text stringlengths 54 548k | label stringclasses 4
values | id_ stringlengths 32 32 |
|---|---|---|
Let us begin our discussion with the variation of the conductance {{formula:cac2a103-47a1-4351-b6f1-4428526afe90}} as
a function of the injecting electron energy {{formula:b87a734b-e219-4fa2-826f-6f6e60b9b265}} . As representative
examples, in Fig. REF , we plot the {{formula:5a2f066e-0fc4-4849-b232-dae0407b73f9}} -{{... | r | 4efe2a72e86b1cd3a4a13da4d76f812a |
For convenience we calculate {{formula:79ffbe23-a489-4816-bedf-33eb888a6d90}} in step 1 with the Vienna ab initio simulation package (VASP) {{cite:583fe7f4905e3a296583bb6f652a3a55bb943921}}, a plane wave code, using PBE-based projector-augmented waves (PAWs) for treating core electrons {{cite:e79e2d905e49ac08866882caf... | r | e5d726bdd44576a174fc46c708e3766a |
Certainly, the nature of attention as a distribution over tokens lends itself to a straightforward interpretation of a model's inner workings. {{cite:c2fedd6455189b72da3ee157236e57a80fadb8af}} illustrate this nicely in the context of seq2seq machine translation, showing that the attention learned by their models reflec... | i | 4218a02b8ad6ccef309abbe85f43f30c |
In this work, we present CAT, contrastive adversarial training for text classification. We build upon {{cite:867ea7f2cd0a03d7073349336b55ab6f67091a3d}} to regularize the fine-tuning of Transformer-based {{cite:3ce9323f73c13dfb273dd477ffde2b0ccd8d33ca}} encoders on text classification tasks. Additionally, we encourage t... | i | d6d0c341dc521bae12e9fc17a0cece41 |
Finally, it can be shown that typed processes are strongly
normalising, which is not so surprising since we followed closely the
logical principles of Affine Logic. This can be shown by a small
adaptation of the standard method {{cite:0d843084cc5be0de6e972237b3010ef32134fad6}}, first by giving an
interpretation of type... | d | e351ffe0a8bd3261f795e7bf585041d0 |
The divergence of the mean and variance of {{formula:8d9b283c-2795-4506-a76c-2e9ff283ac88}} in certain parameter regimes makes the power-law resetting protocol drastically different than the constant rate resetting, which corresponds to an exponential waiting-time distribution, with a finite mean and variance. Even a ... | r | 3938e7c2cfb2acc8b7fc40a0ead73dce |
In this paper, we have studied how optical isolation can be accomplished in three different models of topological photonics. A few basic ingredients are common to all three models. Firstly, the model must be nonlinear, so as to break optical reciprocity {{cite:4a128f0fdb9ed4bc19635a9436f9b8d6312caec2}}. Secondly, the s... | d | 938ae17ed2cbc9a96d5cf8807b5346af |
Beyond the case of a complex inflaton and Q-balls, an additional motivation for this study of Q-ball solutions is the possible insights it may give into the case of a real inflaton and oscillons. A non-minimally coupled Palatini model of this type could also inflate successfully for the case of a real inflaton, and neu... | d | 40af9148c1da6c4b8696d455c66c8463 |
Berkley Deep Drive 100K Dataset (BDD) {{cite:e5c5d2290c9d10aaeb8592d43d6c7446e3ced0bb}} road scene dataset, with {{formula:eaf81687-2d00-42ca-af42-1e555bbd4a36}} frames used according to the official {{formula:c943aa2d-ae31-45a4-8043-eb9fdee04d85}} training/validation split. Models trained on BDD are also tested on ... | r | 531e627ca0cba4359ce8ddd3310ab1a6 |
The basic building blocks of SF-QED are the Compton effect (photon emission by an electron) and the Breit-Wheeler effect (photon decay into an electron-positron pair) in strong EM fields {{cite:409bdc20ee5ba5fbdbac3d9aa76fabd7d8b60902}}. It is most convenient to characterize these interactions in terms of Lorentz invar... | i | 321c9b002a8e17c3560e4c13d863dd88 |
Park et al. 2020 {{cite:9a26aecc23751f9f770733d66831881bb332aa96}} Conv TTFS 68.79 680 0.084 0.04 29.94 0.99 0.79
| m | ade2ba803e7f0922782e0c8d6e85d1a1 |
Note that the state-of-the-art results on Kinetics-600 are about {{formula:c28f7de1-827a-4565-93c9-8b07f61a3b9b}} {{cite:904fe48aac302bc8979fcf240e130cda35b146f8}}, {{cite:da69ef741f8402dc0e77327f4cc8dd05d754b0e4}}. As mentioned above, these results are generally obtained using various mechanisms that are orthogonal t... | r | 433a72ed6975725302726d26c10cb217 |
Our analysis is based on fifteen epidemic datasets (influenza, dengue, malaria, and hepatitis B) collected from publicly available sources. The dengue datasets have been used multiple times in various studies for formulating better epicasting techniques {{cite:ed1a2ff65bc877edb1de854c6b61996e63041baa}}, {{cite:82829da9... | r | 2b7bfb6950852ec9a9a145268bd05af0 |
Table REF shows quantitative comparison of these methods on the same testing set. It can be observed that 3D U-Net {{cite:599167759b7b67abe8e96c9b3236e3c9d31ee961}} got the worst performance in average, and the results of U-Net cSE, U-Net sSE and U-Net scSE demonstrate that using attention networks helped to improve t... | m | fa386d5478214c51d1d236caf0e6f067 |
It is helpful to point out in this paper, we will think about JT gravity and its {{formula:b7df5088-c447-48ff-a9df-9edf317267a9}} deformation from the point of view of the matrix model dual rather than the boundary dual theory. This is because, as shown in {{cite:2bf07c50bdecc6b0fe5cc67b3dbd0d4b9c28bc27}}, higher topo... | r | 8f9aaea059f5ac7dacff613ec373d1ee |
A drawback of our study resides in the small architecture used on medical imaging scans. Extending our “measure preserving DistGP” module to larger architectures such as U-Net for segmentation or modern CNNs for whole-image prediction tasks remains a prospective research avenue fuelled by advances in scalability of SGP... | d | 77b93aef956e7ce436b82f63652f1085 |
Truncating the summation in (REF ) based on this approximation reduces the maximal time evolution parameter (i.e., the maximal value of the parameter {{formula:18950f26-5464-41f5-a682-971b4b0b3424}} in the {{formula:ec88f232-29d2-41d6-9f34-b94ad178037a}} terms) quadratically.
To make this approximation precise, we us... | r | a17f54e395c4509317ffb1ad9d58400c |
It is straightforward to apply the FDM to a geophysical flow model on rectangular grids. These were the first methods used {{cite:fb3f6152939941157626453ecdfa5f8433faae5f}}, {{cite:097d364647355f4138e51d94b4922773d57acce2}} to simulate geophysical flows.
In particular, the Arakawa grids were introduced by Arakawa and L... | m | 87961e8bb847cd35a160c0b9e17f317c |
The most important corollary and main motivation for proving such theorems in the context of extended fermionic lattice systems is the rigorous justification of linear response theory {{cite:78abafb8a2ccf8775983db6c714ed5477022cb17}}, {{cite:3c68ecc7dd6b4a65e340a4bb07dd18e7439e24ca}} and the Kubo formula {{cite:2c36a60... | i | fcb299f61206fa8a7176f2d45718adf9 |
In Figure REF we compare the texture similarity of images generated by our proposed method with real samples based on SIFID{{cite:78f25c7d2640ca260d12823e5d1493d126b2a901}}.
{{figure:7ec689b9-2360-462f-9ad4-419a9698d992}} | r | 2f96c31437f1a872c53bb5b72e6c3935 |
We propose a U-net-based {{cite:c9627c0c3fcd0cde8fccc70669026d657c396e0b}} multitask structure to incorporate instrument recognition with music source separation, which we refer to as Instrument Aware Source Separation (IASS) system. An overview of the model is shown in fig: model.
Although the multitask approach shows... | m | 7f50f31f50b96f1e6b5dbd748fa9113d |
For further assessment of the proposed network, the gradient-based class activation mapping (Grad-CAM) {{cite:ddb39a6ff099e3975402d6cd0cf93e7d4d1befcb}} was employed to depict the decision region on a heatmap. Fig. REF illustrates the class activation heatmaps and superimposed images for three sample images. As can be... | r | ac723e157217124a68e2001ae8ded9be |
In this work we stray away from an all-encompassing definition of an outlier, rather focus on a definition for the one dimensional case in terms of order statistics. In a sense our definition tries to approach the problem from the point of view of investigating data points "that arouse suspicions that it was generated ... | r | f1ccc79cf1174b9367ba62867bb98fdc |
Defenses against physical surveillance. We adopt a systems-view of the problem and reason about how various stages of the CSIS pipeline can work together to make physical surveillance attacks harder. First, one could leverage the recent progress in defenses against adversarial examples to make computing poison delivery... | d | 22d1774955455db672d52725c07c6de8 |
There has been extensive research in the field of
gravitational collapse. Since the pioneering work on the gravitational collapse of homogeneous dust,{{cite:9079a25840ad91c9372346aab5ff3ade93726b73}}{{cite:a32eb87280b85f55cdccfba4da423e9843187640}},
it is now accepted that for a gravitational collapse of homogeneous pr... | i | d438d687feb503a1c276726ba3b152de |
In NAS method, there are three major components {{cite:1da012f39d7dac90885b1468dbd6a79e9462f847}}: search space {{formula:4ca208e1-02f7-440c-8e85-3deb083a2458}} , search strategy {{formula:5db6965f-ff2e-4654-8367-3f9129040f21}} and performance estimation strategy {{formula:3417cac5-a542-4a8e-98a4-721f982f265f}} . Pred... | i | 7d59c82da818c8d8fc7f529148c9794d |
We are in the process of conducting comparison experiments between our white-box attacker and that of {{cite:cb061565ef402b0964e3d0dc99cbf2183f5a6426}}. However, their method does not easily lend itself to be used with the LTU framework, because it requires training a neural network for each LTU round (i.e., on each {{... | d | 3dc24512646ca5cbec168d6d6d657e11 |
Remark 1 It is established that problem (REF ) can recover the positive mean value {{formula:f24fe174-74c0-4b44-b257-735d80700eab}} without requiring any separation between the delays {{cite:4a94ef9af89454a4c6727866bf37455dcf3066ff}}, as long as {{formula:1e5e3acd-6cb8-473f-b8a2-4fda5a23bd1c}} , and
the estimated para... | m | a8545d81f6b9d12adba0a4de277bf18a |
Example 2.20
Let {{formula:b981f273-ae24-46de-8c39-1404d301ad63}} , a subspace of {{formula:509d9108-3566-4a7f-9266-63e395dd3bf0}} with usual topology. If {{formula:ad686fd5-39e6-4002-9a8c-b910a955efa7}} , {{formula:b23cca70-f4ad-4d89-94b3-0f69693a5d3e}} , then the natural density of {{formula:e95e4288-4c50-4a34-8c16... | r | dd5bbc1fa0f80bbb0113d03e1f22527d |
Wangerin {{cite:af661047203644ea02a64965b073ed2b3b4e78e3}} showed that Lamé's equation appears when Laplace's equation is separated in confocal cyclidic coordinates of revolution. Such coordinate systems can be found in Moon and Spencer {{cite:9d54cad75bc3e682681490f9ad610981c1fc816b}} and in Miller {{cite:443793b7c20d... | i | 179f67d6311b4630b613db055017c99d |
The spectra observed far from the electron at angles
with respect to the {{formula:98583da1-18c4-42a4-addd-aa3e039e3c3d}} direction are shown in Fig. 3.
The higher frequencies ({{formula:054b6ae3-f9bd-4df1-afef-f79ae66a0719}} ) are strongly damped
with increasing angles as {{formula:c4dec9a0-f48a-4a9a-8502-5c274acf26f... | m | 2e413bdb6253a2bafb7cc8eb597aaf49 |
The concept of FSL, however, is not new and has been introduced by several previous works {{cite:445ceacd06f96584bd0320656635cee2dede171c}}, {{cite:a6e99a9aecd578665e57a62bf385698260a52a15}}, {{cite:0a93c5328edc79a35db8fa5a03341913a00937cb}}, {{cite:9e788d2617ed00ac886ceb71d156fdf16a041415}}, {{cite:7fc30fbf13c88dce8b4... | i | 4f9cf3eda669a0d8d9d89ffb2de95509 |
It is a popular strategy in comparative effectiveness research to embed observational data into a randomized controlled experiment using statistical matching and analyze matched data as if it were a randomized experiment. As Collin Mallows famously pointed out (see, e.g., {{cite:17878ee6c1a8a49a7825743119ccf4e4a7c4d57c... | d | 9d821a0e05311be6f376aa5833c38e82 |
Before we describe our approach for the proofs of these results,
we recall the situation for the classical Euler equations (REF ).
DiPerna {{cite:8a66ef2169b5d03e0aa228beb2dacfec4ea5f3ef}} first showed the existence of entropy solutions of (REF )
for the case of a gamma-law gas with {{formula:fbebf964-9483-44d7-adba-66... | i | 63be13db0faaefdb97c2646eaaa1f08e |
Two BS candidates in {{formula:436bf0fb-c910-435b-accc-8ca12e57e37d}} -{{formula:c4dd15e2-b940-41a7-b58e-751d092de2ae}} (Fig. 12) lie on {{formula:a172a2e0-d360-4037-a012-49bef32d0352}} ({{formula:9cf938b5-4048-4f83-9240-e0991777e2a6}} mag) and {{formula:1812792e-4869-4063-83bf-79bab1f69231}} {{formula:5ef4dd75-c40... | d | 797bb56be9aca0b7288fc893b477050d |
The performance metric for the MAB algorithm is the regret which is proportional to the number of selection of the sub-optimal arms and it should be as low as possible {{cite:ff511008dc1576de5b7613cecfa314c8c9f027da}}, {{cite:3ff121381c7ab80b913c3c58dd3bd7304a463f51}}, {{cite:a45768c795309d04cbb80e500bb8d6ba670c9721}},... | i | 46f3cee445a0d4a046da76e3dce4b81f |
A version of the spherical top model constitutes the free part of an
effective field theory (EFT) approach {{cite:2c71095c51b1adacacf92b46e83f860b9aeab74a}} to the post-Newtonian (PN) gravity of spinning objects {{cite:4a416b5902a4329c881df3874747fec30332030b}}, {{cite:2914615b2ca82a03441f929f85610dbb3c44e4d3}}.
In int... | d | ed405ae833d1271636b570ea33f9eb8d |
The sub-Gaussianity condition above is equivalent to the following tail bound {{cite:304f5e1bb9db525b6d75eb4015389f94bdc4a2ef}}:
{{formula:72fde53a-86e8-4ae6-9f21-bb2019c4b78c}}
| r | c70d7f068949dae96a51cc83c9516036 |
Our works is based on extending Zhang and Bu (ZB) {{cite:2b1e32bfd24c867692325c6c8ef2c0be52b29ef0}} method for community detection to automate its operation and quantify its accuracy to correctly detect communities in benchmark networks. In order to successively partition the network into smaller modules, ZB method fol... | d | abc813a1904fcb906017ee821a586cf1 |
Research on SSOD boils down to answering the following two questions, i.e., how to generate pseudo bounding-box labels from unlabeled images? and how to exploit such auto-labeled data together with the previously labeled data? While these questions have been answered with some success, e.g., by Instant Teaching (InsT) ... | i | 7f3293d97d83349dfdbaffe3503d14e1 |
Electricity generated from renewable sources is a continually growing component of global energy production and a key driver for a sustainable energy future {{cite:a7c094fa691dc1265ca60db4a698be7ab89ee1eb}}, {{cite:22936c2ad82b300cc5702fb4586827d213ee068f}}, {{cite:3823d0d382875750591520b39755e92a1b4e2894}}. Further ex... | i | 4ff7f439c4cd7ae05eccb2e1603f0cd9 |
We conduct comprehensive experiments by comparing BasicVSR and IconVSR with 14 models: VESPCN {{cite:2106d45a958829148fcff89b8d8d489512f782fd}}, SPMC {{cite:f1f601beb3ca2676f926eff4822062bc8224b578}}, TOFlow {{cite:bd89f1906c1ade7b07cf8df7c197fe2d767995cc}}, FRVSR {{cite:5ba77d31b63b21de623271a8c4b7db95129a4c79}}, DUF ... | m | 74759c2f674473a04f25d86617880c0d |
Despite the potential of panorama images, it is challenging to perform localization amidst drastic scene changes while simultaneously attaining efficiency and accuracy.
On the 3D map side, it is costly to collect the up-to-date 3D map that reflects the frequent changes within the scenes.
On the algorithmic side, existi... | i | 3a628933e3acb304b11de729a1402018 |
There are a handful of demonstrated methods that modify the training procedure to achieve better tradeoffs between the final model accuracy and the time to train the model. Some of these methods include Blurpool {{cite:37b7558b395b1b0ce2871f4f727cc44d32606563}}, Channels Last, Label Smoothing {{cite:274d6078a8d8d6cbc2c... | m | 06ee054234dca82398292161756ff11e |
A major advantage of the proposed method is the possibility to distinguish between epistemic and aleatoric uncertainty in the predictions.
Capturing epistemic uncertainty may be especially important in the area of atomic structure analysis.
In some other areas, where a lot of data is available, it may be sufficient to ... | d | 6120514b58f6836ee691190398521825 |
The numerical results presented in this paper for defect detection have shown that the FCN-based ultrasonic inversion method can be a useful tool to achieve an accurate quantitative reconstruction of multi-layered bonded composites. Compared with other conventional inversion methods, the reconstruction costs of this me... | d | 26bbb9f2395d88ad25552bd47067cd62 |
By noting the design choices and their rationales, the desired ML model is described in humanly readable terms and ML developers thereby produce a pre hoc explanation of the expected behavior and justification of the model, similar to the preregistration of a scientific experimental setup {{cite:e7df49e0d581b2ad40370e3... | d | 5f08c5d98ddb898ddf8e1136529f43b9 |
The proof of Theorem REF follows this roadmap:
(1) We first show that the model learned with UMix can fall into a
specific hypothesis set {{formula:4289c348-f292-404b-8d60-a43fef485a02}} . (2) We analyze the Rademacher complexity of the hypothesis set and obtain its complexity upper bound (Lemma REF ). (3) Finally, we... | r | af1520066bdd355431441676302c9ad9 |
In this section, we first present the overview of BinsFormer. Then, we introduce our instantiation of the adaptive bins generation strategy with the help of Transformer decoder {{cite:4a42b5d150bb858db34a3b33a58929c1c24cd253}}. Finally, we present the auxiliary scene understanding task and the multi-scale prediction re... | m | 7677cb16c07ce235da9871247a05b0ab |
Higher dimensional black holes and their properties have attracted considerable attention {{cite:a34ef5c3d9d9de54cb66fc6b4fdf7a567d9232a9}}, {{cite:9125c3787eb115bc7f2f99ddbe3937bd1c9ec238}}, {{cite:de681cb75081496e41d8a8c7fff41df1e55cc012}}, {{cite:1bfd3546678ac3e6bc6ebc17c9dd2cbb4cd1cc94}}, {{cite:c1263d9a9b1d3becf79... | i | aeb9ecf28cc6a560939707f43e47967d |
On the theoretical front, it is of interest to extend the work of
{{cite:453f78ef1a320492cf7c8b9b81954ce718a86048}} to binary tensors and investigate
conditions on the signal-to-noise ratio to recover true factor
matrices from an observed binary tensor with high probability.
Moreover, the optimality of model selection ... | d | ee3c2be5c18a4d99f06a850ffdac1534 |
Implications and limitations. The finding that methodological tools might affect scientific progress is factually known {{cite:9a7a43bf853b197241897a2a7fa6a8aff9fa10ad}}, {{cite:3bacc12146712b6b865f9df40f579f7b9628ccc4}} and being studied extensively by statisticians and meta-scientists alike. Model comparison methods ... | m | 4289cd1fd14322b6ccf04ce61b97cad5 |
Deep learning has elevated the performance of speech enhancement in the past decade {{cite:200b4c28a40e8ad1366b9589ae1c7531f6682c26}}.
Since the very first success of deep learning in offline enhancement {{cite:c531512161d629a35da608d084d7769b231fbcb7}}, there have been growing interests in using DNNs for low-latency s... | i | a4b77c1bd51ceb1a514e243a762b568e |
The zx-calculus is a high-level and intuitive graphical language for pure qubit quantum mechanics (QM), based on category theory {{cite:4fedb160b3a4c22fd85e5fd68d2ff5f17b358e06}}. It comes with a set of rewrite rules that potentially allow this graphical calculus to be used to replace matrix-based formalisms entirely f... | i | f43bbc44ee43c800d75ff60f944594ca |
In this section, we will evaluate the BER performance of the proposed algorithm by assuming perfect CSI. We consider the average BER performance with a sufficient number of realizations of the channel. Specifically, the corresponding channel matrix is generated according to (REF ). The channel coefficients are randomly... | r | f2461ca209068ced3f1cb0025524d272 |
In this subsection, we study the shadow of a particular rotating solution, in order to show the applicability of the results presented in Sec. and . Our seed metric is the spherically symmetric family of generic magnetically charged regular black hole spacetimes, proposed in Ref. {{cite:da04ac8aab51677304e4717825f4899... | r | 2cafdb19fdf296c695c89fa4a7d23f33 |
While approaches that average the word embeddings for a sentence
are comparable to state-of-the-art results {{cite:b9371268935973cbbe9b424810d27817c211714d}}, Ave and Retrofit do not perform particularly well. This is likely due to
the fact that logistic regression lacks the non-linearities which Iyyer2015
found helped... | d | 0167711fb372ff71fa12ded253523917 |
In Figure REF , we plot both the 90% EB CS on {{formula:3645790a-63f9-4661-9048-73812c26658c}} (top) as well as the corresponding sub-exponential e-values for the weak one-sided null {{formula:acb3c7b8-a6ae-4759-bf08-210f8f75b464}} (bottom), between HCLR and IDR, IDR and HCLR_, and HCLR and HCLR_ on 1-day PoP forecas... | m | 4373a9085d6bc646f197ac7c36c8f975 |
Furthermore, Transformer is a type of self-attention mechanism-based deep neural network that is
wildly used in natural language processing (NLP). A transformer has been developed to satisfy
computer vision because of the strong representation ability recently. The use of Transformer performs
better by comparing with o... | m | ea6102bd3d3b1b8dd0fd41de1f70c352 |
Perturbation-based attribution methods start from an intuitive assumption that the contributions of certain input elements can be reflected by the changes of the outputs when these elements are removed or preserved only in the input. However, to find the optimal results, theoretically, it is necessary to traverse the e... | m | 29670438385b6183bbf9bdc507961f42 |
Encoder Module.
Our method adopts a CNN-Transformer hybrid model design instead of using a pure transformer, which uses 40 convolutional layers, to generate multi-scale feature maps. Such a convolutional stem setting provides two advantages: (1) using convolutional stem helps transformers perform better in the downst... | m | 6e7f7b4320d09f16091f7ea7221f926f |
Contrast learning has been successfully applied in the area of self-supervision learning ({{cite:ea955306170fac06a51b840f01df0425353cfa4d}}, {{cite:705b758293166193954cf34ce17a2813afa3982b}}), especially on computer vision tasks ({{cite:ce5d0fb3c3465a403671f24ef244f541a2f8a3b5}}).
Many extensions and improvements have ... | m | e534cd9cee8360af0856c7f14b09c278 |
Drowsy driving continues to cause accidents. Therefore, an accurate drowsiness state classification is necessary to prevent road traffic accidents. Physiological signals are frequently used to estimate mental states. Especially, EEG is capable of measuring brain activity directly and monitoring brain activity {{cite:4d... | i | 3faa41fe13b8e4b1843e3985096e202b |
Previous work in ABC reduces the data dimension by seeking low-dimensional summary statistics designed to retain information about the parameters {{cite:e41098743856b4feb86ef53bad392d0489685d1d}}. On the other hand, for conjugate linear–Gaussian models, {{cite:966df2ac20e459fdc30257baec568b670cfafc0d}} find maximally i... | i | c2da45657de72ae7cb859f79d64a0c63 |
From a neuroscientific perspective, it is interesting to conjecture whether a similar power-law code with a similar exponent is a hallmark of canonical cortical computation, or whether it reflects the unique specialization of lower visual areas. Existing results in theoretical neuroscience point to the fact neural code... | d | ff0ddf412b8cf81da4b44c4c5b9ec053 |
A set of user requests (or topics) {{formula:62b95eaf-2b6b-4c83-a9b9-58a722c1be7e}} in the conversational form (e.g. “What is Fickle Creek Farm?”) with a label reflects if clarification is needed ranged from 1 to 4;
A question bank which contains possible clarifying questions collected for the user queries via crowd... | m | c3ff3deeb70a04435fa613a831d5fda3 |
To overcome these problems caused by traditional ULAs, nonuniform linear arrays (NLAs) (also referred as sparse arrays) were introduced {{cite:dff3699df9484aa9075385aba3d69cb2cd110a9b}}.
Consider an {{formula:84be8187-2491-430f-83bc-99f36dc9e1b5}} -sensor NLA with sensors located at {{formula:1e3a2bc9-c7d8-406d-85d5-43... | i | b2e291d4fe61c6f0b098b158d486db35 |
In this section, we extensively compare our frameworks with previous methods across
various datasets and settings. The other compared state-of-art results are from {{cite:fab2bc87d55b9ad5072a9d8531d041f5a881360c}} and marked as *.
| m | b7c2061d76e62a92d9910a9ba80b97b2 |
There are many interesting extensions to the results in this paper to be explored in the future. First, as we have mentioned in Remark REF , our results on the connection of Riemannian and Euclidean Hessians are established at FOSPs. It is interesting to explore whether it is possible to connect the geometry of the man... | d | 1c18d5d5569cb38cf724568f8304bfd5 |
We evaluate four recently introduced personalization methods, PersFL {{cite:a999cbe8aea3ec1a6c2e39bda69a5567cbf67ecc}}, FedPer {{cite:354bf13aa9f49a5c98e981f84e8f0c9a6c8f6b9a}}, pFedMe {{cite:64b193734d297cec327119b27dde42c06b35bbdd}}, and Per-FedAvg {{cite:79c266dbad517388b4c9c8b7b9c4c4ae47d66eaa}}, to evaluate their ... | r | fe8352ef298567ab7c50a20d0b848da9 |
The universal approximation property of neural networks (see {{cite:e132b7ed841023184b16f4da1c2f5f33366460a7}} and {{cite:d02f908c4b4f1004595583cb1ac4b7c76a2d0e32}}) might make us assume that GANs can simulate any distribution from a Gaussian prior. However, neural networks, as functions are by design almost everywhere... | i | edb69e1caf066caa3f9fe1dd1a71ee98 |
In this section we numerically compare the classical deep ensembles {{cite:2ac8e9051b816479a32179c7f2b11d58ce287536}} (DE) to the introduced extended approach (DE extended). The implemented code including additional examples is provided BayesianDeepEnsembles.
Following Algorithm , the network training is exactly the sa... | r | 14b08dd8c171aabe65288c27ef17b924 |
Speech emotion recognition (SER) requires a dataset that includes rich emotional utterances and labels. There are a handful of SER datasets, for example, IEMOCAP {{cite:c15f45789e919b1ec673d8ab517da4d3cb5a58e6}}, EmoDB {{cite:c56b77ad8956dee04c83c63e82e088a72f768021}}, RAVDESS {{cite:7da715c1071a529acd947580352f7d87707... | i | 7586dc67662ddabac082e7199723ba0f |
In Table REF , we compare the zero-shot classification performance with existing approaches.
Some models require extra pre-training on 3D point cloud datasets. CLIP2Point trains a depth map encoder on ShapeNet dataset {{cite:184df7fdd50a2e78eb66dd4afbdfd80cd46add7f}}, and then uses it for a 3D zero-shot classification ... | r | 7ca21a2241ebf62149de76fa0f87904f |
Rough set theory {{cite:eb4a563cdadff9bdac2e2ba13481e9bebb4326e6}} is an effective mathematical tool for dealing with inaccurate, fuzzy and uncertain data, and it has been successfully applied in many fields, such as machine learning, pattern recognition, financial analysis, decision analysis and etc.{{cite:05d87a71e3d... | i | 1326f15fa6b941666b00e36b44d4ff06 |
When training AVOD, we follow the methodology followed in the paper proposed by Chen et al {{cite:cc596b66ef934261f2f48c831c36f4782091198d}} on the KITTI dataset {{cite:6b620c3169b524903716f91a052ef295c0a01a62}},
We split the trainval set into a training set with 3712 samples and a validation set with 3769 samples.
W... | r | 90ec82522ee87a54b9f803717d4a7950 |
Our survey area covers the entire extent of the deepest portion of the M101 H1 imaging survey by {{cite:29d51e6f39c83cab47dd06780c0cf6d8954d54c5}}. That survey had a limiting H1 column density of {{formula:d9f98039-2f46-4ac9-a26c-fe8b01872735}} and H1 mass detection limit of 2e6; for comparison, that survey would have... | d | ea80affd51583da10c723b7d4e25ceab |
Unfortunately, UCBVI {{cite:87da2d75c069efbd4b8fcf8e998a96c55836f51a}} does not fit into our framework. However, even if it did, we argue that it would not lead to improved results. Indeed, the algorithm makes use of Bernstein's inequality to handle the estimation error, resulting in the need to bound an additional ter... | d | 8b98d4fd439aba4aabbdd91ddc1e31e8 |
TTFS {{cite:6ea459296297ab06b09eba244057967b104b4dad}} 99.31 99.20 98.76 60.58 83.45
| r | a94451be91e9572d01021c259f6a1c90 |
In Section , we listed the different challenges inherent to a sub-percent calculation of the leading order HVP. Interestingly, they do not affect the same time ranges. If discretization effects are mostly important at short distances, FSEs and the specific treatment of the tail of the integrand become more relevant at ... | m | 1223222d4dfe7951654bec11849fe0ff |
Sampling numbers may also be defined without imposing the linearity of {{formula:f53b9752-e05f-4863-a48e-ec916d997bfd}} ,
leading to smaller quantities. In what follows, we shall establish upper bound on the linear sampling numbers, which in turns are upper bounds for the nonlinear ones. We refer to {{cite:43566cac5ac4... | r | a6e4aab1659a49d21abbf4fa95939326 |
Note that for {{formula:2376b065-f39f-445c-880d-4e9cb539846e}} the space {{formula:ed4dbcfa-2dc9-4c5d-b8d0-f49e8acbebd5}} coincides with the Lorentz space {{formula:60cae310-6031-41b4-9f63-ccae84d500df}} , which consists of all functions {{formula:29262d53-49e2-4d04-b003-b0a802526f36}} such that (see {{cite:ad8c114f... | i | 45ebc48853d0ff1f130651b79940a8f2 |
We next consider three parameter estimation problems, and show that MMD has a benign landscape for those. Namely, the MMD objective has no local minima and all its saddle-points are strict. This implies that gradient based methods can find a global optimum {{cite:e662e7c5dc02798fddffcd75963f6367f39e76cf}}. We focus on ... | r | 651e54f3eed054e761503f985fcebec6 |
However, most of the state-of-the-art DA methods for medical image segmentation require that the source and target domains have the same set of anatomical structures even they can be from different imaging modalities {{cite:eab230d89fbdd82bead10e7e9efdfaa81bf7b064}}. Such a requirement prevents these methods from lever... | i | c66612b1bb0616acf996c7f39c2580e3 |
Model-agnostic methods on the other hand make no assumptions about the internal
structure of the model and depend on the relationship between changes in the model
inputs and model outputs. This is achieved by training a global mimic model to approximate
the original model, then locally explaining the mimic model {{cite... | m | 8b3b1cc3701c107da2d49b2b1d3be453 |
Even in transductive setting where the baselines claim their primary contribution, our approaches still significantly outperform them on five out of six datasets. Note that our models achieve almost perfect scores on Reddit and Wikpedia when the baselines are far from perfect. Meanwhile, the strongest baseline on these... | r | 9ad9728169a0417c0261aa1f0d0563e7 |
The addition of the MMD cost function term significantly improves the results of regression in the low data regime. Furthermore, to the best knowledge of the authors, this method achieves state of the art results on the embeddings of {{cite:0cac7223ab159ae2a919b0d47dfcd3f0bbe3ea59}}. The authors also experimented with ... | d | 874ee158a482935bf181279a73205de4 |
In this section, we present the experimental results of the proposed metric for various standard GANs and datasets.
We use {{formula:1bb9a1ef-75a7-45b2-a585-05a51752c12a}} for the manifold approximation which is used as a robust choice for the size of the neighborhood in {{cite:acb2873cdd6a3beb4ad527f57c2480d02a6f38aa... | r | 9a9bd2cdefd188b4c0921400b9b67a1c |
where {{formula:7d350e4f-8e9f-4866-ad14-24529a5a1667}} is chosen according to some predefined principles, {{formula:19f225eb-db84-4c54-bf43-16c07b414218}} and {{formula:59dfb98b-1b22-4ac4-90ad-854210b4c4c5}} is the relaxation parameter. In the original work of Kaczmarz {{cite:497ba125553df319e066d1938a1b968e7ea69c16... | i | 44cd445cd114a36680c4be15696c91b2 |
Quantitative results and comparison to the SotA approaches: Overall, our model outperforms the SotA approaches by a clear margin on all datasets except the Stanford Dogs {{cite:e755041e90ad76b7a19b70b2aa8ae1d4900a52ef}} and Oxford Flowers {{cite:40abd36b4831d6b69638e2fd3dbdcb1ee01a280b}} (Table REF ). In Table REF , we... | d | fc714f6010d57a06184c88ef3f0d5e94 |
Table REF shows the result of our evaluation of MobileStyleGAN on the FFHQ datase. We compare the number of parameters, the computational cost and the Frechet inception distance (FID) {{cite:7c21ce2c50b2dfa856f7acfbe49d03a8da599cee}} of MobileStyleGAN and the teacher network (StyleGAN2).
{{table:5caddc8f-036a-4cb3-8e3... | r | 08a01212a49535d80fc15f67091145fb |
Acknowledgements. This work is supported by NTU NAP, MOE AcRF Tier 1 (2021-T1-001-088), and under the RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) Funding Initiative, as well as cash and in-kind contributions from the industry partner(s).
tocsectionAppendices
Appendices
Details of the S... | d | 50154904bdf9ea1618f88507cfd85653 |
There are two critical metrics to measure a CAD solution's effectiveness in clinical settings: generality (handling of unseen patients) and precision (generating good accuracy robustly for the given task). Naturally, incorporating as many patients as possible for training is desirable, but patient data often cannot be ... | m | 797341529ab1d380c6da4c078a2d6326 |
With the recent rise of neuromorphic {{cite:cea393abe136e06cd0f4fa838a99ac2cab6f3b3f}}, {{cite:1e800da67ee77f56b7c5b13e664cabc1cd205f11}}, {{cite:ebdf69292c857fdb9db17246f1a0c4dfa3f59c16}}, {{cite:7363c73541736d24bf74f21f6b3497d6192097eb}} and edge computing {{cite:fd62615d8c8d9f7074bcbb02189cb6655be13053}}, {{cite:d8e... | i | 212d16ab9cf78a551484a155a8d0a33b |
To evaluate the quality of generated images, we adopt the reconstruction metrics Peak SNR (PSNR) and Structural Similarity (SSIM) {{cite:e924a910786176dd786dd469f51989970afaf6b9}}. For the lip-sync performance, we verify the recognition accuracy and F1 score of the five selected speech-related AUs in generated frames. ... | r | feed1eda0b2d644085f2f4eadaaafa72 |
Assuming the foreground and the background are well separated, the intrinsic clustering term does not contribute to the correlation of Eqn.(REF ), and therefore
eliminating the impact of the galaxy bias. For {{formula:3202c732-e06a-4353-be23-fe1d3b5ae662}} , it is {{cite:6e2639a785439f270eee6926bea9aa67209f5040}}, {{ci... | m | dc7d0e28db5ad724570861a52415d4da |
In examining the evolution of densities, there are three major types of behaviour that may occur and they are ergodicity, mixing, and exactness {{cite:376d58be9c7e52f61a116e12648bd4eba556027b}}. In addition there is a less well known fourth type of behaviour called asymptotic periodicity (or statistical periodicity), a... | i | d2fac5a8d9fb4df251fb4cf914bc03b4 |
A common extension to this question is the single dot product problem: “How often can a specified dot product occur between {{formula:56abae10-28bf-427d-8449-f6f44ead3f8e}} points in some ambient space?”. This has been studied in {{cite:e8176786f5f0ecf277532df5eb7f7e883edde80a}}, {{cite:79c1124bb5ce95d7eb58641dc3d9ae7... | i | 386b8b990b1097e9c16b01afafcb8a0e |
However, the performance of RGB SOD models tends to drastically decrease when faced with certain complex scenarios (e.g., cluttered backgrounds, multiple objects, varying illuminations, transparent objects, etc) {{cite:67dfecc9df1d87f2c7348f375af3847391027b0d}}.
One of the most important reasons behind these failure ca... | i | 876f8a6cabc8a1ad47516bec800baba0 |
Translators have been widely studied in literature ({{cite:aa48c01818a22271b6ba78cee21b14c913f73072}}, {{cite:c667ff7356030fac1936830ef8798433264446e2}}, {{cite:29fa4285f39a79633e63cdcec6369811d02d7afd}}, {{cite:892bb4f2b0529cf3cef0e3a4dd1d635ae5791586}},..., and references therein). For instance, they naturally appear... | i | 587a711086c64f8094190cb1f4bb8955 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.