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This paper is organised in the following way: In Section , we define extended affine Jacobi group {{formula:e384e115-a411-4e07-8b39-d00558f8bf6a}} and we prove some results related with its ring of invariant functions. In Section , we construct a Dubrovin–Frobenius structure on the orbit spaces of {{formula:ca576f6b-c... | r | a8512d1585929718da2e08791abc7b9a |
Now that we have defined our model, we assess its validity through extensive experiments on a diverse set of 46 publicly available time series classification datasets.
These 46 datasets are used in {{cite:ef87bab1d3b70de72e063dca0190e9303c085ea6}} who, fortunately, also report classification accuracy and earliness of c... | r | 5b71f0658b9a10bdd95c50748a062430 |
In nonequilibrium steady state, the quantity {{formula:f33c72ec-5c6e-44b8-a86b-f04dad2a0778}} might play an important role. Under the existence of the non-potential force, the entropy production rate is generally decomposed into two non-negative parts, the Wasserstein part {{formula:3b348700-612d-4e56-9cf6-af8fdd513d0... | d | a93ffb39e0384370373b0ebbf13a1fd6 |
It is difficult to compare our results with related works, since there are, to our best knowledge, no studies regarding automatic spinal metastases segmentation in MR imaging. Thus, comparison is indirect and refers to CNN-based segmentation approaches for instance of liver and brain lesions, as well as a recently publ... | d | 23b55d10b8d18aa75a0ba006711ddcd2 |
The proposed edge ensembles framework facilitates the operation of deep learning on edge devices by accounting for their unique properties and requirements. In particular, Algorithms REF -REF are tailored to account for the limited hardware and computation capabilities of such devices, combined with their mobile dyna... | d | cc4697a0b8318a7dd8f741c8d6647622 |
A QD-microdisk resonator system is not limited to acting as a source of quantum light states, but can also be used for their control or processing. As an example, this system can act as a Bell-state analyzer, a key element of a quantum optical network {{cite:6082be0f4285b4110dd185d9c899161fbeac4c03}}, either in a stand... | d | c97e34798162466d3c4de52059d33217 |
Finally, to show the benefits brought by multi-antenna UAV data harvesting in terms of energy saving, we consider the trade-off between the average transmit power limit of SNs and the energy consumption of the UAV. In general, the energy consumption of the UAV consists of two parts for our considered problem. The first... | r | 6011f5357397f14e0b3175b07edf3ee2 |
The above effects depend on the typical electron density and temperature of the plasma surrounding a BH, so in the following it might be useful to estimate the typical scales involved in astrophysical environments. We shall consider BHs in a wide range of masses from stellar-origin to supermassive (in practice assuming... | i | 09085284d82bec085218c3a49f27608a |
Can we determine the location of a scene given a single ground-level RGB image? For famous and characteristic scenes, such as the Eiffel Tower, it is trivial because the landmark is so distinctive of Paris. Moreover, there is a lot of images captured in such prominent locations under different viewing angles, at differ... | i | f29ab2369c62e958381986eda83c284d |
The study of moderately exponential algorithms for NP-Complete problems is extensive.
In fact, exponential yet better-than-naive algorithms for NP-Complete problems were known for some problems, for example The Travelling Salesman Problem, long before the definition of NP.
A survey of Woeginger {{cite:0f23c52b7856815e4... | i | cd24e86afb0c5a711899c640ce598b2b |
We introduce an interaction potential {{formula:8e2e1a15-3bad-4c24-b6aa-c25f32d1a18b}} and consider equilibrium states to be Gibbs measures built with the DLR framework, see e.g. {{cite:7553dd26da52d8b293f409f61391f48e2b216ab7}}: they are the probability measures {{formula:e9b1a9e4-a2af-4ba9-bfde-2ad2e015dc12}} consi... | r | 099d69eb41cd01d9f42bdcb878a4bf56 |
In Section , we propose LEATHER, our novel theory for computational learning of dialogue generation. We use the GuessWhat?! visual dialogue game {{cite:11b4f1da2d463ea49927348879c2d5ddb0684f20}} as an example to ground abstract terminology in practice. We conclude Section by applying our theory to analyze a cooperati... | i | db8ab1299f9112d3c5b98c158e53b705 |
Robust Estimation.
For RANSAC-based robust pose estimation, we solve our minimal problem by first running gP4Pc and then using Umeyama's method {{cite:7d33344305424280d4a35a11b981b9623b5e4bf5}} for 3D point-to-point alignment in order to estimate the similarity transformation. We refer to that method as gP4Pc+s to diff... | r | 991b11de4748371a06b660377fad8e00 |
On the other hand, several GNN models were developed in {{cite:9fa17e0e07518df82bb654376c0483084d0b30e3}}, {{cite:6576f98534c54723059f934ce737ffbb3985224e}} to learn vector representations of nodes in signed (unipartite) graphs with both positive and negative edges based on the structural balance theory {{cite:3e224475... | d | 8730cf146d63aaff0f9adfa2f3f17106 |
Stochastic geometry is a mathematical tool that characterizes the spatial distributions of base stations' and users' locations in wireless networks {{cite:c6816afb4577df31dca03c37170c4103e1a1573b}}, {{cite:2ba219656c4f6cf728cdb307bdedf41d19a64285}}, {{cite:504a7ed0c7f0df93ce76eee5ec6c36a05a702dd7}}. Significant progres... | i | bb979fa4314effe4e97eeee15ab46241 |
Existing literature covers how to learn a reward function in cases of
unclear tasks or how to make efficient use of it in cases where it exists
and can be evaluated frequently.
In contrast to that, in many other tasks the reward function is clearly
defined but costly to evaluate.
Providing these kinds of rewards to an ... | m | d66b4cc3b8bf2338790236ab7b31012c |
Enumeration of Conjunctive Query. Conjunctive queries are built upon natural join ({{formula:59fa4023-e0f3-4e3e-821b-690fca36eb5a}} ), which is a special case of similarity join with {{formula:a7470859-4271-47c2-9dd5-de4f6c03b4db}} , i.e., two tuples can be joined if and only if they have the same value on the join att... | r | c8e57c68ea7cf57da4b593c5e816ce55 |
where {{formula:382ea421-41d9-4a48-b68e-f6c51fb1890d}} and {{formula:44c9d1b6-8c79-46a2-a716-8157141502b8}} denote the deviance of the proposed model and the null model respectively. The value of {{formula:7298898d-6c82-4b2d-9099-9f1beb008c77}} shows the ratio of the deviance explained by the proposed model that the... | m | 4b4d6c5c3792298ef54aa68955187240 |
A popular modeling framework to study methods of influencing selfish behavior in engineered systems is the nonatomic congestion game, which is often used to model urban transportation networks {{cite:4ca0edf98c4b06f8662019a297cd1715315d0add}}.
This model was one of the first to admit straightforward characterizations o... | i | fb48dcd8a9913fccd8e739fd65cbd054 |
Most recommendation models extract users' and items' latent representations implicitly or explicitly and then calculate the relevance between them via inner-product or other neural network methods, e.g., MLP. Traditional models, such as Collaborative Filtering {{cite:ad37997a466f3333549ad8ac85f04e6b04b6ba25}} and Matri... | i | fa54a08fd04e7fe32f02045c730658df |
Mathematical cancer models have provided a deeper understanding of this immensely complex disease by unveiling the underlying mechanisms and offering quantitative insights {{cite:2882421b736f234d3951a6e18833f631792a0db6}}, {{cite:c608943dee13d9434e3cbaa6e9073e471b4a1ed2}}, {{cite:7ce8e4974fb4a273b30ab47591c156b050caa64... | i | 1aa277f2ba810b0eba40a4f7c83f4b19 |
An interaction of topological SMs with a continuous-wave laser provides the studies of
topological materials with another avenue from the perspective of the quantum control of
underlying topological properties by means of built-in laser parameters — intensity, frequency
{{formula:e4e1d211-4591-4769-94f6-73912ecba5d1}} ... | i | 7eb9f0e915a4be9aa8108a47053762fd |
We have performed the semantic segmentation experiments on the Stanford large-scale 3D Indoor Spaces Dataset (S3DIS) {{cite:f467b4fa76fe6c606b8d2732339da238d2f5336a}}, which contains 3D point clouds of 271 rooms from 6 different areas. Each point in a point cloud is annotated with one of the following 13 semantic label... | r | 5e4ab1de6ed01d8609a1be6744e9ce59 |
Here we only considered stabilizing SGD with momentum. Adaptive optimizers such as Adam could form a further stable alternative to rewinding or large-batch training, as they typically employ much lower learning rates. Though a full discussion is beyond the scope, {{cite:f7fec14b4ad8ffa57bb53e3eb79bdacc174aef53}} evalua... | d | 6af59b2417c3f361b7c8bb0c1b6a7c48 |
We may extend this work along several directions: The first one is the background independent formulation of closed string field theory. As proposed in {{cite:063f229f244c6ef6357bcef9c297ae5d32e00be9}}, {{cite:2c817ed0a937a124e9daf1d25b2b0ce163490966}}, {{cite:77f5c1f35424009bd82fd9469242f37c65f9e92e}}, this cubic clos... | d | a761bd71424e0dc4001e8b39cb2de538 |
An interesting example of an indeterminate moment problem on the real line is the moment problem corresponding to continuous {{formula:346cdf2c-5e76-41e3-ab82-076734b31a10}} -Hermite polynomials {{cite:1426ef8c92f4514970cd28ee29ada12d742c4a94}} for {{formula:16701243-a6ad-4bad-9ff4-0966787158bd}} . Askey was the first ... | i | 185733f8552832c28d5f7c4b31e96d16 |
Depth, width, and resolution change in an exponential order. They have different values of their change rates among scaling stages. Depth and resolution change similarly, while that of width is slightly smaller, which is similar to EfficientNet {{cite:a8035f5b0e602f2d9b2647352bf85962f745706d}}.
| d | f7461b9e6671022d53596501e1dffc18 |
This year, the RBC/UKQCD has published the first ab-initio calculation of the the hadronic light-by-light scattering contribution to the anomalous magnetic moment of the muon, at the physical pion mass, with a continuum extrapolation and an estimate of finite-size effects corrections {{cite:974fa7ff9dc7465bce23cf2f65b6... | r | 3bc9323ba7f9adcc7f1fe8ec2844b825 |
In this section, we seek to compare the performance of the transformer heads we have analyzed in this work to baseline convex optimization methods. This comparison allows us to illustrate the implicit biases imposed by these novel heads in a practical example. In particular, we consider the task of training a single ne... | r | 59abd5cbeb9887b3547454018092a5d0 |
where {{formula:f1eb0713-93db-4b1c-89b9-3e7bd68d0495}} is the degradation model parameterized by noise parameters {{formula:3b50d023-2997-4e54-aad0-40067122840a}} . The training set doesn't have the clean images {{formula:89cf83f6-1df1-424e-95e1-5ee7710e166e}} and only contains one noisy instance of the corrupt image... | m | 8f233b621ec9145869e048023df60423 |
Such correlations between the two gas phases can be interpreted as the manifestation of a common origin, like the condensation of low-entropy ICM gas through thermal instabilities. The ICM surrounding the {{formula:88aa0527-8170-44a0-a01b-349ca927ec7d}} tail has the
lowest entropy according to {{cite:ee1cdd0e4886533a5... | d | 7c8fdd0c1e220d5a1b90380ec36d3a82 |
This is a new situation that did not exist in classical physics, where the procedure for obtaining theoretical predictions was not very complicated. In any case, the complexity there has almost always been within the reach of classical supercomputers, which are created mainly to cover processes from the point of view o... | i | 2a171857978e0e5ba8c2fefbf3da8402 |
When applying such procedure to the photon gas problem, it has been long known that one detects non-trivial modifications of the equation of state parameter {{cite:0ba1701176a817ec8713f08343cca2010aeaeeb8}} proportional to the ratio between the temperature of the fluid and Planck temperature. On the other hand, it has ... | i | 3ec22dea99aef6e5b1abd2d4b7d775c5 |
Memory Networks. Memory networks can cache sequential inputs in memory slots, and explicitly utilize even far early information. Memory especially receives attentions in long story understanding, such as movie and TV, which not only requires to understand the content of shot video clips, but also to infer more abstract... | m | 67e795fd9d875ce4cfa10dd0641f2df0 |
To study the bipartite entanglement we will use the concept of negativity {{cite:7ccc8717bbb07c31499fab6a73d48f8af1eed481}}, {{cite:b3787c97608868df3bc0a44cb2cb7fcb3b1a582b}}, {{cite:c26dac10f2c1a544362fc6ef011c7bd4613affe7}}, which is defined in terms of negative eigenvalues {{formula:d83ee34d-1e2f-42d8-9f11-1457b564... | m | 789a09443866bed169bc8b4b6cacb571 |
We use density functional theory (DFT) with lattice flexible boundary conditions (FBC) to optimize the core structures of {{formula:de9b41ca-e039-4c7b-b155-242dc791742d}} edge,
{{formula:c9f1e8da-49a9-434b-a0ba-527de1e695b3}} edge, {{formula:1fab65fd-2ad0-4693-a51b-d6f2c1031fab}} edge, and {{formula:b18653ce-c044-49... | d | 646855bc6edd6fc945b2d7a7b39af806 |
This gives that {{formula:b8634273-166a-4b7e-b206-8dc4caf9a12e}} is the singular value decomposition of the compact operator {{formula:8d7b7ee8-6b96-4dee-a20c-1d2863498eb8}} . Now just as in {{cite:d94b66e2beb2316752bcd1b0c3c2759cbb1d4f66}} we can define the regularized solution of {{formula:54b1aa87-7622-4a25-90fe-ce... | m | a470b407be443047abf371616be9342d |
A new opportunity arrives thanks to the Gaia mission {{cite:94968d840111b9a78cf8ffe7c68567734a38f9a8}}.
For the first time, the recent Gaia Data Release {{cite:c3c029dc4d0b477e61220b73e14a50912f6a9dbc}} has provided stellar parameters and chemical abundances estimated from the spectra taken with the Radial Velocity Spe... | i | 40a04224f94b4e072630e338be37688d |
Optimization of Miller-Abrahams resistor network {{cite:0c680d22552535886ff79f1db724148ad8a4cc6e}} of all available pairs of droplets of two adjacent puddles leads to the new H-mechanism conductivity:
{{formula:44cae24f-61ef-43df-86d5-59ea4f244bbb}}
| r | 212e56f3d929dea711bb7c1d794aa0fe |
Simply minimizing the standard cross-entropy loss for highly non-convex and non-linear models such as (deep) neural networks is not guaranteed to obtain solutions that generalize well, especially for today's overparamatrized networks. The key underlying issue is that these models have many different local minima which ... | i | a8e0dbe73e2aa9a2c3ef7164fa3c5182 |
respectively, with {{formula:13eaaea7-7b4c-4be1-a11b-a7ead682ffc3}} for {{formula:fa8fca42-bb84-4a45-a9db-7ad4365336f4}} odd (even). Here, one has {{formula:91064381-fcde-4359-b191-fab3e9a84073}} in the absence of the NF contributions. In the numerical calculations, the Wolfenstein parametrization is used for the CKM... | r | 29617cc40acda35cff5d375f661da97d |
The magnetic transitions (M1) can probe the internal charge structure of hadrons, and therefore they will likely play an important role in determining the hadronic structures of {{formula:4ed4edd0-82b4-4dd6-8c58-3976c1bc8bdd}} meson. The present M1 transitions widths of {{formula:1f75ea76-867f-4e59-98b4-325382cbee46}}... | r | beefe3f2042ebfe90cbc2ca50c3e7140 |
Our calculation in the gauge theory demonstrate the power of the methods introduced in {{cite:12c74e5ae8629d8c4360648a37fa8d91164efb4a}}, {{cite:f74570508ffcc143e21356fb659295620aa8cef1}} for computing correlators of fully-symmetric Schur polynomials. Our methods are in many respects more streamlined when compared to t... | d | f3ad1a56288eae2c04b3595779078415 |
Therefore, one of our technical contributions is to accurately solve the MDP in (REF ). We summarize the high-level idea of solving (REF ): First, in Lemma REF , we show the optimal policy among the extended policy space {{formula:44cb49cb-2208-4951-a5c2-89519b30a8bd}} with universally measurable stochastic kernel {{c... | d | fd3a995ec31f220431c1efa71b12184b |
The second AC multi-agent extension, called Independent Actor Critic
(IAC) {{cite:5a5ed7543eb30b3e3b7b2f46353de3e788ee421a}}, {{cite:6180c17a1b772c69c039662572223085586b2956}}, learns a
decentralized policy and critic {{formula:c0347617-6842-42f0-a23a-71897bf8ab59}} for each of the agents locally.
At every timestep {{... | m | c6e259edf2a108a413b30fee8a823920 |
We then develop a Relationship Feature Propagation (RFP) module that explores the connections between heterophilic relationships. Two challenges emerge in the design of RFP: the effectiveness of feature propagation and heterophily modeling. To reduce computational complexity, we only require each relationship to contac... | i | b5a63afed2754f5255f188ed42eba869 |
DNN
watermarks {{cite:3a542d81507bf3ae9fd95b16484ec6a764fc53be}}, {{cite:7f2c54ba34e5057004440e947044530f70ac4de3}}, {{cite:9125086e4671869d75d85dc78ceae58dc6cf7a66}}
are designed to address the need for proof of model ownership. A robust
watermark should provide a persistent and unforgeable link between the model
and ... | i | c333af4aa1692b65b9c26cab55aea19b |
In addition to the models discussed above, certain
variants of {{cite:85c522f3e4b25ccbfd7c389f5d65a96da87106dc}} and sparse attention patterns (local-to-global attention; {{cite:1524422a4d00b9f907f50705ffa34bdd6b4fa399}}, {{cite:89642547e7cd8bcde956c0d03a2a02bb5354d8a7}}, {{cite:8a69ea6b3a570f33a56edc7ff3f3d50d99309647... | d | b266f9220a0ab39f456c13424cf1f54a |
However, the attention mechanism substantially improves the fitting and prediction ability of NP, its computational complexity also limits the length of the input sequence. In Figure 1, ANP only takes 32×32 image pixels as input, and the pixel sequence of each image is about 1000. However, when facing higher resolution... | i | 4805bdea4945445217fb82739932e849 |
The vast majority ({{formula:9b2c7c6a-b8c5-4f2d-8397-b5c6c0b29c58}} ) of our dataset requires contextual commonsense reasoning, in contrast with existing machine comprehension (MRC) datasets such as SQuAD {{cite:7283fc078178e34e0b1df4339b1223fbf5b70e92}}, RACE {{cite:3c39430578b66b3f9ffcd84f59ede6cb5b6704a7}}, Narrativ... | i | 5bf1993e11c1034019883430e4f030e1 |
In the context of a digital twin, calibrating the simulation element of the twin with current data is essential for ensuring that the simulation is representing reality as closely as possible. Manual calibration is time consuming and not suitable when parameter values are changing. This study explores the suitability o... | d | 99a758abacd56921b430ba2289f0eef0 |
In this environment, we ran experiments on 7 different Atari games to test and compare the fitness-based approach, Sugar Search, and its generalization - Pixel Novelty to other techniques like Novelty Search {{cite:36927aaeaf4f075d27c0bc03447f9bff673434f0}} or DQN {{cite:7335b42f12f07035d099ab02a173cf643408c96d}}. The ... | r | 7452acf1b32a74cce14912b968a79680 |
It is known that for the diagnosis of certain diseases by ECG, a small number of features is enough. For example, for a myocardial infarction, this number can be reduced to seven {{cite:e2b1a9532ec98c76ae260261e3ec76825951205a}}. This indirectly indicates the presence of a low-dimensional structure in ECGs. But our exp... | d | 0a9a6ce007dbdddec955070c3a128f55 |
One theoretical challenge is the proper pre-processing of the problem Hamiltonian by scaling and shifting the coefficients of the objective function, such that we optimally make use of the parameter space {{formula:804e715f-a3fc-4a01-9ae3-d6fdc75d2fce}} (most of the problems in the dataset did not suffer from this iss... | d | 453ad40dab9b01872611009a434721a1 |
Vision transformer:
We validated the applicability of our proposed integer training on the original vision transformer model, notably ViT-B-16-224 {{cite:40ca0903f819c6de1715dd9fa7d729d2100225b7}}. We took the floating point checkpoint pretrained on ImageNet21KRefer to: https://huggingface.co/google/vit-base-patch16-22... | r | d07d387126f50bdfe25625458b74b823 |
Since the phenomenon we are considering is a resonant effect, even a higher multipole moment would also induce transition, if it is sufficiently large and the resonant frequency is hit earlier. As mentioned in Ref. {{cite:6790243429f25cf48e6320dad15575cfb60ad222}}, considering the octupolar tidal perturbation, the clou... | d | 1ba89fe09f71bcda384efa7615fa10fc |
However, these existing methods suffer from three problems. (1) Both the heuristic compression policy and lightweight module design require domain expertise to explore the architecture space. However, the space is so large that such hand-crafted methods cannot afford the architecture search cost. Due to the limitations... | i | 9decac30b96a7cca13e8ec6a1d1fe855 |
Our empirical examples have used VB.
The approach has potential value in Bayesian
optimization {{cite:7ab55841573f6e77d6dc7aebbff9a1ee39eb733f}}
and optimal transport {{cite:69d9e28c6fa5491f6aa0569fd3d0e3497031037f}}, {{cite:c3bc6eec7f08122338bd9540403d412b0e266110}}
as well.
| d | a7fdef4042dc4adbf31c0e71116e6ad4 |
For comparison, two baseline algorithms are included in the results as specified and measured in {{cite:ca17ebe00ae169c522f3b318b4e8955048c52476}}, note that these algorithms too included beat-synchronized features. Firstly, the method of {{cite:2b862df9b9a96eeb472d800b062822efac083733}} is included as it most closely ... | r | e8e761f8565a810f2f5342875935da2c |
In this paper we consider linear-time temporal domains.
LTL limits its set of expressible properties to the
First-Order Logic (FOL) definable fragment of regular languages. This
is quite restrictive when compared with the most popular abstract
models of procedural programs, such as Pushdown Systems, Boolean
Programs {{... | i | 39b8290477cb289d0be90c0670ef7bcb |
Our algorithm is implemented with an adaptive gradient described by the proximal terms {{formula:79fea5f2-9727-4b65-8be1-d7b0d03e5d85}} , {{formula:0d2a4294-2642-4ca4-9286-b8af8c8d9dfa}} (line 6 - 9). The proximal term is motivated by its use in online learning to reduce the regret, where the term aggregates the histo... | m | 121bbb8c5c3b913656321de2f7bfe832 |
Here (and from hereon) we define the `Galactic Plane' as {{formula:9069c618-9761-49dc-bdf3-6e94a560dcc2}} (19 sightlines), including Rosette, Mon OB1 and NGC 2264; the `Gemini region' as {{formula:6f8d87b1-0bad-4759-9f2b-334f3d9232f4}} 5{{formula:cea2859b-81e3-4ba1-846c-c30275f5b7ae}} (23 sightlines), including mini... | r | 2cd8181dbd20faf834f184c63819544e |
blackMethods for the interpretation of machine learning models can be broadly classified into post-hoc interpretation methods and self-explanatory methods. The former typically aims to establish the relationship between the changes in the prediction output and the changes in the input of a machine learning model in ord... | i | 67d7f8cd1099fda8e7665a13af29524e |
Expectation-Maximization (EM) algorithm has been frequently adopted in deep learning in recent works {{cite:c3bb3a8c0c90b1b24c4e699c5c5672e7a4724abb}}, {{cite:6e48d0d281dacda55d9f6027f77342056fa62f83}}, {{cite:9c1f33b5f4f141b424d44837577061de6843db86}}, {{cite:c457a88f24cb6fa91d2a647ba37dd2410f6bdd19}}, {{cite:71ef622c... | m | 9188c6431289c76b759e371f0c0048a7 |
The proof of Theorem REF used the
compactification technique of Section to
show there is R-tipping in the nonautonomous system (REF ) by computing codimension-one
heteroclinic connections in the compactified system ().
A similar approach has previously been used on a case-by-case basis to compute critical rates in sp... | m | b7f9f0e615402442ccd446e0e66fda8d |
Figure REF presents the results of fitting a PINN model, as described above, to Burgers' equation {{cite:e51f9900cc589717cffb82b1522dca7b9f2c7e5b}} using the L-BFGS-B optimizer. This version of the BFGS model extends L-BFGS to take into account the box constraints needed to solve Burgers' equation. The results obtain... | r | 8449d79d72793b9143c11fcc087ca3ae |
fig:lada illustrates the pipeline architecture of LADA, where the generator {{formula:5c41bac6-8b98-4fb5-8375-1068670188d3}} targets to generate mask images that will fail the lithography modeling network {{formula:7d000a3d-17c8-49ef-accd-41d39eb36343}} .
For the best of LADA performance, we select StyleGAN-2 {{cite:5... | m | 0ed880da1bde03bc8a4317f684e243ba |
Henceforth we
use the following notation. For a real matrix {{formula:c4951170-d2f5-4cef-893a-19c8d8dbbbb2}} , denote by {{formula:37bf1d1c-ba81-4354-a1a7-75d8f3cd5700}}
the transpose matrix to {{formula:96a50d81-15f6-429f-9e5e-72e34fc38678}} . The identity matrix is denoted by {{formula:5148c765-83a4-4fda-94a8-d73b80... | r | 39b2dc4f9712964c802bfc6b6261aa0c |
Ablation Study.
To analyse the settings of sRender, we build two model variants by removing the stroke loss {{formula:180825b9-31a0-4fca-b84b-923379173862}} (denoted by sRender w/o {{formula:9a3c9bd9-fe98-4a82-a302-2be508e388b1}} ) and replacing sRender by Pix2Pix {{cite:d7139f2266c48ac77f4d2c71f3b9995d4caa413e}} (den... | r | c5b88819289441f6d44382fb79981511 |
We demonstrate the application of our framework for boundary layer flows. Boundary layer phenomenon is one of the most important flows and is of engineering concern in many scientific and industrial applications {{cite:493a43c02cd7bf98af899dfe82d9abb73af8cba0}}. The behavior of flow in the boundary layer has implicatio... | i | 24e133047261b8b21d64bc287f192d7f |
In deriving stellar radii, we use the Gaia EDR3 results {{cite:1e4547b8603ee9d44c97d57e4cb9940c84190152}} for the LB-1 parallax of {{formula:93808bab-afab-4197-a174-e7f9f082bf62}} mas, notably corrected as recommended by the recipe from {{cite:f3394c23fd7bcfe0aa9f4d9e14b7f2ee965eb439}}, which depends on magnitude, col... | d | c57fa9f09b87a2d08a1b803e293bef0c |
Baselines: Baselines include one contrastive, two non-contrastive, one geometrical, and two whitening (redundancy reduction) baselines, namely, SimCLR {{cite:a6b58e45bafcde8104f570b977583c7dfdccd6ed}}, BYOL {{cite:e586b2d871de8aecb5b3cbc18db3bd36b35e42ad}}, SimSiam {{cite:b58e5ce0842700886fba935ca3d0d275d916bbec}}, SwA... | r | 956fbfdec85b1f614757528a128bb58c |
Multi Task Learning. As shown in Figure 1, our model consists of VAE and geometric transformation predictor.
Inspired by {{cite:68f8df54e2f01cbdfd146670971b381d223e3fe3}}, {{cite:9c6225750bfbeb83754394f88f37f83f1a70c96c}}, the self-supervised learning based on pretext from geometric transformation is used in our method... | m | 5ef64287f86a421c9e6cbfa438b42b4a |
From the results in the first group (the upper part) of Table REF , we have the following observations: 1) with the same model architecture, the full-sized MCAN{{formula:d52456c7-2762-4588-88a7-ae29d14dadbd}} model outperforms the reference MCAN model and another Transformer-based model MUAN without the DST training (... | r | e96229a81df71ab9d19ff0bd2bade786 |
Notice that as a consequence, the expected objective function {{formula:df29ec6e-5537-4ae6-bb79-a8a46d1a94b4}} and gradient {{formula:0539c78e-22d4-4914-b061-6918d9d85bf6}} are {{formula:9beb8725-a4e2-44f7-b453-46f4001a324b}} -strongly convex in {{formula:2f2492cd-930b-4713-a46b-5eb7e770e49c}} , and {{formula:90fa801... | r | 26f0ad98867cc0fb50559b5abf5dffcd |
Previous methods of OOD detection can be generally classified into two types: supervised and unsupervised OOD detection. Supervised OOD detection {{cite:bba6aa9964cb4d3edc8c5f214297c2fe472567eb}}, {{cite:7c7a70f57c27e133675d716d6cc34dea57117a51}}, {{cite:7fac1450b7411b28de039b278540d0435a62f58a}}, {{cite:b9c68509bfdd73... | i | 33f30eea8fbe0546ce6d08a36895556c |
A massive scalar field around a BH can be bound by gravitational interaction, and
it can extract the rotation energy from a spinning BH through the superradiance {{cite:01b06b4dd1b327aecc12ce602e05a16f7f9cd5f7}}.
When the Compton wavelength of the scalar field is comparable to the radius of the BH, this energy extracti... | i | 59720e4fe90faa75bc234244875dc4ed |
Since {{formula:9b8fbbd3-3a40-4299-aa41-93ab640bd334}} is effectively coupled to charged leptons, the muon and electron anomalous magnetic moments can be used to set constraints, which are presented in Fig. REF , being labelled as {{formula:7c514fb8-7267-4ee7-891e-6447167f3c2c}} and {{formula:4c98f219-f88d-45ca-afb8-... | r | d44f32757262395d63de052e83c15f82 |
We present in this section a variety of numerical results about the accuracy of Nyström discretizations of the elastodynamic BIE solvers discussed in this text. Specifically, we show far field accuracy results of solvers based on CFIE formulations as well as Helmholtz decomposition formulations (REF ) and (REF ). In ad... | r | 3df660bf765d7971072a15da74d984aa |
For some definitions and notation, we refer to the monograph {{cite:509aa0d5181e1964a547a5e1c26bda68d78af4de}}.
Given an ordered {{formula:f7db0daa-3904-45f2-a225-fd478348d4f4}} -subset {{formula:9627af2e-1798-4504-99b3-c608492931a0}} of {{formula:7c8b0dff-775e-45e9-ab4e-43b919853360}} , let {{formula:9615ac60-f1ee-4a... | r | cad333ecab1521794131ed1670207c55 |
Circular milling in this system has not previously been studied using the kinds of methods now common
in the study of active matter {{cite:1f82d6f1769a160e18478c0e3dfd96730c562814}}. There are open experimental questions at various levels of organisation in
this setup that mirror those that have been successfully answe... | m | cbe72f5eee4768a0edb4e3094731e588 |
Finally, we can ask what theory saturates the stress tensor correlator bootstrap bound with less than maximal supersymmetry. In 3d, the {{formula:bb3fc401-b526-4e4d-b86c-d558b9219878}} bootstrap bounds were found in {{cite:91c30fb358abede3f264405dc13964d8cf7e4c44}}, {{cite:f3e83a54717c17adb303fa00b948485cdb06990f}} to... | d | b50d0bf94c0f03501ad201b3b41153f3 |
The goal of our experiments is to display the effect of our proposed pipeline and model correction method. We demonstrate our work on one toy dataset, decoy *mnist {{cite:7fb95d88d462f6ec8ed719b9deab7e397df813e6}} and two real-world datasets, Dogs vs. Cats {{cite:f1facfcd75a9178dd53114d5b963489897cc63d2}} and *isic ski... | r | a8798819441272fc8d3be204da2aad0d |
To verify the performance of the proposed method, we consider a simulation scenario that the mBS is located at the origin, {{formula:d8400b69-86d8-4c05-bf8b-7abe58edea01}} IRSs are located at {{formula:e126914f-dc7d-4ffa-98c5-8bc26704fd19}} , {{formula:dc32592b-4b86-47e7-9d42-4d3563578208}} , {{formula:4ea8a323-523a-4... | d | adc299ec53a4c86b8a118678850ff14c |
To demonstrate the effectiveness of the two-stage training strategy, Table. REF illustrates the overall classification performance of VGG {{cite:ab46048021689ce2ee7447742f4679872fc14d67}}, LSTM{{cite:b131ea01d67d2cf7c8a5a274aa5271f97080c114}}, ResNet{{cite:ab46048021689ce2ee7447742f4679872fc14d67}}, and MSNet. The fir... | r | 58e51ba17e7f3959ce606cc79e7fbd11 |
Transformers {{cite:eb692d7862be17664d006f99d232c4d674de28a7}} have become the state-of-the-art model for sequence processing tasks, solving many challenging problems in natural language processing and computer vision
{{cite:7e0731b9842aafbf4371c1b22cc7193360352837}}, {{cite:458b91a9d74ecf2e0547b21f7b3feb00530846a6}}, ... | i | 18f549e7dbc8d0e1fe79efeff21161d2 |
The average CIFAR-100 accuracy of NB201 networks is {{formula:9a215a94-f8e6-4c67-af6c-8df924a29894}} , whereas that of the networks in the subset selected by C-BRED is {{formula:ed3504c5-4546-4c84-be7b-951545d5ae95}} .
To validate this preliminary evaluation, we compared C-BRED to two subspace selection alternatives.
T... | r | 3f605080bb413565ac6fe79b0319358c |
In {{cite:73739700678e4c729343db52e06a336399e670ce}}, Montanari introduced the class of incremental approximate message passing (IAMP) algorithms, which are a special form of the well-studied approximate message passing (AMP) algorithms. We review these algorithms in subsection REF . The work {{cite:5b7d3e2f06a8a9c4c19... | r | 6b8feeada103401cda1b9f9e5616bb70 |
In {{cite:5075b91e8887f1ef6b17668629f059e4ebda576d}} 39 different high-pass filters are proposed,
which work on the grayscale version of the original image obtained by standard conversion.
All such filters are extremely simple,
since their goal is to highlight minor variations w.r.t. to typical behaviors.
Typical examp... | m | 855b8bcc5f7e6ed9089f898a7e3245ef |
Interaction with a squeezed thermal bath is not the only generalized process
that goes beyond the typical settings in classical thermodynamics. Our findings demonstrate how to utilize the squeezing effect of bath as a
resource to control the irreversibility, where the use of nonthermal bath
offers more degrees of contr... | d | 28e6893fe21b31024466e85c408f371f |
As with classical community structure, there are many possible
definitions of a quantum community. We restricted ourselves to two broad
classes based on transport and fidelity under coherent evolution, both
based on dynamics, though in the limits considered in this paper the
closenesses and thus quantum community struc... | d | 56ec801f5181812a491e50f83fe3bc30 |
Most existing multi-person pose estimation methods follow top-down pipeline {{cite:50319b2831530690fecf418819929b2b5a00a07b}}, {{cite:6daa9d138a8459690d11013fde8a5c8218db29f1}}, {{cite:5e6027b5cd1ff779afb82849be33a07b4fd21137}}, {{cite:701cd4e30337caf6cc27d63b317d73922253e5c9}}, {{cite:294c62d9e1c241ec3c4459261d21ff08f... | i | 98bfd70ac0fb74d5c54c9ba22928d4c0 |
In this work we proposed a new image-to-image translation network that is able to synthesise CT images from input MR images by gradually reducing the error using a separate boosting network. We validated the advantages of the recursive boosting model using a four-fold random bootstrapped validation with a 80:20 split t... | d | 8947344db8f9ab17e38b0aab9b8433f3 |
3. Related works.
The possibility of reducing the MFG system to the matrix Riccati equations has been known for other models (e.g. {{cite:cbb4e6bbd45963603cb1bc78b691ee5c08e89a41}}, {{cite:4085bbbea26712ef8262c8baf3bacf5834eb5dc5}}, {{cite:dcf795283034d1a3f1c014e200005d1e4cb04c20}}, {{cite:2dbbe53468c5b9782eed2ecad8a8f... | d | 9982af4848bf5b002ef8bc744d8956dd |
Diffusion-weighted (DW) nuclear magnetic resonance (NMR) methods are highly sensitive to {{formula:3c80c741-bcf4-4eb9-8339-82070b31ecc9}} {{cite:c3949e1b4a6cb196492675b048ab343b57a84642}}, {{cite:c7b21e9ab14ee06453c408f7ae7b2b79f0076e90}}, {{cite:d54eecacd68a83822da12411d758caf019345142}}, {{cite:b91db018b887484614b6f... | i | fe713131667f4eac8c226af702d2dd42 |
We use the Levenberg-Marquardt algorithm in {{cite:dd46c29d5345e8c4b312e79e02a2d8da46dd5d57}} to solve problem (REF ), which takes advantage of the steepest descent and Gauss-Newton method. Let {{formula:55ca56fa-4a52-4bae-bcb4-56f0ab8e01d8}} and {{formula:06219248-79dc-43ff-b86a-f27adf0e8805}} , where residual {{form... | m | 7ac368a18dc9424c41ab202c50b81bcd |
The set of parameters {{cite:f3cd306c5e52cffd11da36e4fb8c196c7b158f32}}, {{cite:6459c3c19c8df2929e863ecb9141d24a79d07f7c}} are varied in the range of ;
| d | 5e2ef631da2f542b254bda2420cab1f1 |
The seminal work by Bennet and Brassard{{cite:1db30661977bb78fa0a054ff9f614f6664800625}} single handedly pioneered the study on quantum key distribution protocols. In {{cite:1db30661977bb78fa0a054ff9f614f6664800625}}, the authors designed a bipartite key distribution protocol where one of the parties(Alice) prepares a ... | i | 03a4580331f039ebd3160387f987d80f |
In this work we simulate very scarce data scenarios. We train binary VAE and RBM using all the available samples. Details
on these models can be found at
{{cite:4d040e32b00121a773afd332388d57b66afb4b0b}}, {{cite:22c9e5673958f18fdf8a1af88c1ac79eb7f0c5f2}}, {{cite:98a6b4b954f8e7dd6f0982246aff0f8b6b258797}}. Once these
mo... | m | 25fa6391847af4cc7ae72124d99ada42 |
In the field of image hashing, many direct discrete optimization methods, such as DCC {{cite:12f87282adbfcd5e3163ac7d8a5767ccfdbe0e50}}, SADH {{cite:684a45f8612f331a3f4d7cc2c3e9faa6aeb195e9}}, ARE {{cite:79b551fa2fc708c4a8dd4bd8c3e561bc8160da42}}, ITQ {{cite:aa8b179d0be99a9f29014c280cd481129ef25ccc}} and FastHash {{cit... | m | b152e1152711a3427ec6e4ac901092f0 |
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