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where {{formula:64820e0c-660a-49e2-b351-74ac01410643}} represents the fluid velocity, {{formula:4680ac25-6e8e-41b4-a471-8ecaf8cf8b0d}} the pressure, {{formula:cb00b14f-9c6e-49c3-b39e-7b57ce9c2471}} is a Cylindrical Brownian Motion, {{formula:d0dda1fa-30a7-4a1d-87d2-b6f3241519f4}} represents the nonlinear term and {... | i | f1d9f3ccb14952ef920f1f2ddf8f2669 |
First, the evaluation results of the proposed models regarding the deployment speed are provided. The performance is tested on a low-power NVIDIA Jetson TX2 module with 8GB of memory, which is a state of the art GPU used for on-board UAV perception. Additionally, in order to accelerate the deployment speed and achieve ... | r | 2f736fa9228cfc71117b0b10ad4aa589 |
One of the main advantages of using PINNs is to leverage Automatic Differentiation (AD) for approximating with high accuracy a derivative at an arbitrary point in the domain. This is a powerful and flexible mechanism for evaluating the residual function in PINN. However, we note that it is possible to calculate the res... | r | 9745d0be95c52e63ce5adc4cb7d08556 |
This generalizes the prediction of Vafa-Witten in {{cite:3f2d1d9f5678207bc9c03c678ea5188bdf73236d}} to the gauge group {{formula:65c66ec2-98b0-4ae8-9701-47f87b11106a}} and proves Formula
(4.11) in {{cite:2b02fb2eeacbc7cf6f62757fb621da46cece88ee}}.
| d | 106088b0e136bcd8a7556778d18fa4ce |
For the high-energy data set (Fig. REF ) we used a beam at {{formula:1320e29b-4848-4a16-b952-7c5f60aafcc3}} 590 from the accelerator, which was degraded by the Al foil down to 471{{formula:2122916f-4293-4953-b5c9-dd32d074be2a}} 25 . This energy value was chosen mainly for purposes of comparison with the previous measur... | r | 1eff4bb2bf4f67cd8816c00a767360df |
1)
The metastable state in the probe computation of {{cite:1f2bcd1f36959356c85d96d346177f0d564816a4}} is a spherical NS5 state.
2)
A natural candidate for the resolution of the observed supergravity singularities involves the formation of a spherical NS5-brane state á la Polchinski-Strassler {{cite:1f982426cb26d4240233... | d | d6d6cefab6cabd27798930a046fdf593 |
Some other works seek novel transformations besides geometric transformation. UVTON {{cite:c9d7845022c1627adc27b60ed5c1f1cc313c1025}} deforms on the 3D dense pose {{cite:f2fea94824ae4d3e858cde6bad5049363c86c48e}} and then fill the surface with clothing textures. Han et al. {{cite:16734f705d716c91a0a50d5110959f55131dff4... | m | d3d23583e28eca6ef8fc3077fb1062fa |
In Figure REF , we consider a set of parameters satisfying the dispersive regime described in the previous section, {{formula:270c1cc3-837b-4a91-a975-b4806774bfe4}} , where the tripartite hybrid system reproduces a strongly coupled optomechanical system well, that is, {{formula:e24ece18-73c0-4941-9a19-18519334d3e3}} , ... | r | a5b759208d57c415e406a60db13dbaaf |
Following and extending the renewal approach from {{cite:0dca8cf0ecaaf9c5a3713f6a6c179b323e8a8ff4}}
(see also {{cite:72add659191dc60a131769548563cfe31d9d8074}}, {{cite:726e1867b68831341e558cf7aeaea9038fd96dd8}}, {{cite:8962ccab10c3c64a5ee433d5a3df746548228dd4}}), we compute the full propagator
with resetting, denoted a... | r | a6045ec8ce567ebe9dfb8add70369425 |
Using kernel methods, it is possible to model non-linear relationships between the data points with a low computational complexity, thanks to the so-called kernel trick.
For this reason, these have been widely used to extend many traditional algorithms to the non-linear framework, such as PCA {{cite:89f8f438533aac067c7... | m | 5c6f64ea99c58c942efe529b94ad84d9 |
In order to study collective effects in a specific collision system, the anisotropic flow observable {{cite:8691ff76e78820a0fe491d14c68a8e6b575da93b}} is used. In a heavy-ion collision, the non-zero impact parameter makes the collision region anisotropic. This uneven geometry will result in anisotropies in the momentum... | r | 0f17f20337faccd8d64272339156af97 |
Uncertainty {{cite:c6c7001be68c2b8fb2e3e30f1f2e8f2265dc8e8a}} assumes that the higher the uncertainty of task data is, the lower the weight of this task loss should be assigned. They design a learnable parameter {{formula:0193c349-52a6-44c1-a606-758ddc7211a7}} to model the uncertainty for each task. Specifically, they... | m | 5b1f91caa8235596292597519aec75cf |
As proved in {{cite:8fbb0351448e9d6b1bf3b33fb8d9679af6dcdcd1}}, current framework inevitably mines incorrect rules
with high confidences, i.e., if there are several rules sharing one or more predicates,
confidences of rules would be coupled mutually. Intuitively, this is because Eq. (REF )
distributes the score of a r... | d | d411c9fe74bba8137b9ed8fd6eedcf8e |
The rapid pace of adoption of GNNs in neuroimaging applications urges us to pause and ponder about the rationale and success of this adoption. While we agree that the motivation is well-grounded in the field and in fact necessary for sample-efficient factual learning models, we question whether the current methods are ... | d | c3093397f15476ed1a986ba3bddae70c |
Recently, the Transformer {{cite:608917206b56ca1b9a27d3c53ea9457caee3c28f}} architecture has shown state-of-the-art performance in a variety of tasks ranging from NLP {{cite:608917206b56ca1b9a27d3c53ea9457caee3c28f}}, to image classification {{cite:2f5d5ed4618233ff35d9b172401358ba2e63aeb5}} and video object tracking {{... | i | 6d45e9fc8b5ee167f873f9d41e55fd84 |
In previous studies, the Boltzmann collision operator {{cite:0adaffe509d88899bb9b9f4e5448e60c2d024ccf}}, {{cite:91352240a67c9eb800ac834e157ff0d00298988f}} and the Ornstein–Uhlenbeck operator {{cite:cb35de12e1e8f639b77899628d38c9b4b9079a7c}}, {{cite:09f38da3d897e64d0c17f144d9b8ef28ce1ac65c}} have been used for a descrip... | i | 27e70334c35020a9a2a07da4f4486247 |
To build a relationship between excess entropy and bulk rheology, we next investigate the connection of {{formula:33974be2-25e4-49b3-996d-a971c45d2157}} to the other dynamical metrics. For this comparison, we compute the ratio of the second to first harmonic amplitude, which we denote as {{formula:b54e55af-7f35-450e-b... | r | a07d86428af2b95b0eff369029551863 |
The pipeline of original NeRF {{cite:7c0a4dea25854b0319dc85becd48504774b3afe7}} consists of the coarse and fine stages. During training, the coarse stage obtains the density distribution over the whole scene. It uniformly and densely samples points and calculates corresponding densities by a coarse MLP. However, as wil... | i | 4e6c1faccde47367e10f87d3f0c74107 |
In broad terms, galaxies could form via either the monolithic formation or the hierarchical accumulation. In the monolithic formation mechanism, a large amount of gas collapsed rapidly to form galaxies. The speed of collapsed gas determines whether elliptical galaxies, S0 galaxies or spiral galaxies with spheroidal bul... | d | 40ec10f88e593fdd27e0b47c8f952108 |
It should be noted that even though our generalized Perfect Hyperfluid construction fits most naturally in a Metric-Affine Gravity approach, this is by no means the only place it can find applications. Indeed, our general construction here can just as well be applied to all Theories that represent special cases of MAG.... | d | 77b7f9ea21f0b6bd5321605aafc66997 |
Seq2Seq model in this study was trained on KP20k corpus {{cite:2b6668fb406d096aa460cd6ccd901fefb9317e9e}} ({{formula:a0324797-c15b-4aef-9ee4-fb005fae4b19}} documents, providing {{formula:652cf389-4900-4c61-9977-235bfc8729b1}} training sets after preprocessing). For training the model, both sources {{formula:0f50eaa6-... | r | 8eff0abb35e5374e5821a9735e3e5b96 |
Iterative search for optimal policy is commonly used in literature {{cite:a7a80b1a65e303cfdb159b757edbafc35f53d79f}}, {{cite:af60152bcd96efa449ba56b6b671c7f07631e381}}, {{cite:70f9d47044e7e67567676c1100962e5fb6ee7146}}.
We formulate the unbiased constrained policy optimization problem over {{formula:a42529de-3ea8-403e-... | m | 0aa727c106e32e8e2cd5b73331833b83 |
(2) Pseudo-Labeling {{cite:683404915c800d9ab47b3290b1f6ac99f493292f}}:
The approach uses a base model's confident predictions on unlabeled images as labels. Concretely, if the maximum probability of a class is greater than a threshold {{formula:49a59473-4d7e-44ca-8f1f-5c6fee8079b8}} , we then take the class as the targ... | m | bf19799fb59c0c7e4b08d3a25011e86c |
There have been many proposals of future colliders {{cite:677e082bc8d1acd5954b21a1dd6511d7f5de9428}}, {{cite:cad4eeb60a734123fd19abaf957bbff86bb96e5e}}, {{cite:8b4703729e8b3943c701b999872c4f23fe963ed4}}, {{cite:c07fe9e08869374f93b445bb83c248d819750d74}}, {{cite:11de4430e2afafd33fd0da7efe94aead31232283}}, {{cite:494a86c... | i | d6d8ce8643ec4baa3e0891863ff26323 |
The methods in the previous paragraph have various limitations, summarized by Table REF , that affect the design of the experiments.
First, the post-processing methods {{cite:21aed915a28406fd3632c635f2c871d5a05483ab}}, {{cite:1a21ce2f99e3f14f1ea25a4c6504489cea34e0d8}}, {{cite:99d990bd6c59bcce492720d0244803077786f884}} ... | m | d89960a5d656a9cae1696479dbc412f0 |
We perform our experimental evaluation on CIFAR-100 {{cite:ae8fe7db3df9e4cdbec34371953b882d29c626e7}} and two fine-grained datasets, namely CUB-200 {{cite:b30cf1c3d2eedfa258eab46772574e901b133873}} and Stanford Dogs {{cite:dba73c2688e7d932a39765d1b2270fb423dd31e5}}.
The CIFAR-100 dataset consists of 60000 {{formula:369... | r | 0e776dc2a2069e505524c51cc576f706 |
We also make use of the following bound on eigenvalues of normalized covariance matrices given in {{cite:51639a652568ba7bde95313551881390ece2af3e}}:
| r | 60231d91480445f7d6a4d095fb1206dd |
Our method aims to learn a representation of scenes as spatial maps of blobs through the generative process. As shown in Figure REF , a layout network maps from random noise to a set of blob parameters. Then, blobs are differentiably splatted onto a spatial grid – a “blob map” – which a StyleGAN2-like decoder {{cite:fe... | m | 6fdbffca0e5efc52576a1a1a67b90920 |
We assessed the consistency of predictions in BOLD MRI time series using our model, and achieved highly consistent predictions (Dice {{formula:0ea62683-2f21-4d12-b377-6bb5494081cc}} ). For many subjects, we observed modest drops in Dice ({{formula:7f8385b6-d96b-45c7-b58a-a59a33fd0255}} ), which were often due to fetal ... | d | f3c1019fd2e37234265263d854a03a4f |
Table REF presents the results of our proposed model and the baselines on the MultiSourceFake dataset. Our best result was achieved by using 10 as the number of segments ({{formula:7b58ef83-3998-4ea2-ab81-00ddb6d955ca}} , as found on the validation data). In Figure REF we show the model's performance for segments of ... | r | 9bcda200c5624f8296090459c19d7e27 |
For discrete random variables, there are two common strategies for stochastic gradient estimation. The first one involves replacing discrete variables with continuous ones that approximate them as closely as possible {{cite:3e8edb0f1dd3cbc130e21cc6aa0971dba7d9ada4}}, {{cite:39431200398040e19128ab1f8d61bffbde5ea7cf}} an... | i | e9af0f39ac08b11234b8ec71ea5c694b |
We use a dataset containing 46,744 cif files which contains the information describing the unit cells of properly relaxed crystal structures from the Materials Project {{cite:1cbad5efed2ec4b899e02039a86f21297d9d579d}}, {{cite:945e8310d39ac7e2063153f3157fbfc2e4be3fd8}}. We use 80% of the data for testing and the other 2... | m | 7b72fa1814f96b59116679a578c10f6b |
Unlike the 0+1d SY model and SYK model which have a large zero-temperature entropy reflecting their “spin glass" like nature {{cite:c8a00b4425168dc59f22fe9239c95b69567706e5}}, {{cite:afef03908f0ee6e185672fafe283442f5afaec1c}}, {{cite:2388cd28946b1d453ac83bea03d234beaef25c06}}, {{cite:56b22b13272dba8c6481e21d07ac4265d72... | d | 0c8d727757c8495d2d066878863ec3a9 |
We skip the proof of the above lemma as it is well-developed in the literature of functional data analysis including {{cite:c1d45c7e341c96fcfe1300c09ab968a93e97fe99}}, {{cite:7d4695023ee116a82c13e33353c46d714d30eafd}}, {{cite:0ebe2c2fa468ef4ced08253056e39ca8586821cf}}.
Next, we show the asymptotic results of the propos... | r | 027687c5d1fbed3c189ee44d408a61b3 |
It could be interesting to investigate to what extent the generalisation and overfitting problems could affect predictions of real-life processes, considerably more complex than the artificially created data discussed in this work. Extra overfitting measures may need to be included as well in the future. One option cou... | d | 8f77295d7f58451caa7970c92718ca1e |
Note that in the smooth case, the higher rank property can be expressed by asking that every complete geodesic admits {{formula:d52875d0-673b-46f8-ab82-1abf54d9e052}} linearly independent parallel Jacobi fields for some {{formula:220a79f9-f8b4-4701-a927-fb5faba191e0}} .
In the presence of a geometric group action thes... | r | 210349f594704d3d34d67e9db0eaa303 |
Generalization is a key desideratum for machine learning models to scale to the dynamic nature of the real world.
The standard supervised learning framework assumes that train and test data are from the same distribution (domain).
Domain generalization techniques {{cite:4b1b3a91788f9c36adef632615a0cbd7dae8b151}}, {{cit... | i | 27e95df43e58f3bfcbf89ec3c3c0b073 |
Recently, there have been a lot of attempts to exploit graph neural networks (GNNs) for graph classification {{cite:dec2d91a5fc39ca616e52d17923b635cea68e4a6}}, {{cite:a8e0a30eb320e36f37c4cac95ff2d78d7c23a374}}, {{cite:cfa766f7abd6d0557863305fa39202800325126c}}, {{cite:e54d0deb2fd715f472a943dad6708ee86744a0bb}}, {{cite:... | i | 5e960a6c6ac1c051541af0eb48551c12 |
The comparisons between the trust-region methods (RDA and MHODA) and the conjugate gradient methods (conjRDA and conj-MHODA) shows that the second-order geometry of the trust-region method improves the clustering and classification performance of RDA, although it may be unreliable for MHODA (Table REF). The advantage ... | d | 1dce3db848f5ea2b410ee1f9ab313e06 |
Condition REF holds for any compact {{formula:bb57734c-73a5-46ac-a14f-d05d2ffc68c0}} ; indeed, by {{cite:776a2e53010fcefd3a736f5760dfcb424f0a5e9f}}, {{formula:154ae982-ac22-4340-b4d1-7b5db370454b}} where {{formula:3994a96f-47a6-4592-bf7e-795b281feae1}}
is the number of {{formula:000756a9-1757-4ad0-ab47-266660daebd0}... | r | 84d50f01c90e57d3ad2f6796e9ffcbd2 |
Recent developments on optical flow estimation {{cite:2afd803b1d200f6c989db6bb560bbcd9439437fd}}, {{cite:b97ead0e3cd3ceb50697f7a00fc24edb84e04fb9}} using supervised learning have yielded state-of-the-art performance. However, such performance benefits have not yet permeated to pose-estimation tasks, where standard mult... | i | 999769753197042efb793c8469811142 |
The effective treatment of the influence of the on-site repulsive Coulomb
interaction on the states of electrons is a central issue of any theoretical
approach, where at the large repulsive {{formula:7b13e159-0923-4d24-b109-b5499b34760e}} , a double occupied state on each
site is strongly suppressed, and the Hilbert sp... | i | 27e1b738adc41c925d6d83a0f2da1087 |
We emphasize that CycleNet loses translational symmetry, which is considered a strong feature of CNNs, especially for image classification tasks.
However, recent evidence suggests that this property may not be crucial.
Symmetries do not have to be hard coded in the architecture: they can be learned, if needed, by stoch... | d | fbea6434683ea47b2d5dff8199d82077 |
The realistic modelling of phenomena in nature and science is usually described by nonlinear Partial Different Equations (PDEs). Comparing to their simplified linear counterparts, these nonlinear PDEs in general has no explicit representation of the solutions in terms of initial and/or boundary conditions. Special expl... | i | b202e8781882a2565f66862208b5f4cb |
Since the fundamental solution systems of neighborhoods of different regular
singularities are different, and many equivalent fundamental solution systems
can be constructed corresponding to neighborhoods of same regular singularity.
When the Feynman integral is expressed as a linear combination of
hypergeometric funct... | i | 5953020ad54c9a64268997d64676c37a |
We have demonstrated a reduction in the second-order correlation function of an HSPS of {{formula:f9fbf083-c0a9-443e-9cdf-3d74580fb18b}} by discriminating the photon-number in the herald arm using commercial SNSPDs. On the detection side, we use the information contained in the slope of the rising edge of the electron... | d | 366fb505c5db7f2507422fcd2f0aa767 |
We choose 14 baselines to be compared with UGCL on node classification tasks. These baselines consist of MLP and three types of GNNs: supervised-, conventional self-supervised, and GCL approaches. For supervised GNNs, we select three widely-adopted supervised GNNs, which are GCN {{cite:0ba13a52e710a43df677e98048c459702... | r | ff417e9cc6e282e78fe3ec06f87a47fb |
Structure-based approaches {{cite:150243e5058abb09437f22c43b45e66a0a372326}}, {{cite:e6ca15be74f45a25d18d1f48ce82162d2b8669f6}}, {{cite:ca541e099821742228b9cb9bb2f6d7298a957636}}, {{cite:e8884809517365aa8191ecfde5d6f70b1b86efaf}}, {{cite:5df437b5cf7af34eaba3135cac7f8a97142819b4}}, {{cite:bbf0fb30b8269b106d15ee4bd989d32... | m | 1b54496ce73a51e786df67f97111e54d |
Athermal materials represent a class of disordered systems where large scale properties are only weakly affected by ambient thermal fluctuations. Such behaviour emerges in many disordered systems when cooled to low temperatures {{cite:a1082004dfa3ffd510f14e7dd108b085a4aa0866}}. Being governed purely by local constraint... | i | 4eb84de0b1521f63d3b199566786369c |
In PFNN-2, the approximate solution of problem (REF ) is found within the hypothesis space {{formula:cc4887ed-a58c-473a-88d0-b0bf7ffc6aa4}} that is formed by neural networks.
Unlike most of the existing methods {{cite:52eae8039aae8344d215fae0396b3d7d6c9f4da5}}, {{cite:2da7a5ec5af1a90a63de4dc085a2f7278efd7d4b}}, {{cite... | m | 13f3d38fe67932da5e6f47446091f596 |
Co-design Model Architecture with SpAtten. Besides the experiments above that leverage existing model architecture, we also explore the potentials of co-designing SpAtten with model architecture by searching a
Hardware-Aware Transformer (HAT) {{cite:0aef3b8c54b085d3965365e2d9b10c36df761cbb}} for SpAtten-e2e. The search... | r | 82cbff024ede77b593b3c2e7b52922c3 |
Experiments in Earth's ocean demonstrate that hydrate forms rapidly upon contact between liquid CO2 and liquid H2O, with visible masses forming over the course of just a few hours {{cite:8caa9719d6c3fa5e3e513198231659dc4dd21a27}}. This suggests that with surface temperatures below the 282.91 K quadruple point of CO2 hy... | d | 2672470366bcdf90bb5d65ca31080e02 |
In this study, we have extended the X-ray scaling method to a sample of heavily obscured type 2 AGN with {{formula:73db2e7e-fd99-4638-a443-83c6e3be504a}} already constrained by megamaser measurements.
This dynamical method is rightly considered one of the most reliable; however, the accuracy of the {{formula:025f4d4c-... | d | 9aef3a5b94063c6ef290846dda59f00c |
For non-convex problems, the computation of the Newton step (REF ) may be an ill-posed or not even well-defined problem {{cite:52d25b8eb245f9752313b91a28b831e4e3eb57fa}}. Moreover, the Newton step might not be a descent direction. The Newton step is only a direction of descent if the scalar product with the gradient i... | m | cd76675e3c49ae953986ec9ef9960548 |
Each image is resized and cropped to 1024x1024, and a set of masks is generated with thin, medium, and thick brush strokes, using the methodology described in {{cite:838c60006fc15913efbacf7465bfb53ab560f9fc}}.
These different mask-types are evaluated separately to observe the effect the width of the mask has on image i... | r | fcbc1549f7c2989583cd3ccdf34148a8 |
Despite many efforts to improve its efficiency {{cite:1cc23766a998742c8ea9a2d77f17ddbd8ab81a15}}, {{cite:ad23fb3d04620d669c149139eab02bcf88ee5bef}}, {{cite:95b7255db2bbe4aa21a751f59297e4522a60cbcf}}, {{cite:2c22cc99831f178dddbd078b998dbd3c5e4113f9}}, blockchain still suffers from poor scalability, which introduces high... | i | 5939e91f8024d057f922791fcd415533 |
This result improves the previously best known time {{formula:03ed5f45-7124-418c-bbc5-3d7dc060df0e}} obtained by {{cite:cd25df833f2e4efa9a4cab5e8f499e3d1514b47a}}, {{cite:08fb43701d53c610fd9aa60ab9673105c2514452}}.
| r | b78a2d3a220b75db41277748d930a211 |
Within the enormous theoretical pool of compact objects available to run tests with {{cite:7167fcda31fd8f71f50b77cfaa23bc58b42777de}}, black holes are undoubtedly still the privileged candidate. The uniqueness theorems {{cite:28c1c65ab7e29e97c8a2e4254c29ae23d4f52f14}}, our understanding of gravitational collapse {{cite... | i | 7e5d416b6e40ed4f350e599670b9c2ab |
the ledger's properties that are at risk, if the
resources' distribution across the relevant parties becomes
centralized.
For example, considering Bitcoin's consensus layer, the resource is hashing power and
the relevant parties are the miners; the properties at risk are
safety, liveness and, to a somewhat lesser degr... | m | e155909b35f9aff4d1425a9322dd341b |
Recently proposed volumetric neural rendering methods, i.e. NeRF and its variants {{cite:cff19d82b1699101c2663e9da85a93c9105c8f90}}, {{cite:395dd9e36dadfa165f826f5f12ec5081be589ec1}}, {{cite:7e22b2e850fe01fec80454e66dcf0a65049cfb7a}}, have shown great advances in high-quality free-view synthesis for static objects. NeR... | i | 54776ce6b5bd9ee7fefb01f893682e49 |
Since {{formula:4a3e9b83-724f-4064-bad1-b7756b5b5300}} is a random matrix with each entry i.i.d. {{formula:94f13736-77d5-42c4-8f83-355dc2f485bc}} , this follows by standard arguments (Proposition 2.4 in {{cite:1bfc6e9cc320646dc24150d429f76d2aad89471b}}). Since {{formula:773d472b-4033-4cff-ad8e-5e96cb2b3ccd}} , with pr... | r | ddd7a06aa4122af02744a64a95c68754 |
Panoramas with depth information are very useful for 3D computer vision tasks such as novel view synthesis {{cite:9cf11f4e8ca6904565e172319f1dd5c727265b0c}}, {{cite:b31c7df0feea61688f6c4b395d1823171b9764c5}}, {{cite:a12ca0a052ba9e1f6bd51439628e261ad6a98ea2}}, 3D scene understanding (room layout estimation {{cite:34467e... | i | d68ebb9e8eb620dc4f16ff6d2fc1a2b9 |
Many cosmologists have considered, wormholes in {{formula:b8bb8bed-3635-412c-a72f-a30c47e621af}} gravity in various perspectives. Now we are going to examine the contribution
of certain cosmologists in {{formula:a9073703-29a0-443e-9cba-4ab79441bcd7}} and {{formula:7c7c98b3-81d9-4348-8a16-5d61f988a673}} gravity theo... | i | 4b8f0c913ef62011062da9ad4667fdc0 |
Ever since the introduction of dimensional regularization (DR) {{cite:9ee6a864c28254b077c7cfab3a6a55e9072f8624}}, {{cite:93b4ef502d57cf0f86b38a3b99d78c601a36ce71}}, it has been recognized that special attention is required in the treatment of {{formula:8f8470a5-d13d-48bd-a9b8-31ca01011a15}} , an intrinsically 4-dimensi... | i | 67d7f155a9994dac0525202179055606 |
We consider the large family of multi-view representation learning methods {{cite:1671df6fb5fa69e61db97435fc02d195d2d71fba}}, {{cite:91198b7f71ce6165aa85c0c9596406e915641c89}}, {{cite:a6ce10ce1690ed2d457956047c33603b546ed460}}, {{cite:3fecbe3d7ab162b86b62ee7c572ecbc0fd57e6e2}}, {{cite:9386512a961e342652cc81ee702bc200c5... | m | bbe7576847768281d96c100c0f9f9f76 |
where {{formula:ccc22bac-28ef-47b3-8fc6-2b05ab42a99a}} contains {{formula:9e8d1205-0680-4334-ac67-3404cfc99bcb}} basis vectors for {{formula:beef4ce7-b8f4-473f-9406-6bdb621332c6}} . For 2D images, over-complete wavelet basis ({{formula:ab2e777c-19d0-497b-8692-cf2b92f74be2}} ) are often used in both dimensions. For th... | d | df67f5de3ff480f40f8ca3fb0a803173 |
In a series of recent studies {{cite:7d3375b9bf727f3e3494c7bc12831bc1aaea51d6}}, {{cite:d516f8c436fd9d4d7d09f9b237eb84294edb0bb3}}, {{cite:6b7c60cdc36015d5af78f12f6df87fcb3081fff2}}, the role of sparsity of the networks for the Bouchaud and BM models has been investigated. For those sparse networks the trap model is fo... | i | 923097fdc4119a40fb933f8215991e9c |
A permutation {{formula:96c4c0c6-6889-471e-9373-452f32fdc852}} is a bijection from the set {{formula:de484a23-55ef-48a8-a5e5-165428e749b9}} to itself and we will write it in standard representation as {{formula:ac6d58de-842f-4843-9435-79e99680d396}} , or as the product of disjoint cycles. The parity of a permutation ... | i | d4af343ad72a3d5e645692abda0fea6f |
In summary, we find that in all the three tasks, our proposed method out-performs the methods of simply tuning pre-trained language models, as is proposed in {{cite:a11ef9f25f615abd9438da4012731eef547a9be0}}. However, we would like to caution the readers in two aspects when reading the conclusion of this study. First, ... | d | 64931067c9f1fdcd9667528cd65e9eff |
One can already provide some initial analysis using known results in the literature. For instance, as the protocol of {{cite:ee5ced8143d1ce5da82e0b6db1473bf1aa0c30bd}} requires the client to prepare and communicate single qubit states, one can wonder what additional requirements are needed to ensure the client can dete... | d | 2376dba6527c57741daedbb1893a4f30 |
Traditional contrastive learning methods adopt instance discrimination as the pretext task. This kind of refinement of classification treats every sample as a category to conduct discrimination. Thus, it will introduce many false-negative pairs, leading to inefficient supervisory signals. And another problem is that th... | i | cb413f0b656450cac3d9bf8cabfc4c3b |
In fact, during the architecture design process, many slightly different networks are trained for the same task. Apart from their final validation performances that are used to guide exploration, we should also have access to their architectures, weights, training curves etc., which contain abundant knowledge and can b... | i | 42b9af9b1bdac208069d8ad553cd78e4 |
[leftmargin=*]
FPMC {{cite:532db91dc95f1d3f3da9a18618e6e0afdb49e4da}} is a sequential method based on Markov Chain. In order to adapt it to session-based recommendation, we do not consider the user latent representations when computing recommendation scores.
GRU4REC {{cite:0742b7b74fb84c6e714998d8fb6db44c7a7f3a2a}} ut... | m | ef8d24a0df97d133fbcbc36b1c7b1a8e |
This model is a Friedmann–Robertson–Walker (FRW) cosmological model, which is obeying the cosmological principle and Weyl's postulate{{cite:4183c059e4fc92dd915d3874a24ed096565f2ed6}}, {{cite:2314a6439ceb8e616a599e1d42242327e8786066}}. In {{formula:35b941c7-44ae-4561-8cc5-f34d4f549ef2}} universe that space expands at a... | m | 8cca37f5e7087ec5e3c616a62eb6a993 |
When we have the vacuum case outside the star, the OMOTS surface coincides with the null event horizon. Radiation emitted close enough to this surface reaches infinity with an unboundedly large redshift. It is this divergent redshift that is the reason Hawking radiation is emitted just outside the null OMOTS surface a... | d | 9797ced498cc5580cd289ddd39139a63 |
Data. We adopt the datasets used in the vanilla FastGANs {{cite:9420a8de32caf92929b3d0f7cc24239333518c0d}}. There are 5 categories tested at the resolution of {{formula:a2b474b7-8842-4698-872a-6503e3080c0b}} each of which uses around 100 training images (see part one of Table REF ). There are 7 categories tested at th... | r | dfa5418f66c15ffb389b25ff31b33e13 |
MS-CMRSeg Dataset: Table REF shows the quantitative results of different algorithms for the MS-CMRSeg challenge, specifically for the 40 LGE-MRI segmentation test data. We first compare with the model trained with only limited labelled LGE-MRI data {{formula:59e68e22-66cd-41e8-ad57-267baa65d86e}} (referred as Supervi... | m | 1b11db4e79fdb9b084046059e62ddf28 |
Gravitational Waves (GW), first introduced by Einstein in 1916 {{cite:bdf7873a9e9b447afec51a5e0e5d0788a25f5f36}}, {{cite:7eff67daf0cead082906c55abd3c294e90413548}} as a linear regime of the field equations of General Relativity, have been directly detected for the first time in 2015 by the LIGO/Virgo collaboration {{ci... | i | 920ba3ccc40acb67a231a939320c932c |
The normal viscous force {{formula:1b3d4176-863e-472e-9857-34069c4968b2}} is due to the lubrication effect of liquid bridges between particles.
Its classical expression for two smooth spherical particles is {{cite:67523f4b32cd7d64f868b6e03decd7bbe4a8598f}}, {{cite:3d48e8a6fd2e6a98cdb251eb31dcec9e04ba259c}}:
{{formula:... | m | 330f7e0fea3433daf05d4d2843751664 |
We analyse all protein trajectories in the framework of a non-Markovian, generalised Langevin equation (GLE). The GLE is a low-dimensional representation of some higher dimension system. In the present case, we collapse the all-atom dynamics of the composite water-protein systems onto a one-dimensional reaction coordin... | i | 90b1a313bd6d3defe2d9aa5dbfc73a5e |
Results are presented in Table REF .
The main proposed systems are “Harmonic-CNN” (the instant method) and “SpecTNT (24s, CLT)” with CTL loss (the multi-point method). In the ablation study, we compare these to SpecTNT without CTL; a regular Transformer {{cite:d08f2e7327c2a3747126e194d39dcc38d60530ce}} with CTL; and Sp... | d | 5bcd490318fe7de94f3da9926cc4debf |
One unexplored direction of creating similarity measures is creating a SNN
similarity measure (Type 3) through training {{formula:61364d2c-5bef-4b8b-9877-0b587f2078e7}} as a classifier on
the dataset later being used for measuring similarity. Then using that trained
{{formula:9bf5038e-4095-4512-a8fc-dc387a362567}} to... | m | 1235c8febd769d3f342730eb531486ec |
Raw data for the results reported in the text are available
from the authors upon request.
Acknowledgments
We thank J.N. Zhang, C.Y. Hsieh, Z.Q. Yin, Z.B. Yang, G.H. Huang, and X. Chen for helpful discussions and comments. We thank the electronics team of Tencent Quantum Lab for preparing the room-temperature electron... | m | 9426d94ce730c4931204d536839b2a07 |
To illustrate the effect of the momentum dependence of {{formula:8eab8d7b-5d8d-4507-8e73-cb791808b826}} mixing, we perform two fits simultaneously taking into account the experimental data sets of the pion form
factor {{formula:fcb4c762-587a-4c5b-8c1b-a63db3b578e1}} of the {{formula:4451a750-8e11-4026-98f9-b4e388d1a9... | d | c7e14ae665685c861a1b62ecad09c3ac |
K-means divides a set of input items on explicitly defined number of clusters. We set this number as the number of all users divided by a coefficient of {{formula:7c95dad0-f577-4593-88d8-249b9478f259}} . Thus we achieved clusters, composed by average of {{formula:2409c201-a423-4e7b-9234-8982b3f4af1f}} users. This coef... | m | 1c6f2ea5ac880a839501f68c67e545e3 |
Figure REF shows the resulting population when running evolution using the RWRL Cartpole environment {{cite:a5b64092ac1bc20807ac976146366e43e977a16b}} and Table REF shows the average fitness scores ({{formula:359a0411-329d-4ded-8b6a-292cfa58dce5}} standard error of the mean) for each algorithm in the Pareto-optimal ... | r | cb9b31f7ac0dfd0ad9f1a892e50a5363 |
In some extreme cases, there may not exist a pre-trained model. In this situation, we can evaluate weights with models trained from several rounds of FedBN {{cite:9f4cc4f4da50eb15b847101d3bc551d8ca058abd}}.
{{figure:adc22905-357e-41a8-9dee-215eddb6c44a}} | d | 544640de188072332894f4fcf5afde46 |
Let {{formula:4624ad19-64fc-4700-a70e-568440f19d63}} , let {{formula:9d527f18-0677-4279-8c6b-5dd78430e7b9}} be a family of independent exponential distributed random variables with parameter {{formula:ba4b4a72-196c-4005-b57d-0eb39949efc9}} ,
let
{{formula:c59d475b-cb83-40b0-ad62-dc8bf9f700dc}}
and let {{formula:e95d3... | r | 2d45e2db8979cc4748d63b8016fdd36f |
An agent exploring an infinite translation-invariant world would find that the statistics of the local random variables which he can access are constrained by the requirement of infinite TI. However, and despite a long history of research on TI systems, driven by the needs of statistical physics (see, e.g. {{cite:3a03a... | i | 1f647fb6de8282ca3fa12282998cd41f |
For anomaly detection, existing Toolboxes are mainly divided into three types: (1) standalone tools implementing single algorithm (like PyNomaly {{cite:464f397748e73bbb73cac844dbdf56ebbd4b0844}} , Jubatus{{cite:87ffad4c92f8dfc3931ff8a65dd741b111377deb}}), (2) part of a general larger framework that doesn't specifically... | d | d67d4627aa2126d66cdd1ea507c09ab0 |
Which machine annotator should we select?
Ideally, we want the machine annotator to provide precise labels on training images. For this we consider ReLabel generated by a few state-of-the-art classifiers EfficientNet-{B1,B3,B5,B7,B8} {{cite:fd6044fcd0eb00fe185af1c6438efa60a92ec4ad}}, EfficientNet-L2 {{cite:52ed1e3cff69... | d | b8a1b120a731630dc3ff27056f9a8f7c |
Working with other {{formula:310dddd6-5335-4bce-a327-daee9e7b88ae}} sets.
In certain application domains, it may be difficult to collect a {{formula:a337a124-17b7-4a50-ac52-12c1187efbdd}} set that is at all meaningful/relevant to the ID task (e.g., attempting to use animal images as {{formula:954754c2-03b0-430a-9aea-... | d | b20bcf3a1bb9f33c0d47caa28038756d |
To overcome these problems, network embedding, also known as network representation learning, has gained increasing attention for the past few years as a fundamental tool for analyzing networks {{cite:8af58dfbea0d3052803f3cc00515324c83f44ab6}}, {{cite:131e9adb94d25aa88339753184db4afd450b9f89}}. Network embedding learns... | i | 04a020cccf9a8faa8594f411a4215ca6 |
We choose three of the most prevalent VAE models for semi-supervised learning as baselines: M2 {{cite:589d94b95d0c3d25a271e4379b33a0124bbf1935}}, Auxiliary Deep Generative Model (ADGM) {{cite:77414f2fd20a780754b0e4b1bcec3be13fe38189}}, and Ladder Variational Autoencoder (LVAE) {{cite:3423ba36b2f14f70e77b969ac2550c28075... | m | aa6b052b59a0e2bf893d218b322ad203 |
As the fraction of closed RCs, {{formula:58d9b80b-5e74-4b86-9908-95d6f1e9091f}} , increases connected clusters are formed. These clusters are characterised by a typical mass (number of closed RCs) {{formula:8bcf190c-23a3-4bf3-b98f-d264c7c23c02}} and a typical linear size, {{formula:cb4050c8-a7c5-4ced-999f-791690097bd2... | r | 0be80fbcb899a21810f1014f760bed14 |
This phenomenon of preheating is typically considered after the slow-roll phase (see, e.g., {{cite:2ef94c4ccd2a0e0791bd1ddaae2993afdaea4811}}, {{cite:034c80c3b964a045e546c9b4a1765718d5b0148a}} for a review), but it can also affect the dynamics of the Universe during inflation in the multi-field setup {{cite:b0efe02b3bb... | i | 1e0bf29d6f280e97b7b2aadb60c7dd19 |
Scalar field (SF) configurations in General Relativity and its modifications are interesting for several reasons. Various SF models are extensively used in cosmology {{cite:47e9fb7ccf19d928618c887c5fc1371aa26f1ce4}}, {{cite:b166499dbfca72dd222080022017fcc4e2bf6607}}, {{cite:dc63021dd2f0f64cf2f4db46353a649084dd8713}}, {... | i | ba826506ce4db58173d2f595d06b5fa9 |
Price of interpretability.
From the literature that we have reviewed, merely 24% of the studies adopt interpretable models, while the majority of them focus on applying post-hoc explainability.
This may be due to a long-held belief that there exists a trade-off between interpretability and performance, exemplified by t... | d | 1f6632891d557c4989d300ebf303801d |
Visual object detection and tracking become a very challenging problem due to several factors like (i) low-quality camera sensors (including low resolution, low bit depth, low frame rate and color distortion), (ii) challenging factors (like tracking non-rigid object, tracking small object, tracking multiple objects and... | i | 889bf94292cd46f8ebb615ccf505862a |
Overview We propose a purely anchor-free architecture named AFSD which is shown in Fig. REF . Concretely, given a video {{formula:5c631665-ab61-4e9a-b742-c6583c02c3ec}} , we first process the video with a backbone network and a feature pyramid network. Take RGB frames as example, for each video {{formula:013b7d02-5797-... | m | 5e244451157dc363a7bcce0aed0fd8dc |
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