text stringlengths 54 548k | label stringclasses 4
values | id_ stringlengths 32 32 |
|---|---|---|
This shift of the modality from the structured (image/video) to unstructured (skeleton) data type provides benefits in terms of data compaction, computation, storage, scalability, and recognition accuracy. Furthermore, the skeleton-related attributes mimic actual physical traits in human body and can be utilized as a s... | i | 8a436f303f71e59c34d4a780629b7521 |
Unimodular gravity (UG) can be defined by imposing {{formula:8a0d0f5d-9fe7-42b1-9502-a62039d8c496}} as a
constraint, where {{formula:ebd10828-6443-4d06-bc71-e4d9b9918f0b}} is a nondynamic background volume
element. One often chooses {{formula:6013a195-a154-4ad0-ad1b-5e986a46394b}} , hence the name unimodular gravity.... | i | b516706a208061f8187713622e567c15 |
Baselines
We first benchmark FeTA against vanilla transformer {{cite:a6f2a7e1d088d18fcaf2c6d57bb757eb88a545f3}}. To study impact of position encoding on FeTA, we compare against recent PE-induced vanilla transformer based approaches, namely Graph-BERT {{cite:e5e85405b16a2f9e52c11caa23f035c739e61e45}}, GT {{cite:2a33340... | r | 7c02ba395bdb38ca6318264bcb4d3567 |
When attempting to derive the Hawking radiation, as far as our quantum improved black hole can be viewed
as an effective classical geometry and geometrical optics for quantum fields can be applied as in the Hawking's
original derivation {{cite:4514b8c1151477229a172e844ea0fe8c78fe20ab}}, one can naturally expect that th... | d | 4f259cbfc557609c3e816f8d682d8b9b |
Digital traces such as social media posts or interactions appear to be extremely powerful in gaining knowledge about our personal lives and predicting political beliefs {{cite:0eba81c6615d2ff202d97eea00ccf6f8e813c727}}. Automated analysis of electoral support on social media could effectively replace traditional survey... | i | 058437b5c668c167c8388718f69f3ecf |
For thorough evaluation, we report the results in terms of different attributes in Table REF . It can be seen that the best five performers achieve the best performance on various subsets. Specifically, improved from state-of-the-art L2S method {{cite:de817bab38898e6b5065dbc206d843ba564e4500}}, FPNCC (REF ) obtains the... | r | efaae8de62895f14179e2550269118b2 |
In this part we state some known results, which are important to prove Theorem REF and Corollary REF . As for the proofs for these known results, we would like to refer the interested readers to {{cite:c58760a2cf83650aae3f9fd22767a6586d9f8af4}} and {{cite:3993601a78740a917c3356f9a709a4d1513a4b75}}.
| r | 9e88845c0dbcbc724b9dbca7881487f2 |
return the combined coset {{formula:f3ae5605-233f-4276-b3af-9d5d3833b8ff}}
That the procedure works correctly follows directly from lemma:isoaut-item2 of lemma:isoaut given the coset decomposition {{formula:fdab1baf-26ac-411a-ad74-5866a9edfc02}} . Line REF is justified by the fact that
{{formula:22d8f36c-6de2-4977-... | m | 6cbe29a2d0940dab3e88ce6501c6ae65 |
We can propose several avenues in continuing this research. In our work we calculated the relativistic effects in the context of perturbed {{formula:32829e71-ac5f-44bd-837c-7d0c0e149932}} CDM to obtain an estimate of this effect. Implicitly this assumes that fluctuating dark energy does not alter this effect. A complet... | d | 0810dae6a875f5d3b1c824cd854b7e93 |
Split Mini-Imagenet: Mini-Imagenet {{cite:474972c882b4f162daefbd4a3a71b39726ae8942}} is a subset of ImageNet {{cite:d631f519a6545ceaa9ddcc0b737c046d2052395e}} with a total of 100 classes and 600 images per class. Each task consists of 10 disjoint subset of classes from these 100 classes. Similar to CIFAR variants, 2500... | r | 13353cb3cbe36f04039e871a632d2f69 |
Theorems REF and REF are two new additions to a long line of results identifying tropical moduli spaces with non-Archimedean skeletons of the Berkovich analytic spaces associated to their algebraic counterparts. We refer the reader to {{cite:24a9c530037aee981b22718e8c8a16a27c431e2f}} for the case of Jacobians and to ... | d | 14fe1edd9df4a82bee0fa969f158b5a5 |
Learning representations by combining quality diversity (here, MAP-Elites) and generative models (here, a VAE) opens promising research avenues for domains in which optimizations of the same cost function are launched continuously. This is, for example, the case of Model Predictive Control {{cite:75d9a4051cbe7bfd896d65... | d | a94f7def08f3cd3b4524057448e2934d |
We also add the the test–particle lines (TP), which are given by {{cite:e5bbbaa1b3a546acd12c1ae1b8c8be68c6b75220}}
{{formula:7b3efc27-9aaa-4f52-9a14-0e0f181735b5}}
| r | 676e3ea343e24a82a62caf2732132619 |
With the emergence of deep learning, DML has gained significant popularity because it can seamlessly incorporate the strength of deep learning into metric learning {{cite:3c465b15848be2894b5c0c26a9aa0ce0bf8e4dc1}}. The DML automatically constructs task-specific distance metrics in a weakly supervised manner. This resul... | i | 8ca163bd681c26256c3397158d614001 |
In this paper, we did not fully explore the effect of the threshold {{formula:a3abd31b-66df-4918-8dc2-589b089e4ab5}} , but rather chose to focus on methods which are less sensitive to this parameter. In our case, there were no significant differences between the results obtained with the two tested threshold, which is ... | d | 2101bab5770e5d12ed6740c963f85c65 |
The spectrum of known heavy-quark exotic hadrons continues to expand
frequently, with about 50 candidates observed to date. Almost all
have a valence light-flavor content consisting of only
{{formula:0a3f2a9f-fc34-4ad9-b3ab-61ed3460625b}} and {{formula:62a82c3a-e7f5-44b9-83db-7edf3d621d86}} quarks, but very recently ... | i | 778173094cf01ea0fb0f4826ca0f8dba |
Results on FER+. In both settings (with and without data augmentation), the local SVM approach yields better accuracy rates than the global SVM approach on FER+, but the differences are not as high as for FER 2013. Without data augmentation, our combination of deep and handcrafted features attains an accuracy of {{form... | r | a3c07d4ef85c8edabe48da5ac15e795b |
As we wrote in the main paper that we also conducted experiments of many-shot and 20-shot, here we show the results in Table REF .
From the results we can make the following observations: (i) The downstream transfer performance is approximately correlated to the in-domain self-supervised learning evaluation, i.e., the ... | r | cdc0d59addbffff0e1135e9fa1ea9102 |
where the angular quantities {{formula:f702d9de-95c2-42ee-b9b9-54a035f56aa7}}
describe a direction of {{formula:6ada4c25-9ba2-45e7-83fe-492c03bf38b7}} in the {{formula:4dbdc2eb-313b-43b8-b9c2-4702fadf2c19}} rest frame
with respect to some specified axes,
{{formula:ce948a9a-189f-41bd-a02f-bdc42e01839d}}
are the angu... | i | 18f5366c07adab2a85c927f650571335 |
Furthermore, left-symmetric algebras are a kind of natural algebraic systems appearing in many fields in mathematics and mathematical physics. Perhaps this is one of the most attractive and interesting places. As it was pointed out in a paper of Chapoton and Livernet {{cite:eb9c722f033a20df601c9d9b5421a5032a00c0ee}}, t... | i | 25c1f31ca8f4211c430265085e178e47 |
According to {{cite:943a756ac70cb4ecda746664710e23bbd688abb5}}, for instance, there is a good correlation between the radius of the H i and the stellar disc for spiral galaxies. Thus, this (local closed-box) model suggests indeed a correlation between the local metallicity at the effective radius and the H i mass frac... | r | ea863f5b397b783b79200a135c5f7ba8 |
Explainable Artificial Intelligence (XAI), especially Explainable Reinforcement Learning (XRL) {{cite:b7476be0c3d2e503f83e41214aa7f9770d078b4c}} is attracting more attention recently.
How to interpret the action choices in reinforcement learning (RL) policies remains a critical challenge, especially as the gradually in... | i | 911aea4b9f916be916b3644430f102c6 |
Regularization IOT consists of different ordered blocks in a weight tying method, which may looks like a parameter regularization to some extent. However, we show that IOT is more than regularization and can be complementary with other regularization methods. Setting (1): We first train a Transformer model on IWSLT14 D... | d | d17eb88be9f6ddb8b4d78f45864f2fb4 |
It is well-known that the Type-II weak topology on the probability space {{formula:d0cc670e-a380-4dcf-9399-b41e2f54d6ed}} can be induced by the Prohorov metric if the ambient space {{formula:049909d7-052f-4d70-a0e2-9febe8bec674}} is a separable and complete metric space, see {{cite:95941a31aaf878e1de561da7672fe2a6474... | d | 0fa6ad386db2d9f79ad45667bebfe0af |
In addition to the binary-based representation, which makes it difficult to capture the inter-category relationship, {{formula:d32b0fbd-f125-424d-acb4-60bc66436557}} -Net uses the Euclidean distance (see Table REF of Appendix ), which is prone to be less discriminant in high-dimensional data {{cite:e283a45532c2bd517bb... | m | 756c8aaacbb098fcbe943197beb6f681 |
At 1 AU, the narrowband oblique whistlers are most often associated with SIRs, often filling the downstream region of increased
solar wind speed, and often variable magnetic field and lower electron
parallel beta. The waves are also seen within CMEs
{{cite:b461949e55e2fdc0be4f5d591c747ac458526cad}}. As shown in Figure ... | d | 715a94c5483a64e07e985d698bc0fa9f |
(Part REF )
We show that 3 implies 1.
Denote {{formula:9c671e68-6963-40e2-acc4-226695511e27}} .
Let {{formula:ff6408da-d908-481b-a897-28d87ca6a3c5}} small enough that {{formula:ddc52cb1-4cce-414a-ad1e-74fa96a9eaac}} .
As the pointwise limit of convex functions, {{formula:a6522e94-89e4-48e4-9883-41a524fd9f8b}} is conv... | r | 9f85ed7123a16dbc126e85edfaf44cd2 |
Accreting black holes (BHs) are bright X-ray sources powered by the gravitational potential energy of accreting materials. The luminosities of Galactic BHs are strongly limited to the Eddington luminosity ({{formula:a6f4348d-ede6-4975-a090-8889cedb9d4d}} ), at which the radiation pressure balances the inward gravitatio... | i | 681d7b6555169841fdf462c3b2430d8f |
The recent new effects at the LHC have shown signals of di-bosons that have masses around 2 TeV {{cite:86a80056fc864d8b13b87a8c112695e554ebc663}}. It has raised hopes for the existence of new bosons in the Zee-babu model. An interesting effect in this model is the small mass generation of neutrino at the two-loop level... | d | b471a6a97b81b740dc012e5b4860b225 |
Code properties. Our findings suggest that while certain code characteristics can be extracted from pre-trained code transformers with linear classifiers, implying that they are firmly encoded in the hidden layers, others, such as cyclomatic complexity, cannot be extracted as effectively. We plan to investigate whether... | d | c60fbf3419d91563b68c734d470d0c55 |
A quasi-deformation of {{formula:5a32b7eb-9940-43cb-84b2-0ff1158db79d}} is a diagram {{formula:e2903128-ed6e-4124-9117-7534f478a4f8}} of local homomorphisms, in which {{formula:84f65bf2-b49a-4b55-a66a-3d59e811e66b}} is faithfully flat, and {{formula:6804421a-7046-41eb-a32a-baf24f8d7ced}} is surjective with kernel g... | r | cf544af4ceaa7b124757dd7a637864f7 |
In Section Methodology we introduce a novel secure inference protocol that aims to improve the time and communication cost while preserving the privacy of all parties. We consider that a server has a well-trained deep neural network and would like to expose it as a service while preserving the privacy of both the data ... | i | 9d175e44343776d96e832024ecc63544 |
The anisotropic part of the Knight shift comes from the magnetic dipolar hyperfine interaction with {{formula:f386495e-1ad0-43bc-9767-2029ce32134b}} spins. The different anisotropy of the hyperfine coupling tensor suggests the site-dependent {{formula:ec393eba-c8df-4b70-84a9-8e49c3af2992}} orbital occupation ({{formu... | d | 1e1be24f33b52299158608d0e143d6ca |
To leverage inertial, energetic, and cost benefits of small-scale robots,
critical future applications of autonomous technologies may depend on
coordinating large numbers of agents with minimal onboard sensing and
communication resources. However, a critical problem for autonomous multi-robot
groups is that state-of-th... | d | 17ac4dfed79b90f48b506588d91852c7 |
The low error rate of SC processors makes them an ideal platform for quantum error correction (QEC) {{cite:1410f099dc8a46b66fcf72671fafcde374d13f9c}}, {{cite:f1063e3f9d04878f86b14b40deaa1085f023b538}}, {{cite:e1aa10a2ba607b0fcef5290e874ed784151fdd91}}, {{cite:94196dc8485dfb6cffa59ff42d17ab18886473ea}}, {{cite:3ed6ad776... | i | 98876af23603f287d2bfc5ec15025061 |
The implementation details of our model are illustrated in Table REF . In the proposed model, the CNN sub-network consists a convolutional layer, a max-pooling layer and a flatten layer. The RNN sub-structure includes a hidden layer with 200 neurons. The MDN sub-model is composed of a hidden layer and an output layer. ... | r | 1980bb150dffc230386072f4d3b0b618 |
In this paper, since the video source for our benchmark is Kinetics {{cite:e65b10cc3c485520a93f08cb2775fce6c39a9a1b}}, our target boundaries are event boundaries.
This is because each video corresponds to one single, dominant event at the whole video level.
Its videos usually are of 10s long, which is longer than the e... | d | f53dd21cc05837b2d0e14410c2c7e5c4 |
Lemma 1 (Lemma 48 in {{cite:b6fe36bc8d87156e54ca524c3c33cf7e85b804de}})
Let {{formula:394993f2-8f98-4732-87fd-da567403d432}} be a matrix that is {{formula:30cd8788-9215-44f3-8502-351b24c8e8b3}} -row-sparse and {{formula:ab84b822-e4fd-4119-a12d-69ebe52154ec}} -column-sparse, and each element of {{formula:cbf35044-482... | r | 554089a9b386ab9aaed924d1dedbeb5f |
For forward Euler type discretization, Assumption REF can be relaxed to {{formula:c75e0fa8-514e-4c77-afd8-61add1e32407}} only. The backword Euler type discretization needs {{formula:34546e39-3014-45b5-b9ba-8797675fc623}} , and other discretization methods need different {{formula:6c58a9a9-852b-411c-9183-1cf377ccdeed}... | m | 8e4ce53290423ba4f7660af5c3697679 |
The investigation of the no-scalar hair theorem and interplay between gravity-scalar systems are not just of theoretical concern, and there are many reasons to examine them. Scalar fields play a central role in cosmology and particle physics {{cite:d65ff374cc65b4e786d27ae0e6086789709cfcf4}}. Scalar fields appear natura... | i | 1df5048a8d9a7f3b0ac8ae2ba5f1adac |
We would like to thank Mona Dentler, Colin Hill, Evan McDonough, and Mikhail Ivanov for useful comments and suggestions. RH is a CIFAR Azrieli Global Scholar, Gravity & the Extreme Universe Program, 2019, and a 2020 Alfred. P. Sloan Research Fellow. RH is supported by Natural Sciences and Engineering Research Council o... | d | 6818197cfd7feabbf0c86b41a04b6282 |
Augmentations. Using adversarial loss with very limited data might cause mode collapse. Thus, we use augmentations in the form of random affine transformations during training. However, when preserving the background is necessary as in Fig. REF (Bottom), these augmentations might leak to the generated frames resulti... | m | dee6ef22ad37839a7096ca7b864d65de |
Lite-HRNet is the state-of-the-art in terms of complexity and accuracy trade-off on COCO and MPII human pose estimation and easily generalized to semantic segmentation task.
Related Work
Efficient blocks for classification.
Separable convolutions
and group convolutions
have been increasingly popular
in lightweight netw... | i | 8540673ab829b02e195d207c6f872f0f |
In design of our method, we are partly inspired by Monte Carlo tree search {{cite:595d173646bf1709e466c9b9b1f4a14f349e92db}} (MCTS), often used for exploring large trees, mainly for applications in combinatorial games. To the best of our knowledge, most research, where a tree search method is combined with ML, focuses ... | i | 56d47b038925a935ff64f7e443e52361 |
In the end one needs to comment on possible importance of the strong electronic correlations in Na{{formula:b07b1de4-80e4-430c-9d77-94833d4c55f7}} RuO{{formula:a631dbb4-be37-460c-9e06-f0e95024de4e}} . We have seen that the GGA overestimates equilibrium volume of the uniform phase on {{formula:b1295e70-5672-4d2e-a8c5-7f... | r | e8fabe3be158315871c2bcf9903b04db |
Researchers have suggested many additive defense methods in response to such additive attacks. The current defenses against such attacks are training modified data focusing on gradient pathways{{cite:94263fdc488767cab547c8d7f7eacf6aff96593b}}, performing different filtering, or removing adversarial perturbation from th... | i | 3008cc2a87d9e6fa05193864bc2da807 |
We chose to emphasize the authoring objective of storiability because of our focus on AI-augmented story writing. Storiability is not a one-size-fits-all metric for this research. The quality of a story can be judged on multiple dimensions that are often not consistently defined across different studies, as discussed i... | d | 8e99912968bf0f78467556a2429d30c4 |
MIME, like ATISS, needs a pre-defined floor plan room layout as input. The resolution of the 2D floor plan is coarse; i.e., 1 pixel stands for around 10 centimeters, which is extracted as a 512 dimension feature by ResNet-18.
Introducing a finer floor plan representation, such as dividing one floor plan into multiple p... | d | 210465cfaf44ee411d3cdccb9b48ec73 |
In particular, we selected 15 of 66 regions in table A.2 of
{{cite:f436c81c6a2bd9cb9fbffa98b5efd08dabc2f14a}}, based purely on the SDSS DR14 spectra,
as satisfying our criteria.
We added 71 data points for 43 regions from the literature and this work,
which include the great majority of published
direct O/H estimates w... | m | 58f5250934fe50eefb3b9269b39f9f90 |
A sim-to-real strategy to utilize intermediate encoded features of a fully trained end-to-end DRL policy for perceiving regions that could cause instabilities for the robot during navigation in real world uneven outdoor environments.
IMU and elevation gradient based rewards to identify critical elevations and rough s... | i | 03638e5a0e5a7eeb90eded734c23d0f5 |
Generally speaking, loss functions can be divided into two categories: convex loss functions and nonconvex loss functions. Convex loss functions including Hinge loss, square loss are the most commonly used. If {{formula:1a86bab6-f699-4e21-9a3e-6d3a58cf312c}} is a convex loss function, then the classical representer th... | m | d10e6f62e23355011221fe8ddc14ca6d |
The one-dimensional (1D) continuous fermionic gas with repulsive delta-function interaction,
which in this paper we call 1D repulsive fermion model, was
one of the first quantum problems solved by the Bethe ansatz (BA) {{cite:f6ec6c917f7366075744fc5f7c36aed0edd7652c}}.
This was achieved by Yang {{cite:96aab1e8195891985... | i | b5cb65fa191439fd33d751bd0bcbd01e |
Figures 5(a) and 5(b) show the band structure and spin density of the ferromagnetic Zr{{formula:1fca8ff9-c39b-4a0c-bbef-22ce3d0643f7}} S(001) surface, respectively, calculated without including SOC. We find that the {{formula:2811013e-8d18-4165-b42f-d0fbae29ad6f}} and {{formula:b40346f1-d11d-4251-9ba7-ba89e36337b8}} ... | r | 0ef3229cf4a243c2552aeb6b9479ddcc |
for all {{formula:2a55ecb6-5ca8-4b0a-b894-e5d9f31ce67b}} , i.e., the Arrow-Pratt measure of risk aversion is bounded below by {{formula:c6269ca1-7829-4992-9a86-a75999fe65d3}} .
The Arrow-Pratt measure of risk aversion {{cite:90f62a293f8b6e3897a3b04e3bb27f7f00dec11c}} has many well-known desired theoretical properties a... | r | 2277dac9c865f861ea9930b1fb7efef0 |
Datasets. We evaluated our method in the following two standard benchmarks for UDA.
Office-Home {{cite:3c4f706abd8159653e61908d5c5c6c9099fab33f}} consists of images of everyday objects organized into four domains: Artistic (Ar), Clipart (Cl), Product (Pr), and Real-world (Rw).
It contains 15,500 images of 65 classes.
V... | r | f45e5706b5bb85b12444a8cc366e53b3 |
In the present paper we consider the modern experimental techniques
of potential modulation for the two-dimensional electron gas
and show that they permit to obtain
the quasiperiodic potentials on the plane with different numbers
of quasiperiods. Then we use the topological results concerning
the geometry of the level ... | i | 593b95aedd4f3a5745f5853916897b86 |
The software implementation of the networks was done in Tensorflow {{cite:2a2320a961e10157d9e3be1db1e0dc717cb25f07}}.
We used the network models and the test set provided in {{cite:5665aa4cc4b29afafc22918d76d6e11b4e4809e6}}, {{cite:5feaadfd83fcbff55b4a074b30c8fcacd41a1c1b}}, {{cite:3b5b3db504fe534c389bbabb4559d2745b93e... | m | 9a13a04ab6034ca2121d7f2be6ec4ed4 |
Most existing studies on representation learning in BMDPs {{cite:fbeeca39d0c419f58019d930d1ac811354651b94}}, {{cite:87e2b867d127b9238774b49a3c315d39e232158c}}, {{cite:b115a8ffc8a833d1758aac224a56799bf5a82c66}}, {{cite:93f399c53d5ee12bd15a7be0b88125b5b7114406}}, {{cite:a1cd1e040736daa9e3eefe2462c964632d77b4e1}}, {{cite:... | i | 8855939aed8e037a3ce8aa7bd52dc5e2 |
In this section, we analyze performance of Mask R-CNN on filament detection, in juxtaposition with Bernasconi's segmentations reported to HEK, using the metrics and methodologies discussed in Sec. As the reader is looking at the results in this section, it is important to bear in mind a few key points in our experiment... | r | 1e58c12f1ad62f04426f2778cb2ffc51 |
To compute the continual learning metrics {{cite:9eb5d1788471034f52f7b585f3cb7781ada306d7}}, each predicted trajectory needs to be marked as accurate or inaccurate based on its difference from the ground truth.
Since there is no preexisting procedure for this, we follow the following steps. We set a threshold on the DT... | r | d94ef98c6a4004aca90d6101f40f8856 |
Deep learning methods have been shown to be applicable to robot manipulation {{cite:8bfea282ee9434cdf16e4b00ac7ec86860381347}}, {{cite:c335866fe5073e249b9ad1078e85faccb0a592e1}}. Grasping is a common topic, as it is often an essential step in many robotic tasks. Learning-based methods can generalize to grasp objects wi... | m | 8424098ac3b762181edd88dfefaf594c |
ReconFormer. As shown in Fig. REF (a), ReconFormer consists of three recurrent units and a refine module (RM). To maintain high-resolution information, ReconFormer employs globally columnar structure. In particular, recurrent units map the input degraded images to the original dimension. Meanwhile, across each recurre... | m | 9ae521f754519b13487a1817f9e3a2b3 |
Moreover, we highlight some recent state-of-art work in this domain, which relates to our proposed methodology, showing promising results in application areas other than UAV aerial imagery. First, the work in {{cite:643a5759e5beb78d12b764b54173f6c91e8421e9}} incorporates two significant improvements: layered boosting (... | d | 5233bb0cd7fab16753851b8c54705e7a |
In previous Sections we used the Krylov–Fock theory of unstable states to
find late time properties of the survival amplitude and instantaneous energy. Similar estimations of the late time behavior of the survival amplitude can be also found by means another method, e.g. methods of the quantum scattering theory. This m... | d | 76b41442324ff333c0cf3bd65c6a0754 |
In future work, it would be interesting to consider many-body effects
in Maryland-type NHQCs and investigate their
dynamical properties.
The interplay between non-Hermiticity and quantum chaos in the NRMM can also
be studied following the mapping discussed in Appendix .
Under open boundary conditions,
the interaction b... | d | 37542850ea00367d8b0c859cfc6f23b5 |
State-of-the-art secure aggregation protocols essentially rely on two main principles: (1) pairwise random-seed agreement between users in order to generate masks that hide users’ models while having an additive structure that allows their cancellation when added at the server; (2) secret sharing of the random-seeds, i... | i | 49703922071a8e21c4ff9cac0a8eb7af |
One type of meta-learning methods is called gradient-based meta-learning, and they include MAML {{cite:47d8ce168aa1e2698a7bb7a949a303e6c8294329}} and Reptile {{cite:1dbf8e5d0538d038e7a294c442dbd2d4d5cd07d0}}.
These methods learn to reduce the loss of the model whose parameters (e.g., weights of neural networks) are upd... | i | 9e5e6413239b8cfa4de78f2819e0e615 |
Dynamic Magnetic Resonance Imaging (MRI) is a powerful imaging modality to non-invasively capture time evolving phenomena in the human body, such as the beating heart, motion of vocal tract during speaking, or dynamics of contrast uptake in brain. A long standing challenge in MRI is its slow imaging speed which restric... | i | 5101a5a534070e2a8150b179c7a29c6a |
Five representative weak forms from Tab. REF were chosen for
studying elapsed time and memory consumption of the einsum evaluation backends
from Section REF , namely the vector dot product, weighted vector
dot product, weak Laplacian, Navier Stokes convection and linear elasticity
terms. For comparison, their counterp... | r | 72f250f3a01d7fda6f17882d06f923f5 |
Unfortunately, it is not know whether or not the evolution system {{formula:7822269c-c55e-401a-89c1-f08ca93b7714}} leaves {{formula:fe9d96c1-b0be-495c-a9d8-b7f0e316ccdd}} invariant and is strongly continuous on {{formula:76022fae-3541-42db-be8a-be2c150c432f}} ; the only information in this direction stems from (REF )... | r | 7e1e9c599548cfc0e4477726eda1f3b2 |
First, the codes are simulated over the i.i.d. {{formula:5f7616e6-881f-4567-a83c-0101c7bbf2b7}} channel model of {{cite:396a138353a0756743644499075a0de5dd84d45b}}, where {{formula:a2b3e53e-d6c2-47e5-b0e1-39fd124526c8}} and {{formula:5c1e29df-e74e-4788-8325-a413e513ea8c}} errors are modeled as independent events iden... | r | 9734fd3506427a1e4fc7b31fcd0e8429 |
Figure REF shows the individual exchange paths for each term in Eq. REF .
The Kitaev term is an indirect exchange interaction with hopping matrix elements {{formula:c4969446-cdee-41d9-ba37-17aacf97e5d6}} between the {{formula:37453f99-dada-4bb5-ba10-6ccb643de6a0}} , {{formula:60345b48-73c2-4188-aebc-e267122f6d60}} , ... | m | 5b012dd33ca60d5885bb6b053ab82725 |
From the point of the quark model, some of them can be interpreted as mesons made of quark-anti-quark pairs and
baryons constructed from three quarks. However, there is a plethora of states whose structure is puzzling, presenting properties
that can be fitted in the hadronic molecular state picture if the mass is close... | i | c665b00cb39cff43550eaf6a38ecf676 |
Imbalanced CIFAR-10 and CIFAR-100. The original version of CIFAR-10 and CIFAR-100 contains {{formula:54558c22-c841-4d99-b237-ac9e233b6019}} training images and {{formula:cad1067e-bf55-46e0-8c40-6cd06f3ef8ed}} validation images of size {{formula:8b82583f-9729-4046-ad10-ab7dde4a4758}} with 10 and 100 classes, respecti... | r | 0b04328912c1adb9503216817268b532 |
To test the generalization capability of U-S-VAE, we provide its performance on different datasets, such as the NTU RGB+D 60 {{cite:a72e80f988f97ff7b0f0b248665c04fcaa1d47f3}}, which is a large scale dataset commonly used for testing action/gesture models. NTU RGB+D contains 60 action categories collected from 40 subjec... | d | b71dee056f1edafb699922bfcad23b25 |
The DQN model's implementation was done in Tensorflow {{cite:846a7c6afca44b3722948c7692eb2418e0005f1b}} on a dual NVIDIA GeForce 1080Ti GPU. The DQN framework is trained with an RMSProp optimizer {{cite:03c001e3510108d021642115111679d32750d3cc}} with a learning rate of {{formula:fb77ae83-b493-4738-ac2f-5d7ab3997f36}} ... | r | a3c5619091b2fd7a733d27dc76550c78 |
We build a new recognition paradigm to improve the transferability using knowledge from the textual encoder of the well-pretrained vision-language model.
We conduct extensive experiments on popular video and image datasets (i.e., Kinetics-400 {{cite:d70b1e287a11265b5f748d1fb0caf5ac2e0ec065}}, UCF-101 {{cite:38f3e70c3... | i | f9cceb9f3e1c70a6817ed28c43f1720b |
The dust is also destroyed by collisions with the nuclei in the hot plasma.
The thermo-kinetic sputtering of the dust, is dominated by collisions with H and He nuclei. In a gas that is shocked to temperatures between (1–10){{formula:fd63cb27-5dcb-4457-836a-1a3ba56bab5c}} K, the lifetime of silicate dust ({{formula:6a7... | d | 53689364a62cbb69743991e014a7de60 |
In general relativity there are covariant quantum fields defined on a curved manifold {{formula:11800532-577f-46be-ae54-5a2bbfcc6c27}} which transform under isometries according to CRs induced by finite-dimensional representations (reps.) of the universal covering group {{formula:7bb1594f-5e35-45a7-95dc-9f7bf895f785}}... | i | e49e3dd65c58bde9b308bdb56c1e4c13 |
This relation also holds for classical mechanics, the classical limit of the above, given the correspondence between Poisson brackets and commutators, {{cite:25d2e2bd536797ffc1de013620222fb7085d6cd2}}, {{cite:edc4a960501cf923718b4fa9d2999bfa967f3efc}}, {{cite:e8776c41fd0e27592ad6636b492a354751940a61}}, {{cite:dd63c5182... | m | 8e9186d42e289c983a6256a3f40aa4bc |
Although network reports are designed to be flexible across different domains and use cases, the usefulness of network reports still relies on the integrity of the creators.
In the near term, it is unlikely that the full contents of network reports could be automatically created and standardized to prevent all inapprop... | d | e60664aa1b3ebdcbd132e552da9a7cfa |
Despite remark REF , we note that assumption REF is strict and difficult to prove that happens with high probability in arbitrary MDPs, as this depends on the markov chain underlying the decision process as well as the Q-values themselves during learning. Thus, we provide a probabilistic relaxation of this assumption ... | r | 9825f6fd83670f763d353ccff7236f9e |
Web APIs consist of programmable endpoints to interact with software systems. They can be implemented in different ways, including the well known REST {{cite:4c10d7adb57c8fb67ba0e9d0d42521cd3aa71d45}} and SOAP {{cite:8dcfb12193042f244d9c4d8bc94cb1c571bb227d}}, {{cite:e878b32c591a2847a4f590093e0b19409507fc07}} paradigms... | i | e55d1621e61a4eecb4e34c860a48b9c9 |
In a semiclassical treatment, a classical orbit {{formula:b243d998-bf47-4258-a1e5-b9d905418eb8}} satisfying the following Einstein-Brillouin-Keller (EBK) quantization condition {{cite:4def2d0f7d6179211cb07de303b5639257915f4a}}:
{{formula:7e26c3ea-5a33-4b93-8795-5dd9cf1d0318}}
| m | bc37b35718fa0ad5436c6f6633c81807 |
Much research is conducted on CT images, but the 3D information of CT images is under-explored, such as the work by {{cite:bc09a7b23c3d27eada1cba131cf6c2eb6406c695}}, {{cite:fdd862ecaf1e678c2588560ad4eb5ab9fe657671}}, {{cite:3c4402b97d45bae6562046ce0c6a232c0065db24}}. These work mainly propose 2D DL models for COVID-19... | m | 967ccbb5280c8ac4f85e76829603cb8f |
Finally, in fig. REF we have plotted the spatial diffusion coefficient as a function of temperature scaled with critical temperature. Expressing the transport coefficients in the units of thermal wavelength is very convenient; thus, we have multiplied a factor of {{formula:4f270fde-f488-470b-a595-b11de846f346}} , maki... | r | 5d941e6dc9c7c9561c64032f0ae7bba2 |
Our conclusion is that the effective theory breaks down for
any physical process involving outgoing particles with {{formula:89f046ce-0a47-41e2-8415-ddf320bf5743}}
(including Hawking radiation)
when the collapsing matter is around a Planck length from the horizon.
This is reminiscent of the brick-wall model {{cite:5f5... | d | 1202b0a9c9acb3fa999def0534bd2737 |
The second lemma is the Pólya theorem, see Theorem 9.1.4 in {{cite:d6140798325ea250364facbe2b221dfc12949ff2}}.
| r | f864eba58ca89c085e1bdcd8c20fdef3 |
We computed the QR probability for two atomic species of experimental relevance (Rb {{cite:7f589817bcea119da93bea1f6934eaf1d87ec2eb}} and Na {{cite:58d3b494b690221a9fc0fd529882fd723fc84bcd}}, {{cite:3603f170b3169333a9e0f24baf5828acabbff269}}), and for three graphene family materials already synthesized (stanene {{cite:... | m | def5e53f7712b2b136b8c75a660ce309 |
We remark that the above statements for the two and three-dimensional cases have been already proved by Bourgain–Li in {{cite:48c4b3fe4246a5047ee2e7f3d6567ce98cb67f78}} and {{cite:f2e6b3d41ed1adfa155eb06320355f7633cca9c8}}, respectively. We refer the interested readers to these works for an extensive list of literature... | r | 30f065a2c4d28201b6dfd2861f0937f9 |
In addition to the ResNet50-based models discussed in sec:experiments,sec:results, we also present results from two models with transformer architectures {{cite:eb1e0eca0506a299242ce6822a0950d120a2fa0b}}.
MAE uses masked autoencoders {{cite:8f5ae443b905d2b0bb94d4cc4a53e5e1d564f4b4}} and we use its ViT-Large variant.
MO... | r | c67c60c85a154cf2c73c8bd1e8437115 |
Table REF reports the intent classification accuracy for different KD strategies in combination with 4 CL approaches, i.e. a rehearsal approach with 3 different sample selection strategies (random, iCaRL {{cite:bcd37c14273c1c04dc9680e45eff321f59271d0c}}, and “closest_to_mean”, where the samples which are closest to t... | r | 76c257f5999d0f1378e29b2850755bf6 |
Categorical logic unifies languages: virtually any formalism, from a simple heap to the calculus of constructions, can be modelled as a structured category {{cite:3221941769a19a18a043023cfc69c72c6619b288}}. In doing so, we inherit a wealth of tools from category theory. In particular, we can generate expressive type sy... | i | 36bd1dcf1d7516708b808d402303951d |
During this presentation of tappings, a few additional issues came up that still need to be discussed.
Models with memory like
recurrent neural networks or dynamic Bayesian networks need special
consideration with respect to tappings. Such models naturally retain
an internal memory of past input values. Because of thi... | d | 1a0880d9add8e3515d26cca18273cf2f |
ViT: is an architecture based on transformer which is used in the field of Natural Language Processing (NLP) {{cite:524c9445c759c5903db1b54341d2130d6968218a}}. Internally, the transformer learns a relationship between input token pairs, and uses 16x16 patches of images as input tokens {{cite:1f707f04b09c6f577d577128bf1... | m | bbe7a2ba895daccfc49a14bd9f66fd7a |
Cosmic Microwave Background: We consider the CMB temperature, polarization, and lensing reconstruction angular power spectra as measured by 2018 Planck legacy release {{cite:74b6ef59c5105a294f9cef8cf08a1fc78ba9d266}}, {{cite:bb9f68b115c035ef1a36d260ea97c35341a7c1a0}}. We denote them as "Planck," and they include the... | m | d6e32409c16012e748cc3a113a771388 |
To best of our knowledge, we are first to observe that adopting existing approaches for fairness-aware FL is not feasible under data heterogeneity. This is because the client specific fairness losses will become unbounded (Section ).
We argue that by altering the aggregation heuristics may ensure fairness while simul... | i | b0cd41f761bea3552f40487066b0ab41 |
Finally, Figure REF illustartes the class-wise vulnerability of the ICARL {{cite:468e6aa9c8d84e3641d5542f1abfbb8a0164df1c}} against the FGSM, PGD, and CW {{cite:cceff7ffb4d3b29c215d08507950b6a5e69f61c6}}, {{cite:c3fccf0ff9253b92c42d2bf0bfc9f109ecfd1a1a}}, {{cite:3519d381d3816b9d84b2d65e2bb04bb34bae094c}} adversarial a... | r | 0c4ae849d083568c29f8d375d5e6943c |
Moreover, in contrast with conventional multi-modal approaches that assume paired input, our proposed method is more flexible since it can process samples with missing chest X-ray images. There is a rising interest in learning cross-modal interactions between modalities during training time and in reconstructing missin... | d | e7355e8f54ffdbb5b62c9281776c2100 |
Compared with the passive RIS, a noticeable feature of active RIS is that it needs additional power to supply the amplifiers. Therefore, the active RIS requires a larger power budget than the passive RIS given the same number of reflecting elements. Even though the superiority of the active RIS over the passive RIS has... | i | 17930d8f9f3fe990be8a972285447421 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.