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Critic baseline
Figure REF illustrates that, for identical models, the critic baseline {{cite:40d21ad23dc11790941a05e3ee685ff32bc1bd1a}}, {{cite:0a15004e74b45fd9515552faa939db607d29b349}} is unable to match the performance of the rollout baseline {{cite:cbb2aade89e8d9eed655769f7948340b8019258a}} under both greedy a... | r | 76f3d38806228de8127ae2703b4e7918 |
GNNExplainer {{cite:42afe5eeb9fe5f6bc88904289d148237f94bd2d2}} is the first general, model-agnostic approach for GNN-based models on any graph-based tasks.
Given a graph {{formula:2cb1b51d-baf1-4068-8c18-da76fa5e91a1}} with node features {{formula:f51b3192-2297-4516-b695-f6855910c0f8}} and a trained GNN {{formula:3fe... | m | a72177c1fd611099b8014c6e803b0985 |
In the second set of numerical results we quantify the probabilistic performance of APLF in comparison with QR {{cite:869356b3df9550cb40d14a9c011f9391763f6aa0}} and GP {{cite:a2828500e93b7684ee11aa42e6e80a4488047b0c}} and we study the relationship between training size and prediction error. Pinball loss and ECE assessi... | r | 2c805d6bcfe3f019a19dae935a58199e |
One challenge is that it is not practically possible to learn {{formula:5fb02d0d-4570-47c0-9115-0707e25cefff}} -SNICA by exact maximum-likelihood methods. However, by framing the model within conjugate exponential families we are able to perform learning and inference using Structured VAEs {{cite:2d9199427ec50875f8623c... | m | f98fcadf1bb4e6774c7a1bdb71051d24 |
Neural Rating and Tips generation (NRT) {{cite:c1994a05d73d3055468a9b53ed8d320c3a174f7f}} can predict a rating and generate a tip simultaneously based on user and item IDs.
The generation component is a GRU {{cite:3ff56cfcb9363aed4c62d7f1a76c89db1079e09b}}.
We take the explanations in the datasets as tips.
Moreover, w... | m | d41c3fe19783b05bfa5379ee6a4e021a |
We compare our model against three baselines: L2X {{cite:d841e07ba2734e4da37289a561f2803d3b0ef055}}, LIME {{cite:3a004b4d85813229de9001a1a0d0da9a44a38989}} and VIBI {{cite:0c95eb9fb9b550f851e78a4a374b7be5b464d38a}}. The experiments for the baselines are run on the authors' published codes. All the baselines are trained... | m | 52304ad9cf8419c3eeccdd57d2145766 |
Recently, the spin-averaged amplitudes for the two processes (REF ) were calculated in ref. {{cite:f61024cd4ca2e82789be147328e18c56a0fd2d52}}. We have found complete agreement for all terms except for those containing {{formula:05949b09-8c4c-4dab-af6f-b4f95689ca8b}} . We have investigated the origin of this discrepancy... | r | b0c8264e8499615081b1d09e9b43141c |
Regarding the quantity {{formula:6faa5fae-ff8e-44d4-be7f-4151ea68f4a5}} itself, it can be nicely related to the Fourier coefficients of {{formula:b7ba9add-3b75-4d73-994f-1eefc50a2c58}} (see Theorem REF in the next section). We briefly mention the noise stability for a few functions. For Parity ({{formula:7b6b45a7-63... | r | b236a05aa2d67891bbd3eea93a1fe2a2 |
In addition to one-vs-rest, other methods are applicable
for our scenario {{cite:49e16c029b71e97f3868d9b98bcd789f83651f19}}, {{cite:02ee1094e8e62be923c336c9fcdba4c1b5803b63}}, {{cite:ca50c811864f491f9655fb49b6d84c03594314e8}}, {{cite:9b8b7000d6a6d34ae8a619bcd5e66167c53288f7}}.
Because one-vs-rest does not consider labe... | m | b7841c3018a034a2547f1fee29886e21 |
The discovery of these potential laws begins with a formalization of the dynamics of information content utilizing the combination of network dynamics and information theory. The presented network dynamics offers a general description of the information-related interactions between individuals rather than constrained b... | d | e404d6e260533446cef8d6ada589f4e6 |
We further evaluated the baseline Places365-CNNs on the validation set and test set of Places365 shown in Fig.REF . Places365-VGG and Places365-ResNet have similar top performances compared with the other two CNNsThe performance of the ResNet might result from fine-tuning or under-training, as the ResNet is not trained... | r | 4b086133e10e296e4008c860cb0ca8c2 |
The other approach takes advantage of the practically null average voltage drop across the junction produced by breathers. Given the structure of the second Josephson relation {{cite:0d1e5dddd27e9eb139b1591b1fd06c4440ad0121}}, it is possible to define the (normalized) time-averaged voltage
{{formula:fba0b41b-b667-4c9d-... | r | 5c811fb79e2c86602230956042334273 |
Suppose we are interested to obtain a batch of {{formula:9135da98-7c48-4bc3-b91e-b3398086136c}} samples drawn from the posterior distribution {{formula:f133902f-4c2e-49db-8d7f-0b6c7bf22b23}} .
Suppose further that we have a method which, relying on the evaluation of the potential {{formula:e11126ec-8fa4-44af-8548-82d1... | m | f94426651e62e321a0de885a218fe8ca |
Logistic regression on pre-trained Imagenet features: We found this performed noticeably worse than ERM across the board, with a slight improvement in loss on hard positives (but worse than most other methods).
ERM trained from scratch: We found this to perform slightly worse across the board than ERM from a pre-trai... | m | 418e0fe1a4e2486a6f4167fe54303ee1 |
Another class utilizes additional noise or speaker information to guide the SE adaptation to certain types of noise {{cite:6bc95dcebd69662f7983e89175cbf4cd43c48961}}, {{cite:a671399e80c88267edcd7e3a3a424a18072c5cd5}}, {{cite:78c7d473c72ad6d096572a71b9fef2c1a3078dca}}, {{cite:7ee736e3d9a68b24b5ccc13f5930c97fe1a62d72}} o... | i | 4f3a2d5208caad64ef2cbcc12c4e21e8 |
Thanks to their ability to extract abstract information from raw data acquisitions, Machine Learning (ML) algorithms such as Convolutional Neural Networks (CNNs) are fostering a revolution in multiple and diverse fields, ranging from personal mobility to health-care. Nevertheless, the increased accuracy of recent CNN m... | i | 27c4dabc0eeb7737f6b0e15a7535bc7d |
Domain-specific training of BatchNorm
on a mixture of multi-domain data has been proposed frequently
in previous works, under the name of
“Domain-Specific BN” {{cite:4c7a2aed4397e9b4b2af53145ed758e1ea47a789}},
“Split BN” {{cite:f9d725080738ad54d65172abdd5dd55b9b8bbce9}},
“Mixture BN” {{cite:062980034254816f6f069f089a7d... | d | 3fe0ccdb5691774b19061a8f3081f4f0 |
By combining {{cite:743a9cf2865cb3ed20dd93f7a053a200db15635a}} and {{cite:cc9243111e19a8d7f8d35f0c846d0c41bf7e1123}}, the following bound on the Rademacher complexity function is achieved.
| r | 99e84d1d784b556e2925cb1719489a79 |
Here, we consider the goal of finding a sparse
solution to this representation learning problem, one where each feature depends on a subset of the latent factors {{cite:b0eba22ae98b36cc53e7c04004d4e9080dcb0474}}. Sparsity is an assumption that often reflects underlying patterns in data. In genomics, each gene is associ... | i | defcc4c7905e35b17122c63be2705781 |
Rather than applying 2D CNN on variant hand-crafted spectrograms, some researchers try to directly apply 1D CNN on the waveforms of speech/music signal to learn acoustic features {{cite:3257527eee3cb417ef2be094c2e7dfea1164b574}}, {{cite:19e2ac4d8da2d56443b8d6d8aaa31d918bfa51f4}}.
In these standard 1D CNN architectures,... | i | 4611673ef26f68eff8647c90b8ea6e41 |
The first term accumulates a large penalty if it takes long for the agent to reach the end point, while the second and third terms describe the change in free-flight time to the target, i.e. the difference in time it would take, if the flow is neglected, to reach the target from the locations at this and the previous s... | m | db10a68ba9a8d64d1e46b5972c623b09 |
Figure REF provides a global trend in terms of types of machine learning approaches employed in our identified records. Among the ML approaches, we distinguish supervised, semi-supervised, and unsupervised like approaches. The analysis revealed that most of the works adopted supervised methods (73%). From Tables REF ... | r | 0be99ae95cff1b729414fa744cbe20a4 |
Discussion on TUBerlin-Extended: As stated in Section , the results could be heavily affected by the chosen classes for experiments. Since {{cite:d4808f8b8793c4510f2e664d1ab34fb4a498a049}} did not report specific details on their train and test split, we can not offer a fair comparison on TUBerlin-Extended. Instead, f... | d | 27bf097c720b9501459b7764bbf14101 |
The inequality (REF ) still works when {{formula:19c1ff94-b429-4cec-9af4-6c0ac9b38019}} is a nondecreasing convex
function and {{formula:49d05bb2-09fe-40c8-a027-2b207dc9132d}} This important remark, due
independently to Tomić and Weyl, can be derived directly from Theorem
REF . See {{cite:03bc50f228705f0fabbd114da432... | i | b10847b01c14452dc5acd4781e7fb7c7 |
The fast multipole method (FMM) was described as one of the top-10 most important algorithms of the 20th century {{cite:fbcbc0e514e4fce497435177dc677c1be5dd10b8}}. It is a numerical technique that was developed to speed up calculations of long-range forces in the {{formula:ea662248-8262-462e-86a5-4cbe23b0a8c9}} -body p... | m | c5d824908c285c056c79518e8a197d1f |
In the complexity theory, it is a well-known fact that the deterministic polynomial time (P) complexity classes are not equal to the non-deterministic polynomial-time (NP) {{cite:a27f7435eeef75e12c90adc471d6bb5b3852b176}}, {{cite:ebd8f31f8f15cda1d71728359b2df207cc5bda69}} complexity classes. The existence of the one-wa... | i | e128355cec5e3679ac1e91d8c20408ee |
We use the following objective metrics to evaluate speech enhancement performance: the perceptual evaluation of speech quality (PESQ) {{cite:4684694e5e58ab139217bcf22ba24000666ae7d3}}, short-time objective intelligibility (STOI) {{cite:92baeb9defee084444e725f63f45de51b76190d3}}, segmental signal-to-noise ratio (SSNR), ... | r | d77207aba49b6dc6a44f374552f9318b |
SmoothGrad and VarGrad. SmoothGrad {{cite:0e15c1eae6f17c3e8967a2fd4564f6acfc85cb85}} and VarGrad {{cite:49e37cae36029af2e243db802a129cf188cce8ee}} are proposed to relieve the situation where the attribution graph is full of noise.
The SmoothGrad is defined as:
{{formula:d7b2f424-5ea8-4e99-ae93-798e0fc9814f}}
| m | cf624b93bbcef845998965a6e0e63766 |
In addition, {{cite:8b55802a73def4276b37d05269138e41a9afdc5e}} states that the radiative efficiency of accretion flow increases with increasing accretion rate, which gets intensified by viscous interactions. However, since the viscosity parameter of the disc is not related to mass of BH, it could suggest that viscosity... | r | 41641b050712063b9340d5c4f2f6db6d |
The differences created by WaveBlocks and enlarged by attention mechanism are quantified in this part. We adopt the strategy of Post-A with Non-local. The difference is quantified by calculating the Frobenius norm between two gradient-weighted class activation maps {{cite:3d5db8e38fe20bf68be3b2c8856b0b395bbf6c9b}} of t... | d | 4235cf98ac0cdbb654c526fb1bf0e89c |
Continual learning is an active research field within the machine learning community {{cite:36000488fbbb263fb39cfb251975286680d752fe}}. To tackle catastrophic forgetting, CL-based methods can be divided into three categories based on how task information is stored and used throughout the sequential learning process (se... | m | a07d158f072fcc4564c0f7b4aaa7c8b9 |
In Fig. REF , we display the effective potential (REF ) of the {{formula:9fb62116-fb3e-4811-a682-d6fc15f393c0}} Cr condensate in the absence of the temporal modulation of both nonlinearities. One may infer from Fig. REF (a) that the potential energy curves do not show any minimum for both repulsive (dotted and solid cu... | m | aba3849c6abb85d45d120bb8febdf14e |
Mechanical model for cell shape and growth. There are many details of cell growth and shape that require interpretation. For example, it is not obvious a priori that growth should be almost exclusively longitudinal. Therefore, we have developed a minimal mechanical model that can explain these observations. We parametr... | r | abf623cc583a5fc038a9f8f69e82efec |
Various independent cosmological observational data like the Type Ia Supernovae (SNe Ia) measurements {{cite:e8bcea102540836cf71e85be9ff41ce70b37a216}}, {{cite:12abb410802b68a1ef839863d784a6245a0ca3b1}}, {{cite:5fb01755004f1cb6da13ab2032b346ab31a10e08}}, {{cite:384227e3fe8012a06d2ec650b9b13ccebeb22c92}}, cosmic microwa... | d | 1f9bde5b8d8df691dc7ab8817b70404d |
DLPNO-CCSD(T){{cite:78ca539a40ee8dc768331eb4a631dc9a9d839a6d}} single-point
calculations were also performed with the ORCA 4.2.1 software.{{cite:7ff002f642007b3abc3c4f03b3d9e5598e254bc1}}
The Ahlrichs's def2-SVP basis set{{cite:78234e7ac792c47f144d49429f6589e1381b290c}} was
used for all the calculations with the corres... | m | 4b9cc11d41ff6c3f29c7dad8b42d52fc |
Tuning of free parameters: There are three set of parameters to tune in Algorithm 1, namely: i) the step-size {{formula:953309d9-bc64-49d0-9a12-db42f27b4569}} ; ii) the proximal coefficients {{formula:1467872e-c1d3-4d3a-87b2-164f96a573c4}} and {{formula:24fdb023-9fad-43bf-bc98-1b8b33ad9c25}} ; and iii) the weights {{f... | d | d3f150ae0e619e2747b5cc5f89560c5c |
We formulate the disease progression as an Initial Value Problem comprising an ordinary differential equation with an initial condition which specifies the value of the unknown function at baseline. The initial conditions take the form of the embedding vectors which are generated for each pixel of the baseline image us... | m | 4789eb939a818371c4dc12154ed8bf43 |
Tasks like open-domain question answering have been popular in recent times in the field of natural language processing. We know that only using unstructured text cannot be fruitful sometimes as this technique uses shallow methods. Using only a knowledge graph is also not practical because of noisy data and missing inf... | d | c0782fdff866984847e45fe8846bb89f |
Tensor decomposition methods are able to provide a lowparametric representation of specific {{formula:6d0d5f5a-05e9-474e-9f79-7ca56c578a6d}} dimensional arrays that possess lowrank properties. Available methods include the canonical polyadic model {{cite:7a10c506043ebbf44af03a18fe7155a935d93f20}}, {{cite:befb1ae5c616b0... | m | f9bf83c15de2cb825ab5fce067f98d86 |
Efforts have been made by the community that researches Explainable Artificial Intelligence - XAI in developing different measures to explain black box models. Many of these efforts are defined in XAI measures that use the well-trained machine learning model, its input data, and its outputs in order to explain the mode... | i | afbddef282391d7af594b760708b14bc |
As illustrated in Figure REF , inspired by VITS {{cite:26e08a4b981a78bed73ee15dbf7011c5fc72b915}}, we formulate the proposed model as a conditional variational autoencoder (CVAE), which mainly includes three parts: a posterior encoder, a prior encoder and a decoder.
The posterior encoder extracts the latent representat... | m | 6a6277512ffa50749c3c2955100c8f3e |
To derive the data in the MPA-JHU catalogue, the continua of the spectra were corrected for the foreground extinction following the {{cite:2779af5687cb52d24e1205d928afa838bbe358a5}} dust maps and were then fitted in the wavelength range between 3200 and 9300 Å following the models by {{cite:ad34a5ee974f46615d560304ee10... | m | ab5f468c3f4166fa59ee08e2b69989bd |
Theorem 6.2 ({{cite:ec773204f2dd59eee4c4df474dd4dc684ac6976c}})
In the conditions of the previous theorem, {{formula:402306f2-18d3-421f-991e-34122032d49c}} converges to holomorphic functions on {{formula:01000b40-38ea-4a7f-9b9a-943ad1168b14}} and the space, spanned by
{{formula:4d0fd35b-ddc4-41c1-ac15-f1739844d299}} ... | r | 9498aa4cec828b41389a1fe85f2871d5 |
The nonlinear hydrodynamical radial-pulsation instrument called RSP in
the recently released MESA version {{cite:0525caefe29635b0cc293c98e28201e463d68c30}} allows to study in
detail fundamental and first overtone pulsations in RR Lyrae and Cepheid model
envelopes. Light curves of both pulsation modes could be reprodu... | d | a49ef4dd8220d10b7e8f1726b236328d |
Comparing the range of trajectories for each UFD, it is apparent that most have
substantially different orbits for the different values of {{formula:6bb968ee-fa99-4d7e-9f00-787d6daaf46b}} . Since these are just the limits
from {{cite:54c0724d3b3bd23bc1eb0524db29e2ae77fa1e31}}, any similar orbit between these two extrem... | r | 9105648f8e0a5ce368629a43779008e0 |
In fact, our results imply that we can distinguish between slowly rotating Kerr-Newmann black holes
and the Ellis wormholes with their Einstein-ring systems. This is because the leading
term of the deflection angle for the lensing by the Kerr-Newmann black holes in the weak-field regime
is equal to the one for the lens... | d | 4ff5f7c568909c62f847e5bdc48f7403 |
The investigation of null geodesic motion can
reveal significant features of a curved spacetime. Especially, there are unstable and stable photon
orbits around the compact objects. The unstable photon
orbits define the boundary between
capture and non-capture of across-section of light rays of black hole such as the sh... | i | c71f788eb0c07a4d0eac5fdbc811ad07 |
where {{formula:b1101042-e485-45ea-9e30-d08e94f61328}} dB represents the path loss at the reference distance {{formula:0af0f50e-75eb-4990-bd16-a97664929885}} m, {{formula:46ab1239-c4ad-4c8b-8b76-92ed6d276b89}} denotes the path loss exponent determined by the environment between the links, and {{formula:480f1b52-1d6... | r | 53fd59def2d0108c0b2295864fd160b6 |
Finally, a rather interesting avenue to explore is to find more general examples of non-local CFTs, along the lines of our discussion in section . Possibly the simplest such generalizations are the single-trace analogues of the {{formula:53f4d306-792b-4e15-90a7-bfbfb8bea7df}} and {{formula:a4496605-5c32-47b5-935a-5ae3... | d | b09cbc2928387d9985ce9e8fc3301984 |
The key challenge underlying DA is to reduce the discrepancy between the source and target domain distributions, which has been tackled using a number of approaches. One main approach is instance weighting in which the source sample instances are re-weighted to minimize the distribution mismatch while learning a decisi... | i | 6358664eff1b85557a202ec0e756408b |
CAP12 significantly outperforms previous single-model SoTA on ASVSpoof2019: Linear models on averaged CAP12 would've been the best single-model entry in the ASVSpoof2019 competition, and would've ranked 3rd overall {{cite:8f6c6d9abec33aa816290e4da1c41ff5349ab135}}.
{{figure:971d44a6-015d-467f-b794-a0472b82b6c7}}{{figur... | r | 25a536c1fbe0a1aaefd603374b87042c |
Experiments on a number of target distributions have highlighted that the Restore process is particularly effective at simulating from heavy-tailed distributions, a class of distributions that other samplers can struggle with {{cite:ddfcd1adf3c7bd8b843aa9a53d7b88cb5616d2a9}}, {{cite:1861d9dc40d4c95f4a20e79d6689e616b17a... | d | 81a8d6238dc129371858cc4826cf5aef |
of the {{formula:6c3726e9-e9c5-4496-ac6f-c4bb3294d613}} -learning algorithm (REF ) is GAS. We next briefly compare our condition to those proposed in {{cite:8dadd371aa32148e7a24878287c33eb47ea265f6}} and {{cite:80b1cf05a31f7870d1325be46903cd10925bd6ac}}. The condition in {{cite:8dadd371aa32148e7a24878287c33eb47ea265f6... | d | 9c01d122d0af7b7250153dbb03365875 |
Let {{formula:eae648c8-6999-4fd1-b77e-5c22e3df7c51}} be the smallest prime with {{formula:422ed4b4-73c8-4a99-b554-d3458d8abcfe}} and similarly, {{formula:e4bf56af-8476-4bc1-b12c-a3a1a3722f36}} be the smallest prime with {{formula:aac44a88-901e-441f-88b8-05a1007ae683}} .
Now, {{formula:bb9bb191-4cab-438d-8b65-85aef3e... | r | 92fbd609a77b1d386810223986c4eb01 |
Analysis of keypoint representations.
We analyze the learned keypoint representation with t-SNE {{cite:cbe043e591a47659342b0980099af3807f8817b2}}.
The t-SNE algorithm maps a high dimensional space (64 dimensions in our case) into a two-dimensional while preserving the similarity between points.
The t-SNE plot for the k... | r | 023d6453c93e3e5c517ea602d8b0a365 |
The continuous {{formula:29070540-9052-4e62-9f7a-ef9f32c3a887}} -means and median problems have been investigated quite a bit in the specific setting when {{formula:fec384c1-2286-4626-bbeb-b2f53e11d650}} and when {{formula:6eab5a92-18a2-4e2a-9ddd-23b8489e8676}} is the {{formula:363cad84-b21c-4cd9-a6e0-26ffb4a886ef}} ... | d | 1e7f65c2e423df3273de8aa58db3977b |
It can be seen that the proposed unsupervised feature learning method can achieve competitive results on the bearing fault detection dataset, combiming the hybrid model introduced in {{cite:7a2e93c82263a39b9c129dd48dfc600fff4d7058}}.
| r | 09e89722059affc519d424a6fb285d1d |
In conclusion it should be underlined that our analytical expressions for Tan's contact of spin gapped
compounds are expressed in terms of magnetizations which are directly observable.
For example, at very low temperatures, {{formula:e72fd763-2243-4dfd-b190-f098a948fe1f}} , one evaluates {{formula:442a7800-f45f-40fd-a1... | d | 92872108cf2839d8968416b578d27525 |
Using the above cosmological observations, we adopt the Markov Chain Monte Carlo (MCMC) method to explore the parameter spaces of our three VDE models. We modifies the public package CosmoMC {{cite:9a64bc6ae9a464122d8360449cf970f3b1692cd4}} and Boltzmann code CAMB {{cite:065a2e69e1db731895ad77d05f36c1972ed350a1}} to in... | m | 05979b6586cebdbc8835600a6b398108 |
It is vital to note that the system proposed in this work can be extended using additional components with few adaptations to the code. Some additional interesting components to explore are lexicons (both generalist, such as Vader {{cite:4f5ba3865d7fcf79fd38b3992f3c787768874e90}} and domain-specific, such as Hurtlex {{... | d | 33b3f313186e5ca9756e2ea9efc21b9c |
Multichannel nonnegative matrix factorization (MNMF) {{cite:25deda6487de09fde609d40b8eb34b7d02bf5b38}}, {{cite:c9704127b1147fd963757d4bba7aa07d0948e9c9}}
is an extension of nonnegative matrix factorization (NMF) {{cite:58e5c22fbabb72f2087e723ec0707513966eb41f}} to multichannel cases, which estimates the spatial covaria... | i | 26d543a8a879fd4e35b05b1f7d8cdaac |
Finally, we can easily recover a very recent result {{cite:98968b65f508bae670d2995c631ffc6870e9a7c3}} concerning light rings in extremal, static and spherically symmetric black holes within the framework of General Relativity under the dominant energy condition. Specifically, if the dominant energy condition holds, the... | d | 94f38734ca0d6d526392afccb59c3d96 |
Finally, we also tested the fgsm {{cite:a170eaa880f165d3c08c7db76158b5007010d1ad}}, which is the first method for generating adversarial samples. FGSM can be considered a single pass of pgd on the loss function with an equality constraint on the {{formula:66ebabcb-afab-4a87-b4e8-75459d06b6fc}} distance, i.e. the adver... | m | e71151e5efcb9a4606cb4cef712dec0e |
In case of normal-inverse Wishart prior the posterior density with parameter {{formula:0f0cf353-47ae-4683-aa85-bbba2ff7bd82}} is the following:
{{formula:c549d7d4-960a-4047-a752-8ce1ed16fbb9}}
After taking logarithm and differentiating we get :
{{formula:529a6e58-3979-4952-bb25-b874ee1a14b8}}
By applying Theorem 4... | r | 84f9bba1fb3d079643304267021c1536 |
A single-photon emitter is a crucial component in building quantum information technologies, such as linear-optic quantum information processing {{cite:a9d3be479787d7c80d834b3748af32bb8bb553e4}}, quantum simulation {{cite:f62189d31187308ef2dc1c944db2c5a35f534980}} and quantum communication {{cite:bee5423d595d8f7cf69933... | i | 5dbc6e8831c53d83bfd50a681b211a08 |
Table REF (part 1) shows the ASR results on WSJ. Rep-Phonestream augmentation improved the baseline WER by a margin of 2%, while none of the other augmentations helped.
This corroborates our intuition that data augmentation works better when synthetic inputs are similar to the real training data.
Furthermore, we conti... | r | 318ed5db8be2e835c2dacf8483ec4146 |
Therefore, we obtain the heat current from electron part as {{cite:3d9673ba08b96b9300428d26ce95bcb70ee66f09}}, {{cite:71a3eba588734738359f1f171eb2e9ffe976d6fd}}, {{cite:f5d75fe9b87e5b184733af904bd9e8374475465d}}
{{formula:b9770ac3-8f63-48b5-a6a3-d95d0dd7ca8a}}
| m | 248ff014196fe285c03aeb43d7a2d8c3 |
Another major implication from the asymptotic posterior normality is the ability to facilitate the derivation of the reference prior suggested by {{cite:4c61b8d765e56282b5880e67afec7f776c962d2e}}. This class of rule-based priors attempts to maximize the information from the sample so that in a formal sense the prior ha... | d | 2c5cf4d3b2051600a5bef20d940af173 |
If one seeks to reduce the complexity of a model or the size of a data set, it is a common approach to project it to a lower-dimensional linear subspace of the state space, which is believed to contain the most important interactions of the model or the data set. The hope is that the parts which are lost during this tr... | m | 31610710408b90615a4f06d339ca62b1 |
The virtue of the real-space approach lies in its elementaryFollowing the definition by Richard Feynman, elementary does not mean easy to understand. Elementary means that very little knowledge is required ahead of the time to understand something except to have an infinite amount of intelligence. nature. In developing... | d | 98963bf2e6abacf19215827ce6468657 |
We test our comprehensive search method on widely-used face verification benchmarks including LFW, SLLFW, CALFW, CPLFW, IJB-B, and IJB-C. The results are shown in Table REF . The bold numbers in each column represent the best results. In Table REF , the last line represents the baseline results without any search-based... | r | 1ce570f4275f7f54ced786df444b4235 |
The QSCMF theory is a kind of mean-field approximation based on the nonequilibrium Green's function, which is similar as the mean field approach in the literatures {{cite:5769172bf0b523cc389b146cfb3eaa1118f9d6c8}}, {{cite:6c34776634251891bf2fbbd85dfbcaa7328d7a00}}. The QSCMF is a good candidate to solve the nonlinear p... | d | 3db614b5b9c2ad79f51a01c9eb048f0d |
Analogous results arise from considering a fully classical damped harmonic oscillator with complex position {{formula:1aa0558c-704e-4871-ab1c-bb54fb3655ef}} , driven by the force {{formula:71996a22-3bd1-464e-9947-a8dae43fa334}} , with a slowly-varying amplitude {{formula:50d14adb-bc2f-4944-a413-a2d8e90ad636}} , where {... | r | 48ce6ed5f31cebdb96fb9978e399f7a7 |
where {{formula:2fccddc9-fc91-4710-a7fa-4d0025b74c74}}
are respectively the susceptibles and infected,
{{formula:c26954d5-f852-48d0-927c-8eb720006702}} are respectively the infection and recovery ratios,
{{formula:c3db2626-a6db-4f18-beb6-9aa7be61b092}} is the graph Laplacian
matrix {{cite:6851abfd06c3198d27b7f86cb8c... | m | f8235c8a5ae0acecd4d62d10638c7d96 |
Several studies have demonstrated the
inaccuracy of
linear approximation spaces to deal with parameter-dependent hyperbolic partial differential equations (PDEs) with parameter-dependent shocks:
this challenge hinders the application of
parameterized model order reduction (pMOR) techniques to this class of problems.
To... | i | f061d93f62b7e2504cee46918038558c |
The X-ray Quantum Calorimeter (XQC) is an instrument flown on a sounding rocket that provided high-resolution X-ray data for the diffuse X-ray background, including the CGM {{cite:fb9a020ee51a7fa50cbed656e9527c02862076ef}}. It has been flown multiple times, including observations during 1999 and 2008 targeting l = {{fo... | d | 0f177783a4ff01b48719635948dafec9 |
We propose a multi-objective optimization based solution to mitigate both directThough not done explicitly, reducing direct bias also reduces indirect bias as stated by {{cite:775d42ab0c289f95e683b50828d539eca5ca8817}}. and gender-based proximity bias while adding minimal impact to the semantic and analogical propertie... | m | 15c272e121381522e5fbd6ce0a627925 |
The data size requirements of the GLM point process model are reasonable for our purposes,
as indicated by our ability to recover stable repeatable influence kernels with 15, 60, or 180 minutes of data.
(See also the SI for a simulation test on data size requirements).
The approach requires the same amount of data as d... | m | 54091903e52958e9c40f6e4b22198b65 |
Networks.
Erdös-Rényi networks were constructed by taking a large number {{formula:ba6ea611-a124-4c93-96af-3d0a6d78dcb3}} of nodes and randomly connecting any two nodes with some probability {{formula:2e5dce9c-8418-4ae5-b601-235f347eeee5}} . This construction algorithm yields a Poisson degree distribution with the mea... | m | ff26fdd0b937b4b8afc6f4714042d1c7 |
Another source that deserves spectroscopic follow-up is N5486-2-1. Although this was located within {{formula:9708ebff-043c-4305-b1d7-7d11fa124003}} of NGC 5486 and does not satisfy the classical definition of an outlying H2 region, assuming it is physically near NGC 5486, it displays many properties similar to local ... | d | d7e0c44258238ad8b604bdc293ea03e6 |
CLEAR is based on the view that a satisfactory explanation of a single prediction needs to both explain the value of that prediction and answer 'what-if-things-had-been-different' questions. In doing this it needs to state the relative importance of the input features and show how they interact. A satisfactory explanat... | m | facefc298ff510b0811cf345b5aac322 |
Extending recent work on stress fluctuations
{{cite:c8c2ebcafe1e63df55f61705324a115f91c9a06a}}, {{cite:d656087ae93d5b0e55b37af690e1a9f007479657}}, {{cite:a30350ff511c2c672a1a47064ae1d55d78236d17}}, {{cite:c4412ed71d0e042f68d04b006eedc31e5de591fc}}, {{cite:feea8315b6e21038d7ceaf5e0baac4a5d822d982}}, {{cite:2635f0ec9c085... | i | 93a751f8628ba9938a99f13569a99fa2 |
We adopt average accuracy (Acc), sensitivity (Sen), specificity (Sp) and F1-score (F1) for quantitative evaluation.
Besides, following {{cite:8d0c79821e41572efdde48fd0762b94237079dd1}}, we evaluate A/V classification
on the ground truth vessel pixels rather than the segmented vessels, which is more strict since some ca... | r | 62119cd293c2cda186e4dc05f854eb27 |
The space {{formula:5c67d003-b8b8-464d-bd02-1f6a23f2d035}} is endowed with the norm
{{formula:370aac48-0b07-488b-9629-4ac3631ebd77}} and it holds {{formula:b4f30b82-d42c-4a5e-920d-6d3ce912dd18}} . Our main reference for functions of bounded variation is {{cite:290108fa2e1ef1f9bd7157d1b4cac5e8cd8028ab}}.
| i | e37bad8e61470d16b0a27f6d39898ee7 |
This work can be extended in a number of ways. One potential direction is to use different ways of creating model ensembles, for example, by using Dropout {{cite:b792321251ece700c27393e8902aa4faf028cb28}} or pseudo-ensembles {{cite:74de560682814fc58c922d4c017d54a326e387bc}}. It is interesting to investigate how the pro... | d | b7604c1a91bc1f697a5614689faa7a19 |
The convexification method.
The main idea of the convexification method to solve (REF ) is to minimize the Carleman weighted functional
{{formula:0d5fd6b2-5369-4fd7-b07d-e21d316e9b88}}
subject to the given boundary conditions for some
Carleman weight function {{formula:dafdc342-ab32-47e5-8b70-da8920dbcda3}} .
With su... | m | 93e903c37e13b9a27dec49c2dab1a7fe |
GSD vs. Single Pass Models
The current state-of-the-art single pass models for inference on OOD data, without training on OOD data, are SNGP {{cite:2776ffcf767ba29c1aef427aeb45efac2f570546}} and DUQ {{cite:7795c883a1f36a9e80e66970ed408bf4c08839f3}}. The primary disadvantages of these models is:
1) Hyperparameter Combin... | d | e1e0a1e8130edfb032de4157980db18d |
The numerical algorithm considered in this paper is based on the ideas proposed in the works {{cite:e1414e92c2165858ee53f230aa9aafe136a33094}}, {{cite:e22502d26cc953fca716d361472d8cbd59e7ec6e}}, {{cite:778db4c5c2ced87a4fec3486088fca10cee463aa}}, {{cite:9f2ace524b549cd63612229494fe43e106d4f1cb}} and modified for applica... | d | e0a4dcca6794c6c5b6dcc55f1a128497 |
We will label solutions as usual by the integerThis restricts the generality of the method but getting non-integer {{formula:741b4ada-8c53-4258-ac4a-f97e87685a93}} solutions to work is highly non-trivial due to the complexity of the EM which only contain explicit integer powers of {{formula:b7720053-a053-42d8-bd98-163... | r | 7e48acbc63cc771e9257c7ec16ab7009 |
Denote {{formula:d1141c3c-1305-4afe-9620-d2aed503f747}} and fix a bounded infinitely differentiable function {{formula:fb4c2cca-0483-4d40-bc00-e9d6766a057a}} defined
in {{formula:11cef833-c921-4b6c-a8e8-a4842ed4b8e1}} such that (see e.g. Lemma 4.13 in {{cite:b79b69f6c83fadece5daaf28ad6bb0a97452c17e}} or formula (2.6... | r | 19116e5456b389746eb0dd0682ef36d1 |
Table REF represents the challenge benchmark {{cite:1e740c1470c23b1965731160a3c559cc47e796c9}}. The best 3 approaches achieve above 30dB PSNR, which denotes a great reconstruction of the original RAW readings captured by the camera sensor. Attending to “Test2", the proposed methods can generalize and produce realistic... | r | 8da553157a095d78348d956b993962c0 |
In Fig. REF , we present the results for the condensate of {{formula:49883dde-53e8-49f3-8155-d2b3d6f845bc}} Cr atoms which have a moderate dipole moment corresponding to {{formula:dacae44d-2283-4477-b5df-7650d0fce3cc}} {{cite:ffa295650969d53329e2d37c01d47bc5838ad5be}}, {{cite:9aaded3dc61c5eb4f82e1badc709eea043d1ffdf}}... | r | d1baeee8ad390fb0b4d1887a5a944910 |
For the first automatic speaker verification spoofing and counter-measures challenge (ASVspoof 2015 {{cite:ffa9e2291d17390d8e8fcbfae32b7bd1de72a5fb}}) even though the best results showed an overall average detection EER of less than 1.5%, the EER of unknown attacks is five times higher than that of known attacks. In ad... | i | a0418111805f57321fc30783c5a29ce6 |
Limitations of state-of-the-art KGE Models:
KGs are openly available, and in addition they are largely explainable because of the explicit semantics and structure (e.g., direct and labeled relationships between neighboring entities).
In contrast, KG embeddings are often referred to as sub-symbolic representation since ... | i | 2d5fa3ef0a32af72c10e9b43e71abb20 |
We first give the necessary notation used in this paper. Let us assume we have {{formula:ee848c24-521c-4db6-84bf-de00f1f9e4dd}} i.i.d subjects, where we observe functions {({{formula:c306488b-95ab-4306-96f9-b2cdf7376712}} , {{formula:0a5101d5-8572-4bb4-a7ce-fccb7a588213}} , over a compact time interval {{formula:0cb11... | m | f32c01ba18e0aeba43fb65fe338f635f |
The algorithm below-{{formula:8adb1ecc-999e-457d-aa97-e951ea0ac9e8}} is just modification of the algorithm {{cite:ed84a86370a5bb7b9f10edccbc7d862559cb05a6}} or {{cite:a0fdb2871185f0d52add30be60c4eb06bfa5ec8d}} in the input phase.
We show observing just {{formula:d93c61f8-26e5-4ea5-b9c3-adf99c057c58}} many entries in ... | r | 0f322729961c6bd3fa259864360103aa |
To this end, we introduce RONELDv2, which incorporates the use of lane point variance, lane merging, and an exponentially weighted moving average method to compute weights in order to strive for a more robust and lightweight solution which further improves on the RONELD method and increases its suitability for real-tim... | i | 95cd3d04618a050ef943e0bc48ee40f8 |
The procedure for computing a diffeomorphic deformation can be modeled by an ordinary differential equation (ODE) parameterized with a stationary velocity field {{formula:bd41b74d-9195-4ebd-af66-5e18f905d215}} {{cite:121da4de531d3c135ce5148facc5246da5f0e82c}}:
{{formula:0684be4c-640e-419e-a51f-52576e22c41a}}
| m | ffed158f4cbf4bf09fef0a71382a69ba |
First we introduce notation. Let {{formula:a8b904de-168b-4d4a-a91f-4c5991619175}} be a non-negative matrix containing the imaging data, with {{formula:7a58f39b-1b25-4c9d-8013-ca6770a6575c}} frames of {{formula:b51c0d22-a048-4d57-80cd-d345cf713abb}} pixels or voxels each.
The goal of non-negative matrix factorization... | m | a520d557632a7257777e3ea9503c8fda |
Our primary focus is on fully Bayesian estimation of GGMs, which remain relatively uncommon in practice compared to classical methods. While several classical regression strategies have been employed, only recently was a Bayesian lasso regression characterized {{cite:c1bee73d8128f2869a82ce4e25f365d48d8c284b}}. Perhaps ... | i | a2fea96013c81482f85e78a07cdc4432 |
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