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As mentioned in Sec. , the aim of this work is to cover
a wider range in the parameter space than was done in
{{cite:4a83782bfbf13a960e8d2b10a073a107678aa459}}. We group our models according to the initial
shell magnetization, {{formula:619ae137-ef5e-48c0-8bd5-d938d20c9a8d}} .
We denote by letters S, M and W the follow... | r | e9329bfc325675e6bd19c307e803fec2 |
limitations and future works. Noticeable limitations are discussed as follows. DKD could not outperform state-of-the-art feature-based methods (, ReviewKD {{cite:fb1aa00dad27d60f36e63e5dc1632e8980f77365}}) on object detection tasks because logits-based methods cannot transfer knowledge about localization. Besides, we h... | d | ed05c30f84c3e4a41685384577bd8f8b |
The FSGM {{cite:250022a57b51fd001e12298c3e49e8e3d1fc6a24}} is different from the proposed adversarial weight perturbation in (REF ) in two aspects.
First, FSGM is applied to create an imperceivable perturbation on the samples instead of the weights.
Second, FSGM only uses the sign of the gradient (times a scalar {{form... | m | 46c9de6d090c6eb75f8d960f9474a436 |
The primary challenge offered by the hybrid inflation paradigm towards building a microscopic model is the following: {{formula:00aa37c5-4321-4fd7-a002-e798476ca36b}} needs to be a light real scalar, but with sufficiently strong non-derivative coupling with the heavy {{formula:7864ef0e-f7be-44a0-be91-46c0b59d8d32}} f... | i | ffab9bcf708408fbb7dc3e4576e956d9 |
We consider an AL setup with the pool-based acquisition as commonly studied in the literature {{cite:c457dd49a1bcac6cdceea7a3440f23b57c6ab512}}, {{cite:1ccd58a947b122c450093460997f1485d98fa338}}. Let {{formula:fc087d9a-6936-404d-9ea3-50978c9db98e}} be {{formula:d69a6e3b-325e-4529-9eb7-d8e397a06e7c}} -dimensional speec... | m | 7a7c4997e99d94f2f7f3793969f9a0aa |
We show per-scene metrics in Tables REF and REF . Additionally, we highly encourage readers to visit our project webpage, which contains image comparisons for every scene, video comparisons for a select few scenes, and brief qualitative comparisons to NeX {{cite:54279364f8db100d901cec5a406f993216f6e59e}} on scenes fro... | r | c11917be27c21ecc1619c524521e1b9e |
It is universally acknowledged that magnetic turbulence properties is extremely difficult to measure in astrophysical environments. For instance, the effect of using traditional Faraday rotation of polarized synchrotron emission is a significant impediment for studying emission of atomic hydrogen at high redshifts (Cho... | i | ca87231d985bf637518dc5b23e4ead71 |
Another intuitive motivation for using {{formula:2121912e-6c84-4a5b-b2e8-2ea185acad46}} as the test function is that the minimax loss Eq. (REF ) for optimizing {{formula:c0d7fdef-da32-437c-a8e0-ec555eafc218}} is based on a saddle-point optimization, and {{formula:0beaee5a-bad3-4b7f-b643-a44d3bdaac56}} is the dual va... | d | 65a941b8a072251bf373caeb40f6fada |
Current VC systems embrace the technological advancements from statistical modeling to deep learning and have made a major shift on how the pipeline develops {{cite:8606013297c6c7f3a235b90c7fd5a24e5a59cd5f}}. For example, the conventional VC approaches with parallel training data utilize a conversion module to map sour... | i | 0680d7242bd049f63f65428cd485e83f |
Fortunately, there are a few robust indirect methods that make it possible to constrain the {{formula:145da2d3-8319-4edf-85b2-a9dc7649f48d}} beyond the range of applicability of the direct dynamical ones. For example, the tight correlation between {{formula:3f463293-e0c1-464d-9891-aa2b33336fc9}} and the stellar veloc... | d | 3b68a56e5213d66241377e24bc8ab5d7 |
The CAMELYON16 challenge {{cite:d84d1a2364237c6fdd102d1ef0b29759058d5362}} is the best demonstration of using deep learning for automatic tissue analysis, outperforming the pathologists in terms of detection of tumors within the whole slide images (WSIs). The objective of this challenge was to automatically detect the ... | i | 6e0ae67472af284bf55d77bd496153f1 |
The intrinsic sparsity of local updates can be leveraged to relieve the bandwidth limitation and improve the learning efficiency of FEEL. This is motivated by the observation that the number of significant elements in a model update is extremely small. Specifically, {{cite:bded48787e98e242f8ddd91fc6d41a698d77bdbf}} pro... | i | 4515fcb963bb8bd4a7f0320ac9848a6a |
Our model ignores the convective cellular flow in the metabolite diffusion equation REF . For this approximation to be valid, one requires that {{formula:f9c503a3-d17b-4202-bfac-bad0847c0cc8}} be larger than the amplitude {{formula:70bcc75c-31c4-48fd-82f8-269ab9f4565a}} of the cellular flow within the aggregate. Figu... | r | e1ea1a73946cc3a40d39f15334dafae9 |
In addition to the simulated environment, we tested our planner on an indoor environment from the Gibson suite {{cite:5053046b7c8cf585108cc20bd6b6f77e90706605}}. Fig. REF (left) shows the trajectory generated by the RRT* and CCGP-MP* (5%) for a single start and goal pair. Fig. REF (right) shows the minimum distance t... | r | 9ef3a450def01639761a780415b88672 |
The first ever experiment that has shown that quantum physics is affected by gravity is the
Collela–Overhauser–Werner experiment {{cite:8a33bc24f68328d3c61e8afba7cf814be1515d40}}. The observed
interference pattern produced via overlapping two beams of thermal neutrons, propagating
at different altitudes with respect to... | d | 20004160aaae69a0b7ec96b12f3ea175 |
where {{formula:265102da-d2a3-4a2e-8a6c-f23536145945}} .
We stress that in contrast to the non-linear Young integral used for example in {{cite:bf9e45270610787e2a6f3f9da600582e522ada9f}}, {{cite:506d73381ccd0b5bcb782958e118ef8d816bd112}}, {{cite:b813d652939f62b3c78730ed51c4f865f12619eb}}, {{cite:25206b3d5a6bf3bf252a08a... | m | bf6c087e29d14334ab8f5d94819d6b86 |
Compared to supervised adversarial training {{cite:8f21863e530beebe732a366d12517f82ee36b181}}, {{cite:5a5e4b7bb0d2fad2773cb7a9fbfcd5af4e68b37e}} our approach has the key conceptual difference of being applied in feature space. As well as improved computation efficiency (no PGD attacks required) Fig. REF shows that thi... | d | 7b6f87f6ecf53840237af639b3758bdc |
However, achieving robust visual SLAM under low visibility still remains
challenging. For typical cameras that collect information by integrating photons
during the exposure time, the captured image is concentrated on the lighting more than the object.
Thus, the ideas of collecting information from visual domains other... | i | ac81cba9cb4be042ca292e1dc8ceaec4 |
where {{formula:8d24354d-6dbe-4924-924c-583807ee7b46}} is a constant with {{formula:4b7899c6-dbb2-4ef5-a494-92f709a7d638}} yields the least modification of the Schwarzschild black hole spacetime and encompasses it when {{formula:8baeb643-ffff-40cc-a6a6-6668120b203a}} . The parameter {{formula:3657ab82-c248-41e0-99c2-... | i | 57682d7ba6ba48140664966d6c1b7e61 |
Implementation of the DEM {{cite:133a85e0eb6ea171da22b2e77a16de46afccacd4}} for multi-block structured curvilinear grids.
Modification in HLLC {{cite:3a051afd9b510680b709c6a514b307ff871137e8}} Riemann solver within the DEM to include surface tension.
Extension of viscous effects within the DEM {{cite:952f6f379ec9386... | m | 99d3eddfb4afa6a91a01ede418ce8f86 |
At this point, we contrast DeepOnets with other recently proposed frameworks for operator learning. In particular, we focus on a recent paper {{cite:3bc89e83745f0e2837cf303887113c2a9fba8722}}, where the authors present an operator learning framework based on a principal component analysis (PCA) autoencoder for both the... | d | f1bea9a01bbe1242a9289fb5c978877a |
In Table REF , we provide additional results of AGKD-BML model trained on 10-step attacks against AutoAttack (AA) {{cite:8805d96942d98b09b4bd04a8c801c0cbfd323d2f}} which is an ensemble of four diverse attacks. We compare two Wide ResNet {{cite:ce91440a3285390adc87c7d55f7d588d148f2961}} structures, , WRN-28-10 and WRN-3... | r | 90379d830b14443d1c6819f5bfa1c134 |
To alleviate the labelling effort required to train FCN, AL methods have been widely used to optimise the collection of training data. In AL, the aim is to selectively label data in order to maximise model performance. Recently, several studies have proposed AL frameworks for deep learning models with image data {{cite... | i | 76ea10eb6002bdf41ce9dc8732a17aad |
Our experiments show that Elodi performs positive congruent training by reducing negative flips with large logit displacement and reducing the variance of logits from the ensemble estimates. But there could still be negative flip samples with small logit displacement.
As discussed in sec:probe:landscape and observed i... | d | c4416cf9b137b21cc849c7f4b7549c8c |
Most algorithms for SAT and MaxSAT are based on the
branch-and-bound process {{cite:411f49625435bb9c0a153b3082810609853e7c81}}. The Strong Exponential Time
Hypothesis conjectures that SAT cannot be solved in time
{{formula:5dd1be8f-03e9-43a8-8f2d-c5e590500ae6}} for any constant {{formula:e336c5ba-1f4d-4d65-89d9-0532b3... | i | f42da6674f9d044a6e0af62f4a517d04 |
Fig. REF d shows the CERs and style opinion scores for unseen style references.
Due to the residual information in the hidden state, priming significantly increases the CERs for {{cite:bc469f3bf3ce448bfd3aee0ea18c74c3c4b8fdcd}}. Without style equalization, the model fails to synthesize legible handwriting in the nonpa... | r | df33a18bd959ff2488b9bfbf14ab749a |
We have established a variational formulation for the role of depth in random neural networks with batch normalization: The entropy of hidden representations increases with depth up to constants. Is this entropy increase achieved by a gradient flow in the space of probability measures? This question is inspired by the ... | d | fc3d941f0245e14449bb872e1abc837c |
Limitation of SESEMI We speculate the poor performance of SESEMI on the SVHN dataset stems from our chosen self-supervised task of predicting image rotations and flips. Gidaris et al. (2018) {{cite:3a68613d510173dce937fe18b1421be59d531e73}} showed that their self-supervised model focused its attention maps on salient... | d | cd96b9df9d351555a88b03f6a8e33e92 |
where the first term tends to zero since {{formula:472489f9-3489-4fce-a4fa-0c4790f18dda}}
and {{formula:e1f11855-1dee-4a0f-8abf-a405cfeea54e}} is continuous and constant on {{formula:87392d7d-2da4-4380-b2aa-938f79ef8c93}} , satisfying the conditions of the adapted Portmanteau Lemma {{cite:bcf726f46ab9d135030f718cb79... | r | ca09607077da7df3b67e954d8eb81946 |
Although, the blazar types optical variability is rarely expected in non-jetted AGNs or misaligned AGNs {{cite:9446e73a4eaa890da0db47eb8c378313cae84cf4}}, {{cite:682bf865678942600bb15a7c16e3bff686445f7a}}. But, in the present study, we have been found the unexpected remarkable sharp feature in the differential light cu... | r | 0815db31f951a6d4ceb45fb964c47983 |
{{cite:7358c48abcbf794d4bcaeda0786fb8ba80cee64a}} revised some of the experiments from {{cite:51c99c2bdc285082d06065ab8ad4cee642b901b5}} on pruning larger networks while training on ImageNet. This domain usually requires a more exhaustive hyper-parameter search to discover WLTs, but when discovered the results tend to ... | d | 35f9fcfb251faf3e19fbe58b4ae4e8dd |
Qualitative: Some retrieval results are shown in Figure REF for Sketchy-Extended and QuickDraw-Extended. We also provide a qualitative comparison with CVAE proposed by Yelamarthi et al. {{cite:f4f7946e9de8522d692b4435cb1bf00f3080c83c}}. The qualitative results reinforce that the combination of semantic, domain and tri... | d | a6b74620ee1c94e6e9303342386e7313 |
One such scheme is the minimal momentum subtraction ({{formula:8085f233-50a2-4165-b04e-94b3347a7118}} ) scheme that was
introduced in {{cite:f88efab1c0334c53eebea0b77376c8dd227e151e}} to exploit and extend a particular fundamental
property of QCD that was originally observed by Taylor in {{cite:fac13304414aecb0d107ce60... | i | 8e69817519e6473e70175cb2a437ff7d |
As illustrated in Fig. REF A, the observability of the {{formula:33b9b137-bf7d-4375-8f96-cedfd9a8320a}} spin alignment is a result of the interference of two wave functions from two indistinguishable target and projectile nuclei at the distance of an impact parameter apart from each other. This scheme is very differen... | d | c98f65dc86537bc3b7341f66a7bbaaaf |
Primordial black holes (PBHs) are early universe objects predicted by lots of inflation models; they could result from large overdensities collapse {{cite:730497fafbab966f415a53280530aa4e825ad446}} as well as more exotic events such as phase transitions or topological defect collapse (see the reviews {{cite:971510f2575... | i | 8c84d257c09952f20c4caf0a73f1565d |
The present version of the GM model considers a population of an
infinite number of informed traders who behave in a competitive
fashion. The situation is very different from that of a single
informed trader, who trades with frequency {{formula:13f47c59-af5a-4713-adae-99aeda73f506}} . In the latter case,
the GM model b... | d | 4ed74ec305d828d44858320997a809aa |
It remains to show the continuous dependence of {{formula:99d25ec7-691c-49fb-bb3f-2d6fdc4d3c3a}} in {{formula:68650a66-513d-4cf0-8abe-4169ef4aad7e}} . Let {{formula:8b9e1b5d-8453-4108-9096-1d47b0b85233}} be such that {{formula:ab30fbef-2dd3-4d39-abbc-61a99f990398}} uniformly on compact sets of {{formula:422cf134-ef9... | r | 92855300149988598452abf1840e5c2d |
We observe
{{formula:e383074f-a48a-49bc-a0ad-224aaebf2c84}}
The first inclusion is trivial. The second inclusion can be seen as follows. Let {{formula:f9d87ef8-dd63-44d1-bd97-c94086ab5f53}} . Then for all {{formula:c9d39866-a06e-4658-9ab2-972553f02c55}} , {{formula:1f116bc3-a87f-4cc8-be97-6e8b723c7552}} and {{formula... | r | 736c2297d5ba0ad3a1a6e94641a3ef83 |
Most of our experiments are made on single U-Net networks, but modern approaches such as conditional generative adversarial networks (GANs) are likely to yield better performance. pix2pix also uses a U-Net as the generator, but the loss function is replaced with a dedicated “PatchGAN" discriminator network {{cite:6842a... | d | 24b2f5d061afe6d74570eac712ad6029 |
Other Architectures and Tasks.
We tested *OccamNets implemented with CNNs; however, they may provide significant benefits to other neural network architectures as well. The ability to exit dynamically could be used with transformers, graph neural networks, and feed-forward networks more generally. There is some evidenc... | d | bd97f074d653799553d83fa190f68770 |
The initial step towards extending FP to real-world games was by {{cite:28ed0f0f5215dc72586af4109f9a21289d22c769}}, which established the equivalence of normal-form games (represented by matrices) and extensive-form games (represented by trees with additional structure). Loosely speaking, this means that results which ... | i | a6317e519e282eae7c0506df32682dec |
For a star that will end up as a PPISN, electron–positron pairs will be
generated when the central temperature of the massive helium core rises to {{formula:6529e4b8-37d9-4fe0-99ab-3eb7e81e416c}} {{cite:4c4cf95eaeba888cc7b2524cb0480cd082813c36}}, {{cite:5a72dd640feec71f32d0f08b7a637217c9b8c4a8}}, {{cite:d3137f71ba1a40... | d | 2ba35167f8bdc1de385f888b09180e7a |
Our work focuses on leveraging synthetically generated data through the use of modern 3D generated computer graphics using a couple of novel resources – Hypersim {{cite:2e53a8df2ae4472e775b4f757827e2263046d3ef}} and ThreeDWorld {{cite:4e93d9b63f131de083741a5d161d8fecb4740ea1}}.
In the past, leveraging synthetic data ha... | i | 331d8120183cb3b5c82a6f0f7971a6ba |
One of the biggest challenges in processing point clouds is dealing with unstructured point cloud data. The early methods of processing point clouds are mostly indirect representation conversion. Some methods try to convert the point cloud to structured data, such as octree and kd-tree {{cite:083941d57796463d7bea916691... | m | 94188365986b2c50ceaebd117e3ad072 |
which is counter-intuitive relative to most investors' notions of risk and reward {{cite:0d21526a1a6432f2910d10c5c6ece7c2cf8eb62d}}. {{cite:d454d0c4319e5179ace56a69501f57e734eff880}} extends {{cite:0d21526a1a6432f2910d10c5c6ece7c2cf8eb62d}} work and investigates high-frequency currency trading with neural networks trai... | m | 7d19cb9314c7e872a875a6ef11bb0b4d |
where {{formula:a2b2ad39-4676-4bf6-a9f6-d246b32e1bf3}} denotes the interpolation operator.
The choice of {{formula:7dee3198-63a7-4041-bb72-36536e4c400e}} is crucial for the accuracy and stability of the scheme {{cite:4e98da2405f3cbbc0b3f2d1d63e136514ba3d208}}, {{cite:96829cb01a129bf5c4c5407787c4aa8e3b6a3cfc}}, {{cite... | m | 5dbadb5d7adb8064cf8647c9541f1604 |
Federated Learning (FL) enables model training collaboratively in a decentralized manner without the need for data owners to hand over their data {{cite:9f91cc8cf509a26d751d378a5df546e561a71a98}}.
A typical FL pipeline consists of two main steps: (1) training a copy of the global model locally on the client's private d... | i | c4662c9023ea5bf42d41212ae149f053 |
In this paper, we presented an effective and efficient multi-task learning network after a thorough study on the previous approaches. We ran experiments on the challenging BDD100K dataset {{cite:cfdb4c29b2063ab43464facf293ddd1049bac17a}}. Our model achieved the best performance in all the three tasks: 0.83 MAP for obje... | i | 1b5637dc3722ffe50645a7d2482667cb |
Rounding the SDP solution is very challenging. The SDP objective has a mixture of XOR-type terms, requiring that the two vectors corresponding to the endpoints of an edge that is not in the current cut are opposite, and OR-type terms requiring that one of the endpoints of an edge in the current cut coincides with a spe... | r | 89ffaa7d870f962bcec5a0f3192cc701 |
Our proposed weak human preference supervision for deep RL allows humans to input dynamic and weak preference levels via our developed human preference scaling model to reflect human behaviour and decrease the number of human inputs for our established human-demonstration estimator.
Based on 5 experiments with the ro... | i | 6a40702768199598ad9425eedc348904 |
We analyzed the responses using the Wilcoxon signed-rank test {{cite:6fbd54c2e649f2e44db4d32b1ed8a195e4f9d014}} to compute a pairwise comparison of the categorical responses between the baseline and confidence score conditions.
Table REF summarizes these statistical results along with the Rosenthal correlation coeffic... | r | d7df571e53c3a15f3c2bd805b8a6aa60 |
The first term is the virtual logit in eq:vlogit while the second term is the energy score {{cite:7c3280066fc5a4e7f1fc1aef26cf818777b8dd05}}.
ViM completes the energy method by feeding extra residual information from features.
The performance is much superior to energy and residual.
| m | 6d29b48f121b8dd6b111033b7727fb6b |
We conclude that the overall properties of OGLE16aaa could be accounted for by the stellar tidal
disruption by a candidate SMBHB.
The delayed brightening in the X-ray emission as well as the multiple flux dips during the decay phase
are in agreement with a SMBHB model with a mass of {{formula:e1cf3712-1b07-48a4-aa50-5... | d | 1d15cc6ced05bd68ce705049ec211ee4 |
Before moving on, we note some previous results in this direction {{cite:c98c1df6b7ac6d72ce4cc8a6d021a632b8a93090}}, {{cite:b91c378818791413e8e3b0601fff56132a39ac1d}}. In particular, Belenchia et al. {{cite:c98c1df6b7ac6d72ce4cc8a6d021a632b8a93090}} study a gedankanexperiment in which Newtonian entanglement enables sup... | i | b50b710f64311bdaf1a09f3933ea3183 |
Experimental results on synthetic data and real-world data at different scales –namely, Telegram {{cite:61edb2b66e74bb31015c76f2849531c901057e7a}}, Blog {{cite:562a97786c89b480d4163fe2d7e16aed73fa8062}},
Migration {{cite:7b7f0fc73368d86951bc504da262088a2193a9a9}}, and
WikiTalk {{cite:6c46c48229728ba13b1dc7c0359df10de16... | i | b8ac2690357e58ed031836a0940898a4 |
Indirect detection experiments such as the Fermi Large Area Telescope (LAT) {{cite:6002bf0a9771ccb24d79142706cff1748e7f62f4}}, AMS {{cite:86ca7e585ddf541fdea3f5358c4b10456ba7cda7}} or IceCube {{cite:1edd8e074e1d9fc50390dd662ffe5c4e3a34d19d}} provide one the possible ways to detect WIMPs. Theoretically, WIMPs undergo ei... | i | 09727f92f498363c6fd468516e4335da |
We now present a mini-batch linear programming algorithm to find the best {{formula:79bbd86e-d5cf-4667-acbc-1b99a8589f88}} given {{formula:5f4efc67-fd9f-4d70-a504-d3e292ca9f25}} in (REF ). Notice that the problem (REF ) is a linear program on the bounded convex set {{formula:e6d45b04-7728-45dd-913c-aea25d9213e7}} of... | m | 478fee2935c1c4103de57bd22e2cdae2 |
While CNNs were originally developed to perform computer vision tasks, the grid data representation used by CNNs is flexible and can be used to process datasets arising in many different applications. For instance, in the field of chemistry, Hirohara et al. proposed a matrix representations of SMILES strings (which enc... | i | fb9c11e5d8fa7f7d79194eae40d9e115 |
The derived abundance for the different members of the C{{formula:9c82747a-3e86-41ce-b213-96fbd11f134f}} O ({{formula:18514ea0-10d5-4b62-945f-1da670343e37}} ) and HC{{formula:5dffca76-aa04-4d64-a87b-350001a2391a}} O
({{formula:19eaf07b-ef34-453b-92ed-6e8c3c6dc6de}} ) families permit one to study the possible routes for... | d | 11b9834748937be157950fa01637af2c |
The author thanks Joachim Stadel for many helpful discussions and the suggestion
to allow {{formula:408c9080-3543-48c7-8a57-8be25116997f}} , Alessia Gualandris for running sapporo
to provide the data for Fig. REF , and Simon Portegies Zwart and
Jeroen Bédorf for providing the timings for sapporo 2 in
Fig. REF . This wo... | d | 18b71a3ae89d71753507908fe072a9f3 |
Detailed performance comparison of the best single SR-ASV system and the challenge baseline ASV system across all spoofing attacks in the evaluation subsets are illustrated in Fig.REF and Fig.REF for the LA and PA partitions, respectively. Note that the results shown are all from single ASV systems. All the results o... | r | 17d7b4c3bb60aaff449a89ce631ae73a |
We have focused on static charged black holes, but Kerr black holes can also support massive scalar hair {{cite:efc0edd88ce3881f386672d76c1ce876e2e7742b}}, {{cite:e41c282237987fa4c96576d7a5bc371497eb388d}}, {{cite:e75b0e5c8f3895c73e77863436d9daf70fe9dc45}}, {{cite:c16bf68d3dabf2587b99b96f9d4a04747b27a9c2}}. In fact, th... | d | 26d6197230b00c52e1d804c437797f67 |
Recent experiments with optical tweezers and traps have verified several theoretical predictions of resetting {{cite:ce641f1d1dac401abedd3c98e2164b27089b1a51}}, {{cite:9d3c230490021718eee83e662ce90d2dc80af968}}. In future if multiple such traps can be used to create potential minima separated by barriers, and first pas... | d | 7404342442c4ce9c0041a7931f6237f7 |
Table REF shows the results on Office-Home dataset. This dataset is far more challenging than other datasets as domain shift is significantly high here. Despite the challenge, our method achieves a substantial improvement over the other methods across most of the tasks. TDMDA outperforms TAT{{cite:f334e3732862c1944a87... | r | e0d083f6515d21ea27bf0cb97a7b7775 |
It is well understood that the Hohenberg-Kohn density functional theory (DFT) is strictly limited to the ground state properties. Therefore, we study the optical properties using DFT and beyond approaches under the framework of many body perturbation theory, i.e. G{{formula:54fa697b-18bb-4b1c-b713-ca331265c980}} W{{for... | m | f006e6ec0045291dcacf698f7d50a869 |
It is known that quark models have achieved great success in studying the properties of hadrons, especially for these ground states. Within the quark models, it is commonly accepted that mesons are composed of quark and antiquark ({{formula:d464e03f-273a-432b-9068-8d5335ec65a9}} ) and baryons are composed of three quar... | i | 633967e5deb863a7903f39979b8cb2b9 |
For future studies, we will investigate the relation between the chiral phase transition and confinement-deconfinement phase transition, and figure out whether the stable holographic nuclear matter is in the quarkyonic phase. Currently, the EMD system and the KKSS action are solved separately, which means we use the “p... | d | 0698aae482964f503b61a49faeeb7d43 |
Analysis of non-reversible Markov chains is difficult, essentially because self-adjointness is lost. Without self-adjointness, it is much more difficult to connect spectral theory to mixing properties of chains. It seems that a good way of understanding benefits of non-reversible sampling is by studying Cesaro averages... | d | 518c9966b1f5166663aecbe3b2849633 |
Unlike relaxation methods, equivalent optimization methods replace the binary constraint with some equivalent forms, which are much easier to handle. For example, motivated by linear and spectral relaxations, Wu and Ghanem {{cite:dbef8eea27629c648eb5cfe44c2403662766fa0e}} replaced the binary constraint with the interse... | m | 6d0e9d5cd8241f6e0c1d1f3467bce975 |
To handle the real-world complex rainy images, the optimization-based methods are firstly proposed with hand-crafted priors such as the sparse coding {{cite:67f4ed5f8c6991307ac1a4e9bb68310d47138c46}}, low-rank {{cite:90cae83ae4de074c2eb4643d32207cea57be24d5}} and Gaussian mixture model {{cite:ea8648664525ee92bc289035eb... | i | ec6d26508f5362f1e28a48eedc035441 |
Firstly, there is an interesting phenomenon where the average reward nearly monotonically increases each epoch, but then there is a slight downward dip after roughly epoch 200, before the rewards start climbing upwards again. There are two possible reasons for this. The more interesting reason, is that it may be an ins... | r | 07fb5ecf7d1db47cabb606f0041b3aa0 |
The SC is a local model, i.e., each perturbation is assumed to evolve independently. It does not account for tidal forces which cause shear, rotation and accretion. It also ignores non-linear mode coupling, which is a non-local effect. Yet, it recovers the shape of the PDF given by perturbative methods and simulations ... | r | c76d27d2392ebc11c7c6fddc184d439e |
In this section, the proposed method is compared with unsupervised methods: SCAN {{cite:233ffd2ee8af3b07ecf142a1423a4e1a9a22a927}} and SimCLR {{cite:72338d7fce8f96cab497d2936b6fb64fb24420f6}},
few-shot methods: Prototype Net {{cite:cf98d655e8335111f7e981e477cf6020518cc7f2}} and Simple CNAPS {{cite:342ebadea3febea3d5745... | m | 297b91a59f7d044c6a94aefe57e8d04b |
In addition, we observed the lasing action of the TE mode from InGaAsP-NBs. From the SEM image in the top inset of Figure REF (a), the structural parameters were estimated as follows: {{formula:6e877d6a-bfa8-406f-be39-a50fdbd07cd8}} = 573 nm, {{formula:12056495-6de2-40cf-bfee-fe7159509e29}} = 0.343{{formula:cb11d637-... | d | 5f97ac993482322c9cf5b6ff3c86df7b |
The future large-scale spectroscopic galaxy surveys with high galaxy
sample densities make the angular clustering analysis possible with such a
narrow radial binning. For example, with the designed sensitivity,
the Euclid satellite can observe 50 million galaxies in the redshift range
{{formula:59768578-b7f0-4c08-bcdb-... | i | da811719bbd91ec0978bec32f749c52a |
Autonomous driving systems have the potential to vastly improve the quality and efficiency of existing transportation systems. With fast reaction times and socially optimal behaviors, automated vehicles (AVs) can improve the road capacity and traffic flow stability of existing networks {{cite:1af7d2b66cc7181a5e3749c4e5... | i | f546e4cb666d5976cdce52c718355256 |
To explore the relation between Xavier and rectifier nonlinearities, He et al. paper discusses an experiment where they experiment a 22 layered neural network and a 30 layered neural network. ReLU has been used as activation functions and Xavier initialization has been used as weight initializer in the experiment. The ... | d | a6b21f1297b9803f0a629fe67306cd7c |
where {{formula:c5b5a1c4-cd03-4d15-91e8-86ff0071d390}} is the binding energy determined by the two-body problem {{cite:b9913f6235c5686b49989d03608cab51a8bb7c7b}}, {{cite:bca84b881463b61fbb9420a3ba1043ff75e74e84}}, {{cite:f5c34d028b8c35a1dc448d66b61d38910c0bfb3f}},
{{formula:ba16091e-06d4-4cec-8cb4-b3461e4677ae}}
| r | 83346683cb4e83d00467f67e892c0e44 |
In the next claim we use SQ, RQ and PQ as in {{cite:3e043a19cd2d3d50cf8a8fdb84c9ff7eb8146119}}.
Thus SQ is the mean {{formula:1673a3f6-52dd-47a5-94cc-7b792d162040}} of the True Positives, RQ is the traditional F1 value and PQ is SQ times RQ.
| r | 5995ce2d37b30bceea8d5931d30423bf |
{{cite:6a893cab5aac6b98805bd237882a69f60f23cfa2}}
covered the same ground as DZ65, but more thoroughly, presenting an
analytic solution.
| d | cc2c8f2700bc432a9e251d4857a57c3b |
As a consequence of the evolution of propulsion technology and the desire to reduce the cost of ever more complex missions designs, trajectory optimization remains an active field of research. A significant amount of research has been devoted to designing low-thrust space trajectories using direct methods, indirect met... | i | dd8d48b46cdd455e41cc78033920526c |
PointNet {{cite:9ce6783cb6e17fac6f45d980bb9c54e5fb3771b7}} uses raw point cloud data as input without any emphasis on their ordering, while GAPNet {{cite:bbf0e99753d539f850c36e72bfa5a09bf6f8b9d4}} exploits local features by introducing GAPLayer, which assigns different attention weights on the neighborhood for each poi... | m | 8ca7e35cd480cbc3dfec41a040daefee |
where the differential operator {{formula:657515c7-4f70-439c-b9a7-b79dbfc7be78}} is defined by {{cite:6ab0bdeb04b071bb02c61af1da812233dc1eb92f}}
{{formula:662de3c9-129e-490a-ad50-b3b9b51596fa}}
| i | e827eb714934bd8a9571596df6adc421 |
For {{formula:20e297df-c056-44db-adc5-6bfb973f113e}} and {{formula:0fd337d2-444c-4096-9fd8-5b258b07dbf5}} , we get {{formula:b295c72a-6e2d-4ee6-bedf-7af4ebe05a15}} which agrees reasonably well with the Sturm-Liouville analytic result {{formula:8a4bfb85-5a00-4006-95b9-82f2d990f958}} in {{cite:62e3aff4f8768b1f5056b981... | m | ee564ca4dbe18218db83a35e1039ab1d |
The most standard approaches for finetuning pretrained models are linear probing and full finetuning (Section ). They have been used for supervised pretrained models {{cite:3d9c987c0f48ff252310fe26c119e3fc45de5417}}, {{cite:e2236f2bf1b55febb1c876a76cde7daedb13987b}}, {{cite:b6324e39fd79c47585949d63e3d2a7c0137a2b9b}}, s... | m | dba2825b626661d02c1659c202e45fcc |
Comparison with other generative approaches. Observe that for our denoising benchmarking in Figures REF and REF , the recent BDGAN approach is the only deep generative model. The reason is that except for BDGAN, neither for generative adversarial nets {{cite:a93729289182386b5ce3439fe5fdcf5ba55011f7}} nor for variation... | d | 1720e843ef4e6050612eff37a46eeaab |
To explore the possibility of a turbulent flow of the charged quasi-particles in a sample of graphene under realistic conditions we simulate the hydrodynamic equations of motion using an adaptation of the relativistic lattice Boltzmann method described by Romatschke, Mendoza and Succi {{cite:00195a56dba7ed91c18cb899249... | m | 640440da60a70179c9ce496c2ac46ac7 |
Given that real direct observations of the primordial GWs in far advanced detectors like ultimate DECIGO will become feasible within this century {{cite:ca5a94fd1a71e76fed5a87dc60b2f9c340e5ad71}},
an important and necessary step in the near future is that the next generation CMB experiments should find primordial B-mod... | d | 45421f877a708dd9954cd0ae16587746 |
Finally, before presenting and qualitatively assessing the results of the best configuration on real-world data, a short quantitative summary and comparison to the results produced by offline *MVS is done in the following. As offline *MVS approach, the widely used and open source COLMAP toolbox {{cite:5362e885e296a7cea... | r | b75bc0613089e8f8c52e3f7644d1a9e5 |
In this Section we present a more detailed review of the estimation procedure for the quantile autoregressive time series that accommodates the specification of the autocorrelation coefficient with respect to moderate deviations from the unit boundary. We first introduce the quantile estimation methodA complete treatme... | m | 94c83c944207d9d9b339c04daeabf6ac |
This result has applications in any scenario where axion stars form with {{formula:34ad5125-3803-4ba0-82d6-457e3def8091}} GeV, including those outlined in the introduction. For example, for ULDM with particle mass {{formula:b54fd8b7-4ac8-4be8-8ecf-0829cac70267}} eV, the correct relic abundance is obtained for {{formu... | d | 501ea83cbdcb73c20da52730d36b50f4 |
{{formula:9bdffba8-ced4-4a12-9b94-bd22f4704905}} SimGNN {{cite:9a571bcbfd332d60a527fcf0f667d26b7f087067}} extracts histogram features from node-node matching score matrix for prediction.
| m | 92bdf5815c436c584555244621868943 |
In this paper, we showed that a more biologically constrained version of Rao and Ballard's {{cite:003d0563a74e69d90f26102dfdfb927f434cbbcc}} seminal model of predictive coding performed similarly to backpropagation on supervised learning tasks using MNIST data. We found this to be true under constraints where 1) separa... | d | 4466508fdb42d3eecaae50141d124a13 |
While the problem of PbRL was introduced almost a decade ago, most work in it has been primarily applied or experimental in nature {{cite:fc7f6749c23a27cbf5143a76140e1cc5a60cd62d}}, {{cite:5582603ac2f2318175a132a6298edf9ab556ef87}}, {{cite:3c2dcb6260137e87537c23ba60460b88921f0e25}}, {{cite:fd294ac9295fde390d5f398b8af82... | i | caf94b65286c633a2b1149ef83fc1a60 |
To align with the proof of the DSML method, {{formula:ac778cbd-673c-4710-9bde-8be9d689ac41}} and {{formula:80b19c6b-e8fc-479d-bae9-0f82fd66ecc4}} should be independently trained, which is similarly required in the standard DML {{cite:0259675df6e872769de642814b5ccec647bfe878}}. To this end, we always divide a dataset ... | m | 83d57c58f51185222609903ce55742c6 |
If {{formula:86608504-62d7-40a1-bdb5-44350d9fa4c9}} is not an integer, it follows from Section 7.2 in {{cite:0f09d6bf6e2a03cbad60bf0bcf71deeac853bf1b}} that the Legendre equation has two linearly independent solutions {{formula:86a04249-9374-4354-acb9-c7fc6e0f221c}} and {{formula:3215956f-ca64-4eaa-b560-7f5428bf7b7d}... | r | e12fb7051a7765af70880208f1598a11 |
The above described method gives all (commutative and non-commutative) weakly associative algebras. But we are interested in developing this method in such a way that it only gives non-commutative weakly associative algebras, because the classification of all commutative algebras is given in {{cite:6eaf3b185c22c52ef4f4... | m | 838f7f4036574971379f1e0d04374185 |
Most prior try-on systems adopt a multi-stage approach {{cite:5d8d02690a24a6c62ba89d7cf3566f91c6ac01ad}}, {{cite:2d174c0370f6ce8dc0cd75cd72ea108f7aac1db0}}, {{cite:1c5a463efa9a3b32c0a575e6af0c55e33a1ebc34}}, {{cite:abc276978a1f757306b66c2ad97bd3b2f6c0703c}} shown in Fig. REF , including clothes warping, structure estim... | i | 065ff7d2923894cd1891d8ad307b8760 |
(3) Evaluation. Evaluation metrics are essential for the development of new models and the benchmarking of existing ones.
Currently, several quantitative evaluation metrics {{cite:741801410f2e6867409ed930b617e1f1aeef4e0f}}, {{cite:0e0d125f7cba8987fbeb934f90500a54b5f82d75}} and human visual ranking methods {{cite:f914b4... | d | ffc55c7e1cc747fb92d8d5e7913db435 |
This paper gives a comprehensive overview of TDA which consists of a set of powerful tools for measuring topological features of time series and using it for pattern detection, clustering, classification, and structural break detection. Research extensions in several directions are possible.
First, TDA for
multivariate... | d | a724c8f22d19e5decd68e2c89f493e95 |
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