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In this paper, I investigate the effect of decoherence on the tripartite
entanglement of Dirac field in accelerated frames by using a phase damping
channel, a phase flip channel and a bit flip channel. The effect of amplitude
damping channel and depolarizing channel on tripartite entanglement of Dirac
field in a nonine... | i | 41c7024bb74d99ea5e29483dbdb3a071 |
The Floquet-Magnus expansion is probably the most widely used
perturbative method in the literature. This technique treats inverse
of the drive frequency (in units of {{formula:bb0dc125-dd85-4975-86d4-c14b7e299a37}} , where
{{formula:4ca98835-591c-4a00-91e0-05455f492130}} is a typical energy scale of the system) as th... | d | b6ac3ba6a207e0183e0b0cb94051ae76 |
As a field of study, information security integrates techniques from a variety of disciplines:
Malware detection is largely a function of information theory as developed by Shannon {{cite:60ff6a147e8a549c907baa58da69e55bfad44b6d}}; incident response borrows techniques from forensic sciences up to and including its need... | i | 31ce9947e4a9f9e0b5454eb25e45e47f |
Results on MORPH2.
Here we provide additional results on MORPH2, despite the performance on it were long saturated. We use the same setting following {{cite:8206ccec8feacb278237822d940393faa1735376}}. The following baselines are tested:
1) DEX w/o IMDB-WIKI {{cite:8206ccec8feacb278237822d940393faa1735376}}: A VGG-16 Ne... | m | d0dc47d7abfcad93ed0865346cfb844e |
Bayesian non-parametric machinery is applied to federated deep learning by matching and combining neurons for model fusion.
Yurochkin et al. yurochkin2019bayesian proposed probabilistic federated neural matching (PFNM) using a Beta Bernoulli Process to model the multi-layer perceptron (MLP) weight parameters.
Observing... | m | 18b0e672f0669bada0a01a11c003708b |
Figure REF shows the clustering accuracy for different variants of the Triplet Loss.
First, we observe that Triplet Loss_2 (REF ) and Triplet Loss_3 (REF ) outperform (REF ) on multicut clustering (left).
However, K-Means (right) performs better on all our experiments given the fact that {{formula:90ce38c2-1719-4110-... | r | e134b1e4b683b325fe5abfdc4c9eac50 |
In this section, we compare VHBS with Ncut {{cite:dafc7242a84e05b638d96deeca99cd7643bfa49b}} and KMST {{cite:08016bcfd77dee6bc8151d16e9f918cdafb6d39c}}, {{cite:9b6f835320ab6672c8a42fd22d7936a62c6e196b}} over the entire test set of Berkeley Segmentation Dataset and Benchmark {{cite:79358fa890824939d578551cc391cdd3313b00... | m | 0030f66b94c09f90bd436368836baec6 |
We validate Algorithm 1 in CIFAR10 and CIFAR100 with ResNet ({{cite:b646c776c7f7b6ae82720c8ee563a6c14c53a82e}}). The results are shown in Table REF and Table REF . As the tables show, the GL penalty and the shrinkage operator can significantly improve the weight sparsity and the channel sparsity with minor reduction o... | r | afa9b286cb9c910b417a7cc90820445c |
In this work, we assume that the pentaquark states are generated by the {{formula:c0720c81-c161-47dd-8fab-3349ba1de338}} , {{formula:c8866b4b-8b22-4374-8b6b-21be26840730}} and {{formula:a32308fe-e0b3-4736-affc-9acd04cd327a}} coupled channels, and neglect the {{formula:10e43bdd-39c7-4e74-8ba1-88c0025efbd6}} contribut... | r | d717298a23d36e8308b4dcec88b485e8 |
which satisfies the Karush–Kuhn–Tucker (KKT) conditions {{cite:0a17acc629e335532b68f8665eb581b5ead5bcc9}}.
| m | 120a106008a2417825423d0f8be556c5 |
Finally, let us briefly discuss the possible realization. This protocol mainly exploits the common linear optics, such as PBS, BS, BD, HWP. Meanwhile, this protocol require the multi-partite hyperentanglement. Such hyperentanglement was also realized in experiment {{cite:427b4ff7bb957f0092b6cd66b592341b871b33c7}}, whic... | d | 9df0c1c279a1f6f99f58d2c1c5e7afc0 |
Remark 3.12 The distance {{formula:6dadcf1d-c745-4ec4-acaf-5b15c2ece79a}} in Theorem REF is consistent with the result in {{cite:c0f12746b712cc1179f4908cc048222d4f852a00}}, where it is shown that the slow manifold {{formula:c30f6ec1-6ef5-46a7-aa98-8e63929efefe}} leaves a neighbourhood of a regular fold point at a Ha... | r | c1f31b7529eb9c64abffceae973fc123 |
The inclusion of electroweak radiation in parton showers opens up a rich field of showering phenomena, in particular at energies well above the electroweak scale.
Rather than considering specific sets of observables for specific processes, in this section we first consider radiation spectra of several particles at ener... | r | 8bc9ae7116b5bcbfca82a946480f1bf4 |
From our experiments and data collection, We have seen that Gatys et al.{{cite:98242ec94ba44a7593609c12bad8fd39bc2f2de8}} and Johnson et al.{{cite:3c7c2bea073fda2e8e6c1cbc80397d8bb21acf33}} both produce the best quality stylized images, but participants prefer Johnson et al.{{cite:3c7c2bea073fda2e8e6c1cbc80397d8bb21acf... | d | 078143a778a405fd5ca33498d4252378 |
Emerging non-volatile memory (NVM) technologies have been extensively studied, which is due to two reasons.
First, there is a gap of orders of magnitude between access latencies of SSD (e.g., 0.1-1 ms) and DRAM (e.g., 10-100 ns).
Thus, there has been continuous research on finding a new layer of memory hierarchy, e.g.,... | i | 22a7601aabd8b2acd3c99d182dfc27a0 |
In the present estimations, there is only one model parameter {{formula:35a48c59-893d-4508-a6b1-7c161c951a0c}} introduced by the form factor. As indicated in Ref. {{cite:24ef7cf7207167989dba48ff9b1474c85e237691}} the cutoff {{formula:24d8b14d-78c4-4890-bec5-38ff3dcc49ab}} in the form factor should not be far away fro... | r | cd8ef6cfd5dae4704536cdf45dd60a0c |
In fact, the calculation of the effective action using a chiral rotation involving the corresponding Jacobian, which is related to the anomaly,
is rather subtle—as clearly shown in Ref. {{cite:1c550e5fed5480c9741e2b78bef54d6fedfe0cbe}} for the case of a WSM. We find it illuminating to briefly describe the main steps of... | d | 5a7ef71b29bde6bcca432437e41a5132 |
All energies and matrix elements are calculated on coarse {{formula:53bfd882-9ac5-4b4a-9ac8-676c97e45d18}} and
{{formula:604e48f5-9d52-4009-a69a-e1901a431faf}} meshes using the DFT software JDFTx,{{cite:e010e49893315da47825c0c716087512fd1882e0}}
and are then interpolated to extremely fine meshes in a basis of maximal... | m | f3dbe25b7c71326f1d661d7e13797f74 |
Inspired by Zhang et al. {{cite:824332804ea9e3446d319720406dae0c33acae7b}}, we propose FloodTransformer to solve segmentation for the flood data domain. It is a fusion architecture of Visual Transformer {{cite:29144ed73b05b782387962742d3a8bf09f772d85}} and Convolution Neural Networks (CNNs) and its model architecture i... | m | d4f3ff003fd2efad70cd325a17c057b3 |
The quantification of fault slip is achieved using the Rate- and State-dependent Friction (RSF) model for friction evolution, which is considered the gold standard for modeling earthquake cycles on faults {{cite:6383044aa4e82a412ceb236cddff2ba94f0c5d6e}}, {{cite:02e68f9058805c56e8b82d43108b2b55ed020835}}, {{cite:e15229... | i | 3e5181aa0774ad47f1db5058f3991835 |
At large {{formula:2290db52-aa34-43e4-81ad-0503be175378}} , the generating function (REF ) localizes close to {{formula:04a8b120-d985-4722-8053-813812a7c808}} , and is therefore dominated by the bulk-channel OPE limit of the discontinuity. This fact puts on solid ground the result first obtained in section via the lig... | d | 547675e060121e9f5e818cd3187413fc |
In practice, Bayesian uncertainty estimates often
fail to capture the true data distribution due to intractability of Bayesian optimization {{cite:61f31fdebe4c37a60bbbd73ecd8dafa1dcfd9d90}}, {{cite:5f053a4b9cf5f27ef32b75b3c70a5e4a057e9bff}}. There exists a line of research exploring re-calibration of neural network mod... | m | 5a44e15c18a859d2cb26cdd95d293f41 |
Line-search methods are particularly appealing as they reduce the possibly high-dimensional optimization problem to a sequence of one-dimensional problems of finding good values for {{formula:dbae6e6b-4db8-4f14-a258-ab6b6aced95e}} . To ensure convergence, {{formula:5e81f8c2-b47a-40c8-97b5-d8c7fddc0713}} has to meet ce... | m | 5134210c729014c29a77a7f065d19e8d |
One of the major results of the present paper is the analysis of vanishing separation between the particle and the oscillating plate. We showed that the standard lubrication theory developed for modeling near-contact particle-particle or particle-wall interactions in steady Stokes flows {{cite:5e9816b3abb53cc0878fd94c7... | d | e1d32d22d06598ba2cbcc60e6adde9e5 |
For online learning problems with general convex losses, the optimal estimation rate depends on both the hypothesis space and loss function (e.g. whether it is Lipschitz or strongly convex). In this paper we did not establish theoretical guarantees for Sieve-SGD when applied to general convex loss, however, we gave som... | d | ab8c5684d55f6d9977755df0038c5d3e |
where {{formula:f4514947-990b-42e8-9ba7-c6071c0f3d67}} is the classic {{cite:dd877726d79b38406004c9623ecefad7f8ed35c1}} stress–energy tensor for electromagnetic field and where {{formula:2d4f540e-f94a-438b-9e51-51b195d011e4}} represents Minkowski metric tensor.
| r | bc3cba4e3da453a5bfe1f5e2cb3c51f1 |
Analogous to the electronic SSH model {{cite:107b5f92fa92bf7c8685698ad81d4c1b0d061819}}, as shown in Fig. REF (a), we construct a 1D FM SSH model including the intracellular and intercellular interactions, i.e. {{formula:17b6315f-edc6-4cf4-9530-dbcb88331026}} and {{formula:9626832b-c2c1-4658-bcc8-9c3e7fbd8395}} , whic... | m | 681fb328034b16f646fdd211e740c228 |
Although we considered networks with all-to-all connectivity within and between
populations, the governing equations were derived in the continuum limit. Thus the dynamics of large
but finite networks whose graphs have the same graphon (or graph limit) {{cite:8a9d99a2f008d2c32adc5185d993331674a1b628}} as
the networks s... | d | 441cd19aa227ad1ae1c21be33efaf2a6 |
In our daily life, recommender systems {{cite:a89e430053bba3ec9954f2a53df295bf048968e0}} play a vital role to suggest right products, right social media, preferable news or travel places to the target users in different sectors.
Using the knowledge of demographic information, past view history and previous purchasing h... | i | 2b7737ab113a3be8de85d745bd571764 |
In the present paper, the problem has been considered from this last viewpoint, assuming that the ultimate decay stages were amenable to the most abstract level of implementation in terms of probabilistic cellular automata {{cite:32376d83c1f4f43ea6bfeb9393ba90c60beb47cd}}, following {{cite:2c7d426152464f49bc920a942f056... | d | 885bec24710b218c318a19aa2a0bc42f |
{{formula:725511e7-fe49-4117-918a-fd823f949393}}Normalization: We normalize the base dataset into a unit sphere using the following steps {{cite:6ae9bff07ab653609eb906e918d13c1f0d2902c0}}. First, we calculate the center by computing the mean of point clouds for each model. Then, we find the point which has the maximum ... | r | 461569e9e354d22f3b7219a6de6518d5 |
{{cite:086c37cb7238c89dfd3d3c364c8f4b975bb25eb5}} fit X-ray observations with a single temperature model for the CGM and found that a small selection of observed fields fit to higher CGM temperatures around 0.4 or 0.7 keV. That work included a component at kT = 0.1 keV with free normalization for local SWCX and LHB emi... | d | c62094a87c76f0536035462dad833403 |
As described in Section , the response modes are of
particular interest because they sustain themselves by self gravity
and can affect or dress the response of our system at any
imposed nearby real frequency. For stable systems, the frequency of
these modes have a negative imaginary parts (damped). Most work on
stellar... | d | f6ef6a2c9a400ffaec4669eb9b4b9822 |
In the following parts of the paper, we will build on Theorem REF for decoupling Rademacher chaos.
We observe that the book {{cite:dfef9e87606066371f178a16c5b0af60c5793276}} provides some bounds on Rademacher chaos but only for the special case of {{formula:256ef8f2-b084-4b4c-b9d1-8a1fce6454d3}} .
| r | 01e12b9eef67ed6e1774348d215f50b8 |
Many classification approaches in machine learning explicitly or implicitly rely on some measure
of distance {{cite:46d329327960bde9d60129d6ccd0bf20b68093f4}}, {{cite:e2d2a8fe08ed395a80153baab089e3fe167f7fe7}}, {{cite:e08959b38c09d87d1bb971eebb233d19e6f989d3}}. This is particularly
apparent in case of the {{formula:3cc... | i | 4d270af5a92367787888c6f1cec005b4 |
Ablation study: We compare the performance of our approach using the benchmarked base CNN architectures such as ResNet-50 {{cite:4d652c687247cf16a22de6299f8b252ad038ec26}}, Inception-V3 {{cite:0ed027114b3332a81d77601bb66cf6441a727a0d}}, Xception {{cite:bb878f7b899295b75670f5097a6b5d6b0e85e037}} and DenseNet121 {{cite:d... | d | f7c1f81bf82df9aed7c626095ca98d64 |
where {{formula:0efe4df3-c7fe-4bd8-a1d5-74a26845bef6}} is the set of rotation, reflection, translation, and uniform scaling maps and their compositions {{cite:be0cc960ea9d276c53901c6bb697823560865d9c}}.
| i | 4201d634f1ac615b0ca9468fe7397618 |
Non-Volatile Memory (NVM) technologies such as Filamentary Oxide-based Resistive RAM (RRAM), Phase-Change Memory (PCM), and Spin-based Magnetic RAM (MRAM) enable low-voltage multilevel operations, making them suitable for implementing analog synaptic weight storage in neuromorphic systems {{cite:470c80d0206fffad0b68d57... | i | 664ff5a48f76e62ed4a9c2bdd7be2140 |
The study of quantum thermodynamic machines assists us to interpret the behavior of the thermodynamic quantities in the quantum realm like work, efficiency, heat due to the non-classical features that occur in the quantum regime such as entanglement, quantum superposition, squeezing {{cite:b3549bcca3f614d8fe05083a4e2c1... | i | afd4dea0671876bd1e16faf8abfe1bea |
We demonstrate the effectiveness of our proposed method on two benchmark datasets (CIFAR-10 and ImageNet) for the image classification task. Unlike previous NAS works {{cite:5ea6db0b1335645c37aa40151358779610df673a}}, {{cite:5996e918b6c4d9db2df621c1d3927e0636e932c8}} that first learn CNN blocks on CIFAR-10 under small-... | r | 6e83d71965fdf5baa4297d04481e5916 |
By Proposition REF , it suffices to consider the {{formula:e5b4bc96-bc92-4ec9-8d55-5088128d4b7b}} distribution. Let
{{formula:9f2937d8-205d-4c3e-9c9f-6dd94f61400a}} be its density function, i.e., {{formula:622117ef-703c-42cb-9f85-e7dccf3ae1d7}} as in (REF ).
Fix {{formula:49da6c01-d249-4e17-83e3-f151be03c627}} . To ... | r | 4e61e2521a99c534183512f486a55b04 |
A key feature of the mutual invasibility criterion is that coexistence is determined by the signs of invasion growth rates. For many classes of multispecies models, positive invasion growth rates of at least one missing species from each subcommunity is a necessary condition for permanence to persist under small struct... | i | d91fa279e735d0b04608cea80a004fb7 |
In our previous work, we have showed that ResUNet++ outperforms the SOTA UNet {{cite:bc6ae5747ab9bcb8247ed445e488cae0ac167687}} and ResUNet {{cite:84204fbe3bb617e03386072b93e77312fa80135a}} models trained on Kvasir-SEG and CVC-ClinicDB dataset{{cite:ba6765f6ec181067da79f60c43b4e6f324c9c6bb}}. In this work, we aim to im... | r | e3df6d49624c3c927902c42357724371 |
The advantage of all these representations lies in the fact that multiple Feynman parameter integrals are reduced
to much lower dimensional infinite sum representations, which are one–fold in the case of generalized
hypergeometric
functions, two–fold e.g. for Appell and Horn functions
{{cite:a172f8bd50be6ab893548b79097... | i | d772a115f2e5a1fa464ca357d4a1d2ec |
In existing literature, discussion on the choice of good landmark points that work for indefinite kernels has been scarce.
In {{cite:ab59a1f80b2edc8af8df167f51eddc487d97a7e2}}, {{cite:bf2880820b4b40b3a872eb2ac52eeecbf59c9cb7}}, uniform sampling {{cite:a3ac8532f1b355c1fd0a3e2e778cccb6167bdab4}} is used to select landmar... | m | fe2318e33b2363042d183c19d303be85 |
Existing literature has been focusing on extending network capacity to achieve state-of-the-art (SOTA) transcription accuracy.
This includes fully convolutional neural networks {{cite:11cb3e59c2d910926663ce3f491b4dc405b01af8}}, hybrid convolutional and recurrent neural networks {{cite:63a93cb530b57f793376bbae142921cf5e... | i | 8e4fba5839b0044611f9965960f7c132 |
A RFS is a random variable whose possible outcomes are sets with a finite number of unique elements. That means both the number of elements in the set and the elements themselves are random. Therefore, unlike random vectors, where both the number and the order of the elements are pre-fixed, RFS are invariant to the ord... | m | f77da90ead96427fbe9acf9e4a6b2158 |
We have treated the problem of table structure extraction as an object detection problem by employing the well-known Mask R-CNN model.
We have implemented a novel anchor optimization technique in a region-based convolutional neural network that produces faster network convergence.
We have introduced a simple and eff... | i | 0fdd044795fb11e901055d0557bf0846 |
NSLSs are still slower than iterative methods, but they enjoy a better utilization of GPU resources and a higher degree of parallelization, as can be seen from the comparison with the pure PyTorch implementation of conjugate gradient.
Moreover, the implementation of NSLS in deep learning frameworks like PyTorch {{cite:... | m | 87f18169bd1207748f8df64a37f51f70 |
{{formula:830142d2-54e2-4eed-a1d1-7a360484f498}} for metric spaces with doubling dimension {{formula:da5b341a-3a63-4a79-b5ab-060a85f8b65a}} . This improves over the {{formula:bbf08c94-ce28-4626-afe5-86c5bc1adfae}} from {{cite:263e18c86833d703ab4216a79c01206f5c81e18f}}. See cor:coreset-doubling.
Since general discre... | r | b65a81b508ea23f71b453762603f91d1 |
paragraph4
.5em plus1ex minus.2ex-.5emDomain Shift. Sec. REF briefly discusses the role of population statistics
in domain shift.
The idea of recomputing population statistics on target domain
is first proposed as “Adaptive BatchNorm” {{cite:39bc2cdede5ae9f1a056f534b3a7c1710991e0e8}}.
This is followed by other works t... | d | 89fd8501f741b364f566f9e3e7000f3c |
Furthermore, there are approaches to use the closure principle to control other error rates than FWER, such as false discovery proportion tail probabilities {{cite:6c7b4a4172a6d9a155dbe61f30abb8db35becf22}}. There also exist connections between FDR and closed testing. In {{cite:b85732ea909fe379be354c1b7e2c4f0904e98b5b}... | d | a0bb153cd0f711a3688ba01131f3a73e |
However, when using MC simulation, in some cases, it requires to consume extensive computing resource to generate converged set of equilibrium data. For examples, near the phase transition where critical slowing down occurs and thermal fluctuation diverges, or when we do quantum MC simulation, a longer time is also req... | i | 6cc363c72f21c8d567c7c41c3328ec8c |
Recent advances in machine learning, such as self-supervised learning approaches, have provided powerful techniques to extract semantic information from complex datasets {{cite:ed90c9e6691922abe340e8301aba87ed5bef13a8}}.
Here, we mainly took inspiration from self-supervised generative models combining autoencoder and a... | d | 38c1ffcd1dcb8839d67ee424b54cdc45 |
All of the Tait conjectures hold.
In {{cite:34ef81863f08a10678bb956ca3c784349a748776}}, W. Menasco and M. B. Thistlethwaite prove the third Tait conjecture, called the Tait flyping conjecture.
The second Tait conjecture follows from the third one.
The first Tait conjecture
was proved
by L. Kauffman, M. B. Thistlethwait... | d | e29125f5e3aab766d2e1836af3865e6f |
To cope with this, one can leverage the social information of users {{cite:e6e9618aaab676d9b8c24b5f7f67f647dbd39653}}, {{cite:8fec2943b235c6f89eae935c3477ea8d5c1b919c}}, {{cite:cfe9797e276f63850f5b5476354a5c3b9c5e595a}}, {{cite:c5c19c107a65a09596c2c1ddc20bf9b6ee7127fe}}.
In this way, we assume that users with social li... | i | 726bce4a110ca0863cb2478737a83743 |
Small systems coupled with heat baths evolve under stochastic dynamics. Their probabilistic description at all time can be understood using the master equation or the Fokker-Planck equation {{cite:abc1a5c00acb1e2b8249e5798f636574502d84b0}}. In this kind of systems, an increasing interest has been devoted in studying th... | i | 9624ade108a0a3887d54e1f005161d89 |
The subjective nature of the perceptual aspects evaluated must be taken into account for the evaluation and the mean opinion scores are indicative of preferences rather than absolute measures of quantity.
It can be observed that the perceived adherence to melody for the prototypical a cappella voice synthesized by the ... | r | 8d49f1ef570fe43ce7464396a9b1a08b |
Once CO is released, we find that its dynamics is different from that modelled in extrasolar systems so far (see Appendix ), i.e., the gas does not evolve viscously inwards as expected in massive disks {{cite:fc60aec3b488955633775ea99d50773255ecb828}}. It is due to two reasons. First the gas quantity we find in the KB ... | r | 6761fd89c0e76fad828df910b28535f2 |
Despite the dominance of FM double-exchange interaction, intra-chain AFM coupling is established along the {{formula:708c86ce-2d94-4bfe-8306-b994c13d6a2f}} axis double rutile chains. It has been suggested that the AFM coupling is due to a weak super-exchange coupling through the bond {{formula:cb0b7732-3efc-4ece-960f-5... | d | e005136ca11881f526116fe73f602587 |
The model architecture we study is an LSTM-based multi-task model for IC and NER tasks, where we use 300-dimension fastText word embeddings {{cite:b0f70c4792d483a662ad260d63c46bc281aff4ae}}, trained on a large voice assistant corpus.The text corpus contains data transcribed by an automatic speech recognition system. A ... | m | 566959ae1238b296e66f42a3c1306776 |
In this section, we introduce our scheme of Floquet engineering to
control the phase transitions in non-Hermitian quasicrystals, which is based
on the idea of realizing dynamical localization in Bose-Einstein condensates {{cite:f3880f5520ce1a9c4cfe12a50e5433837fde9b0f}}.
A schematic illustration of our system and appro... | m | 9c4cbd3bbd0bc61e0e3c02360fb77eeb |
Using the above as input, the two-photon annihilate corrections can
be calculated directly. We use the package FeynCalc {{cite:5e801ce0101b0a2442194eb0e0a9eed8251931ef}}
and LoopTools {{cite:144bc55988e82009bbdfb66a2a1c1121c4fb06ee}} to carry out the calculation. The IR
divergence in the {{formula:e5aac4cc-1f4e-4915-9d... | r | fe1cca22cb8ec14a9bed91d4af16820b |
In this work, we modify SimCLR {{cite:9c7c773109d20b5035f0f7df902e32dd2a780733}}, a state-of-the-art contrastive representation learning method, by explicitly adding information compression using the Conditional Entropy Bottleneck (CEB) {{cite:fee985c7ba4cdb951c5694d1d1973a8464e3cece}}.
Furthermore, we show how BYOL {{... | i | b589faf5a5fa2c16283bf90974c6832b |
As an extension of the MTP, Souza, Wilkens, and Martin {{cite:1e238bea5736555adf32f55f0a0100a77bf7efc7}}
introduced the so called gauge invariant cumulants, which are
essential in the study of
polarization {{cite:34be652b2810fe0909e75d2a3579f506d3369a05}}, {{cite:15f95f280a57d71321e71164e3e64a83fa239455}}, {{cite:697fa... | i | 0e0bdbda1188fd857373feadd33ce5ea |
In this section, we compare CIRCLE with 12 multi-view representation learning or clustering baselines, including Deep Canonical Correlation Analysis (DCCA) {{cite:fa763e3aee19993279df3eed2641f92886e141d0}}, Deep Canonical Correlation Analysis Autoencoder (DCCAE) {{cite:a01a1758d294b8896d7067e437a23c952b5311cb}}, Multiv... | m | b072a98da7a32b66e8d2b506393205b8 |
In the near Maxwellian framework, global existence and large-time behavior of solutions to the spatially inhomogeneous equations is proved in {{cite:e347129ba2db78931d64dd7995a932a65c815a1b}}, {{cite:bb79188f18eec2da011cabb498eee6c8c4bb22c2}}, {{cite:99e8e94c56a07481c470b9c6e5db547bfb27aa21}}, {{cite:826cfe3536ee4b9f44... | r | e8c14e87b169b79d8bd1b4176703adec |
The approach of modelling a sentence pair based on neural networks usually consist of two steps. First, a sentence encoder transforms each sentence into a vector representation. Second, a classifier receives two sentence representations as features to make the classification. The sentence encoder can be regarded as a s... | i | b6f2813315f00925fc65ac47f4e6d24d |
The results in Table REF demonstrate how model complexity may be offloaded from the internal model structure to the input features. In black box models, the relationships between inputs are generally represented by complex data structures (tree ensembles in random forests, hidden layer node interconnections in neural ... | r | 4124fc156eeb922d94d4d1d0d0a505ae |
We follow the classical routine {{cite:788094017ddba9ca130caf1d21c6dcd41e26e72c}} to define the generalization error of QGLMs as follows. When either the kernel or the target distribution {{formula:6c1dfd31-154b-4298-9d21-faf00a84fc4b}} is classical, the generalization error of QGLMs yields
{{formula:635e0f77-7f53-4e9... | r | c7ecec048f648dc891bbd58bf62b12bd |
Comparison with Image-Based Methods.
In Table REF , we compare our FastMETRO with the image-based methods for 3D human mesh reconstruction on 3DPW {{cite:fa2a86215ad15975d777cb85c7b313548aa38de8}} and Human3.6M {{cite:3c2bca5dfb4dbdae667924277691f89e7016b403}}.
Note that existing methods are implemented with
ResNet-50 ... | r | b3263cfea885a022c540f0e1a85dadc9 |
As discussed earlier, the theory developed to describe such effects is quite general, as it is applicable to any Kerr nonlinear oscillator coupled to one or more continuua with frequency-dependent couplings. The consideration of Kerr nonlinearity is not so restrictive: many systems in nature with self-interactions are ... | d | a18880359919dc70fe9d2e315df0fcc3 |
We first solve the model by performing calculations in an armchair-edged sample with the width {{formula:027d0563-f063-437b-b74f-fe960141e3b9}} . Two terminals L and R are
assumed to be semi-infinite. A relatively-short scattering region with the length {{formula:11f9b818-0447-4d11-af2d-d8de0164d6e0}}
is fixed, and th... | r | 09e6f9f042998756dbe439c80d859b03 |
As shown in Table REF , we compare all methods appeared in the main paper, including WAGE {{cite:ad38b89c958c5f63949fff71824305fb0b6e4654}}, LQ-Net {{cite:577e5fa933edfc4e211572454e40fbcf65f5d7fe}}, PACT{{cite:0614a961ad197bb3e852f4cfdb023b547b4ca302}}, RQ {{cite:677307753707d5c46b8473f750656283dde3df5e}}, UNIQ {{cite:... | m | fbec1d3f1c9558d75ea6b17ec7ff6e86 |
In the next section we first review the construction of the operators {{formula:b996ca37-73ec-4246-be43-fb4a0455d48c}} {{cite:6c0f461a9cb1f18ef83d50f88de1c8573cf09438}}. In Section III we turn to the example of the Ising model, focusing on the massless critical case.
The massive non-critical case with only {{formula:1... | i | 9f5796229f473acedc4b79a9733a089e |
Significant research efforts have been made on interpretation techniques that explain deep neural network models on image data. While existing techniques are commonly partitioned into instance-level and model-level methods, considerable attention has been paid to instance-level explanations that explain the prediction ... | m | b60828415860e7b18aabdde73500ec5e |
The most natural direction for future research is to generalize to the non-realizable setting, where there is no perfect classifier from the hypothesis class. Here we may need to relax our requirement of computational efficiency, as the problem of learning a linear classifier in the non-realizable setting (also called ... | d | baa9c8fd46c34dc3168896777815aba2 |
Another source of uncertainty is introduced by parametrizing each momentum distribution by two variables, {{formula:1cb1ca81-d226-41f6-be85-e7fd3c7e0686}} and {{formula:db9ecc88-b0f7-4b0e-9117-bcd4f6dc01e3}} , only. This is of course perfectly justified for the electron sector. For the neutrino sector, the non-thermal... | d | 83141a1d20b12a1064e7cdeeb14f07c9 |
As already mentioned, the computation of the stochastic reduced-order model (REF ) is costly. The cost of the reduced-order model in the moment-mean has complexity identical to classical deterministic model reduction methods and various state-of-the-art algorithms could be used to decrease the cost further. In fact, no... | d | ea0e661a27d5d535d6797044a09a901d |
By Noether's Normalization Lemma (see {{cite:acdf0acb1960a38d12e25512c4880acc4a6d3aed}}, §13, Theorem {{formula:1cc669b3-bed0-41a8-9dae-f56666e4cb45}} ), {{formula:e28d2ff2-86be-49ca-989a-1e535c7dd6dd}} is isomorphic as a {{formula:ff372e62-0e5e-4803-8639-6a981a0ef5ad}} -algebra to {{formula:aae0a42f-26d2-4c05-a023-6b... | r | 3233e0c1bd72aad9b2af05e326309dad |
In terms of analyzing biological data, our results demonstrate that we should not conclude any degree of functional modularity simply by observing a moderate degree of structural modularity. This potentially poses problems for approaches such as connectomics {{cite:74c458899e064034f722da119217b63cbcfcaa42}}, which assu... | d | 847ae7ad2b72c7cabf0ccd0a3bc7db66 |
Both player 2's objective in (REF ) and (REF ) are equivalent because the operation performed is monotone, and (REF ) remains convex in {{formula:fccbc7be-92a2-478c-a61b-da21fd1b4167}} {{cite:18774e28901377ef432bcddc431669f86f50f346}}.
Even though we enforced that {{formula:452946e5-6343-4936-a70a-5ef38de2b870}} in t... | m | e9071cdbc1c06c92768d0f61290e62cc |
The main difference between the semi-classical and autonomous master equations (Eqs. (REF ) and (REF )) concerns the emergence of a transient character in the semi-classical framework. This is manifested by an explicit time-dependence in the kinetic and eigenoperators.
The different temporal behaviour replaces the fixe... | d | 0331b32560d77cb3962ea00d6ba08b88 |
The results above confirm, that we have experimentally verified the canonical commutation relation by weak measurement of the path-qubit observable in a neutron interferometer.
Accordingly, from the quantum foundational perspective, our experiment thus provides a genuine direct test of one of the fundamental tenets of ... | d | efb162ea8a8baea2c2df1636cd770454 |
Although the study on the dynamics in the presence of an electromagnetic field is an old issue but due to the following facts it may be still an important issue in the recent technology. The investigation on the ion conducting electrolytic materials is a key area in physics and chemistry {{cite:e18e8ea96c43ba4dfa5d3eda... | i | d0ebf326d9ade6a75d8fa4aef7710312 |
Before concluding this paper, we would like to emphasize the following points: First, the technique of simulating isothermal processes with adiabatic processes
and isochoric processes are important to our proof, which enables us to establish the connection between large time limit and large N limit.
Second, the calcula... | d | d96e44a46b1429f308d3d8d9a4247389 |
Recalling Theorem 8.2.1 in {{cite:065cdc1ae74d9a619240b9bf4f5a41575dcfa42b}}, and Theorem 1 in {{cite:cdd87764d3b46fb650f92245eeff42ad8a330f18}}, we have that
| r | a21061e836b966f5a442f6bcb02079f5 |
In this section, we report the results of our proposed active learning methods, NDS and NDS+, in comparison to random selection, minimum margin {{cite:9edb7fd1a93dd04c0e50f564d10a84ea9222f7be}}, and Bayesian AL with variation ratio acquisition function {{cite:0b891a262844323c95866385d0b5c3bff5a8a921}}.
| r | 289fa400e134479030f89d93eb619517 |
We report the results of our model and compare these results with the results obtained using the approaches described in {{cite:b6a1a5324e584a589cc1faa690ecb6f91ec5f8ac}}, {{cite:cc6d3249f530e0b16bf725dc90752cd026ecb428}}.
We show that when the input is a very low resolution image, where most of the information is miss... | r | 7db9ea496d84d3ba9a901450c81298ee |
The next lemma is the analogue of Lemma 5.7.22 of {{cite:b27d91d5b59172726f0365ee10b0cb5f597c5017}}.
| r | b83c9c6f71e272eeba89bd4553cc8f7a |
Since introduced in {{cite:817e899c9e1cc74487ac43b710a0ae73da0f9787}}, {{cite:d5717034075ce554fd219bd82e385f65d29b126b}}, {{cite:0845e163d085172b455b40c2cbe4c31e1b494018}}, the idea of plug-and-play has received great attention for its flexibility and effectiveness to solve a wide range of inverse imaging problems. In ... | m | 39218b3fcebda27839e46b862dc6519f |
where {{formula:33ac5e6b-1b7c-490a-aa9f-89bccbc19793}} is the Hadamard product as described in {{cite:824332804ea9e3446d319720406dae0c33acae7b}}.
| m | 13dfbbc2336bebe4bb66b90ef720ccc8 |
In contrast to some other studies (e.g., {{cite:a854fbf0da8bc8ffb20de156e83619ea2dcc90cc}}, {{cite:64bf78600ccbae57ae241a840f83ad9ce2b9c976}}), we do not find any evidence for a concentration of satellites near the pericentres of their orbits, nor for a strong tangential anisotropy of their velocities. We stress that t... | d | 222685cdd2c3ce6f11e730ef0d0c3f6a |
In this regard, we observe that without modifying {{formula:eabdc408-956e-4043-8be2-473897a43152}} , which is in agreement with realistic performances in such fibre-coupled ridge waveguides, our results could be straightforwardly enhanced by simply replacing our balanced photodetection with one with higher efficiency. ... | r | 806aea4b7981e89a7e262be9036f1f62 |
The NA64 experiment in the "visible mode" configuration, i.e. configured for searches for dark matter particles, such as dark photons A'
or {{formula:6c4127ea-c1b0-4163-b16d-e306d2abc8c5}} particles, decaying visibly, into {{formula:177eeeed-bbeb-43ad-b64e-ef0ac0ad4493}} pairs, is described in Refs. {{cite:5b8800950b... | m | d7f868d1d76d0bcb08f466e03c355cd2 |
Comparisons with supervised pre-training. In the original ViT paper {{cite:aa9a21fdd6868296cede97d8e26669e20b47502b}}, ViT-L degrades when trained in IN1K. Our implementation of supervised training (see REF ) works better, but accuracy saturates. See Figure REF .
| r | c83f0ec2cce7bf7d87a7834d9a711f20 |
We also find the ranges of the individual parameters allowed
at different confidence levels from the analysis of the observational data. To obtain this,
we find the variation of {{formula:6a4d9f59-6854-49bb-acc3-2b884ee5f32f}} with each of the parameters of the set
{{{formula:42d94a3c-91dd-4cfb-ad1c-ec93f5e441e5}} , {... | r | ce0e78c164ae1a130e3cdbc540053316 |
Generative Adversarial Networks GANs {{cite:a4e973807b6817f296507047bb31b9d5fc0cbc7d}} have shown to be extremely powerful at generating images and sequences {{cite:41e8434747b6174397a1012e7ba60aed7f297bf1}}, {{cite:5c75ee544edd48450c5e00cd6f2822f66107494b}}, {{cite:6a37dc6d98fb6d21e50437f786f6f7386c090a19}}, {{cite:af... | d | 9268b31ea50ce93b452ed21aea24f454 |
Groups of isometries of finite dimensional hyperbolic spaces have been studied by a number of mathematicians. To name a few Anderson {{cite:94270a1c3e807e1f4cc603819444d397dd5faff7}}, Chen and Greenberg {{cite:cc6c66c43b98e060f0d94ab339856dcb1ad6be31}}, Parker {{cite:f7efc845f9b285a3d97bd8dd72088199af762d95}}. Hyperbol... | i | 14174da503a0cff2cc8ae98cd980b5f1 |
To (ii) integrate the estimated confidence into self-training, inspired by the single-teacher-single-student update {{cite:762c388cc85babd1e482a4b58d7af0afc29136c0}}, {{cite:8e8f9afe9b61130f0258f41760a3c6fdbc7d1c53}}, we develop mutual training with self-training based on consistency training for a training network (st... | i | 39cd2cf3604c45994f1572592f91904e |
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