e-02
-3.32568347e-01 9.24382731e-03 -2.14556530e-01 3.02792341e-01
9.33851361e-01 -5.49448431e-01 1.24689949e+00 4.61712182e-01
2.17463195e-01 -1.42402202e-01 -1.77588689e+00 8.33896339e-01
2.51555771e-01 6.85131788e-01 4.46471989e-01 -9.09662485e-01
1.04195678e+00 5.34906268e-01 6.15945160e-01 3.32167029e-01
-5.83854094e-02 2.80797720e-01 2.11335644e-01 -7.56176561e-02
7.72534683e-02 6.16592132e-02 1.17373683e-01 7.23011196e-01
-7.92123470e-03 -1.04225181e-01 7.22290397e-01 9.28361595e-01
1.41073740e+00 -4.90478218e-01 5.43159127e-01 -6.03509307e-01
3.79352510e-01 -3.52401957e-02 4.58240956e-01 1.25897372e+00
-5.22744618e-02 3.35965991e-01 1.06068850e+00 -4.64130081e-02
-1.38711715e+00 -1.10400593e+00 2.54013866e-01 1.33832112e-01
1.13041565e-01 -7.86779344e-01 -8.19697976e-01 -2.75862604e-01
-1.39506012e-01 4.60349053e-01 -4.25950378e-01 3.74756455e-01
-4.74280231e-02 -8.87306333e-01 8.80371854e-02 -3.44958603e-01
1.56721175e-02 -9.34905410e-01 8.65953788e-02 4.76903796e-01
-4.45799977e-01 -1.13232040e+00 -2.11072013e-01 -7.69429505e-02
-9.99619663e-01 -1.39342403e+00 -4.59099799e-01 -7.04589188e-01
1.17204404e+00 3.74973863e-01 1.23161745e+00 7.33404815e-01
-2.81415939e-01 3.00941855e-01 -3.77629250e-01 1.43491209e-01
-9.46173072e-01 4.44439314e-02 9.13692638e-02 3.94528657e-02
1.61595955e-01 -7.87528098e-01 -3.33485007e-01 3.27804685e-01
-6.63372993e-01 2.55227704e-02 6.12679780e-01 6.45718336e-01
4.85559344e-01 4.27677900e-01 1.22375607e-01 -9.60110009e-01
8.81594002e-01 -6.52212381e-01 -9.22726631e-01 4.65998501e-01
-9.08238947e-01 2.43834525e-01 1.58187509e-01 -1.70648366e-01
-5.66904664e-01 2.41945326e-01 2.81863928e-01 -1.56000689e-01
2.02161781e-02 6.89416230e-01 -9.45575477e-04 -2.52700627e-01
6.61465824e-01 2.28405327e-01 -5.23806326e-02 -1.31809682e-01
1.85838044e-01 5.06214321e-01 7.66248405e-02 -6.94258988e-01
8.44409347e-01 3.76441211e-01 3.47941816e-01 -7.06133902e-01
-2.10667625e-01 -7.18147039e-01 -5.26966155e-01 -5.22826374e-01
3.90309006e-01 -6.62515402e-01 -7.21590102e-01 3.59966457e-01
-1.22968197e+00 -2.28685915e-01 3.40480387e-01 2.34285042e-01
-6.66221917e-01 8.65713000e-01 -5.57629585e-01 -1.36301148e+00
-1.08874924e-02 -8.51659536e-01 5.63778222e-01 -1.36542763e-03
-1.65180579e-01 -1.06251752e+00 3.24152976e-01 -6.43724054e-02
1.08750490e-02 5.71754038e-01 8.00849557e-01 -4.47053611e-01
-9.73249376e-01 -3.72240961e-01 -2.13980868e-01 -2.49109253e-01
-2.56742477e-01 7.82835782e-01 -2.85103500e-01 -7.73493707e-01
-5.23899317e-01 3.03456575e-01 3.81650567e-01 6.70273423e-01
6.14833593e-01 -5.65161467e-01 -1.00931454e+00 1.67304620e-01
2.02307892e+00 -3.17261368e-02 8.77955854e-01 1.39336035e-01
1.94338828e-01 4.92069423e-01 3.52478802e-01 5.09067714e-01
1.00213543e-01 5.32625079e-01 4.91486102e-01 2.17464373e-01
4.29155916e-01 -5.49355209e-01 1.91336066e-01 8.63848567e-01
8.09485614e-02 -6.43337846e-01 -1.16671729e+00 9.36048627e-01
-1.97604430e+00 -1.24646509e+00 -8.83054912e-01 2.29560018e+00
7.84459472e-01 3.21431071e-01 4.11418617e-01 1.34911537e-01
1.34251702e+00 -3.33243817e-01 1.01590671e-01 -3.93825918e-01
-1.38555393e-01 -6.69957995e-02 7.86380649e-01 7.53231764e-01
-6.24173105e-01 6.43647730e-01 8.31709957e+00 1.04639661e+00
-1.08833216e-01 -7.81418681e-02 2.50019014e-01 2.93992758e-01
-4.53696221e-01 7.55120099e-01 -6.80287063e-01 2.85126179e-01
1.13030195e+00 -7.58288860e-01 8.26835513e-01 7.78452098e-01
3.71988714e-01 -3.14076573e-01 -9.44210351e-01 7.25033224e-01
-3.95994544e-01 -1.40913367e+00 -1.24642402e-01 7.60717154e-01
1.38078225e+00 -1.21781178e-01 -7.16365457e-01 -1.16140209e-01
1.02905369e+00 -8.66860926e-01 3.70265901e-01 5.54289877e-01
3.80199850e-01 -7.80787051e-01 7.03246951e-01 7.50361919e-01
-1.14897871e+00 -3.51727419e-02 -4.82254505e-01 -1.04595125e-01
3.03581715e-01 9.83927548e-01 -1.57443440e+00 4.40641761e-01
3.02724421e-01 2.48711482e-01 -3.14949900e-01 1.62348032e+00
-4.08477396e-01 7.09791958e-01 -7.09592760e-01 -5.45444787e-01
-1.54500362e-02 -4.96372968e-01 1.07868516e+00 1.17704248e+00
1.71709567e-01 -3.49360794e-01 3.61348301e-01 8.80519032e-01
3.41847651e-02 1.14557885e-01 -7.21270144e-01 -2.80570507e-01
8.67240787e-01 1.08555746e+00 -1.36723030e+00 -1.66126415e-01
1.98944239e-03 6.68872535e-01 3.03395182e-01 3.49138260e-01
-3.89673412e-01 -3.03445458e-01 1.53270885e-01 2.82489270e-01
4.73856866e-01 -4.75881308e-01 4.20808941e-02 -8.26614261e-01
-2.37460479e-01 -1.01313567e+00 4.58599776e-01 -6.34525418e-01
-1.36772847e+00 3.04294646e-01 4.20268595e-01 -8.68261039e-01
-5.78333795e-01 -4.64605153e-01 -7.36882329e-01 6.56070709e-01
-6.16390109e-01 -6.05361342e-01 -4.75651678e-03 3.36955011e-01
-4.03245538e-02 6.53345212e-02 6.74302816e-01 -4.75348532e-02
-3.22321177e-01 1.33590698e-01 4.49004233e-01 2.17313524e-02
1.72163680e-01 -1.48330081e+00 2.94530064e-01 1.14276314e+00
2.20575884e-01 6.53267622e-01 1.37610734e+00 -9.06949699e-01
-1.03629303e+00 -5.70977032e-01 1.10210001e+00 -8.64498317e-02
8.29505563e-01 -4.61550802e-01 -4.55566496e-01 7.24995315e-01
1.87477082e-01 -5.99008024e-01 3.30951750e-01 2.37704039e-01
3.90545465e-02 2.54687071e-01 -1.24243891e+00 7.87912548e-01
1.03931820e+00 -2.80776352e-01 -5.89681603e-02 7.20682025e-01
3.74480367e-01 2.43262231e-01 -7.39154577e-01 1.44192144e-01
7.87884519e-02 -9.81864393e-01 7.00677991e-01 -3.88921380e-01
1.07899800e-01 -5.02194405e-01 -7.77607085e-03 -1.24714959e+00
-4.14241523e-01 -1.16432440e+00 -1.01516984e-01 9.99287367e-01
6.35515690e-01 -5.26738465e-01 1.00088274e+00 1.15933545e-01
7.70519853e-01 -5.10384977e-01 -9.52533782e-01 -8.81712854e-01
-3.37973773e-01 -8.33262801e-02 5.43544710e-01 9.26430762e-01
1.58304527e-01 1.69226006e-01 -3.40704978e-01 2.48014659e-01
1.46162701e+00 7.59680495e-02 9.51864481e-01 -1.49662149e+00
-4.68409091e-01 -3.13195467e-01 -6.34667099e-01 -7.10478365e-01
1.05449699e-01 -8.50723565e-01 7.45092034e-02 -1.87116182e+00
9.17376220e-01 -3.78669143e-01 2.60646790e-01 -1.02829285e-01
-1.48202889e-02 -2.22331449e-01 -4.13437672e-02 1.30639762e-01
-7.76665092e-01 2.53808759e-02 8.71536553e-01 1.24713995e-01
-4.36799042e-02 2.52866983e-01 -3.64544600e-01 5.02893627e-01
7.53374875e-01 -1.08240700e+00 -3.17184955e-01 2.35477522e-01
7.90061235e-01 4.59908664e-01 3.59481096e-01 -6.79227054e-01
6.17264092e-01 -3.55940551e-01 -8.63047540e-02 -8.33069503e-01
-2.79505134e-01 -7.10089564e-01 9.41575885e-01 8.59790862e-01
-2.11030900e-01 1.71745047e-01 -3.89357269e-01 1.13247466e+00
6.67756796e-02 -9.68560338e-01 5.31377256e-01 -2.87115306e-01
-4.30864185e-01 2.18998119e-01 -8.98648024e-01 -1.08268559e-01
1.03369522e+00 -3.04106444e-01 3.88425998e-02 -9.98176455e-01
-9.36183751e-01 4.74721223e-01 7.51857400e-01 -2.19132185e-01
4.89770681e-01 -1.07928693e+00 -1.12555099e+00 -3.17905247e-01
-2.49275491e-01 -4.21534181e-01 -2.32603297e-01 7.84434557e-01
-9.78372693e-01 1.44622251e-01 6.18362650e-02 -6.94433391e-01
-1.52881050e+00 8.30434859e-01 5.21820366e-01 -8.18410754e-01
-9.81363952e-02 5.85316241e-01 -4.37738895e-01 -5.21039665e-01
-1.03352681e-01 5.59407115e-01 2.86819816e-01 -4.21226889e-01
8.16312730e-02 5.23658514e-01 -4.03876066e-01 -3.19496483e-01
-4.02239114e-01 -3.40722427e-02 1.64693624e-01 -5.74501455e-01
1.17832994e+00 -2.73904055e-01 -6.68708384e-01 -2.20240541e-02
8.98357213e-01 2.35150456e-01 -7.83849776e-01 -1.76087946e-01
5.14210761e-01 -6.21308863e-01 -2.35923409e-01 -2.22595006e-01
-7.17367351e-01 3.33971500e-01 1.28365651e-01 9.74751234e-01
6.64350033e-01 2.84199510e-02 -3.30747180e-02 4.51417238e-01
8.08134258e-01 -1.05621910e+00 -2.13253990e-01 1.00157827e-01
6.35703444e-01 -6.59027398e-01 5.12757599e-01 -9.96170521e-01
-1.74666360e-01 1.06286550e+00 1.70923010e-01 -3.32194746e-01
7.01421440e-01 3.07067186e-01 -5.53283632e-01 -3.32301080e-01
-1.07576334e+00 -2.15570435e-01 -1.41794041e-01 9.07370448e-01
2.49104593e-02 3.52296948e-01 -6.66698813e-01 -9.04561654e-02
-2.17842907e-02 -3.27758104e-01 1.07330620e+00 6.50970578e-01
-5.47019422e-01 -1.37283134e+00 -5.45208693e-01 4.47565913e-01
-2.18667969e-01 5.97301908e-02 -8.94745529e-01 7.07051516e-01
-3.09724808e-01 1.38483441e+00 -1.86665073e-01 -2.66151726e-01
-1.55807987e-01 -1.22173414e-01 7.54340589e-01 -5.80156207e-01
-9.48285162e-02 1.99853584e-01 4.47705746e-01 -9.53690559e-02
-3.79861712e-01 -9.00942683e-01 -7.00573385e-01 -1.03515983e+00
-9.74360108e-01 5.96983373e-01 4.26907003e-01 7.23112345e-01
4.72800992e-02 -4.55477983e-02 9.76400614e-01 -6.57112420e-01
-5.75719297e-01 -8.13790262e-01 -8.30980480e-01 1.52767733e-01
-3.04541588e-01 -3.99215937e-01 -7.31289506e-01 -6.85082451e-02] | [6.962234973907471, 5.282273292541504] |
61011d67-a2ce-4e85-8dd0-5da1493f7274 | generating-natural-language-attacks-in-a-hard | 2012.14956 | null | https://arxiv.org/abs/2012.14956v2 | https://arxiv.org/pdf/2012.14956v2.pdf | Generating Natural Language Attacks in a Hard Label Black Box Setting | We study an important and challenging task of attacking natural language processing models in a hard label black box setting. We propose a decision-based attack strategy that crafts high quality adversarial examples on text classification and entailment tasks. Our proposed attack strategy leverages population-based optimization algorithm to craft plausible and semantically similar adversarial examples by observing only the top label predicted by the target model. At each iteration, the optimization procedure allow word replacements that maximizes the overall semantic similarity between the original and the adversarial text. Further, our approach does not rely on using substitute models or any kind of training data. We demonstrate the efficacy of our proposed approach through extensive experimentation and ablation studies on five state-of-the-art target models across seven benchmark datasets. In comparison to attacks proposed in prior literature, we are able to achieve a higher success rate with lower word perturbation percentage that too in a highly restricted setting. | ['Vikram Pudi', 'Saket Maheshwary', 'Rishabh Maheshwary'] | 2020-12-29 | null | null | null | null | ['adversarial-text'] | ['adversarial'] | [ 8.05983007e-01 5.21116614e-01 8.10344368e-02 -2.40324557e-01
-1.05029178e+00 -1.03382754e+00 8.51601362e-01 3.90422702e-01
-6.81198061e-01 6.73082829e-01 1.09444566e-01 -4.22273934e-01
1.77480921e-01 -6.88508749e-01 -8.47032130e-01 -4.02260005e-01
2.65302807e-01 5.49205959e-01 2.76918877e-02 -4.35657382e-01
2.10443810e-01 3.17077994e-01 -8.98796082e-01 2.81171739e-01
7.24268079e-01 6.09146178e-01 -4.40678507e-01 7.56511390e-01
8.05815235e-02 5.33486009e-01 -9.48764920e-01 -1.24869740e+00
6.61119521e-01 -2.90760070e-01 -8.48817945e-01 -3.07541251e-01
6.58738971e-01 -7.76312947e-02 -3.42817336e-01 1.37425768e+00
7.03619659e-01 1.84910148e-01 9.12021458e-01 -1.15892565e+00
-8.07764709e-01 9.86186445e-01 -2.60196149e-01 1.05257437e-01
3.89103442e-01 4.98672068e-01 1.17282701e+00 -6.25537157e-01
4.68191236e-01 1.53139508e+00 5.86669803e-01 1.06062186e+00
-1.51653695e+00 -9.08111334e-01 2.55357981e-01 -9.34846550e-02
-1.20748639e+00 -4.15412009e-01 6.03639722e-01 -4.69492525e-02
9.65838611e-01 3.35114747e-01 5.61650097e-02 1.76393163e+00
2.47728437e-01 6.70581758e-01 9.57584262e-01 -6.51195049e-01
4.35648352e-01 2.24848270e-01 -1.20608127e-02 6.70819819e-01
3.43880177e-01 2.51804918e-01 -2.64630914e-01 -6.74552739e-01
-1.67632386e-01 -2.53143758e-01 -1.15230583e-01 -8.36468264e-02
-9.11768377e-01 1.20878160e+00 3.02369058e-01 1.63212806e-01
-2.61827558e-01 4.60818291e-01 4.30991232e-01 3.46384943e-01
6.48137927e-01 1.07937777e+00 -4.86494035e-01 1.67792767e-01
-7.89916515e-01 5.30058742e-01 9.62616801e-01 7.77933240e-01
1.42433688e-01 1.65561691e-01 -5.71176291e-01 4.52557921e-01
2.12660104e-01 6.90883756e-01 3.63363773e-01 -5.34814596e-01
6.11323118e-01 1.60027593e-01 -1.45487406e-03 -8.35352361e-01
-1.28958285e-01 -3.68862152e-01 -4.87043738e-01 2.40304604e-01
5.99185348e-01 -3.86167496e-01 -9.73231673e-01 2.06216860e+00
3.39867592e-01 3.86211216e-01 3.60903144e-01 5.39422393e-01
2.17117205e-01 4.81209695e-01 5.76247156e-01 5.24053397e-03
1.44170308e+00 -9.24929380e-01 -6.02543175e-01 -5.96464634e-01
7.92094886e-01 -6.72615469e-01 1.37320805e+00 4.93895918e-01
-9.64799762e-01 1.53223407e-02 -1.27430642e+00 1.33627445e-01
-4.93781537e-01 -4.04795110e-01 4.82940257e-01 1.25964952e+00
-4.67369169e-01 5.12491703e-01 -4.85326469e-01 -1.37807205e-01
5.43033481e-01 2.76732743e-01 -2.04070017e-01 -9.23443437e-02
-1.66536033e+00 1.06848848e+00 4.76990193e-01 -3.54275644e-01
-1.15046382e+00 -9.68729496e-01 -8.43363583e-01 5.89917302e-02
5.77812016e-01 -8.75501752e-01 1.25332391e+00 -1.11001074e+00
-1.58006454e+00 8.50312114e-01 1.30745903e-01 -1.00683522e+00
7.93389440e-01 -4.39304680e-01 -3.09110790e-01 1.22429733e-03
-2.81611055e-01 4.68051553e-01 1.33039474e+00 -1.26107776e+00
-2.01443091e-01 -1.04714058e-01 2.62367874e-01 7.45031908e-02
-5.97877741e-01 1.15875714e-01 1.29735500e-01 -1.26581025e+00
-6.20652080e-01 -1.01163578e+00 -4.50568199e-01 -1.42111272e-01
-7.68070340e-01 -5.20651527e-02 5.93601763e-01 -4.21999454e-01
1.09279406e+00 -2.01011586e+00 2.71362305e-01 3.68445247e-01
1.89406410e-01 6.74400687e-01 -2.68068403e-01 4.04029071e-01
-1.79657474e-01 5.96856296e-01 -6.85342908e-01 -5.88902891e-01
4.74090785e-01 -8.88623595e-02 -1.01496243e+00 4.49299544e-01
3.70689809e-01 9.94073987e-01 -9.19872224e-01 -2.79549718e-01
-7.03279153e-02 2.67593384e-01 -7.92314410e-01 2.30672330e-01
-6.89761937e-01 1.03048533e-01 -3.93776119e-01 2.83566862e-01
5.06579399e-01 1.74836680e-01 1.54236695e-02 -4.31801490e-02
8.03928852e-01 2.77832389e-01 -9.69998598e-01 1.61109483e+00
-6.53579056e-01 2.72068113e-01 -1.98092267e-01 -9.31784749e-01
6.17047369e-01 3.20234746e-01 -2.22403184e-01 -2.77455837e-01
3.57340276e-01 2.31062504e-03 -7.32850563e-03 -3.06131870e-01
3.00621927e-01 -5.13574362e-01 -5.20491540e-01 7.80714869e-01
6.97660074e-02 -3.62936199e-01 -1.36311010e-01 3.67435485e-01
1.32524407e+00 -1.22008458e-01 3.44864637e-01 -1.65724605e-01
6.03940845e-01 -1.02163479e-01 2.08725914e-01 1.23955250e+00
-2.23975718e-01 2.68363774e-01 5.34570098e-01 -2.66117096e-01
-1.03865457e+00 -1.10405874e+00 4.41917516e-02 1.25184405e+00
-6.82364628e-02 -4.34051514e-01 -9.84777570e-01 -1.34498262e+00
9.79130417e-02 1.44069874e+00 -7.99587786e-01 -7.58049726e-01
-4.90314811e-01 -7.76735187e-01 1.47955787e+00 4.51605693e-02
1.14088960e-01 -1.12879026e+00 -2.78442800e-01 -3.38100195e-02
1.33277312e-01 -1.20157158e+00 -6.79017484e-01 1.42531931e-01
-4.35193777e-01 -8.28782141e-01 -3.47742468e-01 -5.95826924e-01
6.80404842e-01 -4.18018788e-01 1.06821835e+00 -4.54147607e-02
-2.00561404e-01 1.49184600e-01 -3.48946124e-01 -6.59398973e-01
-1.00474203e+00 2.35421136e-01 1.32468298e-01 6.46792725e-02
3.39282572e-01 -3.52882802e-01 -2.28641391e-01 -7.04100654e-02
-1.26581979e+00 -3.98451030e-01 4.43360686e-01 8.96535218e-01
1.99422300e-01 8.83513391e-02 7.39353299e-01 -1.45484853e+00
1.03772438e+00 -5.92164218e-01 -5.10872304e-01 3.78450960e-01
-6.14780784e-01 5.17204642e-01 1.19962263e+00 -8.00459146e-01
-8.63268435e-01 -3.36852595e-02 -1.57491177e-01 -3.58561814e-01
-2.70551860e-01 1.70183361e-01 -3.18030626e-01 -1.65138226e-02
1.17601633e+00 2.02878658e-02 -3.33854437e-01 -1.46710813e-01
7.96976388e-01 4.58556235e-01 4.93492961e-01 -8.34969461e-01
1.39413810e+00 2.82097727e-01 -2.34459937e-02 -2.77538061e-01
-9.47167516e-01 2.56282806e-01 -2.13149861e-01 2.58540481e-01
7.87186325e-01 -4.40969855e-01 -7.20626354e-01 3.50707680e-01
-1.22488976e+00 -2.89505035e-01 -3.49388033e-01 1.22725680e-01
-3.58965963e-01 5.46127677e-01 -4.74594533e-01 -8.79400134e-01
-7.08222151e-01 -1.01852381e+00 1.01659608e+00 -2.48448908e-01
-4.85892594e-01 -1.17325544e+00 1.05865806e-01 3.27439427e-01
3.33902717e-01 4.11280304e-01 1.21972191e+00 -1.57329071e+00
-8.48065466e-02 -5.82715988e-01 2.62743145e-01 3.27261418e-01
-7.34313950e-02 -1.78610563e-01 -1.06748629e+00 -3.66522402e-01
7.63122141e-02 -7.99467206e-01 8.04713249e-01 -2.83433825e-01
1.02925074e+00 -6.95057273e-01 -1.07205011e-01 5.22266567e-01
1.22585595e+00 -1.94687709e-01 4.61289674e-01 3.33727628e-01
6.85403705e-01 6.41575038e-01 5.37917018e-01 2.87643939e-01
-2.03957751e-01 6.08925939e-01 5.23106813e-01 1.22561231e-01
2.22874179e-01 -4.26544547e-01 5.81277072e-01 -2.59175580e-02
7.73773551e-01 -7.22952247e-01 -9.25045848e-01 3.75766635e-01
-1.59232485e+00 -1.01040614e+00 3.96091253e-01 2.11064124e+00
1.18933284e+00 6.54021740e-01 -6.46852553e-02 9.01856050e-02
7.35579789e-01 1.76594034e-01 -6.61681116e-01 -7.91017771e-01
4.54797409e-03 7.68848479e-01 6.46722376e-01 7.74755359e-01
-1.33679628e+00 1.40548873e+00 6.29660416e+00 1.18644643e+00
-7.81060100e-01 1.92419931e-01 5.37350953e-01 -4.59599048e-01
-5.60464501e-01 -1.51727289e-01 -7.38481939e-01 3.30332220e-01
1.16655207e+00 -3.96891266e-01 6.44319415e-01 7.18233645e-01
-1.27987608e-01 3.93937975e-01 -1.27129650e+00 5.08552730e-01
2.05384284e-01 -1.08291852e+00 4.25124466e-01 -1.75871074e-01
5.57195783e-01 -3.84560704e-01 4.21576709e-01 3.54228318e-01
9.28852201e-01 -1.38840449e+00 8.00356448e-01 1.00488536e-01
6.27557397e-01 -1.02276862e+00 5.66078246e-01 3.80847245e-01
-4.29679453e-01 -1.09881975e-01 -1.10487252e-01 1.48247689e-01
1.09662570e-01 3.38847727e-01 -9.74157512e-01 2.86066413e-01
1.32690683e-01 2.06567615e-01 -6.95729494e-01 3.35236877e-01
-5.99256217e-01 9.10694003e-01 -3.39167923e-01 -1.56077415e-01
3.95732999e-01 3.71305406e-01 8.19924474e-01 1.40860713e+00
-2.64536917e-01 -3.27410735e-02 7.88994059e-02 8.61489356e-01
-4.76993978e-01 1.86755255e-01 -8.41720402e-01 -1.15357772e-01
6.50203764e-01 1.14556277e+00 -3.98551434e-01 -2.90990025e-01
-1.13218846e-02 1.08891380e+00 4.52782661e-01 2.26165190e-01
-1.07473850e+00 -5.99871874e-01 7.38800049e-01 -2.86268741e-01
1.64356530e-01 1.13806531e-01 -4.33877975e-01 -1.10055363e+00
-6.02294244e-02 -1.42219496e+00 6.51718497e-01 -4.03152287e-01
-1.71258926e+00 8.09589684e-01 7.11894706e-02 -7.02885449e-01
-3.74670088e-01 -5.53509116e-01 -7.25248456e-01 1.00100541e+00
-1.15959871e+00 -1.09352100e+00 3.89981747e-01 6.59326851e-01
5.22721171e-01 -4.29677933e-01 1.17440617e+00 -5.82305528e-02
-6.17054403e-01 1.39986539e+00 -7.31689930e-02 8.91714394e-02
8.49011183e-01 -1.31315613e+00 9.35617268e-01 1.23922157e+00
2.33056217e-01 6.61683202e-01 1.13333690e+00 -6.97859585e-01
-1.01277232e+00 -1.28065765e+00 6.28716946e-01 -7.86218464e-01
8.83856058e-01 -8.33058238e-01 -8.65637183e-01 6.29406929e-01
2.04269528e-01 -1.54631242e-01 8.28900874e-01 -2.29485810e-01
-8.19559991e-01 3.72325808e-01 -1.71639419e+00 1.09588695e+00
9.10564482e-01 -6.69260919e-01 -8.34419012e-01 5.81641793e-01
1.18403614e+00 -2.87968755e-01 -5.06844461e-01 1.78536281e-01
2.36194655e-01 -2.12152332e-01 1.06935155e+00 -1.37172270e+00
5.19868910e-01 3.07039134e-02 -2.79453963e-01 -1.50849128e+00
5.75483497e-03 -1.05755448e+00 -1.98593721e-01 1.19149828e+00
6.99550152e-01 -8.03461075e-01 6.50489986e-01 8.00457299e-01
1.02445975e-01 -5.57295382e-01 -1.00206161e+00 -7.12542474e-01
6.80076599e-01 -5.54922223e-01 4.78577763e-01 9.31792200e-01
-4.67692129e-02 4.08685178e-01 -4.80060011e-01 4.16666090e-01
7.82197177e-01 -4.90242332e-01 6.49122536e-01 -7.07734883e-01
-6.24317825e-01 -3.09504896e-01 -2.97820956e-01 -3.31062824e-01
9.14240539e-01 -1.15344834e+00 2.09429208e-02 -8.35302889e-01
-1.65051013e-01 -1.73722833e-01 -1.30793810e-01 6.29021823e-01
-6.45840168e-01 4.20488507e-01 3.05315197e-01 -1.58153623e-01
-3.73560846e-01 5.27200699e-01 7.93522358e-01 -3.70903432e-01
1.16756953e-01 -1.01527922e-01 -9.95302260e-01 7.53250062e-01
9.63095367e-01 -1.10475266e+00 -5.37377715e-01 -3.24617177e-01
3.45245779e-01 -5.07657349e-01 3.88335109e-01 -7.02259183e-01
-9.63579956e-03 -1.52018011e-01 4.87596635e-03 3.15960705e-01
2.16011658e-01 -8.17877591e-01 -2.30521604e-01 6.46869063e-01
-1.08849835e+00 5.81292668e-04 3.93583655e-01 9.16871667e-01
3.41330707e-01 -6.24246359e-01 1.02276075e+00 4.85832989e-02
-1.18587926e-01 1.53987274e-01 -4.06418085e-01 5.67745626e-01
1.21546495e+00 3.88885170e-01 -4.33636248e-01 -3.87339979e-01
-6.77112222e-01 3.15392651e-02 3.32945377e-01 5.69344044e-01
4.35529947e-01 -1.08671200e+00 -1.00469577e+00 7.94110969e-02
2.31369033e-01 -3.95535856e-01 -2.77983934e-01 7.48821422e-02
-4.42016184e-01 1.96476147e-01 1.77348495e-01 -1.51353180e-02
-1.10746300e+00 1.01799679e+00 4.72336322e-01 -6.84362769e-01
-3.77632231e-01 8.15978646e-01 1.76805109e-01 -5.59994698e-01
2.83006161e-01 1.18045479e-01 1.20913588e-01 -2.67478943e-01
5.37174761e-01 7.54581541e-02 1.72325522e-01 -3.95530611e-01
-4.08058614e-01 6.63220510e-03 -4.30344403e-01 -5.00398815e-01
9.57655728e-01 2.56909400e-01 2.98099816e-01 -7.17316717e-02
1.18475807e+00 3.41189325e-01 -9.25169885e-01 -3.64343077e-01
1.12499692e-01 -4.38835710e-01 -8.64179805e-02 -1.02933037e+00
-7.38747716e-01 7.50491560e-01 4.04005319e-01 2.53895640e-01
9.12454009e-01 -2.03343675e-01 9.16413248e-01 6.52318120e-01
1.38934879e-02 -7.01148748e-01 2.36877382e-01 4.87958163e-01
7.78068602e-01 -9.42751169e-01 -1.32755592e-01 -3.58982712e-01
-8.73316586e-01 6.73188388e-01 5.36991477e-01 -3.49565923e-01
4.36704725e-01 3.33134204e-01 1.11725472e-01 7.66417310e-02
-8.70735765e-01 1.06181338e-01 2.20942378e-01 6.44188464e-01
1.50633961e-01 -1.38188124e-01 -1.32116631e-01 7.33711064e-01
-3.57431054e-01 -5.87159336e-01 3.42677206e-01 8.32072437e-01
-1.98834121e-01 -1.35804963e+00 -4.04960752e-01 2.59769052e-01
-1.11389279e+00 -7.00372517e-01 -7.28073478e-01 5.17179370e-01
-2.79938519e-01 1.12697899e+00 -3.45728606e-01 -4.59741980e-01
4.31138307e-01 3.93877178e-01 4.53580618e-01 -7.88712382e-01
-1.19681871e+00 -4.72113013e-01 2.99334913e-01 -3.41081172e-01
1.13038339e-01 -4.02270257e-01 -1.03618729e+00 -4.14290547e-01
-3.14655960e-01 1.33379444e-01 5.51399648e-01 1.13597953e+00
3.28523397e-01 4.19991702e-01 6.51821315e-01 -5.74660540e-01
-1.25734246e+00 -9.30559278e-01 -1.55376717e-01 8.45048487e-01
2.19915077e-01 -3.84922475e-01 -5.79272032e-01 5.62405214e-03] | [6.0221147537231445, 8.108580589294434] |
56a04e2c-8348-49aa-8dd3-adb446c449fa | leaping-into-memories-space-time-deep-feature | 2303.09941 | null | https://arxiv.org/abs/2303.09941v3 | https://arxiv.org/pdf/2303.09941v3.pdf | Leaping Into Memories: Space-Time Deep Feature Synthesis | The success of deep learning models has led to their adaptation and adoption by prominent video understanding methods. The majority of these approaches encode features in a joint space-time modality for which the inner workings and learned representations are difficult to visually interpret. We propose LEArned Preconscious Synthesis (LEAPS), an architecture-agnostic method for synthesizing videos from the internal spatiotemporal representations of models. Using a stimulus video and a target class, we prime a fixed space-time model and iteratively optimize a video initialized with random noise. We incorporate additional regularizers to improve the feature diversity of the synthesized videos as well as the cross-frame temporal coherence of motions. We quantitatively and qualitatively evaluate the applicability of LEAPS by inverting a range of spatiotemporal convolutional and attention-based architectures trained on Kinetics-400, which to the best of our knowledge has not been previously accomplished. | ['Nikos Deligiannis', 'Alexandros Stergiou'] | 2023-03-17 | null | null | null | null | ['video-understanding'] | ['computer-vision'] | [ 1.80816412e-01 -3.95451374e-02 -1.67822354e-02 -3.92492056e-01
-3.29217911e-01 -8.59992921e-01 9.61264670e-01 -3.39812189e-01
-1.69630930e-01 5.34852922e-01 6.44000411e-01 -2.96501704e-02
3.30031663e-02 -3.81478310e-01 -1.12005830e+00 -5.57840586e-01
-8.22681189e-02 -4.42085229e-02 1.05746932e-01 -8.09979811e-02
1.81180835e-01 4.41569597e-01 -1.53260434e+00 7.69110441e-01
4.68234420e-01 8.30717683e-01 2.44931623e-01 1.00962269e+00
2.39943758e-01 1.00442362e+00 -3.53176117e-01 -1.26091242e-01
2.22513556e-01 -8.35188270e-01 -8.13227773e-01 3.14795613e-01
6.54255867e-01 -4.43392247e-01 -1.09787619e+00 5.63972890e-01
7.31257647e-02 4.23029512e-01 5.67327023e-01 -1.14542532e+00
-1.01877320e+00 3.80287558e-01 -1.22554138e-01 6.22105122e-01
4.08145398e-01 8.28030646e-01 9.86569583e-01 -6.97137773e-01
9.69436288e-01 1.26712346e+00 4.10411716e-01 6.83667958e-01
-1.54903245e+00 -3.20851296e-01 3.98425430e-01 4.43380475e-01
-1.13563263e+00 -6.32253230e-01 7.21977890e-01 -5.89692891e-01
1.30944943e+00 7.60702565e-02 1.03069448e+00 1.57857966e+00
3.53776604e-01 6.22348189e-01 8.37200403e-01 -1.49978355e-01
2.74242520e-01 -3.93985868e-01 -3.88641000e-01 7.87607074e-01
-2.87209321e-02 3.18813384e-01 -7.42262244e-01 3.02959234e-01
1.13147521e+00 -6.42896891e-02 -3.78327727e-01 -6.47221923e-01
-1.59582746e+00 5.79764843e-01 5.10219038e-01 2.81178534e-01
-3.48707169e-01 7.20427275e-01 3.18654120e-01 3.17764819e-01
1.23222679e-01 6.56853557e-01 -4.34267849e-01 -2.09175125e-01
-8.77679646e-01 2.83231825e-01 5.38202584e-01 7.96248257e-01
5.07706463e-01 4.79150474e-01 -4.24908221e-01 1.02838442e-01
8.28180090e-02 1.87295571e-01 6.38525367e-01 -1.47725201e+00
2.54663229e-01 3.67886305e-01 2.87446082e-01 -1.04011738e+00
-2.92884678e-01 -2.98185825e-01 -5.48136771e-01 2.11217731e-01
5.33682704e-01 4.57004532e-02 -1.07298326e+00 2.00637627e+00
-1.12472385e-01 6.30280137e-01 1.08463563e-01 1.12134790e+00
5.25229573e-01 7.74338901e-01 2.44103134e-01 -1.69465749e-03
7.88346112e-01 -9.80525970e-01 -5.88389874e-01 -2.13165283e-01
4.64735121e-01 -4.19069201e-01 1.14037776e+00 2.06249624e-01
-1.27432430e+00 -6.67737961e-01 -1.03976083e+00 -3.40609342e-01
-2.61278272e-01 1.57182544e-01 5.39436400e-01 1.04368657e-01
-1.21631444e+00 9.35592234e-01 -1.27177811e+00 -4.15938556e-01
5.99854887e-01 3.62599224e-01 -6.11922979e-01 2.56913632e-01
-9.13160384e-01 8.14769626e-01 2.57693142e-01 3.15385405e-03
-1.35537863e+00 -7.37173617e-01 -8.91591966e-01 1.53681725e-01
2.87991464e-01 -1.02858901e+00 1.24485540e+00 -1.54528880e+00
-1.66919255e+00 7.91693985e-01 -2.98322022e-01 -5.41420221e-01
3.40441018e-01 -2.81937897e-01 -2.46147916e-01 3.75175744e-01
-7.61226192e-02 9.39751506e-01 1.04990900e+00 -1.03036606e+00
-1.76558003e-01 -1.45313293e-02 2.75339752e-01 2.10652113e-01
2.04627402e-02 -2.67949104e-01 -3.99993360e-01 -9.64433610e-01
-7.88125843e-02 -9.27011907e-01 -1.61549047e-01 2.38758385e-01
-1.08954944e-01 2.47496948e-01 7.44399965e-01 -7.15229511e-01
1.03471839e+00 -2.24625945e+00 7.86490500e-01 -1.87963739e-01
2.78612286e-01 1.45803466e-01 -4.94968861e-01 5.46663523e-01
-3.78545880e-01 1.46274999e-01 -8.04911256e-02 -2.13720873e-01
-8.72337669e-02 3.33252430e-01 -5.48598349e-01 5.30521333e-01
6.27387524e-01 1.28985226e+00 -1.07783055e+00 -4.83381152e-02
3.33994567e-01 7.85538137e-01 -8.84453475e-01 4.49703723e-01
-6.99186921e-01 8.75222504e-01 -3.54041904e-01 2.09606752e-01
-3.55755761e-02 -5.51545382e-01 2.55892456e-01 -5.71764588e-01
-1.99332580e-01 4.19719934e-01 -6.70619667e-01 2.13081288e+00
-2.54262865e-01 9.59413528e-01 -2.87731141e-01 -1.04316211e+00
3.30522627e-01 3.92062783e-01 4.81735140e-01 -7.78789759e-01
3.54502387e-02 -1.09809004e-01 1.76073417e-01 -7.77716160e-01
2.44021744e-01 -6.74735233e-02 2.44577065e-01 4.11451846e-01
4.88035202e-01 4.96019907e-02 1.79696441e-01 3.63842875e-01
1.19590974e+00 8.26595128e-01 1.84561893e-01 -1.41025439e-01
1.28133386e-01 -1.77766122e-02 2.70712256e-01 6.12801015e-01
-1.70522034e-01 8.94957602e-01 6.09225273e-01 -7.27452934e-01
-1.43035781e+00 -1.21342516e+00 5.03781021e-01 1.08931780e+00
-1.55795831e-02 -5.85021555e-01 -7.22650051e-01 -4.90775049e-01
-1.42938063e-01 5.88054299e-01 -9.99895453e-01 -4.55792755e-01
-7.45467007e-01 -1.26709744e-01 2.88585633e-01 6.95999742e-01
2.20462248e-01 -1.09187722e+00 -8.99072945e-01 3.61474216e-01
-3.21088135e-02 -1.18819177e+00 -4.88578200e-01 1.09493755e-01
-8.21801066e-01 -9.85234916e-01 -6.07550383e-01 -4.73308802e-01
6.05390429e-01 1.27812937e-01 1.21175647e+00 -1.60573032e-02
-3.62175167e-01 6.36103332e-01 -1.97661728e-01 2.52480894e-01
-2.78869152e-01 -1.97140366e-01 2.63080969e-02 2.65952706e-01
5.86291403e-02 -8.24515224e-01 -7.82570899e-01 5.05198017e-02
-9.81013596e-01 4.88133252e-01 3.94139439e-01 8.62467468e-01
4.34667975e-01 -5.02555907e-01 2.63693243e-01 -5.12790143e-01
2.33245328e-01 -4.43505198e-01 -3.97075117e-01 9.40150917e-02
-3.55992913e-02 4.23909307e-01 7.30768979e-01 -6.60690725e-01
-9.33439791e-01 2.05195099e-01 2.58847743e-01 -9.44723785e-01
-2.37198025e-01 3.91941428e-01 -5.90392668e-03 1.92134380e-02
6.34631634e-01 3.32349777e-01 7.45930010e-03 -2.64049560e-01
7.89372146e-01 -1.32432953e-01 7.37415969e-01 -5.71339309e-01
5.33254325e-01 6.25459790e-01 -4.96988669e-02 -6.53087795e-01
-8.30302477e-01 -5.86855412e-02 -8.49468112e-01 -2.13505462e-01
1.09329343e+00 -9.74340320e-01 -6.05876923e-01 3.09581518e-01
-1.21296847e+00 -7.81724930e-01 -4.07619119e-01 4.53173816e-01
-1.05039954e+00 1.74883768e-01 -6.15496993e-01 -2.71595359e-01
3.33573133e-01 -1.17485905e+00 9.79047179e-01 9.91133675e-02
-5.76681674e-01 -9.00943696e-01 1.74849629e-01 -4.35971059e-02
3.81372124e-01 4.35504138e-01 7.68274605e-01 -1.98593706e-01
-9.94292080e-01 2.17961073e-01 -1.34430498e-01 -7.38579594e-03
3.68171036e-02 3.17079991e-01 -8.93192112e-01 -2.26646528e-01
-3.05529684e-01 -4.12122875e-01 1.05698407e+00 5.14427483e-01
1.34327531e+00 -4.98640835e-01 -2.42611259e-01 9.45117652e-01
1.20273125e+00 1.94147468e-01 6.38299644e-01 2.17158437e-01
8.15130115e-01 5.12062490e-01 -5.08060446e-04 3.93298030e-01
2.35355943e-01 6.23681962e-01 4.23412293e-01 9.48750228e-02
-3.59538853e-01 -3.60781550e-01 4.66803342e-01 6.50273025e-01
-3.07537735e-01 -2.89115638e-01 -6.75728381e-01 6.92439139e-01
-1.93627918e+00 -1.38958442e+00 4.95511204e-01 1.77992451e+00
7.29891956e-01 4.48662904e-05 6.96892962e-02 -1.78252518e-01
3.00025284e-01 4.42866772e-01 -7.49360263e-01 -2.26349533e-01
-2.01660335e-01 2.18410388e-01 1.61769420e-01 3.79379004e-01
-1.07741117e+00 1.05132842e+00 6.60223150e+00 1.80358037e-01
-1.42043233e+00 -5.48046120e-02 6.13080084e-01 -4.53514129e-01
-3.79176199e-01 1.34094030e-01 -2.06960276e-01 4.69917178e-01
1.06124949e+00 -1.64680198e-01 7.71144032e-01 4.97010887e-01
4.43083793e-01 2.41755694e-01 -1.53892994e+00 9.54355478e-01
2.47791130e-02 -1.85439825e+00 2.78038770e-01 -1.58376947e-01
8.18338513e-01 -2.22969912e-02 3.66056114e-01 2.52108991e-01
2.31244817e-01 -1.40137124e+00 1.09850430e+00 8.81523967e-01
7.01951385e-01 -2.39093542e-01 -1.55520057e-02 -6.04720190e-02
-1.09711826e+00 -1.47349045e-01 -4.25423831e-02 -1.87017277e-01
2.30670631e-01 -2.47811779e-01 -2.22320497e-01 1.48375779e-01
6.03113592e-01 1.21461833e+00 -5.09032428e-01 8.30403507e-01
-1.00335084e-01 6.16978765e-01 -9.92132872e-02 2.99002737e-01
4.91602361e-01 -1.09032072e-01 5.00525057e-01 1.24071372e+00
2.44018257e-01 2.60660082e-01 6.10598130e-04 1.06704807e+00
-1.54677674e-01 -3.55610430e-01 -7.15604901e-01 -6.62400424e-01
6.68054745e-02 9.15422559e-01 -5.74663162e-01 -4.44607586e-01
-5.71338236e-01 1.20134640e+00 4.83139604e-01 8.99711668e-01
-8.75001550e-01 1.68052688e-01 8.92262459e-01 2.45039523e-01
6.52281404e-01 -6.43295705e-01 -8.17541853e-02 -1.48017704e+00
-8.18606019e-02 -8.63661230e-01 1.66570485e-01 -1.07507932e+00
-9.69346404e-01 5.16442180e-01 6.29270971e-02 -1.10779214e+00
-4.55039322e-01 -6.61696911e-01 -6.76953971e-01 4.98935103e-01
-1.00819802e+00 -1.14124453e+00 -3.01033974e-01 5.97803056e-01
7.46432424e-01 -1.84707627e-01 6.87727153e-01 -9.53374133e-02
-4.89993274e-01 1.75600559e-01 -3.17916162e-02 -1.33755818e-01
3.70716393e-01 -1.08277905e+00 6.70028329e-01 8.40085804e-01
2.98917204e-01 7.12595522e-01 9.31870997e-01 -4.36497837e-01
-1.61768079e+00 -1.11130917e+00 5.18330336e-01 -5.64630449e-01
8.55592191e-01 -4.30953801e-01 -9.43813980e-01 1.12366128e+00
4.95358288e-01 2.87786782e-01 4.55817521e-01 -4.08828527e-01
-6.92267299e-01 9.16369334e-02 -6.09315515e-01 9.85935390e-01
1.22235453e+00 -8.55268657e-01 -6.17186427e-01 1.67428449e-01
7.11223304e-01 -3.93618524e-01 -6.33391619e-01 2.26417884e-01
7.95722127e-01 -1.07667291e+00 1.10740757e+00 -1.15244055e+00
6.88420832e-01 -3.64818037e-01 -1.87447026e-01 -1.35471630e+00
-6.02519989e-01 -7.26874888e-01 -4.50414568e-01 6.82471395e-01
1.43772036e-01 -1.08387016e-01 6.23515904e-01 5.93053579e-01
-2.95101613e-01 -6.15186751e-01 -6.77359223e-01 -5.78252971e-01
-1.74238123e-02 -2.09578767e-01 3.91118020e-01 8.24106038e-01
6.49544876e-04 2.57605880e-01 -4.46291894e-01 -3.31017352e-03
2.18115911e-01 2.23114103e-01 6.18974805e-01 -5.77561498e-01
-5.65163136e-01 -5.23572624e-01 -5.61268508e-01 -1.06437063e+00
2.86920547e-01 -6.70760334e-01 -1.34729043e-01 -1.37910426e+00
9.63920131e-02 2.07881838e-01 -2.97219485e-01 4.94163305e-01
8.64655748e-02 3.29589456e-01 2.44119242e-01 2.39758953e-01
-7.05541611e-01 7.87059247e-01 1.34001660e+00 -6.51471168e-02
-8.74960795e-02 -6.30869031e-01 -4.01363701e-01 5.56204677e-01
7.80853689e-01 -1.82497159e-01 -6.56687915e-01 -7.54614770e-01
2.33008623e-01 1.19603008e-01 8.36338222e-01 -1.02731800e+00
-5.11579774e-02 -4.22670454e-01 6.87387407e-01 -9.37978551e-02
6.24246240e-01 -4.48711276e-01 4.49970961e-01 4.02047634e-01
-7.21314371e-01 2.79106021e-01 2.41569296e-01 8.70768368e-01
-1.40937582e-01 3.89079452e-01 7.54861176e-01 -4.15875345e-01
-9.21553791e-01 3.03577036e-01 -4.82159346e-01 -6.57317787e-02
9.95134473e-01 -3.72552723e-01 -3.36582422e-01 -5.04853427e-01
-1.02969944e+00 -1.99579120e-01 7.21833885e-01 5.15867651e-01
6.56405151e-01 -1.29106212e+00 -4.57301289e-01 3.30066353e-01
5.66365756e-02 -4.82715011e-01 3.13745946e-01 7.73525417e-01
-7.02441394e-01 5.19573927e-01 -6.49682164e-01 -6.32912934e-01
-6.65049553e-01 8.54726315e-01 4.73706484e-01 2.17037663e-01
-7.83376634e-01 6.29769266e-01 6.90472543e-01 1.79420978e-01
6.96418136e-02 -5.46813548e-01 -1.04560785e-01 -4.14926976e-01
5.00102520e-01 -9.34199616e-03 -3.75525296e-01 -8.76552224e-01
-2.00792149e-01 4.36749429e-01 1.31412581e-01 -2.74595231e-01
1.27604270e+00 -1.91253573e-01 2.22238183e-01 5.68301260e-01
1.18526649e+00 -3.83003205e-01 -2.05330420e+00 1.31871909e-01
-1.62119001e-01 -4.97466683e-01 -1.11000255e-01 -6.63412154e-01
-1.04922795e+00 9.79586601e-01 3.62679750e-01 -6.14686981e-02
9.09423113e-01 -8.96749869e-02 4.90983099e-01 2.49418512e-01
3.65111344e-02 -7.53438473e-01 6.04241669e-01 4.86805409e-01
1.09618425e+00 -1.04334390e+00 -2.82736927e-01 2.85457447e-02
-6.67051136e-01 1.13265264e+00 6.75445318e-01 -5.26719093e-01
4.39043045e-01 1.18496090e-01 -2.24843964e-01 -1.36643246e-01
-1.25585115e+00 -2.36363828e-01 4.42219853e-01 6.38986111e-01
5.74384034e-01 -2.37312868e-01 -2.04164796e-02 3.83623570e-01
1.21543042e-01 2.06669047e-01 4.44511056e-01 8.10968876e-01
-1.88635409e-01 -7.52713442e-01 1.74981490e-01 2.25760177e-01
-3.44113648e-01 -2.24615913e-03 -2.41543978e-01 6.34163022e-01
6.02736287e-02 5.31405866e-01 2.33857557e-01 -3.27887654e-01
5.93987703e-02 1.84647128e-01 8.44804168e-01 -5.02699554e-01
-4.64724332e-01 8.56976509e-02 -3.23478803e-02 -1.09667969e+00
-6.28752530e-01 -5.98588645e-01 -1.19350672e+00 -1.31246164e-01
3.74226213e-01 -2.95876145e-01 2.92159438e-01 9.15112317e-01
6.96942508e-01 6.43490970e-01 1.63489163e-01 -1.26753294e+00
-2.29282707e-01 -6.22612894e-01 -1.63913727e-01 7.65637577e-01
6.18582487e-01 -7.65255988e-01 -1.68953061e-01 7.40690053e-01] | [8.699512481689453, 0.3707480728626251] |
7a491eb4-becf-4fd0-a43e-a9ed1d7d2860 | conditional-diffusion-models-for-weakly | 2306.03878 | null | https://arxiv.org/abs/2306.03878v1 | https://arxiv.org/pdf/2306.03878v1.pdf | Conditional Diffusion Models for Weakly Supervised Medical Image Segmentation | Recent advances in denoising diffusion probabilistic models have shown great success in image synthesis tasks. While there are already works exploring the potential of this powerful tool in image semantic segmentation, its application in weakly supervised semantic segmentation (WSSS) remains relatively under-explored. Observing that conditional diffusion models (CDM) is capable of generating images subject to specific distributions, in this work, we utilize category-aware semantic information underlied in CDM to get the prediction mask of the target object with only image-level annotations. More specifically, we locate the desired class by approximating the derivative of the output of CDM w.r.t the input condition. Our method is different from previous diffusion model methods with guidance from an external classifier, which accumulates noises in the background during the reconstruction process. Our method outperforms state-of-the-art CAM and diffusion model methods on two public medical image segmentation datasets, which demonstrates that CDM is a promising tool in WSSS. Also, experiment shows our method is more time-efficient than existing diffusion model methods, making it practical for wider applications. | ['Yiyu Shi', 'Tsung-Yi Ho', 'Yu-Jen Chen', 'Xinrong Hu'] | 2023-06-06 | null | null | null | null | ['weakly-supervised-semantic-segmentation'] | ['computer-vision'] | [ 6.25470817e-01 4.76945609e-01 -1.94179937e-01 -3.42366070e-01
-8.18580449e-01 -2.80064881e-01 6.07813835e-01 2.74657793e-02
-4.81899768e-01 3.02293569e-01 5.83084933e-02 -1.40914202e-01
1.23308368e-01 -9.22883570e-01 -5.77111721e-01 -1.10165298e+00
4.12952363e-01 6.99306905e-01 9.12214935e-01 9.69625264e-02
2.64416367e-01 2.95928180e-01 -1.25325453e+00 4.96265948e-01
9.63925004e-01 9.33245003e-01 6.97056830e-01 5.90698481e-01
-3.85043234e-01 8.11718822e-01 -6.68981433e-01 -3.48434985e-01
-1.65659163e-04 -6.45223379e-01 -1.04975557e+00 5.14072537e-01
5.51524460e-02 2.62721665e-02 -1.43319026e-01 1.33240473e+00
5.46424389e-01 1.14649422e-01 1.00203621e+00 -9.24027801e-01
-6.80476725e-01 7.63308644e-01 -7.91889012e-01 4.57661860e-02
-3.21323425e-02 4.85584363e-02 6.31283343e-01 -6.89565778e-01
8.75171244e-01 1.26917613e+00 5.40309072e-01 8.77813816e-01
-1.26539314e+00 -3.24403971e-01 2.15660095e-01 1.88524559e-01
-1.14615607e+00 -4.61568870e-02 9.77599800e-01 -5.47406673e-01
5.07909358e-01 9.97617319e-02 5.61080515e-01 1.20642710e+00
9.10339803e-02 1.46202230e+00 1.40695691e+00 -4.84755963e-01
5.04646182e-01 2.54813582e-01 5.26659302e-02 6.75176919e-01
-7.20036328e-02 -2.75724590e-01 -4.37125236e-01 3.13240253e-06
7.96257198e-01 -2.40786612e-01 -1.60828441e-01 -4.24149901e-01
-1.16948974e+00 8.19614649e-01 3.97334188e-01 5.45095265e-01
-5.22772074e-01 2.38305792e-01 4.21301499e-02 -2.17377067e-01
1.01088083e+00 -5.29247709e-03 -3.45790178e-01 1.64613500e-01
-1.35117078e+00 2.12317020e-01 6.78235888e-01 8.77061963e-01
4.62236404e-01 -1.87887162e-01 -4.32216734e-01 9.83256459e-01
4.77750897e-01 3.99731368e-01 4.42496389e-01 -1.14830852e+00
-8.20283405e-03 4.82704550e-01 -1.83189034e-01 -7.80974448e-01
-2.09872097e-01 -4.17349607e-01 -8.19439292e-01 2.31599957e-01
5.24284482e-01 -6.99466839e-03 -1.28803563e+00 1.31462395e+00
4.81718063e-01 6.43983066e-01 8.25318694e-02 8.35535645e-01
6.89001203e-01 6.61154747e-01 3.78524005e-01 -2.73432327e-03
1.13303912e+00 -1.20845985e+00 -7.30799913e-01 -3.30502212e-01
4.11115229e-01 -8.45481217e-01 6.94555104e-01 6.32533550e-01
-1.01414764e+00 -3.84282947e-01 -7.44413674e-01 9.13396403e-02
-1.39051467e-01 1.36149928e-01 6.64851189e-01 8.08210552e-01
-1.14556599e+00 6.02442980e-01 -1.05356240e+00 -2.95274854e-01
1.06522512e+00 1.48283333e-01 5.71120642e-02 -3.19031805e-01
-9.21465278e-01 7.47952938e-01 2.11511955e-01 5.77371754e-02
-1.09371018e+00 -5.93896747e-01 -7.32671142e-01 -4.10396308e-01
5.09736121e-01 -7.53592193e-01 1.23132694e+00 -1.07536066e+00
-1.65996468e+00 1.03083074e+00 -1.41296506e-01 -7.76869059e-01
8.89432132e-01 -8.65038335e-02 2.03904007e-02 3.63849491e-01
2.57288158e-01 1.24827600e+00 1.16393650e+00 -1.53339183e+00
-6.18212223e-01 -2.34249502e-01 -2.59606659e-01 2.11766735e-02
-8.84511396e-02 -1.22991748e-01 -9.53681469e-01 -9.74356234e-01
2.94082016e-01 -8.91564846e-01 -8.25157464e-01 3.21337730e-01
-6.64613485e-01 -3.50163698e-01 7.22736180e-01 -5.59321046e-01
9.56250310e-01 -2.06239867e+00 2.72137731e-01 2.72349745e-01
9.29799750e-02 2.27103129e-01 7.42204301e-03 -1.53038934e-01
4.09811735e-01 1.62171006e-01 -1.06452334e+00 -6.00605190e-01
-2.34396935e-01 5.13752043e-01 1.79530866e-02 4.31381464e-01
2.38162011e-01 9.59938288e-01 -1.03869247e+00 -9.23599482e-01
3.64824176e-01 6.73506916e-01 -6.61766648e-01 1.35621578e-01
-5.21585822e-01 7.27706552e-01 -5.93039513e-01 6.44922197e-01
7.25500405e-01 -2.27310672e-01 -7.49050826e-02 2.50696583e-04
3.44138443e-01 -1.95611432e-01 -1.10855269e+00 2.04747248e+00
-2.67893583e-01 5.94662666e-01 3.92210037e-02 -1.11798537e+00
7.18699574e-01 1.39806435e-01 4.86515105e-01 -5.07609487e-01
1.18894823e-01 3.13516408e-01 -2.49562994e-01 -5.20940781e-01
2.48447970e-01 -2.19344720e-01 3.32563341e-01 1.60118520e-01
3.28926682e-01 -6.15876555e-01 1.69504181e-01 3.28110754e-01
7.99923539e-01 4.98727709e-01 -1.22395597e-01 -4.26789641e-01
3.05182844e-01 1.74904361e-01 4.50677931e-01 9.86629784e-01
-1.86937153e-01 1.09170985e+00 4.45014417e-01 1.73076436e-01
-6.35016799e-01 -9.84438360e-01 -1.99766338e-01 6.31176293e-01
4.00892049e-01 -2.47546136e-02 -1.49650872e+00 -9.92377877e-01
-3.31760705e-01 8.75194073e-01 -7.99091876e-01 1.17969826e-01
-4.08403754e-01 -1.21573353e+00 4.25350249e-01 4.92575437e-01
6.31809592e-01 -1.22466648e+00 -3.67619902e-01 4.43002731e-01
-2.97555119e-01 -1.17411995e+00 -5.20437002e-01 -5.20545952e-02
-1.12219918e+00 -1.08850169e+00 -1.42440450e+00 -9.54609156e-01
9.92311478e-01 1.67267948e-01 1.05531824e+00 1.08175939e-02
-4.23394442e-01 4.49806333e-01 -2.61547953e-01 -4.39326435e-01
-7.56309688e-01 -3.33388187e-02 -5.66846251e-01 2.33247995e-01
2.23467708e-01 -1.58692211e-01 -8.44422221e-01 3.81185740e-01
-1.08839357e+00 2.52940774e-01 6.07955575e-01 6.65818572e-01
9.86384153e-01 3.28440011e-01 3.33563447e-01 -1.44316900e+00
5.75689375e-01 -4.84112859e-01 -4.00795728e-01 1.49644032e-01
-7.04511166e-01 -6.15574010e-02 -1.64185047e-01 -6.14917219e-01
-1.47786868e+00 2.80558288e-01 -5.22868752e-01 -8.86922404e-02
-4.01910603e-01 1.52182296e-01 -3.03421374e-02 2.20742226e-01
6.99282765e-01 2.70738691e-01 -2.37573925e-02 -5.27775526e-01
5.16101658e-01 5.40677130e-01 4.55472857e-01 -6.48466110e-01
3.05419922e-01 9.18755889e-01 -2.72930246e-02 -9.09927130e-01
-1.01777697e+00 -6.22523546e-01 -6.27310038e-01 -2.96169817e-01
1.26806259e+00 -6.53974712e-01 -1.01716965e-01 8.67875874e-01
-1.26330435e+00 -5.61076403e-01 -4.62185472e-01 2.42888942e-01
-4.92105931e-01 4.63227451e-01 -7.49675572e-01 -8.01959157e-01
-7.05622807e-02 -1.57997823e+00 1.30226982e+00 1.21355943e-01
-3.18956852e-01 -1.24583995e+00 -2.60257065e-01 6.64450645e-01
3.26101214e-01 1.03978455e-01 7.08357453e-01 -4.59845543e-01
-5.99782646e-01 -9.76159200e-02 -1.90010682e-01 8.11047614e-01
-7.64394850e-02 -1.53741270e-01 -1.07879031e+00 3.06464285e-01
2.33836383e-01 6.26617968e-02 1.30160546e+00 9.74463522e-01
1.42046309e+00 9.15129781e-02 -6.54544473e-01 3.06480765e-01
1.22394061e+00 1.01007871e-01 7.32944548e-01 1.52480856e-01
7.27422476e-01 8.59401584e-01 5.81909239e-01 -4.64851893e-02
2.43740097e-01 4.87323791e-01 3.04557770e-01 -4.83559251e-01
-7.50375926e-01 -1.88276008e-01 1.73786938e-01 4.94972408e-01
3.22331339e-02 -3.56176287e-01 -8.25025260e-01 7.32899308e-01
-1.80109990e+00 -4.41218853e-01 -6.16514266e-01 1.62180877e+00
9.24309731e-01 3.90681952e-01 -1.29780531e-01 1.24883488e-01
6.46766365e-01 1.34746414e-02 -5.44651568e-01 -9.47865471e-03
-2.45455414e-01 3.14002067e-01 5.58356941e-01 4.91644859e-01
-1.13600230e+00 1.11939228e+00 5.94224405e+00 1.43368900e+00
-7.15957165e-01 5.23800910e-01 1.11312151e+00 3.65737200e-01
-3.65217924e-01 -5.57678081e-02 -5.76748908e-01 4.35834706e-01
4.60288256e-01 4.80856270e-01 5.09862341e-02 8.77068520e-01
1.72520548e-01 -5.62229633e-01 -7.66328454e-01 7.59301960e-01
1.48112491e-01 -1.44010758e+00 1.77035958e-01 -1.32791400e-01
1.16242480e+00 -2.73664817e-02 7.06385225e-02 -1.27978623e-01
3.36966038e-01 -8.80290866e-01 9.12304461e-01 5.70562780e-01
3.08878541e-01 -4.06813622e-01 8.77758086e-01 4.74062443e-01
-6.23449087e-01 2.84141570e-01 -2.45049134e-01 5.21453619e-01
3.19775939e-01 1.01299012e+00 -7.05819666e-01 3.08556139e-01
6.22667909e-01 7.77330220e-01 -4.71057773e-01 1.03067362e+00
-5.61924100e-01 1.10692751e+00 -1.59101635e-01 2.66152173e-01
4.03786033e-01 -2.66185343e-01 4.57267225e-01 1.49675059e+00
1.85730055e-01 -1.10565923e-01 1.57527983e-01 1.04973769e+00
-3.38797234e-02 8.64504799e-02 -1.68354616e-01 1.21237531e-01
-1.36760712e-01 1.04629624e+00 -1.57395864e+00 -5.13620079e-01
-1.82230905e-01 1.43839288e+00 -2.07129657e-01 3.77041101e-01
-6.52370691e-01 1.88148141e-01 1.87750474e-01 1.04050644e-01
3.02348763e-01 1.49021309e-03 -6.85104430e-01 -7.61977792e-01
-2.59652048e-01 -6.04512691e-01 3.58772814e-01 -8.15990627e-01
-1.27214539e+00 5.93283296e-01 -1.51975900e-02 -9.34894204e-01
1.69926763e-01 -5.15226007e-01 -2.78009117e-01 6.72036350e-01
-1.60320652e+00 -1.29533815e+00 -9.16201714e-03 3.67716521e-01
1.24171078e+00 1.94154501e-01 6.33676350e-01 2.52558023e-01
-2.49842316e-01 -5.68166450e-02 -1.31143108e-01 -1.42756035e-03
4.93845016e-01 -1.44759917e+00 3.63532841e-01 8.39679062e-01
3.77990454e-01 2.55211830e-01 7.88779974e-01 -8.73560131e-01
-7.48467863e-01 -1.12014699e+00 5.83151519e-01 -5.88943958e-01
4.80395615e-01 -1.70277312e-01 -9.79225338e-01 1.87189147e-01
2.23000422e-01 -4.62386385e-02 3.65032285e-01 -4.65450436e-01
2.01193601e-01 2.55196184e-01 -1.32046950e+00 6.44723058e-01
1.04113948e+00 -1.63258612e-01 -3.09666514e-01 5.13303220e-01
6.63608372e-01 -6.06414914e-01 -5.39288998e-01 2.75218457e-01
1.06155902e-01 -8.22227657e-01 1.09474778e+00 -4.70218472e-02
5.11941493e-01 -2.95351297e-01 9.79064256e-02 -1.24539316e+00
1.04436696e-01 -5.19464910e-01 7.65760371e-04 1.27349758e+00
5.34895241e-01 -3.18423927e-01 9.85260546e-01 4.90858197e-01
-1.86257288e-01 -9.53575313e-01 -8.58931601e-01 -4.43496972e-01
2.80164003e-01 -9.36959386e-01 1.48050725e-01 7.05552459e-01
-6.94138467e-01 -6.34163022e-02 -2.35238954e-01 1.70102805e-01
8.63686323e-01 -1.47471026e-01 3.06522548e-01 -1.11756337e+00
-3.42652202e-01 -6.75971687e-01 -1.50101557e-01 -1.36949575e+00
2.56587923e-01 -1.01586294e+00 3.59096467e-01 -2.02079988e+00
1.82282448e-01 -5.89467645e-01 -2.80566484e-01 2.44087920e-01
-3.12278301e-01 5.92327356e-01 -1.42150208e-01 1.68550804e-01
-4.98104364e-01 2.54786015e-01 1.69439876e+00 -5.86831629e-01
-5.89214042e-02 3.10014158e-01 -6.90766513e-01 1.08034241e+00
7.82863021e-01 -8.82864296e-01 -4.87823069e-01 -3.73729438e-01
-1.35046959e-01 -1.65984631e-01 4.10149723e-01 -6.95437253e-01
3.07007760e-01 -6.71131909e-02 2.27752000e-01 -4.69324917e-01
1.75088942e-01 -7.51467645e-01 -3.58967111e-02 5.07403910e-01
-4.11991060e-01 -6.86184108e-01 -8.31518769e-02 8.93728435e-01
-2.01393336e-01 -5.94151676e-01 8.96165431e-01 -3.70246083e-01
-9.37342882e-01 2.66178101e-01 -6.22311473e-01 2.93026902e-02
1.00229883e+00 -3.36199164e-01 2.75904775e-01 -1.83037579e-01
-9.49837387e-01 6.15134016e-02 2.52301872e-01 4.25914317e-01
6.47642612e-01 -7.36620367e-01 -6.21241152e-01 -1.21846674e-02
-1.35550186e-01 4.58501011e-01 4.34598893e-01 9.14004147e-01
-4.92713541e-01 -5.69384433e-02 5.01203239e-01 -9.86645520e-01
-1.09048283e+00 4.45067853e-01 2.54087031e-01 -8.53719935e-02
-9.73166764e-01 1.25812018e+00 4.01839644e-01 -2.16401875e-01
2.64797866e-01 -4.39426690e-01 -2.23152757e-01 2.53060088e-02
3.18591565e-01 3.72481763e-01 -1.18932845e-02 -5.64465344e-01
-1.97708592e-01 5.95715523e-01 -4.63202521e-02 -3.13529640e-01
1.23634303e+00 -1.20107047e-01 -1.52374163e-01 3.37484449e-01
8.51270616e-01 -1.74708992e-01 -1.55705953e+00 -2.94654995e-01
2.15592504e-01 -2.15737671e-01 4.64169353e-01 -8.46927106e-01
-1.35271561e+00 1.02409399e+00 7.27731526e-01 1.89604834e-02
1.11404991e+00 3.62547338e-01 9.17037487e-01 -2.50627339e-01
3.34480315e-01 -1.34445524e+00 2.28747815e-01 7.01986579e-03
6.08784258e-01 -1.27736509e+00 -1.32140502e-01 -9.10774708e-01
-9.99641776e-01 7.69118547e-01 1.76130772e-01 -1.26935884e-01
8.58513713e-01 3.80181789e-01 2.70324647e-01 -2.29178011e-01
-1.89017311e-01 -2.69080162e-01 4.39865887e-01 8.78809988e-01
2.87741274e-01 1.81316465e-01 -2.58667201e-01 3.68558228e-01
2.49904513e-01 7.11233243e-02 4.07336563e-01 8.90050411e-01
-3.79688174e-01 -1.20758772e+00 -2.67923772e-01 3.67357880e-01
-7.13555455e-01 -1.95024520e-01 -2.25551486e-01 4.32163656e-01
3.28359395e-01 1.08383346e+00 -2.50154912e-01 2.70493716e-01
1.17488615e-01 -1.84303876e-02 5.18059671e-01 -8.20206761e-01
-3.30733210e-01 4.15251195e-01 -2.17852503e-01 -5.24935365e-01
-8.59618843e-01 -7.91537642e-01 -1.48407269e+00 4.38083172e-01
-4.39123511e-01 -1.93348043e-02 9.18443501e-01 1.04183066e+00
6.04304820e-02 8.53038967e-01 3.46473977e-02 -8.60693634e-01
-1.37465850e-01 -8.24204981e-01 -6.23530924e-01 4.71652120e-01
2.74558682e-02 -6.14596486e-01 -1.50815934e-01 4.53629673e-01] | [14.38696575164795, -2.0432510375976562] |
8e1e8779-ad16-44a7-9606-7995c5e09261 | explaining-prediction-uncertainty-of-pre | 2201.03742 | null | https://arxiv.org/abs/2201.03742v2 | https://arxiv.org/pdf/2201.03742v2.pdf | Explaining Predictive Uncertainty by Looking Back at Model Explanations | Predictive uncertainty estimation of pre-trained language models is an important measure of how likely people can trust their predictions. However, little is known about what makes a model prediction uncertain. Explaining predictive uncertainty is an important complement to explaining prediction labels in helping users understand model decision making and gaining their trust on model predictions, while has been largely ignored in prior works. In this work, we propose to explain the predictive uncertainty of pre-trained language models by extracting uncertain words from existing model explanations. We find the uncertain words are those identified as making negative contributions to prediction labels, while actually explaining the predictive uncertainty. Experiments show that uncertainty explanations are indispensable to explaining models and helping humans understand model prediction behavior. | ['Yangfeng Ji', 'Wanyu Du', 'Hanjie Chen'] | 2022-01-11 | null | null | null | null | ['paraphrase-identification'] | ['natural-language-processing'] | [ 3.43267340e-03 1.02661836e+00 -9.16753113e-01 -1.06247675e+00
-3.43433887e-01 -4.85724092e-01 5.96786380e-01 4.50863421e-01
-1.63056515e-02 8.62731040e-01 5.48347533e-01 -7.37967849e-01
2.20848516e-01 -5.25109828e-01 -7.12194264e-01 2.91602463e-01
2.30481729e-01 7.37833261e-01 -5.69708720e-02 -1.05730994e-02
5.95261693e-01 -6.05197325e-02 -1.19051671e+00 6.59584403e-01
1.32420158e+00 9.34630692e-01 -6.76400661e-02 4.18354541e-01
-6.73686981e-01 1.21257985e+00 -1.45163074e-01 -9.74862754e-01
-4.16833043e-01 4.91371118e-02 -9.06763732e-01 -3.53718132e-01
-1.75005682e-02 -3.07134032e-01 1.93664610e-01 8.98100436e-01
-5.04901350e-01 -2.47208844e-03 1.06183279e+00 -1.48667908e+00
-1.39334047e+00 1.63351285e+00 -2.12622322e-02 2.81068757e-02
4.60346431e-01 -2.69895971e-01 1.21370149e+00 -1.04618561e+00
2.22293288e-01 1.51611316e+00 6.51243329e-01 8.53219867e-01
-1.22148895e+00 -6.81008339e-01 7.74426699e-01 4.37940001e-01
-1.23030031e+00 -2.02590689e-01 5.21600604e-01 -7.53267348e-01
1.04250121e+00 3.85029912e-01 3.86394382e-01 1.20135987e+00
5.01987159e-01 8.84318948e-01 9.68707860e-01 -3.35190833e-01
4.33067262e-01 1.04736149e+00 6.44098341e-01 4.07582790e-01
5.17423809e-01 3.32034945e-01 -7.28131175e-01 -4.31070954e-01
1.17332458e-01 2.29554206e-01 -2.08055094e-01 4.96821962e-02
-7.14413404e-01 1.08804822e+00 5.98195136e-01 -6.53219968e-02
-3.81155789e-01 2.94117451e-01 -2.17167839e-01 -3.47918980e-02
9.19812143e-01 7.06850767e-01 -9.37544107e-01 -2.86296964e-01
-4.16255802e-01 1.38597459e-01 1.05826950e+00 1.16368949e+00
7.49859810e-01 -1.11250430e-01 -1.19991869e-01 3.20829391e-01
1.00786948e+00 5.20036638e-01 4.78401363e-01 -9.22689438e-01
3.10069229e-02 6.62691474e-01 6.21476054e-01 -8.88528287e-01
-3.06152552e-01 -2.71575332e-01 -3.21535021e-01 -1.39941588e-01
5.23340330e-02 -1.38935611e-01 -6.34415329e-01 1.49694014e+00
-2.97712862e-01 2.96947718e-01 2.52005845e-01 5.78321934e-01
6.11387372e-01 7.19632387e-01 7.74359405e-01 -1.24626338e-01
1.13158011e+00 -8.27000201e-01 -6.50744796e-01 -9.33840752e-01
8.63843501e-01 -7.72334933e-01 1.09536171e+00 2.05048814e-01
-4.87448603e-01 -3.56000334e-01 -7.45032668e-01 -3.35134044e-02
-2.16814995e-01 -1.71130881e-01 9.46185410e-01 6.41582370e-01
-6.20722353e-01 7.06452310e-01 -5.92577398e-01 1.44047871e-01
3.21598351e-01 -1.82981156e-02 1.13255708e-02 -2.40430906e-01
-1.62269711e+00 1.33665693e+00 4.69557554e-01 -2.39815697e-01
-4.46971983e-01 -8.02777827e-01 -1.14936161e+00 2.75208294e-01
3.65571767e-01 -6.76351726e-01 1.74687505e+00 -9.01413798e-01
-1.07518971e+00 1.88052252e-01 -8.76663685e-01 -7.19715357e-01
1.57162324e-01 -5.53760052e-01 -4.55073208e-01 -8.20736885e-01
2.02405639e-02 8.87936890e-01 8.67224395e-01 -1.42309439e+00
-4.69123721e-01 -1.11804388e-01 9.33437049e-03 1.99564263e-01
3.45752016e-02 -2.65375495e-01 1.22050770e-01 -2.88912803e-01
2.88696080e-01 -1.03590345e+00 -5.22409320e-01 -5.00551127e-02
-4.95706081e-01 -5.15329361e-01 4.92397785e-01 -5.18410385e-01
1.35591912e+00 -1.66905093e+00 -4.07025814e-01 2.70609349e-01
5.28020024e-01 -9.58773047e-02 2.08485171e-01 2.07435638e-01
1.69072554e-01 1.01591694e+00 3.59708406e-02 -4.32346016e-01
2.81823754e-01 3.48284602e-01 -9.74532962e-01 -3.97915632e-01
1.87937021e-01 1.14196146e+00 -8.72615993e-01 -2.53522962e-01
2.35641912e-01 5.48352897e-01 -4.46537107e-01 4.03318733e-01
-6.98720276e-01 1.51785627e-01 -7.49622881e-01 4.94711131e-01
4.90397125e-01 -5.80018818e-01 -2.14669362e-01 1.53178394e-01
1.41011193e-01 6.60027087e-01 -8.08706224e-01 7.72736609e-01
-5.48321605e-01 5.67486763e-01 -9.73654985e-01 -2.23379016e-01
7.86381602e-01 6.55755550e-02 -5.18222034e-01 -5.56461103e-02
-2.31664162e-02 -1.86263397e-03 -2.00495366e-02 -2.77173936e-01
6.15218222e-01 -3.52247179e-01 -1.66408807e-01 6.82627797e-01
-4.48424488e-01 -5.67731500e-01 -3.96772534e-01 6.35685682e-01
2.32678071e-01 -5.46051562e-02 8.52907300e-01 -1.68684319e-01
2.10717648e-01 -2.25159619e-02 4.79909599e-01 1.03276801e+00
-2.34928742e-01 2.78143853e-01 5.76265156e-01 -7.18152523e-01
-6.44060194e-01 -8.10796738e-01 -1.63307190e-01 1.01030421e+00
1.06496751e-01 -8.82474601e-01 -3.19974393e-01 -8.09094906e-01
1.67385682e-01 2.02428746e+00 -9.72325385e-01 -3.44982833e-01
4.74048138e-01 -1.40378118e-01 -1.01168275e-01 9.30549145e-01
-1.20268486e-01 -5.86581171e-01 -4.21119183e-02 4.86035794e-02
-3.01752269e-01 -9.25615728e-01 -5.03360033e-01 2.23311424e-01
-1.02773976e+00 -7.49132454e-01 9.24086422e-02 1.26103796e-02
7.97488987e-01 2.31473714e-01 1.60063684e+00 4.44482595e-01
5.98474145e-01 3.93685609e-01 -3.80032420e-01 -1.21664774e+00
-6.13654912e-01 -3.61233652e-01 3.21572572e-01 -6.26921356e-01
1.08920693e+00 -1.94079503e-01 -2.43939951e-01 3.88436079e-01
-4.45304334e-01 4.05104727e-01 2.02420995e-01 5.89995563e-01
4.13421124e-01 -2.56645590e-01 3.45474839e-01 -1.49122059e+00
1.00681949e+00 -8.56046379e-01 -2.09681332e-01 4.96668637e-01
-1.54310894e+00 4.07415718e-01 3.80463839e-01 -3.42780590e-01
-1.16461897e+00 -7.79771358e-02 1.11340351e-01 2.77415603e-01
-6.10821247e-02 6.91560805e-01 2.04447597e-01 1.99177071e-01
8.29423726e-01 -2.57240117e-01 -4.26364273e-01 -6.27266318e-02
7.22365975e-01 4.73957419e-01 -1.81095362e-01 -5.24440348e-01
5.35278857e-01 -8.77706613e-03 -6.02299631e-01 -1.49873912e-01
-1.57628357e+00 -2.24696293e-01 -4.51844066e-01 -3.62772159e-02
5.36770999e-01 -8.98675144e-01 -5.18563628e-01 -3.27401996e-01
-1.28352630e+00 3.78196575e-02 -1.32310823e-01 7.03116596e-01
-1.79483265e-01 1.73814520e-01 -2.28427276e-01 -1.26931906e+00
-1.52346164e-01 -9.66240525e-01 6.68281078e-01 4.42622900e-01
-1.27513134e+00 -1.37793779e+00 -2.45166838e-01 4.66179729e-01
7.75920391e-01 -6.04425251e-01 1.25542378e+00 -1.19264829e+00
-5.78006327e-01 -3.52471769e-01 -1.12661391e-01 1.28428221e-01
-1.59078881e-01 6.48088902e-02 -1.07719564e+00 5.38798392e-01
-7.07652420e-02 -2.80430615e-01 9.25715148e-01 4.71482247e-01
1.38175380e+00 -5.69749773e-01 -5.86096108e-01 -1.88867599e-01
8.17886233e-01 -1.00780278e-01 4.45006520e-01 -9.02952403e-02
4.39868778e-01 7.29958475e-01 7.89951026e-01 5.78728199e-01
8.64265740e-01 2.16477022e-01 3.41826439e-01 4.49234217e-01
5.83666027e-01 -9.11491930e-01 4.55637813e-01 2.27141842e-01
2.53341436e-01 -3.35648358e-01 -1.19322169e+00 1.89847901e-01
-1.82388985e+00 -7.63627768e-01 -2.14420214e-01 1.94137776e+00
7.75142372e-01 4.47144985e-01 -6.76531911e-01 -2.58780956e-01
4.22529638e-01 -1.12644918e-01 -8.08916748e-01 -7.04555094e-01
7.74182826e-02 -4.12934721e-01 1.77896515e-01 1.36136746e+00
-7.42322147e-01 1.29943585e+00 7.12959766e+00 3.23009878e-01
-5.95231533e-01 -2.19193339e-01 1.23270833e+00 2.29256898e-01
-1.38719487e+00 5.26253939e-01 -1.03795683e+00 2.69775838e-01
9.95083511e-01 -8.17955196e-01 6.63372278e-02 1.60889471e+00
2.00536504e-01 -2.73568749e-01 -1.66005635e+00 6.63674057e-01
-1.10267410e-02 -1.24707401e+00 4.55660492e-01 -2.83359677e-01
8.88580143e-01 -3.75461251e-01 3.05379480e-01 6.73564196e-01
7.89564848e-01 -1.54236472e+00 5.72339952e-01 9.43365097e-01
1.32783830e-01 -5.57035565e-01 1.09150493e+00 8.81611466e-01
-6.50889337e-01 -8.68600905e-02 -7.18035638e-01 -6.66674614e-01
2.84499019e-01 1.09675717e+00 -1.44799948e+00 -4.13733006e-01
4.19311881e-01 7.80039847e-01 -5.84205031e-01 3.50503653e-01
-8.20388198e-01 1.05569851e+00 3.49830687e-02 -3.54183882e-01
3.99979949e-02 1.52426407e-01 1.83133364e-01 7.89620280e-01
5.12260437e-01 4.22685921e-01 2.78204419e-02 1.47589362e+00
-1.16749234e-01 6.74925819e-02 -6.57849073e-01 -3.79765034e-01
6.70026600e-01 6.14697576e-01 -5.90538755e-02 -5.06627798e-01
-2.99909890e-01 7.33466804e-01 3.16001624e-01 2.10690483e-01
-6.06050313e-01 4.72922027e-01 7.48784244e-01 5.38973436e-02
-4.21142101e-01 -1.04694858e-01 -9.86243844e-01 -1.27631629e+00
-2.21427709e-01 -3.81837368e-01 2.71348000e-01 -1.34199202e+00
-1.56133354e+00 7.45431781e-01 -9.84158069e-02 -8.17279279e-01
-9.25136328e-01 -5.02967954e-01 -7.33146191e-01 1.30201578e+00
-1.59293938e+00 -1.01987648e+00 -1.60294861e-01 -7.51649514e-02
6.56783462e-01 -8.90973434e-02 1.12502611e+00 -8.05385470e-01
-5.69375679e-02 2.26012900e-01 -3.82042706e-01 -5.77659428e-01
7.87627399e-01 -1.38058758e+00 7.96922982e-01 7.51006365e-01
1.79838464e-01 1.19994426e+00 1.24421096e+00 -1.15028763e+00
-6.45252168e-01 -8.73874128e-01 1.72421896e+00 -1.24727869e+00
5.80875993e-01 1.03037372e-01 -1.39274764e+00 1.10485518e+00
-7.85997603e-03 -2.32362762e-01 1.48598742e+00 7.12828815e-01
-6.67022467e-01 6.18370891e-01 -1.09123504e+00 7.17233717e-01
6.36197448e-01 -5.40098667e-01 -1.02711940e+00 3.24427485e-01
1.28031170e+00 -2.58562326e-01 -5.49254239e-01 1.72324464e-01
5.92082679e-01 -8.27881336e-01 6.60801649e-01 -1.01839650e+00
6.42809212e-01 -1.91541746e-01 -2.30404779e-01 -1.71040916e+00
-5.21188021e-01 -2.24656940e-01 -4.65635240e-01 9.38271582e-01
1.33541703e+00 -5.07134438e-01 8.95122707e-01 2.20133352e+00
1.36403978e-01 -6.98660314e-01 -3.63226384e-01 -1.41721308e-01
1.29739165e-01 -1.14771688e+00 8.49715233e-01 7.92701423e-01
3.59947741e-01 1.69898570e-01 -5.97631931e-01 3.90360564e-01
4.93226856e-01 -8.53328034e-02 3.39054912e-01 -1.57691979e+00
3.13025862e-02 -1.12338826e-01 -3.09419259e-02 -1.16323280e+00
6.62209392e-01 -6.72405958e-01 -4.49423157e-02 -1.67313278e+00
4.13297296e-01 -6.85162127e-01 -1.92909449e-01 5.74923515e-01
-7.76005507e-01 -2.15151817e-01 1.19540207e-01 4.67390329e-01
-5.28941095e-01 4.75588679e-01 8.73919487e-01 -2.01252494e-02
-5.97158968e-02 5.48081875e-01 -1.62745845e+00 1.16876221e+00
8.28719199e-01 -6.49669170e-01 -9.32051539e-01 -3.36244881e-01
9.25963938e-01 -2.19545320e-01 2.48252600e-01 -5.41960597e-01
2.14765102e-01 -8.20181847e-01 5.78062654e-01 -4.37427998e-01
2.22557098e-01 -1.04535091e+00 -4.10412662e-02 2.87845582e-01
-1.19309151e+00 -3.08119748e-02 1.68417171e-01 8.33384752e-01
-8.63343403e-02 -4.68345106e-01 2.61221737e-01 -1.78228587e-01
-1.11418152e+00 2.34196126e-01 -5.06015360e-01 -1.16502807e-01
8.85191441e-01 1.68193534e-01 -2.75213391e-01 -1.07995439e+00
-8.57667565e-01 4.57745939e-01 2.05981538e-01 7.89695084e-01
9.84895110e-01 -1.31858134e+00 -6.12761259e-01 4.87035997e-02
6.31777346e-01 -3.95845801e-01 2.48465180e-01 1.25058234e-01
1.41265407e-01 8.94283652e-01 2.54060328e-01 -4.28768098e-01
-1.09005165e+00 4.63288724e-01 2.24848554e-01 -2.00479832e-02
-2.98532862e-02 1.25414622e+00 1.09018840e-01 -5.12303054e-01
2.63055235e-01 -6.68901443e-01 -3.93893898e-01 -4.25116986e-01
9.14570451e-01 6.80883676e-02 -4.83277202e-01 -2.62172490e-01
-2.64100462e-01 1.15803845e-01 -3.42506945e-01 -3.44239362e-02
8.98442566e-01 -5.23797095e-01 -7.43285418e-02 1.02073324e+00
5.37959158e-01 -6.34836126e-03 -1.11209285e+00 -5.25293827e-01
3.34692687e-01 -7.43126214e-01 -7.86916818e-03 -1.39615524e+00
-1.91408813e-01 1.25974476e+00 8.34694356e-02 6.28634468e-02
2.84889400e-01 3.09334248e-01 4.13655430e-01 7.40548193e-01
3.83228332e-01 -6.99231803e-01 -1.54655680e-01 6.99472964e-01
1.19151449e+00 -2.06269312e+00 -6.78776130e-02 -8.40782344e-01
-1.44310629e+00 1.13987780e+00 1.02118361e+00 6.01247430e-01
8.26131463e-01 4.85611893e-02 2.66261756e-01 2.42016971e-01
-1.23403072e+00 3.44351530e-01 9.82233286e-01 7.06812382e-01
1.05435026e+00 5.68403840e-01 -3.11192032e-02 1.56950641e+00
-3.83355021e-01 1.98925138e-01 6.60204530e-01 2.97880441e-01
-8.97085965e-01 -1.07567704e+00 -8.23875368e-02 7.23593771e-01
-1.40109763e-01 -7.05088198e-01 -8.51883590e-01 1.44746989e-01
-1.35168940e-01 1.20570982e+00 -3.57463032e-01 -6.29414499e-01
-8.38198885e-02 5.57139277e-01 -2.93363839e-01 -9.24170971e-01
-1.65552348e-01 -8.78705442e-01 2.91357428e-01 -5.31096399e-01
1.91501185e-01 -2.95360595e-01 -1.46396506e+00 -4.80481595e-01
-3.29094857e-01 6.07428253e-01 6.80109918e-01 1.19257629e+00
5.29128790e-01 1.31028324e-01 2.44756743e-01 -2.76820272e-01
-7.38761723e-01 -1.09248829e+00 -2.78278470e-01 1.49252340e-01
4.77011651e-02 -4.62292463e-01 -5.63674927e-01 -3.95764187e-02] | [9.561667442321777, 6.810164928436279] |
ef0d4cf2-c6ba-475e-bcf5-34500f10e67d | enhancing-cross-lingual-natural-language | null | null | https://aclanthology.org/2022.acl-long.134 | https://aclanthology.org/2022.acl-long.134.pdf | Enhancing Cross-lingual Natural Language Inference by Prompt-learning from Cross-lingual Templates | Cross-lingual natural language inference (XNLI) is a fundamental task in cross-lingual natural language understanding. Recently this task is commonly addressed by pre-trained cross-lingual language models. Existing methods usually enhance pre-trained language models with additional data, such as annotated parallel corpora. These additional data, however, are rare in practice, especially for low-resource languages. Inspired by recent promising results achieved by prompt-learning, this paper proposes a novel prompt-learning based framework for enhancing XNLI. It reformulates the XNLI problem to a masked language modeling problem by constructing cloze-style questions through cross-lingual templates. To enforce correspondence between different languages, the framework augments a new question for every question using a sampled template in another language and then introduces a consistency loss to make the answer probability distribution obtained from the new question as similar as possible with the corresponding distribution obtained from the original question. Experimental results on two benchmark datasets demonstrate that XNLI models enhanced by our proposed framework significantly outperform original ones under both the full-shot and few-shot cross-lingual transfer settings. | ['Haolan Chen', 'Jianfeng Du', 'Hai Wan', 'Kunxun Qi'] | null | null | null | null | acl-2022-5 | ['cross-lingual-natural-language-inference'] | ['natural-language-processing'] | [ 2.09222347e-01 -3.48300524e-02 -3.70114803e-01 -6.79580390e-01
-1.54044056e+00 -5.56437671e-01 7.12808013e-01 -3.62793654e-02
-8.05048287e-01 9.05823767e-01 2.38445565e-01 -2.91180909e-01
9.24232826e-02 -8.03586960e-01 -9.65560019e-01 -3.64493072e-01
6.82947576e-01 6.14148021e-01 3.32605034e-01 -2.08853230e-01
-5.44803552e-02 -2.38759533e-01 -1.35854948e+00 5.02640665e-01
1.38730776e+00 5.04049659e-01 4.97871965e-01 2.49826759e-01
-8.92100036e-01 7.61975646e-01 -2.36430332e-01 -7.66352713e-01
1.20873533e-01 -7.02118218e-01 -8.82092535e-01 1.13149822e-01
4.34631407e-01 -6.35691686e-03 -5.91343604e-02 1.20014513e+00
2.27689281e-01 4.07488585e-01 3.84835601e-01 -1.07974374e+00
-9.80313838e-01 7.85241425e-01 -4.86127734e-01 6.48211092e-02
4.35174346e-01 7.24207535e-02 1.31868684e+00 -1.16722095e+00
6.11778677e-01 1.60657656e+00 4.60850447e-01 7.00730383e-01
-1.37118328e+00 -6.72288537e-01 3.15153390e-01 4.71343666e-01
-1.32639265e+00 -4.61713791e-01 7.70216346e-01 -7.19915181e-02
8.29460323e-01 -1.15368977e-01 -1.75285593e-01 1.05391681e+00
-2.86367498e-02 1.03258181e+00 1.24033320e+00 -8.57795358e-01
3.39133367e-02 6.03504777e-01 3.28451097e-01 6.33678257e-01
-1.58127174e-01 -2.86310434e-01 -5.01161516e-01 -1.55023932e-01
8.35331753e-02 -2.62185723e-01 -2.68637776e-01 -2.96450257e-01
-1.09000707e+00 9.62370396e-01 -1.20575735e-02 4.75385129e-01
-1.07446373e-01 -3.13091606e-01 5.36339223e-01 4.93142337e-01
5.66793323e-01 2.34111190e-01 -7.37563074e-01 1.29542783e-01
-7.59949803e-01 2.35157624e-01 7.49101400e-01 1.22708237e+00
1.16324353e+00 -3.00752103e-01 -3.31967860e-01 1.13815629e+00
2.41589785e-01 3.33402425e-01 6.37394547e-01 -5.53626835e-01
7.06227660e-01 5.71186125e-01 2.57738084e-02 -4.39922929e-01
2.34608188e-01 -2.47664124e-01 -5.68080246e-01 -3.78807038e-01
5.52153409e-01 -1.60782501e-01 -4.55337346e-01 2.00355458e+00
5.66553473e-01 2.17967495e-01 4.39497948e-01 4.13377225e-01
7.19893634e-01 1.02525449e+00 3.07689101e-01 -2.40257055e-01
1.62286592e+00 -1.19066703e+00 -9.36058939e-01 -3.62289935e-01
8.29768181e-01 -9.16767061e-01 1.77992070e+00 2.10729837e-01
-8.16578984e-01 -8.21285546e-01 -7.29635417e-01 -5.22064388e-01
-4.92018223e-01 1.47517562e-01 1.68991387e-02 4.81359392e-01
-5.30766785e-01 1.12761982e-01 -3.52663040e-01 -4.94696259e-01
1.04613781e-01 -1.58521488e-01 -2.35882998e-01 -6.91325009e-01
-1.63559461e+00 1.02975988e+00 4.63484436e-01 -2.57062703e-01
-5.80136240e-01 -9.50630486e-01 -1.17178237e+00 -1.19962906e-02
8.93798769e-01 -3.90061855e-01 1.35530651e+00 -8.25700641e-01
-1.48971057e+00 1.06656098e+00 -6.48807824e-01 -3.35274935e-01
4.43417490e-01 -3.88982058e-01 -4.16586101e-01 -3.43089193e-01
4.93543625e-01 4.90159541e-01 5.95897377e-01 -1.19034374e+00
-6.29676640e-01 -2.78995216e-01 9.26908851e-02 1.10292390e-01
-2.93377131e-01 2.34496668e-01 -7.18904912e-01 -5.78998208e-01
-3.83366257e-01 -6.31899834e-01 -9.70858261e-02 -5.23618832e-02
-1.26129910e-01 -1.00164175e+00 8.28047693e-01 -6.71172678e-01
1.05901659e+00 -1.76260877e+00 -9.80784148e-02 -2.60637522e-01
-3.69137913e-01 4.49980736e-01 -4.80676174e-01 3.86417478e-01
1.64824754e-01 -2.10344121e-01 -4.41282362e-01 -5.26224971e-01
1.99826971e-01 6.35876358e-01 -4.98777062e-01 1.52036339e-01
3.87588471e-01 8.46548200e-01 -1.13904953e+00 -7.11416483e-01
1.04428940e-01 2.50848711e-01 -7.09509254e-01 7.44211435e-01
-6.63350761e-01 4.70996827e-01 -1.95413917e-01 2.66422659e-01
6.91117883e-01 -1.30181789e-01 1.09043576e-01 -1.31282657e-01
-1.12252891e-01 5.70235074e-01 -9.22599018e-01 2.08790565e+00
-9.64867771e-01 1.05696276e-01 -1.73114792e-01 -1.21929693e+00
1.18223464e+00 4.17935580e-01 -2.33548954e-02 -6.33292913e-01
-3.23970430e-02 1.94084153e-01 2.26898976e-02 -9.03421342e-01
2.90582985e-01 -5.57713985e-01 -2.83112466e-01 6.74219429e-01
5.61994195e-01 -3.08819205e-01 2.89032787e-01 6.19196184e-02
4.80954856e-01 4.18061972e-01 4.97338653e-01 -2.80700743e-01
1.08295465e+00 -1.55972287e-01 6.92342520e-01 8.19688737e-01
-2.66783476e-01 9.65287462e-02 1.67875916e-01 -1.18350685e-01
-8.45561087e-01 -1.05645597e+00 -1.65262952e-01 1.50730824e+00
2.80318111e-02 -4.06069785e-01 -6.79705083e-01 -9.37671304e-01
-1.29807457e-01 1.25582683e+00 -5.68302751e-01 -5.06264046e-02
-4.71024603e-01 -3.99082243e-01 4.69016522e-01 2.30710074e-01
5.20716369e-01 -1.16822433e+00 6.66924054e-03 4.76516247e-01
-4.39566731e-01 -1.53975224e+00 -8.44290376e-01 3.15226871e-03
-3.86523902e-01 -7.94259250e-01 -6.20867193e-01 -1.15705073e+00
4.50803638e-01 1.43832222e-01 1.22188473e+00 -1.32971823e-01
-1.81339562e-01 3.13003957e-01 -3.86496454e-01 -2.71611065e-01
-5.94069123e-01 1.75858170e-01 4.22420241e-02 3.84356022e-01
1.06200778e+00 -3.00535828e-01 6.12605549e-02 1.58670202e-01
-9.08728659e-01 -5.27786724e-02 3.31903905e-01 9.72027540e-01
6.46911800e-01 -2.32835084e-01 1.01396000e+00 -1.13254166e+00
6.82662785e-01 -6.36748910e-01 -6.46837294e-01 7.64791012e-01
-3.35520834e-01 4.13233042e-01 9.41639423e-01 -4.70416695e-01
-1.64508188e+00 -2.20817789e-01 -3.08906108e-01 -2.22947717e-01
-3.42789292e-01 6.43938541e-01 -5.22355676e-01 3.00797671e-01
3.19573164e-01 5.34581721e-01 -1.71071872e-01 -6.48633599e-01
7.95512080e-01 7.77997017e-01 5.85859537e-01 -1.12226748e+00
7.87453651e-01 1.55333966e-01 -7.41459429e-01 -9.39247251e-01
-1.47525799e+00 -6.36640012e-01 -9.28203285e-01 1.70771647e-02
8.69584620e-01 -7.85818577e-01 -3.97493988e-01 2.38828704e-01
-1.56411088e+00 -1.69490725e-01 -2.13919282e-01 4.83151376e-01
-2.35724375e-01 3.96136701e-01 -3.28265309e-01 -8.19233835e-01
-3.54815662e-01 -1.10287273e+00 9.56522465e-01 1.76879272e-01
-2.03650326e-01 -1.33447289e+00 3.56284380e-01 4.92920667e-01
2.89150536e-01 -4.22912776e-01 1.42439485e+00 -8.93629849e-01
-4.28361356e-01 -7.27882236e-02 -1.80036694e-01 5.87802649e-01
4.71667409e-01 -3.55817735e-01 -9.11276102e-01 -7.79178590e-02
3.60005200e-01 -8.81337702e-01 5.17129064e-01 -1.71396554e-01
1.06168258e+00 -2.20548868e-01 -1.23737283e-01 1.91053286e-01
1.42977428e+00 -1.50991783e-01 3.21541965e-01 9.81104523e-02
6.14809036e-01 1.02475321e+00 6.64742112e-01 1.00114597e-02
7.59771585e-01 6.71646297e-01 -3.19876432e-01 1.58711344e-01
-8.58161077e-02 -5.85763574e-01 4.01006937e-01 1.42748332e+00
6.77790642e-01 -5.26535232e-03 -7.50068784e-01 8.75401735e-01
-1.74954355e+00 -8.19311142e-01 1.70294091e-01 2.13095236e+00
1.43887055e+00 5.11167385e-02 -2.54562318e-01 -3.48001301e-01
7.62761772e-01 1.67764947e-02 -6.96530282e-01 -2.73500293e-01
-1.75120279e-01 4.32024449e-01 -1.60272211e-01 9.14130270e-01
-7.94601083e-01 1.30667973e+00 4.88008118e+00 1.07936895e+00
-8.06211889e-01 4.37976062e-01 2.98920214e-01 2.40347460e-01
-6.40592694e-01 1.71595529e-01 -1.13912547e+00 3.48270208e-01
8.73285890e-01 -8.60140085e-01 4.68232296e-02 7.72311270e-01
1.49523318e-01 -1.75085086e-02 -1.21252453e+00 7.70661771e-01
5.07805645e-01 -1.01704597e+00 3.10552627e-01 -5.13475060e-01
7.44139552e-01 -2.61579938e-02 -2.40447134e-01 9.66181278e-01
4.78412896e-01 -6.75927341e-01 2.66772926e-01 2.53880084e-01
7.17145860e-01 -7.58426666e-01 5.86691380e-01 8.08400869e-01
-1.28273630e+00 4.55360204e-01 -5.54836154e-01 1.44531041e-01
2.66909450e-01 2.06207484e-01 -6.01905167e-01 5.85100055e-01
4.84574616e-01 6.34234607e-01 -4.01731849e-01 6.04714632e-01
-5.04837573e-01 7.71870792e-01 -4.62286510e-02 -1.81163594e-01
4.47251737e-01 -3.77631098e-01 2.88226008e-01 1.25614917e+00
1.19355239e-01 -7.05531659e-03 4.40928817e-01 1.13082540e+00
-3.76285136e-01 5.99551141e-01 -6.42463803e-01 1.82648182e-01
4.49464351e-01 1.14990604e+00 2.49026669e-03 -6.76515162e-01
-1.00449681e+00 9.30891991e-01 7.19615638e-01 2.49209389e-01
-6.66662753e-01 -5.38178146e-01 4.82372582e-01 -8.78116488e-02
2.13602170e-01 -1.70396082e-02 2.71497797e-02 -1.49241710e+00
3.61759029e-02 -1.15266037e+00 5.53046465e-01 -6.62788332e-01
-1.87369597e+00 6.50377035e-01 -5.56448847e-02 -1.11916339e+00
-3.89752477e-01 -5.10565758e-01 -5.87606013e-01 1.24402332e+00
-1.86338639e+00 -1.32049131e+00 6.36673793e-02 8.00863028e-01
1.17198265e+00 -1.76949248e-01 1.01163793e+00 3.96231949e-01
-4.32950646e-01 9.17159975e-01 7.74846002e-02 1.59072623e-01
1.02933621e+00 -1.06138647e+00 3.74504417e-01 9.11620498e-01
2.74204910e-01 7.56788015e-01 5.91676593e-01 -4.99137193e-01
-1.29194653e+00 -1.41549611e+00 1.42721057e+00 -3.84178191e-01
1.00594497e+00 -5.64056337e-01 -1.74188721e+00 7.87800550e-01
7.52923429e-01 -4.08291221e-02 9.36437964e-01 1.87550157e-01
-5.57292223e-01 -7.73050413e-02 -1.03949416e+00 7.41677046e-01
5.92299998e-01 -9.58795369e-01 -1.25913763e+00 4.29842323e-01
9.88191485e-01 -7.21294805e-02 -6.10314250e-01 2.34373063e-01
2.01298401e-01 -3.89748633e-01 5.36771894e-01 -9.47917938e-01
4.00266916e-01 -2.38157824e-01 -2.06040069e-01 -1.30296743e+00
2.40953695e-02 -5.88291228e-01 2.83473074e-01 1.61426461e+00
4.92088705e-01 -5.31510174e-01 4.74975109e-01 5.13888061e-01
1.74768455e-02 -5.70179462e-01 -1.00980473e+00 -9.91121292e-01
5.49811900e-01 -6.58050954e-01 4.00701851e-01 1.13069582e+00
5.37707508e-02 8.61184597e-01 -4.87157732e-01 1.75715342e-01
8.80078793e-01 2.28604496e-01 9.54917669e-01 -8.16258550e-01
-3.74955058e-01 -4.60948832e-02 2.38660991e-01 -1.39439738e+00
9.08114433e-01 -1.28488123e+00 4.82712746e-01 -1.20021212e+00
2.32416138e-01 -3.76554936e-01 -1.57526836e-01 2.47549027e-01
-7.43528366e-01 -1.31445453e-01 -1.26587257e-01 -1.64939240e-01
-5.59929192e-01 9.89032686e-01 1.05081046e+00 -1.91880332e-03
9.80891213e-02 -1.31083235e-01 -5.68157792e-01 8.27516735e-01
5.42230964e-01 -5.95900893e-01 -4.11289662e-01 -6.73894703e-01
-3.30724090e-01 -1.10378779e-01 -6.90170601e-02 -5.32340467e-01
4.24088746e-01 -2.17766926e-01 -2.85081863e-01 -6.35624826e-01
1.60567865e-01 -6.69773757e-01 -6.69093311e-01 2.59151369e-01
-6.77730381e-01 -3.95108163e-02 3.43387574e-01 5.15285075e-01
-3.97763878e-01 -5.04895508e-01 9.19920683e-01 -1.99859530e-01
-7.97446549e-01 2.54790425e-01 -2.38291457e-01 7.12351143e-01
7.76416063e-01 3.06898654e-01 -1.75555393e-01 -4.03050929e-01
-4.07625496e-01 5.01401484e-01 -4.70922270e-04 8.45778406e-01
3.92406553e-01 -1.44937289e+00 -9.44572330e-01 1.81251436e-01
6.66041255e-01 -1.15969427e-01 3.59812617e-01 5.18730581e-01
2.50711560e-01 6.02824152e-01 1.52833596e-01 -5.26282609e-01
-1.15119553e+00 7.44329154e-01 2.78144002e-01 -4.48061973e-01
-2.88304299e-01 8.89660358e-01 4.30640936e-01 -1.23673272e+00
2.20258802e-01 -1.99201778e-01 -4.99480478e-02 -9.93631184e-02
6.91504836e-01 -1.96565658e-01 -2.41843332e-02 -5.68186283e-01
-2.17231989e-01 6.92078650e-01 -5.15969455e-01 -1.87749818e-01
1.11534739e+00 -4.13038284e-01 -1.95963547e-01 9.10965860e-01
1.32002759e+00 8.37037116e-02 -8.98566782e-01 -1.30114853e+00
4.48892683e-01 -3.21428835e-01 -2.99347013e-01 -4.87542152e-01
-5.28001189e-01 1.08048010e+00 6.46585524e-02 -1.57680437e-01
6.98555946e-01 2.85560280e-01 1.00107098e+00 5.57051778e-01
3.12345028e-01 -1.07712984e+00 1.81741580e-01 8.04380715e-01
8.74353588e-01 -1.53848696e+00 -4.87684935e-01 -3.50599051e-01
-5.42774141e-01 8.51116538e-01 9.82392311e-01 -3.87857556e-02
6.35860205e-01 5.29603250e-02 3.18350434e-01 2.37524122e-01
-1.09031439e+00 -2.99052477e-01 3.42408925e-01 4.14396286e-01
8.19596887e-01 -2.26178929e-01 -3.45642000e-01 8.58377457e-01
-9.19398293e-02 1.09303281e-01 1.97517470e-01 7.44948864e-01
-4.12302256e-01 -1.48828411e+00 -2.35169306e-01 1.41019866e-01
-2.38906100e-01 -4.56095338e-01 -8.67664963e-02 7.39095926e-01
2.06932515e-01 9.17456746e-01 4.86799367e-02 9.80859399e-02
3.63157362e-01 5.67537785e-01 5.62474370e-01 -1.06443667e+00
-3.23549598e-01 -4.05084491e-02 -4.45920089e-03 -7.29742944e-02
-3.38310778e-01 -5.72767496e-01 -1.00879383e+00 1.01121880e-01
-3.05563748e-01 3.63672763e-01 3.01342189e-01 1.63156509e+00
7.06212595e-02 3.97935241e-01 4.93202955e-01 -7.24406093e-02
-7.91728377e-01 -1.08577144e+00 -2.33614191e-01 4.59198564e-01
1.48566484e-01 -4.90403891e-01 -3.54172409e-01 3.32878143e-01] | [10.961204528808594, 9.436274528503418] |
9870feae-7940-4677-b224-7bcfae569069 | group-anomaly-detection-using-deep-generative | 1804.04876 | null | http://arxiv.org/abs/1804.04876v1 | http://arxiv.org/pdf/1804.04876v1.pdf | Group Anomaly Detection using Deep Generative Models | Unlike conventional anomaly detection research that focuses on point
anomalies, our goal is to detect anomalous collections of individual data
points. In particular, we perform group anomaly detection (GAD) with an
emphasis on irregular group distributions (e.g. irregular mixtures of image
pixels). GAD is an important task in detecting unusual and anomalous phenomena
in real-world applications such as high energy particle physics, social media,
and medical imaging. In this paper, we take a generative approach by proposing
deep generative models: Adversarial autoencoder (AAE) and variational
autoencoder (VAE) for group anomaly detection. Both AAE and VAE detect group
anomalies using point-wise input data where group memberships are known a
priori. We conduct extensive experiments to evaluate our models on real-world
datasets. The empirical results demonstrate that our approach is effective and
robust in detecting group anomalies. | ['Raghavendra Chalapathy', 'Edward Toth', 'Sanjay Chawla'] | 2018-04-13 | null | null | null | null | ['group-anomaly-detection'] | ['methodology'] | [-5.43870069e-02 -7.43600652e-02 7.04574883e-01 -1.95232153e-01
-4.75218862e-01 -1.39961213e-01 8.82481456e-01 5.34896612e-01
-6.22743974e-05 3.76239240e-01 -9.52304229e-02 -3.24437797e-01
5.37545495e-02 -1.05510783e+00 -8.29437852e-01 -8.50943029e-01
-3.40066433e-01 5.68189561e-01 1.36685491e-01 -2.07400262e-01
3.39625508e-01 7.60354340e-01 -1.32767892e+00 -3.46196964e-02
1.05616748e+00 7.34953284e-01 -6.42347455e-01 8.78814876e-01
-1.01248592e-01 7.09745765e-01 -9.75266993e-01 -2.78125703e-01
3.32179010e-01 -4.85334158e-01 -3.38213027e-01 4.38269675e-01
3.13582748e-01 -3.92258346e-01 -3.82619768e-01 1.30644548e+00
4.07721907e-01 5.86576760e-01 1.08923912e+00 -1.79666567e+00
-9.54002798e-01 1.77724771e-02 -7.96778023e-01 7.76777685e-01
6.97495937e-02 2.35564932e-01 7.04026401e-01 -7.97527790e-01
4.80007380e-02 1.07204902e+00 6.95897520e-01 5.43790638e-01
-1.03166115e+00 -4.70328897e-01 5.62305413e-02 3.03527385e-01
-1.18500173e+00 2.68466049e-03 1.14130771e+00 -6.40595675e-01
7.73757100e-01 2.88919032e-01 5.04296005e-01 1.20433128e+00
5.98989666e-01 6.69255733e-01 4.47929502e-01 -2.19734997e-01
6.69202387e-01 -5.06317079e-01 4.77719959e-03 4.21950430e-01
4.56470370e-01 -2.42496375e-02 -1.74025685e-01 -7.48037577e-01
9.01380479e-01 7.31290400e-01 1.19744480e-01 -3.07521746e-02
-1.11386931e+00 1.13597131e+00 3.06519687e-01 3.51106584e-01
-9.09188330e-01 1.62140250e-01 4.96232420e-01 4.59927589e-01
8.27504992e-01 3.32531095e-01 1.55025885e-01 1.78052008e-01
-6.26758993e-01 3.73358935e-01 4.12432492e-01 5.51236987e-01
4.94555056e-01 5.13620079e-01 -1.87948197e-01 8.97078156e-01
4.38656747e-01 4.34760749e-01 6.32928669e-01 -7.23869562e-01
-9.01620314e-02 5.81793129e-01 -1.70329332e-01 -1.16770732e+00
-1.62177980e-01 -1.65141642e-01 -1.26296532e+00 3.82345587e-01
1.89065829e-01 -1.97891369e-01 -1.14709902e+00 1.21869171e+00
4.05023575e-01 8.88565123e-01 1.73880801e-01 4.87558216e-01
8.39290202e-01 8.38727713e-01 1.80632770e-01 -1.09425094e-02
9.38584507e-01 -4.47890639e-01 -7.13952601e-01 -3.55999731e-02
3.65114987e-01 -5.31332731e-01 6.93885863e-01 1.16286896e-01
-8.83578479e-01 -3.63938928e-01 -6.88993633e-01 3.24398190e-01
-3.59474361e-01 -5.11011779e-01 4.17043298e-01 3.80378842e-01
-8.67792845e-01 6.89242959e-01 -1.34294236e+00 -2.68811464e-01
7.52493739e-01 2.04870671e-01 -2.47206256e-01 2.13136896e-01
-7.34752417e-01 3.10840718e-02 2.03222916e-01 -1.18714713e-01
-8.64598691e-01 -7.34191656e-01 -1.01533997e+00 -1.10662699e-01
-2.39006188e-02 -5.85667133e-01 1.01065886e+00 -6.80331051e-01
-8.64604175e-01 7.63425767e-01 -1.90040678e-01 -8.05215895e-01
4.82329816e-01 -2.29936376e-01 -8.89238954e-01 7.75862858e-02
1.54393107e-01 6.98468387e-02 1.03062296e+00 -1.31370151e+00
-4.91770029e-01 -4.76353019e-01 -4.92718965e-01 -2.73797631e-01
-2.57201731e-01 -1.15458451e-01 1.68103278e-01 -8.86311173e-01
5.01356840e-01 -8.64421785e-01 -5.13540387e-01 -2.05638051e-01
-6.73144221e-01 -5.14662683e-01 1.39750350e+00 -6.25922978e-01
8.53754759e-01 -2.26801848e+00 -3.59946460e-01 5.61235785e-01
5.88943839e-01 2.48964485e-02 3.77018213e-01 2.93155909e-01
-1.25800207e-01 3.41392681e-02 -6.88542426e-01 -3.79577756e-01
-4.84585911e-02 5.84496737e-01 -4.51636970e-01 6.54258192e-01
4.00004148e-01 8.15156221e-01 -8.73183072e-01 -2.89279312e-01
3.55093718e-01 1.54089302e-01 -8.49352717e-01 2.88156658e-01
-2.25483701e-01 8.11084986e-01 -5.29565156e-01 9.61836576e-01
8.06094944e-01 -2.21336648e-01 -7.25139797e-01 2.98590302e-01
2.24562868e-01 -4.53707814e-01 -9.85382915e-01 1.06939495e+00
1.64671332e-01 6.62591636e-01 -5.05905211e-01 -1.01801753e+00
9.17236149e-01 2.34374702e-01 1.01805687e+00 -4.32604373e-01
6.24022298e-02 7.96972290e-02 2.36207739e-01 -3.40960145e-01
5.76085865e-01 -3.89961153e-02 7.93861374e-02 6.61503017e-01
-4.86203209e-02 2.68313080e-01 -9.34566371e-03 3.02434802e-01
1.52673149e+00 -8.10006618e-01 8.97614583e-02 -2.57781055e-02
5.55998564e-01 -1.50048926e-01 5.74332893e-01 9.86434162e-01
-3.72659206e-01 9.31734920e-01 4.69923258e-01 -6.81533754e-01
-1.37140560e+00 -1.34807646e+00 -1.04369730e-01 6.00052595e-01
1.10726710e-03 -1.30086631e-01 -6.03737593e-01 -8.80704522e-01
2.50670649e-02 9.66993690e-01 -7.09388793e-01 -3.70921820e-01
-5.34470320e-01 -1.28258538e+00 2.68664002e-01 7.17890561e-01
6.00641012e-01 -1.43107533e+00 -2.27232292e-01 1.03381455e-01
1.73386797e-01 -9.01202857e-01 -2.15787128e-01 -3.83211464e-01
-7.18398511e-01 -1.19607687e+00 -4.82336968e-01 -4.18028653e-01
1.01502931e+00 -1.82756171e-01 1.23444736e+00 1.11276872e-01
-4.80284691e-01 7.15409338e-01 -4.28813398e-01 -1.08349931e+00
-7.10046053e-01 -5.06316364e-01 3.56129289e-01 4.38968927e-01
7.74120033e-01 -7.01597691e-01 -7.34310687e-01 2.90647864e-01
-1.16081595e+00 -7.43284822e-01 3.05166632e-01 7.32166171e-01
9.73327458e-01 4.16320771e-01 4.53875095e-01 -9.40890193e-01
8.32526088e-01 -1.05510414e+00 -3.96687746e-01 -3.13067406e-01
-3.90929997e-01 -4.12324905e-01 4.97545660e-01 -2.91798681e-01
-7.74729311e-01 -5.51510394e-01 -5.99772394e-01 -1.05881739e+00
-6.85965300e-01 5.67673631e-02 6.34529591e-02 9.93792638e-02
7.69127727e-01 4.81566101e-01 2.94969827e-02 -2.17061251e-01
-2.43000329e-01 3.74375433e-01 8.45270336e-01 -3.51786762e-01
8.48897278e-01 8.02300751e-01 1.28753200e-01 -9.94372725e-01
-2.74920970e-01 -5.95408797e-01 -4.20633435e-01 -1.74126238e-01
9.97519135e-01 -6.06671333e-01 -4.57779109e-01 7.72491395e-01
-7.50268519e-01 -1.22182623e-01 -6.48297131e-01 3.40580732e-01
-4.19790328e-01 5.65165460e-01 -5.57982564e-01 -7.65319824e-01
-3.90202940e-01 -9.39916670e-01 1.13145196e+00 2.20306262e-01
-1.18652843e-01 -1.44726181e+00 4.83530581e-01 -1.41581208e-01
2.34512419e-01 1.00227308e+00 7.61081994e-01 -1.46647000e+00
-5.13329744e-01 -5.70688426e-01 1.07634418e-01 5.60877323e-01
2.46783346e-01 2.87346780e-01 -8.97011995e-01 -2.17326194e-01
1.22052953e-01 4.54357743e-01 6.24071002e-01 6.61148250e-01
1.93346012e+00 -2.39667177e-01 -2.60393381e-01 6.07981861e-01
1.18754327e+00 4.88211900e-01 9.02138174e-01 2.23158762e-01
1.06887710e+00 2.42187846e-02 3.38695556e-01 6.56383455e-01
-4.24213186e-02 7.97028765e-02 7.61451840e-01 -1.06222853e-01
3.94263953e-01 -1.17820036e-02 1.89207330e-01 5.81691563e-01
-2.75460541e-01 -5.25787711e-01 -1.20183468e+00 7.53484070e-01
-1.93501925e+00 -1.35620308e+00 -4.73301947e-01 1.98369908e+00
-1.04512833e-01 4.47032452e-02 1.54577807e-01 2.92480677e-01
8.23271990e-01 1.93970069e-01 -7.58546114e-01 -3.94959629e-01
2.88509950e-02 1.80189908e-01 2.66899318e-01 7.14949965e-02
-1.28048480e+00 4.28582311e-01 6.43805456e+00 4.57008481e-01
-6.60926342e-01 1.33361682e-01 7.62307882e-01 6.27690628e-02
-3.82887125e-01 -4.75186497e-01 -2.10538790e-01 8.99538517e-01
8.06162953e-01 -1.66954339e-01 -1.96665764e-01 8.49288523e-01
-1.32533774e-01 2.58288443e-01 -9.89105046e-01 1.02130210e+00
9.06389132e-02 -1.21452081e+00 1.72613218e-01 3.99934113e-01
9.64768648e-01 1.85534120e-01 2.30208427e-01 3.11314523e-01
5.92038929e-01 -9.52205181e-01 -3.95931490e-02 7.50392258e-01
1.02526069e-01 -1.16038239e+00 8.97303581e-01 1.79192290e-01
-5.91582298e-01 2.39735190e-02 -5.16458213e-01 2.66687781e-01
9.58968773e-02 9.07771885e-01 -7.80065596e-01 3.34452063e-01
9.40050542e-01 8.20646405e-01 -5.08492589e-01 9.98286903e-01
1.92289844e-01 9.24399674e-01 -4.18420643e-01 4.21698630e-01
3.00082117e-01 -4.52898800e-01 1.15651441e+00 7.65823603e-01
5.33200026e-01 1.05034955e-01 2.49383137e-01 9.98428285e-01
-9.47074816e-02 -8.63641873e-02 -1.00912023e+00 7.52797499e-02
1.41778320e-01 9.47754145e-01 -8.57787907e-01 -2.66466498e-01
-5.33779442e-01 1.10787642e+00 -2.39950597e-01 3.14586997e-01
-7.59159744e-01 -1.43584922e-01 1.10561812e+00 1.20054096e-01
8.26905444e-02 -1.01685278e-01 -9.68149379e-02 -1.10779583e+00
-1.39467031e-01 -6.92135751e-01 6.87969565e-01 -5.48262477e-01
-1.93219233e+00 4.71276492e-01 -5.05306870e-02 -1.41683006e+00
-5.84866464e-01 -4.34425145e-01 -1.62955248e+00 5.37149429e-01
-9.50472534e-01 -7.65210330e-01 -6.39472008e-01 9.83972609e-01
6.66621506e-01 -7.22488225e-01 6.16882861e-01 2.11280957e-01
-7.66566455e-01 4.99384046e-01 3.94635230e-01 5.46166122e-01
2.24560365e-01 -1.65035009e+00 9.93817151e-01 1.25491631e+00
3.70316207e-01 2.48605594e-01 9.45014417e-01 -9.23063397e-01
-7.61642396e-01 -1.50456381e+00 7.58446306e-02 -7.62250543e-01
6.45736098e-01 -6.11682758e-02 -1.51668155e+00 1.09253347e+00
5.84036075e-02 6.38895690e-01 9.87666905e-01 -5.20662218e-02
2.09210083e-01 4.47804630e-01 -1.50354314e+00 4.77150172e-01
8.26900482e-01 -2.31781304e-01 -4.85048801e-01 6.73323750e-01
3.81176621e-01 -5.38309276e-01 -1.00201309e+00 5.21575987e-01
-2.44887039e-01 -1.11817920e+00 1.10745668e+00 -7.59172499e-01
5.64442456e-01 -3.68308276e-01 -1.24496117e-01 -1.52662253e+00
-3.38194728e-01 -2.82895803e-01 -6.26366675e-01 1.06114697e+00
-1.69124648e-01 -1.00218463e+00 8.38766813e-01 4.05409873e-01
-4.73516077e-01 -5.72519958e-01 -7.39545763e-01 -6.73120201e-01
-3.74600664e-02 -4.80526090e-01 8.44218135e-01 1.10541975e+00
-7.93839991e-01 -3.53999227e-01 -7.82788247e-02 9.27401245e-01
8.92711163e-01 -1.19069569e-01 9.51184988e-01 -1.52218056e+00
-1.46833241e-01 -2.83870280e-01 -1.09679401e+00 -1.48404002e-01
1.62802577e-01 -5.80070317e-01 -1.23911910e-01 -1.31306410e+00
-2.65399635e-01 -2.39075288e-01 -6.08793974e-01 1.42238960e-01
-3.44270557e-01 4.32200551e-01 -4.28201705e-01 3.50631505e-01
-5.35275578e-01 7.48190522e-01 7.18157768e-01 -1.69270083e-01
-1.53637186e-01 3.43172073e-01 -3.97031486e-01 1.23207855e+00
9.68615592e-01 -4.73838151e-01 -2.22862110e-01 -4.59151678e-02
-8.68131518e-02 -5.18887699e-01 9.01615977e-01 -1.30933094e+00
2.03298271e-01 -1.97818931e-02 6.86450422e-01 -8.38286817e-01
-9.65668559e-02 -6.58553541e-01 -5.16518131e-02 2.14577362e-01
1.32616177e-01 4.64478403e-01 2.32347086e-01 1.01240504e+00
-4.28625256e-01 -9.08604413e-02 6.49700463e-01 -1.23704411e-01
-9.81890559e-01 8.71472895e-01 -4.52657223e-01 2.12603807e-02
1.40489614e+00 -8.00228640e-02 -1.99634925e-01 -5.63835025e-01
-1.01325893e+00 2.83241004e-01 4.18024749e-01 2.81146735e-01
8.98747861e-01 -1.55737102e+00 -8.77606928e-01 6.43060029e-01
4.25883263e-01 5.23337483e-01 6.22355044e-01 6.34425521e-01
-8.03301036e-01 -3.81097883e-01 -2.20357433e-01 -1.00621319e+00
-1.14409626e+00 5.26155174e-01 5.46405971e-01 -2.21089683e-02
-1.21977830e+00 6.81023359e-01 3.16264212e-01 -2.08649650e-01
-1.67217344e-01 -5.60725145e-02 -2.22325563e-01 -3.69885206e-01
5.74163973e-01 4.62213248e-01 4.79145050e-02 -6.23692393e-01
-4.39619720e-02 1.51819944e-01 -3.33785743e-01 3.77544731e-01
1.34008443e+00 2.13379040e-01 -1.26884282e-01 5.86061060e-01
8.88659120e-01 5.61901852e-02 -1.07012236e+00 -1.76744699e-01
-2.22577751e-01 -5.03188133e-01 1.53293386e-01 -2.35176086e-02
-1.18669415e+00 6.54061198e-01 8.22005808e-01 7.60782778e-01
1.00374913e+00 3.19816053e-01 9.92224216e-01 3.60591352e-01
-1.65690243e-01 -9.79518473e-01 3.28710824e-01 2.33336970e-01
8.88530910e-01 -1.52501714e+00 -1.83397651e-01 -1.10095330e-01
-5.22209942e-01 6.74970925e-01 7.37405896e-01 -7.65291393e-01
9.62147236e-01 -7.93762729e-02 4.19620238e-02 -7.43721664e-01
-3.85928571e-01 -7.58163333e-02 3.71785581e-01 6.20409608e-01
-6.19726777e-02 -3.95158939e-02 3.14801604e-01 1.97062954e-01
-2.49395296e-01 -6.32672668e-01 5.44823110e-01 9.82567132e-01
-3.51734936e-01 -7.20586121e-01 -7.19039679e-01 1.05493915e+00
-7.77784646e-01 1.79535821e-01 -1.45974398e-01 6.31894231e-01
1.71815738e-01 5.71030796e-01 1.01484966e+00 -1.02923453e-01
3.14769685e-01 2.05245376e-01 -6.40317053e-02 -3.59894663e-01
-2.11627677e-01 -1.67310700e-01 -7.51702249e-01 -4.78924692e-01
-2.00197861e-01 -9.38546538e-01 -1.21040714e+00 -5.68565488e-01
9.74645317e-02 5.16318940e-02 4.69916224e-01 9.42630053e-01
4.08708602e-01 1.04492986e+00 7.03926027e-01 -5.20137608e-01
-1.22943684e-01 -9.22408283e-01 -7.87437141e-01 1.07483232e+00
7.29601145e-01 -6.23743713e-01 -5.99384367e-01 -1.41007692e-01] | [7.617884159088135, 2.3114383220672607] |
0a9782ff-59ba-4610-9691-061d512f0564 | two-level-temporal-relation-model-for-online | 2210.16795 | null | https://arxiv.org/abs/2210.16795v1 | https://arxiv.org/pdf/2210.16795v1.pdf | Two-Level Temporal Relation Model for Online Video Instance Segmentation | In Video Instance Segmentation (VIS), current approaches either focus on the quality of the results, by taking the whole video as input and processing it offline; or on speed, by handling it frame by frame at the cost of competitive performance. In this work, we propose an online method that is on par with the performance of the offline counterparts. We introduce a message-passing graph neural network that encodes objects and relates them through time. We additionally propose a novel module to fuse features from the feature pyramid network with residual connections. Our model, trained end-to-end, achieves state-of-the-art performance on the YouTube-VIS dataset within the online methods. Further experiments on DAVIS demonstrate the generalization capability of our model to the video object segmentation task. Code is available at: \url{https://github.com/caganselim/TLTM} | ['Fatma Güney', 'Jordi Pont-Tuset', 'Oğuzhan Keskin', 'Çağan Selim Çoban'] | 2022-10-30 | null | null | null | null | ['video-instance-segmentation', 'video-object-segmentation'] | ['computer-vision', 'computer-vision'] | [ 7.68317515e-03 -8.05746615e-02 -1.54304922e-01 -3.65379959e-01
-7.49146938e-01 -5.46993911e-01 2.50926226e-01 6.32767975e-02
-4.45536762e-01 2.47476056e-01 -1.40951527e-02 -2.42644757e-01
1.13021418e-01 -6.25250876e-01 -1.08823144e+00 -1.91036478e-01
-2.93098986e-01 1.32346228e-01 5.27253926e-01 8.50783810e-02
1.30406037e-01 4.16367412e-01 -1.50550961e+00 3.76458228e-01
5.70267737e-01 1.26606262e+00 9.76338983e-02 1.01785743e+00
1.12901434e-01 1.14811575e+00 -8.77980068e-02 -6.01047218e-01
6.52299404e-01 -2.68826544e-01 -9.50231433e-01 4.25230563e-01
7.65092731e-01 -8.03282678e-01 -1.01909363e+00 8.65562201e-01
7.89109841e-02 2.11347207e-01 2.40008265e-01 -1.24061286e+00
-6.28898859e-01 4.82489616e-01 -5.52331090e-01 5.25554717e-01
3.88840616e-01 1.74343303e-01 1.07450175e+00 -9.37271118e-01
8.04088712e-01 9.83131826e-01 5.40044248e-01 4.16409701e-01
-1.06959832e+00 -4.40099686e-01 4.09586489e-01 5.51496744e-01
-1.27803707e+00 -5.88945568e-01 4.91747350e-01 -4.97373819e-01
1.01442862e+00 1.37941996e-02 7.99524665e-01 6.79248691e-01
8.17429051e-02 1.24536288e+00 6.15165055e-01 -5.89587875e-02
2.41015088e-02 -2.63711780e-01 3.12704474e-01 9.37438071e-01
1.51032895e-01 -9.00174528e-02 -5.68675339e-01 1.95722565e-01
8.28201473e-01 2.80111521e-01 -5.02090812e-01 -4.93719965e-01
-8.67844284e-01 5.83029032e-01 5.84696352e-01 1.19043626e-01
-4.68264520e-01 6.35139704e-01 4.53576475e-01 2.76757777e-01
5.90988278e-01 -3.09800580e-02 -5.60073376e-01 -3.58568847e-01
-1.17501640e+00 1.62203565e-01 8.92854810e-01 1.20423937e+00
8.97573709e-01 -5.63301034e-02 -2.14486927e-01 3.17606121e-01
2.19700217e-01 1.06213778e-01 2.13279113e-01 -1.29935920e+00
4.57233310e-01 5.07928789e-01 6.53128047e-03 -8.28069985e-01
-2.32512534e-01 -2.17911646e-01 -3.78285348e-01 8.37485269e-02
5.02766013e-01 -2.04984322e-01 -1.05825484e+00 1.52506268e+00
2.99471945e-01 7.22525656e-01 -2.16963068e-01 1.06248152e+00
8.74957263e-01 8.42637360e-01 2.36281082e-02 -5.10650203e-02
1.03219843e+00 -1.48175180e+00 -5.77801466e-01 -5.76892830e-02
5.19553900e-01 -5.62974870e-01 7.95746684e-01 4.20830190e-01
-1.44433558e+00 -6.44359291e-01 -9.01980400e-01 -3.03363889e-01
-3.35120946e-01 2.19351336e-01 6.34241104e-01 4.45277959e-01
-1.51164937e+00 1.07315183e+00 -1.30281770e+00 -3.99926066e-01
7.91810274e-01 5.09755969e-01 -2.00022429e-01 -3.49441841e-02
-6.83317542e-01 3.90975446e-01 3.07951272e-01 1.46511629e-01
-9.59791601e-01 -6.86167777e-01 -8.89274359e-01 2.80917197e-01
5.63234210e-01 -7.05535889e-01 1.40313709e+00 -1.33602595e+00
-1.45200825e+00 5.72523952e-01 -2.59063482e-01 -7.08591700e-01
6.71196818e-01 -5.25525689e-01 -5.73532730e-02 6.74455941e-01
-7.96491727e-02 8.25164795e-01 8.68529677e-01 -1.01706564e+00
-8.69834006e-01 -2.05534503e-01 4.99806255e-01 1.76675022e-01
-3.51172566e-01 2.46791989e-02 -1.07723784e+00 -3.55769664e-01
-1.08899422e-01 -9.34656858e-01 -2.14450330e-01 2.08473876e-01
-1.63113862e-01 -2.15471178e-01 9.05172467e-01 -1.03933620e+00
1.10836208e+00 -2.22446775e+00 1.14753492e-01 -1.15405070e-03
2.93097228e-01 3.73052746e-01 -2.76287913e-01 3.87638509e-01
-7.18691722e-02 8.42351913e-02 -1.69576377e-01 -5.40795267e-01
-8.40527043e-02 -3.89655307e-02 -1.30910248e-01 7.03601778e-01
2.75097102e-01 1.09322727e+00 -8.20554733e-01 -4.99141663e-01
1.81302801e-01 5.72063625e-01 -7.00959682e-01 1.94566458e-01
-1.21825814e-01 1.62995249e-01 -3.74721497e-01 6.25382423e-01
5.73397934e-01 -5.86069226e-01 1.66825309e-01 -2.86746353e-01
-4.38244008e-02 1.38431974e-02 -1.07653964e+00 2.00806546e+00
-5.09233996e-02 8.10288310e-01 1.63905129e-01 -8.41109395e-01
2.40073115e-01 3.12323153e-01 7.21191764e-01 -5.43019772e-01
3.41909796e-01 -3.37373950e-02 -2.45654583e-01 -5.25561929e-01
6.11527085e-01 6.90900922e-01 3.64426881e-01 1.95264921e-01
3.29189152e-01 2.23908976e-01 7.12465882e-01 4.38926607e-01
1.21475852e+00 6.70294285e-01 -6.52687773e-02 -4.62340750e-02
3.67549807e-01 1.30100120e-02 4.33710456e-01 5.37884235e-01
-3.15146983e-01 6.29016399e-01 4.85680223e-01 -3.60676527e-01
-9.24297214e-01 -1.00890779e+00 1.45409003e-01 1.08465338e+00
3.60485524e-01 -6.23295724e-01 -9.78267789e-01 -8.22663367e-01
3.32717411e-02 3.70189965e-01 -4.61448342e-01 1.15790263e-01
-5.85990250e-01 -6.51146621e-02 2.17972726e-01 8.51354241e-01
4.49727237e-01 -8.53631914e-01 -8.50341141e-01 1.61850587e-01
-2.53615528e-02 -1.48781717e+00 -5.91410995e-01 -1.32427201e-01
-9.30905521e-01 -1.16939068e+00 -5.50275385e-01 -6.38738036e-01
5.70818663e-01 5.41946590e-01 1.11626387e+00 3.86167973e-01
-3.01264465e-01 7.52088010e-01 -5.09557962e-01 -3.45586203e-02
3.45390029e-02 7.80616626e-02 -2.60519087e-01 1.00103989e-01
2.77894169e-01 -4.35555130e-01 -9.35488760e-01 2.10819039e-02
-1.05714548e+00 1.29129469e-01 2.91437536e-01 4.62468326e-01
5.75158000e-01 -9.41203013e-02 2.27522507e-01 -8.04680765e-01
1.43868849e-01 -5.00074267e-01 -7.39091575e-01 6.17336668e-02
-3.89610797e-01 -4.91944462e-01 6.23868048e-01 -1.09002396e-01
-6.60715044e-01 3.85981798e-01 -1.26568511e-01 -9.23415661e-01
-6.82019442e-02 4.24925625e-01 1.75266728e-01 -1.81443542e-01
1.94765255e-01 1.99315250e-01 4.20726538e-02 -3.24144930e-01
5.26169837e-01 4.35698330e-01 4.29525256e-01 -2.82361805e-01
7.13306725e-01 6.34380341e-01 -2.19018996e-01 -5.78724980e-01
-8.19054902e-01 -6.55897796e-01 -7.40902841e-01 -4.19502586e-01
9.48081553e-01 -1.21727598e+00 -6.39580846e-01 3.52825344e-01
-1.04290056e+00 -6.33023381e-01 -3.06257039e-01 4.15801585e-01
-8.93861890e-01 4.90781963e-01 -1.08517563e+00 -4.94477272e-01
-2.63512820e-01 -1.15668011e+00 9.58911955e-01 4.49311435e-01
1.43219203e-01 -8.80612493e-01 -3.11945766e-01 4.67575967e-01
1.95715934e-01 1.12911768e-01 2.71357358e-01 -6.12637818e-01
-1.03410649e+00 -2.15590090e-01 -5.51163375e-01 4.50403392e-01
-5.43422215e-02 2.62942433e-01 -9.50511813e-01 -6.04346156e-01
-2.18128577e-01 -3.17325771e-01 1.10740757e+00 6.33454978e-01
1.47495508e+00 -1.86985284e-01 -2.13828281e-01 7.95311987e-01
1.74454844e+00 6.11405335e-02 5.52742004e-01 1.66649595e-01
9.10599589e-01 3.94599229e-01 5.41937768e-01 4.92722720e-01
6.05168760e-01 3.98702502e-01 5.45247316e-01 -1.59993678e-01
-4.25399244e-01 -1.63724914e-01 4.17995751e-01 6.68294489e-01
-3.13893795e-01 -3.93269747e-01 -7.62439489e-01 7.12201118e-01
-2.26726866e+00 -9.49717164e-01 -7.08801746e-02 1.79099667e+00
3.82070214e-01 4.85318638e-02 3.37442935e-01 -1.07636340e-01
6.19505167e-01 1.82541832e-01 -5.03157914e-01 -3.14907342e-01
2.76736617e-01 1.21459454e-01 6.90939367e-01 3.21864396e-01
-1.29437602e+00 1.15402400e+00 5.90104914e+00 7.25526512e-01
-1.12960124e+00 2.64619350e-01 7.59357154e-01 -3.48098308e-01
1.28782317e-01 8.43525380e-02 -6.44994140e-01 2.50819117e-01
1.02690709e+00 -1.55423969e-01 7.42218375e-01 8.26908827e-01
2.69180000e-01 -8.30392390e-02 -1.36286318e+00 1.00317311e+00
2.20727518e-01 -1.52469778e+00 -4.26098444e-02 -7.83498883e-02
6.52072668e-01 2.51518756e-01 -6.04245737e-02 1.94597796e-01
1.61798559e-02 -7.71138787e-01 1.02611494e+00 4.95068818e-01
6.82809532e-01 -5.97677827e-01 5.71878195e-01 1.62293352e-02
-1.42283189e+00 -1.56543672e-01 -2.14561656e-01 -1.87573612e-01
2.08905280e-01 1.77857831e-01 -5.72284400e-01 7.07561970e-01
9.74165857e-01 1.14719796e+00 -8.60180259e-01 1.27507484e+00
-8.55321214e-02 7.92616785e-01 -2.07614288e-01 2.12901041e-01
3.55125099e-01 -2.67016828e-01 3.80305946e-01 1.40387738e+00
1.83879346e-01 1.61712587e-01 5.59115887e-01 6.91597462e-01
-2.81315178e-01 1.86975941e-01 -5.22249639e-01 -3.24862152e-01
2.18944460e-01 1.39853311e+00 -1.05000257e+00 -5.93016505e-01
-7.27691829e-01 1.01994944e+00 4.62430000e-01 5.75356960e-01
-1.02104056e+00 -3.14954519e-01 4.32007074e-01 5.38517460e-02
9.14640307e-01 -4.24818516e-01 -8.11828598e-02 -1.15642893e+00
1.98277816e-01 -6.48729205e-01 3.42724144e-01 -6.13775253e-01
-1.08986163e+00 4.98003185e-01 -6.06547035e-02 -1.15915835e+00
-4.32846323e-02 -7.07891285e-01 -4.60360557e-01 3.20738733e-01
-1.67074251e+00 -1.07186043e+00 -3.67813945e-01 7.72578299e-01
8.41033161e-01 2.18534574e-01 3.25336337e-01 5.06195784e-01
-6.30024612e-01 4.82224643e-01 -5.32175638e-02 4.74621952e-01
3.18709105e-01 -1.00764096e+00 4.81611699e-01 1.11625469e+00
3.15240055e-01 2.55921423e-01 3.99151981e-01 -5.39572060e-01
-1.69478905e+00 -1.27577507e+00 4.52346563e-01 -2.51019150e-01
8.40374291e-01 -2.67955482e-01 -7.94926047e-01 9.98645663e-01
4.75715220e-01 2.80151755e-01 4.42779541e-01 -1.85966998e-01
-2.39307985e-01 -4.65839915e-03 -9.33828056e-01 5.23796380e-01
1.24282682e+00 -3.65093261e-01 -2.41091847e-01 4.80225354e-01
8.77139568e-01 -6.68860197e-01 -8.09709489e-01 1.93892390e-01
4.80996639e-01 -1.06229413e+00 7.57082820e-01 -6.77890837e-01
6.54220819e-01 -3.04382920e-01 -2.24393055e-01 -8.55641961e-01
-4.50180948e-01 -6.20741308e-01 -4.55064893e-01 9.72284734e-01
3.15022886e-01 -4.39360887e-01 8.61828566e-01 5.54709613e-01
-1.62356809e-01 -1.04644108e+00 -7.85391510e-01 -7.39759326e-01
-1.97799996e-01 -5.63812017e-01 3.59715551e-01 5.54490924e-01
-2.15803310e-01 1.81603320e-02 -1.46809965e-01 2.18055323e-01
5.96084952e-01 2.44122535e-01 7.18104362e-01 -8.21705759e-01
-4.49458539e-01 -3.65834743e-01 -5.97870767e-01 -1.20501614e+00
1.87977254e-01 -9.18917418e-01 -6.57370687e-02 -1.76450026e+00
2.26893187e-01 5.29728681e-02 -3.48066390e-01 5.37785530e-01
-4.28630821e-02 4.93282199e-01 7.53413677e-01 1.59040853e-01
-1.10446751e+00 2.95559973e-01 1.13091862e+00 -5.50898872e-02
-8.25599656e-02 -2.13913888e-01 -5.09894133e-01 7.63764441e-01
8.63205433e-01 -2.70316452e-01 -3.21424425e-01 -8.12750995e-01
-4.11985107e-02 2.14853734e-01 4.38033462e-01 -1.19274282e+00
3.34576994e-01 5.40844947e-02 3.82380426e-01 -5.20090520e-01
4.56296742e-01 -8.24304461e-01 -1.28909558e-01 3.74345660e-01
-1.38355255e-01 2.79888093e-01 2.02202097e-01 7.31698275e-01
-1.12794623e-01 -1.40992358e-01 5.88323772e-01 -4.83196713e-02
-9.51792121e-01 7.89712429e-01 -3.11925083e-01 2.60337163e-02
1.18075836e+00 -4.17670190e-01 -2.84735590e-01 -4.40268129e-01
-6.85008228e-01 4.82175708e-01 5.84776640e-01 4.11094904e-01
6.99036896e-01 -1.01700807e+00 -6.59454286e-01 3.49706374e-02
-2.74480820e-01 -1.08248420e-01 3.33544582e-01 1.06643605e+00
-8.08832049e-01 1.62134692e-01 -1.05604835e-01 -7.03150868e-01
-1.24580848e+00 6.29507005e-01 1.77860707e-01 1.55197000e-02
-7.63390839e-01 9.10876095e-01 5.32116853e-02 1.88508585e-01
3.82977664e-01 -2.37197667e-01 -2.06731483e-01 4.24364619e-02
4.03176665e-01 4.19885486e-01 -3.36481258e-02 -6.42503917e-01
-2.99889207e-01 5.98877668e-01 -1.26090646e-01 1.42360628e-01
1.48909485e+00 -2.52217472e-01 -3.90631221e-02 3.43826830e-01
1.31635773e+00 -2.59988815e-01 -1.71814406e+00 -1.27428651e-01
-9.16373357e-02 -7.36279249e-01 2.28399988e-02 -3.63839924e-01
-1.50314748e+00 5.95733821e-01 6.21972382e-01 2.37780839e-01
1.26661289e+00 -4.57340181e-02 1.02431428e+00 3.53074461e-01
1.84767947e-01 -1.14341080e+00 1.07507184e-02 4.83037829e-01
5.66092014e-01 -1.18795478e+00 1.13871008e-01 -5.98976374e-01
-5.19173861e-01 1.26309752e+00 5.10210991e-01 -7.45980322e-01
7.75323808e-01 1.86979443e-01 9.05124843e-03 -1.70197293e-01
-8.66234004e-01 -2.95209944e-01 2.29350880e-01 2.03193918e-01
4.47753936e-01 -1.46489009e-01 -3.74088883e-01 3.03651929e-01
2.86348425e-02 4.41491753e-01 6.33357108e-01 1.15703607e+00
-2.81325489e-01 -8.41436088e-01 7.81375542e-02 5.66207349e-01
-5.79755008e-01 -2.51864605e-02 -1.34880960e-01 6.74608231e-01
-4.72697057e-02 1.06062496e+00 2.71507233e-01 -3.09245527e-01
3.34941864e-01 -8.87714624e-02 5.39369881e-01 -4.39275146e-01
-6.69639111e-01 1.13609448e-01 9.40040126e-02 -1.17033589e+00
-5.96725941e-01 -6.32568955e-01 -1.43229389e+00 -2.82198310e-01
-2.16320455e-01 -1.42036080e-01 5.40784299e-01 7.01012492e-01
5.83992124e-01 6.47833407e-01 6.10307813e-01 -1.25032794e+00
-3.18249553e-01 -5.80153346e-01 -3.92842770e-01 5.34539878e-01
2.70702958e-01 -3.52957338e-01 -1.65422559e-01 4.31773126e-01] | [9.143362045288086, -0.018099702894687653] |
5f793a38-3590-4080-b6de-62a9fdcc3a41 | analysis-of-nuanced-stances-and-sentiment | null | null | https://aclanthology.org/2021.socialnlp-1.1 | https://aclanthology.org/2021.socialnlp-1.1.pdf | Analysis of Nuanced Stances and Sentiment Towards Entities of US Politicians through the Lens of Moral Foundation Theory | The Moral Foundation Theory suggests five moral foundations that can capture the view of a user on a particular issue. It is widely used to identify sentence-level sentiment. In this paper, we study the Moral Foundation Theory in tweets by US politicians on two politically divisive issues - Gun Control and Immigration. We define the nuanced stance of politicians on these two topics by the grades given by related organizations to the politicians. First, we identify moral foundations in tweets from a huge corpus using deep relational learning. Then, qualitative and quantitative evaluations using the corpus show that there is a strong correlation between the moral foundation usage and the politicians’ nuanced stance on a particular topic. We also found substantial differences in moral foundation usage by different political parties when they address different entities. All of these results indicate the need for more intense research in this area. | ['Dan Goldwasser', 'Shamik Roy'] | null | null | null | null | naacl-socialnlp-2021-6 | ['relational-reasoning'] | ['natural-language-processing'] | [-6.36907220e-01 4.25332665e-01 -7.12768793e-01 -4.96735930e-01
-4.08502698e-01 -5.20498455e-01 9.63150263e-01 6.56813800e-01
-3.84797066e-01 3.55107307e-01 1.22106266e+00 -3.58135223e-01
-8.68889019e-02 -1.11978519e+00 -3.19216341e-01 -4.50078964e-01
3.59760910e-01 3.71806234e-01 -1.66021451e-01 -8.06292951e-01
5.88423371e-01 -4.71381322e-02 -1.02005219e+00 5.17558277e-01
6.81324780e-01 5.49222469e-01 -5.53128779e-01 8.44996050e-03
-2.64105082e-01 1.35726738e+00 -5.65680027e-01 -1.12597990e+00
-1.11660235e-01 -8.21683332e-02 -1.16425419e+00 -3.71488541e-01
7.88538396e-01 -2.15192717e-02 -1.86283663e-01 1.18362796e+00
2.66716927e-01 -1.16832912e-01 8.93629730e-01 -9.03739691e-01
-8.11802924e-01 1.07945561e+00 -7.55986989e-01 6.49944961e-01
2.24078938e-01 -3.14094156e-01 1.85110915e+00 -4.93808329e-01
9.94608283e-01 1.47250998e+00 9.15547431e-01 1.32479966e-01
-1.10072029e+00 -6.33262336e-01 -6.50891736e-02 -1.34802356e-01
-9.14336920e-01 -2.20556557e-01 5.21950841e-01 -1.21273386e+00
5.59348047e-01 1.28340662e-01 3.91286820e-01 1.16030765e+00
5.00452220e-01 2.72098258e-02 1.28967798e+00 -2.12690607e-01
1.39696943e-02 6.22429729e-01 7.41284847e-01 3.80648136e-01
7.74880469e-01 -5.30657709e-01 -2.98359424e-01 -6.33179486e-01
1.21139899e-01 -1.75823912e-01 2.59052813e-01 3.70307535e-01
-8.23824823e-01 1.51555729e+00 4.48915064e-01 6.47769928e-01
-5.97573578e-01 1.87727869e-01 7.04909563e-01 2.37445235e-01
8.51944029e-01 5.01180649e-01 1.69410892e-02 -1.28748044e-01
-5.40054083e-01 2.81011611e-01 1.07963026e+00 2.30590776e-01
7.74802923e-01 -5.98870575e-01 -1.33917809e-01 5.77664912e-01
3.32384139e-01 3.30534011e-01 -1.46931812e-01 -1.34417737e+00
5.15242457e-01 6.72481000e-01 2.42472783e-01 -1.99210668e+00
-3.91062558e-01 -3.75990182e-01 -5.38361311e-01 -1.50495380e-01
5.01542985e-01 -4.13373023e-01 4.36757654e-02 1.75058544e+00
2.63050586e-01 -3.24114442e-01 3.41880843e-02 7.13642776e-01
1.23280096e+00 6.95728302e-01 3.12408298e-01 -6.68363869e-02
1.92318392e+00 -4.15936053e-01 -8.79594684e-01 -2.47980282e-01
6.75849974e-01 -7.54677773e-01 8.05686295e-01 1.55450106e-01
-8.56019855e-01 -9.91005450e-02 -5.42118132e-01 -1.21933691e-01
-3.61471772e-01 -1.58578362e-02 9.43909049e-01 6.24590337e-01
-7.02058852e-01 6.66043699e-01 -1.00405596e-01 -6.30739510e-01
3.82741511e-01 -1.87954277e-01 -1.68261230e-01 4.32602197e-01
-1.73756719e+00 1.03712785e+00 -1.96925253e-01 -4.20825273e-01
-2.95829654e-01 -2.12245747e-01 -6.08977675e-01 -2.17569232e-01
1.43035963e-01 -4.20432508e-01 1.02437484e+00 -8.66588235e-01
-8.30920279e-01 1.67798257e+00 2.90823393e-02 -2.44826123e-01
2.00004682e-01 -3.21332008e-01 -5.07336318e-01 7.59866685e-02
9.97950852e-01 7.36267343e-02 5.67857504e-01 -9.95611906e-01
-8.64081144e-01 -3.01422715e-01 7.84832478e-01 -8.62391368e-02
-7.50068724e-01 8.07605803e-01 1.78117022e-01 -3.09858322e-01
-8.56401175e-02 -7.26887405e-01 -1.15093984e-01 -9.05578434e-01
-3.34292740e-01 -9.01689291e-01 9.66280028e-02 -4.41757560e-01
1.62458968e+00 -2.07246470e+00 -1.49145707e-01 1.11541420e-01
4.80604321e-01 -1.24512263e-01 5.38028240e-01 9.47142303e-01
-1.30305840e-02 8.77114952e-01 5.63747287e-01 4.57511842e-02
1.08336270e-01 2.00525403e-01 -8.18088233e-01 8.08467090e-01
-2.30631128e-01 3.28577429e-01 -1.05819368e+00 -7.07835793e-01
-6.25451684e-01 1.27195790e-01 -6.86523974e-01 -3.88815999e-01
6.29437342e-02 1.90724075e-01 -7.25193977e-01 3.36829275e-01
4.46699560e-01 -3.35217685e-01 3.32119703e-01 -2.47984633e-01
-4.98863190e-01 9.52976286e-01 -3.87385905e-01 7.91492462e-01
-1.85176209e-01 1.04919171e+00 2.65749633e-01 -7.93898761e-01
9.07568455e-01 5.20174563e-01 2.92206854e-01 -4.22535449e-01
5.83198667e-01 1.98253408e-01 1.05945520e-01 -5.62513947e-01
9.51067626e-01 -5.97607493e-01 -7.20445871e-01 9.36010838e-01
-5.78876913e-01 9.31399874e-03 1.23867340e-01 4.75685418e-01
7.31623888e-01 -4.27730590e-01 1.81056798e-01 -7.79982090e-01
5.45083284e-01 2.87646621e-01 9.33752000e-01 4.81398076e-01
-4.31105286e-01 -7.67279230e-03 1.31398058e+00 -9.15423810e-01
-7.91968226e-01 -4.68528301e-01 -4.17672515e-01 1.47006762e+00
2.16402873e-01 -6.35257244e-01 -6.49961770e-01 -5.59132397e-01
6.19005188e-02 9.26031590e-01 -9.70925331e-01 3.08005482e-01
-6.91591799e-01 -8.40264320e-01 4.19285774e-01 4.33154777e-02
3.43533367e-01 -7.91366994e-01 -6.66309893e-01 -2.01649040e-01
-7.89615333e-01 -1.26509106e+00 5.85332774e-02 -1.67816445e-01
-5.36164403e-01 -9.20688510e-01 -1.63549021e-01 -5.82881272e-01
6.43212557e-01 2.78230697e-01 1.27218473e+00 6.67871386e-02
2.75359720e-01 1.14797458e-01 -3.66807401e-01 -5.43665767e-01
-6.81568563e-01 2.23160490e-01 4.44209278e-01 2.83963699e-03
8.07500243e-01 -3.56473655e-01 -2.81481415e-01 1.54012337e-01
-4.33396190e-01 -2.53124028e-01 -2.29355782e-01 2.35190257e-01
-2.19997421e-01 2.49322310e-01 4.29912776e-01 -1.14545476e+00
1.02116978e+00 -9.69172299e-01 -7.47271851e-02 -2.27921546e-01
-4.26750749e-01 -2.67581880e-01 2.95706570e-01 1.54793948e-01
-9.22527969e-01 -1.19178689e+00 7.37811625e-02 7.03838110e-01
2.03822136e-01 8.21341634e-01 4.61102962e-01 4.73274112e-01
1.07615685e+00 -7.67279625e-01 -1.65640488e-01 -1.32234335e-01
1.26709387e-01 8.76043618e-01 2.06753269e-01 -9.34769571e-01
6.75221026e-01 9.21402574e-01 -2.54677087e-01 -8.98392618e-01
-1.66005409e+00 -4.22380835e-01 -1.91730395e-01 -4.27147031e-01
1.18856359e+00 -1.07990324e+00 -1.02690625e+00 -9.19982791e-02
-1.42446065e+00 1.79535314e-01 1.30809322e-01 6.61611676e-01
-1.85266703e-01 3.71511042e-01 -7.81217337e-01 -6.52971148e-01
-4.62490290e-01 -7.26659715e-01 4.96972054e-01 1.74873963e-01
-9.56406236e-01 -1.26031852e+00 5.78124940e-01 9.86622870e-01
2.40065098e-01 5.53291500e-01 1.02727878e+00 -5.62159181e-01
2.93002695e-01 -6.86042085e-02 -2.84266353e-01 1.11295305e-01
2.09963456e-01 3.68869424e-01 -6.83002114e-01 3.86752822e-02
1.71739727e-01 -5.01018465e-01 6.65574431e-01 3.81103605e-01
3.59503068e-02 -6.72562540e-01 -2.22239390e-01 7.76632726e-02
1.37076366e+00 -4.62667376e-01 4.40724999e-01 1.10309768e+00
3.95499706e-01 1.18500459e+00 6.73313320e-01 5.63052118e-01
7.25275397e-01 3.79302442e-01 3.72978598e-01 9.14375857e-02
5.32389641e-01 -1.52397305e-01 7.22636223e-01 6.70556486e-01
-6.05360806e-01 1.56823799e-01 -1.30108488e+00 6.77099109e-01
-1.84784293e+00 -1.43808556e+00 -8.43468487e-01 1.56532633e+00
7.28025556e-01 3.41546923e-01 1.23090863e-01 -2.30656728e-01
1.04318810e+00 6.14315689e-01 2.97582597e-01 -1.00740802e+00
-1.03664853e-01 -3.36992651e-01 5.03549933e-01 6.73270404e-01
-1.19991767e+00 1.13426197e+00 6.49467421e+00 4.59225684e-01
-9.07974184e-01 2.75123477e-01 8.64328980e-01 2.05790222e-01
-5.83332241e-01 2.60895312e-01 -9.07834888e-01 2.00593591e-01
8.11042726e-01 -4.97474879e-01 -2.74178654e-01 8.10549498e-01
4.82162118e-01 -3.17624956e-01 -6.66201293e-01 4.37753052e-01
-5.13142832e-02 -1.49578011e+00 -4.34354931e-01 4.73077416e-01
9.15933132e-01 1.89205632e-01 2.96130240e-01 1.38043061e-01
9.08473551e-01 -9.00740623e-01 7.52739727e-01 3.05767179e-01
3.99849147e-01 -5.13949990e-01 9.65202987e-01 3.38247031e-01
-3.55135649e-01 -1.36228487e-01 -6.57360196e-01 -7.67630160e-01
3.58834475e-01 8.01130891e-01 -5.67453504e-01 4.85343263e-02
9.24600065e-01 6.20394766e-01 -1.43948138e-01 -3.23431082e-02
-5.49491227e-01 9.02995408e-01 3.29317972e-02 -8.50200579e-02
7.47735083e-01 -4.99987841e-01 5.18496454e-01 1.32266271e+00
-1.55114889e-01 1.32215485e-01 -2.48600274e-01 7.61183202e-01
-4.86301072e-02 2.57134140e-01 -8.06381464e-01 -2.19149634e-01
1.86440259e-01 1.73195386e+00 -8.79265904e-01 -3.16995949e-01
-4.31242228e-01 2.54189730e-01 4.80272412e-01 7.08685219e-02
-9.36392188e-01 7.27443909e-03 8.69391620e-01 5.97396791e-01
-8.66911262e-02 -6.81308210e-02 -5.02366066e-01 -9.49213624e-01
-4.65877861e-01 -6.92596436e-01 4.26753491e-01 -4.44167018e-01
-1.49038076e+00 4.89927173e-01 -4.21940498e-02 -6.27790213e-01
1.51344016e-01 -3.79090190e-01 -1.05574000e+00 5.49383283e-01
-1.33485663e+00 -9.04859662e-01 -1.83302432e-01 1.27999946e-01
-3.04329574e-01 -1.28386095e-01 6.51975691e-01 8.59300047e-02
-6.72709584e-01 -8.36955570e-03 -3.10551852e-01 5.28859198e-01
8.52819026e-01 -9.82805729e-01 2.68611699e-01 3.20785910e-01
-2.82112926e-01 9.03090298e-01 1.15848446e+00 -7.22464144e-01
-6.75391078e-01 -6.53406501e-01 1.83295524e+00 -8.69178355e-01
1.19878840e+00 9.73169059e-02 -3.77509534e-01 6.81775510e-01
8.04722071e-01 -7.44896054e-01 1.44943976e+00 9.60387111e-01
-6.14340305e-01 8.76231343e-02 -1.05253279e+00 6.33044720e-01
7.03232586e-01 -6.22423053e-01 -1.34773207e+00 7.07081378e-01
5.16860187e-01 3.31754297e-01 -9.50115025e-01 1.68503821e-02
3.10321420e-01 -1.26988280e+00 6.63510978e-01 -8.91380966e-01
1.15471292e+00 1.63618490e-01 -2.87468255e-01 -9.56378818e-01
-9.44484472e-01 -5.22985101e-01 6.53172314e-01 1.46951330e+00
4.21626270e-01 -7.01075077e-01 6.15453660e-01 8.64015460e-01
2.24136263e-01 -5.20252585e-01 -7.27491021e-01 -1.76392674e-01
6.18583858e-01 -3.23824197e-01 3.11131328e-01 1.65496302e+00
6.40378237e-01 8.58888984e-01 -1.01438977e-01 4.43145720e-04
4.64420646e-01 4.01384294e-01 8.98623049e-01 -1.58680081e+00
1.18274070e-01 -5.40027797e-01 -1.71254158e-01 -2.72372574e-01
4.43319827e-01 -1.07506156e+00 -7.17497528e-01 -1.96248913e+00
3.83302182e-01 -3.85301590e-01 1.01963155e-01 1.94904327e-01
5.92064895e-02 2.45986017e-03 -1.07099235e-01 5.24956703e-01
-3.99202943e-01 1.25986755e-01 9.80799496e-01 -3.78386751e-02
-3.86183038e-02 -1.67143211e-01 -1.59542620e+00 1.39476132e+00
9.49931145e-01 -6.50815487e-01 2.42090672e-01 -4.23577458e-01
1.40702629e+00 -4.11396265e-01 1.29197761e-01 -3.65571111e-01
1.01376902e-02 -6.37771130e-01 -3.68090779e-01 -4.24770117e-01
-7.54387230e-02 -5.53716302e-01 -1.81002572e-01 5.18404067e-01
-3.33431572e-01 2.14673609e-01 -2.24816144e-01 1.99768350e-01
-3.78657788e-01 -4.13144410e-01 6.45331919e-01 -2.89457828e-01
-2.45126009e-01 -1.77014127e-01 -5.67493081e-01 5.72488606e-01
1.01297784e+00 -5.03421463e-02 -6.42887056e-01 -6.98926628e-01
-4.25995141e-01 -1.92083810e-02 4.93393868e-01 1.74642757e-01
8.23447853e-02 -1.30252123e+00 -1.36832631e+00 -7.77867675e-01
-8.56974423e-02 -5.02106607e-01 9.17288102e-03 1.26047754e+00
-7.07485080e-01 4.36595500e-01 3.74235660e-02 -9.39958394e-02
-1.11371446e+00 2.30939433e-01 9.89921913e-02 -3.28571171e-01
-3.76235515e-01 9.02888834e-01 2.29464024e-01 -3.87089193e-01
-2.48370245e-01 1.88173819e-02 -9.70081329e-01 1.19963336e+00
3.07163715e-01 6.74405932e-01 -6.82337046e-01 -1.31494904e+00
-5.13061941e-01 6.87138140e-01 -9.84598398e-02 -8.22191462e-02
1.59698749e+00 5.72549440e-02 -9.38363671e-01 5.79055190e-01
1.12407041e+00 6.90330744e-01 -2.96458215e-01 -2.94528097e-01
2.37640470e-01 -5.15498698e-01 1.44075770e-02 -1.17119186e-01
-7.58987427e-01 6.27842426e-01 -4.45886374e-01 8.13965380e-01
2.51612067e-01 3.10703605e-01 6.78021371e-01 1.24493308e-01
2.57639796e-01 -1.84200799e+00 3.56341302e-02 8.74982178e-01
9.05592203e-01 -1.06412959e+00 4.02337343e-01 -4.93002385e-01
-1.02283525e+00 9.97153461e-01 4.62252051e-01 -2.66486287e-01
6.62232339e-01 -1.24874912e-01 3.98061156e-01 -9.06219661e-01
-7.43074894e-01 1.44418448e-01 -1.34160936e-01 -5.84382936e-03
9.81095672e-01 4.28957254e-01 -1.07079899e+00 7.43251383e-01
-6.50787354e-01 -3.44736934e-01 1.16041315e+00 3.42050940e-01
-6.63942873e-01 -7.42297947e-01 -5.66717148e-01 1.82849064e-01
-1.18675280e+00 -2.10083276e-01 -7.81563401e-01 5.10300577e-01
3.95910233e-01 1.17604494e+00 2.06139386e-01 -5.68596661e-01
-4.02504429e-02 -3.80644530e-01 -2.39947811e-01 -9.07093823e-01
-1.09489870e+00 -1.52221695e-01 8.24754834e-01 -1.88372195e-01
-7.70735025e-01 -9.74361539e-01 -1.29961908e+00 -9.37572300e-01
-2.06107542e-01 5.27655363e-01 3.94269913e-01 7.69673765e-01
2.50801176e-01 1.26965925e-01 7.14544773e-01 2.26525106e-02
-5.32551765e-01 -8.50887597e-01 -5.28166175e-01 5.27985990e-01
8.04383904e-02 -5.60221851e-01 -7.85583854e-01 -3.87243629e-01] | [8.950910568237305, 10.021453857421875] |
afab0552-cd68-4ac1-8562-5ee4b74db053 | multi-modal-hypergraph-diffusion-network-with | 2204.02399 | null | https://arxiv.org/abs/2204.02399v3 | https://arxiv.org/pdf/2204.02399v3.pdf | Multi-Modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification | The automatic early diagnosis of prodromal stages of Alzheimer's disease is of great relevance for patient treatment to improve quality of life. We address this problem as a multi-modal classification task. Multi-modal data provides richer and complementary information. However, existing techniques only consider either lower order relations between the data and single/multi-modal imaging data. In this work, we introduce a novel semi-supervised hypergraph learning framework for Alzheimer's disease diagnosis. Our framework allows for higher-order relations among multi-modal imaging and non-imaging data whilst requiring a tiny labelled set. Firstly, we introduce a dual embedding strategy for constructing a robust hypergraph that preserves the data semantics. We achieve this by enforcing perturbation invariance at the image and graph levels using a contrastive based mechanism. Secondly, we present a dynamically adjusted hypergraph diffusion model, via a semi-explicit flow, to improve the predictive uncertainty. We demonstrate, through our experiments, that our framework is able to outperform current techniques for Alzheimer's disease diagnosis. | ['Carola-Bibiane Schönlieb', 'Zoe Kourtzi', 'Nicolas Papadakis', 'Christina Runkel', 'Angelica I. Aviles-Rivero'] | 2022-04-04 | null | null | null | null | ['multi-modal-classification'] | ['miscellaneous'] | [ 3.45925152e-01 4.24010873e-01 -1.32445619e-01 -4.22462493e-01
-7.45204389e-01 -3.26412737e-01 6.56798601e-01 4.00759250e-01
-3.33808631e-01 5.63153803e-01 3.56085598e-01 -3.30646262e-02
-7.87004948e-01 -7.82532632e-01 -2.04105645e-01 -8.10809553e-01
-5.12859643e-01 8.66839468e-01 5.31644046e-01 -1.67372122e-01
-1.09502800e-01 5.36747456e-01 -1.24725580e+00 3.90908360e-01
8.57139230e-01 7.74547756e-01 1.35294139e-01 6.85301483e-01
2.23602280e-01 6.09687924e-01 7.19949827e-02 -3.70433837e-01
2.79432744e-01 -3.10374439e-01 -1.16732407e+00 2.82847971e-01
4.54910129e-01 -1.78629354e-01 -4.57771182e-01 1.23754311e+00
7.05590427e-01 -3.38275701e-01 9.10589218e-01 -1.24763870e+00
-4.48123485e-01 3.58636349e-01 -5.17534196e-01 5.42002976e-01
2.52904564e-01 -1.17787428e-01 1.22818446e+00 -2.90737331e-01
9.01088357e-01 1.21373904e+00 6.20922208e-01 5.60082614e-01
-1.56210482e+00 -4.69692871e-02 2.50547733e-02 6.01553380e-01
-1.06648910e+00 -2.47352615e-01 1.00749493e+00 -7.55596101e-01
4.90214586e-01 3.60740453e-01 9.41619754e-01 1.05881560e+00
6.56694889e-01 4.05534148e-01 1.41696167e+00 -5.31866908e-01
2.73747683e-01 1.92618091e-02 4.69308257e-01 1.05157566e+00
2.05101520e-01 6.43592924e-02 -1.77854508e-01 -6.21832132e-01
6.73233271e-01 6.70554638e-02 -4.72588778e-01 -8.98969889e-01
-1.28025603e+00 1.11617076e+00 5.29323876e-01 5.90793610e-01
-4.73559797e-01 -1.47411451e-01 4.10815835e-01 3.16516846e-01
6.06045783e-01 4.20246869e-02 -2.66118329e-02 4.78723615e-01
-9.38789427e-01 1.02280706e-01 6.98665917e-01 5.68842173e-01
5.13651550e-01 -4.51236099e-01 1.66422520e-02 7.71351695e-01
7.60737240e-01 1.48990452e-01 6.70113087e-01 -9.74701047e-01
2.05196276e-01 7.30431736e-01 -5.18222988e-01 -8.96394372e-01
-7.54888296e-01 -3.82258296e-01 -1.19874108e+00 3.94157231e-01
3.62789690e-01 2.51611859e-01 -7.91378319e-01 1.61374986e+00
4.32528704e-01 1.78041115e-01 1.24543821e-02 7.92779505e-01
4.13886189e-01 9.76775587e-02 4.65765484e-02 -5.17729223e-01
1.74755538e+00 -6.54419184e-01 -6.65646195e-01 9.33629926e-03
6.69085205e-01 -2.14434713e-01 8.37581575e-01 1.82200268e-01
-9.25908566e-01 1.21004991e-01 -8.87260318e-01 -4.93924953e-02
-2.85198003e-01 -1.55602083e-01 4.80582923e-01 6.67222142e-01
-1.27720749e+00 6.10756040e-01 -1.00498009e+00 -3.70110691e-01
5.30450702e-01 4.30710137e-01 -6.76150680e-01 -2.43400574e-01
-1.34631395e+00 1.00237846e+00 3.13666165e-01 -1.30950481e-01
-5.43472052e-01 -8.95780921e-01 -7.46610582e-01 -2.24495336e-01
2.65970618e-01 -1.13133693e+00 5.79846919e-01 -5.86356759e-01
-9.99459386e-01 1.13322794e+00 7.22906590e-02 -5.57935953e-01
7.67047763e-01 2.13586092e-01 -3.49052161e-01 7.92306244e-01
1.05711810e-01 4.46383089e-01 8.63592684e-01 -1.35052204e+00
-3.23682368e-01 -9.78316665e-01 9.64379534e-02 1.05459392e-01
-4.45155203e-01 -1.54449716e-01 8.78797919e-02 -6.71680808e-01
2.78084993e-01 -1.14941692e+00 -5.95660925e-01 2.35647514e-01
-4.50726658e-01 -1.90441646e-02 8.07180882e-01 -7.51992106e-01
1.09668911e+00 -1.81342602e+00 7.22782791e-01 5.52252293e-01
1.07063329e+00 -8.80194232e-02 1.46030262e-01 6.37697205e-02
-2.72872031e-01 1.08267792e-01 -6.72802806e-01 -2.56835133e-01
-9.85163823e-03 4.24086750e-01 3.48569721e-01 7.00682640e-01
1.26014933e-01 7.75685310e-01 -8.71954381e-01 -7.93117523e-01
1.73211470e-01 7.29016364e-01 -5.12609720e-01 -1.67320162e-01
-2.31997482e-02 4.56055999e-01 -4.94430095e-01 4.18124139e-01
4.03534383e-01 -5.90134323e-01 3.70357305e-01 -6.10774040e-01
2.37397224e-01 -2.79609978e-01 -1.00821829e+00 1.71838558e+00
-2.79645294e-01 4.59616892e-02 9.02290717e-02 -1.20537806e+00
4.05108154e-01 4.23330724e-01 1.11922419e+00 -4.80986476e-01
6.56661810e-04 1.05635516e-01 2.33324692e-01 -5.83668530e-01
-8.65470916e-02 -2.75761813e-01 2.04535201e-01 5.52052259e-01
-6.95897732e-03 2.29263663e-01 2.47754261e-01 4.71089274e-01
1.47955906e+00 -4.32501882e-01 3.91823977e-01 -5.29876471e-01
6.40370131e-01 -2.72879064e-01 4.61046606e-01 4.37312871e-01
-4.10876393e-01 5.66741943e-01 7.07114458e-01 -3.27066690e-01
-1.03668463e+00 -1.09647119e+00 -4.30168808e-01 4.52265263e-01
-1.47273943e-01 -4.81033534e-01 -6.86095953e-01 -1.02765429e+00
4.12823148e-02 2.82528549e-01 -7.82309413e-01 -2.98906714e-01
-4.66348529e-01 -1.34628749e+00 2.67891973e-01 3.17333996e-01
2.50089616e-01 -4.62746203e-01 -4.45584297e-01 1.12611003e-01
2.88124866e-04 -9.74156857e-01 -4.04155374e-01 9.29850265e-02
-1.20202160e+00 -1.33656883e+00 -1.01470840e+00 -6.84103370e-01
6.56693876e-01 -1.36151701e-01 9.58191872e-01 -4.19580638e-02
-7.65542150e-01 1.00725579e+00 -2.08010390e-01 3.86804968e-01
-6.21057093e-01 -1.22879737e-03 1.56364478e-02 2.36943007e-01
6.68757362e-03 -1.01601768e+00 -7.98774123e-01 6.51227012e-02
-1.11309612e+00 -1.50174230e-01 6.86480939e-01 8.44249368e-01
7.07743287e-01 1.47319570e-01 3.60469609e-01 -1.09926391e+00
6.11199975e-01 -4.63400453e-01 -1.24233477e-01 4.52785134e-01
-1.08522975e+00 4.67732638e-01 1.32755250e-01 -2.89960921e-01
-7.73375452e-01 3.36799800e-01 -4.48276103e-02 -2.62878120e-01
-8.51622224e-02 5.04735053e-01 -2.16663629e-01 -4.59601074e-01
6.65311158e-01 -3.06521580e-02 3.06099087e-01 -4.72000271e-01
5.63390911e-01 4.68000382e-01 2.43084431e-01 -3.76650214e-01
5.42554498e-01 7.70859480e-01 5.54948151e-01 -8.70765209e-01
-5.34110129e-01 -5.90541065e-01 -1.17280662e+00 -3.08153719e-01
1.00518739e+00 -6.12390757e-01 -3.43498498e-01 2.85147727e-01
-8.99026513e-01 1.65580795e-03 -2.55073816e-01 4.31723624e-01
-5.98873973e-01 7.85549164e-01 -6.55247808e-01 -3.56540501e-01
-3.02919507e-01 -1.33399069e+00 1.11220288e+00 -4.62497830e-01
-2.77203359e-02 -1.67689073e+00 4.70201343e-01 4.42987531e-01
1.47613108e-01 4.69973832e-01 1.35678160e+00 -6.54384434e-01
-4.37047094e-01 2.20466070e-02 -3.51198852e-01 1.51775330e-01
2.14278623e-01 -5.23335755e-01 -5.98888814e-01 -3.80182803e-01
2.04987600e-01 -2.65034125e-03 1.10848343e+00 4.05969948e-01
6.97357237e-01 -3.36602658e-01 -4.70955849e-01 3.49048167e-01
1.44672990e+00 -2.26409331e-01 5.82781196e-01 4.94736880e-01
9.90188956e-01 7.55909026e-01 1.06412033e-02 4.01364595e-01
6.98933125e-01 7.91879594e-01 3.96103591e-01 1.26940802e-01
-3.48429114e-01 4.69709992e-01 8.65112394e-02 8.54985595e-01
-3.62415135e-01 3.91957909e-02 -1.11557651e+00 4.53498304e-01
-1.91000259e+00 -9.08073008e-01 -4.80482340e-01 2.09519029e+00
8.00330758e-01 2.38156002e-02 2.07477003e-01 2.88435102e-01
6.95974410e-01 2.15069279e-01 -4.27648395e-01 2.87219465e-01
-1.06440157e-01 9.13103372e-02 4.66235846e-01 6.97458684e-01
-1.17175198e+00 3.01286787e-01 6.26894379e+00 3.75283718e-01
-7.86215723e-01 4.61314440e-01 2.94267148e-01 1.16012476e-01
-6.87361419e-01 -1.24819137e-01 -4.32117671e-01 2.84314096e-01
9.28967416e-01 -6.29255027e-02 1.27111092e-01 5.01080811e-01
4.34579290e-02 1.06412351e-01 -1.07869577e+00 7.76958764e-01
2.34011680e-01 -1.15129721e+00 1.60037130e-01 4.43446547e-01
2.87781626e-01 -2.41444539e-02 -1.62010774e-01 -3.73456389e-01
1.66012481e-01 -5.24726808e-01 3.04587156e-01 8.65758896e-01
4.70466554e-01 -5.76449990e-01 4.69888538e-01 -8.29570368e-02
-1.19772947e+00 2.25809775e-02 1.51723728e-01 6.09940946e-01
4.34779704e-01 9.86396313e-01 -4.87019271e-01 8.26259613e-01
4.08142745e-01 9.64551508e-01 -9.46369529e-01 9.62595522e-01
1.12936780e-01 1.54581323e-01 -1.99238613e-01 5.07168114e-01
1.34792952e-02 -3.82657170e-01 9.35722709e-01 1.00229788e+00
1.21686570e-01 2.41316552e-03 3.08421582e-01 5.77961624e-01
2.69834578e-01 1.37786150e-01 -6.14387691e-01 4.99698557e-02
-1.71660781e-01 1.30367804e+00 -8.27954829e-01 -1.91783085e-01
-4.04419333e-01 1.15936756e+00 2.79871613e-01 8.79028067e-02
-4.97489005e-01 5.91283739e-02 2.74063468e-01 3.91426563e-01
-1.06788874e-01 -2.07775459e-01 -1.46631703e-01 -1.34301686e+00
8.12301114e-02 -6.77183330e-01 7.90772736e-01 -4.05773044e-01
-1.48938775e+00 6.52862549e-01 1.00267038e-01 -8.45401943e-01
-3.29054922e-01 -6.65388763e-01 -2.60452002e-01 5.07894754e-01
-1.63714886e+00 -1.56310117e+00 -8.94561261e-02 8.15504789e-01
-4.46853973e-02 -2.74658233e-01 1.01456356e+00 5.62922955e-01
-3.55433136e-01 1.61334321e-01 9.80494395e-02 -2.20732272e-01
6.57405436e-01 -1.73552215e+00 -1.88222528e-01 5.23860514e-01
-9.14167017e-02 3.53475541e-01 5.95621109e-01 -7.98399150e-01
-1.13242567e+00 -1.14512324e+00 7.77500689e-01 -2.10460901e-01
1.02261698e+00 -1.21003091e-02 -1.07492304e+00 6.88661873e-01
6.76626861e-02 1.92048386e-01 7.59022713e-01 -7.78565854e-02
-3.20909411e-01 -2.45253257e-02 -1.33680880e+00 3.53827417e-01
1.11228406e+00 -6.54075205e-01 -5.86574256e-01 7.30748832e-01
4.48541194e-01 7.05730841e-02 -1.58499217e+00 4.26018924e-01
4.78097111e-01 -9.40602779e-01 1.30297196e+00 -6.12389565e-01
2.09355921e-01 2.25333511e-04 -1.89754888e-01 -1.29183769e+00
-5.42279303e-01 -4.18685198e-01 -3.46127152e-01 9.40121889e-01
2.23850921e-01 -7.56458461e-01 6.63026929e-01 6.09344661e-01
-9.87823866e-03 -6.90862477e-01 -1.11727083e+00 -7.06348896e-01
1.60993189e-01 -1.05899774e-01 -1.44218385e-01 1.03254163e+00
-1.18085891e-02 3.21857512e-01 -2.32291952e-01 3.74525011e-01
1.16824877e+00 -1.41799703e-01 -1.72032282e-01 -1.75322831e+00
-2.96529263e-01 -4.75327522e-01 -9.34719980e-01 -1.39739349e-01
3.47278953e-01 -1.29792488e+00 -4.85955864e-01 -1.61978686e+00
4.87677664e-01 -5.06494820e-01 -3.69923919e-01 2.97797412e-01
1.37762323e-01 3.50577980e-01 -1.62423536e-01 4.43756282e-01
-3.79165798e-01 4.04151797e-01 1.18184090e+00 -2.76739597e-01
-6.05821051e-02 2.43394822e-02 -4.13177520e-01 6.49078965e-01
6.83673620e-01 -4.86616880e-01 -5.77341735e-01 -8.60796124e-02
1.33536339e-01 -1.22236289e-01 8.75808775e-01 -8.94232988e-01
1.43410489e-01 2.36451253e-01 -2.62678023e-02 -2.64494140e-02
3.27259332e-01 -8.67919505e-01 1.46272197e-01 6.37333035e-01
-3.82454693e-01 -4.80321683e-02 -2.15994641e-01 9.49327767e-01
6.51119128e-02 -3.53593111e-01 1.00354671e+00 -1.60392582e-01
-4.51410174e-01 5.39763093e-01 -2.76780635e-01 1.16074510e-01
1.16259539e+00 2.24243000e-01 -1.11733712e-01 7.20559880e-02
-1.51340580e+00 7.76146948e-02 3.20429832e-01 1.33640587e-01
6.84309661e-01 -1.46051085e+00 -6.65910959e-01 -2.46173460e-02
1.55154586e-01 -3.93059939e-01 3.64970744e-01 1.33118451e+00
-2.92979032e-01 1.65398121e-01 -2.68458426e-01 -8.26489091e-01
-1.57333887e+00 4.83274102e-01 5.00732780e-01 -5.91183066e-01
-1.02144110e+00 2.39792362e-01 -1.25627974e-02 -2.82595307e-01
2.18334179e-02 -2.38540426e-01 -3.73106837e-01 4.65537429e-01
4.94159251e-01 4.51000303e-01 2.22139791e-01 -8.80119920e-01
-3.56293738e-01 6.48987889e-01 -4.28070873e-01 -3.70274365e-01
1.52873445e+00 -4.27966833e-01 -4.51855719e-01 4.96945471e-01
1.28031230e+00 -4.11811203e-01 -8.35662425e-01 -3.27858597e-01
2.60285139e-01 -3.29089016e-02 6.35614634e-01 -5.72465658e-01
-1.09374464e+00 7.52138734e-01 1.07363784e+00 5.91074646e-01
9.63704288e-01 3.61712188e-01 6.66004539e-01 2.32742891e-01
1.32658854e-01 -7.99715042e-01 4.71329577e-02 -5.10837436e-02
9.97448623e-01 -1.31742835e+00 2.68404067e-01 -5.81610382e-01
-4.61823225e-01 1.31481087e+00 -8.15397203e-02 -8.62068310e-02
1.13791764e+00 7.82952383e-02 -1.37856051e-01 -6.14894331e-01
-4.91176248e-01 -2.80450881e-01 5.46585321e-01 7.44757771e-01
1.69083446e-01 2.49667652e-02 -3.41043085e-01 2.65794724e-01
1.74992397e-01 -1.61653876e-01 3.57082754e-01 9.96160269e-01
-4.45146888e-01 -1.50080335e+00 -2.05168813e-01 7.52272904e-01
-3.59560877e-01 -1.13772303e-01 -4.47139621e-01 6.64788961e-01
-3.62201110e-02 3.69107485e-01 -2.53450155e-01 -2.04388127e-01
1.98847100e-01 1.76847801e-01 8.79061043e-01 -5.02092719e-01
-5.27464151e-02 1.75139919e-01 1.83203183e-02 -5.60199499e-01
-9.40122485e-01 -9.79150951e-01 -1.01667404e+00 6.56824186e-02
-1.44566223e-01 -1.24778926e-01 4.40046489e-01 1.09088218e+00
4.54522461e-01 8.28131855e-01 5.06561339e-01 -7.63300836e-01
-4.81339335e-01 -5.65404058e-01 -8.55812609e-01 3.69724363e-01
3.57918173e-01 -9.10386801e-01 -4.65575218e-01 2.89968371e-01] | [12.377704620361328, 3.364475727081299] |
001352a2-f610-4642-8000-7396ad76b264 | a2j-transformer-anchor-to-joint-transformer | 2304.03635 | null | https://arxiv.org/abs/2304.03635v1 | https://arxiv.org/pdf/2304.03635v1.pdf | A2J-Transformer: Anchor-to-Joint Transformer Network for 3D Interacting Hand Pose Estimation from a Single RGB Image | 3D interacting hand pose estimation from a single RGB image is a challenging task, due to serious self-occlusion and inter-occlusion towards hands, confusing similar appearance patterns between 2 hands, ill-posed joint position mapping from 2D to 3D, etc.. To address these, we propose to extend A2J-the state-of-the-art depth-based 3D single hand pose estimation method-to RGB domain under interacting hand condition. Our key idea is to equip A2J with strong local-global aware ability to well capture interacting hands' local fine details and global articulated clues among joints jointly. To this end, A2J is evolved under Transformer's non-local encoding-decoding framework to build A2J-Transformer. It holds 3 main advantages over A2J. First, self-attention across local anchor points is built to make them global spatial context aware to better capture joints' articulation clues for resisting occlusion. Secondly, each anchor point is regarded as learnable query with adaptive feature learning for facilitating pattern fitting capacity, instead of having the same local representation with the others. Last but not least, anchor point locates in 3D space instead of 2D as in A2J, to leverage 3D pose prediction. Experiments on challenging InterHand 2.6M demonstrate that, A2J-Transformer can achieve state-of-the-art model-free performance (3.38mm MPJPE advancement in 2-hand case) and can also be applied to depth domain with strong generalization. | ['Joey Tianyi Zhou', 'Zhiguo Cao', 'Jinghong Zheng', 'Mingyang Zhang', 'Cunlin Wu', 'Yang Xiao', 'Changlong Jiang'] | 2023-04-07 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Jiang_A2J-Transformer_Anchor-to-Joint_Transformer_Network_for_3D_Interacting_Hand_Pose_Estimation_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Jiang_A2J-Transformer_Anchor-to-Joint_Transformer_Network_for_3D_Interacting_Hand_Pose_Estimation_CVPR_2023_paper.pdf | cvpr-2023-1 | ['pose-prediction', 'hand-pose-estimation'] | ['computer-vision', 'computer-vision'] | [-3.43638450e-01 -6.88573942e-02 -9.75464061e-02 -6.18260503e-02
-7.82836497e-01 -4.59997654e-01 -7.47365952e-02 -7.38202691e-01
-3.89161818e-02 3.11704785e-01 3.81391108e-01 3.60719651e-01
-2.42585003e-01 -3.34363699e-01 -6.12636626e-01 -6.12077773e-01
-6.20961525e-02 8.76355588e-01 4.57010716e-01 -3.02310437e-01
-6.39814138e-02 8.10025513e-01 -1.35125172e+00 1.15704529e-01
4.54605937e-01 1.15538204e+00 4.98895884e-01 3.23531866e-01
4.91368473e-02 3.30174387e-01 -4.66235936e-01 -3.89253259e-01
4.20955300e-01 1.64628178e-01 -6.10618412e-01 1.21416703e-01
6.32326484e-01 -7.61504710e-01 -7.80059934e-01 5.05763650e-01
1.09866428e+00 -6.71691000e-02 6.55151546e-01 -1.04999804e+00
-5.44234574e-01 -3.08424085e-02 -9.84297514e-01 -1.15236290e-01
8.18054020e-01 4.61491466e-01 8.34154904e-01 -1.14333212e+00
7.82315016e-01 1.66001940e+00 5.70097864e-01 6.67887807e-01
-9.50767756e-01 -7.03770041e-01 5.86507916e-01 1.52210563e-01
-1.74399257e+00 -9.36923176e-02 1.09789789e+00 -1.96980596e-01
1.06718957e+00 3.19416374e-01 1.05693352e+00 1.31740785e+00
1.33965626e-01 1.17088640e+00 1.03114831e+00 -2.80746549e-01
-1.77758202e-01 -4.77575213e-01 -2.08041340e-01 8.70785654e-01
-3.05333734e-01 -1.65383518e-01 -1.00652552e+00 2.54855324e-02
1.40423131e+00 1.18603580e-01 -3.46724302e-01 -5.46702445e-01
-1.10778463e+00 8.10798779e-02 7.64660597e-01 7.01483861e-02
-4.47451353e-01 4.02221233e-01 -2.57877703e-03 1.77844837e-01
2.03914538e-01 4.18063737e-02 -7.79208422e-01 -3.39948177e-01
-5.11760592e-01 5.57381749e-01 4.38736439e-01 1.35487962e+00
4.78682995e-01 -3.30521315e-01 -3.56896400e-01 7.69776046e-01
7.94705153e-01 6.78472757e-01 2.00583756e-01 -9.20806289e-01
8.86969090e-01 7.04754531e-01 1.53010949e-01 -9.69887555e-01
-6.18210077e-01 -5.33595264e-01 -6.70351088e-01 3.40888202e-01
4.38626826e-01 2.76277632e-01 -1.05120695e+00 1.64011776e+00
5.20653784e-01 -3.82545203e-01 -5.73381662e-01 1.38702178e+00
7.48146832e-01 1.00642741e-01 -2.69823164e-01 4.66881320e-02
1.53878665e+00 -1.17393959e+00 -5.51213443e-01 -2.81939268e-01
-4.79549170e-02 -8.58362973e-01 1.31303298e+00 5.06558180e-01
-9.58402693e-01 -7.97785282e-01 -6.47063434e-01 -3.93582791e-01
-6.37908131e-02 1.12350754e-01 6.67597413e-01 3.14833313e-01
-8.14286113e-01 2.08052397e-01 -8.91890466e-01 -2.19214588e-01
4.04796898e-01 5.51206291e-01 -6.47920847e-01 -2.55301982e-01
-8.61406028e-01 8.73375416e-01 -6.12085685e-02 5.83753049e-01
-5.96499383e-01 -4.67237890e-01 -6.45470798e-01 -3.90823513e-01
4.82503533e-01 -8.56735170e-01 9.74385977e-01 -8.29663128e-02
-1.75278246e+00 1.07597435e+00 -4.39298928e-01 5.57770252e-01
8.98424923e-01 -7.17025101e-01 -7.73487240e-02 1.21594362e-01
1.55693829e-01 6.36003494e-01 8.92222404e-01 -1.53155077e+00
-2.50156552e-01 -1.22702360e+00 -7.43122399e-02 5.49061000e-01
-6.37895912e-02 -4.08285171e-01 -1.28088713e+00 -1.01471078e+00
9.42019522e-01 -1.02632201e+00 -4.28792052e-02 5.76804101e-01
-6.72390163e-01 -5.01940370e-01 8.96428585e-01 -7.94979095e-01
9.66629267e-01 -1.91133940e+00 7.37176597e-01 4.64237899e-01
4.44239587e-01 -5.87277971e-02 -1.26139522e-01 2.72108227e-01
2.59286791e-01 -4.07415032e-01 1.39189050e-01 -7.04679191e-01
2.46918350e-01 3.57171029e-01 1.96094513e-02 5.20531416e-01
6.33536372e-03 1.25698125e+00 -5.99981904e-01 -6.49808168e-01
3.67106557e-01 7.74839699e-01 -4.06750500e-01 4.30025220e-01
-1.28560379e-01 7.86705554e-01 -8.43019545e-01 1.12084734e+00
8.45487058e-01 -2.53094602e-02 -1.82421640e-01 -6.36341751e-01
1.26162797e-01 1.34846913e-02 -1.44350088e+00 2.58739042e+00
-4.03316975e-01 -6.23062514e-02 2.67851412e-01 -3.20710808e-01
7.18446612e-01 3.02418590e-01 4.70749915e-01 -7.14384317e-01
8.56919512e-02 1.73402205e-01 -2.75411934e-01 -6.39375925e-01
-1.50719121e-01 2.36704260e-01 5.04834540e-02 2.01198235e-01
2.26868708e-02 -2.66207874e-01 -6.61473930e-01 -2.77697891e-01
7.10247636e-01 7.17861772e-01 -1.82024121e-01 1.91162765e-01
2.98236161e-01 -5.55153072e-01 3.50431651e-01 4.95407879e-01
-1.54883727e-01 9.55491543e-01 6.83717132e-02 -3.49932224e-01
-8.57464969e-01 -1.25861061e+00 2.74393149e-02 9.41870093e-01
3.90035093e-01 -3.39098632e-01 -4.61636871e-01 -5.67147434e-01
4.37411785e-01 -1.09568015e-01 -5.95956862e-01 1.49198681e-01
-8.68668020e-01 -8.14990923e-02 3.37233901e-01 9.43456233e-01
6.29485428e-01 -8.34956408e-01 -6.43093824e-01 2.24934697e-01
-9.81954932e-02 -9.09482121e-01 -7.39769638e-01 5.72905056e-02
-7.49475300e-01 -1.03859806e+00 -1.38487744e+00 -9.20205951e-01
5.05113363e-01 2.50159264e-01 8.57932270e-01 -2.26318404e-01
-5.00084102e-01 6.59739971e-01 -3.55092138e-01 4.86721285e-02
4.73208427e-01 1.87854558e-01 3.51033807e-01 -2.77921796e-01
1.61465451e-01 -1.01276314e+00 -1.21297395e+00 7.27980733e-01
-2.04918265e-01 -1.25724673e-01 8.38329613e-01 7.14416385e-01
8.25462103e-01 -3.06710660e-01 4.35682461e-02 2.37924270e-02
2.83682346e-01 2.54255086e-01 -2.12168191e-02 4.45682675e-01
-2.51051873e-01 -1.03569634e-01 2.32789546e-01 -5.37991583e-01
-1.05172205e+00 2.82604545e-01 -3.81258279e-01 -7.97967494e-01
-1.41824469e-01 -1.20021164e-01 -7.98925579e-01 -2.71338940e-01
2.84693152e-01 2.62584180e-01 6.05489351e-02 -9.51893806e-01
4.87251312e-01 6.96308076e-01 5.57582498e-01 -9.64718163e-01
7.97902584e-01 4.71880764e-01 1.55822530e-01 -4.16528136e-01
-5.11933863e-01 -4.26372230e-01 -1.07259178e+00 -3.89803618e-01
7.62081265e-01 -8.16841125e-01 -1.21236515e+00 8.27563286e-01
-1.26144326e+00 -3.32196355e-01 -6.03108592e-02 3.78665417e-01
-6.31663740e-01 4.78367060e-01 -5.90000212e-01 -9.03983355e-01
-4.30042803e-01 -1.33645344e+00 1.74261451e+00 -6.65177545e-03
-2.63047099e-01 -4.71257865e-01 -8.64735469e-02 6.43060327e-01
1.27994688e-02 1.64218217e-01 6.03625596e-01 6.37428388e-02
-4.68324512e-01 -3.75486821e-01 -1.48168847e-01 -7.38024414e-02
3.02392036e-01 -4.11700308e-01 -1.11569762e+00 -4.83585030e-01
-1.52641907e-01 -3.81857932e-01 5.01809180e-01 2.42386296e-01
1.16123998e+00 -1.52817264e-01 -4.29328650e-01 5.89361489e-01
8.47850859e-01 -9.14090946e-02 5.28581560e-01 2.03381777e-01
1.09674823e+00 6.78126514e-01 6.45404339e-01 4.63793933e-01
6.72533333e-01 1.34205401e+00 5.70457935e-01 -8.34259577e-03
-5.47087014e-01 -4.20402169e-01 6.78448230e-02 7.89396465e-01
-6.18201673e-01 1.00199327e-01 -7.12495446e-01 6.00235760e-02
-1.81760240e+00 -4.50279057e-01 1.09242663e-01 2.01703405e+00
8.70344877e-01 1.04602344e-01 4.66566622e-01 1.24967717e-01
2.90640593e-01 9.11093801e-02 -8.43401432e-01 4.81688142e-01
-1.44926712e-01 3.30762297e-01 1.83648095e-01 4.24763322e-01
-7.07803667e-01 1.08660483e+00 4.93022251e+00 1.00775623e+00
-9.42207098e-01 2.15946168e-01 9.53695178e-02 -2.21998721e-01
-1.38351023e-01 -2.97648996e-01 -7.64993191e-01 3.40302259e-01
-4.40044194e-01 8.41216743e-01 4.20808643e-01 7.77960181e-01
-1.29461987e-02 1.07213773e-01 -1.07307220e+00 1.39194787e+00
-6.40963530e-03 -5.35833478e-01 1.19141549e-01 1.79060414e-01
2.72128165e-01 -3.95926863e-01 1.98981583e-01 -3.99422832e-02
-3.36239755e-01 -1.07936978e+00 9.70098615e-01 6.35967255e-01
1.07119370e+00 -6.05289459e-01 4.53929693e-01 3.04355234e-01
-1.65185058e+00 1.64303500e-02 -2.70226091e-01 -3.32193263e-02
1.66809559e-01 2.29035437e-01 -3.06032270e-01 5.72085500e-01
1.03410590e+00 5.54329753e-01 -4.48591530e-01 6.76629245e-01
-3.75589460e-01 -1.60913110e-01 -6.06280208e-01 2.29413033e-01
-3.90855409e-02 2.09349081e-01 5.81023276e-01 8.17432046e-01
5.75936288e-02 3.52427483e-01 3.14465493e-01 6.72785461e-01
2.85515308e-01 -1.46044821e-01 -2.97663510e-01 6.42529964e-01
6.17096126e-01 8.74582708e-01 -5.18034041e-01 1.24653190e-01
-1.53975233e-01 1.75087023e+00 4.12209660e-01 5.26411533e-01
-5.66610873e-01 -2.21265957e-01 7.63591945e-01 2.09417924e-01
3.58187973e-01 -5.62229872e-01 -2.04884440e-01 -1.14712739e+00
7.52236784e-01 -6.82764173e-01 1.04469746e-01 -9.41528797e-01
-1.36733103e+00 5.07814169e-01 -1.26588225e-01 -1.21458101e+00
1.29473105e-01 -1.02741182e+00 -1.72689930e-01 1.03356063e+00
-1.23857450e+00 -1.77496839e+00 -6.69230044e-01 1.02418363e+00
6.27145648e-01 1.00162283e-01 1.00385690e+00 1.69881761e-01
-4.11828667e-01 9.98424828e-01 -3.47056508e-01 1.74414739e-01
7.58415461e-01 -1.21915936e+00 4.04453099e-01 1.92625806e-01
2.64264569e-02 7.83864319e-01 2.74713576e-01 -6.44960821e-01
-2.05300331e+00 -4.32893157e-01 3.39703172e-01 -8.60432446e-01
1.53565571e-01 -5.51849484e-01 -5.10690093e-01 5.15108585e-01
-3.09953570e-01 1.26333937e-01 3.64846259e-01 2.02305451e-01
-7.16640115e-01 -3.11980784e-01 -1.25274515e+00 6.86611056e-01
1.89663565e+00 -7.67748237e-01 -5.91757059e-01 4.06529546e-01
4.60068762e-01 -1.00029027e+00 -1.23814118e+00 4.29234535e-01
1.32488418e+00 -7.99160659e-01 1.41859579e+00 -4.07776862e-01
6.68670163e-02 -4.02348906e-01 -4.77837265e-01 -8.45558763e-01
-4.81684268e-01 -6.85156167e-01 -7.26997674e-01 1.05054140e+00
-2.17951089e-01 -4.36840713e-01 1.21560502e+00 6.64808810e-01
-1.06347026e-03 -1.17341828e+00 -1.48181772e+00 -7.56952167e-01
-1.41089648e-01 -4.68887866e-01 5.50186813e-01 3.61037105e-01
-8.15677941e-02 1.53092772e-01 -4.50174093e-01 3.69483292e-01
8.09645891e-01 2.74260700e-01 1.12750185e+00 -1.15538800e+00
-3.74068052e-01 -5.44675946e-01 -6.52498603e-01 -2.01195097e+00
1.00761242e-02 -3.79045844e-01 -1.26452269e-02 -1.47006547e+00
2.81819385e-02 -7.09072948e-01 -1.01931378e-01 7.07900882e-01
-1.45192102e-01 5.35983920e-01 3.25987667e-01 6.20123744e-01
-3.50313991e-01 6.41128778e-01 2.06327391e+00 -1.40374184e-01
-2.68822044e-01 1.51849821e-01 -1.64722443e-01 4.47738647e-01
2.21771926e-01 -1.73227955e-02 -3.13346535e-01 -6.27937019e-01
4.03382517e-02 1.18723176e-01 7.09891021e-01 -9.01638746e-01
1.09850496e-01 7.39562884e-02 7.75225639e-01 -9.34918880e-01
8.76294434e-01 -1.09161139e+00 1.84553728e-01 3.35586399e-01
1.55091330e-01 6.55632988e-02 -5.09468429e-02 5.69635808e-01
1.24499269e-01 2.80053169e-01 2.42565244e-01 -3.63316357e-01
-7.98127413e-01 6.91601872e-01 1.50788262e-01 -7.14254081e-02
7.91022480e-01 -6.35358274e-01 1.41870618e-01 -3.40556413e-01
-1.04838252e+00 4.11285698e-01 5.43753982e-01 4.84872580e-01
8.85532618e-01 -1.43314385e+00 -4.76540208e-01 3.74075085e-01
1.90055370e-01 6.60677195e-01 5.79083622e-01 9.43818212e-01
-4.10936058e-01 4.76581872e-01 -1.85297340e-01 -9.46952522e-01
-1.14215839e+00 3.01316947e-01 2.77130187e-01 1.24087874e-02
-9.47579324e-01 1.34179282e+00 2.24913314e-01 -6.27369225e-01
8.00164223e-01 -3.46003830e-01 2.74373144e-01 -5.97785525e-02
2.61490703e-01 3.90254766e-01 2.90167313e-02 -7.13626325e-01
-6.85388982e-01 1.52492368e+00 -2.78990921e-02 -4.42782715e-02
1.21906435e+00 -1.52349874e-01 9.78485029e-03 2.83863574e-01
1.20608270e+00 1.11139603e-01 -1.67021835e+00 -3.01753759e-01
-6.68685853e-01 -7.84219801e-01 -2.56172001e-01 -1.05631649e+00
-1.19139504e+00 1.10226357e+00 9.06356573e-01 -4.27159190e-01
1.01237881e+00 4.74081188e-01 9.61089671e-01 3.56896460e-01
7.98020542e-01 -8.55823159e-01 4.67800379e-01 1.90624833e-01
1.51926017e+00 -1.02035761e+00 3.17099467e-02 -5.64321876e-01
-5.41502476e-01 1.19500864e+00 1.00763309e+00 1.36943221e-01
6.06662512e-01 7.04381689e-02 1.00841224e-01 -5.46041727e-01
5.49563579e-02 -1.26192093e-01 6.62601531e-01 8.74885678e-01
1.99702337e-01 1.54727576e-02 1.94766551e-01 5.90224445e-01
-2.37955168e-01 -2.67351389e-01 -6.14678264e-01 1.19159484e+00
2.72600376e-03 -1.15416932e+00 -5.54115415e-01 1.83606103e-01
5.57446331e-02 3.15104932e-01 -4.89595652e-01 9.31284904e-01
2.61872709e-01 5.69857240e-01 -1.29858077e-01 -7.06188023e-01
8.67504120e-01 -5.68367504e-02 1.27168322e+00 -4.48341399e-01
-3.81026387e-01 5.43740094e-01 -4.15932298e-01 -9.11940813e-01
-3.89669120e-01 -4.40050483e-01 -1.10599530e+00 -1.38834521e-01
-4.17342424e-01 -3.73073786e-01 3.50646317e-01 9.13771152e-01
4.85992730e-01 3.29593271e-01 4.57360506e-01 -1.58718634e+00
-6.21901572e-01 -1.02761531e+00 -7.05680609e-01 2.42211863e-01
3.44058663e-01 -1.28182793e+00 1.28390983e-01 -5.30227780e-01] | [6.671361446380615, -0.836001455783844] |
30a40b1a-30f3-4fac-a0ed-f2a90ee1bf4b | resource-lean-modeling-of-coherence-in | null | null | https://aclanthology.org/W17-0910 | https://aclanthology.org/W17-0910.pdf | Resource-Lean Modeling of Coherence in Commonsense Stories | We present a resource-lean neural recognizer for modeling coherence in commonsense stories. Our lightweight system is inspired by successful attempts to modeling discourse relations and stands out due to its simplicity and easy optimization compared to prior approaches to narrative script learning. We evaluate our approach in the Story Cloze Test demonstrating an absolute improvement in accuracy of 4.7{\%} over state-of-the-art implementations. | ['Niko Schenk', 'Christian Chiarcos'] | 2017-04-01 | null | null | null | ws-2017-4 | ['cloze-test'] | ['natural-language-processing'] | [ 3.29183906e-01 3.50751370e-01 -3.89941812e-01 -4.89023566e-01
-7.39687860e-01 -4.08987314e-01 1.15030932e+00 1.73090190e-01
-4.39926088e-01 8.02924037e-01 1.13487756e+00 -2.80054569e-01
-1.40754223e-01 -5.61529994e-01 -5.06371021e-01 -9.63776745e-03
-1.75556362e-01 6.92112565e-01 1.68551251e-01 -5.68551958e-01
4.76173401e-01 -3.06703486e-02 -1.09339464e+00 8.74703288e-01
4.76274490e-01 5.44002831e-01 -1.03943177e-01 8.46505284e-01
-8.89207870e-02 2.30621982e+00 -9.95317101e-01 -4.58891332e-01
-6.41302407e-01 -8.25127006e-01 -1.42124772e+00 -2.10777029e-01
3.64972591e-01 -5.02907097e-01 -8.88935804e-01 4.32456166e-01
3.82784933e-01 3.77459258e-01 7.25097597e-01 -6.92829251e-01
-8.94151211e-01 1.53365040e+00 -7.00829551e-02 6.58268452e-01
8.70834529e-01 -2.34542489e-01 1.38958466e+00 -5.79568148e-01
1.08161759e+00 7.76276290e-01 8.18676531e-01 4.78958488e-01
-1.05108929e+00 -2.74067938e-01 -4.67331931e-02 5.89708209e-01
-1.04029810e+00 -8.94146860e-01 8.09200406e-01 -5.83528996e-01
1.80261290e+00 4.11882848e-01 5.41936994e-01 1.57603276e+00
-1.48663521e-01 9.62626934e-01 1.02044511e+00 -4.57394272e-01
4.07569334e-02 -2.32129574e-01 4.44072723e-01 6.09419167e-01
-5.24403863e-02 -2.89283067e-01 -1.01729989e+00 -7.05332533e-02
6.01670980e-01 -7.32457995e-01 -1.01227395e-01 4.68054444e-01
-1.26070154e+00 8.83573055e-01 2.49410197e-01 5.85916638e-01
-2.43285909e-01 5.11331379e-01 7.40462363e-01 1.83485150e-01
4.61186737e-01 8.90015721e-01 2.40668774e-01 -9.64454532e-01
-1.17410219e+00 5.83978176e-01 1.21059930e+00 7.22988605e-01
-4.59327877e-01 4.09481943e-01 -3.58352929e-01 1.05826604e+00
-1.29118234e-01 -2.65547335e-01 5.12205839e-01 -1.14825189e+00
6.29460871e-01 3.49398553e-01 -1.48500696e-01 -9.29479480e-01
-5.48102140e-01 -4.79759663e-01 -5.65557301e-01 -1.74583331e-01
2.97132254e-01 1.65119141e-01 -2.13631541e-01 1.54910207e+00
-5.47810316e-01 2.86490005e-02 1.57045454e-01 5.14285326e-01
1.42939591e+00 5.95670104e-01 6.55939206e-02 -2.65959233e-01
1.19296169e+00 -8.13952148e-01 -8.22255790e-01 -3.71785253e-01
5.56822836e-01 -6.60036802e-01 1.27093399e+00 3.29372168e-01
-1.34790254e+00 5.08365817e-02 -1.33914888e+00 -3.02546442e-01
5.89738451e-02 -3.10569610e-02 9.31439877e-01 3.86599392e-01
-6.89410627e-01 8.72081041e-01 -5.81587195e-01 -3.04903924e-01
7.67488599e-01 -1.70458809e-01 -2.08630383e-01 3.26298654e-01
-1.23746693e+00 1.46824229e+00 7.75625706e-01 -3.25155169e-01
-7.37751365e-01 -3.98917526e-01 -6.17157996e-01 1.48417437e-02
5.31064332e-01 -4.20450449e-01 1.69421363e+00 -3.05879086e-01
-1.82587504e+00 1.21162808e+00 3.70043591e-02 -6.97093844e-01
5.11855781e-01 -4.95511591e-01 -3.18498671e-01 1.57276362e-01
-4.53111120e-02 -7.46171027e-02 5.66703491e-02 -8.53088558e-01
-3.07954773e-02 3.97097647e-01 3.64663154e-01 2.66903669e-01
-2.73062348e-01 6.88602448e-01 2.18839288e-01 -9.30932164e-01
-1.54659584e-01 -5.09240270e-01 2.05992952e-01 -5.60368657e-01
-5.49316764e-01 -4.35499996e-01 3.68068665e-01 -9.74082053e-01
1.54481220e+00 -1.44819200e+00 1.34608030e-01 -3.23387593e-01
2.55004197e-01 3.67480963e-02 1.41490430e-01 7.73212254e-01
6.90637231e-02 1.57886103e-01 -1.85775772e-01 -2.38790005e-01
2.42460176e-01 1.42240420e-01 -5.55719078e-01 2.50183970e-01
3.84322762e-01 1.06354809e+00 -9.84523416e-01 -5.87676823e-01
-1.65679440e-01 1.17748328e-01 -4.42571878e-01 2.65704244e-01
-6.04815781e-01 -1.29645810e-01 -2.22422212e-01 4.30611104e-01
-3.70604038e-01 -4.33008105e-01 4.21919584e-01 2.37453073e-01
-7.20250010e-02 1.36334407e+00 -7.75756717e-01 1.67026734e+00
-1.38823539e-01 1.42456293e+00 -6.42180562e-01 -7.64246285e-01
7.35073209e-01 6.67230785e-01 -1.29511014e-01 -4.10031050e-01
4.35566992e-01 1.09928086e-01 2.15936661e-01 -6.81258321e-01
9.36784863e-01 -2.31525421e-01 -3.47267330e-01 9.82482433e-01
1.76928550e-01 -4.75651979e-01 3.83672893e-01 3.37737411e-01
1.34333050e+00 3.53481740e-01 7.70411193e-01 -2.24438891e-01
7.88830593e-02 1.55202404e-01 -6.95499033e-02 9.76015925e-01
8.50482211e-02 5.80373287e-01 7.72594094e-01 -4.78651136e-01
-1.25087166e+00 -8.34277570e-01 -3.81598324e-02 1.20473659e+00
-4.15177256e-01 -8.20461750e-01 -6.65434182e-01 -1.80247709e-01
-5.36131382e-01 1.42636323e+00 -7.81183362e-01 2.69816309e-01
-1.01947212e+00 -5.44337809e-01 1.30170953e+00 8.32790196e-01
4.31832165e-01 -1.42730808e+00 -8.77891004e-01 5.03722072e-01
-4.59942549e-01 -1.36062503e+00 3.30831222e-02 1.53404579e-01
-5.46583354e-01 -9.53463793e-01 -7.11464807e-02 -4.87543911e-01
-3.01840752e-01 -1.75046638e-01 1.42275202e+00 -5.26519911e-03
-5.54055274e-02 -1.88955516e-01 -3.80338520e-01 -2.48623490e-01
-8.04032981e-01 2.79283762e-01 -1.73522577e-01 -9.33434784e-01
2.58068234e-01 -7.74622798e-01 1.74643248e-01 -4.05604690e-01
-6.74395621e-01 4.50023592e-01 -1.42003782e-02 1.03885937e+00
-1.16088375e-01 -2.41598919e-01 5.13045430e-01 -1.17945421e+00
1.25016916e+00 -5.43313503e-01 1.76495761e-01 7.11182207e-02
-4.44673032e-01 -9.21696946e-02 5.07218599e-01 -5.41641593e-01
-9.84436393e-01 -6.38817012e-01 -1.25582725e-01 2.40797445e-01
5.23802266e-02 8.79910052e-01 2.98401326e-01 5.12660325e-01
1.09289038e+00 1.03075072e-01 -3.19211632e-01 -1.09894790e-01
6.14808857e-01 5.20212531e-01 1.04103148e+00 -7.59717405e-01
5.32319903e-01 8.88519138e-02 -3.05750877e-01 -8.72049451e-01
-1.09660804e+00 4.75373454e-02 -4.06114399e-01 -4.32403564e-01
7.82217324e-01 -7.69320726e-01 -7.90293455e-01 1.60743937e-01
-1.61641407e+00 -5.04914045e-01 -4.30175841e-01 4.29476500e-01
-9.86331403e-01 -3.63962576e-02 -1.10009491e+00 -7.27811575e-01
-4.14308697e-01 -3.73187512e-01 3.38827252e-01 2.37891376e-01
-1.34581125e+00 -9.09010828e-01 2.07419261e-01 5.24187386e-01
5.17296374e-01 7.18341768e-01 1.01172662e+00 -9.34575915e-01
-1.73734531e-01 -7.66090602e-02 -1.30115956e-01 -6.17411472e-02
-3.69496018e-01 -3.62120639e-03 -1.09095967e+00 4.94670689e-01
-5.80872223e-03 -8.69070709e-01 7.98134923e-01 4.95497324e-02
7.42436469e-01 -6.40570879e-01 5.93880340e-02 2.59835094e-01
1.09653151e+00 1.30611405e-01 6.29220665e-01 8.36681545e-01
5.82483828e-01 3.07249963e-01 2.41643991e-02 6.63266599e-01
5.80356717e-01 5.43860614e-01 6.37487546e-02 3.58342856e-01
-3.59323353e-01 -2.77605861e-01 1.56249598e-01 9.39039528e-01
-6.43576324e-01 -3.04784924e-01 -1.14936471e+00 6.04822695e-01
-1.96611369e+00 -1.72884154e+00 -1.44057110e-01 1.24747908e+00
1.38523090e+00 6.82195365e-01 1.93695456e-01 2.10404694e-01
1.84680030e-01 8.92088771e-01 -1.54921427e-01 -8.52145851e-01
-5.52861094e-01 4.35445607e-01 -1.03860617e-01 6.26976907e-01
-1.10610020e+00 1.09203982e+00 7.79779053e+00 7.41608322e-01
-5.87351203e-01 2.58112252e-01 3.47963184e-01 -5.95243633e-01
-3.21229875e-01 -1.30201221e-01 -3.75280261e-01 3.14863846e-02
9.76487100e-01 -5.42892456e-01 6.32011235e-01 8.78703058e-01
-4.53210622e-02 -1.73689157e-01 -1.44044077e+00 5.88407159e-01
6.87036932e-01 -2.17063093e+00 -2.85060346e-01 -4.57682461e-01
7.36530662e-01 1.25181645e-01 -3.39488447e-01 3.87807310e-01
7.84912109e-01 -1.51633430e+00 1.19829237e+00 4.97480750e-01
6.62328959e-01 -5.40953219e-01 7.46090233e-01 3.92071873e-01
-5.42891026e-01 1.90591678e-01 1.53900370e-01 -7.34976113e-01
3.22287410e-01 1.19890817e-01 -1.01849806e+00 3.71053554e-02
4.35016811e-01 6.53546095e-01 -4.67026532e-01 4.64174449e-01
-6.23045266e-01 1.06345654e+00 -2.11611748e-01 -6.77805960e-01
3.58011752e-01 3.90399784e-01 7.71972477e-01 1.87259960e+00
-3.16776991e-01 5.51808774e-01 1.89258729e-03 1.13251054e+00
-3.30074370e-01 4.22083121e-03 -6.10284925e-01 -4.82889980e-01
7.00541019e-01 5.95265150e-01 -5.99008024e-01 -5.29345393e-01
2.57443413e-02 8.07017803e-01 7.24121511e-01 -6.26938641e-02
-8.66008759e-01 -3.64440829e-01 1.82786286e-01 -2.71221399e-02
2.31279299e-01 -4.35682297e-01 -8.68817806e-01 -1.00136352e+00
1.76424012e-01 -9.59666848e-01 2.66233236e-01 -8.22034478e-01
-1.32759666e+00 1.02444816e+00 3.20107937e-01 -7.18596578e-01
-8.73142242e-01 -2.91527689e-01 -8.44198227e-01 5.37911594e-01
-8.83616745e-01 -1.32342589e+00 -1.22042261e-01 5.11873439e-02
6.52569950e-01 -4.79644686e-01 1.32279015e+00 -2.16279283e-01
-3.47902030e-01 4.52762336e-01 -8.16629007e-02 4.34567541e-01
2.74639219e-01 -1.14683115e+00 6.07273519e-01 8.03494155e-01
3.37258726e-01 6.51044786e-01 1.05368829e+00 -4.39898670e-01
-9.73529458e-01 -4.53894854e-01 1.36034560e+00 -7.08367825e-01
1.28079391e+00 -2.53271580e-01 -7.93827891e-01 8.43548715e-01
7.63092041e-01 -7.92871118e-01 9.84393895e-01 5.75867534e-01
-9.12520647e-01 4.95691210e-01 -6.84849262e-01 9.78275836e-01
1.18463433e+00 -9.40759778e-01 -1.37447667e+00 4.59115177e-01
5.64507246e-01 -7.66286194e-01 -1.02247310e+00 4.81520481e-02
7.33397186e-01 -8.67372334e-01 7.46765018e-01 -9.41692531e-01
1.52102518e+00 7.70869032e-02 -4.43562001e-01 -1.02445507e+00
-4.87981349e-01 -8.51610661e-01 -5.34215808e-01 1.31067753e+00
2.56730884e-01 -6.18977025e-02 6.96027398e-01 4.38079506e-01
-2.57081866e-01 -7.38498390e-01 -1.09935784e+00 -6.12010121e-01
2.18823180e-01 -6.88732624e-01 2.41810188e-01 1.32677984e+00
8.33009601e-01 9.83537376e-01 -4.58085209e-01 -5.30619740e-01
3.03247362e-01 1.00966111e-01 3.81218851e-01 -8.68088126e-01
-8.08497906e-01 -1.24742329e+00 -2.36577913e-01 -6.34395063e-01
3.80727679e-01 -1.06411290e+00 -4.34515513e-02 -1.82027364e+00
4.84644532e-01 -1.85164949e-03 1.72063082e-01 5.58030546e-01
3.33635136e-02 4.92877185e-01 3.78705680e-01 1.84306070e-01
-6.59552097e-01 3.24547917e-01 5.67985892e-01 -2.17661202e-01
-1.38692215e-01 -4.67123657e-01 -8.30637455e-01 8.64028573e-01
9.13088024e-01 -4.48481470e-01 -2.42561743e-01 -4.91167247e-01
4.67080891e-01 1.30872816e-01 3.65805835e-01 -9.36753035e-01
2.44679317e-01 -3.11553806e-01 2.00689062e-01 -5.63499749e-01
5.04080176e-01 1.23916283e-01 1.46652088e-01 2.10228220e-01
-1.07629490e+00 -7.48425052e-02 1.94150418e-01 -9.64578986e-02
-1.64374381e-01 -4.79889005e-01 4.81192648e-01 -3.00824225e-01
-5.87515533e-01 -6.03545785e-01 -7.03342319e-01 5.13408244e-01
5.89466631e-01 -3.25672060e-01 -9.99310970e-01 -7.33730435e-01
-4.14462417e-01 -3.68885756e-01 7.15227872e-02 4.00392532e-01
5.80556750e-01 -1.25187087e+00 -1.30504704e+00 -7.39794612e-01
1.29176795e-01 -4.17581111e-01 -2.62272835e-01 4.76967752e-01
-7.83308387e-01 3.30334395e-01 -2.02185377e-01 -1.52951494e-01
-1.18536353e+00 -3.24979946e-02 1.16613276e-01 -4.77294117e-01
-8.24823380e-01 1.08608651e+00 -8.18664551e-01 1.13419190e-01
2.42091149e-01 -3.12697962e-02 -4.29309517e-01 -6.90025929e-03
7.01229095e-01 4.93528903e-01 -1.69225305e-01 -4.94577259e-01
-2.84799397e-01 -3.13748755e-02 -2.34095976e-01 -4.73578513e-01
1.78864181e+00 4.48764801e-01 -2.32197165e-01 1.17604768e+00
8.15862119e-01 2.82392465e-02 -7.10678816e-01 -2.92612612e-01
5.00106990e-01 -5.93121834e-02 -1.43457010e-01 -1.16556621e+00
6.27052188e-02 4.55652565e-01 -3.00365984e-01 3.61704618e-01
4.78673071e-01 3.42415124e-01 6.28237605e-01 7.49552131e-01
-1.17767937e-02 -1.19315922e+00 2.68460989e-01 1.25438654e+00
1.25605261e+00 -8.54645073e-01 6.21728599e-01 -3.20372805e-02
-8.75319541e-01 1.37780881e+00 2.88875729e-01 -6.68745577e-01
1.25041977e-01 7.61534989e-01 -3.15992087e-02 -4.41023380e-01
-1.13658810e+00 2.13798091e-01 1.82505101e-01 4.46024448e-01
1.13177145e+00 2.81118482e-01 -5.16475677e-01 7.83348978e-01
-9.85755026e-01 1.15042835e-01 9.16727245e-01 8.61522317e-01
-3.97384495e-01 -5.87816894e-01 -5.34068160e-02 5.00351071e-01
-5.17996013e-01 -4.51339662e-01 -6.89222813e-01 1.01807022e+00
-3.12593997e-01 9.04901624e-01 1.44443303e-01 -5.06855488e-01
3.24330002e-01 3.17682892e-01 8.78562033e-01 -5.28094232e-01
-1.06561220e+00 -3.23257208e-01 1.27853978e+00 -4.34267223e-01
-5.57307363e-01 -9.39233601e-01 -1.33465493e+00 -6.37925565e-01
-6.73525706e-02 -1.37400270e-01 2.97424406e-01 1.13263690e+00
-2.69566000e-01 8.27901363e-01 7.15680271e-02 -6.87666655e-01
-4.63898391e-01 -1.28304577e+00 -9.71361995e-02 2.97345221e-01
2.59413328e-02 -3.36418927e-01 1.18234657e-01 3.10019404e-01] | [11.189542770385742, 8.872467041015625] |
3c2cbae1-f2eb-4fc7-975a-e7f0f29536e6 | w-mae-pre-trained-weather-model-with-masked | 2304.08754 | null | https://arxiv.org/abs/2304.08754v1 | https://arxiv.org/pdf/2304.08754v1.pdf | W-MAE: Pre-trained weather model with masked autoencoder for multi-variable weather forecasting | Weather forecasting is a long-standing computational challenge with direct societal and economic impacts. This task involves a large amount of continuous data collection and exhibits rich spatiotemporal dependencies over long periods, making it highly suitable for deep learning models. In this paper, we apply pre-training techniques to weather forecasting and propose W-MAE, a Weather model with Masked AutoEncoder pre-training for multi-variable weather forecasting. W-MAE is pre-trained in a self-supervised manner to reconstruct spatial correlations within meteorological variables. On the temporal scale, we fine-tune the pre-trained W-MAE to predict the future states of meteorological variables, thereby modeling the temporal dependencies present in weather data. We pre-train W-MAE using the fifth-generation ECMWF Reanalysis (ERA5) data, with samples selected every six hours and using only two years of data. Under the same training data conditions, we compare W-MAE with FourCastNet, and W-MAE outperforms FourCastNet in precipitation forecasting. In the setting where the training data is far less than that of FourCastNet, our model still performs much better in precipitation prediction (0.80 vs. 0.98). Additionally, experiments show that our model has a stable and significant advantage in short-to-medium-range forecasting (i.e., forecasting time ranges from 6 hours to one week), and the longer the prediction time, the more evident the performance advantage of W-MAE, further proving its robustness. | ['Jie Shao', 'Changyu Li', 'Chenghong Zhang', 'Xin Man'] | 2023-04-18 | null | null | null | null | ['weather-forecasting'] | ['miscellaneous'] | [-3.82356882e-01 -3.39885443e-01 -8.41869798e-04 -5.91325581e-01
-1.27694845e-01 -3.64573598e-01 7.44534850e-01 -1.73209667e-01
-2.44406298e-01 9.61346209e-01 4.95032459e-01 -7.04551697e-01
-1.40964955e-01 -1.20832586e+00 -5.58668911e-01 -8.63929987e-01
-7.23550558e-01 6.43427223e-02 -1.19806185e-01 -6.76201463e-01
-4.18217510e-01 4.95315790e-01 -1.49249268e+00 -2.98130177e-02
8.43845546e-01 8.31035376e-01 1.89470172e-01 9.40501511e-01
8.05427209e-02 6.35916531e-01 -5.00467062e-01 -2.58759130e-02
4.15205866e-01 -2.59012848e-01 -4.08549845e-01 -1.14110157e-01
2.86801249e-01 -5.21475255e-01 -4.68963683e-01 4.46384430e-01
3.61786425e-01 4.62648898e-01 3.49840969e-01 -9.52744246e-01
-4.84709501e-01 5.16552687e-01 -3.33095789e-01 5.76240778e-01
-5.02938628e-01 2.35562861e-01 9.66826320e-01 -7.58635700e-01
1.02800004e-01 1.10841238e+00 1.00018072e+00 2.71340609e-01
-1.17866445e+00 -7.22446620e-01 3.36274981e-01 -1.46472275e-01
-1.24000573e+00 -3.26307774e-01 3.24450046e-01 -7.35434771e-01
1.10096157e+00 3.93528402e-01 5.52361071e-01 1.02007973e+00
7.00237870e-01 9.19585302e-02 1.28724122e+00 -6.03705831e-02
2.92377442e-01 -2.00066462e-01 2.20813647e-01 1.87298328e-01
-1.17072374e-01 7.46261835e-01 -3.12997133e-01 -1.39272332e-01
6.68325961e-01 4.54316765e-01 -3.24113488e-01 7.39829242e-01
-1.05354452e+00 9.91105556e-01 6.82471633e-01 3.59249741e-01
-7.70056427e-01 -3.26670031e-03 3.90667208e-02 6.32567465e-01
1.12351847e+00 3.85595083e-01 -9.96146321e-01 9.03875381e-02
-1.45546031e+00 5.57527781e-01 5.92053592e-01 2.59408206e-01
8.11841369e-01 7.28533924e-01 1.89327467e-02 6.78519666e-01
3.10324579e-02 1.08904779e+00 4.44720685e-01 -5.49822867e-01
2.66694427e-01 -3.31481844e-02 3.87939930e-01 -1.16586769e+00
-8.31992567e-01 -7.23869085e-01 -1.54268789e+00 2.96609014e-01
2.67838567e-01 -9.55264986e-01 -1.07042336e+00 1.75651646e+00
7.43725896e-02 7.60938823e-01 3.73945683e-01 9.93640780e-01
7.20779777e-01 1.52314031e+00 1.60666466e-01 -1.07237704e-01
1.00176752e+00 -9.61003244e-01 -7.53800392e-01 -4.39859658e-01
5.03759325e-01 -4.04167652e-01 8.54893744e-01 2.76991576e-02
-5.02557099e-01 -6.87388301e-01 -7.44129539e-01 4.75562185e-01
-8.71268392e-01 2.45678842e-01 6.83024883e-01 2.22909763e-01
-1.17518544e+00 9.24495578e-01 -7.32396781e-01 -8.84399787e-02
-1.18603013e-01 -4.90621477e-02 -2.78057426e-01 2.35611379e-01
-1.89118338e+00 9.30420339e-01 4.01046246e-01 5.47217190e-01
-7.99552202e-01 -1.15472889e+00 -7.95752406e-01 4.33324575e-01
-2.89045066e-01 -5.02066672e-01 1.00291836e+00 -7.94437587e-01
-1.46276951e+00 1.74432918e-01 -4.41171438e-01 -7.04766452e-01
1.30033463e-01 -2.99156308e-01 -1.23310113e+00 -4.40125972e-01
-1.13876835e-01 3.78418714e-01 7.77933896e-01 -1.07544744e+00
-8.13790858e-01 -2.07100630e-01 -1.48463979e-01 -3.34666632e-02
-1.99107647e-01 -2.10285291e-01 1.69814944e-01 -9.08519208e-01
-2.98812002e-01 -8.71523917e-01 -7.21934319e-01 -4.72436786e-01
1.55425832e-01 3.37200835e-02 7.61111915e-01 -9.82959628e-01
1.36364615e+00 -2.10917473e+00 -1.14212267e-01 3.90752077e-01
2.14505583e-01 3.74912173e-01 -4.75805491e-01 5.07735252e-01
-2.82895029e-01 5.46969809e-02 -4.91010368e-01 -4.94315386e-01
-1.74291283e-01 7.98384666e-01 -1.13658905e+00 4.68799174e-01
3.26208889e-01 7.93089569e-01 -6.67270660e-01 3.83542359e-01
2.43898720e-01 5.97220302e-01 -1.82679638e-01 5.48981667e-01
-2.86768734e-01 6.85193837e-01 -1.66797847e-01 3.22389275e-01
9.61484432e-01 -3.23180944e-01 -9.68030542e-02 4.43240434e-01
-4.94326472e-01 5.82735240e-02 -1.03593922e+00 9.74331379e-01
-8.98839891e-01 8.72421503e-01 -2.38327659e-03 -8.14692795e-01
1.14904261e+00 5.02282619e-01 1.67566851e-01 -9.10653353e-01
-2.96449721e-01 2.78355144e-02 -5.96044064e-02 -3.72665584e-01
7.00750530e-01 -1.23783000e-01 1.94611520e-01 3.63488704e-01
-1.47431269e-01 1.15112290e-02 -3.06243710e-02 -1.96484968e-01
5.09875476e-01 -1.93941802e-01 5.94036058e-02 -3.93981874e-01
1.73076987e-01 -1.43046573e-01 6.91065073e-01 7.98181355e-01
1.07007027e-01 4.28029060e-01 1.43762544e-01 -1.11063790e+00
-9.59224105e-01 -7.04866469e-01 -4.43119019e-01 1.31339276e+00
-3.18842381e-01 -2.68591791e-01 -7.87884966e-02 -2.48387113e-01
2.73387313e-01 8.07348430e-01 -9.80703354e-01 2.40369990e-01
-4.25604463e-01 -1.36959374e+00 5.39134204e-01 4.26719606e-01
3.66114050e-01 -9.83277321e-01 -5.10478497e-01 3.97885740e-01
8.87894705e-02 -8.72740209e-01 1.22049168e-01 2.83823520e-01
-1.00420058e+00 -3.70907515e-01 -9.58141685e-01 -2.70461410e-01
2.26726666e-01 1.26256838e-01 1.48290706e+00 -7.83861149e-03
2.96578914e-01 -2.00490609e-01 -2.57015079e-01 -4.60058242e-01
-2.24650800e-02 1.92024991e-01 7.58158416e-02 1.53927784e-02
1.72651127e-01 -9.64083254e-01 -5.88001430e-01 1.43628687e-01
-8.39050114e-01 -1.54228032e-01 3.41820657e-01 1.00874770e+00
2.56410003e-01 1.11962810e-01 7.74227142e-01 -7.62691915e-01
4.78945285e-01 -1.11565220e+00 -9.88675535e-01 9.19710845e-02
-7.00755715e-01 -8.07389915e-02 7.86249995e-01 -3.18194956e-01
-1.01810503e+00 -2.10470214e-01 -3.33440363e-01 -2.96557486e-01
-3.89826208e-01 1.21066391e+00 5.38784325e-01 2.31656015e-01
6.01117074e-01 4.34694052e-01 -3.78754735e-01 -6.50407434e-01
4.57968950e-01 3.94639283e-01 6.61798418e-01 -1.41586453e-01
8.69764507e-01 4.01006550e-01 -3.71899232e-02 -9.53036666e-01
-8.45068455e-01 -3.31557393e-01 -3.24253649e-01 -1.75798550e-01
7.29702294e-01 -1.38645601e+00 -4.39543009e-01 5.83953977e-01
-9.83145356e-01 -8.84644151e-01 -6.64156824e-02 6.67239308e-01
2.04974368e-01 -1.97411388e-01 -5.55648267e-01 -8.13856304e-01
-6.06605887e-01 -6.67447805e-01 8.22341800e-01 1.96144074e-01
-1.98570993e-02 -1.51757658e+00 5.96691310e-01 -3.67091775e-01
1.07389295e+00 4.35650110e-01 6.31706774e-01 -3.41809779e-01
-5.85994124e-02 3.95390354e-02 -2.02352181e-01 1.69228822e-01
1.51684359e-01 9.05611068e-02 -1.29894578e+00 -2.13263020e-01
-7.73058981e-02 -1.38099179e-01 1.30405772e+00 6.80721462e-01
1.19423997e+00 -4.57692623e-01 2.22537890e-02 1.04456973e+00
1.39347172e+00 -1.88017841e-02 5.06684899e-01 2.91065872e-01
4.55933988e-01 5.62604487e-01 2.43840724e-01 7.08483934e-01
6.75978184e-01 6.83837831e-02 4.45174426e-01 -7.03340113e-01
3.73872042e-01 1.52996376e-01 2.22215906e-01 8.32767189e-01
-2.85167724e-01 -4.07652080e-01 -1.19434893e+00 6.81081891e-01
-1.83944726e+00 -1.15098798e+00 -3.36766720e-01 1.88435745e+00
8.26765180e-01 -2.12679923e-01 -2.20881253e-01 -1.30825400e-01
2.28746325e-01 8.46867681e-01 -4.51680809e-01 -5.02500296e-01
-5.20879388e-01 6.25388384e-01 8.52856398e-01 7.53654480e-01
-1.48592794e+00 9.50175464e-01 6.69281387e+00 3.19361538e-01
-1.80069327e+00 1.20765038e-01 8.78324747e-01 2.34707035e-02
-2.18323708e-01 -1.76065445e-01 -8.95002246e-01 6.67757094e-01
1.70304537e+00 2.98721921e-02 3.82490635e-01 7.42633224e-01
6.49615347e-01 -4.01485078e-02 -4.99989688e-01 4.60578293e-01
-4.75904256e-01 -1.61776364e+00 -1.56376511e-01 -5.42131960e-02
1.14175856e+00 6.99562073e-01 1.32416368e-01 5.75595200e-01
7.96996713e-01 -1.38705969e+00 2.80208498e-01 6.24068022e-01
6.05141282e-01 -6.93514943e-01 9.72537816e-01 5.07605731e-01
-1.19796920e+00 -1.07625194e-01 -5.41502833e-01 -6.46660924e-01
1.57157928e-01 1.33654547e+00 -2.60619015e-01 6.38202310e-01
1.01204598e+00 1.14830780e+00 -2.17034176e-01 7.32532382e-01
-1.98846310e-01 1.33443105e+00 -4.59621370e-01 4.38610792e-01
5.98256409e-01 -3.23952287e-01 2.85397977e-01 1.47528124e+00
5.80661058e-01 4.31195468e-01 2.24771485e-01 3.99522245e-01
1.37503102e-01 -2.05304146e-01 -4.79926020e-01 2.93538392e-01
3.01178753e-01 1.04291630e+00 -6.88758194e-02 -6.42284513e-01
-5.24762094e-01 6.27799690e-01 2.10163087e-01 9.03424323e-01
-6.83545291e-01 -2.29049236e-01 1.20452809e+00 -2.58315682e-01
6.39593184e-01 -4.93508995e-01 -3.52597147e-01 -1.30921113e+00
-2.29831263e-01 -6.99964225e-01 2.92594314e-01 -7.31088698e-01
-1.37213492e+00 1.10239923e+00 -2.69487828e-01 -1.06812131e+00
-5.55902481e-01 -5.07308483e-01 -1.20129263e+00 1.51155603e+00
-2.27760816e+00 -1.02258849e+00 -2.48715028e-01 5.22444844e-01
3.26411664e-01 -1.24224111e-01 1.27560115e+00 2.50482261e-01
-6.45090699e-01 1.63295165e-01 7.43874133e-01 1.90407053e-01
7.00107753e-01 -1.12634313e+00 9.06295359e-01 1.13361907e+00
-1.06353909e-01 5.16371548e-01 7.02036202e-01 -5.09636223e-01
-9.88773286e-01 -1.78048229e+00 1.28518271e+00 -9.51323435e-02
8.98452401e-01 -2.58409500e-01 -1.30799031e+00 8.11290383e-01
3.57567608e-01 3.95253330e-01 6.63989425e-01 4.48640376e-01
-4.54110801e-01 -3.07045192e-01 -7.05340505e-01 4.27234173e-01
2.15881571e-01 -5.31827867e-01 -5.54885030e-01 4.11806762e-01
7.27843285e-01 -4.23276216e-01 -1.14643979e+00 4.99797910e-01
4.57611769e-01 -8.44785810e-01 7.85445809e-01 -6.24324083e-01
8.00720811e-01 -2.04925999e-01 -2.29241058e-01 -2.07576728e+00
-7.36500502e-01 -3.68754923e-01 -2.47536346e-01 8.03472102e-01
6.87794864e-01 -1.00000477e+00 2.97311902e-01 3.65422875e-01
4.53645736e-02 -6.85652435e-01 -8.69183004e-01 -6.99622452e-01
6.18877232e-01 -3.67030889e-01 1.05723631e+00 1.42835319e+00
-5.94252825e-01 -1.16076872e-01 -9.52030182e-01 8.76707435e-01
2.31523663e-01 6.21331096e-01 5.68828821e-01 -1.39690721e+00
-2.57930756e-01 -3.40552390e-01 1.83133557e-01 -1.04678094e+00
3.23099524e-01 -3.90999883e-01 1.01850787e-02 -1.12498307e+00
-4.94837761e-01 -4.24951494e-01 -5.06534278e-01 7.51778781e-01
-4.40805912e-01 2.05248930e-02 -1.15331605e-01 2.31373534e-01
2.42507890e-01 8.11494172e-01 7.90728927e-01 -3.66124511e-02
-3.51855129e-01 2.22377837e-01 -4.48329784e-02 4.29846257e-01
1.02432597e+00 -3.93378705e-01 -1.29361004e-01 -7.44087636e-01
2.06483871e-01 1.97169438e-01 2.36750856e-01 -9.40462947e-01
-1.50890285e-02 -5.47178864e-01 7.48637974e-01 -6.58248067e-01
1.89116016e-01 -6.68069899e-01 2.44790822e-01 2.77012557e-01
-2.15308160e-01 4.23902601e-01 5.85909247e-01 2.55205393e-01
-5.64826608e-01 3.36555302e-01 4.82001215e-01 2.98931599e-02
-1.05074346e+00 5.71507215e-01 -8.50187957e-01 -1.61711827e-01
4.51295078e-01 3.65564495e-01 -2.48617187e-01 -4.83716458e-01
-8.55266988e-01 6.21432900e-01 -1.09163269e-01 4.39466327e-01
2.77296513e-01 -9.27089870e-01 -1.15046012e+00 5.66332817e-01
-7.71967461e-03 -1.24175727e-01 5.40432274e-01 4.19451445e-01
-2.05532372e-01 3.19584250e-01 -3.28604765e-02 -4.49913293e-01
-8.09124768e-01 1.59448832e-01 5.46463966e-01 -4.41871524e-01
-6.95501566e-01 6.53706908e-01 5.92421517e-02 -7.80461252e-01
-7.37110227e-02 -8.40574622e-01 -3.74054044e-01 1.97121188e-01
8.81101370e-01 8.15230459e-02 1.11474395e-01 -5.15652597e-01
-1.02871798e-01 4.53838587e-01 4.77642387e-01 -1.17402114e-01
1.88135612e+00 -1.82294354e-01 4.31839153e-02 6.84150994e-01
8.97134364e-01 -1.35572359e-01 -1.41911101e+00 -4.60047990e-01
-2.42875218e-01 -2.03756571e-01 7.41170228e-01 -9.29917991e-01
-1.51696670e+00 1.09557247e+00 5.65351963e-01 2.72540778e-01
1.14476478e+00 -5.25333822e-01 9.39415336e-01 5.19538641e-01
-2.47720450e-01 -6.51802063e-01 -7.61204302e-01 1.17495263e+00
9.13754761e-01 -1.53134358e+00 -6.69142455e-02 3.91490221e-01
-6.14374399e-01 1.09880626e+00 3.29996228e-01 -1.74883679e-01
1.24762285e+00 3.88481081e-01 5.14151454e-01 -6.35592341e-02
-1.04538286e+00 -2.24519074e-01 3.82605731e-01 2.00681269e-01
3.83506626e-01 5.54184735e-01 3.32998306e-01 6.81449294e-01
-4.39880461e-01 3.63880284e-02 3.51191640e-01 4.78957385e-01
-3.29618067e-01 -5.70801616e-01 -5.37335336e-01 3.89519811e-01
-3.90050918e-01 -5.36577463e-01 2.76270747e-01 5.50638199e-01
-1.54139008e-02 1.02326107e+00 4.90581542e-01 -2.81433493e-01
7.30353221e-02 7.81390741e-02 -6.50814235e-01 -5.08667789e-02
-8.27804625e-01 -2.36097455e-01 -5.97182401e-02 -5.36787987e-01
-4.62830573e-01 -3.29291523e-01 -7.95220613e-01 -7.89762795e-01
4.13016528e-02 3.28734457e-01 5.75655162e-01 1.05609262e+00
5.63676715e-01 5.56618035e-01 1.01597083e+00 -1.16371179e+00
-3.31349522e-01 -1.08381653e+00 -7.64467418e-01 1.32299498e-01
1.07705307e+00 -3.70957077e-01 -5.77446461e-01 -1.03432402e-01] | [6.5988945960998535, 2.907141923904419] |
84c924c5-acc7-4f5c-a2ed-cc9e1f457c0e | w-posenet-dense-correspondence-regularized | 1912.11888 | null | https://arxiv.org/abs/1912.11888v2 | https://arxiv.org/pdf/1912.11888v2.pdf | W-PoseNet: Dense Correspondence Regularized Pixel Pair Pose Regression | Solving 6D pose estimation is non-trivial to cope with intrinsic appearance and shape variation and severe inter-object occlusion, and is made more challenging in light of extrinsic large illumination changes and low quality of the acquired data under an uncontrolled environment. This paper introduces a novel pose estimation algorithm W-PoseNet, which densely regresses from input data to 6D pose and also 3D coordinates in model space. In other words, local features learned for pose regression in our deep network are regularized by explicitly learning pixel-wise correspondence mapping onto 3D pose-sensitive coordinates as an auxiliary task. Moreover, a sparse pair combination of pixel-wise features and soft voting on pixel-pair pose predictions are designed to improve robustness to inconsistent and sparse local features. Experiment results on the popular YCB-Video and LineMOD benchmarks show that the proposed W-PoseNet consistently achieves superior performance to the state-of-the-art algorithms. | ['Ke Chen', 'Kui Jia', 'Zelin Xu'] | 2019-12-26 | null | null | null | null | ['6d-pose-estimation-using-rgbd'] | ['computer-vision'] | [ 1.08542576e-01 -2.43616179e-01 -1.89762354e-01 -6.98074818e-01
-9.28497493e-01 -2.48397946e-01 1.75120905e-01 -4.15139824e-01
-2.53138214e-01 6.16123617e-01 -3.76397111e-02 3.63112271e-01
-1.37714788e-01 -4.09894735e-01 -1.01316595e+00 -6.69462621e-01
1.11640267e-01 6.76418126e-01 9.79955718e-02 7.76653886e-02
1.88879222e-01 8.32326531e-01 -1.27876437e+00 -9.66456980e-02
6.69338465e-01 1.37041700e+00 1.45638093e-01 2.00138971e-01
2.21837565e-01 4.01096195e-01 -1.65694535e-01 -3.47059146e-02
7.06968844e-01 2.33989186e-03 -2.89738983e-01 5.11370063e-01
1.31104445e+00 -5.74108422e-01 -4.44055110e-01 1.15315163e+00
5.20453691e-01 8.94578174e-02 3.29674542e-01 -1.21771157e+00
-4.20821935e-01 -1.79254040e-01 -1.03983152e+00 -1.36695862e-01
4.54950988e-01 3.26432377e-01 8.03250074e-01 -1.31227422e+00
8.52304816e-01 1.35047722e+00 8.07787061e-01 2.64156222e-01
-1.38574934e+00 -8.24712396e-01 3.05673957e-01 3.01688045e-01
-1.62788391e+00 -3.49561810e-01 1.17338657e+00 -3.13260168e-01
7.96505451e-01 1.33133933e-01 6.67204142e-01 1.01315832e+00
7.93649778e-02 6.25616491e-01 9.31049585e-01 -2.80647159e-01
-2.38797247e-01 -2.47594178e-01 -2.62632132e-01 9.25793648e-01
2.80050576e-01 5.43119349e-02 -8.03087592e-01 -2.24670749e-02
1.16782296e+00 1.05991326e-01 -4.79872406e-01 -1.29674125e+00
-1.32424605e+00 4.64899659e-01 7.19377637e-01 -1.68449774e-01
-3.80479574e-01 3.11786771e-01 1.49139836e-02 -2.93043368e-02
6.11110210e-01 3.70799243e-01 -8.77985299e-01 -2.14428664e-03
-7.79550612e-01 2.57052898e-01 3.48599255e-01 1.19540906e+00
1.01114523e+00 2.15087816e-01 3.08089312e-02 6.80536568e-01
4.79849100e-01 7.83689797e-01 2.25920126e-01 -1.11618662e+00
7.70025969e-01 5.37749171e-01 2.44763359e-01 -1.48112261e+00
-6.09993815e-01 -7.29415596e-01 -7.43620932e-01 5.94635010e-02
3.58688027e-01 1.69264793e-01 -8.25048149e-01 1.67790318e+00
6.14591718e-01 3.65442842e-01 -5.27222395e-01 1.23083186e+00
8.77139986e-01 5.44480860e-01 -4.00327146e-01 -2.98170000e-01
7.87867844e-01 -1.07011282e+00 -5.36345243e-01 -3.17604661e-01
2.17034951e-01 -8.76706123e-01 9.05354738e-01 2.50911325e-01
-9.61235285e-01 -7.19537795e-01 -1.02650476e+00 -3.44406277e-01
5.84322549e-02 4.12535489e-01 4.24182236e-01 1.33388922e-01
-7.44587362e-01 3.68649274e-01 -8.16529036e-01 -2.17196897e-01
5.45810997e-01 5.65474391e-01 -6.17998958e-01 -2.70603031e-01
-7.06928849e-01 8.90620530e-01 3.98423076e-02 3.98869783e-01
-8.30618203e-01 -8.75431776e-01 -1.10159957e+00 -2.34248877e-01
6.69193387e-01 -6.67939782e-01 9.33054507e-01 -5.89244783e-01
-1.48503709e+00 1.03676522e+00 -1.82141036e-01 -8.30270723e-02
7.58954167e-01 -6.85333490e-01 -1.23145655e-01 1.20233297e-02
8.68015066e-02 7.58325219e-01 1.24483168e+00 -1.42712271e+00
-3.87125254e-01 -7.66859651e-01 -1.92134023e-01 4.40955549e-01
-2.40885630e-01 -3.85111183e-01 -8.79904509e-01 -5.32870173e-01
7.75046825e-01 -9.64350760e-01 -2.02335283e-01 6.46459639e-01
-3.45575541e-01 -1.03486098e-01 1.20542204e+00 -6.04367256e-01
6.41562819e-01 -1.97163963e+00 2.82793313e-01 2.70199239e-01
2.81729490e-01 1.21522337e-01 -5.33987224e-01 -7.06222951e-02
-1.60130575e-01 -4.86936033e-01 1.65646926e-01 -5.56727767e-01
-2.34571490e-02 2.00051039e-01 -1.07425176e-01 1.05445540e+00
3.41940165e-01 9.22231793e-01 -7.60544777e-01 -4.45993572e-01
5.78444242e-01 7.06874251e-01 -5.62788963e-01 1.96745753e-01
-1.99765190e-01 6.65654957e-01 -6.01865470e-01 8.73982668e-01
9.30893242e-01 -3.09747726e-01 -1.91648558e-01 -8.52411687e-01
-1.45450579e-02 3.38292941e-02 -1.27020943e+00 2.34106159e+00
-3.86992961e-01 5.35697222e-01 6.31531551e-02 -9.58979964e-01
1.18335664e+00 -1.54941425e-01 8.67476344e-01 -5.80992222e-01
3.15328956e-01 1.52325168e-01 -2.56836534e-01 -3.12922716e-01
2.49962956e-01 4.28176314e-01 8.42262357e-02 3.43571678e-02
1.56882748e-01 -5.03996611e-01 -3.45057636e-01 -3.21735978e-01
6.30989909e-01 7.50714004e-01 2.99580932e-01 -7.23064586e-04
6.86952412e-01 -2.54979402e-01 1.03960776e+00 3.24360728e-01
-1.88649461e-01 8.99060011e-01 1.11797549e-01 -8.67828310e-01
-1.02074873e+00 -1.02704060e+00 -2.04082042e-01 5.75706422e-01
5.32496035e-01 -2.69409537e-01 -4.35164660e-01 -7.10733950e-01
1.54293388e-01 1.76757410e-01 -3.78167659e-01 -1.41366556e-01
-9.01632249e-01 -5.03562570e-01 -1.78400442e-01 5.87825656e-01
6.19608521e-01 -5.88099241e-01 -3.81128848e-01 2.11952537e-01
-1.23056740e-01 -1.43021941e+00 -6.45205796e-01 1.13185264e-01
-8.80334079e-01 -1.03639209e+00 -4.99680936e-01 -7.77683854e-01
9.30189252e-01 3.72011483e-01 1.09733796e+00 -1.91608131e-01
-4.27722037e-01 2.74845153e-01 -4.25579175e-02 -1.50547728e-01
3.84242207e-01 -1.80880837e-02 3.00075561e-01 1.89919084e-01
3.17806929e-01 -5.47038734e-01 -7.66774178e-01 6.09355211e-01
-3.98074210e-01 1.45735309e-01 5.14875114e-01 9.22458053e-01
1.10815871e+00 -1.44743860e-01 -8.85446593e-02 -4.39928174e-01
-1.14471346e-01 1.21028654e-01 -1.00022614e+00 1.79404259e-01
-3.78710091e-01 -1.76054835e-01 2.33457446e-01 -3.76008213e-01
-8.88705790e-01 7.32194483e-01 1.24572814e-01 -9.23874557e-01
1.71350464e-02 1.20628618e-01 -4.31359708e-01 -6.82374895e-01
4.79314506e-01 1.45933494e-01 1.20126188e-01 -6.00401044e-01
1.89486042e-01 3.68903838e-02 6.69088066e-01 -6.09578133e-01
1.41783535e+00 5.80594659e-01 4.86900121e-01 -5.44498384e-01
-1.10236323e+00 -3.13998878e-01 -1.03975451e+00 -3.09668183e-01
7.96056449e-01 -1.19713998e+00 -6.26525581e-01 6.31699443e-01
-1.20410860e+00 -9.92844775e-02 -2.04719782e-01 5.15818179e-01
-7.43905604e-01 3.69878471e-01 -3.28804284e-01 -2.59987980e-01
-2.48142645e-01 -1.25654674e+00 1.46457374e+00 1.01951927e-01
2.55626515e-02 -6.13191724e-01 -2.06324145e-01 4.26420093e-01
1.75746843e-01 4.76913303e-01 5.74226856e-01 -3.00966855e-02
-1.08695889e+00 -4.25703913e-01 -4.19590801e-01 3.36926520e-01
1.50359601e-01 -4.66206782e-02 -7.09020734e-01 -4.36160117e-01
5.28782718e-02 -5.27603745e-01 4.50926155e-01 5.53689837e-01
1.58371139e+00 -9.42789838e-02 -1.52541235e-01 1.26277983e+00
1.60279071e+00 -2.62010753e-01 1.74719512e-01 3.29470724e-01
1.16419804e+00 4.11821008e-01 1.04543746e+00 5.38813472e-01
3.24963748e-01 1.09688783e+00 8.91694665e-01 -2.64642864e-01
-9.10823867e-02 -3.81562889e-01 3.79545204e-02 7.31456459e-01
-2.10774280e-02 1.81681916e-01 -6.92122102e-01 -3.99980141e-04
-1.89299142e+00 -5.02772987e-01 -1.43200457e-01 2.07523465e+00
7.59099245e-01 -1.92353572e-03 -2.54774183e-01 -2.07060143e-01
6.36831701e-01 3.69900882e-01 -8.92173588e-01 3.86921972e-01
-2.56696582e-01 6.74018413e-02 6.92491591e-01 3.83980930e-01
-1.18961108e+00 8.96869659e-01 5.60588312e+00 8.07775795e-01
-1.22908318e+00 3.38827707e-02 6.49536729e-01 -1.76720396e-01
4.67704050e-02 -2.37728104e-01 -9.39330578e-01 1.22240469e-01
-1.19949058e-01 3.07303965e-01 3.21801722e-01 8.77869964e-01
1.38359249e-01 -4.16162312e-02 -1.29509389e+00 1.54530501e+00
4.76488978e-01 -1.26078749e+00 -2.00555399e-01 5.14968671e-02
1.07669079e+00 1.14387184e-01 2.93434829e-01 -9.87762213e-02
-4.76174802e-02 -8.18119287e-01 8.54432642e-01 6.14662886e-01
9.31002080e-01 -6.92618012e-01 5.68863094e-01 2.67157853e-01
-1.13046849e+00 -2.84328815e-02 -5.71551085e-01 8.54585096e-02
1.81823224e-01 5.33337235e-01 -5.83279312e-01 3.29591453e-01
1.02219653e+00 1.17028058e+00 -5.62979758e-01 1.03278434e+00
-2.75838435e-01 -8.25595260e-02 -4.66210783e-01 3.46857190e-01
1.81761175e-01 -1.97981954e-01 5.53595126e-01 5.97636044e-01
4.83547181e-01 -6.42226413e-02 4.08197999e-01 8.63873005e-01
-7.75339035e-03 -4.51153070e-02 -4.49168175e-01 5.53284883e-01
3.36361527e-01 1.38635528e+00 -3.46444935e-01 1.00893490e-01
-4.74341214e-01 9.08612788e-01 3.48383725e-01 4.41123188e-01
-8.28227758e-01 2.56453156e-01 9.28231895e-01 1.99874073e-01
4.75713849e-01 -5.36935627e-01 -2.72555262e-01 -1.32918370e+00
2.97870100e-01 -7.69676030e-01 -5.26441224e-02 -1.10348785e+00
-1.35371816e+00 3.06051075e-01 -1.68954849e-01 -1.70547307e+00
-7.78742582e-02 -7.30785310e-01 -2.80616343e-01 7.63959050e-01
-1.62617183e+00 -1.31061149e+00 -7.39223421e-01 7.92626560e-01
5.48681140e-01 -1.27509654e-01 6.11429632e-01 1.98828295e-01
-4.20061886e-01 6.53434157e-01 -3.71825024e-02 9.59229395e-02
9.24435854e-01 -8.12977552e-01 1.61253631e-01 5.56772113e-01
1.15851767e-01 3.92637581e-01 4.88096803e-01 -4.31116313e-01
-1.79381418e+00 -1.26797581e+00 6.81460142e-01 -4.91298139e-01
4.40910488e-01 -4.76996779e-01 -5.78208506e-01 5.18983006e-01
-2.67978936e-01 8.07921767e-01 1.82265505e-01 -2.18567178e-01
-3.71334970e-01 -6.44623578e-01 -1.08518136e+00 3.99816155e-01
1.40041173e+00 -4.50187355e-01 -2.46277586e-01 5.06151557e-01
7.03323603e-01 -1.04267883e+00 -8.57302070e-01 6.91285491e-01
5.80677509e-01 -7.18716860e-01 1.43200684e+00 -3.35502952e-01
2.07293451e-01 -6.46009624e-01 -3.63063157e-01 -1.12364972e+00
-4.55967635e-01 -5.77393353e-01 -2.05026254e-01 1.00526929e+00
6.88694790e-02 -2.90659100e-01 1.07834947e+00 4.31517452e-01
-1.11913130e-01 -9.19359922e-01 -1.09360933e+00 -6.33181453e-01
-4.25201744e-01 -3.03147376e-01 7.09415376e-01 8.21774185e-01
-7.96765089e-01 1.26875311e-01 -6.63429022e-01 2.97916740e-01
9.35142219e-01 4.16638970e-01 1.20636809e+00 -1.15378129e+00
-4.91049439e-02 -6.87620863e-02 -8.24087262e-01 -1.48951459e+00
3.59545767e-01 -5.53743541e-01 2.09525377e-01 -1.07508123e+00
1.36484921e-01 -4.15312976e-01 -1.56137317e-01 4.16422755e-01
8.17177119e-04 7.69387484e-01 2.04937771e-01 9.44481492e-02
-6.46275997e-01 8.62541795e-01 1.70251274e+00 -1.94089323e-01
-1.32951677e-01 -1.69955298e-01 -1.13203086e-01 8.83805633e-01
3.75417113e-01 -3.26415718e-01 -3.62161189e-01 -7.08613932e-01
2.71569401e-01 1.40987085e-02 4.99111831e-01 -1.04527378e+00
2.08812922e-01 -3.65407407e-01 9.20319796e-01 -1.25025237e+00
7.56021440e-01 -1.33352435e+00 5.55114858e-02 8.83572176e-02
-2.06970707e-01 5.73058426e-02 -7.73574859e-02 5.17296553e-01
-1.81090146e-01 1.70017675e-01 7.64562011e-01 -8.50075409e-02
-8.35282862e-01 1.00058591e+00 5.76517045e-01 -4.06404994e-02
1.02067423e+00 -5.11410236e-01 -6.76529191e-04 -3.97839814e-01
-5.62818646e-01 2.57226080e-01 6.77953780e-01 5.16302049e-01
8.68555903e-01 -1.71078300e+00 -6.14045382e-01 6.32904232e-01
2.76421338e-01 5.57646871e-01 1.88837558e-01 9.42426503e-01
-6.83176756e-01 3.30581069e-01 -3.29431385e-01 -1.15434313e+00
-1.25421691e+00 2.62420058e-01 3.78344029e-01 2.58421991e-02
-5.59849381e-01 1.06271243e+00 3.61778349e-01 -5.90158343e-01
6.06745720e-01 -4.02503550e-01 1.49115801e-01 -2.49276713e-01
6.21926412e-02 2.13615656e-01 8.89829844e-02 -1.01863134e+00
-4.16289479e-01 1.33987653e+00 -7.24498648e-03 3.69601727e-01
1.66444433e+00 -3.39690506e-01 -2.33285338e-01 1.36709839e-01
1.63832736e+00 -3.36030811e-01 -1.88371551e+00 -6.47778213e-01
-3.75925869e-01 -1.00679433e+00 1.20772809e-01 -4.04066950e-01
-1.55149901e+00 7.64544249e-01 7.37073720e-01 -6.84326470e-01
1.11805677e+00 -1.61555752e-01 7.74659693e-01 5.75192690e-01
4.30053502e-01 -1.22470844e+00 4.58405346e-01 5.49984932e-01
1.19850433e+00 -1.45954478e+00 3.91648829e-01 -6.43664181e-01
-7.27880523e-02 1.21059716e+00 1.20517659e+00 -3.92557740e-01
6.88871503e-01 -1.10807149e-02 5.86465411e-02 -1.14000291e-01
-3.73875439e-01 1.83381796e-01 6.97282016e-01 7.86405385e-01
1.59326166e-01 -2.53292233e-01 -9.56699923e-02 8.34002271e-02
-8.62151086e-02 -1.96298718e-01 -4.35217507e-02 6.18657351e-01
-2.18422174e-01 -9.17688727e-01 -7.09754765e-01 2.75695831e-01
-8.53556544e-02 2.72454739e-01 -1.91703066e-01 8.16857874e-01
3.36001068e-01 3.70156556e-01 1.53256476e-01 -1.77251413e-01
2.95175761e-01 -3.68974477e-01 7.51686335e-01 -5.36854506e-01
2.25041341e-03 5.05652249e-01 -1.82152510e-01 -1.21005237e+00
-6.92344069e-01 -8.58385801e-01 -1.01238215e+00 5.40963598e-02
-3.67441535e-01 -5.77530861e-01 5.80859423e-01 7.59219825e-01
2.11629122e-01 2.32782423e-01 7.61577547e-01 -1.45350707e+00
-6.99710250e-01 -7.64433682e-01 -5.24813116e-01 4.75919724e-01
5.15008390e-01 -9.54809308e-01 -2.82617211e-01 -2.30197585e-03] | [7.524645805358887, -2.639711856842041] |
035feac2-c4b0-4570-810f-afaf9f2fa534 | vital-node-identification-in-complex-networks | 2202.06229 | null | https://arxiv.org/abs/2202.06229v1 | https://arxiv.org/pdf/2202.06229v1.pdf | Vital Node Identification in Complex Networks Using a Machine Learning-Based Approach | Vital node identification is the problem of finding nodes of highest importance in complex networks. This problem has crucial applications in various contexts such as viral marketing or controlling the propagation of virus or rumours in real-world networks. Existing approaches for vital node identification mainly focus on capturing the importance of a node through a mathematical expression which directly relates structural properties of the node to its vitality. Although these heuristic approaches have achieved good performance in practice, they have weak adaptability, and their performance is limited to specific settings and certain dynamics. Inspired by the power of machine learning models for efficiently capturing different types of patterns and relations, we propose a machine learning-based, data driven approach for vital node identification. The main idea is to train the model with a small portion of the graph, say 0.5% of the nodes, and do the prediction on the rest of the nodes. The ground-truth vitality for the train data is computed by simulating the SIR diffusion method starting from the train nodes. We use collective feature engineering where each node in the network is represented by incorporating elements of its connectivity, degree and extended coreness. Several machine learning models are trained on the node representations, but the best results are achieved by a Support Vector Regression machine with RBF kernel. The empirical results confirms that the proposed model outperforms state-of-the-art models on a selection of datasets, while it also shows more adaptability to changes in the dynamics parameters. | ['Hamid Khayyam', 'Mahdi Jalili', 'Justin Munoz', 'Ahmad Asgharian Rezaei'] | 2022-02-13 | null | null | null | null | ['rumour-detection'] | ['natural-language-processing'] | [-1.57365073e-02 2.49680176e-01 -5.96765459e-01 1.57306597e-01
4.68336940e-01 -4.92914617e-01 1.08205044e+00 6.14316940e-01
-2.40710735e-01 7.11511254e-01 -1.87341392e-01 -4.02962506e-01
-6.46457076e-01 -1.22576976e+00 -1.94360867e-01 -9.78228986e-01
-6.05381250e-01 9.77479696e-01 3.62085134e-01 -6.79360390e-01
3.65689069e-01 6.93647802e-01 -1.04692221e+00 -4.47849065e-01
5.52501976e-01 8.73145521e-01 -6.58155531e-02 7.06319273e-01
-1.52662098e-01 8.43379438e-01 -7.15195119e-01 -2.25438699e-01
-8.21800157e-03 -4.34490800e-01 -8.77375007e-01 -2.14298397e-01
-4.75093782e-01 3.31309915e-01 -4.57040787e-01 8.07289422e-01
4.10680361e-02 -1.16360664e-01 8.50428283e-01 -1.63008046e+00
-3.24303001e-01 6.94060028e-01 -5.37454844e-01 4.99885678e-01
3.46823812e-01 -3.52490455e-01 1.17544317e+00 -3.51302981e-01
7.40928948e-01 1.03377330e+00 8.70506406e-01 2.54444569e-01
-1.32982266e+00 -5.47968090e-01 -1.82344802e-02 1.11414276e-01
-1.33349276e+00 -1.40081067e-02 8.07311594e-01 -5.02741456e-01
5.35830736e-01 4.22856212e-01 9.36949074e-01 8.70279551e-01
4.51630175e-01 2.56707996e-01 8.90121996e-01 -1.80326879e-01
1.32762775e-01 3.99762601e-01 3.26072007e-01 7.65217423e-01
2.76193947e-01 -9.66195911e-02 -3.98262255e-02 -5.96943140e-01
7.05393136e-01 2.61138201e-01 -1.28768474e-01 -2.14088097e-01
-1.09829128e+00 1.16514099e+00 7.63139069e-01 8.39474201e-01
-6.70229554e-01 7.33453373e-04 1.94668874e-01 6.69684529e-01
7.72108316e-01 3.50566655e-01 -3.95546585e-01 1.90182343e-01
-9.56456184e-01 -1.06603049e-01 1.31376529e+00 2.73682743e-01
9.32667971e-01 -3.19843739e-01 7.90800527e-02 3.89360428e-01
3.16573024e-01 2.48118669e-01 2.97358781e-01 -4.33844954e-01
-2.03314841e-01 1.06825018e+00 -2.51875401e-01 -1.50899351e+00
-8.04375947e-01 -8.93704951e-01 -1.41781628e+00 -1.51257247e-01
2.38356799e-01 -7.87914470e-02 -6.63706660e-01 1.56108201e+00
4.69493926e-01 4.15292174e-01 -8.63161907e-02 5.66923141e-01
6.60253465e-01 9.54302490e-01 -1.56425536e-01 -5.57012975e-01
9.67446446e-01 -7.78344750e-01 -4.55294192e-01 2.45776549e-01
6.23709857e-01 -4.09703583e-01 1.74948171e-01 1.08887278e-01
-6.97824359e-01 -1.37248307e-01 -6.70982063e-01 7.70337224e-01
-5.75117528e-01 -2.06169695e-01 6.35964274e-01 6.55038536e-01
-1.39111304e+00 7.69073248e-01 -5.26635468e-01 -7.58031189e-01
6.63151033e-03 5.78109026e-01 -2.90541172e-01 1.53272167e-01
-1.42066491e+00 8.05409968e-01 1.85441554e-01 1.61370233e-01
-6.85830951e-01 -5.67096710e-01 -3.69108260e-01 1.87989011e-01
3.27991605e-01 -6.61935210e-01 3.27166289e-01 -9.85983729e-01
-1.08333993e+00 6.34094894e-01 6.72503412e-02 -5.44981718e-01
4.48989391e-01 4.26261425e-01 -4.30716872e-01 1.94836199e-01
-2.17836648e-02 2.31700897e-01 9.70701218e-01 -1.21553981e+00
-3.86826724e-01 -1.37678921e-01 2.00028494e-01 -2.86256641e-01
-8.35043073e-01 -1.64872959e-01 -3.46782953e-01 -5.06843507e-01
1.21622354e-01 -1.15069628e+00 -5.02498925e-01 -2.00114965e-01
-5.01866281e-01 -4.55776483e-01 1.02787733e+00 -3.46505076e-01
1.35862136e+00 -1.71413374e+00 4.41592336e-01 9.21988368e-01
6.56537950e-01 2.83921510e-01 -2.33765900e-01 9.58970070e-01
9.33166072e-02 2.43472844e-01 -3.24963219e-02 -5.77553846e-02
-4.59623814e-01 2.51726985e-01 5.72312549e-02 6.83061838e-01
4.63729352e-02 5.95994234e-01 -9.61925745e-01 -4.78938699e-01
1.07153244e-01 7.39653349e-01 -2.59479970e-01 1.28973901e-01
6.34234920e-02 4.03026521e-01 -6.66370928e-01 3.23528767e-01
4.93584037e-01 -7.69308209e-01 5.29095411e-01 2.89752744e-02
3.33740294e-01 -1.34039164e-01 -1.03057587e+00 6.59258068e-01
-1.88413218e-01 5.83737910e-01 1.84166253e-01 -1.42123353e+00
1.25986588e+00 1.91506281e-01 1.05096698e+00 -3.45641226e-01
1.54566258e-01 3.60282846e-02 1.83523148e-01 -1.01451650e-01
3.01163793e-01 1.38284042e-01 1.50092199e-01 7.57298112e-01
-8.59838203e-02 3.42936963e-01 3.98300320e-01 6.92474484e-01
1.43883514e+00 -7.38236487e-01 3.51677269e-01 -4.49929833e-01
9.58839417e-01 -3.62948291e-02 1.62649930e-01 6.49755120e-01
1.12406574e-01 -5.78802153e-02 8.55360150e-01 -4.46935534e-01
-6.97259724e-01 -6.77978098e-01 -9.32084695e-02 1.08622873e+00
2.95540303e-01 -5.25597036e-01 -6.18284941e-01 -6.40721321e-01
9.09979343e-02 2.06810951e-01 -1.04410338e+00 -3.82071227e-01
-3.34953785e-01 -9.80926514e-01 2.53647000e-01 -1.48614854e-01
1.93570763e-01 -9.83545721e-01 -1.96568474e-01 2.83553481e-01
-3.17663141e-02 -9.29993927e-01 5.20532541e-02 1.07142910e-01
-8.96479905e-01 -1.35764396e+00 -5.54023921e-01 -6.60390139e-01
9.09972906e-01 2.88393497e-01 1.15892351e+00 9.70208824e-01
-1.66658744e-01 4.02102947e-01 -5.40136039e-01 2.74100631e-01
-8.99214506e-01 7.10535884e-01 2.07505479e-01 3.05949569e-01
-5.88240176e-02 -7.58190095e-01 -5.31804502e-01 5.94907463e-01
-8.05704892e-01 -2.83798456e-01 6.52484715e-01 8.03582191e-01
2.92862058e-02 4.88802075e-01 5.47751427e-01 -1.05058527e+00
9.55543518e-01 -1.12244844e+00 -2.85033554e-01 1.86923161e-01
-1.06341410e+00 4.93828133e-02 7.45343924e-01 -6.22556686e-01
-3.28326851e-01 -3.03729892e-01 2.36213416e-01 -1.55473500e-01
3.87000263e-01 8.39598358e-01 4.88931984e-01 -3.45603049e-01
5.67213476e-01 2.42077887e-01 3.10487270e-01 -2.92487741e-01
5.82319647e-02 4.24512118e-01 -6.75984100e-02 -1.47289351e-01
1.04634535e+00 3.25781196e-01 5.41542351e-01 -1.19608045e+00
-3.83485675e-01 -5.39697230e-01 -6.32933140e-01 -4.47048783e-01
6.09919764e-02 -3.55136275e-01 -9.41430092e-01 3.70183021e-01
-7.81652987e-01 -2.13497188e-02 -7.17906952e-02 1.95912063e-01
-4.67722863e-02 2.68089890e-01 -6.72711134e-01 -8.95909190e-01
-4.82726246e-01 -7.25197434e-01 3.72295171e-01 1.30180046e-01
-2.25747854e-01 -1.57115042e+00 4.31009233e-01 -7.94554781e-03
7.44960845e-01 4.01055664e-01 1.12561989e+00 -9.33393061e-01
-3.84464413e-01 -6.18691683e-01 -1.88942835e-01 2.10125335e-02
2.11750031e-01 4.29048240e-01 -3.51184487e-01 -4.78150487e-01
-3.45873564e-01 1.16431504e-01 9.60482061e-01 4.27830905e-01
5.08097172e-01 -4.10299450e-01 -8.81894529e-01 2.76626289e-01
1.30294847e+00 -2.89772511e-01 2.99523026e-01 1.98658779e-01
4.30786759e-01 8.35372269e-01 4.35818553e-01 6.23628855e-01
3.21262658e-01 4.75822568e-01 8.84395480e-01 -1.62706822e-01
2.60698676e-01 -1.81752026e-01 1.77231610e-01 8.61887693e-01
-3.93028378e-01 -5.45467794e-01 -9.79648829e-01 3.95659000e-01
-1.86407173e+00 -1.05424082e+00 -3.59764993e-01 1.98207307e+00
4.31414366e-01 3.04196864e-01 5.43107986e-01 5.71546257e-01
8.71669829e-01 3.40951920e-01 -3.31128508e-01 -1.85977623e-01
-2.64543016e-03 -1.97612211e-01 4.32348073e-01 5.63483655e-01
-7.30393827e-01 7.06408739e-01 6.48445463e+00 5.74233651e-01
-1.24483204e+00 -4.76424694e-02 7.07201600e-01 3.28406841e-01
-2.95467794e-01 1.12468667e-01 -5.54928243e-01 2.97287822e-01
1.15831470e+00 -2.71659642e-01 5.23227930e-01 5.51359236e-01
1.85730562e-01 -7.51431882e-02 -6.19942307e-01 5.12252450e-01
-3.63720469e-02 -1.43854415e+00 -1.72261924e-01 4.48361814e-01
6.35378838e-01 1.09248199e-01 -1.22992516e-01 -6.75036281e-04
3.74620438e-01 -1.06261230e+00 8.74404609e-02 7.14328527e-01
4.39777017e-01 -6.42460823e-01 9.37104225e-01 6.72292709e-01
-1.31869626e+00 -1.85399726e-01 -3.07555526e-01 -1.30172968e-01
-5.97312711e-02 8.62464011e-01 -9.80617940e-01 4.53701228e-01
4.86895353e-01 9.54618692e-01 -7.46474087e-01 8.78992915e-01
1.23383045e-01 8.51989567e-01 -5.75289488e-01 -5.89248061e-01
2.41152659e-01 -4.82395709e-01 6.25339508e-01 9.88098443e-01
1.70811296e-01 -2.80085027e-01 2.52826177e-02 5.64077497e-01
-9.69935954e-03 1.69968665e-01 -5.81312537e-01 -2.79136360e-01
4.57453609e-01 1.72413802e+00 -1.18610799e+00 -1.91115186e-01
-1.01532593e-01 7.59878695e-01 4.14426029e-01 3.12672019e-01
-5.09606361e-01 -1.01892866e-01 4.84820783e-01 6.24589801e-01
9.96791646e-02 -1.93228662e-01 1.67500764e-01 -6.70938253e-01
-4.64667857e-01 -4.08602148e-01 4.15175527e-01 -1.89634010e-01
-1.36642241e+00 9.51230764e-01 -6.87897354e-02 -9.02516901e-01
-5.60185790e-01 -4.36386824e-01 -9.22928512e-01 6.19830251e-01
-1.21976495e+00 -9.55987096e-01 -4.18986797e-01 7.33758390e-01
-1.47396639e-01 -3.01390707e-01 9.11985159e-01 9.77458134e-02
-5.86974502e-01 3.67157340e-01 4.67962056e-01 6.49839714e-02
1.23403579e-01 -9.99919772e-01 2.55885065e-01 3.51716995e-01
2.29442328e-01 5.80975235e-01 1.01358402e+00 -6.79840147e-01
-1.35139728e+00 -7.13274717e-01 1.01871443e+00 -2.69577801e-01
1.05127859e+00 -2.90517569e-01 -8.36522639e-01 4.10118788e-01
4.72110771e-02 3.19133639e-01 3.60149741e-01 3.05733532e-01
-1.06433630e-02 -1.53603971e-01 -1.20022833e+00 2.82925189e-01
9.12920833e-01 -1.13190331e-01 1.08279921e-01 4.81568694e-01
3.55225205e-01 3.66987556e-01 -1.08643126e+00 2.07663298e-01
4.44328576e-01 -9.13167119e-01 1.01233053e+00 -6.14360809e-01
1.64110005e-01 7.23176673e-02 2.88073182e-01 -1.52705896e+00
-6.99839234e-01 -6.93839729e-01 -4.84178007e-01 1.12887287e+00
3.90168965e-01 -1.00312185e+00 1.08174050e+00 -7.22855851e-02
8.27841640e-01 -1.00346553e+00 -9.08809364e-01 -5.24951100e-01
-2.06296429e-01 1.97031200e-01 3.72595191e-01 1.17767131e+00
1.07960515e-02 7.42694378e-01 -4.24164027e-01 -1.29236057e-01
6.15695119e-01 5.85645586e-02 7.68901825e-01 -2.09599495e+00
-1.79438833e-02 -5.25647283e-01 -7.02530622e-01 -6.37446105e-01
2.52804875e-01 -8.41358960e-01 -5.70119262e-01 -1.50567687e+00
1.53512239e-01 -1.03838027e+00 -4.39131260e-01 1.55229151e-01
-3.42524573e-02 2.73515940e-01 -2.52401698e-02 5.99750638e-01
-3.35113525e-01 1.82912067e-01 1.11650944e+00 -2.16709882e-01
-3.32543164e-01 6.07654333e-01 -4.90806907e-01 4.34883803e-01
9.48861241e-01 -5.93033552e-01 -5.42877913e-01 4.13115859e-01
6.26225948e-01 1.64122105e-01 3.27480078e-01 -8.08141708e-01
4.72363949e-01 -5.95056862e-02 9.39065069e-02 -4.56147522e-01
3.67654651e-01 -1.01064205e+00 3.96298468e-01 9.16069448e-01
-1.69459984e-01 2.72983432e-01 -4.41139519e-01 8.13954830e-01
-2.15853825e-02 -2.99060553e-01 5.81381440e-01 8.13418925e-02
-2.59424806e-01 4.78034854e-01 -4.08307910e-01 -1.86500624e-02
1.11540842e+00 -1.44129530e-01 -3.99809897e-01 -7.34074354e-01
-5.81530333e-01 1.55827761e-01 3.96449536e-01 3.72532964e-01
5.12262583e-01 -9.69778180e-01 -8.45162511e-01 1.45499527e-01
-1.57201216e-01 -6.32872999e-01 -2.41706818e-01 1.24514151e+00
-3.27256471e-01 3.44621718e-01 -1.73574373e-01 -6.80953979e-01
-1.26471174e+00 5.76260984e-01 3.66169572e-01 -6.65474057e-01
-4.85139012e-01 5.01719773e-01 -3.02948415e-01 -3.27462554e-01
-1.38221225e-02 2.64127254e-01 -7.49845386e-01 4.26812768e-01
1.11122899e-01 5.37104249e-01 -1.37752622e-01 -9.94480431e-01
-5.45324087e-01 5.44779956e-01 -8.86391550e-02 2.76774704e-01
1.52988386e+00 -1.66030657e-02 -5.36637306e-01 3.49285662e-01
1.22896743e+00 -6.61724508e-02 -6.41904831e-01 -5.57611465e-01
4.39075828e-02 -1.78107738e-01 2.12542713e-01 -3.53114724e-01
-1.45631838e+00 5.87347746e-01 3.00669700e-01 1.06236565e+00
8.88941765e-01 2.21877277e-01 3.89704585e-01 3.34316552e-01
2.76093811e-01 -7.24095464e-01 1.43936023e-01 3.95539403e-01
4.40441489e-01 -1.01289904e+00 1.98537037e-01 -5.36767721e-01
-2.84533381e-01 1.21644926e+00 1.72375396e-01 -3.25873852e-01
1.22812784e+00 1.08549021e-01 -1.77276149e-01 -4.39815849e-01
-8.48881483e-01 -6.33574873e-02 2.25669909e-02 6.08130395e-01
2.27067739e-01 2.58739777e-02 -3.82094502e-01 4.96060923e-02
-8.89178142e-02 -4.02409494e-01 4.72190648e-01 5.19940138e-01
-5.93197167e-01 -9.91316497e-01 -2.04024971e-01 7.34524965e-01
-2.86098421e-01 3.89518216e-03 -7.87653685e-01 8.75362158e-01
-3.19424003e-01 9.43949401e-01 7.30989948e-02 -6.37453735e-01
-1.17960125e-01 -3.65203857e-01 1.16852550e-02 -2.25745365e-01
-8.67549479e-01 -2.98421264e-01 1.92747116e-02 -1.03606910e-01
-5.82608223e-01 -4.41176772e-01 -1.03277445e+00 -1.15099883e+00
-4.88702834e-01 5.71364820e-01 5.42609394e-01 7.66223907e-01
1.98531702e-01 4.31941241e-01 1.18272758e+00 -7.33480036e-01
-3.05906534e-01 -1.03509378e+00 -8.21964860e-01 2.38639355e-01
3.75805020e-01 -6.59541070e-01 -7.05627441e-01 -5.45219302e-01] | [6.957242488861084, 5.661983489990234] |
f4283269-044b-4c4b-9e89-d468ffa2d433 | locally-non-linear-embeddings-for-extreme | 1507.02743 | null | http://arxiv.org/abs/1507.02743v1 | http://arxiv.org/pdf/1507.02743v1.pdf | Locally Non-linear Embeddings for Extreme Multi-label Learning | The objective in extreme multi-label learning is to train a classifier that
can automatically tag a novel data point with the most relevant subset of
labels from an extremely large label set. Embedding based approaches make
training and prediction tractable by assuming that the training label matrix is
low-rank and hence the effective number of labels can be reduced by projecting
the high dimensional label vectors onto a low dimensional linear subspace.
Still, leading embedding approaches have been unable to deliver high prediction
accuracies or scale to large problems as the low rank assumption is violated in
most real world applications.
This paper develops the X-One classifier to address both limitations. The
main technical contribution in X-One is a formulation for learning a small
ensemble of local distance preserving embeddings which can accurately predict
infrequently occurring (tail) labels. This allows X-One to break free of the
traditional low-rank assumption and boost classification accuracy by learning
embeddings which preserve pairwise distances between only the nearest label
vectors.
We conducted extensive experiments on several real-world as well as benchmark
data sets and compared our method against state-of-the-art methods for extreme
multi-label classification. Experiments reveal that X-One can make
significantly more accurate predictions then the state-of-the-art methods
including both embeddings (by as much as 35%) as well as trees (by as much as
6%). X-One can also scale efficiently to data sets with a million labels which
are beyond the pale of leading embedding methods. | ['Manik Varma', 'Kush Bhatia', 'Purushottam Kar', 'Prateek Jain', 'Himanshu Jain'] | 2015-07-09 | null | null | null | null | ['extreme-multi-label-classification'] | ['methodology'] | [ 4.40626651e-01 1.27612635e-01 -4.07734245e-01 -4.62530941e-01
-1.20180166e+00 -8.29559505e-01 5.71650386e-01 4.91276532e-01
-3.12919647e-01 4.49007511e-01 7.89534971e-02 -2.06788793e-01
-4.51242119e-01 -6.66587472e-01 -3.12260747e-01 -8.95047545e-01
-1.60137385e-01 8.41014683e-01 -5.67262853e-03 1.88083351e-01
2.05205008e-01 4.44262385e-01 -1.89831877e+00 3.01730722e-01
2.79160112e-01 9.75762844e-01 -3.52430999e-01 6.81746840e-01
-8.65114108e-02 4.68937665e-01 -1.04094528e-01 -2.30151966e-01
4.21180278e-01 -3.06826923e-02 -8.91005397e-01 -1.34273872e-01
9.39452291e-01 -3.77673544e-02 2.16719490e-02 9.05550897e-01
6.11512780e-01 2.38131806e-02 1.11140358e+00 -1.41549826e+00
-9.36999917e-01 3.10879976e-01 -6.76004410e-01 -1.49950042e-01
2.97871172e-01 -4.42929447e-01 1.54950702e+00 -1.26223016e+00
6.21159136e-01 1.02905631e+00 1.22273111e+00 6.65473640e-01
-1.62145543e+00 -6.19790792e-01 -1.82294846e-01 1.19185455e-01
-1.50770366e+00 -2.66960621e-01 6.04909718e-01 -4.98486638e-01
1.03864980e+00 4.96854633e-01 9.98553932e-02 8.18599224e-01
8.73010680e-02 3.90230268e-01 1.34085834e+00 -6.03045642e-01
8.05411935e-02 3.65855962e-01 5.46598554e-01 9.02400255e-01
1.44744664e-02 1.50116622e-01 -4.40022916e-01 -7.34806299e-01
-2.86492556e-02 2.71473825e-01 4.36686948e-02 -6.37477040e-01
-1.44993865e+00 1.19912565e+00 2.12427661e-01 3.35816622e-01
9.08761248e-02 2.13411763e-01 6.01466060e-01 4.56884861e-01
7.82662809e-01 6.40989542e-01 -6.26425445e-01 -2.66204476e-02
-8.59166682e-01 8.19450095e-02 7.64831841e-01 6.55454755e-01
9.27890897e-01 -4.85777467e-01 4.59740125e-02 1.05209422e+00
1.99105129e-01 7.44038820e-02 6.34464800e-01 -1.02737975e+00
2.43945777e-01 5.97376883e-01 -5.06996028e-02 -8.82868767e-01
-6.71265900e-01 -3.91654104e-01 -7.00031281e-01 2.98500806e-01
3.46243918e-01 7.83133134e-02 -5.59860170e-01 1.73235738e+00
5.05706251e-01 3.06953132e-01 -8.14213455e-02 2.51309216e-01
4.05904442e-01 6.80361986e-01 5.15393019e-02 -2.96833038e-01
1.39093447e+00 -9.23878610e-01 -3.81712109e-01 -1.43787339e-01
1.52591968e+00 -7.62533545e-01 1.04798424e+00 1.17643528e-01
-4.76856560e-01 -4.72307742e-01 -9.83063281e-01 -1.43623710e-01
-6.95752442e-01 5.94188087e-03 7.59818673e-01 6.94530606e-01
-1.12214565e+00 7.58088171e-01 -3.71616840e-01 -4.67306405e-01
3.66924316e-01 6.30912006e-01 -7.76060939e-01 -3.57533038e-01
-1.13174260e+00 1.02444971e+00 3.77321571e-01 -4.73842353e-01
-2.53114074e-01 -1.02046716e+00 -7.80965924e-01 -1.20775104e-02
2.84492364e-03 -4.04209942e-01 9.60307479e-01 -4.87897336e-01
-9.51282024e-01 1.21532559e+00 -5.35821135e-04 -5.84129132e-02
1.45648807e-01 3.39843221e-02 -5.01781762e-01 1.65155306e-01
3.19586247e-01 9.19092953e-01 4.31383431e-01 -1.20905828e+00
-9.06202435e-01 -4.03430164e-01 -2.37078309e-01 1.20182388e-01
-9.46508586e-01 -3.70529182e-02 3.47905874e-01 -4.67493206e-01
2.88171798e-01 -1.41141009e+00 9.58317295e-02 1.88668251e-01
-1.01711884e-01 -7.08990276e-01 1.10570884e+00 -1.81267247e-01
1.16252804e+00 -2.18857360e+00 5.37680313e-02 -3.30935651e-03
4.15562272e-01 2.07319558e-02 -3.71236920e-01 6.69013739e-01
-5.75501025e-01 1.69884399e-01 9.10660401e-02 -5.23703575e-01
2.78979897e-01 2.80819505e-01 -4.86950070e-01 7.55314887e-01
6.78893104e-02 8.19578528e-01 -9.74588275e-01 -5.92263639e-01
1.44897461e-01 5.09022117e-01 -4.54326242e-01 -4.04038914e-02
6.15214184e-02 -9.71334651e-02 -9.46465731e-02 6.77350402e-01
3.86820704e-01 -4.63394016e-01 1.55362934e-01 -1.48381174e-01
9.91419405e-02 -9.33893919e-02 -1.24786413e+00 1.39089513e+00
-5.50231755e-01 4.59631801e-01 -4.85737532e-01 -1.01807904e+00
8.21003616e-01 3.55753541e-01 9.64009523e-01 -8.09086189e-02
-7.30402842e-02 2.97160327e-01 -4.75599378e-01 -1.84738681e-01
1.87522963e-01 -5.34994960e-01 -2.74069846e-01 8.53498757e-01
1.51528999e-01 2.84361124e-01 1.06083276e-02 1.27277635e-02
1.27292728e+00 -2.59186596e-01 4.12843317e-01 -2.90912420e-01
2.39913791e-01 -1.69208482e-01 6.85942471e-01 5.52545249e-01
-2.35840291e-01 4.41810727e-01 4.41997975e-01 -7.37067878e-01
-1.11334109e+00 -9.47955191e-01 -7.28191435e-01 1.77082431e+00
-1.35277957e-01 -6.11799777e-01 -2.55720586e-01 -1.20326900e+00
3.85760695e-01 7.22783744e-01 -9.62344646e-01 -3.46868008e-01
-3.27568680e-01 -8.60518754e-01 5.53804994e-01 5.93494296e-01
-6.69551194e-02 -5.95145166e-01 -6.74288794e-02 9.82943475e-02
1.64227203e-01 -7.60704219e-01 -4.42953646e-01 7.18744218e-01
-8.60580266e-01 -9.41973388e-01 -4.82047230e-01 -1.16033387e+00
7.37949550e-01 1.69842228e-01 9.32900012e-01 -1.42201424e-01
-3.28192562e-01 2.17806906e-01 -3.58377904e-01 -2.27246564e-02
-3.84694129e-01 2.05760196e-01 5.26407659e-01 9.24782548e-03
8.48875582e-01 -6.43720686e-01 -1.84723154e-01 4.88076150e-01
-7.52686143e-01 -1.95476234e-01 5.05333126e-01 1.15695691e+00
6.80755913e-01 1.24084368e-01 8.75364542e-01 -1.27156162e+00
2.98587680e-01 -6.94535375e-01 -3.23872805e-01 4.57374185e-01
-1.21825039e+00 3.19610804e-01 7.75865793e-01 -7.31940567e-01
-2.82927781e-01 4.18091774e-01 -1.69756897e-02 -2.64241427e-01
-1.20328389e-01 1.14165433e-01 7.15409070e-02 -3.84480685e-01
7.14448571e-01 2.52839625e-02 -1.18031234e-01 -6.35066688e-01
7.20750034e-01 1.01183510e+00 3.70438285e-02 -3.88204277e-01
7.83130705e-01 2.68363267e-01 5.17784119e-01 -3.84436816e-01
-1.36099851e+00 -8.25250030e-01 -1.11696625e+00 1.23826250e-01
6.52219236e-01 -7.34881282e-01 -6.79107606e-01 1.87100358e-02
-5.87832153e-01 2.62798574e-02 -4.48592573e-01 3.65056247e-01
-7.51053810e-01 4.18191552e-01 -7.27125049e-01 -3.78802240e-01
-1.70666888e-01 -8.57017934e-01 1.22834063e+00 -2.09473208e-01
-4.84412968e-01 -1.34985495e+00 5.76413035e-01 2.81881362e-01
1.40671134e-01 2.58371443e-01 1.40089130e+00 -1.03151643e+00
-2.06421223e-03 -5.54263592e-01 -2.43866950e-01 2.82831639e-01
1.09731942e-01 -2.41584077e-01 -1.14632988e+00 -6.28784716e-01
-3.04820627e-01 -7.46675730e-01 9.17968869e-01 -1.51003405e-01
9.41421032e-01 -1.75750822e-01 -7.72303641e-01 4.56156492e-01
1.54219413e+00 -2.76351988e-01 9.84448344e-02 1.98389933e-01
8.55106235e-01 6.25334680e-01 7.44694114e-01 2.18151644e-01
2.94037998e-01 9.46398735e-01 2.62355626e-01 2.05805972e-01
-1.61399871e-01 -1.85757428e-01 2.26254120e-01 1.10209715e+00
5.37628829e-01 3.66883390e-02 -1.03098893e+00 5.90779006e-01
-1.78383398e+00 -9.48658884e-01 -5.36936074e-02 2.16686344e+00
9.59669232e-01 -5.42581454e-02 -4.58361916e-02 4.60440844e-01
5.96324146e-01 1.34504884e-01 -4.68059987e-01 -5.64216197e-01
2.09089071e-01 3.69785242e-02 5.05281866e-01 4.85320330e-01
-1.53138638e+00 5.94836533e-01 6.67817879e+00 7.86404908e-01
-8.16751897e-01 3.88340056e-01 4.49657321e-01 -3.23948175e-01
-9.40415561e-02 2.38082409e-02 -1.27898073e+00 3.12595397e-01
1.36440098e+00 -4.76891315e-03 1.42769560e-01 1.09473956e+00
-5.49390316e-01 3.08697909e-01 -1.68610156e+00 1.13691878e+00
2.67500371e-01 -1.15514553e+00 -2.07447067e-01 5.50191462e-01
1.01238561e+00 6.80374680e-03 4.37805682e-01 5.52533388e-01
2.68579334e-01 -1.08785760e+00 1.97077259e-01 3.45229536e-01
1.42751563e+00 -8.31994712e-01 7.16539919e-01 4.21493560e-01
-1.20161188e+00 -5.49886107e-01 -6.74900770e-01 -4.08288166e-02
-1.33840032e-02 9.19885755e-01 -8.51806104e-01 9.68239456e-02
2.55470723e-01 9.04933691e-01 -9.15159881e-01 6.93358123e-01
2.54321188e-01 5.58874071e-01 -4.55007046e-01 2.89298762e-02
3.26148510e-01 1.11974776e-01 1.15386276e-02 1.09726894e+00
4.19909209e-01 -5.68419360e-02 3.85965854e-01 5.62248677e-02
-3.07381958e-01 3.58308405e-01 -9.83877420e-01 6.28136694e-02
5.09925544e-01 1.37747777e+00 -5.94692707e-01 -1.75413758e-01
-6.36980891e-01 1.00338471e+00 8.18295658e-01 -7.18123913e-02
-5.47447622e-01 -3.73361766e-01 7.97366261e-01 7.24317878e-02
2.12667003e-01 4.83130850e-02 -3.20788771e-01 -1.04355478e+00
-2.03045264e-01 -6.05299950e-01 5.60167611e-01 -3.11962068e-01
-1.71691072e+00 3.25067848e-01 -2.84205347e-01 -1.30516839e+00
-3.98661435e-01 -8.45874965e-01 -6.48925006e-02 6.75089240e-01
-1.30177963e+00 -1.40773821e+00 1.38792038e-01 9.51807797e-02
1.64697289e-01 -2.76725799e-01 1.71269679e+00 5.27086258e-01
-3.57189387e-01 8.20338368e-01 9.94177043e-01 -6.09985143e-02
1.12232864e+00 -1.64931607e+00 1.34336036e-02 6.91439658e-02
7.61411011e-01 3.63689303e-01 3.74206185e-01 -2.33324423e-01
-9.65182245e-01 -1.33162236e+00 1.54412973e+00 -1.03119040e+00
7.50782132e-01 -6.08332336e-01 -8.00357044e-01 7.73692608e-01
-3.50988150e-01 7.56112099e-01 1.50644529e+00 5.70282280e-01
-9.46843565e-01 -2.32283637e-01 -1.19823289e+00 3.19431335e-01
1.01235616e+00 -8.87878239e-01 -5.69787383e-01 8.51386726e-01
5.03208518e-01 1.89302608e-01 -1.37564278e+00 3.19169194e-01
6.98109746e-01 -6.67028904e-01 1.07091486e+00 -6.56918526e-01
2.53599405e-01 -9.22259390e-02 -4.79573905e-01 -1.23795438e+00
-7.56959558e-01 -8.15753825e-03 -3.92214030e-01 1.43216562e+00
3.50597769e-01 -6.92582786e-01 8.26475203e-01 4.38892126e-01
3.23123127e-01 -1.16000915e+00 -1.06493628e+00 -7.45969713e-01
4.13193673e-01 -1.38825595e-01 4.04215634e-01 1.42253709e+00
1.67644352e-01 4.95592535e-01 -3.24660987e-01 1.41173989e-01
8.02170753e-01 3.58603150e-01 3.24735701e-01 -1.75817287e+00
-1.68750703e-01 -2.04956830e-01 -9.00129497e-01 -6.57926083e-01
7.55652189e-01 -1.44793141e+00 -2.91587353e-01 -1.26697361e+00
4.19775009e-01 -8.69106412e-01 -7.68453956e-01 8.17008555e-01
-8.09432194e-02 8.22705805e-01 5.44854514e-02 3.81944776e-01
-6.99826598e-01 3.09515119e-01 5.71196377e-01 -1.02329127e-01
2.21257716e-01 -1.24132872e-01 -7.92703092e-01 6.98233902e-01
6.02825224e-01 -9.97320056e-01 -4.17217851e-01 -9.76787433e-02
5.34233153e-01 -2.19521523e-01 9.99657065e-02 -1.01443350e+00
7.67397061e-02 1.48000624e-02 3.80601287e-01 -4.01815742e-01
3.04225057e-01 -9.93349671e-01 8.44920427e-02 2.14601725e-01
-8.55127931e-01 6.31735697e-02 -1.96580917e-01 7.72538960e-01
2.03441805e-03 -4.47905660e-01 9.24073815e-01 1.99547291e-01
-6.48934960e-01 2.53437221e-01 1.06793582e-01 7.75994137e-02
1.50312006e+00 -1.11964844e-01 -2.57700890e-01 2.76044756e-02
-8.54681909e-01 -1.44861965e-02 6.23075843e-01 4.11123008e-01
3.67744744e-01 -1.82477474e+00 -6.26651764e-01 2.05459639e-01
6.47862434e-01 -5.10275304e-01 -8.24397802e-02 5.05855680e-01
-2.07663655e-01 4.67646718e-01 -3.05416458e-03 -4.65107024e-01
-1.61121452e+00 9.33269620e-01 8.57895389e-02 -4.94390339e-01
-6.22141600e-01 8.83406520e-01 -2.10870337e-02 -8.76103580e-01
1.34812891e-01 1.33576468e-01 -1.96924523e-01 5.10025918e-01
6.30835116e-01 4.25469816e-01 -2.84002889e-02 -9.71809387e-01
-4.69322085e-01 1.10789788e+00 -3.25230300e-01 1.32414445e-01
1.45395243e+00 -4.45753373e-02 -1.23012140e-01 8.85566413e-01
2.15738463e+00 -1.02728181e-01 -9.70268250e-01 -3.98642033e-01
2.66445339e-01 -4.88466531e-01 9.28219557e-02 -6.89887762e-01
-5.48839688e-01 1.05750465e+00 9.45808232e-01 2.18409598e-01
7.54941344e-01 1.84463993e-01 7.85143435e-01 5.68890631e-01
4.13697064e-01 -1.08984935e+00 2.37659410e-01 3.47319752e-01
3.67644042e-01 -1.34794796e+00 1.02985755e-01 -2.63242364e-01
-3.47474068e-01 1.12219250e+00 2.41877973e-01 3.34797520e-03
9.71866429e-01 1.09087370e-01 1.52374923e-01 -2.25203738e-01
-9.64032710e-01 1.07950769e-01 2.33886540e-01 5.54127455e-01
4.31756884e-01 1.61863461e-01 -7.18763024e-02 1.38940677e-01
2.98840646e-03 -2.30709121e-01 2.49579430e-01 7.23708749e-01
-6.00702345e-01 -1.38409960e+00 -1.95711330e-01 8.84046972e-01
-4.90041137e-01 3.79523523e-02 -1.75980449e-01 4.07252848e-01
4.11408424e-01 8.20946038e-01 -1.20134257e-01 -5.76159835e-01
4.82689552e-02 8.11600626e-01 1.95300072e-01 -9.65929151e-01
-3.36677492e-01 -5.14025390e-01 -1.04893580e-01 -3.98757845e-01
-1.45540416e-01 -7.37206399e-01 -1.14843261e+00 -3.96810919e-01
-5.77570975e-01 5.76306023e-02 4.80650932e-01 6.64794624e-01
4.36556399e-01 4.68227379e-02 9.28900242e-01 -6.34412825e-01
-1.13479400e+00 -8.58803391e-01 -9.43160415e-01 7.17859924e-01
2.44052589e-01 -8.95526946e-01 -5.87416947e-01 -1.02457069e-01] | [9.496755599975586, 4.349610328674316] |
74658466-796e-483c-9163-c91eba0dfe2f | planar-structure-matching-under-projective | null | null | https://www.cs.umd.edu/sites/default/files/scholarly_papers/AngLi.pdf | https://www.cs.umd.edu/sites/default/files/scholarly_papers/AngLi.pdf | Planar Structure Matching Under Projective Uncertainty for Geolocation | Image based geolocation aims to answer the question: where
was this ground photograph taken? We present an approach to geolocalating a single image based on matching human delineated line segments
in the ground image to automatically detected line segments in ortho
images. Our approach is based on distance transform matching. By observing that the uncertainty of line segments is non-linearly amplified
by projective transformations, we develop an uncertainty based representation and incorporate it into a geometric matching framework. We
show that our approach is able to rule out a considerable portion of false
candidate regions even in a database composed of geographic areas with
similar visual appearances. | ['Larry S. Davis', 'Vlad I. Morariu', 'Ang Li'] | 2014-01-01 | null | null | null | eccv-2014-1 | ['geometric-matching'] | ['computer-vision'] | [ 1.89747155e-01 4.33100045e-01 2.14645132e-01 -4.23609644e-01
-1.01224220e+00 -8.49498391e-01 6.77663803e-01 2.32234314e-01
-4.76001352e-01 4.60931510e-01 -9.84207019e-02 -2.09138557e-01
3.01254471e-03 -9.15838301e-01 -6.67770386e-01 -2.33292580e-01
-2.00444162e-01 4.95349884e-01 4.68395531e-01 -1.77338779e-01
4.03325140e-01 7.90775299e-01 -1.24621093e+00 -3.71759564e-01
8.04358602e-01 7.67320931e-01 -5.51161349e-01 8.82739007e-01
8.06358233e-02 3.82884175e-01 -5.93275666e-01 -5.57555258e-01
6.90929890e-01 -4.51667160e-01 -8.74642432e-01 4.82582331e-01
9.92182672e-01 -1.17692016e-01 -2.97218442e-01 1.39226329e+00
2.32398897e-01 1.29899099e-01 8.07752073e-01 -1.25031304e+00
-4.69236493e-01 2.53549993e-01 -8.81818414e-01 2.84580320e-01
7.66116917e-01 -3.18457752e-01 7.83764958e-01 -9.92772877e-01
6.66468859e-01 8.93065095e-01 1.09605408e+00 -3.71241778e-01
-1.19766593e+00 -1.72707185e-01 -9.75028798e-02 -2.29558170e-01
-2.33376384e+00 -4.57643747e-01 6.01038814e-01 -4.67312753e-01
7.82362282e-01 4.21039224e-01 5.27613699e-01 1.48890018e-01
1.40632734e-01 2.33185276e-01 8.21137011e-01 -9.59332228e-01
6.90916404e-02 1.47295773e-01 -2.52867401e-01 9.71387684e-01
3.97248417e-01 1.04594439e-01 -2.55735964e-01 -3.70865464e-01
1.08634067e+00 -4.05320674e-01 -3.40788960e-01 -6.88884497e-01
-1.28506875e+00 7.82495379e-01 6.26176417e-01 4.11442101e-01
-2.38381580e-01 2.65316308e-01 -4.03020948e-01 1.27702758e-01
5.17745733e-01 5.92915475e-01 1.76022381e-01 2.64723003e-01
-1.28765380e+00 7.48436749e-02 7.12633550e-01 1.33334208e+00
1.16166806e+00 -3.09824627e-02 4.13857609e-01 3.13831478e-01
5.36922552e-02 7.74534762e-01 2.26857811e-01 -1.01071191e+00
3.91636252e-01 4.64256674e-01 4.85089809e-01 -1.59576738e+00
-4.95941281e-01 -1.93601176e-01 -4.18375731e-01 3.12461436e-01
6.06410503e-01 -2.92004198e-01 -8.39476526e-01 1.34439719e+00
3.73962313e-01 5.53789921e-02 -1.65113330e-01 7.05982685e-01
1.41691834e-01 2.78928936e-01 -3.12129319e-01 1.38878390e-01
1.18442321e+00 -5.22641957e-01 -1.75553992e-01 -3.61315012e-01
6.61235929e-01 -9.08629000e-01 3.99144441e-01 -8.10390152e-03
-8.72058213e-01 -4.42963630e-01 -1.26877952e+00 7.48540983e-02
-4.74002391e-01 8.54252651e-02 2.06166551e-01 8.64282966e-01
-1.45253432e+00 4.28203344e-01 -4.04445946e-01 -8.33481908e-01
-2.02420980e-01 4.23899472e-01 -6.49484336e-01 2.95846552e-01
-9.50075805e-01 9.70266521e-01 4.98463959e-01 8.46992359e-02
9.25839767e-02 -3.45413461e-02 -1.17242730e+00 -1.93228424e-01
2.11217508e-01 -7.87412941e-01 9.24030840e-01 -1.01022279e+00
-8.68171573e-01 1.38761783e+00 -1.47247210e-01 -4.97265786e-01
8.96065652e-01 1.05631620e-01 -6.72307909e-01 5.17957151e-01
4.47957605e-01 6.60642445e-01 8.98492277e-01 -1.28246343e+00
-9.33952868e-01 -4.37236160e-01 -8.64193514e-02 4.32278425e-01
4.21010882e-01 -6.81269392e-02 -3.96327347e-01 -5.86699307e-01
8.73555362e-01 -1.14926744e+00 -3.83817255e-01 2.90013347e-02
-4.71730947e-01 4.39960182e-01 2.65698940e-01 -5.58237731e-01
1.05129516e+00 -2.02275085e+00 -4.36266571e-01 8.49292874e-01
1.68152317e-01 -2.87446409e-01 1.93482459e-01 5.30740857e-01
-1.09596945e-01 4.45602119e-01 -2.71790534e-01 -1.04055239e-03
-1.12915978e-01 -1.25161111e-01 -3.96032006e-01 1.09476793e+00
-7.25724827e-03 6.88148558e-01 -9.46483195e-01 -8.33410800e-01
3.40585142e-01 4.88058552e-02 -1.85862370e-02 -2.02389508e-01
3.82459223e-01 1.01265289e-01 -3.86692226e-01 7.04945743e-01
9.62098002e-01 3.79850939e-02 -2.15686947e-01 -3.98222841e-02
-4.29112583e-01 -2.41392478e-01 -1.39066184e+00 1.53335130e+00
-2.09232736e-02 7.90628850e-01 -2.13175803e-01 -5.20679355e-01
1.08379686e+00 1.73849445e-02 4.48472291e-01 -4.46812779e-01
4.64813858e-02 2.46157423e-01 -4.03088987e-01 -1.89024389e-01
1.03448880e+00 -5.95882647e-02 -3.89127105e-01 2.91057885e-01
-1.81069061e-01 -5.83609939e-01 -3.01622421e-01 9.92220491e-02
1.03989971e+00 5.37630031e-03 8.14167798e-01 -2.95329481e-01
4.29465294e-01 6.59782648e-01 3.14501852e-01 1.03365028e+00
-3.82732213e-01 1.25015926e+00 5.75023480e-02 -4.42398041e-01
-1.26418447e+00 -1.20435679e+00 -2.30338499e-01 3.25589180e-01
7.72536337e-01 -1.95770085e-01 -8.74712646e-01 -3.68164062e-01
-3.97122428e-02 4.74931508e-01 -7.68513381e-01 1.58520088e-01
-5.24416506e-01 -4.67637897e-01 8.05450022e-01 2.79152215e-01
6.58130884e-01 -2.35243514e-01 -6.01879835e-01 5.93481623e-02
-2.10106313e-01 -8.09884250e-01 -6.58537447e-01 -1.65529624e-01
-6.16388261e-01 -1.15680337e+00 -9.50702965e-01 -6.62235618e-01
1.08190739e+00 7.52389669e-01 1.04352987e+00 -7.67189935e-02
-2.03987524e-01 8.76067877e-01 -2.46677890e-01 -2.12803543e-01
-1.90138027e-01 -6.19190522e-02 -4.96127121e-02 1.06629357e-01
3.65247458e-01 -2.61339992e-01 -5.45762122e-01 6.44962430e-01
-5.79492927e-01 -2.55650610e-01 3.27130973e-01 6.00814104e-01
5.58722198e-01 7.70979524e-02 -1.15627602e-01 -6.51139915e-01
2.36340895e-01 -4.46983755e-01 -1.01529169e+00 5.91834009e-01
-5.03489912e-01 6.60001189e-02 -4.84416559e-02 2.80395597e-02
-8.27730894e-01 5.87300420e-01 1.81143388e-01 -1.76905572e-01
-1.36571452e-01 2.94733167e-01 1.29938900e-01 -7.90286601e-01
1.07382572e+00 -5.19628301e-02 -3.25972199e-01 5.12562878e-02
6.88070595e-01 3.57948184e-01 1.04523683e+00 -2.78302282e-01
1.32823730e+00 8.70199680e-01 2.86563653e-02 -9.72522616e-01
-2.64717340e-01 -9.29390550e-01 -1.00304735e+00 -3.43538404e-01
7.42606759e-01 -1.03499508e+00 -1.70164883e-01 9.24818814e-02
-1.16547072e+00 2.89880037e-01 -3.25412512e-01 6.07979655e-01
-7.23501027e-01 6.05603099e-01 5.17776012e-02 -8.97309780e-01
2.11900920e-01 -6.45191669e-01 1.25163960e+00 2.80296087e-01
-4.01215285e-01 -1.10018766e+00 3.67062151e-01 -1.63371205e-01
-1.97235271e-02 5.92136323e-01 3.13163489e-01 -5.91983259e-01
-5.97832799e-01 -7.34342039e-01 -3.44425201e-01 -3.72232795e-01
4.76630218e-02 1.47595659e-01 -1.01505435e+00 2.91116573e-02
7.22358748e-02 3.09706241e-01 5.76484203e-01 4.44880605e-01
1.72857091e-01 -2.21543893e-01 -5.55479407e-01 7.56166399e-01
1.71470892e+00 1.38070032e-01 6.73477888e-01 6.48607850e-01
5.52428961e-01 5.80706835e-01 7.87516296e-01 2.47292206e-01
4.27696168e-01 7.28155375e-01 2.73349911e-01 -3.80136639e-01
2.64223188e-01 -5.26665449e-01 -7.61852786e-02 1.62136972e-01
2.74320003e-02 -3.75427186e-01 -1.22680521e+00 7.93188035e-01
-1.95791328e+00 -1.03428721e+00 -4.84710425e-01 2.39623308e+00
1.47419468e-01 -5.96993193e-02 1.08228467e-01 -1.96655005e-01
1.25907755e+00 7.26073012e-02 -2.00989544e-01 -1.25120506e-01
-4.75282967e-01 -3.73810410e-01 1.47228193e+00 8.42147470e-01
-1.30677474e+00 9.29912567e-01 8.26907825e+00 4.05838430e-01
-8.13619316e-01 -2.59339064e-01 4.86869991e-01 5.71465552e-01
-3.54546100e-01 4.41936910e-01 -5.38652480e-01 9.49865803e-02
4.77626503e-01 -5.80391407e-01 -6.35662256e-03 9.44293439e-01
-3.75399552e-02 -8.44172716e-01 -6.51505351e-01 1.07933652e+00
4.47310895e-01 -1.16365635e+00 -2.67706066e-01 1.63253427e-01
1.00480211e+00 3.11436150e-02 5.98536730e-02 -4.82496619e-01
5.80665231e-01 -8.36450219e-01 1.12780237e+00 5.20649374e-01
8.11629236e-01 -5.43915212e-01 5.94496429e-01 1.13319442e-01
-1.22203553e+00 3.82023811e-01 -4.50790554e-01 6.86087906e-02
1.43935233e-01 4.37640905e-01 -1.32336521e+00 8.57526302e-01
3.42802703e-01 1.45473599e-01 -9.52066839e-01 1.57171249e+00
-2.35363334e-01 3.96395521e-03 -7.40906656e-01 6.37229383e-01
3.28738123e-01 -3.85294110e-01 5.12669265e-01 1.04101586e+00
8.64480793e-01 7.90183470e-02 1.80918518e-02 7.74931967e-01
2.86401182e-01 1.31307319e-02 -1.25124526e+00 5.08514345e-01
5.95807493e-01 8.73573422e-01 -1.17223704e+00 -3.09168607e-01
-2.24929288e-01 1.35876167e+00 1.84212327e-02 3.66998106e-01
-7.64008760e-01 -6.50143683e-01 1.44151255e-01 2.78364420e-01
1.21977754e-01 -6.12596214e-01 -3.55512470e-01 -1.27494252e+00
6.49297014e-02 -2.27795050e-01 4.16294456e-01 -1.13170767e+00
-7.55170584e-01 7.36241758e-01 2.18368098e-01 -1.57404947e+00
-7.09335029e-01 -1.97001368e-01 -5.96302032e-01 1.00775504e+00
-9.86234486e-01 -1.16323912e+00 -4.28740233e-01 4.72404748e-01
-4.72469106e-02 2.55572021e-01 6.55053556e-01 -2.01675203e-02
-2.79610157e-02 4.57283437e-01 2.89442003e-01 2.50765055e-01
8.57138753e-01 -1.41855276e+00 7.74102390e-01 1.42579055e+00
5.84100664e-01 5.32003701e-01 9.88500357e-01 -7.74569392e-01
-6.78385496e-01 -9.47296202e-01 1.20721936e+00 -6.73335552e-01
6.16796315e-01 -9.23384577e-02 -5.58809698e-01 1.05577707e+00
-2.83713769e-02 1.50835246e-01 3.53846848e-01 -2.46895790e-01
-2.87850022e-01 2.65572995e-01 -1.32221699e+00 5.63637137e-01
1.00151324e+00 -6.89425290e-01 -8.62640858e-01 2.01316521e-01
1.81238979e-01 -5.30480325e-01 -6.28710628e-01 1.65550768e-01
4.14579064e-01 -1.17246640e+00 1.11422265e+00 1.37737542e-01
-4.41239566e-01 -8.07857215e-01 -3.12406514e-02 -1.25381517e+00
-2.28337958e-01 -7.26355791e-01 9.72543895e-01 1.13996840e+00
2.92545050e-01 -8.23676884e-01 8.92991126e-01 8.89927506e-01
1.97173372e-01 3.24620843e-01 -1.19146705e+00 -1.03136289e+00
-3.58110160e-01 -2.40435392e-01 5.24333954e-01 9.53871071e-01
1.46289691e-01 -2.16885641e-01 -3.12995225e-01 6.58976376e-01
6.63124621e-01 6.73380792e-02 8.24579656e-01 -1.09459805e+00
1.83119252e-01 -2.24341944e-01 -1.14845562e+00 -8.53257716e-01
-8.68843347e-02 -3.95435572e-01 1.88277498e-01 -1.15198016e+00
-4.90276515e-01 -6.31383836e-01 3.27802896e-01 1.45811364e-01
7.24473968e-02 6.43309474e-01 -1.22427121e-01 5.89704275e-01
-5.33480227e-01 7.37752095e-02 4.10612911e-01 -1.33816361e-01
-1.03188619e-01 2.61304453e-02 -4.40407753e-01 1.06491828e+00
5.61699510e-01 -6.59846425e-01 -1.96954146e-01 -4.78445739e-01
3.56824696e-01 9.29228887e-02 4.63438332e-01 -1.39371860e+00
6.98615372e-01 -1.93325475e-01 4.68911946e-01 -6.81842446e-01
3.15473497e-01 -8.70753169e-01 5.55738747e-01 2.46763393e-01
-4.84009162e-02 4.78965759e-01 6.63876384e-02 7.14940906e-01
-3.81012589e-01 -5.52347958e-01 5.91551244e-01 -2.29519859e-01
-9.84867871e-01 -5.02061844e-03 -5.23891449e-01 -1.08268656e-01
1.16592073e+00 -8.78486991e-01 -1.36391565e-01 -7.17928469e-01
-6.69229448e-01 -2.87372191e-02 1.32078505e+00 -7.85356984e-02
3.80464375e-01 -1.33067238e+00 -4.73969460e-01 1.14241816e-01
5.35642564e-01 -1.71017334e-01 -5.29495953e-03 5.33231020e-01
-1.26267219e+00 4.48121816e-01 -1.04378097e-01 -5.80163062e-01
-1.14634776e+00 5.47167242e-01 5.78852594e-01 2.55321950e-01
-4.97831166e-01 7.50209272e-01 1.50267929e-01 -5.63410670e-02
-2.14981884e-01 -3.42306763e-01 2.60902077e-01 -3.49128060e-02
3.10262650e-01 2.76322246e-01 9.78593249e-03 -1.36688483e+00
-4.97727990e-01 1.06496656e+00 4.38542813e-01 -7.48651803e-01
7.37430930e-01 -6.92687273e-01 1.99339449e-01 3.54790062e-01
1.15232980e+00 5.96603096e-01 -1.03994894e+00 -2.81832933e-01
2.94960260e-01 -9.27729309e-01 -2.55339056e-01 -2.80517161e-01
-5.45396268e-01 4.29713786e-01 6.99994504e-01 3.13888639e-01
8.12334895e-01 -1.41590619e-02 1.12137444e-01 3.23888481e-01
7.55967975e-01 -1.07376468e+00 -4.22229201e-01 2.50195354e-01
7.28206515e-01 -1.38629174e+00 3.69790614e-01 -7.50797570e-01
-4.07308787e-01 1.23024261e+00 1.95763767e-01 -3.17565501e-01
5.39611995e-01 -6.38714433e-02 1.76057011e-01 -3.27893525e-01
2.17779979e-01 -5.64917445e-01 3.35075378e-01 8.95030260e-01
-5.86906411e-02 -7.94839412e-02 3.53228278e-03 -3.32029223e-01
-3.89013261e-01 -3.11758697e-01 7.79701471e-01 9.75080192e-01
-6.39546573e-01 -6.95048153e-01 -1.08258200e+00 -1.19372413e-01
1.81552656e-02 -1.11666292e-01 -7.04990745e-01 1.16749120e+00
9.34599712e-02 8.32163513e-01 3.93334985e-01 -4.02221501e-01
3.21056426e-01 -9.07102898e-02 4.64661330e-01 -4.25297171e-01
-2.25970328e-01 6.35778112e-03 1.62310719e-01 -2.50744581e-01
-4.44680214e-01 -7.02881277e-01 -1.02267599e+00 -1.86869934e-01
-5.33469677e-01 3.07547897e-01 6.21533692e-01 6.10273719e-01
2.37440884e-01 -2.96527803e-01 6.99698269e-01 -8.38722706e-01
-2.09810510e-01 -4.07118231e-01 -8.64599288e-01 6.34264499e-02
3.06888998e-01 -5.29120922e-01 -5.46395183e-01 2.38172352e-01] | [7.820370197296143, -2.2888660430908203] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.