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To sum up, we conclude that Lanczos coefficients and K-complexity behave in an inverted harmonic oscillator as if it was a chaotic system. Some comments are in order. First, our result differs from OTOC, where OTOC does not exhibit chaotic behavior at low temperature{{cite:560d012672543b27fae10b74d78b4cff7436b112}}. Th... | r | 259e494a7d9d5acdeec52bd0a758275f |
It would be interesting to explicitly identify the dual {{formula:01a28f43-2ece-41a0-bb7f-30fe3df93ba3}} SCFT together with relevant deformations dual to the solutions found here. Uplifting the {{formula:cb0de23b-8c5d-4c01-aea7-fa062fd89e45}} gauged supergravity considered here to higher dimensions will allow to embe... | d | 6759af2e976743eae8a789c8870567b7 |
After all the iteration, we can obtain the stationary point {{formula:eba06a40-dc51-4948-9282-b1adf5a37cd3}} .
Here, we can use other splitting methods such as ALS {{cite:f65d5e9e6716b21a7428977d1f97244c8b097423}} and PRS {{cite:9c1cce6e55be2b0d2bf95cd14c37d74ec92e462a}} to compute the objective function (REF ). When t... | m | 37993834f8c0cee88fa9c5060cb9cb34 |
Robots with different numbers of limbs have different advantages. Quadrupeds are known for their agility {{cite:87c4714c277cf28c24efe6bf8a04eee3ac7d6ef3}}, whereas hexapods and myriapods for their stability {{cite:b6a500b0e835286927345cbacbb4c34f121bb296}}, {{cite:0e0de8d1c4d5a1c3d79f7bddd2612590bfb36343}}, and limbles... | i | 5245ded283c55045f50b2cef6db85183 |
We test AVOD's performance on the proposal generation and object detection tasks on the three classes of the KITTI Object Detection Benchmark {{cite:9c991246041fd08a2d2ffad088f2a700e0dcae49}}. We follow {{cite:ed477753967ddeb63a508b67a23e58257a022e35}} to split the provided 7481 training frames into a training and a va... | r | 7cc62705e3536e21cd79cae6534aeffd |
Many searches for new spin-dependent interactions have been motivated by the idea of axions {{cite:8b74a4e481b00c727af9596c8064477824ffc2bb}}, {{cite:4f065bb78d0a98b67af3d6a720fedade9eec9c02}}, {{cite:9e3ebdcdf275062cefd5884387433c5ca7781555}}, {{cite:97a79b9fa24931cb7b24fd56b5fbd418a343b3a7}}, {{cite:7917c79bc9a42463... | i | e90216571a49cbfe251a21b5c105f1c8 |
Identifying the underlying structure of a data matrix and extracting meaningful information is a crucial problem in data analysis. Low-rank matrix approximation is one of the means to achieve this. CUR factorizations and interpolative decompositions (ID) are appealing techniques for low-rank matrix approximations, whic... | i | 9a0603a8ad078e9eae35a091812dd5d5 |
Online cloud computing platforms have made large scale distributed computing accessible at affordable prices, leading to a surge in usage of distributed computing frameworks like Apache Spark {{cite:f643ccd4d56a76b54cb7eb6c047dcb106e0082c4}}, Hive {{cite:2fec87388ce0aab165b32a0247de84c0863f40dd}} and Presto {{cite:1301... | i | c61e75236e7428d2f871b31856df6f2f |
We consider a sketch to be a collection of strokes, wherein each stroke consists of 2-D continuous offsets and 3-D discrete pen-states. This representation is also known as the stroke-based format. The discrete outputs pose a difficulty for the gradient updates to be passed from discriminator to generator for the weigh... | i | 9b5eca217e5778c7012a13257107f0eb |
As a fundamental and efficient approach for solving (P),
the classical augmented Lagrangian method (ALM), dating back to {{cite:ee2c26a3849157a8951c2f00cc2caf266ed6ffdb}}, {{cite:e1103ab22ddca8ebe6660c14479a00e3607c3f9d}}, reads as
{{formula:8e54666e-75ae-4ed9-9e56-a53072b6b253}}
| i | c7d47a25ebd550ae9936fc75002b46cc |
The extracted values of {{formula:06216f39-0b0e-46c6-b44f-f51278c89da3}} from the {{formula:624e8205-f846-4661-8e93-d399f98e7207}} distributions as a function of {{formula:6434a85b-3761-4dfd-aab3-ac8990938673}} should have the least contribution from photon transverse momentum and interference effects. However, ther... | d | 1e424d84869a29c9a3a7d45e8b3557e4 |
A version of this result is shown in {{cite:1d97f253d8bd693c7ee0436dea4670a380efc8bc}}
for surfaces over {{formula:9c3b5afa-7a11-4a71-b91d-45380a3b8bd0}} CKS(X){{formula:fc1f54bd-8e3a-41d4-9fd7-e08f5b7922d5}} H2nis(X, K2,X){{formula:d9ef0cf3-0502-4282-a488-8c4c36cfa4a9}} K*,X{{formula:ee142949-3941-4841-88f9-02fa2da8ce... | r | c5dffe4081965c87d4b18bf780dc25fa |
Numerical solution to the minimization problem (REF ) poses a challenging problem due to
the presence of a highly nonlinear and non-differentiable term. To
get around this difficulty, a large effort has been devoted to construct
effective schemes for the minimization problem (REF ) and
the PDE problems (REF ) in the pa... | i | 8d50a21cdba268cb76d3f3be38f15d4a |
The proof of Theorem REF is divided into three main steps contained respectively in sections , and .
As a consequence of Theorem REF and the Urysohn property of {{formula:cdb9e659-831f-44fb-9b84-4964e0454413}} -convergence {{cite:2f2fc11dd7f989339382110df946525c9581ea55}} we deduce the following corollary.
| r | 0f8d7501b50f42e3399a33301303cf2d |
After the work of Nambu {{cite:8d7c29bde4be6702d439d81c687ffb98ae21a83a}}, there are more works done on the classical solutions of Weinberg-Salam theory. A well-known case is the sphaleron (sphaleron is static, particle-like, localized in space and unstable solution of the Weinberg-Salam field equations). Klinhamer and... | i | e03b8e2fbc91269e126ab065182dc077 |
As shown in Fig. REF , our approach achieves significantly better texture results even when the texture is extraordinarily complex like the floral dress and the geometry we estimated filled with elegant details instead of a sketchy and bloated object. Even applying per-vertex texture mapping in the geometry from Multi-... | r | 9b7246b8951386c798aa403e3420ac00 |
Deterministic Rule-Based Methods: The general principle for such methods is looking for keywords within a conversation that can be used to instruct an agent to provide predefined responses. For any such conversational agent, a 'script' can be defined from which response clauses must be generated according to expected ... | m | cae13490185b756a9b3de357ad15ea3b |
To prove part ii) we follow the same steps from part i). We obtain {{formula:fdec3afb-5d33-47b4-943c-9e20f1e5bb17}} , {{formula:6b2f50d4-33b4-42ce-a70b-3840c780b6bd}} by following the method in the proof of Theorem REF , and using Theorem 3 in {{cite:e65c2ad7cda00001b626e940b810b13f8a3d31df}}.
| r | 682585fd770cb2f34584f86a3032e068 |
This has been proved for the ideal Bose gas ({{formula:aee42b45-c6ac-41b6-a336-a06c324ce25f}} ). The representation of the one-particle reduced density kernel in Theorem REF for {{formula:d984d842-fb5a-4204-8ba7-243198016e23}} allows to perform the thermodynamic limit (cf. {{cite:fcec3e9966bc2f3f561380d3b97b6b7be34a1... | d | 17f15849a6c7bb00f879516fca1a0e10 |
Like the original paper, “XEntropy” stands for cross-entropy using fixed word vector, and “Optimized” stands for optimized word vectors. “Average WordVec” means that we have taken the average of vectors representing words in the metadata and used that as the target. We also trained a variant of DenseCap {{cite:1efe5ccb... | r | 58156d913a749d2bc38758ed413e711d |
Trying to find such relationships, one can observe that symmetry drivers allow to construct differential operators which map the characteristics of conservation laws into symmetries, and integrals (including formal ones) generate differential operators which, roughly speaking, perform transformations in the inverse dir... | i | f97caa3bb287b79aca08a4b390e4d941 |
Recently, Jimenez et al. {{cite:e90f7dc264078e543eae65b31bab48b9ab2ba6f0}} introduced a new class of modified gravity named symmetric teleparallel gravity or {{formula:97c777c5-2513-4c84-9bb6-36660969bd9c}} gravity, where {{formula:e150819e-407f-483d-88f8-083f649f1eff}} is the non-metricity scalar. In this theory, bo... | i | 022b5816c1f1cd120c906d7e12c3ccc9 |
We use model, ground-truth and loss function designs very similar to those proposed in CornerNet {{cite:5de99efafa63373bd8e8a4d18ed1ce203e283c1e}}.
These components, and especially our modifications for TetraPackNet, targeting tetragon-based object detection, are explained in the following sections.
| m | 32e1df1ebd7dbb760d3fc03f79ba33c7 |
This section evaluates our proposed fusion model on the individual test dataset for each weather. Similar to the state-of-art method {{cite:67c18270b2c70ea044ae095d59269247357251e5}}, we evaluated the proposed GLA framework over PassengerCar class because these are the most prevalent class in the DENSE dataset.
| r | 071cb3574cf66ece70f24c002c7658cf |
In this section, we describe the proposed approach to learn discriminative features for multi-label classification. The detailed architecture of the network is described in Figure REF . It is built upon ResNet-101 {{cite:7cd3f3766bc11ad0d6f2a975d3bb18f0e23352aa}} as a representation learning backbone.
The proposed loss... | m | befe5057db476b32f934eb91380e6952 |
where {{formula:8dbc6cc4-7918-4ff2-adc4-ca401be7dec2}} for {{formula:071b8197-93f7-45c7-b678-d7bb7c92ed5a}} and {{formula:5095b28f-8825-4a96-a5b5-ab4faf5d1782}} for {{formula:5f7fcd4d-debd-463d-890a-2fe15db52ee7}} . In the case of PBH baryogenesis {{formula:a320339c-cf6c-4094-880e-8e8837f200cc}} . Now using Eq.REF ,... | d | 27de73227946b3810729651a462d5599 |
Recent works on generative modeling for 3D objects or scenes {{cite:79cb65980d040ec8c34a0a2935a2dc79b63e7bd1}}, {{cite:d17805c97290983b9cfb4eb499a8bad13ff9abc9}}, {{cite:1f29d013867856baa6d858da80a2f880b27b2c60}} employ a Generative Adversarial Network (GAN) where the generator explicitly encodes radiance fields — a pa... | i | 245846f269f7afbc134c283e62740480 |
A promising path that offers almost arbitrary flexibility is the use of optical dipole potentials (see {{cite:543782e28ab0fefef3a3d8a0cebec7e10b0c3e76}}) due to intense (laser) light. Spatial control of the incident laser beam for BECs using digital micro-mirror devices (DMDs) was shown in {{cite:37eb6aff0939ec1eae785d... | i | 62949b722a7136b441661c086bc536ac |
In practical applications, we should not only consider the effectiveness of LP, but also inference efficiency.
Many LP applications generally require fast retrieval of the top scoring neighbors for low-latency services {{cite:29573da1fcbc38463dce8f5115dbf3d1b9b055f3}}, {{cite:7e0631c8d2ec5a126568fae804732ed6fc5ab9d8}},... | i | 134289cdfa9dcf0818abfb7947926771 |
One disadvantage of any simulation-based design approach is that the objective function to optimise over is stochastic. Even though the classification approach reduces the stochastic noise compared to ABC, the optimisation algorithm needs to take the noise into account. Our focus in this paper is not on optimisation, s... | d | bc7b4114e5365b436420e0ce6b8a9486 |
To validate the effectiveness of our proposed framework on representation learning, we visualize the generated speaker embedding with T-SNE {{cite:5d1d54d40289316e8758d1614ab17b7cd0ee41b6}} in Fig. REF . We observe that each speaker forms a well-differentiated cluster for each emotion. These results suggest that the pr... | d | 79804df70240f0c053c8c592fa46c9ee |
Model selection procedures for LSB processes were discussed using NIC,
an information criteria similar to AIC. While model selection for LS
processes have typically been done through different information
criteria, it would be an interesting problem to develop other types of
model selection methods such as methods base... | d | 314292e2f6c075f840be2a4ed89f3ffe |
{{cite:e95f717d3a801bed379b561bb70ecd9fb8a3ef27}} 2020
{{table:8ec01074-4aa9-4ff5-952f-3d1012b29326}} | m | 757c9d509b615ad0126aabf7c269af5f |
This paper focuses on these approaches by considering the popular StarCraft Multi-Agent Challenge (SMAC) {{cite:0cf04ec74eb3fb029da295f640f1c14abf5e23a0}} as a testbed. We do this by first adapting and then improving the DRL algorithms of the Deep Quality-Value (DQV) family of techniques {{cite:b2ffae152a98884ed7ed1515... | i | 803cd249de8d5dc5d538626dda3a2832 |
This result aims towards a correspondence between orbits of linear forms in Hom{{formula:545b47e3-288f-4ff2-9446-f049537aae6e}} and primitive ideals in {{formula:03770808-e22f-40d4-881b-19f648435372}} , in line with the classical result of Dixmier {{cite:f2bd65a192cbfae7052f65a1eb614316af30db9f}}. In a subsequent pape... | r | a24d9a0d43c89f3f1fec4b7909ebf32f |
Photonic crystals (PhCs) are employed to control the light–matter interaction using the photonic bandgap (PBG) effect {{cite:4e4c98a1a3a9b9408b66353cbed424d1ceaf0be2}}, {{cite:f202e6ff9d7baf1820d8b2ab3b937e0786cf2244}}, {{cite:e7bba567a1d4094924527545ce6ab53340b4d803}}. In particular, two-dimensional (2D) PhC slab stru... | i | 2eb2e613f1a65a7001d804c88deccc91 |
It is also noteworthy that the storage cost for Tucker decomposition in the proposed procedure grows exponentially with the order {{formula:79bd95f6-4ce1-4e49-9063-e63bc31e02a4}} . Thus, if the target tensor has a large order, it is more desirable to consider other low-rank approximation methods than Tucker, such as th... | d | f015f352a71096e94bf6f85c6872661a |
Nematic order has been widely observed in two-dimensional (2D) realizations of active matter {{cite:340b14d164338869917b34ca532b04561813404c}}, {{cite:0dfd223b9229aa486f20cdc9b2c87c784bc98fc1}}, from vertically vibrated rods {{cite:ae390caa49076b12e25df11049082a9a02c9ee4b}} to mixtures of cytoskeletal filaments and ass... | i | 50fa6dd5eaa936daa4c368b6f2598616 |
To also put these results into context with QKD applications over short links, we estimated the back-to-back detection rate, the quantum bit error rate (QBER) and the asymptotic secure key rate for the entanglement based QKD-protocol BBM92 {{cite:895ee9122a26152f0088cf951ee1f2fb623dcafb}}, {{cite:b478680e541b6c588368cb... | r | 8d986256a1d734eb47a6eebcfe26d9e9 |
If the community structure is truly capturing the protein's topology, we expect this grouping to reveal aspects of protein function. We can test this claim using Gene Ontology (GO) term analysis {{cite:dd14825bb2db65f4a7010f6f9920da0d2da5fa70}}. This effort assigns functional relevance (e.g. lactase activity, oxidoredu... | r | cb7adb77468fc5ee5d8e1e9994d16c53 |
MAEs (MaskFeat, VideoMAE, SpatioTemporalMAE, OmniMAE, and AdaMAE) generally outperform previous supervised representation learning approaches (such as TDN {{cite:e35b2ded82397fbc0fe9b5c3db6c0803544b2c77}}, TimeSformer {{cite:3bcac0015dcb887d6017524ce84ea133254190bb}}, Motionformer {{cite:4a0bc9ed28e1d89b926b458706e3acc... | r | 74f95a4564bd3072f78ab1ea9db40cdc |
The motivation behind using MTL includes the implicit data augmentation, since a model that learns two tasks simultaneously is able to learn a more general representation. Also, if data is limited MTL can help the model focus its attention on those features that actually matter as other tasks will provide additional ev... | m | 1ea096617930ccf040efa5917627580b |
a{{formula:32476c35-d720-4b0c-be99-fdfc9af69aca}} and {{formula:d82983ea-e000-4ca0-8f8c-04d7f052d4b3}} are beginning time and end time of the giant X-ray or optical bump, respectively.
b The references of GRB prompt phase observations for our sample.
c The references of GRB redshift for our sample.
d The reference... | i | d972758c5583f88ce91f331e558f4736 |
Based on {{cite:e2fd3d0703231e72c5dbe4e7e33e8a3df2c8ba2e}}, the optimal solution should satisfy the following Karush-Kuhn-Tucker conditions of Problem (REF ):
| m | ba282faa217f243223b05ed131a8da43 |
which, using the value of {{formula:be7f7dc3-0942-44b8-adff-1043312a9e8c}} from studies of gravitational radiation from string loops {{cite:9c60b25b408638c2c1db89e8401a59784b79820a}}, is about {{formula:6d4cf865-f7ea-4f90-b7b7-bfc056dbfe14}} , assuming no Eddington accretion.
| d | ec4a7c345b4c38a5a6c67465a70d9f9d |
The results presented highlight some ML success against baseline forecasts and also a number of unique avenues that could be explored moving forward to enhance and improve both ML-based guidance and the SPC human-based forecasts, as well as increase interpretability of the ML `black box'. While the feature assembly exp... | d | e10893d4b90de056f0ac49a85f0847a1 |
Our predictive benchmarking method uses the performance results obtained by a SLAM algorithm in a number of environments to predict its performance in new ones.
blackCompared to current SLAM evaluation techniques, which are used to perform ex-post benchmarking, our predictive benchmarking approach provides an estimate ... | m | c7232679c78695bde3cf6ce1324984d8 |
Vanilla dense neural networks architectures suffer from overfitting on the balanced EMNIST dataset. To mitigate the problem, we tested a lot of regularized models using dropout and L1, L2 norms that clearly show a massive improvement in generalization strength of the models over time, if fine hyper-parameter tuning is ... | d | 8aad00299038c2c83f5b8b787ac500a5 |
OpenImages. This dataset {{cite:efa030d382efd50dafea1c414758683806a258aa}} is the latest endeavor in object detection and is much more challenging than its predecessors.
Our classifier achieves 69.0% top-1 accuracy on the validation set of OpenImages V4 which is lower than other the three datasets. We achieve 58.9 UAP,... | r | e51aaa7759f369e8195e6a61f2a539c7 |
We also compute VMM from the tree level diagram, the vertex
correction and the four-fermion interactions respectively. The
contribution from the tree level diagram agrees with the result
obtained in ref. {{cite:0750ab1853ea5b1bc189c6145ae426009f71cca4}}. The other two contributions counteract
each other and therefore t... | d | 5ff2f5480129c9bfbafd60acab486600 |
As seen in Table REF , DAT improves FID, KID, and IS consistently and significantly across many datasets with three popular models. This suggests our approach is versatile and can generalize across multiple data domains. In particular, the usage of DAT greatly improved the FID of SSGAN on STL-10 dataset. Due to the lar... | m | db854025d3d3600a2e7a8449b53d4c19 |
In this paper, we discussed multi-soliton dynamics of
anti-self-dual Yang-Mills equations by analyzing
the action density in the asymptotic region.
By considering a comoving frame with the {{formula:315b8016-1a75-4aa8-a6d3-d98a4d1d676e}} -th soliton,
we proved that the entire multi-soliton distribution is asymptoticall... | d | 2404299dca2fc296b4aece9f432b7048 |
We empirically evaluate our proposed algorithm on six different continuous control tasks from the Open AI Gym continuous control tasks {{cite:42bccb2baa79eead11f53e2d0b32105e60d5ff71}}. We compare our method against well-known optimization-based reinforcement learning algorithms such as proximal policy optimization (PP... | r | af4270108e5c338d03f7566f9b74d7c3 |
Our study is limited to extant words in English and randomly generated character {{formula:805f71ab-3977-405c-962e-aa9d7e82e068}} -grams using the English alphabet. Given the unique impact of a specific language and alphabet on representation spaces, there is motivation to see whether the relationships we identify gene... | d | 0afd56c5e1c43724216ac272b79a7474 |
Since the historical success of AlexNet {{cite:ffb9f982dd78f5c4035586bc2bb6f6d43249c3e0}}, convolutional neural networks (CNNs) have been applied for a variety of machine learning tasks {{cite:d713537b241582a42919589abd948abd72f71954}}.
In the research field of geometric deep learning {{cite:b74f8ecefe42c2e0d0a3d783389... | i | 2ef4b21bfb822bbad2b7aaa1242fb78d |
The theory of iterated integrals was developed first by K.T. Chen in the 1960's {{cite:7d708cccca1a54b6521a8e3bfb0a5f1607ff1fff}}, {{cite:cb44e4a465848b852463345e109a8b93d36879c6}}. It has played important roles in the study of algebraic topology and algebraic geometry in the past half century. Its simplest form is
{{f... | r | 44b6179a04edfc17a6bb879a241234b8 |
Our initialization method is designed to alleviate the problem of learning local minima solutions — an issue that the family of EM algorithms are well-known to suffer from (as well as slow convergence rates) {{cite:8e483ff8947b765e72b0860237991df94d355ce6}}, {{cite:a6bc2f17cce9e87a7e725327ec01012f83a780b4}}, {{cite:a60... | m | 43788eacd0b0a2591802b2e18f393115 |
In this section, original ViT is named ViT-Base {{cite:ce974ab518dc974e7c57240048544979fc6cc133}} with several changes, as shown in Table REF .
{{table:d7f358be-3c21-47e4-baf7-d93886590f92}} | r | 662bef60891140b45b780cf4263585a9 |
In this Letter, to resolve the stalemate in this research field, we propose an alternative route for creating an effective {{formula:03bfc8aa-c769-4fc9-815d-6435279433ee}} -wave superconductor.
We specifically consider a three-dimensional Josephson junction illustrated in Fig. REF ,
where a thin-film semiconductor is s... | i | b4f5c119decad5e90168bd32cb673626 |
Our results are mainly based on an adaptation and a combination of the techniques used in Holden et al and Chase's papers {{cite:78c622ced26a604e8f34c7cd167e5c10db97d383}}, {{cite:77bfd2ab07019a1c05b530d5d1c099ac6695e356}}.
Here, we will give a brief overview of their methods and why it is not trivial to combine them.
| r | 6c0e3424e422051fa386608f6184f33e |
We compare post-training quantization using INT8 and FP8 quantization.
To allow an apples-to-apples comparison, we do not use any methods to improve post-training quantization that have been developed in the past years (e.g. those mentioned in {{cite:76d331408d2df1dec0c1c72676154c36d9c20f23}}), other than the methods d... | r | ef3daf89ead26777670529abf1dbadb5 |
The first inequality is due to Rosser {{cite:639cfae210c44f2f5aeae0d988ab2b3c3d4e892a}}, whereas the second is due to Rosser and Schoenfeld {{cite:a0b79805ed3879470a385a3fa3d02d6e0f8bafae}}.
| r | da57dce7f5f825655f6cca032cc7d798 |
The main limitations of our study are the requirement for hypergraphs to be produced by the generative model of Sec. , the use of the mean-field approximation, and the use of approximation (). [Here, we refer to the approximation that all nodes with the same hyperdegree are statistically equivalent as the mean-field ap... | d | b33b6768526aa3aa8264458682599fe6 |
Our training set for the ChIMES force field was determined from DFT-MD simulations of amorphous TiO{{formula:7eb123e3-9084-4fcd-a955-e9f6d0859353}} run at temperatures of 2250 and 300 K using the VASP code {{cite:fa05b92be45b4af42f0c001a9bbbf8e4b9738eb7}}. For these calculations, we used the PBEsol functional{{cite:88... | m | cea11c28f1e4958aedfb8af4043cddc1 |
A common approach to discovering these seemingly disentangled representations are variational autoencoders (VAEs) {{cite:4c3dbff8b81b822cab52fc83b4a33e35d082a302}}, which are trained on unlabelled data to learn a lower-dimensional representation capable of reconstructing the given input.
Unfortunately, it has been prov... | i | 2aa52a000e2c1392155e40de7c6fbe31 |
On preventing phase transitions, anomaly detection already offers one path forward. Once we can detect anomalies, we can potentially prevent them, by using the detector
to purge the unwanted behavior (e.g. by including it in the training objective). Similar policy shaping has recently been used to
make RL agents more e... | d | c4acc129f850ab118e6509eb2222ae56 |
where {{formula:542352a7-5502-40c0-8cd9-bf8431f5577d}} and {{formula:ca40c861-2127-4ab0-8fce-d694f6de2694}} are the bag radius and quark energy, respectively.
Recently, {{formula:23c67551-29d6-434d-a6f0-41d8d0017627}} has been updated by BESIII {{cite:d000ac1d1c874303a9029c76fdd057b760ac9fc3}}, {{cite:6dc7f40dcf7ecf... | r | cd081e20bae12ab4f4fde887172ea27a |
The Grad-Shafranov method allows to solve the boundary value problems (A),(D) and (G).
The case (A) has been already considered in {{cite:a676fed81094cd2c004ab17c003bf2207ca76c1e}}, {{cite:6b71d6c96f37f292be76690fec6b2943e81bcbb0}}. In this paper we will discuss the application of the Grad-Shafranov approach in Section... | r | adbeb235829793b5f0378ec3db814d52 |
Recently, {{cite:227b4210472462df533a4a1eee9f442e56c92ba3}} developed a mixed-integer-programming-based (MIP-based) approach that builds representative matched samples. MIP-based matching algorithms ({{cite:d5a14ad6bfce3b9e2fce0561e1043ea4b952ae4a}}, {{cite:c1816e9aedc37d4d798e48d439623c83ad5474c3}}, {{cite:227b4210472... | m | f70bb8d52bb423a5fd73352f4e4ada93 |
Note that although the SDR of problem (REF ), i.e., problem (), is equivalent to problem ()-new defined in Appendix D, the reconstructed rank-one approach proposed in Appendix C is no longer satisfied for problem ()-new. In general, the SDR tightness for problem ()-new may not hold due to the limited degrees of freedom... | d | d29c271a763874882c277f8912a95593 |
The detailed quantitative analysis and comparison of algorithms within the locally-balanced class in the high-dimensional limit is made possible by the mathematical framework developed in Section 3 of {{cite:378140678e9dd1b01961d1854760825bb31062d6}}. This framework identifies and uses only essential Taylor series expa... | d | da8d679282231ce0aae096115cb7942f |
To evaluate our method in simulation, we implement a suction gripper in the ManiSkill environment {{cite:72f6ae2b0f7c88fb5036a139bcf90b4737d038d3}}, which serves as a simulation interface for interacting with the PartNet-Mobility dataset {{cite:cbbea7f43258d7065e1ab82d2c67a23f2e290ed6}}. The PartNet-Mobility dataset co... | r | 87b46e30d52f52d7af3bfb36749c2cbe |
In our future work, we will apply the photoionization computation to the current hydrodynamical results in order to obtain the local emissivities of O6 {{formula:acd27031-e192-4d8a-90eb-0bab115da184}} 1032 and {{formula:a0bf4830-e7a1-4a38-b025-2ac812ffc4fe}} 1038 and the distribution of neutral hydrogen. The emissiviti... | d | b99b93ddac7512ef78394a78ac4b1549 |
{{formula:86a9d047-2ae6-4022-84a8-3d219bc3714c}} is triangulated by {{formula:c128a87c-0417-4825-9d8d-8962ecd62cd4}} that consists of simplices {{formula:3b2c164f-9eeb-434a-85e6-322218aee161}} with {{formula:37935db2-2b10-4a4c-85b8-a9c11ddddcc4}} its diameter and {{formula:730e9ce9-ca7c-4665-a88e-fceb134efabf}} . W... | m | c653a5bebc5fd6ea65147fc7d99ee1b4 |
Our Architecture.
We consider a 3-layer neural network {{formula:43a86815-3144-489d-9479-cd914512261a}} , where the input {{formula:8abc7ed3-eaf9-45d8-842d-174b997fe30e}} passes through a wide randomly initialized fully-connected non-trainable layer {{formula:54cce2e7-1275-4fff-9e5d-b706d92921dd}} followed by a ReLU ... | r | dd796446b0bf94e33d9272f24ee33140 |
Interestingly, in a recent paper {{cite:ae3eb05346074499dcf4427efefef0963aa4b4a0}} that explores the discriminative power of graph neural networks showed that GNNs are at most as powerful as the WL test in distinguishing graph structures. By choosing right aggregation function, they develop graph isomorphism network(GI... | d | 8c382f77364833690dcd490cac3a1330 |
Since the proposal of the Weak Cosmic Censorship Conjecture, several counterexamples to this conjecture have been found, including collapse of dust {{cite:53d9f8973e2941d4f09d854379d5945f3fcc88ea}}, {{cite:a3b439faa5c03eee56c8b82cf1361adb2ec122f1}}, {{cite:83aed4ef4a000e8e3c62796e8aa9b24ea7d9dd53}}, perfect fluids {{ci... | i | 03c03089c3fce538ad6635c7eb9c8f4e |
The use of semantic vector-space representations of classes, i.e., class embeddings, is prominent in
zero-shot learning (ZSL). Most mainstream ZSL approaches learn
to estimate the
degree of relation between a given input (image) and a class embedding, so that
previously unseen classes can be recognized purely based on ... | i | 3116637e069f18a4af0fc379af411e00 |
We have made a comparative study of RHDE models in different dimensions. A few points are worth noting. The density parameter is plotted in figs. (REF ), fig. (REF ), and (REF ) for four, five and ten dimensions respectively taking three different delta values. It is seen that density parameter exhibits a sharp transit... | d | 576c1882ec8b5c563bec21845bc87e5a |
In our paper, we will build on a formalization of shacl {{cite:b9fa36ae661abfb88a870350f2d824119476eb80}}, which has revealed a striking similarity between
shapes and concepts descriptions, as known from description logics
{{cite:92a7e5b29c9f71f9c885ddaeca3583e98285eb40}};
we recently deepened this connection further {... | i | bd4b332ec022b114c0204384970afd3b |
We have performed all the calculations using Vienna {{formula:cc9e16c0-9bb7-4560-b04a-266a4f4dedd5}} Simulation Package (VASP){{cite:5f541a423227d3c65ef9c7dc0eee033cba2f09f6}} and projector augmented-wave (PAW){{cite:a07fc0390c65a16fefe627fa9b43f1e1bcdb4932}} pseudopotentials within the framework of DFT.{{cite:d4a350b... | m | a859c5160db88779ea313f39f75caf7c |
Despite substantial performance improvements introduced by DNNs, they still have significant shortcomings due to their opacity and specially their inability to represent confidence in their predictions. These downsides hinder the deployment of DL methods in safety-critical systems, where uncertainty estimates are highl... | i | 2c4945c1b701553984ffde450726bc58 |
Recently, deep generative models such as StyleGAN {{cite:0344773e23c7bb2a1a705f2e045e2dc68cdc2b2c}}, {{cite:502d4faa5766542a4d228d53a063ca419d5d164c}} and diffusion models {{cite:13abbed6280b86443923604941700ae4e13a6b6e}}, {{cite:30a1144ea135e7e6271dee095a295e44759846a3}}, {{cite:2306016e8fedee5fbc5daf82e5d9d3da5e63d6f... | i | 354febfaa28e21c0953439daa059a150 |
where {{formula:f2617d8f-4d3a-4987-aba1-a2cfe8450fae}} , {{formula:2350a820-d359-4cf3-bb58-68a6e56f454b}} are positive constants and {{formula:0c50f63b-9876-4c13-b9bb-0b2277229fc5}} is a smooth strictly increasing function. This system has been introduced in {{cite:7e995126779f6d02285d9a7a9820438fbc2c737a}} to model ... | r | 57b118429f552ba355e94727c1ccd69d |
Traditionally, images from compressive cameras are recovered by solving a convex optimization problem, minimizing both a least-squares loss based on the physics of the imaging system and a hand-chosen prior term, which enforces sparsity in some domain, Fig. REF (a). For successful image recovery by compressive sensing,... | i | 8277d5635c6d1f929710051c97f3309e |
The compensation of costs and benefits is certainly a natural interaction strategy through which rational agents determine their connections {{cite:fa9d612f463923fc793752c12411237c772d90b7}}, {{cite:eaec82df880ebdcf7e05ea700042ed976376b22a}}, {{cite:9c48e25674dd36bec54934f28c7d8376fd581e1f}}, {{cite:52a947889b0a84fad58... | d | 813424626312e506b901a98c6f972454 |
Our formulation of Theorem REF
owes a lot to the pioneering works of
{{cite:8f559882cb7d40d8c8ab39115b3a0fabf4af93ad}} and {{cite:4a6550294a6bc97fe67b25587261a4b667b638f3}} (PN). Our is merely a refinement of the results
published by these authors together with a clarification of the underlying mathematics.
The intere... | d | 432340911e415184340cca52e793704e |
For a thorough treatment of the algebra of quaternions {{formula:821d5145-b34c-4f38-8083-22672fca378c}} , the reader is referred, for instance, to {{cite:58c1ab856d1b7dfdd138896af4f8eac716d6b19a}}.
| r | cfee8b25083cf8615b5fbb5518de1481 |
The KM3NeT/ARCA detector is currently under construction at the bottom of the Mediterrean sea near Portopalo di Capo Passero on Sicily, Italy {{cite:958968f039e5e7ea7a35514ecce38086c031aeb1}}. The detector consists of a 3-D grid of optical modules that each contain 31 photomultiplier tubes (PMTs). The timing resolution... | i | e532945d5ac4ff2779bfa95acc5827af |
As the speech synthesizer, we used Tacotron 2 {{cite:5ba5204a4845204295ea495907205677f62a850e}}. Tacotron 2 is a combination of the Tacotron-style model{{cite:5d42af7b4d2094fd9652dfbd2706f012cc0e518e}} that generates mel-spectrograms from a sequence of characters and the modified WaveNet {{cite:79f016f43c03b11eabf6dae6... | m | 63ec25a9b7de674993e077c44016c58a |
RMs of polarised background sources are often used for analysis of magnetic fields in nearby objects such as the Milky Way {{cite:884ad8aaa98c8811cd9eac420e2f983b05bcb5f5}}, {{cite:5b51773a6f0fc5d055f094924c333e29c8b41514}} or the Magellanic Clouds {{cite:0d06278eb97787a4f3cdde13e5aa6705385b8101}}, {{cite:f61b2ff86f3c8... | d | 7792be5bed444b59a31d54c5371269bf |
(iii) Also HL gravity treats space and time in a different way.
For the case of isolated black holes, the metric is time
independent and hence the spacetime is invariant under
infinitesimal diffeomorphism transformations. As a result,
according to the argument of {{cite:76150a8719e769085b4e452fec053bd385eb5c9e}}, the f... | d | ba050669be6f5525278077527ab42a2a |
The experimental results of nuScenes are summarized in Table REF . Our SPCM-Net achieves a competitive result compared to other baselines in all metrics. One interesting observation is that both SPCM-Net and PointNet++ {{cite:c535f92ea22634f8b3576ba8b24706b06669af71}} + LSTM outperform PointRNN {{cite:1493008f04356cbb3... | r | 374f1604490e90d61177f1ffa0fc30e1 |
Nonetheless, it is worth recalling here the inherent limitations of standard DFT approaches in estimating accurate band
gaps in semiconductors due to the ubiquitous electronic self-interaction errors and other fundamental problems {{cite:b419dd2c76b161c59fe7a095498cb69de0802be2}}.
In particular, it is well known that c... | r | a6d71b8038af3712f5a3264da6d46c23 |
where {{formula:07c0d0b3-5c02-4f9c-90a8-4e06b485d0ce}} denotes concatenation.
For instance, to approximate the RBF kernel, {{formula:bb61504c-95c2-46a1-94f1-36d6060cd97e}} , we would draw the {{formula:27dc5c0f-fdd5-4af3-9912-4f8cbbf98118}} -dimensional frequencies {{formula:103b7d75-d831-4b95-85db-8e41103e814b}} {{c... | m | 307617764ad63b617809f6d0bc7181a0 |
We have used the common normalization techniques used in NLP tasks such as batch normalization(BN){{cite:a537c710201768c2485fd566763bdb85f04f7dfc}}, layer normalization(LN){{cite:1d07fcf9157f85eefa1e1a08834bcc68e36c4a98}} and group normalization(GN){{cite:cd9773e03e0372907818fc427be6a047a3346b98}}. Such techniques do f... | m | 9092bc822de066587a9d65d5a4d1d2a7 |
This work presents an extended contribution to RocketQA {{cite:57ba3c7cbc3645e2021902b1239583f713f34d2d}}, called RocketQAv2.
As seen from above, RocketQAv2 reuse the network architecture and important training tricks in RocketQA.
A significant improvement is that RocketQAv2 incorporates a joint training approach for b... | d | e3b349fe68a825c76c529a9648fc5a90 |
For the three datasets we have in common with {{cite:111423a1b944a4b601d74901252cd5e5648eab66}} it is possible to draw performance comparisons with that work, though retaining our concerns about the use of AUROC for highly imbalanced data, which we found did not distinguish well between the methods. The two best-perfor... | r | 6772f5f63a5c6f3ca2b2ac56c1a80b95 |
Image-text Datasets: We report the comparison results for both Pascal Sentence and Wikipedia dataset with prior approaches, in Tab. REF and Tab. REF respectively. We report the mAP score for prior methods as provided by the authors in {{cite:6c87890dcd7a2b343f6482ee393d2b279b648f41}}. Since there is no fixed split pr... | m | 41dce83a070d229b2bdbf597a2ebed3c |
We observed that our basic prototype-based method, under the training-free setting, does not gain from more given examples. We hypothesize that this is because tokens belonging to the same entity type are not necessarily close to each other, and are often separated in the representation space.
Though it is hard to find... | m | 5deab6eea346c8d3eec563424ebf3101 |
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