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which is satisfied according to (Corollary 4.8, {{cite:42e9351356f46bf2fcf582c70b20f4a0535cb1bb}}) and (REF ). The second line of condition (REF ) is voided since {{formula:fb2a22bc-0c45-485e-89c8-4419cf13f2cc}} commutes with {{formula:84529ee0-cfbf-4d6c-994b-f85624332d61}} .
| r | 4246cefc93f50db7fb925fe509cbcb4c |
Now, we will look at the calculation for {{formula:3fcf1e62-93fd-4194-80be-22aa6282e56c}} when {{formula:f89c293d-d06b-4425-ae12-8f2621b25b5d}} in the magnetic field interval shown in Fig. REF . It is worthy of mentioning that the case of {{formula:6f7dc8bb-7fac-4a08-aada-55c95dcd52d7}} and {{formula:9558cff8-a037-4... | r | 2a4719b07be17f5664f401eb6374aaa9 |
Location problems with distance constraints have received little attention within the vast literature on location problems in OR and related areas. There are some early works that considered maximum distance constraints between the demand nodes and the facility locations {{cite:a31ae4e4b893a29c03d9cb471d719410421bae59}... | i | 6a09c1abe08c33e01634481eb244d055 |
Observations of PSR B1259–63/LS 2883 have also been performed in HE gamma rays with the large area telescope (LAT)
onboard the Fermi satellite. As part of its full-sky coverage pointing strategy, the LAT monitored PSR B1259–63/LS 2883 during its last three periastron passages in 2010/11, 2014 and 2017 (see e.g.
{{cite:... | r | 918ee93d528dbb5b638d857b90fb020e |
In this section, we state our results. In Section REF , we consider the large-scale kernel ridge regression (KRR) problem. We generalize the Fourier transform result {{cite:29d4d05d790124af97039edeaf4f871164eee32d}} of accelerating the running time of solving KRR using the tool of leverage score sampling to a broader c... | r | ec441c1b9f254a027469bafed58b3da9 |
Results on Head Pose Estimation.
Tab. REF shows the comparison results of our methods with several recent head pose estimation approaches.
SVR {{cite:acfcb7fcf6b6eb9d3b5e300b6c0c8b942f85a442}}, RRF {{cite:c9fe8314428d0390b4f61e56185de788c04f9a44}} and KPLS {{cite:c1394d534c76bff575a940c2d7b02dd712d21363}} are all conv... | m | d55b34a5d244c91e5883d2b3550db559 |
The gauge/gravity duality and for that matter, the AdS/CFT correspondence {{cite:819dcfc2dae8e6397555c18f01fdfe066edcc144}}, {{cite:e6dbce007553c0d73d58b9e233bcb02d98e3c0e3}}, {{cite:717cc0f82a49cd692d7daeafd55b203ce0d5e520}} provides a significant improvement of our understanding on quantum systems with large number o... | i | 3684ec0c25188a566c37e88a38077f63 |
Another limitation is that the level {{formula:1a423bea-8ae8-4bb5-b11e-a38b689589ae}} is considered fixed. This is also needed in the proof, and is specifically used in the bound (REF ). In some applications, especially in multiple hypothesis testing, the level {{formula:11019d7a-a65c-48fb-93f8-7333763c5bae}} needs t... | d | 1b3880885988e14507bede33389fb43b |
Virtual Camera: preprocessing of unified camera's intrinsic and extrinsic parameters.
Front View Backbone: the front view feature extractor.
Spatial Transformation Pyramid: Projecting front view features to bird-eye-view features.
YOLO-Style Representation: Head of detector base on YOLO{{cite:8608f76b44c3c72956e306... | m | 2cdcbfd635edb1e1ea826cb8d298c72e |
where {{formula:26fcfd6b-aaf5-4617-829d-faca12b62735}} and {{formula:d107df06-f0e8-4b31-a066-f94b181d7c3f}} represent the exchange interaction in the unit cell (intracellular) and between the two unit cells (intercellular), respectively. And {{formula:7bb256cc-47ef-49b7-9aa1-c7da59064d2f}}
is the easy-axial anisotro... | m | 993a7a9d28cfb41c3da18aaa615df19e |
The advantage of topological spatial descriptors is their versatility in analyzing spatial and temporal structure in complex data. With the flexibility of PH to propose and adapt different filtrations, the standard PH pipeline can be tailored to study a wide range of other spatially patterned systems.
Here we showcased... | d | 47dfa518f8bbac468deb70fc2a7e78dd |
To demonstrate the effectiveness of our SS-CADA for solving cross-anatomy domain shift, we compare it with several other methods which can be divided into four categories: 1) using only {{formula:047e799b-8bb1-4b10-acb5-3c5299e3d643}} : A standard U-Net {{cite:9a126600fd24992537c489b2b923a5b8cebeb3d3}} is learned only ... | r | 3309a85eb0642d073c015f8f8e2bc33e |
For the NCT-CRC-HE-100K dataset, EfficientNet {{cite:99824352bc6558df00f71a03b275f1481b743f0e}} pre-trained on ImageNet was used for feature extraction. The training set consists of 70,000 randomly sampled images, and the test set includes the remaining 30,000 images. Table REF shows that ESH1 and ESH2 achieved the be... | r | 22a28bd0418e110427d5b184abaacfb0 |
+ ShaekDrop + RA {{cite:2cc83d2e8feb2d1c5fa7ad1dac31602d81b857d2}} {{formula:6a8b7dd8-0443-41e8-906b-b40b0e118c9e}} - - {{formula:88d982cc-1cb2-4870-8a8f-56bdd7aea754}}
| r | 4a481a0dc7a9be9e3048ffe6511fcefe |
then t:perp recovers {{cite:a28ba4a9ed636b44484d83ea4db020f895f48cd9}}.
Note that (see {{cite:3f96d20325e4ab5ae5fefccf4c308dbce1865fe7}}) a linear isometry need not be
surjective.
| r | a6641ee53bdf50f9af5da17142e530db |
The flare energy, which is expressed by Equation (2) given by {{cite:f35b155ef9ee2c8b4a23e84c05bf50fca32bad26}}, has been generally used to examine the level of flare activity in lots of studies in the literature. The studies of some authors such as {{cite:2a4dedad85bf64fed3ba290fd3136faadefb1fc3}}, {{cite:2f9b5ace89ee... | r | a5111f2556f515cf3aa60b8b9e7f8fce |
The effect of the well-known receding torus model {{cite:46add6e6f62fb6a719c025426d696be5807091e7}}
predicts that {{formula:12e803b4-44ef-4264-8df8-78a4452af835}} decreases with increasing {{formula:a584c7ef-a7af-4bd3-a7e2-6597618bcbac}} . Whilst our data marginally supports this prediction we find a stronger anti-cor... | d | 7b8912491351c648ef32f7d78f7e3971 |
The present paper illustrates the possibilities and scope of such signal-driven policies in the classical optimal investment problem with jumps, going back to {{cite:e710538e8be03b503232cb82dbcd4bd145c6bdd6}}. Specifically, we will assume that in addition to the standard Brownian motion the stock price is also driven b... | i | 6e1ec7ba5549d72199346216f490fa16 |
Our
results within the HBM
are given in Table REF , along with the ones from the literature and experimental data {{cite:44386ecd9f33039b25f1ebdc12e57eaa5cd6ac6d}}, {{cite:d101236ba6bb319457e0e1c49be3fabb9a2cf3a9}}.
Our values of {{formula:9a0e3d7a-a61b-439f-8d54-f7f16347bf98}} and {{formula:276206a4-78d6-4e23-84d0-4c... | r | 1cf19bfb138b9044db561bed99f374eb |
If we assume that the coefficients of equation (REF ) are rational functions, then the method in section also applies to the third Painlevé equation {{formula:f1949d98-b5f0-4c22-bbcb-60593bed747d}} . Recall that the first four Painlevé equations {{formula:9ea52692-1847-4cdf-b5d8-ac081dff293c}} , {{formula:19e3195f-7d5... | d | c635a62cbfd7037a9064fd9fb9853e4b |
These approaches are non-heuristic but arbitrary to some extent in that researchers should determine what to resample from the data. A classifier should effectively approximate the hyper-plane which forms a boundary between classes. If the resampled data does not fully represent the quality data points that are crucial... | m | 2cc31f0b9ae40fcc143927d82fbd627a |
It is worth mentioning that with the recurrent design of the architecture, it is natural that the parameters for each iteration are shared, whereas this is not the case for other approaches such as VNs {{cite:901c551db1d2ce566182fbfcf358db5c41806272}}. Similar to other DL-based unrolled network architecture, our propos... | d | 3be7d517af25af91a72a6883fa2665e8 |
For the distributed algorithm using alternating directions method of multipliers (ADMM) {{cite:0e90dceb459beaf6a140f0b11d774f99f9da7146}}, {{cite:a1a7f5d771693f14bc73da872ab54716507ee29b}}, {{cite:da45db1d3bdc257204085437c80fbee619800af7}}, it is hard to obtain the globally optimal solution of Problem (3) with {{formul... | m | 94c91b5e0c8b2576f0bca3fa250bad46 |
Thirdly, {{cite:82ddb366eb366d55608fea98c297d3df1b41ed2c}} consider a more general model in which {{formula:5a0f4293-bb69-46d0-95e8-50ace2095249}} and {{formula:b148cb08-7934-449b-9edf-227b124a74cc}} are not necessarily uniquely determined, in which case the above restrictions would actually have to hold for all vali... | d | de680b1367c5b244445b99808a022d3e |
To evaluate the performance of the proposed OESCN, we benchmarked it against the EEGNet {{cite:6dd9681a65cd91f2a3388d1192fc486cefb28082}} and the AFBD-SVM method {{cite:d44318e85e0b0b270afc423d0b85a65e77d0f580}}. EEGNet is a classic deep learning network with excellent performance for processing the EEG signals, which ... | r | d57c8c5cc9f2a1fa00dbd0c3d3274fbf |
The geometric interpretation of the SGD algorithm we have presented
shares these qualities, as the concept of moving pairs of vertices one by one towards an ideal distance is just as simple.
In fact the stress formulation (REF ) is commonly known as the spring model {{cite:54ee8b22ef1cf2930ba3814679870405cd70534d}}, {{... | d | 2eaa4678f81beb088b1698b1a80e2d38 |
Despite the simple implementation, our EGD has not been proposed earlier for user interaction encoding, and it has two important differences from geodesic distances: First, EGD is parameter-free with higher generalizability. The geodesic distance method {{cite:bba3333eaaeda98aa53411b5caf8c345ba77f57e}} requires a user-... | d | 68eba30d51ea7c05932653f0ab3243dd |
In this section, we present the details of the interleaving learning framework. There are {{formula:9da3a5cb-0026-4f9c-9ec9-389e0b0531d4}} learners. Each learner learns to perform a task. These tasks could be the same, e.g., image classification on CIFAR-10; or different, e.g., image classification on CIFAR-10, image ... | m | 99fa786e20570b4fdec087735e14dcbf |
Anchor-Free One-Stage Detectors. We quantified the performance of state-of-the-art one-stage anchor-free object detectors on the LN detection task in T2 MRI: 1) FCOS {{cite:45fba05045653a0b88f8736411c709075a42dfd6}}, 2) FoveaBox {{cite:7bd1441ddd29c21b5c8d92927f5f56d0d71da6df}}, and 3) VFNet {{cite:f0d9657f76361171f6c3... | m | ce57cc4ae492327c85bb61e113aa580c |
Lastly, we argue that the common task formulation, extracting a span or a paragraph from a single document, limits answer coverage.
To further improve, models should be allowed to generate the answer based on the evidence document {{cite:ec3e7d58b7c8adf4e8d890d775c7e3b69cc53875}}, instead of limiting to selecting a sin... | d | be3c825fc46af19b77fa7e21cf564a4e |
However, major works on network quantization like BNN {{cite:5baa0f8242140bec087c21cdf908bd29303c33b5}}, WAGE {{cite:049f56ab0fcd796f22cf8952bd46b2c3c6c0cd60}} mainly explore quantization on DCNN designed for object classification. Due to the complexity of pixel-wise prediction, semantic segmentation tasks have to use ... | i | a1b7e2e25456402bfcea495d657e1a88 |
Although the CMS method is also an expansion method, it can conveniently be carried out to the order of 15-20 or higher {{cite:0137b1ed1384bc66ad0f7e4b8bfcdf199746020d}}. Therefore, it enables high-accuracy computation of the high-order {{formula:03def503-3561-438a-8788-72e337c09c7b}} up to the order of the measuremen... | i | 5aa0822477eb91a0890d615fad84d0d6 |
The function {{formula:dc4a9a8b-b60a-49f6-b8cd-0cc0ceed9dad}} satisfies the differential equation
{{cite:6ab0bdeb04b071bb02c61af1da812233dc1eb92f}}
{{formula:50551c76-d1e9-426d-a805-940d3dd381e6}}
| r | d32fc2c27b1d771c87c80a1150fadf4a |
Three popular E2E models are connectionist temporal classification (CTC)
models {{cite:61c8c00cd9b5a342f707f7eeeccd0d35bee9fc49}}, attention-based
models {{cite:7f7f9dfed54985a8f961be19c222a80e1680a935}}, and RNN-T
models {{cite:b834e8b83a32ebcfa604124dd2ca22ba66cfe2ff}}.
RNN-T models are naturally streaming and can be... | i | 91e957b4c1b1316c2d453c61de340230 |
Gaussian beta ensembles, with a parameter {{formula:8ddc325a-8251-4282-8268-345cd25d2615}} , are one of the most studied random matrix models. They are generalizations of Gaussian orthogonal/unitary/symplectic ensembles in terms of the joint density of eigenvalues. A nice tridiagonal matrix model for them was construct... | i | b861c37ec15122a666dbfaa230af5fe0 |
The second method involved deriving the CME speed and Alfvén speed and taking the ratio to evaluate {{formula:9ae681c8-ca15-4f8e-9075-ec5c2dc913f4}} (whilst accounting for the solar wind). As it is possible that the shock formed over an extended region around the nose, we examined five traces over this region. We foun... | m | 1fdeef2d6a5396ae84787c52fe0e6792 |
paragraph4
.5em plus1ex minus.2ex-.5emPreciseBN. We note that recomputing population statistics like PreciseBN is actually how the original BatchNorm
{{cite:119009c3fa4eb69498c5c83c4f3e6eaab0ed41b8}} is formulated, but it is not widely used.
This paper thoroughly analyzes
EMA and PreciseBN under the standard ImageNet c... | d | bfa1ab84ba20b8c705b78b6331449ec8 |
Until the next era of surveys is being ready in order to set light on this issue, our main objective should be to find new probes (or new alternative ways to employ current astrophysical data) which might add information to the argument and be competitive with measurements for what concerns the feasible precision. In t... | i | e85f064b6acce935207d18fed7a6e27b |
In this workThe source codes for this work will be released soon. we apply EWC and LWF on acoustic models trained using the LF-MMI {{cite:09da395ac8090e77b761a906061459f55237926b}}
criterion and assess their efficacy.
Furthermore, as the main contribution of this work, we propose a sequence-level version of LWF regular... | i | 6d43120f8222a46996301a6913275840 |
Guan's {{cite:52f409844e38758eab2a9da61d7b24f93e50b997}}, {{cite:3a5a730246beef3026c74bb3a86ad5b41deec1c9}} proof of Chern-Levine-Nirenberg conjecture on intrinsic norms.
The work concerning Donaldson's conjecture in Kähler geometry due to Chen {{cite:adbd6fd6043f2c5537e556657b6c50c9715903ed}}.
For more related topic... | r | 1907c613926f64cff15bf2c57bf02e65 |
Finally, the search cost of quantum embeddings is significantly higher than searching for classical neural network architectures due to the computational limitation of near-term quantum simulators. For example, candidates in neural architecture search are convolution neural networks involving up to millions of paramete... | r | 0bfff24aae7617cc78416fbc59af921c |
Another possible direction is to compare the model with human behavior in empirical or experimental studies.
Group-structured populations could better describe human behavior than the more traditional well-mixed population model because human relationships often involve a limited number of people.
At the same time, it ... | d | c9b8a01d598a5d7e0c131e2cce0cc0ba |
As commented by {{cite:06051b2b5601ba305e5fd7fc28fb81cccd4d8a8c}}, “PPR does represent an important intellectual advance, one that has blossomed in its reincarnation in the field of neural networks”. {{cite:06051b2b5601ba305e5fd7fc28fb81cccd4d8a8c}} attributed the low popularity of PPR to the computational issue, which... | d | c957c6df114c1008d06d11cc5f0eae0c |
This section presents an application of Algorithm REF to the
Douglas-Rachford splitting method for finding zeros of an operator
{{formula:6df5e737-f959-4444-9d52-babe6a288346}} such that {{formula:6b21b4af-dfe3-4e4e-88b5-27090acf7601}} is the sum of two maximal monotone operators,
i.e. {{formula:6295825a-57a7-4432-8... | m | 6cdd2aba5f9de0ec8459a15c31d3d54c |
To tackle this problem, unsupervised domain adaptive object detection (DAOD) {{cite:54f45929a343b5d97106da5fa96dec4e520975f0}} attempts to train an object detector on the labeled source domain that can be generalized to the unlabeled target domain. Existing DAOD methods {{cite:54f45929a343b5d97106da5fa96dec4e520975f0}}... | i | 7b06f14fe8284ea3af26a7db560c85ed |
Hard clustered FL's second challenge is that it cannot effectively exploit similarities between different clusters. Though FL clients may have non-IID data distributions, two different distributions may still exhibit some similarity, as commonly assumed in personalization works {{cite:b90ac7d3518547a2cd40c5d1efd174c87e... | i | 80d7229efaf588c4f554a8dddf76784f |
There has been a renewed interest in the study of quintessence models within string theory and supergravity.
This interest has been sparked from the difficulty to identify controlled de Sitter vacua in string theory,
and from the various swampland conjectures that restrict de Sitter directly {{cite:f517d0a9246c15fce308... | d | 22070763b51e440f5409d647b16238ae |
For the diameter and the mixing time it is not clear what the `correct' answer should be. It seems likely, but it is not immediate, that {{formula:5b0c4354-4036-4f9a-ad5b-395660cd53cc}} should have larger diameter and mixing time than {{formula:92ac3d79-3bdb-4a19-8847-0cb64ae8b5a8}} does. For the diameter it might be... | d | b91e4499d9bc787081557f284e6c0730 |
with {{formula:a0f96999-5f2f-4888-884b-609cacc29713}} a positive constant and {{formula:14330d09-be46-4764-b0ca-b0dca68d937a}} , {{formula:aa80f00b-75bf-4ff0-82be-b95a3e2d3565}} ; here {{formula:37620b94-a999-4a74-b497-ad9e8780727b}} denotes the natural matrix-{{formula:d7cfb7ea-3515-4e87-915f-1a397df79f65}} -norm.
T... | m | f6b31cb6432d863412b7b3f13a34294c |
Fig. 2 presents examples of stain separation obtained by different methods. As illustrated in the figure, the NMF-based method {{cite:e16c7b6f4c909ffe95f296ccd4f2fe1eec0085b8}} and U-nets {{cite:cb7d7ea70308cf08250fb9201979e67a368a9990}} fail to separate co-localized fluorescent stains in the images. Though the pix2pix... | r | 3bbc52f775f112d36eb20fa88250065d |
Given the mains (aggregate) power consumption at time {{formula:7eeb2558-4f49-46e7-87be-77d531bc343f}} at time {{formula:e4cf6135-f2aa-4316-9668-4aae3a3a094f}} , our aim is to estimate the power {{formula:20e54002-8515-42e6-9ad7-d9e07e1f47b3}} for the {{formula:aa7aa921-d88b-4862-bee4-0be1d3bb873b}} appliance. We no... | m | 67325dba0afcd9ff2668cf7807a01b74 |
A number of OTFS equalization and detection schemes have been proposed in the literature in recent years. The majority of methods can be categorized into either low-complexity linear equalizers {{cite:ebde2c73f8533faeafc91b7302d99e991164318e}}, {{cite:4341be3e8f0af0de0d0790b5623286837ecc5bc8}}, {{cite:2fae1e4b5c5c68c01... | i | 6503f1d49af6c38328c6052c2236fdd4 |
In this paper, we aim to train a ML model to learn the relation between halo properties and the occupation numbers of galaxies from a galaxy formation simulation. This invariably includes the complex set of effects related to GAB (such as the preferential occupation of galaxies in early-formed haloes as one example). W... | i | 409a62a318a93a81d39738aa31f8a895 |
We consider that the concave hull of {{formula:22ea7aa2-aa56-4bb3-bb11-96372ac57a08}} represents the outermost layer of the RRT expanding outward and can be used to delineate the RRT expanded and unexpanded spaces.
So we construct a concave hull enclosing all the nodes in {{formula:78d9a1af-b547-40e5-9ceb-021cffc12d69... | m | 5f86bcb7919f5ca1c4f546e3de02de74 |
The decision boundaries of real-world classification problems are often not convex. Outputs of IOC-NN are convex with respect to the inputs by design. Melzer {{cite:f5a8e4ccc9d3c3ea095bab29a854636a73d34cab}} and Kripfganz {{cite:2cedc7ea011113ebba21dd83e86a08afd4ddf954}} show that we can represent any piecewise linear ... | d | e257065618fc88bfb1087b216b16ee26 |
Optimal Transport methods assume that the shift between the source and target distributions is induced by a function {{formula:6a1d8b0d-24b6-4ef4-8871-4ab5cdbd4b01}} . That is, if {{formula:14764dfc-bd0b-4bcf-b970-741de33a1e25}} , then {{formula:9372b842-ee90-4e94-9ab1-55230f593e76}}{{formula:1ee460a0-0d7d-481c-bab9-61... | m | 28e8ccc7e09eff24723474b44007443d |
The claim of {{cite:b38d746df201043f1433a56c0bf4a7e82761028e}} was that any bulk operator with support in the interior of a Python's lunch should be exponentially difficult to decode, with an exponent that is controlled by the size of the bulge and grows as {{formula:35370cfb-af72-45f1-9f04-55452d229d91}} in the semic... | i | 938e990a4ec3d353789d8e5cc2093a04 |
Denton el al. {{cite:1d44b2a3f312f01752158719c2ee1aac89f30e80}} have recently shown that the components of eigenvectors can be recovered from the eigenvalue spectra, which they name as eigenvector-eigenvalue identity, and is valid for any Hermitian matrix with non-degenerate eigenvalues. Specifically, the identity hold... | m | 920606f921b9a8457cc1a2c647138758 |
The development and theory of the extended Kalman filter is
documented in the text {{cite:353bd8576d765583f9315f2666c52e6745603034}}.
A methodology for analyzing evolving probability distributions
with small variance, and establishing the validity of the
Gaussian approximation, is described in {{cite:6156c0b2a4f6ef69f8... | d | 72e60ec37f0a77b4b63f3a67c3f184f2 |
We also show the class-level performance using 20% of the labelled data and compare with other SOTA methods in Tab. REF . We compare with the previous baselines, namely original mean teacher (MT) with Densenet169, SRC-MT with Densenet169, MoCo V2, and GraphXNet with Densenet121. We also train a baseline Densenet121 mod... | r | a5db4e87e89bd882f4375889766f538a |
One additional objection is that, since depth requires optimization to be inferred, and the choice of loss function is a form of transductive bias, that is no less arbitrary than inductive bias. But this is fundamentally not the case, for the optimization residual in transductive inference refers to the data here and n... | d | 88c42414f925d6db82666f8eec7bb61f |
The task of question answering is to correct answers given questions, which requires a high level of language understanding and machine reading comprehension abilities. As pre-trained language models on Transformer {{cite:6bfb8c14c62e6ed6e7548c0a0094a47652baabd1}} have brought significant improvements in performance in... | i | 6f20dc8e97c2378327090ee267b4fc17 |
Bounded planar thin-film flows are common in both nature and technology. A variety of interesting flow behaviours fall into this class, including rupture {{cite:47d0041f10cef3a8b516081de4ea6f18a3e576e0}}, dewetting {{cite:0c51a540b291af00026387632433991b27f699f6}}, droplet spreading {{cite:009d68a804622c13f23642cde8464... | i | 3ee73bf206244ef62346ebf29f52297f |
We conduct all simulations on a Lambda workstation, which has AMD Threadripper 3960X with 24 cores, 128 MB cache, 128 GB RAM, and 2 RTX3090 GPUs. We evaluate 5 convolutional neural network (CNN) models – LeNet, AlexNet, ResNet (ResNet18), DenseNet, and VGG (VGG16). All these models trained on the CIFAR-10 dataset. We u... | m | 0181360fa00aa96a08d4f5762d369db9 |
paragraph40.0em-1emSemi-supervised ResNet-50. Recent works {{cite:0ee430ddfee75d34abf3ede23683b93ad457fcf2}}, {{cite:276ff11fc49bb00146c6703eaf340bf1abd67cdd}} have demonstrated the possibility to leverage a large collection of unlabelled images to improve the performance of a given architecture. In particular, Yalniz ... | r | 07471809a5a95373586f27caff08fc22 |
Example 3.4 Mandelbrot introduced a tiling fractal, known as the fudgeflake in his classic book (see page 72 in {{cite:fe7fd7ddc8ab65288ae364ae862643d2e337cda6}}). The fudgeflake is a self-similar attractor generated by three similar contractions:
{{formula:f61621b3-7af2-4553-a9a9-534de5d26a43}}
| r | 3b96b559607d7c50469ac7c330c18a4e |
We have presented a data-driven kernel method that robustly extracts dynamic modes from high-dimensional, nonlinear data.
The method may be viewed as a confluence of the dynamic mode decomposition, the sparse identification of nonlinear dynamics, and kernel methods.
Specifically, we use a kernelized identification of n... | d | 4cd21b1c4192001caaf588d0e48cc335 |
We test the different balancing techniques on three problems (Burgers equation, Kirchhoff plate bending and Helmholtz equation) originating from physics-informed deep learning, where the objective function consists of various terms of potentially considerably different magnitudes and compare their performances, as well... | r | 71ad4000b685e813cdead6b980121608 |
Among our competitors, we note that the celebrated conjugate gradient (CG) method is another instance-optimal algorithm for quadratics. Whereas our method minimizes the distance to the solution at each iteration, CG is instance-optimal for minimizing function values at each iteration. Perhaps interestingly, the two met... | d | ef862c3b9da2c5c0dcf27baa9f16b406 |
As obtained by Banerjee and Majhi {{cite:f59ada5995999b12fcc41f7da5b60146de8b3339}} for the metric that has a time-like Killing vector, the metric (REF ) also leads to such a relation:
{{formula:768a4f3d-f23f-4b84-a63d-0a1e7b7a43bd}}
{{formula:dfe4f744-2e54-4c75-a760-5e387ad9a5c2}}
{{formula:77179564-0fec-4e6c-8719-d... | m | 319aa34f49793f20394b3cfe8b2d156e |
For the experimental confirmation, clarification of the molecular basis for heterophilic adhesion is important to support the experimental idea. A possible candidate for the heterophilic adhesion molecules are TgrB1 and TgrC1, which is manifested in dicty slug {{cite:3a0f9fcbe1c236237e397966b69d2eab1b68786a}}. Further,... | d | 6b50383c441d21810b1ce450d9b9f2f4 |
The first thing to note about our rate (REF ) is
that it is consistent with the rates recalled above. When the complete graph topology {{formula:1856dcba-89b6-43fb-bb2e-c97bd0a43f5c}} is used at each iteration we have {{formula:b2f38481-70ed-4105-9c55-9752c3b97b51}} and {{formula:ef64f526-0363-4bdd-a4a4-2de2583cdf22}... | r | e07a51fc1f253fc9d80a418fb643dbd6 |
at lowest order in {{formula:8b43e9cc-1cb5-4707-9f44-56ea92eec81e}} .
This behavior should be contrasted with the findings in fluid dynamics, either in simulations {{cite:2b41f2aab0e5b4312ceaa6eade822d25618dec03}}, {{cite:2fbed2d6f0a65cd428f263de940bd909ebdb81ab}}, {{cite:e8ee107e0055da8a2083f35a874bf50b29e5d392}}, {{c... | d | a75031ff47c3e908ff3c0051c1edb1b9 |
Quantum mechanical effects such as superposition and entanglement open the doors to novel quantum information processing (QIP) technologies in communication, computation, sensing, and metrology, that are hard or impossible to build using conventional classical technologies. Among the various implementations with superc... | i | 6e72a0c3bbc9bebc1d57d146a6fe5bc6 |
The LHCb collaboration also measures the same process at {{formula:0f762c30-29b5-4d0b-bee6-f7bc1137bc24}} TeV
with the same cutoff of {{formula:2db6d787-7a9c-473d-a9bf-589262d497ad}} and {{formula:2a672330-ae41-4921-9334-d1328ec1ba08}} , and
they obtain {{formula:f1ebcb2a-300f-4f62-bbe1-e33d7230078b}} nb {{cite:72a... | r | df784518fd3bf39e3a860db3472bba7f |
Blockchain consensus methods are numerous covered in detail in {{cite:cdac960ca83f7dc84c63adcdd9efc46b410b6b62}} and {{cite:407f60490faf79e251914343a6a18e676ec8ef82}}. An identification, explanation and examination of current consensus methods in relation to blockchain have been extensively documented. A general overvi... | m | 40815f250ecda85003ebaee38afe2ba5 |
In what ways can our reachability graph be generalized? First consider staying within the setting of {{formula:0a1f6de1-d266-45f0-abee-54c6e440b846}} -qubit states. The existence of a graph stucture is most useful when we have a gate set that can be used to pick out only a finite number of states, rather than a continu... | d | 68bee17f7ac3a49366b1e316f89497ba |
Some obvious future directions include: (a) self-dual gravity with cosmological constant {{cite:46e941b49cbea631983ea6ce760ca5d27a6678ee}}; (b) higher spin extensions of SDYM and SDGR {{cite:dd2617a5806c41c4d3be41b9155df56aeff1c38c}}, {{cite:cfa14e0c86b76eb226c954f5f1defe615d99c7e7}}; (c) the supersymmetric higher spin... | d | af8a7132ce9c17e25b328e829fba0d7a |
In this section, the measurements of the flow coefficients, the non-linear modes, symmetry-plane corre-lations and the non-linear flow mode coefficients are presented. They are compared with hydrodynamic calculations with various settings {{cite:b3ca312ff48dff8bcc2db6f2df30cb2135b442c5}}, {{cite:87bd312e77e6ee22f67416b... | r | fec3678cd6ed8fb13c9dbdba2753f885 |
The primary component of the {{formula:985fc4d0-9c16-4c37-ae0a-2564fae4071b}} Dra system is an evolved A-type star, which is an extremely rare case when it comes to eclipsing double-lined binaries. Querying DEBCathttps://www.astro.keele.ac.uk/jkt/debcat/, an on-line catalogue of detached eclipsing binaries with the ma... | d | 690d8ae3c9dc6b658442c70492ccf01d |
however some loss functions cannot be interpreted as a negative log
likelihood as shown in table (REF ) and as discussed
for the SVM by {{cite:00d1594658cc69100f5f9cc02f1e817cee85d352}}. If, the likelihood is a log-concave
function of {{formula:eb84381b-0c9c-4f22-9a95-25da47fb95be}} , it corresponds to a convex loss fu... | m | 186d2585660d2a0e1725643e77fc29d0 |
The community appears to be deeply split on the issue of model dependence, with the proponents citing the necessity of explanation fidelity {{cite:2a7a2668f6627208ec014444b2bc2fdbcc253c2e}}, while opponents doubt the inherent fidelity of the directly model-dependent explanations {{cite:1811817a569307f921479e414fe18c683... | m | 9791866de42c1084d3a4fe403955373b |
A cutoff can naturally occur if it is produced by a maximum acceleration energy in the sources. In that case, the parameters given above would be reduced to upper limits. However, the detection of a pronounced pileup just below the cutoff would be prima facie evidence of a {{formula:82433a83-b924-462d-8e98-0eadc7485d96... | r | c39f7655fdd9c587ac85d6a2e0dc0282 |
We applied these new tools and methods to inspect, for the first time, the imprint on cosmological recombination of inhomogeneous photon injection by accreting PBHs. The physical origin of this inhomogeneity is the dependence of the accretion rate on the velocities of accreted baryons relative to dark matter, thus PBHs... | d | 2c46cfd1062df0fc37900f10f85a0a60 |
Fig. REF reports synchronization diagrams {{formula:a8bafd23-9dcb-41a4-aca2-6118c197e7cb}} in the absence and presence of coupling constraint for fixed {{formula:0294e532-52ae-453a-ac93-024bcd29a7f9}} . As expected, without consumption {{formula:2b05c639-8651-493d-a703-707e4949edec}} (Fig. REF a), our system exhibit... | r | 53bb87c84521038aeb65306bbd7f8240 |
We have also evaluated the above base CNNs (B), and the influence of our novel CAP (+C) and the classification module (+E) in the recognition accuracy on Aircraft, Cars and Pets datasets (more in the supplementary in the end). The results are shown in Table REF . It is evident that the accuracy improves as we add our m... | d | d5170a6368c1b53cbd98bfc9770bc73e |
In terms of speed, CNNs are very fast and have a smaller memory footprint (see fig:complexitycomparison). The throughput gap can be evident by investigating the vision transformers reported in Table REF . A particular strong ViT is the Focal-ViT {{cite:e9a20e895d15e68c5c819697c722d222be82b1ed}}; in its tiny version, it... | r | 35f65fc2bf9318614594afdc915fcf63 |
Comparison with deformable convolution.
In {{cite:b196533919fdfcd73e764151974dd580debd9ca6}}, Dai et al. propose a deformable convolutional layer, which allows the sampling index set {{formula:5c97e026-b65f-406d-84f7-4fa3b9631413}} to be non-grid and irregular. It assigns an offset for each index in {{formula:dcda706b... | d | a613f2404fcf3ea3cb0242ca62650ff5 |
Additionally, we include results for using stronger networks on CIFAR-10, namely VGG11 {{cite:16f136be25d8c23b63cce54fbac163ba0752e003}}, in Table REF . Here, we use high performing networks trained only on CIFAR-10 to assess how well consensus through HD-Glue works in this scenario. We have dropped poorly performing b... | r | 551d790724116e7aded4902f307f188b |
To further verify the effectiveness of those technologies, we combine RTD, DES and DA to train models of different sizes(i.e. large, base and small) using standard pre-training settings. Since all of our experiments are modified based on DeBERTa code base and follow most of the settings of DeBERTa, we denote the new mo... | r | 403aa281ec46d55e4afa15eb81702517 |
We observe from Table REF that boosting algorithms such as AdaBoost {{cite:803d40d249fb4adb271eb359aa8230142382f138}} and domain pre-trained transformer models such as LEGAL-BERT outperforms all the other models in terms of Accuracy and Macro F1-score in both the ID and AD datasets.
| r | 6c7624d0af9492a3dbebf86323276738 |
SNGP is a method for deterministic uncertainty quantification, that is, given a single, non-random representation, SNGP improves the base model by enhancing its distance-awareness property. This is a orthogonal direction to what was taken by popular ensemble-based approaches (e.g., Monte-Carlo dropout, BatchEnsemble {{... | m | e9ec301992eb9c5bcf51a1b5a2beb438 |
More recent methods are often data driven, in contrast to model-driven conventional methods. As such, the challenge shifts from building a good theoretical model towards building a suitable training dataset which enables good generalisation characteristics for unseen data.
In general, data-driven deep-learning methods ... | m | 30bcc50044c0bc52723f6943d916ab84 |
Multi-epoch photometry can also be used to identify young stars from their inherent variability {{cite:0ddb6aab9ad29168e851943f2b408092dad2430f}}, though {{cite:a395c6effd55cfbea0aea672b945c5d2ef3d71ca}} find this method needs spectroscopic verification of the members and has about a 50% success rate. Certain types of ... | m | 183485da57743dcf626629889303eb2d |
This fact, which follows from a simple double-counting, was observed by Wiener in his original paper {{cite:2239530ec1d3c31c027d593d8555c62bbcfea448}}, where only trees were considered.
However, (REF ) fails to hold for most other graphs, owing to the fact that shortest paths are typically not unique.
| i | 77d19d35c731d36782c6c87eadc4d49b |
Results on miniImageNet. The experimental results on miniImageNet are reported in Table 2. It can be observed that our method significantly outperforms other methods under both 5-way 1-shot and 5-shot settings.
Especially, we are 2.5% better than the second best method {{cite:bc292e0d8d57d134a76e616538f5c4abd89abc75}} ... | m | 2a9c29d377d3de5186f9929f8861362a |
In Fig. REF , by calculating more data of the energy for different temperatures and {{formula:e5ae60b8-e79a-4dff-9f91-95e3b106d8b0}} , we verify again that {{formula:892114ec-a82a-4cf4-8c23-b91869a40179}} satisfies the simple relation (REF ).
We have also found that the fermion energy for {{formula:14ee4e72-2891-4dfb-... | r | b904f47eea04962fa5261a7e1b557ca6 |
The third line of research gives up the expressiveness of the full
{{formula:6c398ec7-86a5-4faa-96bc-a3c63e75d6c0}} -calculus and focuses on decidable fragments. Patterns
{{cite:1803b7f324d7c857ff1e3fece7bde8bab4aabed2}} are arguably the most important such fragment in practice,
with implementations
in Isabelle {{cite:... | d | 3ef91c54a2184411dde44a6e878dffec |
Comparison with Other GAN Models: Our proposed model is simple and unique as it does not require 3DMM information or external synthetic images during training {{cite:5a7f4ca4eab3ae1e5e1d5e07e5f49d27216a6078}}, {{cite:bbd5a32eddd6b7cad74d6192f0227c41299a12d5}} nor do we need to fine-tune our model during testing on inpu... | r | a39debd01023f181319dc0025d570fe1 |
Limitations. We are aware that there are still limitations of our model.
First, as discussed above, our model presents bias to a certain degree,
which might be caused by: 1) the data bias existing in the original LAION dataset {{cite:f03eec13e19d46e833a5155833edaa7e8b30edd2}}, or 2) the performance bias of the face det... | d | 3cc7531823669a00e5bc2f5a9a6db3a5 |
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