text stringlengths 54 548k | label stringclasses 4
values | id_ stringlengths 32 32 |
|---|---|---|
A number of choices in the algorithm are taken to aid computational efficiency.
We allow for intra-limb coordination of multiple joints encapsulating multiple actuated joints within a graph node, which reduces the number of message passing steps compared to related work {{cite:be755a458e07df024074f1484ddde5fd8974d158}}... | d | d2e8ef3902102cf0d224915cf780053e |
For both the HBOS and the iForest implementations the data was preprocessed by a standardisation step, which sets all the features means to 0 and their standard deviation to unity, followed by a principal component rotation, where we retained the full dimensionality of the feature space. The purpose of this rotation is... | m | 89ffb75709450c2e116e89b056841c15 |
In the foliage-gleaning bird case study, we explored the sensitivity of model run time and parameter estimates to the number of neighbors chosen for the NNGP spatial MSOM. We found a fairly linear increase in run time as the number of neighbors increased (Figure REF A), with parameter estimates being relatively consist... | d | bb178b44dca9323a07423d4885c29b25 |
In recent years, although the identification of scalar mesons is difficult experimentally, some experimental efforts have been devoted to measuring {{formula:770cc7ac-d313-4833-970e-5ff37320348e}} decay modes. For instance, the light scalar {{formula:2eeaf5ea-3d26-4a71-90ef-6d350111972a}} was first observed in the {{... | i | 46702e870a9bb1feca22747c534c775c |
For {{formula:c2b87ebd-0d94-45d7-a05b-964052bf7e8b}} , a pre-trained ResNet architecture {{cite:cb0ffec4fbbeeb493bb50c528eb80bfa597843b8}} was used (the classification layer was removed) and the image feature size {{formula:51e89ef1-7570-4d16-947c-bb0e501dcbd7}} is 512. For {{formula:8b9290ae-ca59-407a-8cc6-b7cdec4644... | r | 90540836eb43527c351b1b58af88edac |
In this work, we directly use the playback signal as an additional input to the network, allowing the model to implicitly learn to perform AEC. We propose an encoder-masking-decoder architecture to achieve this in a computationally efficient manner capable of running continuously on edge devices.
We evaluate this techn... | i | 33e0b5175f6f7227623ac881ff4c6f1a |
Finally, remarkable results have been obtained exploiting time-dependent signals. An entirely complementary field of electron quantum optics {{cite:392df3e8525204a37cd945fbe237f8a6692c6b0e}}, {{cite:254f4b36df83ab5818826e3fbff48e5c08f4d426}}, {{cite:eab0aa721023ea7492cef03c30dbefb1ad130f6f}}, {{cite:33b0c7f4c47a996d327... | d | 9b3d1df32ceb05b0b69cc19691f8ae82 |
For example, the framework can be applied to eigenvalue problems related
to physical systems. For instance, the general conjugation formula Eq. REF
has been previously invoked {{cite:9c34acd3ea05e1117a33313c20ae1632f3dfb910}} in the context of particular
parameterized quantum circuits for the electronic structure prob... | d | 072313d20ec8546aeac740c7c95b5019 |
Estimation of residual dual norm is straightforward for affine problems
(cf. {{cite:e58f82591b5bf07f61fa8250c3c8c06af51aa997}}); furthermore, for certain classes of linear and nonlinear PDEs, the successive constraint method (SCM, {{cite:eb727f96601fd8fed9e093c269c5a6e831df74c0}}, {{cite:62e5760cd16b16a734aa9e007e7830... | m | a10e9f79d30e6a388773ea2b13e45524 |
Fig.REF shows the result of linear regression between ImageNet (IN) {{cite:fdf1290f23c64d3952b2b377d9fb96ab2d10c189}} test accuracy of a pre-trained model and its performance in a target task with distribution shift. For self-supervised models, we use the linear probing result as the IN accuracy as reported in their p... | r | d0f494b70b5787b40cd9414ad3c9d88c |
c. Repository meta vector generation:
We map
the metadata in a repository to an {{formula:5da5b2bb-7464-4d81-b51b-e14f4d4ab50a}} -dimensional distributed vector, {{formula:46fdd33f-1f4e-4177-93df-d683f8a5c2ce}} in this step. Following the basic principles of doc2vec {{cite:ce392d0cca61007e86ec60a80a269dfa20ba0317}} a... | m | 49a731734526196399043259cb7f1507 |
In contrast with the same behaviour of the elimination and deletion problems with respect to the inclusion in {{formula:017e1093-7b57-476e-94eb-353b44f07356}} , we would like to point that they behave differently with respect to kernelization (we refer to the books {{cite:fdcb4defe39009e7c51941a1712cee62dc9f2cae}}, {{c... | d | 54205d7c6b5b71d7ea008fb4fd4853a8 |
A strong correlation between {{formula:45f5ab23-c021-48a5-bed8-3ebd5e6f1a23}} and {{formula:aa075cbf-4178-4033-ba19-c3834e6c8cab}} has already been observed in a number of X-ray binaries, for example 4U 1608{{formula:53544afd-e1e6-444a-88ba-2636e3dd289e}} 52 and 4U 0614{{formula:fe563499-c854-4e90-a8f8-f64f25f7d61f}}... | d | 5eca51c37231d6881defbeaa77302d29 |
where {{formula:f05ff7c6-7403-4ff9-8379-42129734c988}} is the learning rate. Here we use the Adam optimizer {{cite:917389d6e291f243b78ab6e4440087bd3fcb0a08}}, a highly successful version of the SGD method.
From the derivation of the DNN formulation, one can see that the proposed method automatically deals with the
ph... | m | fe17b27850a5dd5fcc2c5a9f273ea738 |
The usages of large sets of images has been a common practice for computer vision research. The usage of art datasets has been less common, but paintings have nevertheless been used in various ways. Models that learn to convert photographs into
painting-like or sketch-like images have been studied extensively for their... | d | 1bfb3496ac9cdfd215944fef42ebf1fe |
In this work we adapt three GAN generator architectures to the 3D lung CT patch modelling problem: the widely investigated DCGAN {{cite:ac98c5aca09ee1cae70ec0a11a7084c058eea331}} representing a baseline approach, and styleGAN {{cite:4590b8afa7b07e4d1676886959dc657f9ef33743}} and bigGAN {{cite:a3b165307a9ced66dccccf490a... | m | e1a6e0ad42cfe79a8059273d12d59cf0 |
However, deterministic neural networks assume that the mapping learned by the network is accurate, which is not always the case, and produce only the learned output for a given input. On the other hand, uncertainty quantification (UQ) not only describes predictive distributions over outputs for given inputs, but also i... | i | 3724af045a5593ab4f625068e6b9f831 |
The available data described in Sec. is split in a 7:2:1 ratio into training:testing:validation sets.
Using the training and testing data the networks were trained with the Adam stochastic optimizer {{cite:64227464026d7454bf4a08be849d729b2385fbe3}} with learning rate 0.001 until there were 100 epochs of non-improvemen... | r | 6dc27bd63bd999b7eb19527bcb47035c |
Lastly, a disadvantage of applying resubstitution with upper bound correction to analyse DL models is that the final classifier should be linear, as the computation of the upper bound becomes more complex in other circumstances. The large number of connections in the net and aspects to be considered such as activation ... | d | 81e26763615fe8813fc4df884d984617 |
We make a direct comparison to the square lattice CNN model described in Choo et al. {{cite:01205bf2ae5289151fa69e456a3c875740c15c69}} who use a translationally equivariant CNN symmetry-averaged over {{formula:9771a2ee-a45b-4688-aecd-a65127758327}} , while we use a model that is equivariant over the full space group {{... | r | 89fc17878b667f5e2a40480f15334666 |
By definition, it is easy to check that (REF ) is L.S.C. and () is continuous. Moreover, (REF ) and () is coercive (see {{cite:e76b2b0c36af55844a6eba10d268dcb839faa466}}), that is,
{{formula:088f9e3e-9f45-4fac-b094-1bcd760682af}}
| m | e3c1f9fab5b65702bcacef9f43678553 |
Spoken speech refers to the natural speech that we use in the everyday life {{cite:5ee102ad6c48afcd5b775b76f3bd68f0cabc7dcf}}. It is known that imagined speech brain signals resemble the features of spoken speech brain signals in some portion, therefore, holds potential to utilize spoken speech data to improve or enhan... | i | c530eaf70678df097b20ef8a49b28861 |
{{cite:2de6bb383923677b70e23a6b523666abfb6eacdc}}, {{cite:4cc86e01b4ce1f7a508e100b22e659d9b49d30df}} formalize the divergence between two domains as the {{formula:d685bb92-110e-4f6b-8519-32a884e97d0a}} -Divergence, which they approximate as the difficulty for a discriminator to differentiate between the two.The approxi... | m | d1e12d3b33cab8b418371c6a9efcdd27 |
Evolutionary simulations: In order to simulate the evolutionary dynamics of this system we consider a population evolving under a “copying process” {{cite:1676c132a6ebee86b167f705a23704ec1205fe0c}} in which individuals are able to observe the utility of other individuals and compare it to their own. The dynamics of the... | m | b47206f3f9e528e958f4fcae09a58f87 |
We include four existing methods for comparison in this work, DrBoost {{cite:ff1bc6f62e2ff6a544d31769b0f24045efe9d3a2}}, DPR {{cite:42d4a21722e3295a083657fc6939d903cdfe9636}}, SPAR {{cite:870f5ca895ce6f660606e16a76df6714977e1a42}} and a heavy hybrid model BM25 + DPR {{cite:42d4a21722e3295a083657fc6939d903cdfe9636}}.
SP... | m | 6fde0d9a328de7a9230239bf73ee3760 |
There exist several variants of edge length optimization problems in linear arrangements {{cite:bd2275a1e1e931e59dcea3d898eb35b893137103}}; two of them are the planar and the projective variants. In the planar variant (minLA/MaxLA under the planarity constraint), the placement of the vertices of a free tree is constrai... | i | b0bdbd7bb90b446633d8cd5e27036d27 |
Due to its stability, an entanglement source based on the Sagnac configuration has been installed on the first quantum-communication satellite (Micius) {{cite:bba81b13e5bf8f35ac72e19358a8143b80da0a66}} and used to demonstrate satellite-to-ground quantum key distribution {{cite:3b660c4592036074c67363585f30bd2e906cd201}}... | i | d3c9e80b860cca273f186d0117c233c2 |
On the downside,
direct ST suffers from the lack of large ST training corpora.
This problem has been addressed by researchers through transfer learning from the high-resource sub-tasks {{cite:811c09737c6724cb83cebdec171a2642e83adda1}}, {{cite:109737002c6d4929d75d79eee4df04a14f5e049c}}, {{cite:e31b52c2eed853de6274e89eb9... | i | c276c63dea33c3e4b67621a3d69564b3 |
blueLaplace’s (1799) calculations and conclusions have been confirmed, prominently by {{cite:b807bbd0bc8ba1e1e8cff0457342d57e3c4fd02e}}. Based on these equations, a link between the rotations and the torques exerted by the planets of our solar system is expected. Indeed, we have shown elsewhere the influence of Jovian ... | d | b89455b20fd8f29e3b29cbfcf263f639 |
The above formula written in a schematic way allows to easily explain our idea and differences with other methods. Indeed we have written the above expression with {{formula:c01f6041-2703-4241-8b01-80207b347391}} as {{formula:43d02b73-ac12-4f6b-a11d-53ea20336ab8}} hadrons are ultra relativistic. In our actual analysi... | m | bed0af3899daae50a5dcfb12b2e76390 |
The transverse momentum dependence of the strange baryon to meson /ratio provides a unique way to study the properties of the hot and dense, color-deconfined QCD matter called quark-gluon plasma (QGP) created at the Relativistic Heavy Ion collider (RHIC) and the Large Hadron Collider (LHC). It is observed that a pronou... | i | 4dddca19fe84e5b4ddbb3566e5fd030c |
A term of this form remains because the gravitational Lagrangian, built from the Ricci scalar, contains second-order derivatives of the field variables.
The established procedure, given by {{cite:b0da939cebdf09580ac06afc44f43e892a54f5e6}}, is to just extend the EH action with the negative of this term.
Thus, this final... | d | a7e9a09cf902983e5c6d228d270aa311 |
Results and Analysis. We report results using the same evaluation metrics as in {{cite:11066c6bb9090ef60c42551622151c8f1852e6f5}}; Table REF and Table REF shows evaluations at the segment and event levels, respectively. Audio, Visual and AV refers separately to audio, visual, and audio-visual events. As the name sugg... | r | b93af1eb31965558ea166c8413fe9967 |
MOT17 Table REF shows quantitative results of PatchTrack along with other recent MOT systems on MOT17 {{cite:b61da861df65d5c82470b40e509bd17167e026fc}} test set in private protocol. Compared to Non-Transformer-based methods, PatchTrack reports best numbers in MT and ML, and shows superior ability in trajectory predict... | r | b09c4ea1a592d400472d785e7929c048 |
A classical approach to perform model discovery is by sparse regression and consists in finding {{formula:0c6c330e-ce82-4992-b426-df4d0342ae7b}} such that, {{formula:135f24ba-19be-49da-ab0e-5d0c59b8a931}} , where {{formula:32feb897-f5a7-4dc5-b8e0-439f4284651d}} is the time derivative of the field {{formula:b95f5a6b-7... | i | 9aa094a4b1782c949d589fa6831331b3 |
To investigate the stability of our system, we show the boxplot of the RMSE values of ATE over 5 runs for all the 5 sequences in Figure REF . We can observe that, on V101 and V102, our system not only achieves lower the RMSE ATE than ORB-SLAM3, but is also more stable with smaller variance. On V103 and V201, our system... | r | b6d5403892c136424bd30eee9f9d29a6 |
[RQ3] Performance of PerDoor against state-of-the-art Defenses:
We evaluate the effectiveness of PerDoor against two existing state-of-the-art defenses, Krum and FoolsGold. Figure REF shows {{formula:017f42b8-5b13-416d-821d-212eb93a0805}} for 5000 successive rounds considering both these defenses and unprotected FedA... | r | 938fb02f0075cc5135082dc774725b06 |
For likelihood problems, it is common to use Bayesian inference and deploy the MCMC toolkit. Unlike frequentist estimation, Bayesian analyses rely on sampling from a posterior distribution rather than optimization. Well known samplers include Gibbs and Metropolis-Hastings. Because they can be slow to converge, gradient... | m | f080c6653f1974afbccee3f92fc9b59f |
In the dispersive regime of cQED {{cite:443a9d66fbf7db7a9329e57d896e94fc887e9a67}}, after applying the rotating wave approximation, the bare system Hamiltonian in the driving frame (at frequency {{formula:1e34bdef-3fb7-4f5a-96ec-012db634e155}} ) reads
{{formula:0290df87-34ff-438d-b0d6-e52a9de23f54}}
| m | b99d4edde31080fd8a8fc9aace4033f8 |
First, let {{formula:3dd7e315-3445-4e70-b608-1b381fff85ff}} be a simple group of Lie type, then using {{cite:db1cc7f3c0d215c094d8207433f5cdfea3ea4fa1}} the Steinberg character of {{formula:d00aa4df-1036-443a-9776-cc778d4ae532}} is not a {{formula:b36480a8-8515-4b69-a366-f66b396f7f29}} character and it is extendable ... | r | f12d2147862c356db16f42af69371750 |
In this paper we have shown that HTLs arise from classical limits of off-shell currents. The classical nature of hard-thermal loop amplitudes was made manifest by relating the momenta of the
soft particles to wavenumbers. The classical limit is then obtained following the KMOC algorithm. In this way, the
high temperatu... | d | 6cb56d4ee1a6ae38aaf496a105ef0bc0 |
In order to build language-invariant models, it is critical to consider the two perspectives: (i) avoiding catastrophic forgetting and (ii) learning language-invariant features.
Catastrophic forgetting {{cite:0f88d165fd0f9ff69e6c5bc8672589f274cd0992}} is the phenomenon that a model forgets knowledge of previously train... | m | f06bd37af802118cdca35ae02d258c25 |
Principal Components Regression (PCR):
Principal components are the linear combinations of predictor variables
such that the transformation makes the new variables uncorrelated. In
addition, the variation of the original dataset captured by the new
variables is sorted in descending order. In other words, each successiv... | m | 9b68ef926254d56281557d55b6bdef52 |
tocsectionReferences
Appendix
Asymptotic Variance
To state the asymptotic properties of {{formula:d8403b54-0f21-49cd-b8b1-3f413bc0ea3c}} , let
{{formula:b27132ea-39cb-4651-954b-ebdfedf1fe88}} be the individual's contribution to the estimating equations for {{formula:37eff4f5-66cb-482c-8827-658ec6bd84f3}} ,
{{formula... | d | 040da478a1bffc60ed7e36b8c43e375e |
The RWA model reformulates the attention mechanism into a stand-alone model that can be optimized using gradient descent based methods. Given that the attention mechanism has been shown to work well on a wide range of problems, the robust performance of the RWA model on the five classification tasks in this study is no... | d | fae3014be641210756f7dbef9c57a994 |
In this section, we breakdown the quantitative analysis of Tab. 1 in the main paper into a per-scene analysis. Tab. REF shows the per-scene quantitative evaluation of our method in comparison with iMAP{{formula:c7ba57c0-f9b7-4759-aa94-c7a7de4d230b}} {{cite:d8c7f5d01724b76ef8a9f940f847fc022019042b}} and NICE-SLAM {{ci... | r | 9519b39121f9dc5b7bb78967ad435a08 |
FEM eliminates the need to calculate the gradients from the output neuron and provides a faster and simpler method to get an importance score of the input pixels based only on the features that have been extracted by the network. It does not examine the classification part of the network but uses only the feature extra... | m | 64094db3126d40eccc4e8920fdd1b9f7 |
To compute the probability of this event it is convenient to rely on the {{formula:fca42275-7d1c-4d9c-aae2-8b9884cf6d55}} -dimensional generalized spherical transformation of {{formula:93536408-a432-4fd5-b469-743e9bf297f0}} {{cite:f6c4e76dfdd602d3092b45254a016e0979678e2a}} given by
{{formula:84e7e6c4-5b42-48ef-9560-7... | r | 7e8c1b031b6acdd459e1651ddfa65762 |
After freeze out, the only mechanism by which polarization of a DM medium can be achieved is via irreversible processes like those discussed above. But this can only happen if the spin-flip rate aligning the anapole moment with the background current is much greater than the universe's expansion rate. When DM decouples... | d | a6ee01823ef46bc518ac0f5b85808d2b |
Datasets. Currently, we perform experiments on the Something-Something {{cite:fd3395f6ccf956c65fe8d6362d455bdd6d795b19}} (V2) and the Something-Else {{cite:168f047c3d011db51c08138441279eb55e3b71c8}} (compositional setup) datasets. Something-Something is an egocentric video dataset of people performing actions with thei... | d | 1dea831c29e766c9b974a905fc1d5418 |
The presence of a permanent EDM in an elementary particle implies Charge-Parity
(CP) symmetry violation. Even though the phase of the CKM matrix of the Standard
Model of particle physics (SM) provides a large CP violating phase it results in
tiny electric dipole moments of elementary particles, too small to measure any... | i | 4649253fa238cf88869be05309151882 |
We assess the performance of HLR and HLR++ on these four datasets, for the top-{{formula:f42c0ad5-b80b-4caa-b493-6a38a122eb8a}} recommendation task introduced in Section REF , with {{formula:3f8d3a51-ab15-4352-8cea-2d0602c06659}} . We closely follow the evaluation protocol proposed by Sun et al. {{cite:4c7f257d99b1c5c... | m | 0891a4b6c93a5e184a41a92becdcfdfc |
The success of the conventional theory of superconductivity {{cite:0099a3c2117cd27113249f4716016c1e7c6e9c8c}}, {{cite:07d375dcd35661448375d486acfe8ad8d4000145}} in the description of numerous phenomena observed in superconductors prompts us to consider the validity of the almost universal belief in the law of entropy i... | i | 313e382db445963594c707f2961c4931 |
Autonomous mobile robots have recently started walking around us in shops, exhibitions, controlled closed areas around universities and innovative companies. However, human motion is unpredictable by nature, a mind state determining similarly to decision-making and inner motivation processes.
Still, recent data-driven ... | i | 1df77ab8fd530f2fb26fdca9d0b9de54 |
The delta method {{cite:441340b9e59d4adfa8675c63e2dd4c5d2b6adc2d}} is a classic approach that is widely used
with small models with an analytic Fisher information matrix
(, linear regression)
and, more recently, auto-differentiation unlocks
the delta method for a larger class of models {{cite:d68e816e17066b1b2743bb23f4... | m | 69d2bdd1f9af85f213e60498dbca031b |
There is always a trade-off between privacy protection and other quality of models, such as model effectiveness or efficiency. It is well-known that cryptographic-based approaches require high computational overhead, and perturbation-based approaches could damage the model's accuracy.
Recently {{cite:2ae71a8427918aac13... | d | 7ab55f5bd2878df874ac8a2f0f24c55e |
The original BERT paper {{cite:421e35fb99a1cfacfa2d68f8aca2a3ff76d26f58}} reports a perplexity of 3.23 for the 24 layer model with 1024 token input. The BERT Base model, trained on the same corpora has a perplexity of at least {{formula:1b2c4d5e-b387-4d1c-98f2-daf2379efb50}} both for English and Russian language. This... | r | 79aaaf8022a2160342e48e124926f4b4 |
The two findings directly lead to the proposed change in computational procedure as shown in Fig. REF , which reduces the computational complexity and accelerates the inference of the GCNs.
Here, the proposed techniques are applied to four representative GCNs {{cite:4b6093a02872ebbc0be126142680f0fdcf3eb436}}, {{cite:4f... | i | 7eb388b2cc650ff947ec0242de05957d |
This is equivalent to applying the nullspace
method {{cite:2e87c1a3419b4797792f7e71617cedd760b6e9ba}} to the saddle-point system sadsys.
| m | 0605869d0f584b3bc2c0d1d41e061e19 |
In this paper, we attempt to explore a knowledge distillation framework for learning to segment multiple organs combining a set of single-organ datasets.
In particular, we employ teacher-student models {{cite:7ac20dfb5f01a9ec1ec73e63ddd9129edcc3fc1a}}, widely used for knowledge distillation for image classification {{c... | i | 6059954c5142798843f6c8760979f473 |
Remark 2 Note that all the four schemes considered do not directly estimate the cascaded BS-IRS-user channels for all users, but leverage the previously estimated BS-IRS-anchor/anchor-IRS-anchor/BS-IRS-BS channels or reference user's cascaded channel, which thus makes their NMSE performance affected by the accuracy of ... | r | 0200dcd6aa5b150b69b4c26860dc03ce |
VGG-f.
Since VGG-f {{cite:8e96cd364ace78aa6987f659bb2023ed4c6f3728}} is pre-trained on a distantly-related task, object class recognition, we do not consider it as a viable model to be included in our combination. However, the fine-tuned VGG-f model reaches respectable accuracy rates (see Table REF ), even surpassing t... | r | 1ff6acd94c39e47046b6b02f88491d12 |
The whole flowchart of the neural networks based synthetic speech detection models is illustrated in Fig. REF .
Firstly, acoustic features are extracted from the speech signal. Then, several different designed convolution blocks are stacked to extract contextual representations of the input acoustic feature. Finally, t... | m | 7419ff99be83400d2a9e56c521f164d4 |
Once equations of motion were found, we asked whether these equations match the ones already known in the literature. For TNC we showed that the equations in the present work match the ones obtained from world-sheet beta functions {{cite:705e775e9676685a38f93c7c2096943157c8863a}} when {{formula:58fcdb61-126c-4f88-8469-... | d | 7ac8b82fedb0f2570061d764ec32c5a6 |
Synthesis and crystal structure.
Polycrystalline sample of NdTa{{formula:a3bf8965-8f77-4d3f-b2f2-14d6771cbf77}} O{{formula:9022a939-d023-4cd9-ae81-bdc186346360}} was prepared by conventional solid state synthesis method from high purity Nd{{formula:a84605ac-5e6b-4864-b301-0cb007ef78ad}} O{{formula:1d236f84-18ab-41c7-b... | m | 476616723c78eb537026d40cf6b4687e |
CNNs have served as the defacto architecture for medical image segmentation for the past decade including UNet {{cite:9d01c24079d035fc5162170c0fd23a01a4095897}} which follows an encoder-decoder based architecture utilizing skip-connections to retain multi-scale features. Since then, extensive research has been done to ... | i | 7f3cd9b25ca43acf81bb9852780e0ea4 |
DistgSSR {{cite:727fa83b3cf80097c0e725c3838ac02a03bb0224}} and LFT {{cite:f1a0b52c2520f130e9b58a20fa587e135ab0e8d5}}: two top-performing LF image SR methods developed on the bicubic downsampling degradation;
SRMD {{cite:ade05958ec695a6cb2b11e55a7691ae05957c782}}: a popular non-blind single image SR method developed o... | m | 3188cf4854792427d8788eb25b54879b |
Pulsars are rotating neutron stars that emit broadband radiation received as pulsed signals
by the observers. The pulsar radiation reaches the observer after propagating through the
ionised interstellar medium (IISM), which disperses the pulsed signal, thereby delaying the
times of arrival (ToAs) of pulses as a functio... | i | ea8499941e38637642b34e8c279fe8cb |
Following {{cite:ee48ac3ac00ee48491afd81c42a84f2ce21148eb}}, we applied the procedure proposed in {{cite:de09ce5133f2cb1362cc2efda9e3dd20615cae55}} to calculate the tracer sidereal rotation rate
{{formula:afda7827-0c35-4c5d-8d9f-7c9180050a1c}}
| m | 11d7c42907c61329d4618a65d9e3bcae |
Ensemble methods belong to a family of architectures with a long pedigree in artificial intelligence that begins with Selfridge’s pandemonium architecture {{cite:37d22c7a03185e779a7edade358bb492fcd927f7}} and includes Minsky’s “society of mind’’ {{cite:90c27c420ace2b52a5d97ecb2fe16d2b7a682eb7}}, the blackboard systems ... | d | ca791e008b08e51fd15401c6d9493246 |
To interpret the performance differences for depression detection between our DMSN architecture and DMSN-A, DMSN-B, DMSN-C models as well as P3D, we present the class activation maps (CAMs) employing the Grad-CAM method {{cite:bb9dcf74bdb09fddb6530c8e7b16543449caac8a}}. In the visualizations of Fig. REF , lighter color... | r | ed7616ad67525e85a88690ccf1f90a47 |
The gas expulsion process can also significantly affect the dynamics of the star cluster during the gas embedded phase {{cite:83f3999c19d0059e5a0ed545c3dd0f4da9b8fa0c}}, {{cite:34e3b37866059218acfdce2e87b9abb1bc294a15}}, {{cite:9537536f0b467397b32f877ed9954dece1c603c8}} and the formation of tidal streams {{cite:68fcace... | d | 6c673d090cae5d1c19edea42640db40d |
Here we discuss several exciting future research avenues that can address current limitations of our method. While the disparity estimation network outputs dense disparity maps for each view, we do not explicitly utilize the estimated disparities for 3D object detection. We rather use the disparity estimation network a... | d | 651a47d17577af7306c46eb15a49112f |
For the {{formula:de980749-e310-4c63-adee-4068349dc75c}} matrix multiplication in neural models,
we refer to {{formula:de0bae7f-8ac1-410b-bf77-3efa20c8202f}} as weights, and {{formula:fcb4e550-b675-42ea-814a-b325453e1244}} as features.
Weight-based methods {{cite:af3c3f19617540572227012ebd4dbac3443ef330}}, {{cite:ea... | d | 7e8a4f8db8e52cc8bfb843ace2b06941 |
In summary, by leveraging insights from neuroscience, we designed an original brain-inspired deep learning architecture and thus add to a growing body of literature exploring the cross-pollination of neuroscience and AI. On the one hand, the current study demonstrates that we can effectively use neuroscience principles... | d | 2cc12cfab70e441b5e999a3602224745 |
To extract visual features, GoogLeNet {{cite:fcfdbe0bc2140f7d6b5e26215cf84196a91e2914}} or
Inception-V3 {{cite:9202b93b16f7bf4d9e6e23624799f54219aa1de2}}
were applied
as base models.
GoogLeNet {{cite:fcfdbe0bc2140f7d6b5e26215cf84196a91e2914}} is a 22 layer deep
CNN and was the winner of ILSVRC 2014 with
a top 5 error r... | m | 8380104c8c23119cc260022abe060358 |
and shown in Table REF . It can be seen that the obtained soft photon's energy for each FSRQ is about a few keV. For FSRQs, the number density of the soft photons at the keV band from the dissipation region inside is very low and cannot absorb {{formula:b09f9e04-54e9-411a-8bc7-0a6d9ba93da1}} -ray. Therefore, if {{formu... | d | 58e17df75bdf27c8fc517ff9038674ce |
In general, it would be interesting to see what is a maximal local closed sub-sector of the holographic dual of Chern–Simons Matter Theories. We expect that Chiral Theory covers all of it. In this sense, the relation between our results and particular vertices of {{cite:9f5d42fab7978d19641fab83a0ad834b8bba55cb}}, {{cit... | d | 1f47deb6747ebc690358177cfe5d6415 |
For estimating the variance of parameter estimates in the outcome model, we compared a resampling approach and a novel analytic approach for a logistic regression model that accounts for uncertainty arising from the propensity weight estimation. In empirical studies, we found the proposed analytic estimates performed b... | d | 26e986bf269059e61734de0c756d91aa |
where {{formula:86768945-5c76-47b7-bab3-d9bcec4cf2b7}} stands for the t-product {{cite:50777014646301d8b7c6bd2dfe992fa6257e043f}}, {{formula:23282805-33a2-4469-b561-435a25954890}} and {{formula:bd597eda-2940-42a0-94fe-166694a5b09c}} are some sampled lateral and horizontal slices of the original tensor {{formula:4558... | m | 2493380588c06daae5bbb8b89e4e2a17 |
However, the basic model for MPMAB in most prior works assumes that players have full access to all {{formula:de5cb91b-e5e9-41bf-bbbe-f01933719221}} arms in each time. This neglects several important factors of systems for many real-world applications, where each player can only access a subset of arms that dynamicall... | i | 7fe10b0bd65f7b10060d54a5da51bbc1 |
We consider only trees, but similar results should hold for standard generalizations of the model with more edges (e.g., {{formula:3785f0cd-5000-4459-b518-4410aa9e40a2}} edges are drawn at each step, {{formula:155b84a6-b737-415c-8af4-a6173dc57b58}} could be random). Such generalizations are of interest because their ... | d | a34a2a55d7a5720131e7f36423a4192d |
In previous work TlNi{{formula:c477e7c2-0867-45b0-a9b1-e4007fee6839}} Se{{formula:ce67ffb5-cbbf-4ea9-a845-baf1d3a9ffdb}} showed some evidence of potentially being a d-wave superconductor {{cite:8ad11be6a46739c7796aba9963c05234533feae9}}. Generally speaking d-wave superconductivity can be identified in SANS studies by ... | d | 5a881671053d7330a77835432aa81507 |
Farhi et al. first proposed QAOA {{cite:56d243582ee60e75b5c9bbf55589010765d3135b}}, and studied it in the context of finding a maximum cut in a graph, known as the Max-Cut problem. For 3-regular graphs, they showed that a {{formula:7ba6cb4e-d0b9-46c8-9109-c5848c92cd33}} QAOA achieves an approximation ratio better than... | i | 88ff5a31af3ff40dbdec7a350b017f57 |
Image-level adaptation, such as {{cite:bbad1d1083103cb3d42c916dcb2f2c65e717a5bc}}, {{cite:e4022e9cc120c3ec92147e7caf88c51d3941a3ad}}, uses a generative adversarial network (GAN) {{cite:7f44bee48fbe399cd2d2d032ceb30a173100846a}} to transfer the image styles of the source domain to a target domain. Feature-level method l... | i | 464ce36aff490450394c9fc150d4d9cd |
The problem that Byzantine-tolerant training algorithms cannot solve is the backdoor problem {{cite:862920be737e7b97c86f2e87fe379f15f5edd351}}.
The backdoor attack is a hybrid of training-stage attack and inference-stage attack, which is very different from pure training-stage attacks such as the convergence-preventing... | i | 17ca0729dd40768333a066a2b5af8634 |
However, the partial decay width of the {{formula:7219bff5-6952-48cb-8c9c-1785f26314b2}} is much smaller than that of the {{formula:bc99b30b-8737-45ac-aa3c-1e5723e65ee1}} three-body decay.
Detailed numerical results are listed in Tab. REF . We find that the {{formula:f38d1e78-ca54-4212-a70f-f8c364f013bf}} three-body... | r | eef1cbc1b84ae76799b45937327b85c5 |
Local contrastive
In dense predictions tasks, we desire a fine-grained pixel wise prediction rather than a global one.
As such, we further investigate the difference between global contrastive MoCo v2 {{cite:6ffb9e54a6782c912e8a10af2d965de684acf726}}, and its variant DenseCL {{cite:e0e5b6e9030ffed0bed76e1affd75eb9df08... | m | 6cec8b0ef30980595738d0d12f503dc9 |
Our virtual patient is modeled through two ordinary differential equations presented by {{cite:89ac4f2602aa5e667438523fdb2f5ba5f46f4f9c}}. This system is trivially flat with obvious flat outputs. The design of suitable reference trajectories with the corresponding open-loop controls becomes straightforward. A major sou... | i | 472ec010a6ca8f02bea3a3379af71850 |
In {{cite:47bfa7974486cbce3554ac2e72f3e5ce51345bd1}}, the first part of the series, we focused on characterizing the topology of Gaussian random fields via homology, quantified by the Betti numbers. Simultaneously, we presented a study on the geometric and topological characteristics of Gaussian fields, exploring the d... | d | c19dde14faacd3283e731640f85dbb3e |
The technological advances in WET to power wireless devices efficiently open up the potential to build a fully wireless powered communication network (WPCN) without battery replacement. This would significantly reduce the maintenance cost and the frequency of energy outage events due to battery depletion. Another inter... | i | 030f834680849d62430849d45fcfdb89 |
where {{formula:12cbb61f-9fff-41b0-9012-08620920576b}} is the hydrodynamic force in submerged conditions and {{formula:9ea77e28-871e-457b-97eb-a5f80e481428}} is the particle velocity. In granular flows, the Reynolds number is usually very low, hence the hydrodynamic force can be assumed as the Stokes force {{formula:... | r | 0017657036069a24e1998f63141d6c80 |
Fig. REF shows the UAV optimal hovering path for the proposed Algorithm REF and compares with {{cite:11ec2c70865a5c26b79e673c58cca8839238b02e}}.
For Algorithm REF , the UAV flies between the BS and user.
During the entire flight, the UAV keeps a safe distance from the adversaries though the UAV does have the perfect ... | r | 48e5b2facfdf50212c2cb1301ec9397f |
We also highlight the evolution of {{formula:29cfc0f1-1b5a-4076-8a8e-087a26b18ea4}} in F3, which shows clear oscillation with 180 s period that is sustained over time and does not show any observable damping (Fig. REF ). There is no consistent phase shift between the oscillatory behaviour at the loop apex and in the l... | d | ddd2fe14418b17a51c6c2077ae100458 |
We used four different machine learning classifiers (with default parameters except for increasing the number of iterations) to predict the degree of warmth for the individual twins: Logistic Regression (LR), Linear Support Vector Classifier (Lin-SVC), Random Forest (RF), and K-Nearest Neighbours (KNN). We used the Sci... | r | 6110f36eb1640356e22c301be7db5fe0 |
Since the triplet and fiveplet include charged scalars, we consider
{{formula:d2709f20-5ef8-4a82-a629-38bce8492b64}} as a lower bound on {{formula:ff6182a8-e2a2-4b9d-8572-4ef12860aa10}} {{cite:eca89b6e1414a663fb937e09f42ef3b16b1de112}}.
In order to check whether there exist wrong vacuua that are deeper
than the EW on... | d | e9969135e1fc14ef538c8045e91039c5 |
Based on our error analysis, we see opportunities for further work in the development of tailored loss functions or post-processing methods. The prediction of speed should be disentangled from the prediction of volume to avoid the bias to predict low speed. Also, the underlying city map should be utilised to adjust the... | d | ea581728659d91f02451e16f3e7efb80 |
The SORT {{cite:dfea57e3fd4f5ed865569085da3b996fc5b14a4a}} algorithm obtains the least IDF1 score and the highest number of identity switches. This is due to the linear motion model assumption and simple IOU score for re-identification. Deep SORT {{cite:ab14512a1604c57fff96fa00f3f186f3a0b46ea6}}, on the other hand uses... | d | 84ada5be688c66b682007cdbcab5e9d9 |
For {{formula:959670ab-ad52-4006-8604-6e3b5c9460af}} GeV/{{formula:8bd25c95-6a47-494d-9437-6f0f1c5051db}} , a suppression of similar magnitude is observed for both mesons within uncertainties.
The suppression is described by NLO calculations using EPPS16 {{cite:3f26c4fa32ab41656e8b56129cf51fffafc229a9}} and nCETQ15 {{... | r | 2e3a4445718ea8a30d0b7fb9dc9c65ee |
Frequency conversion and comb generation in optical resonators and microresonators are transforming research and applications of nonlinear and quantum optics. They impact precision frequency metrology, modelocking, soliton photonics, quantum and classical processing of information {{cite:3249bd8eead9743f2e62ff16562777d... | i | 38e6f402a1c51fb2ed27b636caa3456a |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.