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(3)
The relative phase {{formula:24266009-72f8-4b97-bc33-e3b192b777af}} is very small.
This is consistent with prediction of the QCD factorization
approach {{cite:b2510f2b86bf73e5938942b21c04aa7fcc9ad1e3}}, {{cite:58a3af597412c1bf9be7cd88e9aa83586c7c9084}}, where the strong phase arising
from nonfactorizable contribut... | r | 9e825ab1b9ead4cc6ed1ef8283759a2f |
First, our algorithm alternates between computing decision rules that are compatible with a tree in Step REF , and updating the value function accordingly in Step REF . Given the value function {{formula:78568c41-7a50-43f1-9dc6-b27fce2b57d6}} , (REF ) is equivalent to an Optimal Tree Policy instance with {{formula:ab7b... | d | 68d6b31214b7709c4c2fa8c02b7123e8 |
In all these and related considerations, a possible first-order chiral phase transition, and the quest for a corresponding critical end point in the QCD phase diagram, have always been themes of prime interest {{cite:91770ba72e5fcb3b90c66d03570193a28a41b956}}, {{cite:8f059f6c3a1ff5ac3b17e5ae2e190c684d75b683}}, {{cite:4... | i | 9696a2161261a8a9994730881f2ba644 |
The proposed model is a scalable auto-encoder that uses vision transformers in its encoder and decoder parts, as illustrated in Fig REF . The degraded image is first divided into patches before entering to the encoder part. During encoding, the patches are mapped to a latent representation of tokens, where each token i... | m | ef25a2e950602325ad61bb3e29a3e2fc |
Then, following the classical text of Federer {{cite:b5f71dfe6cf80504050053ca7b6adc693c6feff3}}, the {{formula:858c6af5-2025-4997-b024-2d9b2db17d0e}} -dimensional upper and lower Minkowski content of {{formula:c7753f31-3230-4bf7-a49e-e35770e23b21}} are defined, respectively as
{{formula:bcad26ad-ae2f-4ef7-a5ac-8edb959... | r | 70e4fc5da6c69d56334bb8d759e9c2cb |
The presence of Dark Matter (DM) and its role in the formation of large scale structures of the universe {{cite:f31224bcf47b99a984960b49241e036988876898}} altogether with the observation of neutrino oscillations {{cite:a64067771e966f6a80b13ec95f3ff483469d9fd6}}, {{cite:2f3d867920fa399f232d33396c02b48469ac0476}}, {{cite... | i | e4d74aadf7be50c7df5e90cae7f78382 |
Most of the research efforts in the space of detecting hateful content focus on designing and training machine learning models that are specifically tailored towards detecting specific instances of hateful content (e.g., hate speech on text or particular cases of hateful imagery).
Some examples of such efforts include ... | i | 8aeddb2fb67fe1163d9b8f78f01cc19d |
Turning now into the issues in kinetics, the {{formula:7789ca1f-d88d-44a4-8ebb-8ae40f0b8e3a}} phase transformation in zirconium base alloys comprise the process of nucleation and growth. For instance, on heating from {{formula:4e0a1287-4514-4dcc-aee5-4e731e9949b2}} phase, the transformation involves {{formula:9ab0fb2... | d | 76e80736853920b610a8c29072461f75 |
At relatively low Reynolds numbers, {{formula:4ceee466-73aa-4e32-8a58-75791e964fad}} to {{formula:2a1b4bff-4863-4c07-a5a8-59214acb1b95}} , near-wall streaks are the statistically dominant turbulent structures close to the wall and follow inner scaling {{cite:5f365dba1a2b61224af229c9614e4d794c98171d}}, {{cite:c98091a7a... | i | b015f236f6c33fbf131c13aab0eab7c1 |
This differential equation is well-known as the confluent Heun equation {{cite:412958927714e90e4c9e37438fb784494b858a68}}.
The relation between the master equation (REF ) and the confluent Heun equation was discussed in great detail in {{cite:1f3fe9e5fbd1871cbc2bd12a4d07ba2051d47932}}.
We construct formal series soluti... | m | 2d0ad10dc513bc3d3e30f1e60860b093 |
Bayesian Optimization is a state-of-the-art framework that had successful implementations in machine-learning, engineering, and science {{cite:dd40c78549f93f365cd24f4575fd266d26c22b62}}. In short, the BO algorithm contains two different functionalities. The first functionality is a function approximator that tries to m... | m | a02f2cfff90fb70667fb7a9b05dcc10c |
We propose the taxonomy depicted in Fig. (REF ).
The first distinguishing property is that
the models can be divided into two types: the ones based on processes or interactions within a city and the ones based on processes between cities.
In the former, intra-city type, most models consider that urban scaling emerges f... | d | 239664411fca829cbc5c2a9851ab3665 |
To end, we give a comment on the correlation length of {{formula:08d166b7-daf9-4167-83d8-7e8382d31319}} in the original Affleck-Dine baryogenesis scenario, where the Affleck-Dine field gets a negative mass from the inflationary field {{cite:b3b128fe58a652875be79a6a72a15f057bbe3e63}}. In this case, {{formula:2cddcf63-e... | d | c37f403c4b3f6c71322be0d15e711eec |
Camera calibration is the estimation of a camera's mapping function between a set of known world points and their measured image coordinates. The parameters that define this mapping are usually divided into two categories: intrinsic and extrinsic parameters. The intrinsic parameters represent the internal characteristi... | i | 01efea6165d2e5e7bc7cca40d1b0b7b9 |
{{formula:8d4ad816-835e-4b75-ad59-4f3adab98bb3}} By Proposition REF , since GCD-domains are integrally closed ({{cite:75c6b8a212bac578ce0eb1c7576221682b77478c}}, Theorem 50, p. 33), {{formula:f22915d0-2ec3-4974-b9ef-15e5c6cc2669}} is the quotient field of {{formula:5e190306-d299-4559-a29f-762c5eff29c4}} and {{formul... | r | e2de4859bff7b17820b65b3bacb9f5c5 |
To reduce the annotation burden on doctors, many methods have been proposed for medical image segmentation applications. Considering that unlabeled data is usually abundant and easily available, many researchers focused on implementing segmentation tasks in a semi-supervised learning fashion. The main idea of semi-supe... | i | da74be1eefcb97ddb1975037651adbc5 |
To solve the optimization problem (REF ) with the inequality constraint (REF ), we employ a quadratic penalty method {{cite:d01bd7012239650bf7d2c42eca0514a3f3b4775e}} by first defining
the exterior penalty function
{{formula:e2e988df-9aff-4f97-9653-7f9f28778918}}
| m | 7a4d23847cb3290a0c42933ae7d2abe7 |
Proof:
Since {{formula:27d051d2-80ec-4ddb-8cd1-4782eb4511a0}} , and {{formula:9ee3d25f-259d-4a6f-9b6a-ead24c9c321c}} is {{formula:58daff35-fdef-4419-9d7c-60098918a5ee}} -Lipschitz continuous, by {{cite:af71780380b6ded23af5793de0224d54187fa26e}}[Lemma 3.2], {{cite:f3ee84ab6aaa61d596af6172c8b22ba43ad9040f}}[Propositi... | m | 73b63181a1e2efd4f6a4477165c95f81 |
Other works bring in the model compression methods into sparse adversarial training. {{cite:f8365e6afa4daba2a80584dec367b6092aba69cf}} integrates pruning, low-rank factorization and quantization into a unified flexible structural constraint. {{cite:127c6ddba921de29373bb1f5e07595bf146b6df4}} proposes concurrent weight p... | m | 22840ed04c0b7325a0e6f8612fd6db26 |
The second methodology, pair-wise based, considers the relationship
among documents related to the same query {{cite:7946633eecdc37d4326f953ae5b6a4e4c68f72ae}}, {{cite:bb3bf8c3ba4e499f735be6e216ede5acfb157767}}, {{cite:7b079c06aff36ad857495f61ff21040cb4c42f8a}}, {{cite:04d26363da972c30590f634fc5214e88f00dada8}}, {{cite... | i | 2f0dd52f01e37cf984ac08a5f9906383 |
This should be compared to the usual derivation of hydrodynamics from kinetic theory, where the (linearised) collisional Boltzmann equation in the strongly collisional limit {{formula:f697e1d3-2eb8-4b40-849e-920f6dafc0a9}} is considered instead of collisionless Boltzmann equation. Using a multiple-scales expansion kno... | d | baae881ede0f5913fbbf47688bb31fa9 |
Within the cellular structure, self organisation and dynamical instabilities causes mechanical oscillations{{cite:f7b8fb506afe1433268cc2ddb099a8d328280fb5}}. These periodic jostling forces might profoundly influence the conformations of the biopolymer, mediated via the cellular fluid. Further, dielectrophoresis (DEP) e... | d | 96d66a7517e8cde1ee4ee58b9cfa20db |
+ Shake-Shake + PBA {{cite:2354de1c84473cb3784fbd98c6629a81cbf273a3}} {{formula:e815748a-52de-4731-9d03-dcee23793f5a}} {{formula:5d3f2db9-675f-4989-9f18-c78ea8b489c3}} {{formula:a9cc1513-0bc0-42a9-8e64-bec05e015f20}} -
| r | 7e7fd3503d953b4e8cf7c4933f5b702e |
The structure and characteristics of the accretion disk were calculated using our MHD model of the accretion disks {{cite:0bfd7cb292fa18a10a340f11277dadf1f1a3fdf1}}, which is based on the model of {{cite:d2fd708a91814e3a1a52d4d2b8415c4f30ac3d8f}}. The vertical structure of the disk at each radial distance {{formula:9d3... | d | 7f2016e0b796775969f70daaa1b9d46e |
Cosmic voids are vast holes in the distribution of galaxies, which appear devoid of matter {{cite:a2f6aad85bdb3b40ccd21e897ee01e1694437e17}}, {{cite:c8ec6c19910509f38d1a9a4c8c8563a19f29fbae}}, {{cite:537934af9abb72243a57ed3b13f69a4677eda1fc}}, {{cite:af6272350e0e6085a3d8c5ff64bf8b31215925c1}}, {{cite:232f0fb1c938aba2b8... | i | fcc12432a8c91fe6b24292569180270e |
Following the proof of Theorem REF it is fairly easy to show that the set of candidate changepoints stored by the offline pDPA algorithm {{cite:3ac553310a89f06a7b5af0b7ce016c26c4a540e1}} run for one change is included in the set of changepoints stored by {{formula:f2b74097-43e0-485b-85a1-cc75304ed0cb}} . This provides... | d | 98b2b79cb4a9cdfb98ad431f9243b05f |
We have shown that the lightest axion of {{formula:c3b2e7a9-b6bb-469d-8c76-ee75d02c0695}} eV implied by both the Fornax Galaxy {{cite:aa535bf3f6342a930991eaafa0021a000fa00ec6}}, {{cite:c172d5f294ebad17178f1461fea990fc15844244}}, {{cite:4668ba0e57cbb43aa80d48bb0ae441b4786a9c57}} and the central Milky Way {{cite:62bc571... | d | 63fabb88c389ce3082f7609a8c9bf354 |
In both cases, following {{cite:42fbde23b12a8d061e5626cb3380073024f25ad1}} consider the formal power series
{{formula:54c44557-6c87-43f5-a23a-b031f3943f1f}}
| i | 904048e1fb27632d759033766bd4174d |
For the hierarchical structure construction, we utilize the average linkage clustering approach (also known as UPGMA). The algorithm starts with nodes in a network treated as a separate cluster each. The closest pair is identified based on the lowest distance in the distance matrix {{formula:ff78d8d1-58de-4277-9ecd-efb... | m | a3d67219e98f15ea2f3f2e5c50f3c957 |
Domain adaptation is thus proposed to transfer the knowledge learned from a source domain (e.g. synthetic images) to another target domain (e.g. real images). One common approach is to learn a domain-invariant feature space across domains by matching their feature distributions, where different matching criteria have b... | i | 1882b5786d87dbc707e8176bf7cdb9c7 |
One well-studied class of combinatorial operations is that of sorting operations, where for the base set {{formula:217d9527-2243-4b05-a0d9-358b1cc64225}} we take the symmetric group {{formula:cd8e7d1d-783d-4ed8-b001-85774a01e924}} – the set of all permutations of {{formula:566ec11a-8f1b-448f-9b76-59e38efd1f31}} . The... | i | 7924e08dfe4e4960db44f200b4e036b7 |
For example {{cite:16b03e383d30e07bc0789870edf2b41d9cefbd5c}} and {{cite:1a4a32bdd996afc4964eb1355940f03c0b3d7fab}} determined the electron density for their sample of BCGs based on the {{formula:30a9b037-b4fe-4320-90a0-5cc9e164a736}} 6731/6716 emission line ratio and their inferred values in order of a few hundred {{... | d | d46c5180ae70bada4614a3c7ad400436 |
Semi-supervised learning (SSL) plays an important role in many real world machine learning applications, such as image classification {{cite:d8c09ef499770136bde95dc196e4c1443c66c367}}, speech recognition {{cite:cb1b0d6e8faa4994234ae6360ccfb8e9815ebd1d}}, and text categorization {{cite:418b2886bbe4f5c9823f95f76713c57149... | i | c758402620e089c6759cb6bdad122733 |
Bayesian Network. In this paper, we focus on Bayesian Networks due to their better interpretability compared to other machine learning algorithms. A Bayesian network is a directed acyclic graph representing causal relationship between variables using the Bayes rule {{cite:60365f4765afe60ed94960a192b97dca76961648}}. Bay... | d | a7e2a1e8c25f625205a10b99f5ceb9e6 |
Pseudo-labeling is another technique to address UDA and also achieves substantial performance on multiple tasks. Pseudo-labeling typically generates pseudo labels for the target domain based on the predicted class probability {{cite:a2410d66e39987756e953f7b58e3348526e61ba7}}, {{cite:12439441ed1eb15938823f3dd93cbeb2e36c... | m | a0467f17bdcbe31abe57aa510639aacf |
For open lossless dielectric waveguides, a regular guided mode at a
given real frequency is a proper eigenmode with a field confined
around the waveguide core {{cite:b2dbbf8e1bba14b55cf58ba4dee32a2e4921b126}}, {{cite:e253ae746068ff78d5c646b04770431e0d048467}}. It has a real
propagation constant, carries a finite power,... | i | 72d979e6561b9c7194305981eb75b6df |
Eq. (10) is analogous to the definition of total mass in the NGT. This analogy is termed as rather `deceptive' in the literature {{cite:3319a8be92bb65c9c2d1f46d588c1d8b55c46803}}, because the energy-density {{formula:936eed17-f2ea-439b-bccd-9b4e16659941}} is measured locally whereas the integral over the volume elemen... | m | c4b9cf009aae18ccb22856eead0cf693 |
We discuss now how temperature dependent {{formula:1a906d89-0141-4439-9e20-789326f56920}} and {{formula:dd290a5b-9567-4651-b1e7-cc0680bd8dac}} may affect the best fit value of the exponent {{formula:f963945d-2050-47c8-a749-74c15d6a5235}} . In the normal state, {{formula:5c412bff-a679-4821-b229-14bc56ac4833}} by virt... | d | a84f50b1db19407698e538d14cc67198 |
We evaluate the performance of Magic Layouts and contrast state-of-the-art baselines such as (Faster-RCNN {{cite:2badc28463523d873f74404ec968afbf70324224}} and popular variants {{cite:adbc0ddb18112fa3f2cd0480c2b3740881d52187}}, and RetinaNet {{cite:6b58b81f97f11342391698e71c29ae631c7940ad}}) as well as the recent spati... | d | bcfad139f0d9fb0573e8079be8f270ef |
In order to leverage strong supervision, one could try self-supervised methods.
It has recently been shown that these methods, e.g. {{cite:7734d8c3c6c44d4945b0d7a4e3b4591c82aa2a4d}}, {{cite:f09010bb5da167644edab5510faeca20941e4828}} can learn generic representations that generalize for many
visual tasks, in particular ... | d | e441524f7faf9e24c03a8d75b1bb7290 |
The position angle of the primary jet, as determined from jet model {{cite:0263fe25a8a4bc1ace15efff08990631cdc058df}} as well as from VLBI observations {{cite:aa7f784847cab39c0a4d27d63c22e5336d66881a}}, agrees with the polarisation position angle observed in this work. The models give {{formula:f71f2178-c67d-48ea-a48e-... | d | aa038b2612637d6f34560ed579d7fb17 |
Finally let us comment on the cosmological constraint.
In the {{formula:1d1cb4b8-7264-4a01-9731-bbdba879c346}} model, the SM gauge bosons have only even KK modes.
In particular, the fist KK photon is projected away and cannot be a dark matter, unlike the minimal 5D UED model.
Therefore the most phenomenologically natu... | d | 7922cbd36e06e2d70906399755983112 |
Large changes in head pose. The reenactment results we presented are mainly frontal. This is attributed to the training data, which consist mostly of frontal poses. Actually, both 2D and 3D-based methods are limited by the head pose variation that exists in the training video. We observed that all systems struggle to s... | d | a5914978b6a6196865cefe17d02181aa |
In this paper, we examine two different types of layered structures where the layers are rotated with respect to one another as sketched in Fig. REF . The geometries of the individual layers are called square (Fig. REF a){{cite:3c27e657993106a690fc696ca9a3ba3732a7e391}} and pinwheel (Fig. REF b){{cite:df0ebb10d340f1279... | i | 85828b62d348827d8c2fa56bdc0af4ed |
With the LVD method several arm structures have been suggested.
The densest and most coherent LV ridge is called the Galactic Center (GC) Arm I, the second is Arm II, and further Arms (III and IV) have been proposed {{cite:1c725be9a34dfeba41269a1729727e7cdf920023}}.
More recent analyses have shown a larger number of ar... | i | 7394f7522817d514d01811161ed0dbaa |
ItemPop recommends the most popular items (i.e., the item with the highest average rating) from currently available items to the user at each timestep. This method is non-personalized and is often used as a benchmark for recommendation tasks.
LinearUCB {{cite:c94846347af5d3f0a71db33c2ff2c6bd591e47d9}} is a contextual... | m | 7c1433fb76148e4469c2042208da4baf |
Bi-based materials are known for the presence of TSSs {{cite:9d74f6f47a1bc5b42682499c1b996ff71a36dd43}}, {{cite:10d5c7b49b9ef350f31e52d2243db89ca9613a8d}}, {{cite:d207bdac0421808537fb1b2f457d6bf89e51ecb0}}, {{cite:d4f1efa681c26df74eb058a941742835428b7b97}}, {{cite:268202eca265e524e8b9a9d06c6ef25d7c1ef67a}}, {{cite:9828... | i | 6161cf57034d408938c934b1d5914df8 |
A more challenging direction is to retrieve relevant commonsense or passages from open source and incorporate them as evidence for answer prediction.
Previous work {{cite:9e8ad24e8f08311fdb8dd45653972217f6445f63}}, {{cite:3c9464fb98f87a23ab94f3bdbfddadb6ac47461e}} can only achieve poor performance on this topic due to ... | d | 7ff0d60520c7cafe21c1ed9de012bac6 |
In this section, we evaluate our proposed multi-level SMDP through numerical and simulation results. The results are compared with the staggered threshold and bulk setup policies with parameters given in {{cite:d33a09009a890dda132e395b0e9a14f60676e309}}, and the uniform state-aggregation method in {{cite:215e7d4a0cbe22... | r | a4a773f7942eb3cc467a6b9f085a8478 |
The performance of deep learning-based classification should be further improved. Although the published papers showed the advantages of deep learning in EEG classification and demonstrated that deep learning is superior to conventional methods, the performance is much lower compared to the performance achieved by deep... | d | 6beaf8c88d958f0bfdbbf0d76b09a3f7 |
The lattice structure of qHPC{{formula:9cc962a7-5145-4310-92cc-e6d70f6586af}} is available from reference {{cite:c82ffb743e1648297c917d77da890c28ae71a0da}}. Its square unit cell consists of 120 carbon atoms, (see Figure REF ). We fully optimized these structures and calculated their electronic, optical, and mechanical... | m | 754cd9e67adc7e28e786c08e54ea3227 |
The main advantage of the ETDM implementation presented here, based on a general preconditioner, L-BFGS algorithm and inexact line search is robustness. For small molecules
the computational effort is similar to the standard SCF approach when the latter converges, but the ETDM is found to converge for all the molecules... | d | b0319290a8e925fc600946cd59125413 |
Linear optics has inherent probability characteristics for the implementation of controlled quantum gates. With the help of an additional entangled photon pair {{cite:6f2af1bd347d25f32073eea5e866b6ccbe3d9de2}}, {{cite:287c869508a464c9d05c7a0018e0fb7a5a518235}} or a single photon {{cite:954e7d08ea7bb720df9b26096986eedbc... | d | 6bef868504047aa8bf802960a149abde |
In addition to {{formula:3161b3b0-3f5f-4f53-8861-f30dee312207}} , the estimation and inference for noise level {{formula:75bd95be-1ebb-490a-a009-44dbbd6fc4d0}} is another importance task in high-dimensional double sparse regression. Motivated by the recent development of scaled Lasso {{cite:46d023f9330941978fabf19567d... | d | 8373adaebe649c44b1807611a7908cce |
which are the same as those used in Ref.{{cite:dd5690e56f4d4a592a1f092d3f071be24d7b53ce}}. The factorization and the renormalization scales are taken as the “transverse mass" of {{formula:0a7ccd7b-da37-40a3-97f3-4fb66bf4735e}} , i.e. {{formula:891718f3-7144-42b5-bec1-d3ca41de4af1}} . For the extrinsic PDFs, we adopt th... | r | 0d87b412280dc0d9b4d9aab92168a6e6 |
Optionally, we apply a PCA (Principal Component Analysis) transformation to reduce further the number of features to the range of 30-50 features. This speeds up the computation of pairwise distances between the data-points in the next stage and suppresses some noise without severely distorting the inter-point distances... | m | b6abaa1d77e1d30451b87597449c50cf |
Complicating matters is that even when regularity conditions hold
at parameters near singularities and boundaries,
convergence of the expected AIC may be slowed, and
a generalized form may converge faster to its target. In this sense, the AICg
can be thought of as a finite sample size correction to the
standard AIC. Wh... | i | 8ba1959dd916e25c6d6b4bd2387355ff |
This small-scale quantitative study of model evaluations provides clues as to the values and goals of the ML research communities. Test data was often old (e.g., the CONLL 2003 English NER dataset {{cite:cd9a4c04da80ccdac617d56456fcfcfaf97208ca}} used in two papers); optimizing for these static test sets fails to accou... | d | 07aff70402400f500521017c97a310c6 |
Since blind deblurring methods cannot be implemented in real-time, we next use three non blind deblurring methods (as explained in section ) with a known PSF. Since the blind method {{cite:172c2900ebcf863c9d7423cec96b6518c121eff6}} gives good results, it stands to reason that it is able to fairly model the underlying b... | r | 0752f4c09ac55a2d9907f498ff01032a |
The initial discovery of the anti-D3-NS5 metastable state was performed from probe computations in {{cite:1f2bcd1f36959356c85d96d346177f0d564816a4}} in two complementary ways: {{formula:134c9cc4-2045-4bd8-80af-e795567ebe0a}} using the worldvolume theory of the anti-D3 branes and {{formula:20399ffd-63ad-4e61-9b42-25b67... | d | 7f2afd596f6bb0d95312c133be1db45e |
For appropriate transition densities, {{cite:2c8912567600efb88476369533da3653eb4d9f5a}} showed that the
forward and reverse-time Markov chains may be viewed as discretized
diffusions. We derive the continuous-time limit of the procedure
presented in sec:discr-sett-mark and establish convergence results. The
Markov chai... | r | 410f4236c0690595107b9e8a52e10947 |
We calculate the excitonic spectra by solving the Bethe-Salpeter equation (BSE) in the Tamm-Dancoff approximation
{{cite:bc71d6607f2d24ad80f1817c88096f37a7bb2e0c}}, {{cite:4956096e6251787eb31bf9fed0806634b0845ce0}}:
{{formula:fbfc0e3b-27b6-4b68-8906-2cadb578817b}}
| m | 6ba203023577e469a5da82d50f2822e9 |
We show more visualizations and quantitative results to show the efficacy of our method. Namely, Section shows qualitative comparisons between our method and existing state-of-the-art methods, StyleGAN2-ADA {{cite:8429e3eb250e188d721b0c1d123ac6a0ea10632b}} and DiffAugment {{cite:6387e4ea4d115a4761e7be633341cf8cf08f8aa... | d | 93a6fe6eb1b467778b997d5a2439a428 |
Episodic Rehearsal: store a subset of the datasets used to later "rehearse" them in subsequent training of newer tasks. While this method might be the easiest to implement out of the 2 sub-types, the model can easily overfit to the subsets due to the limited number of samples, and does not scale well in terms of memor... | m | 9f17ab2a4cc0546c3025752597543578 |
We then report the WER performance of MSRL in various conditions, as well as comparing it with other competitive methods. Four recent published methods are selected as strong baselines, which are RNN-T {{cite:5d7d6ec2789b9eddfd3b9b3d4d2ce549f71612f9}}, TM-seq2seq {{cite:c82bbdd8671eb630215e3ea06ea332be87796a02}}, AE-MS... | m | 94fb38ac4dce3222434d5d9d4b052c9e |
We compare the proposed network LS-MBD-LCISTA (fig:ls-mbd-lista) against the optimization-based method of fixed and structured MBD (FS-MBD) {{cite:6d475d0cfce7ae6c95e72fc660396b3859ff3832}}; FS-MBD uses source information in the Fourier domain to design a compression matrix {{formula:756562f8-4bb9-4571-a040-42ab35a05a4... | m | 9424c153f451334e32cc90e70965d770 |
Path-following (PF) is one of the most fundamental tasks to be executed by autonomous vehicles. It consists of driving a vehicle to and maintaining it on a pre-defined path while tracking a path-dependent speed profile. Unlike trajectory tracking, the path is not parameterized by time but rather by any other useful par... | i | ad5af7a7425d74ec674b2b79ebbf11d4 |
In this work, we investigate a set of leptophilic models, {{formula:2d8a592c-958e-44e0-9621-85acee0c3a16}} , {{formula:2848be7b-383d-4434-ad81-393428cad228}} and {{formula:1ff14e49-a8ce-4bae-b1f0-2726845335ad}} , where neutrino quark couplings arise only at one loop level and, due to this suppression, are therefore ex... | i | a9ca80bee1cd6110cbbaccd851bc26b0 |
Datasets and Settings: We use widely popular datasets {{cite:0954b4b9a73157ec13768414b2ba2251ddd03c7a}}, {{cite:0358f7a3b6a1672b506395cd4cc465e58a38272f}}: MUTAG, NCI1, and the OGB-MolHIV for graph classification; PATTERN and CLUSTER for node classification; and ZINC for graph regression task (details in REF ). We borr... | r | 57c981da1b0cf8310f75d30d65a336b5 |
All the improvements over {{cite:ba4807111adefa8caaca8ad758aa591b6f2be138}} mentioned above (excluding the generalization by King) maintain {{formula:0dd78e2b-3be5-4743-bd8f-020300390c02}} -approximate distances rather than exact distances. A result by Roditty and Zwick {{cite:175d5d058fce07ce8e76e8cf75b7195989e93905}}... | i | 7361cb003a4a3cbdf9bda652f0c3c2aa |
Other approaches. To address the challenge, we also have tried two other approaches: transformer-based behavior cloning {{cite:4b6d7e50736623cc49d4975320c29003b029df2e}} and offline reinforcement learning {{cite:2a44f528a30e45ee3c8fb5641cc290bb24bf1d6c}}. However, the hundreds of demonstrations we collected for the hum... | d | ce69ea994f27b21fdc748c75a845f97f |
where {{formula:a13d89dd-f50b-4531-beeb-4062bf5c8b6d}} is the magnitude of the electron charge, and {{formula:06748d45-76b2-46bd-90be-a32d81c55d4b}} [with {{formula:27d3b4fa-2dbf-4706-8aec-c147a6616b13}} and {{formula:d0aa39ef-176f-4ea0-8414-29cac7763dbe}} ] are the normalized (by {{formula:8b8a1bd4-4ccf-4794-bfa1-8... | m | 1b9ea9f21562d9f95332e3765c0ceac8 |
The scoring function used here is found by automated machine learning techniques (AutoML) {{cite:e2c40a35102ef2831b3bc18cd742740941a938d0}}, {{cite:59ad583cf6d5f10bd02dbb6097a3ed98fece8906}}.
We first describe the search space where we find the scoring function (SF) in Section REF .
And our search algorithm is introduc... | m | 836609773601470b5bda00bd7b75a11e |
Young star-forming regions often host massive stars ({{formula:789695d5-bc0a-494b-b8ee-c3fcc2daf4da}} M{{formula:1294ab8f-6d17-4bd9-ab1e-8552291f57bb}} ), whose rapid internal evolution produces intense far ultra violet (FUV) and extreme ultra violet (EUV) radiation fields. Several authors {{cite:eec4702f8870eb3491fcb... | i | c22de04a45bab6368ed4749eba1fdf5f |
Another useful direction is a hierarchical multivariate dynamic model (HMDM) setup where the observed data vector {{formula:1cf38420-17c2-4b53-9d90-ece27c646d62}} follows a multivariate Gamma distribution.
Several multivariate extensions of the univariate gamma distributions exist in the literature (see {{cite:e45c4d5... | d | 45a1a8ecb60f5c14f745a76c19ac7bca |
The AOUP describes the motion of colloids in a bath
of active particles {{cite:b3420932898829f5366ac98bcc372963eab9d41b}}, {{cite:cbb2f56c7476d048f1abc567f0e81d3e8c3176e5}}, {{cite:d13e17d728a6141044012a7c621b55e2482158a6}} and, in the case of a bacterial
bath, Wu and Libchaber {{cite:a0af752999aa515843163f996d05e38c24... | i | c61d04717be5fe7d48985606e0ff0eb5 |
Our electronic structure calculations are performed within
density functional theory (DFT){{cite:2879d540edae7940fbf8aaa9288f933b68586306}} using
the full-potential linearized augmented plane-wave
method as implemented in the WIEN2k package{{cite:ed06a60185b2d7b39245898e217e20dec5490169}}.
We employ the generalized gra... | m | 879dbd455dbb06e09580760204f8f68e |
Low-data regime.
On the VTAB benchmark, we use a similar setup and hyperparameter budget as {{cite:ae7afe55e38718b89ed44feed89af3bc4da0bb0d}}
(but fine-tune with half the schedule length). tab:vtab shows that, while performance is similar for V-MoE-H/14, experts
provide significant gains at the ViT-L/16 level,
indicati... | r | 34bfadca6f72206bfa25f4d6b966c273 |
In this paper, we have presented an efficient method for sparse identification of dynamical systems described by ordinary differential equations. We have shown that the Levenberg-Marquardt algorithm, on which our method is based, can be rewritten in a form that enables parallel computation to a large extent. Therefore,... | d | a3aece9264c3791d6af20e43701b72b8 |
It should be noted that a recent trend in incorporating machine learning, especially deep learning, into modeling molecular potentials emerged {{cite:a14b88b757913ffe6df95f23e08c4b61571b65dd}}, {{cite:4bad91bba5826d39976434060119df3815f6438b}}, {{cite:08170f820f501d8f9d275b0f33a40a430f0f3853}}. Another related field of... | d | 1747b61958e3a86dcdba782e3225dc12 |
ACNN: A CNN-based model {{cite:a1a9687eeba1028b296c98f2e0d9e7d231dbd11c}} coreference resolution model that can also produce the mention and mention-cluster embeddings at the same time.
C2F: The end-to-end coarse-to-fine coreference model {{cite:c2770e22fc5035dcaa32e1be79013bd73296a1b4}} with BERT {{cite:a391574c1f77... | m | a67e153fc11f0f650d39edc9d8e90460 |
Still, the fact that we can train an SVM that matches (and even outperforms) its corresponding deep GLN indicates that our theory allows us to successfully disentangle the particular optimization procedure used from the inductive bias it implements.
This means that we can consider alternative learning algorithms that f... | d | c218dcb2cf99fc07b60a87bc89c7129c |
In Figs. REF and REF we report
results for {{formula:4ee9c25d-6f42-4182-ad58-d1c1c609f6f1}} . In this case, the order parameter {{formula:f76c8db8-dfe0-4cf9-b78c-c7881a1b7e4d}}
defined Eq. (REF ) is critical, signalling the breaking of the
SU(2) symmetry and therefore the presence of a transition that belongs
to the... | r | fd466534a968e7b1799f2aaa59321433 |
Therefore, {{cite:47a1d1ddfe82e02f6eaff469b2862651704d20a5}} propose to replace the buffer with a generative model in the form of the Generative Adversarial Network (GAN) {{cite:7e8699ae6711e4d487a0d4da423b2edbdc0fa702}}. Any structure used to regenerate past data may also suffer from catastrophic forgetting. To avoid ... | m | f404da8647e71f72297fc62bef7b7557 |
We further compare the performance of MirrorNet with state-of-the-arts reported in {{cite:75a1bca4025459b3fc16ce29eb0817a619a1c3b9}}. Table REF shows the performance of different methods in terms of E-measure ({{formula:ec1a2308-0fa4-4859-978f-8e9471e5425e}} ) {{cite:ac07384520a6ea479fa28333e87c9646eaa79c4d}}, S-measu... | m | a3bcff0f6b35c33dc031ba39de0ce55b |
Unconventional computing frameworks, such as reservoir computing (RC) {{cite:455155eeb1987279a8f03f411f3d7fae82e568ed}}, {{cite:78be43bc2304db7cfa4676d6b68c7d6394a1ee6c}}, aim to take advantage of the dynamic traits of a given substrate to perform computational tasks.
RC was originally developed as a method to avoid th... | i | 69043affb04314a9a9b4e0f4f2078517 |
We rewrite Theorem 8.2 of {{cite:4e7052764bfad7abc2f4a5c456b196b6ec764cef}} for our convenience.
| r | 644c26c865461f2ae5a224838a4b21f3 |
All code was developed in Python language.
The machine learning techniques presented for the activity recognition and the CNN-based decoder were implemented with the Tensorflow/Keras framework.
The computational models were implemented using the NetPyNE platform {{cite:235b3d2398048c8cd804a9efafbb6e561600cf31}}.
The ro... | m | 55722585d23ef58ba7dd937aa596fd93 |
Density functional theory (DFT) based calculations are performed to study the structural, electronic, and magnetic properties of Fe{{formula:525e0b38-a4cd-406e-adc0-ee0cb7197743}} GeTe{{formula:013f2d50-baa0-41dc-8152-13c59b2bc578}} (FGT family) systems. Structural optimizations are performed using Vienna Ab initio Si... | m | 7490190e90d54422e8bee9d93e6dd34b |
Wireless technologies have been anticipated to move from the conventional orthogonal to non-orthogonal solutions to meet requirements of future wireless networks, such as, ubiquitous coverage, high data rate, low latency, high transmission reliability and scalability {{cite:82e407f5c7a32123a8dc8cc5f394769524f8381f}}, ... | i | 0ef25b25eb9f21e263c203659167ded9 |
The current rise in popularity of colloidal active matter is due in large part to the recent advances in colloidal synthesis. Through the pioneering work of synthetic chemists and material scientists, there is now a number of experimental realizations of synthetic microswimmers and active colloids. These active particl... | i | aed3594a5ff0efaa0a61c4ff8f47f8ad |
We discussed in Section and Section that various methods to calculate sparse loadings exist. For the examples in Section we used the method of {{cite:1865069f80df0fb444997c9f3bb79210614a081b}}, and the loadings for the example in Section were obtained by the technique of {{cite:c127671756f66d6f6253aaf24ae53ca838ccd... | r | fe904335cf82e19436a5025d24df0545 |
For the case of LRHRC we find a rich phase diagram, where the power-law distributed unitary interactions are leading actors in determining the properties of the stationary phase. For {{formula:cf5b5bd8-418b-4c47-b7f2-1473da1604b0}} the system persists in a volume-law phase for any measurement rate {{formula:e81d1376-a... | d | 49cd0e7fc082e1a8d8063c562ecff3f1 |
In Table REF , we provide our ablation table by also adding the results with the content variable. As explained in the main paper, content variable does not improve the performance of our models in contrast to the state of the art video prediction {{cite:0daa2ca83ff0f3ef5ec7947da0e1c419da5020df}}, therefore omitted in ... | r | 736926ac5dc689bc8956af0f84ecb04f |
where {{formula:a7594b92-de34-482a-b7ca-19e7b906148e}} , {{formula:28f9ab57-9844-4dbc-802b-9402282430f1}} and {{formula:3dae172b-3212-43fe-bf53-96f24631f423}} denote, respectively, the number of free neutrons, protons, and total nucleons with local densities less than {{formula:13a26b19-ca31-4616-949b-33054f58875d}} ... | r | 46d5f035e66e5cd7885e822036fc00b2 |
(ii) According to numerical simulations with some analytical analysis
{{cite:45502f9e4932d6775f6d23ed365d21e60dfbb288}}, {{cite:3691b34a54ba14e6629d8eddf4e7dc567964fef1}}, {{cite:7431be3ad68a0b8d85dc68e8b4a02a8f51d2c342}}, {{cite:b115cfb94e3f772bf93dd808a56738c7d0bfe11b}},
{{formula:714828ca-caa5-469d-b309-86662b3d0adb... | d | 1ad444259f61a63480022d38b2049b77 |
Emotion-dependent models may require more training data than emotion-independent models because the number of units/models is increased by multiple times (n times where n is the number of emotions). However, with the recent advancement of pretrained acoustic models, the amount of data needed for training speech recogni... | i | b2dcf0447079afb2e9e4d56a9034f84a |
We train MoE models based on the Transformer-big architecture {{cite:9efc7b64af64bf1362cc490cd7feaeb289a1ff35}} with 10 billion parameters on the Web-50 dataset for up to 20k steps, it is very time consuming to train such large models for too many steps.
In Table REF , we report the throughput of different methods meas... | r | fef9b068c2a3bd2904dd9746ad1ea336 |
Next, we will introduce a new property of dynamical systems which give a sufficient condition for that {{formula:bfa9861a-4b7d-41be-895d-29a573158093}} is a nonempty open and dense set in {{formula:baa6a99f-5b32-4f09-914f-9739dc2c6e2e}}
Before that, we recall specification-like properties.
The specification property ... | r | 99cb420e574e7c9921df6b82b2cb834e |
Another major set of algorithms, known as empowerment, have also proposed using intrinsic rewards as the sole goal of behavior {{cite:953a9fc683a42b249404387c0b4ee7480def4ab3}}, {{cite:9182b7cc58e8f8f0b6b0fb654c00a3f2687b6ec2}}, {{cite:a5976134cf66aa7f495b35c7a8e5d769858469cc}}. In this approach, the mutual information... | d | caee5f86439bf3f1a554db1d8591d058 |
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