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as desired, where we used {{cite:6a4147270e96baca348c27792d47d39b5a11c40c}} in the final inequality.
| r | e695911a4d97f6ee15c7a0c231cb49f0 |
The existing system design schemes in AirComp based FL are mainly focused on the separated mean square error (MSE) minimization in each communication round {{cite:5448c144faffb1e85132409833ac72d40d05e9c9}}, {{cite:0be066050d8f42d8fff04a337adf02d9ddf9583d}}, {{cite:004202a50f125d1e73d369cfa8fcc425fff1bc2c}}. Although it... | i | c48362b48ab8e1ffbf5f9477fa63f470 |
Finally, analogous fishnet diagrams also exist in 2,3 and 6 dimensions {{cite:176fc47a4344910ae8c323928554d145b053f8e3}} and one may try to derive their duals. In particular, one may consider the large twist limit of the ABJM model {{cite:d8e8b57e7780d7c23e78c577e88c95c7aa09415a}}, {{cite:19608b9a5d2f7268276b1369f05621... | d | 4f10fc74f2d3c95532f12436631faa0e |
Are the results of RINGSS reliable? This is the fundamental issue for
any turbulence monitor. Scintillation sensors are `self-calibrated'
because intensity fluctuations that they record are related to the
turbulence parameters by a well-established theory, at least in the
weak-scintillation regime. In the case of MASS,... | d | 63f6e7c298b514880a5590e71762f997 |
Lord Rosse was the first to observe
spiral arms in a galaxy; he published {{cite:96457e03c4e8bb8b80eeb56aa0949c2a81d72ce6}} a sketch of
the pattern in Messier 51, aka the Whirlpool Galaxy. However, it took
many decades before spiral nebulae were recognized as external
galaxies having sizes comparable to that of the Mil... | i | 985e172dfa8523354e8213ca139af17b |
The paper is organized as follows. In Section we derive the structure of the physical part
of the flavor singlet polarized unrenormalized off–shell OMEs to three–loop order. From their pole terms of
{{formula:1988404b-fdac-4803-93a7-dce563468e69}} one can extract the singlet anomalous dimensions. We work in the Larin... | i | a19c1815bfb3429c94f6a377c97eb505 |
Importantly, when the inner product is calculated, the resulting element {{formula:560d8f9a-260f-48c2-a191-a0d9be82cc91}} loses all spatial information. Thus, the Gram matrix is spatially invariant and does not describe local structures, but rather describes stationary textures and patterns as the correlations between... | m | 9bb7e4dddee2fd3016d79c9f875124f3 |
It is interesting that the mass of {{formula:443fa19e-c8fe-4306-bae9-165f8689c06a}} is close to the {{formula:4a021901-66aa-40b6-bff9-7a1091409622}} from a theoretical calculation
{{cite:8302d3f1cb0dd4e0486701c6663bb090efea6464}}. If the two structures seen here are {{formula:a852c2bc-9426-45da-a339-696ee026681d}} ... | d | 1bb8e66896b025416b786aaec08afd73 |
Let us briefly review previous efforts to analyze transitional elements.
Evidently, the three-dimensional prismatic elements are relatively straightforward to analyze, as they can be constructed by forming tensor products between line segments and triangles, whereas, a similar procedure is impossible for pyramids.
As a... | i | eb7220654cb138aafe20475c15896448 |
For MNIST classification task, we use both a multiple layer perceptron (MLP) and a convolutional neural network (CNN) to train two different classifiers by using the regularized form of the mutual information learning loss in (REF ), the conditional entropy learning loss in (REF ), and also its regularized forms as Tab... | r | d2e9661ab349d56d9c157e5473636a6f |
Our Rosetta loss, which simply fixes the embedding locations of a small number of data points, is both simple to implement and conceptually intuitive: by “tacking down” our Rosetta points, we effectively remove symmetries in the latent space that prevent identifiability. In this sense, our {{formula:74c2c755-c99b-47cc-... | d | 5f7b0b3ca55075d5a50f7fb3426c031e |
Misinformation spread in social networks has become a critical focus as users rely on these platforms as a primary source of news {{cite:0f68e2db657b02b4177cc63839303750acaf18b0}}. Current studies in this area have focused on rumor and misinformation detection with a primary focus on the network's role in information d... | i | 7f0205d1ebe454dbdfa6f7d087f6516f |
The construction of double-stochastic gossip matrices compatible with directed graphs is not straightforward, often requiring distributed and iterative numerical procedures such as iterative weight balancing {{cite:d87d2f78d75f2d1e24762a6cd9f6f468e7b7825d}}, which is not practical in large-scale networks. Therefore, pr... | m | 92cdbe4713cb3801e947cbe1d85a2b56 |
Similar to existing MARL architectures {{cite:683dd5c575db65e8a4e6df3045cdbf2f7b4207e4}}, {{cite:44f96364fe88738f2bc2baab6a8e32b0e3ff9bce}}, {{cite:e42ca4283c4c176d1f8ad04ad47448fd0e26550f}}, {{cite:93bdc5c7cb97c333942dfbc18444c1b8c92fa8ed}}, DISSC used an MLP feature encoder with an LSTM in the Predator Prey and SMAC ... | r | ef21379034c803879aefab3b1c3efd9f |
Compared with FNN {{cite:8fa5e304c10d9843de3581101348e6f15bf1e695}}, PNN has a product layer. If removing {{formula:40afa39d-d01e-4e7d-afe7-7b22f6bb49a6}} part of the product layer, PNN is identical to FNN. With the inner product operator, PNN is quite similar with FM {{cite:a52db24ef1aa7ae8271734b25e65426b2b950283}}:... | d | 9df1b7892c32cad5e3ec6c9f66a8c62b |
Another possible conceptual application concerns tensor network toy models of holography; since the Riemannian bit threads naturally live on a standard tensor network (see e.g. {{cite:416898a7c5379a1b8ecfc604631c0a1812804a05}}), the covariant threads, both V and U, may help in understanding how to incorporate time into... | d | 6bd5c9eab381b78e7cc45fbe36d87d7c |
In all, we explore six different method variants under our framework, as shown in Table REF , each adopting different design choices introduced in the previous subsections.
We note that the techniques used in some method variants were already presented by prior works in different contexts.
Specifically, the Joint-NoTra... | m | 682ba76aba4b938c838063f23fa3c0b5 |
Our proposed method is capable of identifying transitions between discrete brain states and infer the patterns of connectivity between brain regions that underlie those brain states by modelling time-varying dynamics in BOLD signal under different stimuli. In this section, we validate our proposed methodology by applyi... | r | 38b16fdc339d8bd4a90151152e5bc95a |
We now compare PhaseForensics to existing popular and state-of-the-art DF detection methods (Fig. REF shows an overview of our evaluation steps).
In our evaluations we consider the classic methods such as the Xception baseline {{cite:fc30bd842accfe4fbda93638686cbcce2e20a954}}; recent popular approaches such as PatchFo... | r | 4b04366e60afaa792b600879f44bc9bf |
The wireless link is a single-input single output wireless channel
operating within a metallic cavity with variable losses.
Following tradition, and as adopted in {{cite:5aab948fccdaab8345f3b38959230f793060bad5}}, {{cite:4819b122a20ddf04296381fb31d80d6a5f376d49}}, the transmitter is hereby referred to as
Alice, the rec... | m | 40026ca42a8e2aca11306269c03edd64 |
In the case of CIFAR-100, we have an opportunity to challenge HD-Glue in a harder setting. The 100 classes of CIFAR-100 are easily handled as hypervectors can perfectly recall hundreds of aggregated vectors {{cite:5b6e5b1cb690ce516ac9977daa70d33e2136afc4}}. For obtuse numbers of classes, multiple hypervectors can be us... | r | 96c6a365e3ccae8ae341d6148aecdc5e |
Given the morphology reported in {{cite:484a06d9068e8b0eaab611bbb3644d92e63d2390}}, we would expect to measure a flux that is about 1/5 of the flux they report, assuming that it smoothly follows their reported two dimensional Gaussian morphology.
With a differential flux normalization of (9.5{{formula:cb84ac6c-add9-4fe... | r | 727d4b58ca463bf2a29d2914bcd1c2c2 |
A configuration assignment based on the effective alignments depends on how
accurately these alignments can be predicted. For example, the application of the
effective alignment approach in the {{formula:10fef2df-9235-4c27-9397-454444b21229}} region of superdeformation
requires an accuracy in the prediction of {{formu... | m | a14bd87d655b65245a7e05fc75e7a76f |
It is important to remember, however, that inflationary cosmology is not the only model which can explain the current date on CMB anisotropies and on the large-scale structure of the distribution of matter. As was discussed ten years before the development of inflationary cosmology {{cite:0431436701949b67627250665c5631... | d | 952be8ad238f80b33133eb464da16a00 |
The discovery of SLF variability in massive stars has inspired and energised various theoretical studies dedicated to providing possible explanations of this new type of observational signal. Motivated by there always being a convective core for main-sequence stars, {{cite:11de5521483e01c0ab66180ddbf3c1ee4b312501}} pos... | d | caae389a9cb9ed21acb05e893c6e6825 |
{{cite:b1601e794a51a5e39b4f817df1a60210c5854eb9}} suggest that the compute optimal trade-off between parameter count and number of training tokens is linear, though the authors expressed some doubt and considered other possibilities that are near-linear as well. We establish an upper bound on the minimal information-th... | i | 5c01f330ec7cc9028fb13406f0e27ad8 |
Proof. When {{formula:0e0f8cd7-a3c4-4a13-a083-36921c4920ba}} is finite-dimensional, then this follows from
{{cite:273461f78becd8e80daed2adb7394b1fb3e37436}}.
If {{formula:70ee645e-9b15-48ab-b00e-8f09ed9d8fea}} is infinite-dimensional, then use {{cite:519837450b5aec4694e8f5ba13a58ebc993d5161}}.
{{formula:a1ecf379-f6ca... | r | 482dc0b1fc86f9ad0714f91bf6d6e6d7 |
This goal has been pursued in the literature {{cite:dc5277270607135beffabd47ef3daa8075bbff8a}}, {{cite:16ed0cb65b43591f550783d83a1720a7d7c98685}}, {{cite:d201ad7179ece791026928df95c77880c6b81130}}, {{cite:c23c4cdc73441fa77ff829aa1a0b0f439be3661e}} with deep neural networks, with predominant approaches being based on Va... | d | 1176e05a2ab2c65581c36af92a804321 |
blackThroughout the paper we assume that computing a partial derivative costs {{formula:6a0632e3-cb33-4c99-a49c-406f050505f6}} of computing the full gradient. This essentially means gradients are computed component by component. This is seen in almost all PDE-constrained inverse problems, where to compute the gradient... | d | 733356d12ab77766e88e004dbc525752 |
Another example of oversampling method is data dependant cost matrix, where a weighted misclassification cost is assigned to the misclassified classes {{cite:fe3e9253d2f602875a3e842482bfbe611d438803}}. It is not easy to determine the this cost {{cite:6ded771e8c832376f67882ee12499a54c0755999}}. The cost-sensitive loss f... | i | ec8a8159caf26b81ae07091eafaa6fe0 |
Impact across different hardware accelerators: Fig. REF shows the impact of using the proposed aging-mitigation technique for a TPU-like {{cite:3352faf051911c79e7c5e0a147e781e526e62ce7}} Neural Processing Unit (NPU) architecture that has an on-chip weight FIFO which is four tiles deep, where one tile is equivalent to ... | r | 8758126e49217126772d07411588f3d7 |
Ignorability: {{formula:50f789ab-a6d9-48ab-bccb-05892c064243}} Ignorability states that there is no unobserved confounding. Under ignorability, the distribution of the potential outcomes are identifiable from the observed data, that is, {{formula:cf88cd41-e5f0-44e6-8909-35e4a9af862d}} . Overlap assumes that the treatm... | m | 91bbf3a9da24c47aacadb6e2b6447fbe |
The method we propose here avoids both pitfalls. We synthesize controllers directly from the pre-computed frequency response, thereby avoiding
system reduction and identification. Discretization for computation is performed in frequency space on a low-dimensional object,
which avoids the loss of information.
Our tests ... | i | 9b83d884f9059d2daae4feb38db53809 |
The results of such analysis are relevant for understanding the phenomena of activation spreading and pinning in large random networks. It is well known (see, e.g., {{cite:d94de1bbaf7e9522eab95f0ff815f95e66be932c}}) that, in the large size limit, random networks are locally approximated by the trees. If the number of c... | d | 31f2f45ef5cc74aadfdff00168592e4d |
As a comparison, we directly extract the proton mass radius from the CLAS {{cite:54a01f0f545c4e67f3472485a2c6c52bd374b159}} and LEPS {{cite:0b6839c39d8cd51b7ac4e4282318f301f319bb15}} experimental data as shown in Tab. REF . One noticed that the extracted proton mass radius values showed irregular fluctuations with incr... | r | e9e22d44c40cf13aa2719f6fe15075ca |
We can interpret (REF ) in the context of two boundary conditions of AL: high-budget and low-budget. In the high-budget regime, achieving full coverage {{formula:67799086-cd8d-4053-a3a2-dbd71996f3ff}} is easy as we have many points, and the remaining challenge is to reduce {{formula:1b5609ad-2164-483e-92e6-9f5c0bd2526... | d | 4ec0e93dbce4fba30f88ae4106255806 |
A key advantage of using a reinforcement learning objective instead of a maximum likelihood
objective is the maintenance of generalizability.
tsimpoukelli2021multimodal,mokady2021clipcap fine-tune their lightweight visual-to-language adapters using paired visual-linguistic datasets such as Conceptual Captions {{cite:bd... | i | f80751ea9314b48b6039d2b306d97cc3 |
Conclusion.
This paper made theoretical and methodological steps on the study of underspecification. It complements an observational study {{cite:89bf0b5fee7e9faa2d2c63f6bd846a38376c2dc8}} with a method to diagnose and address the problem.
| d | 7aea7570e7ba2751ae2aef379bf7102d |
Datasets. The experimental evaluation is performed on STL-10 {{cite:ff052fc2c0e701185a0b9fea2828fedf57ba749a}} and CIFAR100-20 {{cite:b40843363e619891b500f1a5977f4cce25165449}} datasets. The experiments aim at investigating the impact of ScatSimCLR architecture and image augmentations on the classification performance.... | r | efbc4b4091472d7cc16e45521f2a410a |
Aside from segmentation network studies, transfer learning is widely used in medical image analysis to improve the performance {{cite:b01e512e80de200b70687ac218c4bd4cc6e92e81}}{{cite:a1fe945a0575f9351ceff087d5f6bfc6e0355bb2}}, which follows the pretraining-finetuning process. Here, the pretrained model can provide a be... | m | 449c5a0ae550cfbb84018d05d4117842 |
The results of the first experiment are presented in Table REF , where the classification accuracy between the models trained with the original NSynth training set augmented with audio effects can be compared to the baseline (unprocessed dataset). We see that the increase in accuracy only occurs for chorus, heavy disto... | r | 765ebe0d17c106123f582883251bce85 |
Visualizations of synthetic data rewards. The plots below visualize the synthetic data points {{formula:809944bc-06f5-4155-b1a3-95904d47315d}} (i.e., in 2-D embedding using UMAP {{cite:089f04fde0d4aaf55f3bae7d3310d1b88280db33}}for CC, MNIST, and CIFAR-10) as rewards to the corresponding parties {{formula:0fd1bd7c-2226... | r | 93af51089d84fb839651378d77832a76 |
We also compare to theoretical calculations from Model I and Model II that take into account the interacting photon's transverse linear polarization and the quantum interference effects.
Fig. REF shows very good agreement between the data and both models over the entire {{formula:1fff5a85-0fd9-410a-b605-d094cb922903}}... | d | eee6169e2fd586636d1ac03edf50b06a |
After the strategic idea of quark and gluon interaction with the vacuum medium became clear we delved into the uncharted waters of microscopic hadronic physics. Remember, in 1977 nobody could imagine that basic hadronic parameters for at least some hadrons could be analytically calculated, at least approximately. As a ... | r | 26bd32e510224350afdd55d3f1f2e41a |
Dark matter (DM) constitutes 84% of the matter content in the universe {{cite:09aa3fa56ab1c373a492314c0a44affea28c637b}} and plays an important role in the evolution of the early universe. It has so far eluded detection in all channels other than gravitational interactions. DM annihilation or decay could inject energy ... | i | 6460f49bde69c282150c4717b7617243 |
The tensor product is a generalization of the usual matrix product, and satisfies a very useful property:
the associative law ({{cite:88e196f3c8a32f0cdd6f8f7f26d1369e04476af5}}, Theorem 1.1).
With the general product, when {{formula:058082ed-76cb-459d-9cf1-58135a581a50}} and {{formula:5682213a-d6d1-4d16-8792-f5acf5e78... | i | fcc6b640debb1ead35e560c7d991abba |
We implement both methods, along with ERM, and use a ResNet-50 CNN {{cite:0976e0433f76c693ca99e35f88ccb1143bd059cd}} from Torchvision {{cite:76aa8b78bcbbd3f471a2117a2dfcd57a93573182}} pretrained on ImageNet as the backbone of our learning model in all experiments. Hyperparameters were chosen by tuning over a grid for l... | m | ee743073db445d72038b79c81249062e |
Then, our proposed CERT is evaluated on PandasEval and NumpyEval.
We train CERT on two base models, including PyCodeGPT and CodeGen, named PyCodeGPT-CERT and CodeGen-CERT, respectively.
For each benchmark, we extract corresponding library-oriented files to train CERT. The file numbers are about {{formula:e2ad2d88-c13a-... | r | 1e95959ba1d44d32459a25cb8224af37 |
Limitations & Looking Forward. Our experiments on learning action-conditioned world models and extrapolation of knowledge in the form of learned rules in video prediction highlight the advantages brought by the factorization of knowledge into a small set of entities and sparse sequentially applied rules. Immediate futu... | d | 1daf0ce2e26a579cc94c70cdab17c392 |
Denote by {{formula:5ae62203-ef99-4135-9596-92161dc46492}} the Strominger connection {{cite:b497eb0810db94f6c514606d4b30789e5ace9f90}} of {{formula:b7cf55f7-b84d-40ed-9eee-ce9bc6d1996f}} . It is also known as Bismut connection {{cite:1c08f8eda76efd4ffb38e9e31815f001bb5ce4bc}} in many literature. A Hermitian manifold i... | i | 22d56edc9315b98492417dab32bb36ca |
Auto-decoder.
Also known as Generative Latent Optimization (GLO) {{cite:bba870774c46e5472ddd1d4e05b8be79d9407200}}, auto-decoders are a form of generative model which generates an output conditioned on a latent code {{formula:240a53c3-9549-45f1-8730-1a68a867c0d9}} .
Here, the latent code is not predicted by an encoder,... | m | 51f834bb3fd8f6ac3844aeb38c3ed472 |
In the setting of -operads, the machinery of which is detailed in {{cite:f257aea724b7860147a1cec297ecf8e1acc7004a}}, this is true by construction. However, we are working in the setting of ordinary operads (with color implicit), there is only a model theoretic structure on it, and there is a simplicial enrichment possi... | r | 952d397a6fb2e2b0ed3463c0672cc576 |
Sums of squares have been studied for centuries, and although (REF ) does not have nice modular transformation properties like many other generating functions related to partitions, asymptotics are known. For example, see {{cite:afbe39efa42d6b799e9a04c6a6b8139c824a3638}}, {{cite:b91f9a89fd883249261734731eaa0944a20ba87f... | i | ae79e1ac3e3a3b7165e96e823b191cd6 |
Nanoscale coherent light generations via stimulated emissions have been the scientific frontier of nanophononics, topological photonics{{cite:64b2ff374f97a804f5bb6f2fe9434c57892152ec}}, {{cite:02a2e8ef0483fdac6a6af62575c1429dda522637}}, {{cite:ba6c8d6e90cd2d5217ae4b58165ce28b45e95414}}, non-Hermitian physics{{cite:017d... | i | 12321aa06d48dd2102ad2b8c8e5b51eb |
where {{formula:c76e35ae-9f13-4cb8-b511-6474be5e3351}} is the parameter vector used to fit the data from participant {{formula:85f3b8cf-37d7-4759-aa36-21dc249a4d5c}} with model {{formula:141a2eff-b8db-46a9-a072-ab062c7eeb43}} , {{formula:15ea982f-f1bf-49c8-8f27-e96a5c517d3b}} is the vector of number of clicks that t... | m | ef34a6d4b7bf7f262db84eaf3a4c969d |
Let us focus now on the entropy evolution. In Fig. REF , we show the behaviour of different dimensionless entropies with the scale factor. The entropies are normalized in different ways (see caption). We analytically calculated the Bekenstein-Hawking entropy of the fine-tuned standard {{formula:a79e1c6f-acd7-4745-a030-... | r | eeeb5a77e96ab0bb9418a87bd11fbdf0 |
Stop: The function {{formula:6a79f6dc-f98d-43bb-95b1-57f27c2c0e2b}} determines if a new co-training cycle is executed. This is controlled by the co-training hyper-parameters {{formula:8b03b524-3634-4223-a7c3-81ddffa9ea51}} . Co-training will execute a minimum of {{formula:6d542516-16ad-4335-97fd-55ef8f86a9e8}} cycles... | m | fe4c29da1eeca84512b5c46401e8f367 |
Failure cases of MOORe can be found on the random benchmarks (walker2d-random and hopper-random), which are generated by random policies {{cite:c8bf85725658d19c4dac6728bed594d1db38a2bb}}. We guess that contributes to the collapsed policy in the offline learning stage. A ruined policy can not be improved by MOORe. Fortu... | r | 1dfa65678ad6d77f35c59a1c35b313de |
The results of our networks compared with other lightweight networks are reported in Table REF . Our Dite-HRNet-18 improves PKCh@0.5 score by {{formula:067231fb-6f68-4e02-9d44-22b38c1d5fd0}} points over Lite-HRNet-18 {{cite:901abf4be4c2d5b5824c5342981cf2b987a81c89}} with the equivalent model complexity, has the same s... | r | ce2e4e0e4825d9cef17cfab67cd31af1 |
We propose a parsimonious approach for covariate adjustment in differential network analysis.
A number of improvements and extensions can be made to our current work.
First, while this paper focuses on differential network analysis in exponential family models, our framework can be applied to other models where conditi... | d | 80e655828bb3355a4f94162002577ce5 |
We refer to {{cite:f0b2b37935ce1558c159410e8e1018238c44336e}} for a comprehensive study of Kodaira types and how they may be detected via Tate's algorithm. For {{formula:1b0e2eba-0cc6-4498-9e60-95526db78364}} , we say that {{formula:e01fa7ad-f051-4d06-84e5-239766c459f8}} has Kodaira type {{formula:430290f0-076e-49b3-8... | r | 15a2e6335b7dcab9f9c2c66e76653968 |
To avoid issues due to scale differences, the ground truth parameters are normalized at training time by dividing them by their standard deviations over the training set, which are saved and multiplied with the network output at test time.
The network is trained using the ADAM optimizer {{cite:cfbfa1adebaba7d7f0631d52b... | m | cff145b3c8c8d6ac800bbcf11d0e864a |
While the Gaussian approximations recover a lot of practical use cases, their nature makes them inadequate to approximate, for example, multi-modal posteriors. Designing proposals with more modeling capacity, anf fully utilizing the additional degree of freedom offered by the different roles of {{formula:102bd2e5-e5e6-... | d | d0d308bc0fcd4a1c6ed6e994c6d735dc |
As mentioned above, our general family of MSRD codes recovers linearized Reed-Solomon codes when using a trivial code to construct the evaluation points. Even though linearized Reed-Solomon codes recover as particular cases (generalized) Reed-Solomon codes {{cite:04fd6769efa7944749f5c614c02357309ff121f7}} and Gabidulin... | i | 64401da5291251fc1e6847d1481f1f7b |
Let us now analyze the mechanisms determining the CFP on the rare-earth site and, in particular, the impact of the N and Li interstitials on them. We consider the NdFe{{formula:c4949c05-a92e-43ff-ba94-b53b27206905}} ({{formula:69514f7a-b141-4565-a154-83c3565a6931}} Ni, Li) compounds as example. The N atom nominally ca... | d | a8e4ee45e70e34e3d49ce34a7d52b301 |
For the quantum quench, our main goal was to demonstrate the advantage of the spread complexity over more geometric measures studied in {{cite:3865ec021f5f98628d8c68afa95043f6fe289da6}}. Not only was this clearly shown but we also found various universal features of the evolution, e.g. at early and late times, that are... | d | d108ae645046134ff633b3ee8b08abfa |
We would like to develop control schemes to generate effective periodic “self-deformation patterns"We consider self-deformation patterns as relative movement of body and limb elements for the general class of serially connected legged and limbless robots.
Over the past decades, many techniques (e.g., gait generation {{... | i | db3512bbab85c563000bea2b5e4d3fe6 |
In Table REF , we report the performance of PolarMask {{cite:9998b96a17ffa9a5d9e472e780ec2b13abe69483}} on our dataset. As is shown in the table, PolarMask can not solve the instance segmentation of irregular objects. That is because PolarMask can only represent a thirty-six-side mask due to its limited number of rays.... | r | d5a3d54f9e196402b1b3dec218917066 |
Our work also opens up further questions of the joint problem and the theoretical understanding of GPM. For example, the phase transition experiments indicate that the theoretical lower bound of parameters remains sub-optimal and calls for continuing improvements. We mainly credit this to the rather strong assumption o... | d | 849cd1357e15090a5494a0e650c1a48e |
One way around this issue is to use the Poincaré inequality
rather than log-Sobolev. Indeed every log-concave measure
satisfies the Poincaré inequality.
Kannan, Lovasz and Simonovits {{cite:071d366a2ddbcd3bc1647ad58cec33cfdeba24df}} proved that the
Poincaré constant of an isotropic log-concave measure
on {{formula:104b... | r | 76a79836b9355d62f7bf8f11588466e0 |
As shown in Fig. REF , the spatial distribution of particles exhibits different behaviours in the three {{formula:6f4b52c6-489f-4084-ba55-81f13f693d37}} ranges we considered. When {{formula:f939b725-325f-4ac7-aff3-d8185ea1832c}} , particles tend to be trapped in regions where high gas density occurs. This is consisten... | r | e48e0ef5039740f53332ee1fae524019 |
Besides using the loss in (REF ), we also trained our model with the MSE loss. In this case we computed the loss between the middle projection and its denoised version. We chose to compare results against the recent self-supervised approach of {{cite:25c81792e537d440e8c3cc1e110dae00dba751a4}}. We observed that the algo... | r | 4a21aec8b3ab82743ceada5b072478f1 |
BERT {{cite:72e2ac4df4ee6ece71b1e94ba64ef8ac9a2022bb}}: The BERT baseline for ERC, initialized with the pre-trained parameters of BERT-base. We concatenate historical utterances and the query utterance in order and then feed them into BERT for classification. The hyperparameters are tuned the same as DialogXL.
| m | d574ac6d67e3c3fff4d119ccc7c212da |
More specifically, the Top-10 performing methods on the KITTI dataset
are (i) four SPN-based models; DySPN {{cite:058c862bab13f450fe66bf55fd9794457ac935a4}}, PENet {{cite:392c200ca1518272b2587ac34f144867d428f68f}}, NLSPN {{cite:828d71423f14d1e9c3a742176a4f0278e689bf32}}, and CSPN++ {{cite:aa432e063f4760d957c936507c3715... | m | 2e4efa62d8ea55548f9fadb96638bf94 |
Lemma 5 (Hoeffding's inequality {{cite:f9a8a5be71cad340ce79e423cea03897f7a34373}})
Let {{formula:86a43cc1-d84a-40ef-88e3-9827c0b8d912}} be independent random variables. Assume that {{formula:683969f1-1799-42ce-96a3-3d0b4ba2d6b4}} for every {{formula:b57f75cf-6856-419d-9f66-1d78aaecf37e}} with {{formula:d961ec91-f... | r | 5d225f9fe26b10fc1d88ea015b800af4 |
Firstly, the Discrimative Correlation Filter (DCF) based trackers have shown promising tracking performance on RGB videos.
Therefore, there are a number of DCF-based RGB-D trackers.
For instance, Camplani et al. present a real-time RGB-D tracker based on the Kernelized Correlation Filters (KCF) {{cite:d1cf5a8f38dd56eab... | m | b2ccc96ee8d0a8b473093d22652a8323 |
The results are also not directly compared with those from MuZero due to discrepancies in the evaluation protocols and computing resource requirements. For example, MuZero uses a smaller frameskip for the environment time steps and uses a longer allowed episode length of 108,000 frames compared to the 18,000 frame maxi... | m | d68c392a9324b5d32dd873cf475a152d |
From the lattice QCD viewpoint, supposing a vanishing chemical potential, then the transition from confinement to non-confinement phase occurs at the temperature {{formula:b4a02321-ce91-4ce1-9c9f-f707c2261960}} MeV {{cite:f619f475251968061a285a65ee2009dbd82e68f9}}, {{cite:bebcff4de72ac300efb721e8969cf0199a1e1044}}. In... | i | abec108d0d109b3f1c67a1eb53adbd50 |
In addition to being more sensitive to QPTs than first order TTCs {{cite:2d8804a0638a4bab21e814a6af7d196429e5ffe8}}, {{cite:e28080bbc2ff03a069179c8b9d30598b3d87863c}}, {{cite:2484f5d021f2d452766e51cc1088bf45dbd0b3f7}}, OTOCs have been used to identify the `scrambling' of information across a system's degrees of freedom... | i | a3c66c0ab6b10843c3da2d7e45606a92 |
Researchers have considered deep learning as a rising subset of machine learning techniques. Rather than using pre-defined hand-crafted features, deep neural networks can learn hierarchical features thoroughly from the input images. A sketch comparison between traditional and deep learning based brain tumor segmentatio... | m | 36d6359c0083e4dada132f178c7cdf1c |
Remote distribution of secret key is an essential task of quantum cryptographic network. Quantum key distribution (QKD) {{cite:9a0c5b5a0ddb6f395b9697881e7b1f9e8b9c8f95}}, {{cite:163ef06719a3a2e20887d52191cb6637eb425c11}}, {{cite:224a2b7c3d1bd83eb903ab86e10cc9f397eb6813}}, {{cite:fa329c9c9547204750664e9fa2a079fb8a7dcb85... | i | bccde9ddfbf80705067d16e5cc571520 |
Many interesting fundamental and practical physical problems arise in open quantum systems {{cite:d767040ef623791d73a6ed7b678f3b6f382954c4}}, {{cite:083f10367fe10c47e6072cd76bf588dcfc6f3ccb}} interacting with an environment acting as a thermal bath. One of the most widely used equations to study open quantum systems is... | i | 602161fec527b2b390f94d4b03c7f527 |
Replay methods. These methods store a subset of the training task samples in a memory buffer and revisit them while learning a new task. The task samples are either reused as DNN inputs for rehearsal {{cite:b26b70d9e4e5518d2c128e3713bdb95ddfe7f3c0}}, {{cite:4c0367c91e0e10ed5ae1d385468e92ab2bee8a50}}, {{cite:3bce24790ea... | m | ac170038bf5221e6ff20a6830d19e6d0 |
The aim of studying the properties and interactions of the most elusive particles neutrinos is to infer their true nature and explore physics beyond the standard model. The past decades have witnessed
remarkable discoveries in the field of neutrino oscillation physics with the help of phenomenal experiments, substantia... | i | 0f93798b22c511bc229659c6b9ea38f3 |
Measuring the angular rotations with high sensitivity has an increasing of interest recently, for its growing potential in a wide range of optical science and applications. For example, precise measurement of rotations plays a vital role in atom interferometer gyroscopes{{cite:8fd51b8b8228440876da01d935154238d7e9bcb8}}... | i | 5eb87eaa4bdfe9e7896004db32856501 |
Nevertheless, most state-of-the-art neural networks used for speech applications still employ hand-crafted features, such as FBANK and MFCC coefficients. These engineered features are originally designed from perceptual evidence and there are no guarantees that such representations are optimal for all speech-related ta... | i | dffc0eaa6f5644c8b0b9e9b2e307a03e |
Figure REF shows a VAE trained on FashionMNIST and tested on both FashionMNIST and MNIST, and we observe the quality of reconstructed images of in-distribution and OOD data appears to be different; the model trained on FashionMNIST reconstructs what it knows (fashion images) when fed with digit images, and yet, the bi... | i | f49c1113da51c95d20f2e44c484e52a8 |
In the literature, there have been extensive datasets for vehicle trajectory collection and vehicle interaction analysis. The most commonly used is the Next Generation Simulation program (NGSIM) dataset {{cite:b3f203e633486cde6d5899cb718cc0de3a4050df}}, which is collected by processing the video from cameras installed ... | i | a2604d98cf9e7b39f8b0e5f4f8b42f6b |
Replica exchange methods where one replica is unbiased are easy to apply since
the learning procedure can be based on the reference replica.
Methods such as parallel tempering {{cite:00cb3405f3d1e55667342863aef9a54138edbe3e}}, solute tempering {{cite:1e2d6950074ae01a0c6a01af0a80b8619ac8e5ab}},
bias-exchange metadynamic... | m | 1a78b99c8acebbfb3ac67a4acca82c2a |
USL ReID. Our methods are compared to MMCL {{cite:e6d0cda28a793e693714d1f191417e7390094c3c}}, HCT {{cite:7c1e7c86ae7e45dd8587543a50746bd1e390895b}}, IICS {{cite:a35f970d6b117488f63e1c553965b7532a02a543}}, SPCL{{cite:46bee9dbc3ec9b4c1406ad98cdfabd07b415215e}} and C-Contrast {{cite:4141890ec361ef9d85e406a2a10ce6ee8ab335d... | m | 55b53906dfa8491c890f67138d29bd81 |
Although our analytical results focus on features of the surface code with pure {{formula:9fd74590-fdc5-4a5a-8bfe-950d2bcbebe1}} noise, it is interesting to put our observations of the performance of surface codes with biased noise in the context of other proposals to adapt quantum codes to biased noise {{cite:7e0b205... | d | b8eef14d937fd8151bfe5686eef208ef |
©2022. We are thankful to ChunJun (Charles) Cao, Sean Carroll, Steffen Hagstotz and Cora Uhlemann for helpful comments and discussions. OF gratefully acknowledges support by the Kavli Foundation and the International Newton Trust through a Newton-Kavli-Junior Fellowship, by Churchill College Cambridge through a postdoc... | d | 3abc1d09a744d34de933b062f3cc6fc2 |
The hot Jupiter WASP-33b is one of the most irradiated hot Jupiters known and hence is among the most favorable candidates to host a thermal inversion in its dayside atmosphere. Studies in the past have suggested that extremely irradiated hot Jupiters should host thermal inversions due to strong absorption of incident ... | d | a85b11d19ce9cb514f09fa146382fe0c |
For this experiment, we consider the ResNet-101 architecture for both object detection methods. ResNet-101 is a robust network that showed great success in other camera trap studies {{cite:c670cd8dad8c2d3de90e1ebb9f2ddfff38f90fde}}. We initialized both object detection classifiers using a pre-trained model of the Commo... | r | 2fa20cf5ab36b0f6ae9776095c5c66ce |
Part (a) results from {{cite:62665329d3a9075c9e23033444fe11eded4b165c}}. The first equivalent representation of {{formula:c6982bb8-da7a-4ee9-b271-0f856e36814d}} in (b) follows from the chain rule for the subderivative in {{cite:62665329d3a9075c9e23033444fe11eded4b165c}},
which holds under the basic constraint qualific... | r | 459e236340c0641131e7e081e34fd7ab |
Encouraged by the success of early Deep RL works such as {{cite:6753896367b2050400d6148c001d3520d1349a59}}, most succeeding works adopted variants of earlier models rooted from a similar design. For instance, convolution layers for image down-sampling and feature extraction (the visual feature extraction module) are fi... | m | 025983ea22ca756c18856fa2fb1f92f1 |
The nuScenes dataset {{cite:67d0aa78ca9cccdea178dd9c8328752efe9bdc26}} consists of dense urban environments, and is divided into 750 training scenes, 150 validation scenes, and 100 testing scenes. We compare InterTrack with existing methods on the test set, and use the validation set for ablations.
| r | 62acea0cc1a505e8683b79d031529828 |
indicating that {{formula:4ebb6e3c-8867-4572-bc87-0f4871214b4f}} should be a universal function of {{formula:7d4cdcfc-248c-49d0-b3c2-0859b7566edc}} . Excellent scaling over three orders of magnitude of {{formula:d843fb5f-2237-4bf0-b84e-82d39a8e2072}} with {{formula:5124b406-d9f5-44c9-8b35-9184369a8cb0}} and {{formul... | r | a6db73eca085b9c93391ab189b409a18 |
As for the {{formula:cf0b6e49-2e21-48ca-a946-da781bf1162d}} , {{formula:7afc7d03-b331-43a7-adb4-157fd7f844a4}} , {{formula:8a0c5c66-22b9-4260-96c9-35e738ac40c6}} and {{formula:28143427-4ddf-48fc-b542-9693dd38adfc}} channels, the three body partial decay width takes the standard form {{cite:78b6182acfada4035964cc71d44... | d | e3919de02a76253c4de202acb93c511f |
One of the most striking consequences of the discovery of the kinematic space associahedron in {{cite:7b11a839cece5b66f7e2eebdaa44b9ee4a360bca}} was a derivation of the CHY formula for bi-adjoint {{formula:fb7d4673-1f02-4005-a493-c860af938305}} theory. In {{cite:7b11a839cece5b66f7e2eebdaa44b9ee4a360bca}} it was shown ... | d | 1e6e8e2baf0fef50f0563112aa435ff2 |
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