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The temporal smoothness term introduced by Sultani et al. minimizes the difference in anomaly scores between temporally adjacent segments {{cite:ddc9447aa181d78aa6f44d218ef34b96d5b8652f}}. However, from the above results, we infer that this term has the regularization effect of ensuring that all segments in a video hav... | m | a6bfa12da3ac6392c46694b5103dba48 |
A natural next step is to study the regimes in which catastrophic forgetting is most problematic. This includes the setting where tasks do not have a nearly orthogonal relationship but also when data does not necessarily live on a low-dimensional manifold. We are also interested in understanding how the ideas of this p... | d | 29f8a8f1ec1cc82618ff18f63c865cb9 |
Sparse vs. Transformer GNNs. When we compare the performance of sparse GNNs (GatedGCN, PNA) against Transformer GNNs (SAN, GraphiT) augmented with LSPE in Table REF , the performance of the sparse GNNs is surprisingly better than the latter, despite Transformer GNNs being theoretically well-posed to counter the limitat... | r | 620c6d17d0afd66e0afb69f628ff0eea |
at time {{formula:8ec68f80-4a01-429f-bf4a-f456f6f2eb47}}
(e.g., in the general setting without decision-dependence this follows from {{cite:af37f22c443565af257874526c64ee7c11dda75a}}).
The reason for projecting onto the set {{formula:fcc5b081-5f10-440a-b279-66f750aa23a1}} is to ensure that in the next iteration, the ... | m | e5a679b6401f28416d791a0da72eac45 |
Our approach towards Theorem REF relies on an argument introduced in {{cite:59116ee8a4407ad107e21841564510e1d2aa0c38}}. By double-counting the number of solutions to a tautological equation, we derive an inequality involving second and fourth moments of certain representation functions. In {{cite:59116ee8a4407ad107e21... | i | 8eb6cc5bd2a0e20f06f13408c882ed5f |
Our earlier studies found that the anisotropy of polarized synchrotron intensity could be used to estimate the direction of projected magnetic field roughly. This is still a complementary method to synchrotron gradient techniques that can trace projected magnetic field directions more accurately. The advantage of struc... | d | d656848e8d3c9f5efec8d246c9c0065f |
When (REF ) varies regularly with an index different from {{formula:c29a8898-de9e-4889-9e1b-bf8754bff2b2}} , the questions we address here have already been answered, see, e.g. {{cite:9f7ffe3b2c293039361bb06ca75099dc790d3b92}}, {{cite:d53122e3ae43b35a5fb819c7d7b41865f329e8c0}}, {{cite:fa79aeaa3477480d133a2dfbca6a5db0b8... | r | 41e2fc39ad336d6c86f709b59ee70f35 |
In a core collapse supernova, neutrinos are trapped in the neutrino
sphere and slowly diffuse out. These neutrinos have self-interactions
that lead what is known as collective neutrino
oscillations{{cite:ee4c67c08f2b19095a7a6216fec5cae034dcce5a}}.
These phenomena can also occur in the hot plasma of the Early
Universe{{... | d | e65a2c563d401fdc39109c29d827a2d6 |
Lastly, the data illustrations have utilized a pre-specified set of regions for functional connectivity analysis {{cite:b79e32b6397c5ee059e508c0c350c62218044546}}. This approach relies on a predefined brain parcellation, commonly in form of an atlas, to determine regions of interest. As a result, different subjects are... | d | 7fbc8e338e625d81b3bc26e70af57b20 |
It is apparent that the outcomes of Data Analytics [DA] and Machine Learning [ML] are often perpetuating the human bias present in the datasets and therefore enacting illegal discrimination. Constraining the DA/ML outcomes to be fair is problematic as there is no universally accepted definition of fairness while at the... | d | 4fad7f1eb98825223f790e4aa7cc46b3 |
For QA, the computational advantage of incoherent tunneling over certain classical methods (typically SA{{cite:385f86d1f0185223ff6d1ed349f84c100f4fbc3f}} and the Hamze–de Freitas–Selby algorithm{{cite:358c84222e2fc58e083e0fc9fc150208fadf03cf}}, {{cite:991d41ad6f7432a929c0f665d58ae9a682193e65}}) for certain classes of p... | d | ffc11ee5bc0465f45022bcc1f001ff69 |
For readability purposes, we refer to convolutional layers with x feature maps as CONVx layers, and
max pooling layers as POOL. The convolutional model has the following architecture:
a CONV128 layer, a {{formula:0da527a2-d84a-4d97-a362-7bc69514c620}} POOL layer (max pooling only on the time dimension), again a CONV1... | r | 080d473a53efd15e58e4580a4a9e0c37 |
where {{formula:6c0d62e7-88d1-48a2-8443-d086a4a666af}} is an undetermined function, and {{formula:05572547-7378-4946-acf0-4260d4607931}} and {{formula:4ad7f457-6678-411c-ac40-6dda91057b8e}} are the critical exponents. The constant {{formula:eec21394-b7de-44bb-985c-f00b35b86ca2}} , which vanishes in the standard powe... | r | 5c483cc7259e51b67156a7809eb3ba89 |
To address this, recent works have explored the joint optimization of machine learning models and explanation methods to improve the reliability of explanations {{cite:ee9a21595e0401edbef5ef6414278793c6b6c7c7}}, {{cite:4ece91239e8b9d19576275302c4022de66b3079c}}. Zhou et al. {{cite:4ece91239e8b9d19576275302c4022de66b307... | i | c8289dcb57ed9b04a0cbd602c197501b |
Transformers:
We fine-tuned a BERT {{cite:e9040feaad74659eb9ea0624ab193f2cbb367bfd}} and SBERT {{cite:25c59f05008465e4bb74ea8bed9c48d72950acdc}} based encoder with a dense output layer.
We used a pretrained BERT-Base model from the huggingface https://huggingface.co/transformers/ library.
For SBERT, we used an all-mpne... | m | 571b478fe3ab54ebdc6d96c3436e91a1 |
There are a few points about this framework that need to be further clarified. In general, turbulent flows have universal behavior in their smallest scales {{cite:aab708205ef0dafe7695321917049fc5274ada3a}}, {{cite:41fc124d107875b61580e0ea158bdc6fdd7a6131}} and vary in large scales due to forcing and geometry. This migh... | d | 84bd13215f41081f4c55f8e06ad8261c |
When the data is independent and identically distributed, the learning results of FL and CL are similar. For instance, the work {{cite:0d8e075a9e84cee36fbbd6832d46e1e9a220443b}}, {{cite:425ac8f336c4a0ce83604ac5bd85ec095c839c45}}, {{cite:7fb7fb9d0b97b7e224f2a321106f0de052e74c81}}, {{cite:18573778f79dab575426c7ee7f1352f... | d | c9313b3c7fca5247cd8b8db72e7bfb4d |
The paper {{cite:d83d81fdfdf52fa15a353fe2042aa10bbbf908e0}} constructs metastable states where the graph is close to {{formula:1a7877f7-1e35-457d-9c0a-86ebada781e5}} for some {{formula:1b0a5f9c-62c1-435e-a111-30d5322a06d2}} which is a local maximizer of {{formula:6c4e9f47-20ca-4198-8c22-04ae053cd939}} , from which an... | r | 6fc15cb1d8ae039ca825a088d11ed13d |
Our method is superior to state-of-the-art unsupervised approaches and gives comparable results to supervised techniques for image manipulation and image-to-image translation. We showed that incorporating the proposed auxiliary module as part of the training encourages better disentanglement of the structure from the ... | d | c7cd40d3b4b7f793e0dd9ecabead3206 |
Our method falls within the category of federated learning algorithms. This means it can be implemented for situations when data mining is to be performed over remote devices or siloed data centers {{cite:9290c4fc8aebb412d2893d9da5046d7f4ce10b56}}, where aggregating the data tables is prohibitively expensive in terms o... | d | 38041c14daec58dda99b6f68b4084dc2 |
Concerning the number of CG iteration we want to point out several observations. First, we generally observed for various parameters that the number of CG iterations increases as we emphasize the singularity, i.e., as {{formula:5e20800f-31fa-40c4-b71e-2b5ce8f6bfab}} . This coincides with Theorem 6.3 in {{cite:b38fa8330... | d | 9e2cdef9342bad47fcd5df8c82b62d04 |
We end this section by comparing our results with existing works on private value-iteration RL, i.e., {{cite:b8d635d9fba7037b732bd955db309f3a2160662c}} on LDP and {{cite:468b5d33cc9b8da89e7b44d1c1f87462fab170c7}} on JDP.
| d | d499a639064718501dfdff51c755e53d |
Our goal is to localize objects that make characteristic sounds in videos, without using any manual annotation.
Similar to prior work {{cite:b383b83055cba5b25842c82276737c387c1ecff5}}, we use a two-stream network to extract visual and audio representations from unlabelled video.
For localization, we compute the cosine ... | m | ca2c9ce25d69d825daacafb0cdda0d82 |
In this paper we studied hyperbolic codes for two-dimensional topological states, where {{formula:5b6afd52-bf88-4dda-ae22-9af6ad717825}} .
However better codes exist, such as the hypergraph product codes {{cite:a34683a58f9a428b54f49f8fb734d349540f5b38}}, {{cite:e41a20c7e691e1fbdbc98fd8fb41b9d772ef1d27}}
or homological ... | d | 525cac6285706d36ae94875d4fc8183f |
A plethora of clustering methods {{cite:35814b38afc51f00a2996812bb0282128c74d687}}, {{cite:e329109ad0426bdf15db40ade0c3bf8dfa4db891}}, {{cite:80596db47ab32d5f2b11d35fd3597c489851dcc3}}, {{cite:4909e666aadfcecfef56532ee54cf6c977c492aa}}, {{cite:43af7e46dd029ae71a315b383bfe931a60fafce0}}, {{cite:fcee46698d51ca4a85e518811... | i | bc72b87a768e57dedb3520104e5984f9 |
We first introduce some preliminary concepts which are needed in the
exposition. To that end, we follow {{cite:2de2df9dce6f97231faf89c1a591ceee6ef5c3c7}} and {{cite:4673f24d19529360ffae22f4b7d1ed30c3d35727}}, see also {{cite:e26ad356d507a33e453a14a3208f406d0e311fa9}} and {{cite:77bc8d3862a9a678aabd0843d10d158f54ebccf5}... | m | 68987c821efe752562af813a4bbc8441 |
Probabilistic programming languages enrich classical imperative or functional languages with native primitives to draw samples from random distributions, such as Bernoulli, Uniform, and Normal distributions.
The resulting probabilistic programs (PPs) {{cite:6068090e9890eeb04a91b9fb14e5a868902e8f92}}, {{cite:792dec34661... | i | 46f2deb2641b2ee2d0e6e30f82b6715a |
At {{formula:858d3295-b66a-4431-84ce-ec15fbea5ae0}} , rest-frame 1500 Å falls in
the optical to near-IR spectral range in the observer frame, and is
accessible with ground-based as well as space-based
instruments. Again, luminosity functions which extend several
magnitudes fainter than {{formula:a9e233e4-f37e-4d6e-bcb2... | i | 19001fd0ff5afc87b3c6a74a9a22fa30 |
The persistence of TBM characteristics can form the basis for a strategy to extend TBM features long after the topological system that supports it is gone: namely, by quenching to a large gap wherein postquench eigenstates are energetically inaccessible. Since the persistent TBM PD arises from the fast postquench Larmo... | r | 194c5a6a134cce8ca2423c50b7c95815 |
In the previous sections the variation of material parameters was used to model structural details like areas of lower densities or void regions with (close to) zero density. This approach is conceptually similar to immersed boundary methods (IBM), where a known structure is embedded in a larger, simply shaped 'fictiti... | m | 5170f3695e4d2ceba3cc007b6b919cfc |
Decoding strategies are crucial and directly impact output quality. In general, Beam Search {{cite:c6eff3c125e455d3cf3175ae3bd4dac0cac3d926}} is the most common algorithm, in addition to some other sampling techniques such as Nucleus sampling (Top-p) {{cite:a3f01ca4695761770f9bcd384fc5105841d6558e}}. In Beam Search, th... | m | 2254dbc726a00ad31d76ac2ffd41d408 |
We tested the accuracy of the QGCN on the datasets above, as measured by the test accuracy and compared it to several baselines that can be divided into four groups:
Graph Kernel Methods. Shortest-Path Kernel (SP) {{cite:05a9b41f5715a4b1427bfe886062234e72a42217}}, Weisfeiler-Lehman Kernel (WL) {{cite:1e515eb5444bdf12... | r | 7917b725db335b3f80c05be9c763a113 |
The following two theorems were conjectured by Fomin-Zelevinsky {{cite:71d4e5d51815b8f7ff6e5430d3ab14a80026ae81}}, {{cite:7aa8f4ccc2b0aeda1cece9261c9b868c44f9ccbe}}
and proved by Gross-Hacking-Keel-Kontsevich by the scattering diagram method.
| r | c9c0c11a0b8e5a49b49fe04846b57fd0 |
In this section, we present our salient objects detection model's
results. In order to obtain the LTP{{formula:3021c72c-d425-40ce-9ec3-1376434013b2}} pixel's code (LTP code
for simplification), we used an adaptive threshold. Let a pixel at
position {{formula:4aefc223-ce05-4d2c-9b24-22b28c447c85}} with value {{formula... | r | f91133e4e7047b519e028b93a36c888d |
Beyond the four challenging image semantic segmentation benchmarks above, we also test MCIBI++ on other benchmarks, including PASCAL-Context {{cite:4bf185bc431fbeb0850b91d359eaf7ee926b78a9}} and PASCAL VOC 2012 {{cite:9ddedc4be75a1f940e5db52e351293391d0d829e}}, {{cite:dde7e964ed50c51d6e16b2b6e854b93e1bdf81f4}}.
| r | 6143778ad59a668438e875a78621dc47 |
Data augmentation mechanisms are often used as regularization methods for
deep learning classifiers. The study of data augmentation mechanisms in
ensembles of simple classifiers have achieved state-of-the-art performance not
only 10 years ago {{cite:fa494fcb45281f0a4bff30e05db8ab8ce25d79a4}}, {{cite:c8a19fd7b347ae37187... | d | 3ca5f0cb76f870d037423f439eb47b4c |
System Architecture. We build upon the recently proposed dense indirect VO method of Min et al.
{{cite:0fe2793349462f0f9d2b646bb17a71583be2c7e0}}, which addressed the joint probabilistic estimation of camera motion, 3D structure and track reliability from a set of input dense OF estimates. As standard practice in SLAM ... | m | 8267b4e77015bdcaee6b23f851dd1210 |
To solve the inverse problem involving the two data sets just described, we use a sequential data assimilation method {{cite:755052552fdb97deded180881633416042419ee6}} based on the ensemble Kalman inversion {{cite:37de100774cc27aa8955da1f8050a3a2389a7662}}, a methodology pioneered in the oil reservoir community {{cite:... | m | 8d9e5e312aba7b78ac5f353f4dabac81 |
We first analyze the role of two key parameters {{formula:7c0bb557-0124-49c1-8722-e194e8602cd3}} and
{{formula:fc67a761-3054-4336-83f1-52f153463c83}} in determining the strength of the effective field
{{formula:d8f6fb73-58dc-4455-b6b5-a54bd09994c4}} and the torque efficiency of the system. Figs.
REF and REF show t... | r | 0041a1083fa093124af734a5fbc07d6f |
High-quality embedding of words can help boost the performance of many machine learning models in NLP tasks.
Recent work about word embedding can be categorized into two genres, i.e., neural network based methods {{cite:f162bd7b53fe723cd03f7290e9296757ca597671}}, {{cite:54d210e36d8d01d551da2da6514c395fb4ebd343}}, {{cit... | i | cd39a6e5f53aa1924fbb5a843cd39107 |
Our method is compared with several baseline methods, including IQL, VDN {{cite:7b44534cabff9626e2f3da659c317f1ff4456d5b}}, QMIX {{cite:a18699a276848c71662c8fd485d4c185d6bcc10c}}, QTRAN {{cite:a3c3359fa2d0440550620188eea4620c361703c9}}, QPLEX {{cite:f61ff830136be4d821ae751171d2c6adadd67af1}}, CWQMIX and OWQMIX {{cite:... | m | 3530707d7c971b9e77801bec4cc5cb2a |
This section introduces the proposed AA-TransUNet model which uses the TransUNet {{cite:05a7f97adbd6e39e990449b6eebe97a7601c3954}} as the core model and extends it to reduce its parameters and improve its forecasting performance. We then investigate the application of the proposed model in precipitation nowcasting task... | m | 69b6240e7ef0bec12a9e15cd532b7de6 |
Studies of word embeddings range from word similarity {{cite:ecc97b6584eafa24e1c6533b4e24c01689fb5b47}}, {{cite:0c2278065d00dab8097fa169c28c7f4fb148b43f}}, over the ability to capture derivational relations {{cite:bc5f27a2436adb1dcbfa2827af4fddbbd92267e0}}, linear superposition of multiple senses {{cite:92ece05a82bcf40... | i | d5459787c095b7e2c4891a302b731852 |
To verify GraspPF quantitatively, a comparison experiment is conducted with baseline algorithms to predict grasp. We adopt GraspNet{{cite:a35ceba54d8ce409fa3c2d631c9bb1f43f714e12}}, Contact-GraspNet (abbreviated to Con-GraspNet){{cite:4272079fce2a369061ccc2db52b025f7e42890be}}, and GG-CNN{{cite:865d1629265253f371416d41... | r | b8ee156262aa5ee13b004db604131398 |
PINN challenges. The training of PINN, however, is far from simple, especially for nonlinear systems of equations. To construct the multi-layer perceptron, non-linearities should be applied to each element of the output of the linear transformation. This is unlike the finite element method, which is a more entrenched f... | i | f78fbd64b834990f81c2be3464a1f517 |
Previous works on quantum cosmology have shown that the aforementioned phantom rip-like doomsdays, namely the BR, the LR and the LSBR, can be avoided due to quantum effects rising up as the universe approaches the classical singularity {{cite:17560477a2dea9e68161ab259f0762e042d3e3de}}, {{cite:33798dc3d708c8a1545aa83e2d... | i | 2cbb0337ad0251f0cde6fa3d8ab590bc |
Due to the good structure {{cite:4f3d79a808cea3ba010216c48437f1a899467877}}, {{cite:bf794b235d4e646151a410d53e7318db70a67e65}}, {{cite:c8ff8dfbe248fccd6dff4a7db66bf85dd18efe48}} and the excellent learning method {{cite:53025733b07b20dcd0a03d342d9179688f5c2e9b}}, {{cite:6dee091926af4c7d4b65ed34e437f330f396e93f}}, ... | i | 95dc971435c367ccd6e15b4e6cd51585 |
A third possible field of future work involves the knowledge and
competence of the researchers themselves.
Researchers in the field of
software engineering should follow best practices
with respect to research methods.
Guidelines, e.g. the books by
Kitchenham et al. {{cite:24ea147743279b4f53a15c01e980f0c07620af9f}},
Ru... | d | 4d08c22a94c3fb615c2d11ae3fc5abe3 |
Classical black hole solutions of general relativity contain spacetime singularities {{cite:bdab1c0b1ffd0795bb9f713c427b56593608c6a6}},
which are expected to be removed in the quantum theory of the gravitational collapse of
a compact source (see, e.g., Refs. {{cite:28f0dbd7d6de633977a9fda755c38fb753f2fee8}}).
Moreover,... | i | 3805b3405cbd8c871fab0d50d64c440f |
As empirical findings suggest that the image feature is more vulnerable, we first employ an existing image-based defense method that removes high-frequency component through JPEG compression {{cite:dae105c46c5cce0f1fff4b044303561fb23f7609}}.
In addition, we conduct adversarial training against the attacker.
Since gener... | m | 76853df45fb0add78c1b0a1089ebd335 |
RL. The RL group uses PPO ({{cite:6f7ce4ee91c5ef7ebbdce7b4b1dde570bfd0cb64}}) with GAE ({{cite:41d5e067712c7506b35b94505bc7609db6887b02}}), and use collision as its feedback. Every iteration contains 10,000 frames of data and 20 epochs of training. The test is performed after each training epoch. We ran the training pr... | m | e83b1c8d08d80fb4dbfc810a15f3c35e |
and hence {{formula:1157aee4-04a2-483b-b8c5-cbb1f68a1d01}} -a.s. that {{formula:7501a5c3-ce52-4abb-9866-6ffc7b84cf2a}} by (REF ) and {{cite:761d93f7958b8052c094c09459e845ec07590602}}, thus giving
{{formula:3b3b08fd-4ad8-4b7b-a1d3-1803b2dd0473}}
| r | 1545a3aed894f3345b07c67ce45dcd08 |
In this paper, we consider the general class of single-field inflation models in which an Einstein frame can be defined. We outline the essential qualitative features of these scenarios and propose a novel, analytically solvable model capable of capturing these features. Our analytic method uses the Wands duality {{cit... | i | c6476b6740e104d90ca313d3c9196303 |
In 1847, Stokes {{cite:3749a73c3b2b0af1dad5ee7d4bee61ff7489d3c7}} derived a formal asymptotic expansion for the small-amplitude, periodic traveling wave solutions of the full water wave equations in infinite depth, see Figure REF for a schematic. Seventy-five years later, Nekrasov {{cite:b1ee718f3c2db47c14dbb6c90e8350... | i | 24fd52ebdc33695ef49a7e305874d56d |
Theorem 4 ({{cite:cea2cfd3408d989f9158cfc4dc5951a7f16c3f0e}}, {{cite:3e9f55f2758ff64a039bb744e5acee2869024899}}, {{cite:8a84e45d4cfbb3275c43d29b83ffcdf0be261c4f}})
{{formula:3f99e227-337a-43a9-8a7c-f07dd3bbfe83}} ,
{{formula:2a4fd9a8-381c-4388-b050-ad730bcc3a5c}} ,
{{formula:cdfa668b-71b4-4cb7-85f9-63cd7eb2e2a8}} ,
{{... | r | ad70374a5da590eaf7ec54104a89a60c |
We first compare our PlaneMVS with a SOTA single-view plane reconstruction method PlaneRCNN {{cite:71d1f2f1168934792541547f2a612b28846995ac}}, which also serves as the baseline of our model. We test it on our re-implemented version with plane semantic predictions with the same training and testing data as ours. Tab. RE... | m | 7bcdf193f4bee2f169a863fe57d37397 |
During cross-validation, the training set was split into five folds at every iteration, where one fold was kept as a validation set to test the performance with the trained parameters.
For the classification of Musky OC, we applied an oversampling method to the training data, excluding the validation set, to reduce the... | m | 5b226dd157c0589bc4ced7da3486c9fb |
where {{formula:edff551c-6af5-426e-9b76-b5da6d474500}} is a 2-dimensional copula, see for instance {{cite:f6c81d5a43f68aafddc80d0551f4252069236c93}}.
To measure assortativity of a graph, {{cite:005eedb10b344d680f32bc2e1678110caa6985d6}} introduced
the assortativity coefficient of {{formula:09011665-1b70-435a-a326-5be2... | d | 4466676b37669b60eca8814f697114de |
The presence of a coupling in the dark sector may not be ruled out a priori {{cite:9e6b446eb83021a89fa73cd5699ae09c08b5a7f7}}, {{cite:62b205364a4d00477f01a45ce234e296441ab642}}, {{cite:53eb5ceef1d8a3616d8c8490de9b436fc1afd9e1}}, {{cite:2f219977c1a30ea779ca0dd27d3cebaa858eecc7}}, {{cite:a0ade98cb168f3290312e1310343e8525... | i | 2c2b55ee1c7d26b0375bc126a2fbaf24 |
This work could also shed light on the double copy theory {{cite:1803817dffe1f53da7cd8b060c7e9104b1593de9}}, {{cite:584a9c3bc308e64e5ebf1d80294be5dd05543d1c}}, {{cite:079a096804cdddf91d76469371dfa48ec447c905}}, {{cite:4242e9042eea22e440846eef14430f423df63a03}}, which is based on the proposal “gravity = gauge {{formula:... | d | 84e1d58dd2ce8c6311e0b03f4fbcb169 |
WKB method. The Schrödinger-like wave equation (REF ) with the effective potential (REF ) containing the lapse function f(r) related to the regular black holes is not solvable analytically. Many numerical methods are developed to compute QNMs of various black hole spacetimes in the literature.
One of these standard met... | m | a7842893233f50bbf05e4e603530d893 |
One promising direction for improving our proposed methods is to improve the narrative coherence evaluator.
For more accurate coherence evaluation, the coherence evaluator needs to have world knowledge and common sense reasoning skills.
Imagine the story of Cinderella.
To be able to identify that the absence of event T... | d | eed7fe95b3cd8eaf1bb932b4d27b9102 |
For the ease of use, we define MNACR, EF-0ACR, and EF-3ACR which are MobileNetV2 {{cite:573ebf801473cd24ba9887a2d05ee1bf6333413c}}, EfficientNet-B0 {{cite:8f0c0362f11c32e3add7cb2b4d47ffefda44e671}}, and EfficientNet-B3 {{cite:8f0c0362f11c32e3add7cb2b4d47ffefda44e671}} being trained using our ACR Loss versus the corresp... | r | fdc123d1c1442c643a01e76c3920930d |
(i). Task masking. This approach masks a subset of neurons at each layer for a task (identified by task-id). Since the mask can indicate what neurons have been used by previous tasks, in learning the new task, the system can freeze the used neurons to prevent CF of the previously learned knowledge. The most popular sys... | m | 492cb0dfce14d2f10aab9d99f1f7964e |
Our construction differs from the T-dual field redefinition of the NS-NS bosonic closed string action {{cite:df3ba2fd441596ca0b82a59f51ff2b9bd93f5f75}}, its Lie algebroid description {{cite:32ae7ce7d24aa3b5c2405081fa6e95d61f01b6a2}}, {{cite:cb3715fef4822528cd558c57a4d11aed73c2b272}} and their respective generalized Ric... | d | 9a94a85af2b9a66b30622a59d03cf5e0 |
This question has been the subject of a substantial body of literature. One line of works considered the case where gradient methods converge to minimal norm solutions on kernel regression {{cite:613c4f3a45fee75787d44ae13dd43cddb01121a7}}, {{cite:e0c249f1f5201ceacc81041767fc240bb8c0425c}}, {{cite:a09504b9b9a9da1ea7a06b... | i | 787fb88563b35ed16ae1b70f35462d7d |
More information about neutrino-nuclear CCQE interaction can be obtained from
the analysis of the charged-current QE event
distributions and {{formula:7bca6525-ac83-4057-8d4a-b4c1506cf718}} differential cross sections as functions of
{{formula:bad876e6-4ca1-40a2-820a-82d08ddba7f2}} (squared four-momentum transfer) {{... | i | 65cbebd74fbc72201b4d21a442528a8c |
So what is the reason for the sign problem in Eq. (REF )?
The answer lies in the linear constitutive relations (REF )
defined in the lab frame. This is valid for a static medium and not
for a moving medium. The linear constitutive relations should be defined
in the medium's comoving frame as the relations for three-vec... | d | dd332f1ca37353c859ecdb04bd22f1d0 |
The Cityscapes dataset {{cite:f5fbbb7ee51b843466cf5af899bcfe4a7ca41cc9}} has 19 classes. Its fine set contains high quality pixel-level annotations of 5,000 images, where there are 2,975, 500 and 1,525 images in the Training, Validation, and Test sets, respectively.
Like other works {{cite:48a104863bf5183d64d2deb2c7571... | r | 517b62540b50406c3330c9f897dc42f6 |
Thanks to their low cost and high mobility,
uncrewed aerial vehicles (UAVs) may soon take over important tasks including search and rescue, delivery, and remote sensing.
In the next decade,
UAV taxis may also redefine how we commute and, in turn, where we live and work.
For these and other applications,
UAVs will trans... | i | fa45dae8c5c695e33011910074847fb6 |
It should be noted that reachable accuracy using the transfer learning method with two base models and two classifiers is reasonable, while the high-tech deep learning methods using complicated structures are able to reach an accuracy of more than 99.79% {{cite:39595794f924b73e586bc44041af2a793193cbf7}}, {{cite:fdb58c6... | r | 0e2f24d5feaa50d44d002c8630a28bf2 |
Fixing {{formula:c60f9a4d-c998-4f2c-bc48-6f3b5202140e}} and following the standard notations of {{cite:fe72d360ddb3a45c92e6571209342b60606eef9b}}, {{cite:1dd28207ae33a306bc747b3515ca7cb03b76571a}}, the {{formula:5f273a22-e295-49ca-8714-4533b054e1e0}} -shifted factorial for a finite positive integer {{formula:901ed085-... | r | a87a2235cb4709f52cf14194c826eb0a |
From the beginning to the present, two-stage approaches
{{cite:1a7e551c54e8be0407ec02f6719bd0789ce37c8e}}, {{cite:f8adcb0afcaf995c04be6d2673a966b250ec3083}}, {{cite:ce782536345e6bfa42cd3e6f42b7b7aa6cfa8b7d}}, {{cite:203d20bdee9f3e186ae3c5dc1cf7c1241a428216}}, {{cite:7d9580fb3917e95a03fa419a722576882309ae3f}}, {{cite:40... | i | 6c5da8f173430024915a0514827c89c2 |
The first rigorous study on data compression was published by Claude Shannon in 1948 {{cite:7d5658f44e088c2d910a77086a76de8c13504570}}, in a seminal paper that constituted a firm setting in the foundations of classical information theory. In that work it was considered a {{formula:1a1eb495-9d09-46ca-8f0f-b209c7c2cde0}}... | i | 1d06c5ac71a5720b237b3bea8b113893 |
From the Tensorflow dataset, 10 keywords: "Yes", "No", "Stop", "Seven", "Zero", "Nine", "Five", "One", "Go" and "Two", have been chosen to explore the functionality of the pipeline using some basic command words. Considering other works comparing NN based pipelines, 10 keywords is the maximum used {{cite:e6867fb4eb34e4... | r | 3695c0367db27101c2277d44dafad8ce |
As we have discussed earlier, in the analysis we have performed
we kept {{formula:4a148f61-4bb5-4163-89cf-bd26a9d740e2}} and {{formula:afd41458-0fd5-40f7-9da3-669926dd2f37}} fixed to certain values.
We have obtained results for {{formula:dcfa49bd-746c-4a52-a65c-61a0e2f50d7e}}
and eleven values of {{formula:a8e23132-... | r | e15a7c2450ad18652ac2b9eaa0672bee |
The other class of the noise based methods introduces adversarial noise as well as adversarial training to improve the model robustness {{cite:79b068652c7b9d0d3b386dc942ba69e200b4f8dc}}, {{cite:a9d170a79896474940380d8471a199efc832cc63}}, {{cite:540def64d311bfdadd03b0e416e87c355fab5279}}, {{cite:7540ddfde83fe59ef14cbb4e... | m | b92ce2085638d6397d3422f65750e0a9 |
Shared bipartite quantum systems, and in particular shared entangled states, are among the most basic resources in quantum information theory. Several developments have demonstrated the usefulness of entangled states in completing tasks that are constrained by the causal structure of spacetime. Two cases of interest ar... | i | 3d3d919640c0e91d37ebd3cb9436c9fc |
BC with policy improvement. This algorithm utilizes the entire dataset to estimate the Q-value of the behavior policy, {{formula:8ea0ff1c-9615-4d66-9d54-5b23eeb2d0db}} , and performs one step of policy improvement using the estimated Q-function, typically via an advantage-weighted update: {{formula:06b75d82-abcd-4d23-8... | m | 9c606cb4b5f0b8f3b209e827edc6cec3 |
The PDFs resulting from SM NLO fit are presented in Fig. REF demonstrating the contributions of the fit, model, and parameterisation uncertainties. The NLO values of {{formula:6e5e4c2c-2690-4d42-82d3-71d21e9cadc4}} and of {{formula:f1c77134-5a95-4ff4-8486-b2251048ba8c}} are determined simultaneously with the PDFs as... | r | 6636aab3e889af5d22dd1d71a8d76cac |
We name Algorithm the extrapolated proportional-integral projected gradient method for the following reasons. First, if {{formula:711dd733-1d8d-4660-ab10-2a91499deb95}} , then Algorithm reduces to the proportional-integral projected gradient method (PIPG) {{cite:0160423d7b30a1ef7c715f894e09d852c5027e62}}, {{cite:8b5d... | m | e25cee5400785f2539f8fc5fe111b00f |
We compare {{formula:6da46a6e-df28-41de-b9b9-d93e869a53f7}} with supervised data valuation methods, LOO (Eq. REF and Truncated Monte Carlo (TMC) version of Data Shapley (Eq. REF ) {{cite:1c468cc3f15f46df76f74d3193703f33b8144c76}}, as well as a baseline method that randomly assigns data values. All these methods are a... | m | 1e2071e8c604bf7b3749fdc53ced54b4 |
Fig. REF shows the performance of the proposed angle-based beamforming algorithm. For comparison, the algorithm in {{cite:24ad07f87910cfad38cc48382c22b7478db7c60d}} which assumes full CSI is presented as “Benchmark 1”, while a beamforming algorithm based on angles estimated by the MUSIC method is presented as “Benchma... | r | f35922e66e81353aafea831f54278cb4 |
Table REF shows the fraction of valid molecules generated by GRASSY, GSAE {{cite:de0a2431adffc6fdc271a30a96c59148764cb316}}, GraphAF {{cite:184f2c341612b4cf734c1a0dac47c2841fc4a5ca}} and MolGANhttps://github.com/nicola-decao/MolGAN (full RL version with hyperparameter {{formula:cd99d036-5d17-4402-958a-b2d2e633aa58}} ... | r | 996795b1f003af92b785598d1ad0fa9b |
Before our transit searches we: (i) rejected data with quality flag values {{formula:88ee69de-d5c8-4c2b-8f4f-036987347d7a}} {{cite:ff3b3ff58ac4f77f588417fc0b100e2ba2c00bd4}} leaving 14827 cadences; (ii) recursively removed
outliers exceeding the median flux (of the entire light curve) by more than three standard devia... | m | 9c1c8fcdb6cce996ab4cc21536d7693a |
We evaluate the proposed approach on three publicly competitive fine-grained visual classification datasets, including CUB-200-2011 {{cite:ea8114aef6f118de9d84db11464b066d62ebce25}}, Stanford Cars {{cite:b6966ca8486de8fc81e26e6ca6dea1ba71144dc9}}, and FGVC Aircraft {{cite:dbfb7b395e120f10758d4a4244e515c4f5cff350}}. The... | d | 25ad308ffd587621719d898e7aefe593 |
Let {{formula:09c8ec79-38ac-49ef-9c70-e2dfe25301f7}} be a Hilbert modular form congruent to {{formula:23c1354f-2b59-4485-9351-97c79dce2259}} modulo {{formula:80e3f1f9-4809-46cb-b9a9-865018124603}} which satisfies {{formula:61589c84-82b8-45fb-9695-29acd357ae46}} and {{formula:8d8806b3-7934-48d1-bb30-02b8382038a2}} .... | m | 0bd76b7fe23a7e0b7def222b08181fb1 |
We have shown how a two-step learning approach can result in efficient and accurate solutions to the HJB PDE. In our setting, the output of the neural network was set to directly be the value function {{formula:099399ed-d88d-479f-b579-9e0f9ed29013}} . However, as in the SDRE derivation, it is possible to assume that {{... | d | 2a3675befc5bc635f1b0724a69ea6a3a |
The labeling challenges in ImageNet were identified by the research community {{cite:9a4652a5d45b9f6326ea0c312b85efc6ac84479e}}, {{cite:4b2771369208cd722a78250322501644fb932133}}, {{cite:2d084b4ab0f7d243181922ae54761c7612ef9313}} and initial attempts were made for mitigation. Northcutt et al {{cite:4b2771369208cd722a78... | m | f4c2811fdf657b195c1b8df408be4346 |
There are many plausible extensions to this line of work. We have assumed a rigid model for treatment effect heterogeneity in this paper: treatment effects vary according to a known stratification on observed covariates. More modern work {{cite:f65e0778e07c51427edbf3f8e0593d25f9004bea}}, {{cite:98ac01c2fa0c6353a87ad7e7... | d | 67c24af74ced3165248eb28aa5b4ee4e |
where {{formula:feae4c96-38a0-49d0-9d44-dd18ff72abc2}} is the film thickness,
{{formula:3e90502f-fc5b-41f1-a51d-1be1d44074d3}} , and {{formula:137a42f5-225e-4258-bd2e-9dc44d40d7f6}} , see Ref. {{cite:27394d0d139b13f709a9b7819ad7c9c33ed722a1}}.
| m | 28df54e81af4f1d2b52f43f12a87d5e4 |
It should be noted that we have ignored saturation mechanisms other than the axion emission to infinity, such as the spin-down of the BH {{cite:6af8070ba2825bfc7df16b622212f35b9e39a648}} and the energy dissipation due to the existence of the multiple superradiant modes {{cite:942fccc6dbabdb3fb7f0a44f91b0cdd32e445ad1}}.... | d | 458f69022a100c5448083db0912c2887 |
When comparing with the experiments {{cite:95f9d9654aa0fe435015fb96711ac78a9866b86f}}, {{cite:eccbefcce18a50a4241a149e4bb5cb2a74c8508d}}, {{cite:49e7302ee60bd72e52796b378ebf1070df219a8e}}, we find that the typical electric potential performed on TDBG is higher than that used in our theoretical calculations. This may be... | d | 7bc1963506fe172c109eb07827b3054f |
The posterior distributions estimated using the proposed algorithm, although close to the MCMC results, nevertheless differ slightly. The results are slightly noisy when estimating stochastic volatility, while in the DSGE model they are biased. This signals an opportunity for further improvements of the neural networks... | d | 1d68b1c9292a3b13283f58016339185c |
There are many real-world challenges in computer vision, aiming to solve the problems of the COVID-19 dataset described above and classify slices. For example, Fang et al.{{cite:943515e5b14832983f4c73c4f5bf18f72511b559}} proposed enhanced local features based on convolution and deconvolution in CT images to improve the... | i | aaa3f100acecd4a59e52f03b1f60b235 |
We compare our method to an RNN {{cite:18e3b639ae48075803e90fe4879af5b0798384f7}} and a Transformer {{cite:55689e1788a0e36d42dcd9bee8fcd1a294c0ef78}} baseline and present some ablations for the proposed novel components of our model on HumanAct12 and NTU13 in tab:HumanAct12NTU13 and UESTC in tab:UESTC.
Furthermore, we ... | r | 8e313ec7fff91b66feea5c8ad805d26d |
Like RNNs, transformers are designed to handle sequential input data. However, unlike the latter, they do not necessarily process the data in order. Rather, the attention mechanism provides context for any position in the input sequence, and self-attention itself identifies/learns the weights of attention. In the case ... | m | 4bcdba029d7c91404864a5933fffe9a6 |
Due to the very different energy and time scales involved in prompt charmonium production, phenomenological models assume that the cross section factorises into a hard term, describing the initial production of the {{formula:8cac89f7-9aee-4bd5-8c9d-9632a50290fe}} pair, and a soft term accounting for the subsequent evol... | i | 8cc9dbaac83c86fb7ae9e53a192b6ece |
In earlier work, {{cite:164b38e24fc7daf01ec86c338d5c1b4907faefd1}} proved that the binned empirical estimator {{formula:099b062c-c22a-401c-8e3b-a13edb7c93e3}} consistently underestimates the true ECE, and showed by construction that this gap can approach 0.5. Our results complement this work in that we are concerned w... | r | 46a371a2a42cc8b87b3d12ac5625f665 |
If the integrand can be extended into a region in the complex plane, each univariate rule can achieve an exponential convergence rate. Hence, this choice of quadrature rule exploits the smooth dependence of the solution on the parameters {{formula:a8dfe13d-7c43-40ca-91e1-aa1931b1ab42}} for {{formula:e1b64037-eae0-4aff... | m | 4d6a8d8624a17d77675dd62f68c1acad |
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