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The ability to communicate effectively with other agents is part of a necessary skill repertoire of intelligent agents and commonly seen as one of the great achievements of humanity. A number of papers have studied emergent communication in multi-agent settings {{cite:1068e435a362968ce4828b5278a9e07b07420337}}, {{cite:... | i | c0688d6de7e337991cd88a582c85786e |
We introduced a multitask learning approach to AQA and showed that MTL performs better than STL because of better generalization which is especially important in AQA and skill assessment since datasets are small. We showed that the representations learned by our MTL models are better able to capture the inherent concep... | d | 00ee1dbd9fd268257c0cd4b72ab4891a |
We use faster r-cnn {{cite:8f58806319c6825eb82ab6f00988db6abf65fad4}} and mask r-cnn {{cite:1b5f1a753bdf5878defe296a733fccd422540e5b}} algorithms to benchmark the newly created dataset for graphical object detection task in business documents. Experimentally, we observe that the creation of a model trained with iiit-ar... | i | 86bfd0c17e667c34c197dcf6a16e7707 |
It follows from {{cite:7b1f3bee17a759ae98e1e0f39ea1baddd4cd1ed2}} that
{{formula:7e2101bd-e3d2-49eb-89ae-c24fab1e402d}}
| m | b47b238683896851d61ff388d57c9b81 |
This is reminiscent of the case of asymptotic coherence distillation. As shown in Ref. {{cite:32a5eb1b7cf535247de18d198ff43588621135c6}}, in the asymptotic case, the distillable coherence of {{formula:ed6d6f4d-4ae4-49c8-8846-3494ed0f371f}} is
{{formula:f9a5dcdd-e824-4b00-bf81-98f646a0f80b}}
| d | 34cf21095856e8dcb328cd1cc7f6f3fe |
Related to GAN reconstruction quality is the ability to efficiently find a latent code that corresponds to a target image. Longer optimization can better reconstruct the image, but becomes intractable over a large dataset. In supplementary material, we investigate classification accuracy as a function of the number of ... | d | 1f5a4920b83838735770f6408562cf8a |
While fitting the LSPM is computationally feasible on the networks considered here, there are many improvements that could be made to shorten run time. For example, a preprocessing step can be used to decide the truncation level of the dimension of the latent space to be fitted. Using a truncation level that is close t... | d | 62f4b6cd00f9f422b4ead384283aabcd |
This appears to be a viable alternative to that which we have
presented in the main text; it is worth briefly outlining the
method. The basic idea is similar to operator (Strang) splitting
and the method is discussing in some detail in
{{cite:15f6660e500abe7b3836ff6f87f9b941118db2da}}, {{cite:5b1bd7cdaf76b203bd5e1057b6... | m | 0586db4f98be114f7d6749e5be892e65 |
FPFH {{cite:a17a9f1d0efe2308236af3ab04af68c599f37b1b}} and FCGF {{cite:1f3bf1a2493134b0d6e0dc664d50993efb79fa67}}: State-of-the-art hand-crafted and learned geometric descriptors used for point cloud matching. We densely extract these descriptors and train a custom shape vocabulary on the global map. We also compare t... | m | a5fdff64256b99dc706f4a3ad31e6cad |
IIR-SNN with and without batch-norm. Recent works have achieved low latency by adopting batch-normalization (bn) suitably in SNNs {{cite:38a774de214c4dd03cf80e357a15558f049b4a88}}, {{cite:984a80d39783b48e92c1bb6ade048cd7db810e21}}. To disentangle the effect of bn from the proposed gradual latency reduction scheme and ... | r | 88d614b096ecb7635d073f4a2d3fca87 |
To conduct experiments and determine the effectiveness of our method, we choose three different biomedical image segmentation datasets as the use case. These three different datasets have different types of segmentation masks. At first, we experimented with the 2018 Data Science Bowl (DSB) Challenge dataset {{cite:4fcc... | r | 0ec7abab84f96f924e718f18e4fe0590 |
In recent years, several vector charmonium-like states have been observed, such as the {{formula:f28f4f66-f428-4ad0-b270-7775add16e15}} , {{formula:3f6b9034-52fa-4465-b898-e309c87fba38}} ,
{{formula:71390ad3-ff35-47cc-b3db-8bc1a22ff9eb}} , {{formula:d4b10db4-493b-440e-b528-b5214b08878f}} , {{formula:c7e07177-33b1-454c-... | i | 8b17a0c13bf0c45a443ebde8697cebbb |
Modified weak formulation.
The nonlinear system () is equipped with non-homogeneous boundary conditions. The analysis in this paper is based on reformulation of () using lifting technique {{cite:5d6772ddeff3897fa8248008aaa93af64f82884b}}
that reduces the problem to a system of nonlinear PDEs with homogeneous boundary c... | r | aed99901a88f522ed830bb189728694c |
Protons (pions) above 200 (300) MeV kinetic energy have simple or no nuclear corrections as long as formation zone effects can be ignored. Either {{formula:5f29e7c9-cfc2-456d-949a-c73891ec57fb}} or transparency as a validation goal is equally correct.
Low energy protons (similar effects will apply to low energy neut... | d | 584022f930ccc3b06a089aca3e795f3e |
The proposed model aims at learning a representation that predicts the sequence of encoded motion {{formula:6ed1c04f-9caa-4e83-9694-2cc754ac678d}} over {{formula:548deab9-dbd3-4150-b3b0-c73be8411348}} future time steps given an input image sequence {{formula:197520b1-8409-4e25-b084-74f8ebdf6cf4}} of length
{{formula... | m | 3353331ab3ac0399669d4aaf4f6d3d54 |
Two versions of the NN anomaly detection algorithms have been proposed: {{formula:b52a0067-d2c0-494d-b37d-05e67c1e4bb1}} {{cite:ffcab871559279a71924e2449d4405ee60c75ef1}} and {{formula:2a60c9ef-fde6-4460-beb3-adc958512466}} {{cite:ec6455ff9bb58f26cf4caec9cd0e65e294518f8a}}. {{formula:f4a4dab7-7c3a-4ff0-b4c7-b78f10b4b... | m | 45dacbeadac0009241c5557397196d90 |
In order to find the underlying reasons for the prediction models' results, we utilize two gradient-based attribution methods, Integrated Gradients (IG) {{cite:2d9100fb0fa65089fdadae16e94bed04d85a9aa5}} and SmoothGrad (SG) {{cite:4049e07d11b8413b9f3fe220a09e0239f26f375e}}, to interpret the event predictions by attribut... | m | 05a765f1d30e57951e8328a48cb8a183 |
While Morcos et al.{{cite:0fca1d9dc1d82de7f2184204c0cbf804d1d0b591}} used direct correlations as pairwise interactions between residues, direct correlations (in liquid theory) are generally different from interactions. In fact, the approach of Morcos et al. may be interpreted as the mean-spherical approximation{{cite:2... | d | f094aa5176caa1ea906c8778db4df95f |
In this paper we investigate the use of the recently introduced physics-informed neural networks (PINNs). In their seminal paper {{cite:8d40fb485882e30c1fbea532b12126c69167a0f8}} Raissi and co-authors introduce the idea of utilizing modern machine learning ideas as well as the computational frameworks such as TensorFlo... | i | 7ce5b80d5ee730408741411cb564bbda |
Modern 3D camera technology allows us to capture 3D point cloud data more accessible than ever {{cite:914ea922c4a60db2c98b222dc39c306dd8b01aa5}}. Now, it is time to adapt 3D point cloud recognition models with LwF capabilities. We identify some key difficulties to address this problem. Firstly, in comparison to image d... | i | f43da1d305c785df9b37f228aa2d951f |
The dominant approaches for ED involve deep neural networks to learn effective features for the input sentences, including separate models {{cite:639f74fe8b128a0bf6ee7ff29f08e491b7dbb58e}} and joint inference models with event argument prediction {{cite:24f0b64a480e6c77f7bd46ecd19189f1e1fe56fd}}. Among those deep neura... | i | b7045a1179682af410cade6e4e509713 |
Agent: We train three agents {{formula:f64faf7b-fc6b-4002-aeaf-4ed8f96a8b0d}} , {{formula:ba74acc8-362a-4b6b-81d9-2282f35a3417}} and {{formula:8ae948e5-f770-4c40-a44d-352e7ced7520}} with reward functions {{formula:718aa22f-1f51-4a39-a638-b9e88581c838}} , {{formula:0b34c629-b052-4c23-bb40-d68f9bbb9c59}} , {{formula:3... | m | 21597d6d6ea2ea028f70240d28556b76 |
In experiments, one type of driving force that is relatively easy
to engineer has the form of harmonic function {{cite:04fc14005ef683f0da757636788ebbb8fa77ad62}}, {{cite:f3880f5520ce1a9c4cfe12a50e5433837fde9b0f}}, which can be
introduced by shaking the lattice back and forth periodically {{cite:892896f20795319def9d9fef... | m | dc2490d6206912b562631ec95d9da3be |
We proceed by induction.
By construction, for all {{formula:3221e0dc-abdb-42a3-b157-8a699798eb47}} , {{formula:703729e1-300b-4a78-9de8-a080603276fc}} and Equation REF holds when {{formula:9a09385d-04f2-4077-99c8-afc966835c73}} .
Fix {{formula:5bc5e011-6bc0-4f85-ab22-0f0fe5ac5a96}} and suppose that for all {{formul... | r | 727409e4061f56dff525ad302e981e9c |
Continuous-time dynamic graphs (CTDGs) can be viewed as a set of observations/events {{cite:6fe92d2d45a0306e9e6f4ed19e0bd0cd053889bd}}, and the network evolution information is retained. There are only a few works on CTDG. But recently, more attention has been paid to continuous-time graphs. All three representations o... | m | 2ced82b26622965cfb072d4de48de2f7 |
We used the recurrence analysis method to study the non-linear behaviour of several X-ray sources mentioned in
{{cite:422f2baa4269823c289360567224433e609f35fc}}.
Our present analysis confirmed that the
variability in these sources is significantly governed by the nonlinear dynamics of accretion process.
We confirm that... | d | f749ce97078ef2fa42553167bdfaf5f2 |
Haze removal {{cite:b02ddb9174f9534cc67bf5099d1ef2fd3410b102}} is a classical ill-posed image restoration problem, which plays an important role in intelligent transportation systems, e.g., object detection under haze conditions {{cite:d832afce42216d8164b602bceb2fec1b15a3f855}}, {{cite:f4c3691347ac5f50b4bcf6d5645ffbc82... | i | 8ec6a2888641c923459204b33590a4d9 |
Electrocardiography (ECG) reads out a spatial map of the time-varying electrical potentials of the heart acquired using electrodes placed at specific locations on the surface of the body. Interpretation of the ECG unveils structural and functional abnormalities of the heart that can aid the noninvasive diagnosis of car... | i | cf7ea471c5dda428967314f32a732073 |
In this section, we compare the visual results of our proposed MDDM
with the above mentioned demoiréing methods. The visual results
are shown in Figure REF . The red square
means zoom-in of the image such that we can compare the details of
the results. From left to right are the moiré image, results of
DnCNN {{cite:33d... | r | d9efb0ff6d488ab98bbe70bbe95dd39f |
We have shown how gapless fermions modes bound to defects or solitons in various dimensions may be detected by computing the index of the Euclidean Dirac operator in the presence of additional background fields. The method involves determining the divergence of a generalized Hall current via a 1-loop Feynman integral, ... | d | ace3b6c1e02a2cc77b2b6c58cfb23559 |
Among the most popular visual grounding tasks is referring expression comprehension (REC), which localizes an object given a referring text {{cite:8cf1160a9f1877fbc2870f128ad21bfb9dc5c1ee}}, {{cite:71b45c73988f615ca2ac6364910d5a2107523400}}, {{cite:85f536630930ea0f155030bdfd4ebe3e842f8a0b}}. This task often requires co... | i | b3edf54434af292571f0799feb05d1fe |
The Jacobian conjecture originates from the problem posed by Keller in {{cite:f0cf96ddf35e4f95dd22c7107b849d4383b00272}}. It is the 16th problem in Stephen Smale's list of mathematical problems for the twenty-first century (cf. {{cite:efaa9096e56fb5a335833ba6a4118275b6d63e43}}). Let us recall the precise statement of t... | i | 6d81971cb1db1175c266700c9423114a |
In the domain of medical image analysis, Pham et al. {{cite:e3e95e780791e5aed275f19e237e4703e59b35ae}} proposed to remap targets to random numbers close to one, finding that this method improved model performance on the CheXpert Dataset {{cite:6fe90101ed27937b46ffe2649ad670309f350fd7}} by approximately 1.4%.
Moreover, ... | d | b0b33bc8b5ba466ea0d8c17bab2ffd94 |
Now, with reasonable descriptions of low-lying meson masses at {{formula:cd24f5f6-3b9d-4941-90a5-8f3bcd50445d}} ,
we examine the low temperature thermodynamics.
Shown in Fig.REF are the entropy densities of a neutral meson gas for various {{formula:1a027a88-9ea9-4a55-bd48-211e4f7185d4}} and {{formula:e74a7a3c-f2d7-42... | r | 4fdbfc24e9862e5fb2ebe28b0acd5821 |
While none of the automated approaches evaluated comes sufficiently close to HYPE-Style for standalone use, our work still constitutes an initial foray into evaluating style-level attributes of multimodal cross-domain mapping, an area where it remains difficult to use mainstream automated evaluation metrics out of the ... | d | 696803d0c41f2e440babe9773c05615d |
2) Visual Comparison: Figure REF shows the estimated disparities and corresponding BadPix0.07 maps. Since the proposed OACC can handle occlusions in a fine-grained manner, our OACC-Net performs well on scenes with heavy and complex occlusions (e.g., the nested structures in scene boxes). Besides, our method is also ro... | m | d8de3d295cc081baf2eacd4a0073b278 |
In this chapter we address these issues from a different point of view, inspired by the landscape of string theory vacua. We consider a large number {{formula:8991753b-5bdc-46eb-9802-69025a77b045}} of sectors contributing to supersymmetry breaking. Large number of sequestered
hidden sectors have also been considered r... | i | 5b0cf55103de6bda52fdb0e782978a79 |
Image patches that have similar pattern can be spatially far from each other and thus can be collected in the whole image. This so-called nonlocal self-similarity (NSS) prior is the most outstanding priors for image restoration. The seminal work of nonlocal means (NLM) {{cite:8b5c6e4a57b2f662797d71e884443ead3867eac4}} ... | i | 2c3dd2cb91d38006835352250f5d7c98 |
CTIN was implemented in Pytorch 1.7.1 {{cite:4fd52ca000bd86bb09cbca60b13e3e767f4cf94e}} and trained using Adam optimizer {{cite:94506423cd6a2828a95223f22c0ff63ee5976641}} on NVIDIA RTX 2080Ti GPU. During training, we used an initial learning rate of 0.0005, a weight decay value of {{formula:2e02d1de-07b7-4860-abd8-3aa7... | r | 83783c2a6cc59857d2dde33507648391 |
BEiT: Since ImageNet-1k pre-trained weights are not available, we use the official BEiT code release {{cite:1cf8c6642c79d0b7f60a520968c86aae30d23096}} to train ViT-B and ViT-L ourselves for 800 epochs (the default training length used in {{cite:1cf8c6642c79d0b7f60a520968c86aae30d23096}}) on unsupervised ImageNet-1k.
| m | 8e902caa4bb8e7bbe09c98f82d4af1a4 |
and the conclusion that {{formula:2b83ec8e-0640-4771-90d3-6f54fa557a8a}} with {{formula:4f462946-3110-4714-a612-18dfc4c26937}} , see {{cite:da6b89d1de26286b0ad31854113d6fe1dd2dc366}}, we get
{{formula:60fab868-dfab-4dc4-9119-a5f6c21b5f34}}
| r | 4702833b67bcca62cc701e9ef557e625 |
In Ref. {{cite:5522382d1b6e7ac9749027ea4f7f5f62298c8863}}, the process of {{formula:32a1c720-8113-44d3-b830-ca70da863c3e}} is recommended as a discovery channel of {{formula:e4f7ea15-c24c-4249-b007-c2b2843e2155}} , which has been confirmed by the LHCb experiment in Ref. {{cite:d824d5c6cd4a46ba2eb76e2ae08ad259cf1cb35... | r | adb9c2b7c662d3d305473e115581d36b |
For the fit of the benchmark simulation, we let the sampler run 50,000 discarded burn-in steps followed by 50,000 sampling steps in 15 different chains using the Metropolis-Hastings algorithm {{cite:0697710fd7866684118c495a680aa9798c455112}}, {{cite:1c713dd3a4d609187175f6f95da757defe291cc3}}. Convergence is ensured by ... | m | 28f9ebbc24e3b525a547716a2c16831b |
The present work has several perspectives and possible extensions.
First, it would be interesting to re-derive the approximation
(REF ) in a more rigorous way and/or by a direct analysis
of the eigenvalue problem, e.g., by matched asymptotic methods. In
fact, our derivation involved three approximations, and it was
dif... | d | db9049c78752a669824fe49af119e9ab |
A variety of distributed planning and decision-making problems, including multiplayer games, search and rescue, and infrastructure monitoring, can be modeled as Multi-agent Markov Decision Processes (MMDPs). In such processes, the state transitions and rewards are determined by the joint actions of all of the agents. W... | i | 9eced68c61960b9fdb11648674e92258 |
large visual spatial contexts combined with efficient iterative patch-based training and dense inference. The output of the CNN is often interpeted as the parameter of a conditional distribution. For instance, in {{cite:e65b3902f9a5612182efe0b774f9ab4365f8a8a1}}, {{cite:29f4160fed4ee7e0d26a97c2b63384ac9445b5aa}}, the o... | i | 27e0b94ac99163fb3e6bec15ba0d793a |
The model is interpretable, and thus admits the use of
prior knowledge, e.g. if we already know some things about an
object. The formulation is also composable in that models
for individual objects can be learned separately, then combined
together at inference time.
The variational inference algorithm is obtained dir... | d | 590ca6d3f4c9e064ca734d24a13c4abe |
In this paper, for Korean-specific table question answering task, we present KO-TaBERT, a new approach to train BERT-based models that learn jointly textual and structured tabular data by converting table structures. To address this, we firstly create two datasets written in Korean language: the tabular dataset contain... | i | f62894678b83ef958728cb1d445bd3bb |
The study of products of random matrices has been proposed many decades ago by Bellman {{cite:436b30e2a565f78914af0d3a9fe48cfa642e5271}} and by Furstenberg and Kesten {{cite:dd16c23eb5b2a37ce9823b05721ae49449367a60}}. The motivation was to understand properties of the Lyapunov exponents {{cite:dadcaf727684727b016622a53... | i | 6fc85ef4d8d8d9da2aa57344d28bfec3 |
The skeletons are a good privacy-protecting source of information about human posture. However, the quality of body joints approximation depends upon the resolution of video frames and the degree of occlusion due to objects or people in the scene {{cite:42abe659391b8c752678f34f1c505ecd1d5cc32d}}. Occluding the appearan... | m | 1835b61cb89eedd8636368ecc2e3b6ab |
where {{formula:6b77027d-494d-49a9-ad74-8708d9393c25}} is the learning rate and {{formula:40be0c84-032c-4392-b3ab-e5db9ad4e106}} and {{formula:4ed0bb28-4906-4ef7-a491-cd64a693c80a}} are positive scalars denoting the portions of the speaker and age group adversarial tasks’ gradients backpropagated to update the gener... | m | 1ed3d8426a03652597ad5533ceb28dc5 |
Our above remarks are of course only speculative, and other
possibilities remain. For example, one may have different product
structures that are possible in twistor space (corresponding to
different ways of picking cohomology representatives), but such that
these correspond to different double copies in position
space... | d | d212abc97c84fa208b08b8282caaabd4 |
In {{cite:d95f9ad59c8aa958355c137694b1339325c26a8e}}, the sunspot oscillations in the chromosphere were investigated in conjunction with SJI filters 1400 Å and 2796 Å. In both the filters, the global period increases from sunspot center to the penumbra. They also found that apparent horizontal velocities decrease from ... | d | 539786f4562e30e680df1470c4df6099 |
In addition, we also validate our ResNet50 pretrained with VGGFace2 on the AU detection track. The validation is summarized in Table REF . Details of evaluation metrics can be found in {{cite:fcda7c78069cb2e53ec15131bcc6674ce3abf1c1}}.
{{table:7ed3ef1e-3581-496c-84f3-5b30d1d5d061}} | d | f51d6c17d80b4ea34d08736bbf5c6a8f |
In our model, there are five parameters, i.e., the viscous parameter {{formula:1f2e0700-900b-473d-a1cc-06dce7c22998}} , BH mass {{formula:b9b2bb00-6bb7-41fb-a4ba-04cde356a180}} , dimensionless BH spin {{formula:240da768-3000-4d38-92d9-db0088747d54}} , dimensionless accretion rate {{formula:ad32ec37-9a88-4c74-8507-ca8f0... | r | a4b7e83c377914bc14c6b3b66b79a6b7 |
By the generalized dominated convergence theorem, this will imply that {{formula:c0764e05-2d6d-41fd-af02-de10feb13cc7}} and {{formula:1e5ac705-8854-49ef-939d-d7551c02b838}}
{{cite:3ed0047e869c51ca149e271e083f076684ff7fd1}}.
Supposing this for the moment, we show how the result follows.
Since {{formula:41014e9c-7aec-4... | r | 3a96e6741f067da5ee3b3d2b9011eaac |
Agent in Data Augmentation
To efficiently render depth image, we build an agent that encapsulates Open3D {{cite:0976b935c3946ba9e38a77cb6aa6767ad543dcbe}} GL framework. Our agent contains the implementation of depth projection and depth image augmentation {{cite:6c524388cc94bca2b16bf723c86c46251403d0bf}}. To get more R... | r | 132f864d0c11d689fef4b5c28fa87c80 |
where {{formula:081670b4-edc9-435d-97f4-047c57ae87c8}} are polynomial functions or formal power series. We omit equations admitting a symmetry of order {{formula:bc8aa523-d0f2-4363-81bd-8b54cb4b70b6}} , which have been studied in detail in {{cite:27b2c914f4cc5e96de87f3a27f30d1e849e4ef29}}, {{cite:b03931bc1e50321bc5696... | r | b742f70707543cf7bd5e5613484f230c |
We close this work with the proof of the following duality result that extend the one of {{cite:534428b852494c871cdb156b64110f4bf6fec525}}.
| d | 0e2d7659bfb7eb754acc2b988f3be3f9 |
Following the formalism in the previous section, we turn to numerical analysis with specific decay modes. At the LHC, about 5% of the total {{formula:f9fcf7e0-26ca-4450-b804-620e2b9eb687}} -hadrons produced are {{formula:2ccfafd3-b2b5-4768-b601-c90a3a886207}} baryons, and both at the LHCb and CMS the muon reconstructi... | r | 7a9cfe4e7c19c3848159ffbfde5855c3 |
We suggested a model of purposeful kinesis with the diffusion coefficient directly dependent on the reproduction coefficient. This model is a straightforward formalisation of the rule: “Let well enough alone”. The well-being is measured by local and instant values of the reproduction coefficient. {{cite:579df23dfe01506... | d | 2f52b5d9fdb60293249a1decdec425ad |
Computation Cost. Compared to pure ILs, there are two extra cost sources in common meta-game analysis: approximating and solving the meta-game {{cite:b504f366d1761b9700d71586327cb1cb3681275b}}.
In our case, the meta-game is restricted to a local two-action game, where two actions, {{formula:4667feab-89bb-4d94-89eb-a3a2... | d | 2fa1af88ad91d08f64c3ca849182d219 |
Using Corollary 1, we can derive the result of lock-free parallel optimisation algorithm {{cite:dba6dcecf646b25d3eb81c0da5aafcd3da79db59}} and the asynchronous distributed optimisation algorithm {{cite:0c1e208e582718ef7177807a3bc58c421aeaa694}} as particular cases. By setting the number of threads {{formula:188817b7-56... | d | ba4fe11c4022ce477bb173d076f9a120 |
({{formula:a1d3361a-1a57-488b-86be-91c8346c269c}} ): The U-Net implementation used in this work is based on residual units as used in {{cite:d0cb522ee5af42e70dd664e4f6d132209f607379}}, instead of using the classical convolutional blocks, this is meant to to address the degradation as proposed in {{cite:6c2b17f7619a012... | m | a79aec335ec87d214e5a96b405eddd37 |
We assume that the readers are familar with the concept of vertex operator algebras (VOA), modules over VOA and the {{formula:7a93c4f4-b940-41c3-9c20-cf2c494bea03}} theory, see {{cite:d84e93e3b820012e7083eb664caf84eee3a19ce5}}, {{cite:2bcc26e0462d0d29c5eb642fbb3c21e5fdce36df}}, {{cite:0c2cf2d981e84ac15ddbaa666317c9735... | i | 0337b8ef88cff836d7ea02cde4923a5f |
always reaches the global minimum after a sufficiently long sampling time (cf. {{cite:20b265cec9b85d4b9016e88f9fcc8c3120a66999}}).
| m | 66598920c5e713b2879cd0bd351e501c |
with {{formula:2a353a47-28c6-4bf8-b0c8-e523ac147ee4}} . It follows that {{formula:04a0f891-1446-4f0d-9823-0413783da47b}} is well defined by (REF ) (see {{cite:5ab021148a81510b3064ba1794c292a879f62a1e}} and references therein). Hence, the problem (REF ) has a unique solution.
| m | 7c30905993b0a15b7c5431a46727947f |
Overall, ethical aspects of applied AI are a hot topic, and we partially cover it in previous work {{cite:a3fb24f4c986d6dc167fa9376ecbf36e08f9eda9}}.
Jobin et al. {{cite:54c6c1a201c113c7cc957581614e435df501bd6a}} found that transparency and justice/fairness were top ethical principles in guidelines for ethical AI {{cit... | d | 9405e95b4621c86b0e95106a4c155324 |
First, no single existing AST-based model can beat the simple token-based models in all tasks. This may indicate that the plain text of source code has revealed strong naturalness of programming language so that applying classic NLP models directly on source code could already bring pretty good performance on most task... | d | 3787bbe51e28641f2b171cb14cc63d4a |
In Fig. REF , we report the density of states (DOS) for {{formula:b90f49b8-391e-4df8-9219-d8d044a15e1b}} and {{formula:e1281d62-55c9-42f8-998e-9f8f2c329d58}} at different temperatures.
For all the temperatures, there is a strong renormalization of the bare band whose width becomes twice smaller (from {{formula:3d69de... | r | 159b735910b3ee763c35bff60db7182a |
Our model based on the EFTofLSS was described in Section and has 10 free parameters. The monopole and quadrupole are both calculated at redshifts {{formula:8ff40bca-216c-4f30-bd21-76f7d4988d2d}} and {{formula:ed9b296f-65c3-4a8d-9a87-f9ce5a786a38}} . For each likelihood calculation, the cosmological parameters are ass... | m | 24a0b576da7db57cc981ffdf7cb8e9e1 |
Each input image is transformed into a feature map divided into {{formula:c8bea453-420b-4e56-960f-f56c10e1b321}} patches.
The {{formula:ca330a1e-03ff-4d02-952c-023ab2a06c4b}} -th patch, with {{formula:2889cfac-5918-4f38-8dee-f23570311239}} is fed to the corresponding column {{formula:a88881d4-0e8e-4ac5-9a0c-834eba415... | m | b424764a4b55fd22f724db2c1aa713bb |
Cases {{formula:2c314fe8-f7dd-4905-8a9c-bed850af8c4d}} and {{formula:25338b0c-cc3b-4926-8473-72e609b983d1}} are treated in the same way. Let us only prove the statement when {{formula:42dc6ee0-cd4b-4dba-9c6b-365cd6d6d0d9}}
Dividing {{formula:4273a335-c2c8-4fda-81a3-a68afcdc3757}} with {{formula:b4f7583e-2907-4a93-bb... | r | 0fe0d6d55797032e60d1c1e59bfdbcd4 |
The resulting model amplitudes, including additional background terms, were fitted to the available
data for {{formula:b2116efc-c0f1-4de8-a5f5-643d1c0dc76d}} in all charge channels in the region up to the total energy {{formula:19590355-5ed9-4dd2-8fe3-5b377ba3d323}} MeV.
The asymmetries {{formula:5885abec-3481-49f9-9... | r | de9637a6ee68978fd55095ae8e9cbc68 |
In Figure REF , we display some qualitative results under 1/8 protocol on the Cityscapes val set, and all the approaches are based on DeepLabv3+ with ResNet-101 network. Benefited from the proposed framework with a series of components, our method shows more accurate segmentation results than the previous state-of-art ... | r | d9e67e4c39502c0b61410677356e942b |
paragraph4
.5em plus1ex minus.2ex-.5emVariance of interest. As each encoding is the encoder output of an augmented view from an image, the total variance in encodings mainly comes from three types: i) changes to the encoder, ii) changes across images, and iii) changes within a single image. For type i), MoCo {{cite:122... | m | 7853fff2b2ff14cc6335124fa904df36 |
Our study differs from other approaches in network inference in so far as our aim here is not to infer the existence, or otherwise, of links but rather to infer the most likely network class that led to the observed population-level data resulting from an epidemic spreading on it. As a result, the data needed for infer... | d | 3e7f9f40e8be57317167d4a38502f9e7 |
paragraph41ex plus1ex minus.2ex-1emDatasets and Baselines.
We follow the same experiment protocol as prior works. Two datasets, CIFAR-100 {{cite:3163f6944af7c32d0a36e9e8cee4b14f3d1082b0}} and ImageNet {{cite:a97394b04dffce3b7af323c46bd1f59b20e663a1}} with 100 classes selected randomly, are used for experiments. The dat... | r | 490ea44b2db558d41586646a87a5b045 |
Existing methods for multi-hop QA have two main strands.
The first is to predict the sequential relation path in a weakly supervised setting {{cite:8297c7c8f487c9c7da2b466a56ddfba7de25d9dd}}, {{cite:629f4f58c37b539515aec46bc14259c95c8b1bfb}}, that is, to learn the intermediate path only based on the final answer.
These... | i | c4af04d0737234bf1492299a6812935c |
which is the counterterm of the asymptotically AdS spaces. Having the total
finite action {{formula:a5967d5b-23b5-46da-86e4-133a811601ec}} at hand, we can use the quasilocal
definition to construct a divergence free stress-energy tensor {{cite:164f92a4d91136edcfac38335f8b1395d087d8b5}}.
Thus we write down the finite s... | m | 753ffbc729e5f65e4f327c5597bb941b |
Chignolin. For chignolin, the crystal structure was first obtained from Protein Data Bank (PDB ID: 5AWL) {{cite:b9c4fa19ee89f15299417755ec1159d8a7d7584c}}.
In order to achieve the initial unfolded conformations, one MD simulation in vacuum at 1000 K is conducted for 5 ns.
12 fully extended conformations are randomly ch... | m | b2178fda9d13844756352b2d9941be79 |
where {{formula:28ed6b5e-ba70-4875-8c06-c8ff4454d7de}} and {{formula:45210c4e-9fa0-4138-9517-9b4ccf728f15}} are given as functions of {{formula:e8ca5925-4b97-42d3-ba13-a127e3ffb0bd}} by equation (REF ). This relation between thermodynamics and entanglement in harmonic systems at their ground state has been exploited... | d | 7b0bccc4d93fe63b5cf364dd66bd4045 |
Today’s commercial speech recognition systems in both academic and industry fields require ever-increasing volumes of text-annotated speech signals for training. The need for massive data in supervised learning hinders the fast advancement of speech processing research. To tackle this issue, self-supervised learning (S... | i | 0b4ce4073906d5449da16fb5a99f3537 |
Looking-to-Listen model {{cite:6d1263852045ae94df8e3e4cf0b69c56f84d92b9}}: A speaker independent audio-visual speech separation model.
Online Visual Augmented (OVA) model {{cite:fedd0c23fad05d83dfdcacf209792ddca9396662}}: A late fusion based visual speech enhancement model, which involves the audio-based component, v... | r | 66bd662b20509b23558e1011d8708033 |
All these algorithms and indeed the general RL study have been hitherto predominantly limited to discrete-time Markov decision processes (MDPs).
It remains a largely uncharted territory to study RL in continuous time with continuous state and action spaces. The few existing papers on RL in the continuous setting are mo... | i | 08123bc022af98c14b479ca56fa94857 |
Existing methods for learning-to-defer to an expert aim to improve the performance of a prediction task e.g. {{cite:670e29118b908ee73095229f0ad55ff9bbdeb0b6}}, {{cite:93113003430fb2f4fa8972313ee059b439c7578a}}, {{cite:f79b4eb5f790040aa6aeba8fb26adaad6a5cd1ec}} by deferring to the expert. These methods defer to experts ... | i | 7fa9454563652e6e6942316acf3c9a62 |
As discussed before, our method achieves some measure of knowledge transfer to restricted discrete action spaces. However, what remains unexplored in this thread is the application of this method for transferring knowledge to expanded action spaces and action spaces that have disjoint components. For target domains tha... | d | b1fb5e4206f4cea039adec81db75d9b6 |
Empirically, we found more learnable parameters are needed with greater {{formula:c81c5cd0-78e2-428f-b469-a356ac02b0b7}} . Thus, our generator {{formula:7ada3a60-9bd5-4f95-acd0-e13741b107cc}} is a CNN illustrated in Fig. REF with 16 residual blocks and {{formula:d28d1fdd-b21c-4061-a802-05eacce95c6d}} kernels of size... | m | 52c3d268f964b09b8fa4edeb08ad6e8e |
Parametric denoising methods in the literature consider the noise in PET images to be additive Gaussian {{cite:3a0897edc670a6f654c0bf0e7f862d260f8bd42c}}. However, Gaussian assumption in PET images may result in the further loss of already poor resolution, increased blurring, and altered clinically relevant imaging mar... | i | 88074ba7e5bd985ddd3d1151ca97deec |
A more popular algorithm is {{formula:3898df38-fda8-4d8d-aa7d-0ebd5ea0e9d1}} {{cite:4ac4db40486eb9354afc4550c149ea812e02a757}}, which adds EMA-style heavy ball momentum to rmsprop.
Adam has an optional “bias correction” scheme.
With no bias correction, Adam employs the rmsprop preconditioner rule in Eq (REF ); with b... | m | 01aae7eb925c010e436360466b272507 |
Some methods, such as the wavelet approach in {{cite:b0132a5b37e0b2c848d5c22a5783816c8a605a46}}, allow for a bit more of an unsupervised approach in terms of data sampling, but the results are largely the same.
In theory the input to a LSTM model can also be trained using complete life time sequences.
Additionally, sta... | d | 0c7a8d6fea56fa8699242f9ea517c0e1 |
The fact that Newton's constant is the natural cutoff is consistent with the idea that the Bekenstein formula for black hole entropy involves a renormalized Newton constant
{{cite:8e2c71be0d9a5b5033accad0ff9cb9d8eda937b4}}, {{cite:142701f5e01af59a71a8d94118c64f7c22382c65}}, {{cite:9c1fbf753e0bc69df6c72d04ca461001fcc09a... | i | 5fc34ba6f45a1bac8f34997e752901a0 |
The results of the ablation study on the KITTI dataset are shown in Table REF . We can see that the backbone Monodepth2 model {{cite:5de2838f4ded0999b64a2a5cf5fc164e38b7fbbf}} performed the worst without any of our contributions but by changing the architecture to a Siamese encoder- Siamese decoder, the evaluation meas... | r | 83b4a18bab5a8fe55de0c3c6709f934b |
E-FT: As described above.
E-LwF {{cite:04a0050e882c01082d37b3cda517b80cb38ed678}}: It aims to guarantee the output embeddings {{formula:2df72b8d-0b90-4636-be12-13372c25c0c4}} of the models belonging to previous tasks is similar with the output embeddings {{formula:96aa87c7-bdd7-4765-845c-9c7a23853e09}} of the curre... | m | c60666dcdc87bb7db7bae1e351995614 |
Recently, {{cite:7c7f85db901c6095a14ccd3c98f39ca116a52912}} derived a slightly improved uniform stability bound that implies
{{formula:ae0b7d70-10c2-427f-bea9-7dc2ec010917}}
| r | 3781681dc36bfe436202ef8baca92503 |
Sequential decision making tasks are most commonly formulated as Markov Decision Problems {{cite:501b478ab948ab56c20cfab5d33ac3573825f917}}. An MDP models a world with state transitions that depend on the action an agent may choose. Transitions also yield rewards. Every MDP is guaranteed to have an optimal policy: a st... | i | 1bbe19eec802c636989d7f1e3f6daf22 |
The qualitative results and quantitive results on the KITTI Eigen split are shown in Table REF and Figure REF . In Table REF , it can be seen that the proposed H-Net outperforms all existing state-of-the-art self-supervised methods by a significant margin. Compared with other approaches that applied direct supervision... | r | 1da38daa94cd5cc667014b8bae9c0fce |
Readout function. The readout functions are widely designed by statistics e.g. min/max/sum/average of nodes to represent the graphs {{cite:e615dc2679b0423bdd4aa6ca4e4684b69b922cf1}}, {{cite:9de1b8fe43285fdab5fe6218ea62339c1cfe8621}}. On the basis of global pooling schemes, SortPooling {{cite:345d15115d71889166ec8debb6e... | d | 18e98c7835a6ca038077cfde52e8ec5c |
NN model compression methods include not only techniques for pruning {{cite:20e365fc5478f4f3dbf7e54a2161980d30d8227d}}, {{cite:7973f8fa1f0d88532dc3b18647ff9ec808f9778d}}, {{cite:79bbb8c4d784fe89f52e3bd276548feca547eb2e}} or quantizing parameters {{cite:5759627c97201d84258db6f15198eccd45bd77b1}} of a trained model, but ... | i | 0ab5da26369bc6f6d78f40b6678599d6 |
With this definition, a maximal coupling {{cite:51f0cc47feb118d46195957a180e00ac8b8e26eb}}, {{cite:395fae925b8ddba9b4c4114c55f88418320bb4df}} is a diagonal coupling with maximal mass on the diagonal event {{formula:e6ed217e-7b94-4872-85b9-cb9b22f45095}} . The maximal coupling also has a connection with the total variat... | m | 9f75a450d47241a6425cb97b2b2c111d |
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