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This suppression has been quantified using a semi-analytic approach in {{cite:e6a8d553f2e1747047e59b92d3411e61bb0fc7ef}} for the case of protons, with the results being also valid in the case of nuclei at the energies for which the interactions are negligible. In this paper we will extend the study to the case of prima... | i | dca239f6973909132dfce92194bc5d02 |
Modalities. We use optical flow, released by {{cite:0b39851dc7d0cceb45cc58e698541e159bbbc7f7}} for Something-Something and Something-Else, and bounding boxes & categories released by {{cite:4c0c38302175b42629e81d51aa36ec429fe2cde9}} for Something-Something and {{cite:168f047c3d011db51c08138441279eb55e3b71c8}} for Somet... | d | ffe6e4a168d4dfbc43b91e62f428393d |
Graph backbone and aggregation functions. Various GNN backbones {{cite:9de1b8fe43285fdab5fe6218ea62339c1cfe8621}}, {{cite:e615dc2679b0423bdd4aa6ca4e4684b69b922cf1}}, {{cite:633c36e51ff82bd09ddcc88d66fac82bfb10ebf7}} have been devised to capture graph structural information. They mainly differ in the specific aggregatio... | d | cc8ed6c5e7e40923bbf0cf9c507b66b2 |
Here, we characterize the nature of such inductive bias in the case of dense networks trained to classify natural images, and reveal that the winning lottery tickets of FCNs display the key features of CNNs. We apply iterative magnitude pruning (IMP) {{cite:9b9d1703735cb830fea291fa5f8f9ebc29bb8dfe}} on FCNs trained on ... | i | 1bc16a5462483b759a4b285571913784 |
The basic concept is the algorithmic (or Kolmogorov) complexity (AC)
which measures the complexity of an individual object
by the size of the smallest program that can reproduce it.
In fact, the AC of a sequence {{formula:bcd673e1-6db1-4d03-922d-60ee94a176ee}} ({{formula:bb24dee6-66d8-444a-b814-b9b38a38c212}} ) is the... | m | 4270e38db95024fae095365fb85a1eb2 |
In the past few decades, with the rapid development of laser cooling and trapping techniques, extraordinary advancements in optical atomic clock accuracy and stability have been demonstrated {{cite:0ba9e01e4e3c8682478f111395226ab257629b38}}, {{cite:a54277f08eab65ce3e4b4b34d60d25bf3ed8fcaa}}, {{cite:8b35ec8c5d1fe9c092f0... | i | 007e4579a9358ffc1ea03752ff86a834 |
A key step forward was taken in {{cite:e261116fc450d8e1484fa82ed6b8c8c78efa6b35}}, {{cite:d97a890b4c2889c9db1d8775c439a9f133b7dd00}} where it was realized that by applying a simple perturbation coupling the two sides of an eternal AdS black hole one may make the wormhole traversable. This, in principle, allows us to pr... | i | caf940921ecd5b830c2c09c49511d6de |
The BP-PDF was evaluated for each TS of {{formula:7d3e6adb-2fce-448d-bb65-aeadcd812e87}} data, stochastic and
chaotic, following the lexicographic pattern-order proposed by
Lehmer {{cite:f6b9bbfdffa8c1fe3acc44b7957ac2baf6cbe71f}}, with pattern-lengths {{formula:b6d90e20-e64e-4ba5-a5e9-0b599e4223f1}} and time lag
{{fo... | r | 491ba1ce90e13b1fda2eb5bbd19560e4 |
Recently, due to the success of CNNs in many fields {{cite:7debbb0faf9021ab9d0f0e203f43ed2e43944bd3}}, {{cite:0efda089e3778154b09d18acebc213e3fed0e096}}, {{cite:4a6deae183b42e7d316ac86770c1a91ba172817b}}, {{cite:25d357845b1f6eccbda80d6a47cdc42a3bc858cd}}, {{cite:cc60e828cbe72bbd1b192859d391595f8354520c}}, CNN-based met... | m | 33c6b4bb705f5ca085a9cefe9f40a27d |
Models of the X-ray emission from the ring {{cite:ed5114e454b3e69b903ee9450cbeea98ac2d2ee2}} suggest that X-ray emission comprises of a soft X-ray emitting component, generated by a {{formula:966d1c22-1db4-4d06-a468-fe222a09de4b}} km s{{formula:fef94175-1377-488c-9ebc-535c0a0307b8}} shock propagating through the dens... | d | 278d756d02cb02a7380985d6d9a8bdd7 |
We train and evaluate our models on the COCO val dataset. We use the detection results from a person detector with AP 50.2 on the COCO Val2017 set. Following standard practice {{cite:136df470834722dcac0e53a09d7a48475b9afd60}}, {{cite:a3f84e4b5684892224eeb4bd303d81a325345d0b}} we use flip test and average the results fr... | m | 7f3f89ee6573a85072da91b560a5413e |
We used ResNet152 {{cite:e88cadab7bb25ef48884f8fbb8c6caa4648d982b}} as pretrained model for the encoder.
We tested several set of parameters to find the one that would allow a transfer learning from Western fashion data. As the latter are more abundant, we wanted an architecture leveraging Western style captioning to i... | r | 5f5348929dca05b8e951fa2ce0b06ae9 |
Here we specify additional details on the baseline methods used in the learning experiment.
The ADF method, called AP2 in {{cite:f7dddc71bea8240903bd3da15b5f911977465917}}, propagates means and variances through the hidden layers fully analytically. This method is the equivalent of the PBNet method in {{cite:03dba83080... | m | cc8d8415f9b3718da30300844fa1b401 |
Limitations.
Extensive discussions about social data biases are presented in {{cite:83a2eb5c3a5a86f318aa9609afa3574b44b86478}}. The biases can be introduced due to the choice of social platforms, data (un)availability, sampling methods, etc. Here we discuss three limitations in our data collection process.
| d | a507e956e9e0e3d6d78b6ff0466476f9 |
Self-supervised learning is a widely used paradigm to learn representations from input data without human annotated labels. In computer vision domain, it has shown superior performance in many tasks, such as classification, detection, segmentation, etc. A popular self-supervised learning framework is a Siamese Network ... | i | f861c37db2c95b896a8730d185bbffe3 |
Algebra of quantum fields, rather than their particular realisation in terms of creation and
annihilation operators, should be of underlying relevance {{cite:4cc859e917398e8f9e6a27075a53cd3b2e77b390}}. We have
proposed in {{cite:1000b9c5ba86e33b158c4eb403e3ffe84592f9e9}}, {{cite:043b6bde4e17955d908b9bd00572ef4b9b06ce57... | d | e7e894a59ffdbf39ba39ba96c0ce3988 |
We make use of the following basic results related to matrix inverses (see e.g. {{cite:48ced209368465efc3e12b3d0b8035253a681b93}})
| r | b8daa6b01aec9c6e4e5980d217b08343 |
Even though the classical wavelet transform (WT) serves as a powerful tool in signal processing and analysis, its analyzing capability is limited to the time-frequency plane. Fractional Fourier transform (FrFT)({{cite:94a4ac14d728372b83972bcb50d273e00b8c4001}},{{cite:6704370185b8830f9e784eda671d8ea9a2413551}},{{cite:21... | i | f0e3d867b78ccd9cd7f6670f333b159c |
Gradient {{cite:d36d5d9056f9b2783ad7bfdd9986aa6fabda3cb3}} uses the gradient image,
which measures the sensitivity of the confidence score of a target label to changes in each pixel.
Integrated Gradients (IG) {{cite:8a39e84c5f9422470010b7a9e7b6e03e297c4b2e}} ameliorates the gradient saturation problem by linearly inter... | m | 3bfc87692f32147e04a789c67acedd54 |
Moreover, the deep learning imputation methods leverage deep learning models {{cite:165d2fb684f502006f1504b9bb78a7f6b65769b4}}, {{cite:6aa268ae0c13cb968f1b1fa19f0640a3b68c950a}} to impute missing values with the mini-batch gradient descent.
This category consists of i) MLP-based ones like DataWig {{cite:623f1a95fa15ff6... | m | efef9d8e79cd3540c56a9b6a697208d7 |
The interest in kernel methods has recently surged due to their profound connections to deep neural networks {{cite:3b609d07876cf29ce6051bcbf41e026bf1283f80}}, {{cite:e9c4ff42f7506121d422c5aa1f587c0cc41cbd96}}, {{cite:ad90a8c5eb82951cb6ca2fad0c11926fe2407dea}}, {{cite:4e814706c0b8c7e14725e3c3f7d417dfd30c9f89}} and repl... | d | bd065283f4260d891797354630fd2c99 |
In the experiments although we restrict the visibility of the robot to real world (lidar) sensor ranges and subject the robot to noisy state estimation, we do not account for occlusion and uncertainty in observing the environment. A tighter integration with a perception or mapping pipeline would be necessary here and w... | d | a10df6a1b0f2c9b474795608eefd8ba4 |
We used Steinhardt order parameters{{cite:d9d8d8b237a34704036f1cf98c8519a21286d652}} to classify particles as having AlB{{formula:d03d60e9-d6e5-4709-8d8f-3d84868d89ce}} , mixed FCC-AlB{{formula:13af9056-557e-41c3-b9b7-e043291bc434}} , or fluid environments.
We discuss our specific use in section S2 of the Supplementary... | m | c48db349e8f8fd40053a6d9a006c9a38 |
In this paper, we set the transformers as rational-quadratic splines. In fact, other splines could also be considered as long as the transforms are invertible, for instance linear and cubic splines {{cite:0a2cf2c4ccbda18d292fa3c2092ddd13bcf80e35}}, {{cite:06d95fd8891bd8b093f3d1cec069ccc50d5864d5}}. However, it is hard ... | d | f2abbfedd44115e75fe1c4d03657c371 |
Ensembles derive a prediction based on the predictions received from multiple so-called ensemble members.
They target at a better generalization by making use of synergy effects among the different models, arguing that a group of decision makers tend to make better decisions than a single decision maker {{cite:1e0f27ec... | m | 4360dab9de98874b1102b3f9585457da |
An elliptic Painlevé mapping comes with nine parameter points, whose configuration determines its dynamical properties {{cite:0a59ba24cafb2ee9322edca908192168f73cf0e3}}{{cite:224fca42806c6cb2bcfb9146cf604ce4ceb092c9}}. For some special configurations of the parameter points, one can find autonomous reductions of the el... | i | bf7b7a4e2549f22f3643cde6b681a69a |
For the PKU-Sketch dataset, we compare our method with Triplet SN {{cite:1bf5e5d46d709dbcbc62267eae44aeccdad25525}}, GN Siamese {{cite:96dd09bf40f5f9e6652c2d9c148489a5e71f1bb4}}, and CD-AFL {{cite:d9c406f9ece9d4b9d7979391bbe502d1f95dc140}}. Among them, GN Siamese and CD-AFL are pre-trained on the Market-1501 dataset. N... | m | c7502a69034bbc3c910185081889f30b |
Limitations of RSC .
First, to guarantee the model accuracy, we only replace the sparse operation in the backward pass.
Thus the upper bound of RSC 's speedup is limited.
However, we note that the backward pass usually is more time-consuming than the forward pass, which is also empirically shown in Table REF .
Second, ... | d | bb916ce7c9a293368402cbf0e5aa9132 |
In contrast, hamiltonians of PTQM models with broken {{formula:429cab0d-66d9-4d10-adef-230ec8e00fe0}} -symmetry are associated with indefinite metrics, and are referred to as pseudo-hermitian {{cite:5d89706bee6b2115c72a380130eee99bf680cf83}}, {{cite:07e80aa3dbbfba34b087635f3343da1fe26c26f5}}, {{cite:cce2bdf0eca1880db4c... | i | 8ada7c897c37d94a1494b1b3b32c2428 |
where {{formula:1a1662fc-caef-42a1-ac35-c29ea8bc7bfc}} are the theoretical predictions of the N=156 observables used in the fit and {{formula:7f150be2-1801-4e03-8ef3-252d1b212ff2}} are the corresponding central values of the experimental measurements. The total {{formula:9ba302ad-303e-4069-8ee4-b8829706cd9d}} covari... | m | 46146dde5bae88f73b8f6aef58196d28 |
If all the matrices {{formula:b6348cee-e26d-47e9-aebe-7246d4f9d5f7}} commute with each other,
the function {{formula:7a983fe9-3c42-4b11-81bf-69454db6fdb6}} is called a prepotential or a free energy (cf. {{cite:e3ede04b403e383462e54b51b2a2f0f63481f174}}).
Writing down the matrix entries of {{formula:7cb4a9f0-cd6b-4fbd... | i | 057270888bacfeee8bac73ac787232b1 |
where {{formula:78baaa95-9e6f-4066-bbcf-e3bfe5f23abe}} is a class of explanation models; {{formula:b655f015-9a02-49e2-87f2-12e28f0a688c}} is a fidelity function which quantifies unfaithfulness of {{formula:092acbd1-70f7-4424-a494-82bdbb314c62}} in approximating {{formula:f00bf6d4-87cd-49fb-a053-d603bdbe8bde}} withi... | m | 87eabb7be7ce81316ab37e64bf5086b2 |
Another area to explore involves the particulars of the DNC's external memory. It could be useful and interesting to analyzing the memory contents through the timesteps of simulations, to get a grasp on its inner workings as it moves through different parts (tasks) of an environment. It is also not certain what an adeq... | d | 1aaac1c29c0123065461baf02746b876 |
Understanding the physical process of thermalization within the framework of quantum mechanical principle has been a
long-standing problem. Thermodynamics and statistical mechanics are built with the hypothesis of equilibrium
{{cite:462d491a7d7dd3b29b29745c1844936bf742d36b}}, {{cite:1ba89c77436c8d3cc0a72e93c687a9031838... | i | 24e77f97543f5e8bc4a1e7f4847dbc51 |
Table REF gives the normalized signal and background cross-sections due to all selection cuts.
These are obtained by multiplying the production cross section given in the first row by acceptance efficiencies.
The production cross section are estimated by multiplying the leading order (LO)
cross section obtained from P... | r | b7bca8b0c4f196eba514a4eab88e87b9 |
In quantum cosmology, the wave function of the universe is studied in problems of its quantum origin {{cite:6b7e82bcd4304b96c998f30d0991dd8ff326c34e}}.
Quantum tunnel transitions with a change in the signature of spacetime are described in the imaginary time
formalism {{cite:33e6aafa5d2015cdadbaaafac25157c70405cb0d}}. ... | d | 4e9a8f4e24bd80517a14dc61b848a358 |
This statistical model implies many other strong
performance guarantees for a variety of tasks
such as covariance estimation, OLS, Lasso, PCA etc.,
which directly apply to data transformed by Gaussian embeddings, regardless of the
distribution of the original data matrix {{formula:0818f465-26fd-4aa6-9939-99762cfc466c}}... | i | 5e2b7cb40647b974d147d886aefc56ad |
Experiments were carried out on a dataset acquired from 2012 - 2020 across the German federal state of Lower Saxony. The dataset contains a total of 19,995 aerial images, each of which consists of RGB and near infrared bands with a spatial resolution of 0.2m. The dataset was randomly divided into training (70%), valid... | r | 561cb42571f2eed9b7e78b4ade352788 |
To compute the conductance of such a wire, the Landauer-Büttiker formalism of coherent transport
is used {{cite:cfbedb4639be035bbd57cc82e4985c8a93fed87f}}. It allows to relate the dimensionless conductance {{formula:dec38adc-edb1-409c-95d7-d47a7548defd}} of a diffusive wire with the scattering matrix {{formula:ed349b9... | m | 47135911e629b0910425cf11ece3a5b0 |
As the 2.5-D slice classification network, we use a 2-D ResNet50 pre-trained on ImageNet {{cite:9f9b4dfc2780f80f0fe86f12ef321eb3d0ae148e}} as feature extractor with a consecutive LSTM layer. Furthermore, we also incrementally evaluate the benefits of segmentations on the input images to perform an informed cropping, as... | r | c11a092c226f1c72e1f028a7d3ff21f1 |
Human study to evaluate concepts' explainability. We performed a Mechanical Turk study to evaluate the explainability of our extracted complex concepts to the end-users. The participants were asked to select from four different options (presented in random) of what they consider to be the best possible Explanation for ... | r | a6665d6486920d897abfd49a04b82e32 |
Sensor fusion algorithms are often developed with, and evaluated on, data sets with perfectly synchronized sensor measurements, e.g. the EuRoC data set {{cite:e44c40f242eef519788ec74027e8d7a3d3900661}}.
In reality, separate sensors are never completely synchronized.
The degree to which they are synchronized depends on ... | i | 551c4907de29c9f5e1575d057df86fb7 |
denotes the relative entropy of {{formula:94d0cb8a-fcd8-4cc4-ab9e-e7b76e69b536}} with respect to {{formula:8837d3c2-cee2-4fb2-8090-21081b3d316d}} . In the special case when {{formula:8aa59df3-dfbe-4f87-a3c9-0377c9b13251}} and {{formula:886e3bb4-67a8-407f-8c88-c6584207ea92}} are probability measures, (REF ) reduces t... | r | edc9aa0f1cc66bea212b617f30cce14e |
1. Replacing pronouns by entities using the neural coreference system {{cite:30c1fa1362f1c3ae3a11486d5f9b023b3bb2d1c7}},
| r | 2e21d3e61a89c7c02486df00465e98ed |
We consider a memristor Liénard system with external harmonic perturbation from Eqn. REF
where the parameters {{formula:f892246c-fc9f-44ae-8526-6fa36dbb4d3f}} are known. We generate our synthetic dataset by simulating data points from the nonlinear differential equations using the Runge-Kutta method {{cite:971ef68b32... | m | 4e74a2b91f97ecf2e246c4dd15a2afb7 |
The theoretical result is based on CSP, which is not computational feasible. As mentioned in {{cite:ef7215a502de6207c139c5394d87509436fa4bdf}}, finding the solution of the CSP optimization through exhaustive search over the codebook is infeasible, even for small values of the video size.
It is hard to verify the valu... | r | 252c399096c6d406730bfa3f671e8b8e |
ALM was first proposed by Hestenes {{cite:ee34fc7bf5b038139d7a01f741ac6aa28bfa4b20}} and Powell {{cite:860f2e95fe087d7829af2afdd3269dac4d4f059c}} in the 1969s as an alternative to the penalty method for constrained optimization. For the penalty method, the Lagrangian multipliers are absent ({{formula:fd6291d5-7ff2-4c8b... | m | 1cbd66a5c034d09d6eaf76abf7aa2850 |
[leftmargin=*]
I.
Active Ornstein-Uhlenbeck Process (AOUP): We first consider the scenario where the active force at each boundary undergoes an independent Ornstein-Uhlenbeck process {{cite:65486ce850aef28c97ca8c2da37dea4c3a29b1fa}}, {{cite:4d59b0a9c330207ace9ff07921110625b20f9610}},
{{formula:02a6a75b-8450-4af3-a030-0... | r | be0d3cfe47ac1a4df769c5ec6800135e |
In this section, we discuss the power of conditional SI.
It is important to note that a conditional SI method is still valid (i.e., the type I error is properly controlled at the significance level {{formula:7ead0f78-e6a4-46d2-bfe6-70d70f6c1e1f}} ) in the case of over-conditioning {{cite:5245bd2829d5f6f1df614e1c0145efd... | d | 9d0a57673ddc538fb7d09c7d10935124 |
We employed the Gillespie algorithm (GA) {{cite:1f4906ffb434aedb06e458d00a36b0b302492338}} to simulate the protein networks.
Each protein network was made up of these reactions:
{{formula:42b5cd10-0388-43a0-8e35-db4d8d84e21c}}
| m | 74218246beb688c5388e56150bcd0e98 |
In fact,
we adapt the single-spin-flip variant of the Metropolis algorithm {{cite:b610fe6fdec4dab148615ee3a0eeb782137ed037}}
since we use the single-junction-flip dynamics to generate new states.
We refer to the literature to elaborate more sophisticated variants {{cite:b610fe6fdec4dab148615ee3a0eeb782137ed037}}.
| m | 256600544d0637bb81f2093848744e6c |
A black-bounce spacetime suggested by Lobo et al. {{cite:616648dbc641a8e78f7057c7c49e46def55179a9}}
forms two photon spheres which can be observed by an observer in the parameter region {{formula:c2bc382a-b5e0-4f0a-83fe-4d7dd6a90a5f}} .
We apply the formula in the strong deflection limits to a supper massive black hole... | d | cb341bf348167ee6d4ea03206d5f9fdd |
Full data.
We follow the setup of {{cite:ae7afe55e38718b89ed44feed89af3bc4da0bb0d}}, except that we apply a dropout rate of 0.1 on the expert MLPs (as done in {{cite:5fc2ec709721950a4d29f013e584d1daccdd26a4}}),
and we halve the number of fine-tuning steps for all datasets other than ImageNet.
fig:imagenet2012testaccflo... | r | 7dae2b8bbfbfff82d605c46879611a9e |
Federated learning supposes to support co-building models among multiple devices, while preserving privacy in-between.
Among these devices, each holds one replica of versioned model and its local data objects. Usually, one small set of
devices, called servers, are powerful that can publish a master model, and compute t... | i | c56cbd0d9572ebd2eb04f3b2f8d3b8a4 |
the inverse of the minimum value {{formula:49aff405-b882-43fe-ad70-c7cc9c16ae00}} .
Adopting PDFA techniques takes us into a different direction from
existing approaches based on a direct clustering of histories such as
{{cite:541868f80717e9f92340554f2badee26f6a4bff2}}.
There, histories are clustered according to the p... | d | 0fe77760411b34ad5f416a94578d7bde |
Hardy and Littlewood {{cite:2f979e7ff9b145aa320316123fe8dc8ba1077a9b}} showed that {{formula:0774a97e-66b5-446e-b7db-c741f01c7cf6}} , and Ingham {{cite:9d931bf671e1a54b26c425d978d1ed07e09f0c3a}} showed that {{formula:c01230d7-111d-4e7a-9daa-af27589f9c13}} . It is conjectured that
{{formula:53f22062-bb1e-4fac-af8e-fa0d6... | i | f267241071e3cb882f7cd54b5c78b8bd |
In real scenarios, we cannot obtain a solution directly from Eq. (REF ). Therefore, {{cite:cc6262a0dff277cd8a2610bffb8282c92fe3a901}} proposed a solution by splitting the {{formula:68f474c8-cc77-4c4d-9162-ba47b4947826}} axis into bins, computing the local effects inside each bin with a Monte Carlo approximation, and, ... | m | c1ada2d993e7452b9dc78f4476bd973b |
By the same token the higher spin extensions of SDYM and SDGR {{cite:a8e3608b34ca569e76913b322381cc8548498936}}, which were previously discovered as contractions of Chiral Theory in {{cite:087fc6232adaf817c929284a75ebf5c3b30ebaa8}}, must be consistent contractions of the present FDA as well. We note that in the latter ... | d | 5309fb76d5457ca782b59617a1a1aff8 |
In contrast to active tracking, passive tracking collects information about people without the need for active participation. Under the category of passive tracking, some currently used methods include cellular activity tracking {{cite:2b1f5a52f807c6dcfcd47d283a85ff7f51b32bbe}}, {{cite:f1dcfca73f90ebe80c57160a82c68579c... | i | 0dc395395624e0ac684e2c85d0b80679 |
To alleviate this problem, we focus on the Deep Convolutional Neural Network (DCNN) which is a modified version of Xception {{cite:a303d1870690126d3438800c206bf91fae713028}}. We leverage multi-task learning to enforce the encoder to learn weather and time specific features. We add two simple identical models Weather-Aw... | m | 66eca8d45238a9494c68f8dc14e645d6 |
The mixture distribution facilitates the closed-from Markov-Bayesian recursion greatly in two means: First, a mixture of conjugate priors is also conjugate and can approximate any kind of prior {{cite:0835e051225623fa923362f242309751599a5328}}, {{cite:f92d97fad8c2b43dc3807b419ba74a4d01ac9e63}}. Second, the linear fusio... | i | a4097529f4edcf4c72298eea7c601e43 |
With this multi-disease segmentation in mind, one of the main future directions for the BraTS challenge would be to expand beyond its current focus on glial tumors towards general brain abnormalities. Furthermore, the extension from solely pre-operative baseline scans to post-operative scans, and the inclusion of an ad... | d | 519f0065ca6d5d000fe8c5e9d30cb1d1 |
All spectral fitting is done with XSPEC 12.11.1 {{cite:bf861bfc4e7b14bfe2b709c077051ea2a2bafe35}}. We use the PG-statistics, for Poisson data with a Gaussian background. We use the wilm set of abundances {{cite:5f61bf41bd67eb94961c7d8a8d76d84e1b1f66f8}}, and vern photoelectric cross sections {{cite:fec8f1f9767509b10614... | m | 82ea1980e433ea4b424a9ec5392f65a7 |
are generically produced. They come with completely fixed coefficients as a precise prediction of the model {{cite:7456c834203b0c03ced19ce07129e3231eb9b9b2}}, {{cite:e703d2285e0857b2aab45cc2c1834cebba0c894c}}, {{cite:562289e9ea109ccefb590e4e9f5e6a32777ddef2}}. The presence of such terms, where the {{formula:866eff9d-77... | d | 7bf6d94b444e16c9f5fef65dc2d5a69f |
The Fermilab Muon g-2 experiment {{cite:6c78deaec9a114869c6e255183911da1a210209c}}
reported recently their first measurement of the muon anomalous
magnetic moment, {{formula:8a05ebd7-5a4a-4053-85f6-0d550dd17c2d}} , confirming
the old BNL result {{cite:10b50323b7213e557e499dacc8b429efc3e48546}}.
The combined value of
{{... | d | bc6f17a105e8ee8ddd9b88881eab635b |
One can see this result in {{cite:096193f4de577fdffe415af5729a300240907c96}}.
{{formula:ab9757ad-eb6b-4d70-b483-a7080e738d1e}}
Next, we state the functional equation for the Dirichlet {{formula:d20f4504-2a1f-4cb1-a258-49863497cc61}} -function.
Lemma 4.5
Let {{formula:45524ee0-786d-4232-9b37-37e5cdb81cf9}} be a Diric... | r | 3c512fbbc460bc3eaf85f9af4f0b7d3d |
Distantly-supervised Methods. (1) KB-Matching reports the distant supervision quality. (2) Distant BiLSTM-CRF, Distant DistilRoBERTa, and Distant RoBERTa fine-tune the corresponding models on distantly-labeled data as if they are ground truth with the standard supervised learning. (3) AutoNER {{cite:c93730997de1b3f6ad0... | m | cb11f9be629a5a63833b76440b77989e |
A pending goal in this research would be to obtain the effective electromagnetic action in our approximation and also as a non-perturbative result in the tilting parameter {{formula:d3a6a480-8f1a-4830-9f6e-c371ee508124}} . This would be especially important in the context of Weyl semimetals, since the value of {{formul... | d | 63db008e756cb5271277f6cc236daeb4 |
The proof of Theorem REF is quite long and technical, relying on the machinery of stochastic estimate sequences {{cite:0628faed751167604c5d2bfdbfc2b3b5f2a5ad31}}. Therefore, we have placed it in Appendix . The high level idea of the argument is as follows. Existing arguments (in the unbiased setting) based on estimate... | m | b4bb8ab1795a8dcd249396953f76f18e |
The question arises (of interest from a theoretical point of view, though irrelevant for applications as in {{cite:5446486f3af5a1a843be0ed1110d4abe9bf2ab55}} or {{cite:d6cc13cfaa9b7fe31d306b605f07f1eceaec7936}}) what precisely happens at the thresholds. The first part of the following is concerned with this question. I... | i | 8a05259a63e801a1c7fcee7c7c56c48f |
In this section, we demonstrate the performance advantage of the sample-based PMD-PD algorithm (Algorithm ) in the same tabular CMDP described in Section and in a more complex environment Acrobot-v1 {{cite:a16a8573a56cdfcc226c3cf161ae432e9285e3e2}}.
| r | b45c2204be0ee8675837943504a63262 |
The systematic study of stochastic optimization problems under changes to probability distributions extends at least back to {{cite:185bf8bf9d44d7c4c6078576bacb43b30cdf5e51}}, {{cite:0e53985e8e55b42af06ad4d1f6c5bd480909e1a7}}, {{cite:47e5ac2f90cef44373b3751200f59236577975e7}}, {{cite:3d60ffaed791d671014d6539387b30e8575... | i | 3a4b91f758faecee4e6cf638b1a7d2cb |
The output of the two approaches described above were compared using pixel accuracy, Intersection over Union (IoU), and mean IoU; three metrics that are commonly used in semantic segmentation analysis {{cite:8b9097beafd26ec34b7bb9fe5322aa8f5ed1c273}}.
| m | 9abe2313ecad232d8d39abfe26bf21ec |
Over the last several years, substantial interest has been
generated in the problem of solving underdetermined linear systems
subject to a sparsity constraint. The field, known as
compressed sensing or sparse recovery, has applications
to a wide variety of fields that includes data stream
algorithms {{cite:3d681be00daf... | i | e1d84bcf2297dad05604188a7dd5be8c |
In general, an agent can experience a quadratic speed-up in its learning time if it can perform an arbitrary number of coherent Grover iterations {{cite:5a417ab9c233d19388202b44af99df12defb3b76}} even if the number of actual rewarded sequences is unknown {{cite:aa7531b1bcd29f851a9526cbf200107115a7a888}}.
| r | 40a4a0d51c9ee3a7200b82d0eea7fe9e |
In Table REF of the main paper, we compare to published works on the validation set of EPIC-KITCHENS-100.
Unfortunately, most works do not report on the leaderboard test set.
In Table REF , we provide results on the test set comparing our model to baselines from {{cite:81b3ca571824e14686b55e79e46f15d8a54185be}}, as we... | r | 59fa7d93f794d82e284e1079540f4681 |
Label correction-based methods. In the early learning stage, the model predictions are accurate on a subset of the mislabeled examples. This suggests that label correction-based methods are potential for correcting the corrupted labels during the robust training process. For example, {{cite:ae923d9fb1844ec58b4c3adcc77d... | m | 8923e7db1f62d54ce3578cba58562e1e |
See {{cite:81a6101a6ce8f00281c2f93c6e76c53efa63f8c8}}
| r | 781b6e458df9c69584f1a2e20458e431 |
Despite efforts to make the lectures self contained, some familiarity
with basic ideas of statistical data analysis is assumed.
Introductions to the subject can be found, for example, in the reviews
of the Particle Data Group {{cite:b7f42fa66abb764b9a102967d07c40d59dbc951a}} or in the texts {{cite:41f07f9cbe6bef89a8eb3... | i | bf49c51f4c6b12620adbe9e4923e67b7 |
Training time becomes an important matter for tasks that have high degrees of complexity, like the block manipulation tasks in OpenAI's Gym environment {{cite:8463f373591d530549388481ff93f53882670c78}}. The most popular method for learning in this kind of goal-based environment is Hindsight Experience Replay (HER) {{ci... | i | 0df0c29431787296dcd86503c54f4875 |
The recent discovery of billion solar mass SMBHs in luminous {{formula:79ab7dba-6b46-452b-bb57-f70e6760cab4}} quasars at the epoch of reionisation poses the most stringent constraints on the masses of the seed black holes and the early accreting mode {{cite:74dc8f755d8bf1353ce128165bcac1fdd28ff83b}}, {{cite:31c521bf33... | r | 5fbf38289f221ae1528f1a075a217cbe |
Numerical simulations reveal that cosmic structures develop universal properties, for which the radial density profiles of gravitationally-bound objects are an important example {{cite:7daa8f27df6db839f3318efadc77e5f916a2b00b}}, {{cite:1a1e482a486c239fb23073a1207d4d82aaf5cbf4}}, {{cite:a300e4310e4cdcd2dc4f5673afcb775b1... | i | b5a3dabe923185a90130b20977b144bd |
It is well known {{cite:75ea482bb6dfe5b77a57770c9696fecf190f9561}} that models using a balanced static batch can have higher performances respect to those that use an imbalanced dataset. It can be interesting to know if this aspect is valid for streaming methods, too. Our proposal is a meta strategy, as Swt, called Reb... | m | 7afd780d189150fd61d2cee99f882a66 |
The consistency of the PLS methods was proved by Delaigle and Hall {{cite:396da1e7e35e33f927ab0adf130fbf123a2554fc}} where they found an equivalent space with explicit expressed basis functions
to the PLS basis space. For PQR and PCQR methods, it is difficult to find such equivalent space and therefore their consistenc... | d | 53f40dc2b788bc5363768d9480b4689a |
Many defense strategies have been proposed to counter adversarial attacks {{cite:3906b352c65da9f0270a0a816ecbf8380fab88cc}}, {{cite:99786d397b7b6db0c1d7a9883f92efccf4fe995b}}, {{cite:75aebbac18b4906d9bd9f350adf0460ea091120f}}.
However, it happened many times that a new defense strategy is broken down by a newer attacki... | d | 9016e1d1d2bb106de55d3cc19eef1520 |
We show more qualitative results of the proposed method on the PROX {{cite:749a416f69fbfc03a1101080896ecda8d186d4c7}} and Matterport3D {{cite:c8c8f0325058e18a56f8bee82312df755f6a013a}} in Figure REF .
We show all three aspects of the synthesized scene-aware motions, including the human-scene interaction anchors, divers... | r | b3abe5a7ca89f6dde20938e6c865ea71 |
where we used the Jensen inequality. For the logistic model, the PAC-Bayesian bound Eq.(REF ) holds {{cite:ef4ab73d2981ef24e68fc8ff42e6e89ab62c1f37}}, we have
{{formula:9729716e-b575-4b43-9c98-c1d5ccaaa25c}}
| d | 65ed35ed2f83a47fc9e2aadbd027a439 |
The first set of diagrams, depicted in the top panel of Fig. REF , represents the correction to the quark-connected contribution in the electro-quenched approximation, where QED corrections for the sea-quarks are not taken into account. The right most diagram is the strong isospin correction while the other two diagram... | r | b54857056cceb5feedf4c0532a0220d0 |
The FL {{formula:3a4a9eb1-1c72-49a1-8098-3f3860f364aa}} resistivity mechanism discussed here explains the behavior of resistivity seen near band edges in magic-angle TBG {{cite:f85c247dcdfceb05becd19495498984ba3b97ca5}}. In addition, while the “strange-metal” linear-{{formula:d857e2e4-66a8-4543-a07c-44c2499c8dc2}} re... | i | 26a099d6624dc0a74aa82f36691cbefd |
x1Rn, y1Rm.
In problem (), {{formula:4879a99b-09be-48ef-965d-5c3e01f9ae4f}} are decision variables and {{formula:4591f724-48b5-4464-99e6-89db5ffae08c}} are fixed parameters. To handle problem (), we employ performance estimation method introduced in {{cite:7e69f0c13efba13f5307e4e4a5d142e5938476fa}}.
| m | e4c90b33aef971d4bcb4339a4c2d04ca |
Inspired by the recent success of the text-to-image generative approaches, such as DALL-E {{cite:a1153d7d36bf8398fae937ef84f1decbe458b25a}} and stable diffusion {{cite:8d15fcfe8b4ad25f68d59aa3112147bddd42167c}}, we propose DiffAlign - an approach to data augmentation where synthetic images are generated using the textu... | i | 49985ff7dabc1362ee6cf031d3fef4a3 |
More specifically, We analyze our per-class accuracy on CIFAR-10 {{cite:757bf4e3bd86c9abad6e14ae19fdf2d616aabe88}} with 40 labels, compared to FixMatch {{cite:59b6839e68565961cee1c67aa8f55144dbcd3590}} in Table REF . total accuracy of FixMatch {{cite:59b6839e68565961cee1c67aa8f55144dbcd3590}} is 87.11%, but it can be s... | r | 02260a24e3da9288a16141106787e55e |
Some GRBs with hard spectra in the GeV energy band can be explained by the IC/SSC mechanism, while it is
hard to explain some GRBs with soft spectra by the IC/SSC mechanism. It is possible to solve the GRB spectral
diversity by the jitter radiation with the turbulent cascade scenario {{cite:998da0d23c36c9a5bffb15ff523c... | d | 4f2b4f5262b205f86ef5f43e7c9c8454 |
{{cite:8f5dd21276a0aae124024f63c2539ac490b4bc54}} focused on the idea that these data show that the
hmsfrs are orbiting the Galaxy with a velocity that lags the
circular speed by {{formula:c78b3084-6855-464d-b893-dd573fd9090e}} . Our analysis of similar models
shows that the data are fit better by a slightly smaller of... | d | 7bb4523c2d418c966e98c0836c4d41be |
One of the first zero-shot methods is BM3D {{cite:d329045951f33e1c7873c21b90883f56072e6f22}}. BM3D collects overlapping patches, clusters them and then finds a lower dimensional representation of those clustered patches. BM3D assumes Gaussian noise and requires a user supplied estimate of the standard deviation, theref... | m | c0f5d8b6e18ac0b432658822411f9833 |
Following the strange nature of dark energy and considering the similarity of this component with inflaton field, an alternative to cosmological constant for explanation of the late time accelerated expansion is a dynamical scalar field with infinitesimal energy density, called quintessence, which its slow-rolling evol... | i | 1fc7a4d7cf3b8c8f18f718f4ba845b14 |
Fig. REF shows examples of caption generated by SGN and TA {{cite:5cec516fbecd24c9dedc8a533e36d4943aaea257}} - the same pre-trained CNN features are used.
SGN is able to better identify the subject responsible for the action performed in the lengthy video scene. For example, SGN chose to predict “a band is performing”... | r | c44501f85aa85ffa0bec0027127b1de1 |
Taking a relatively large perturbation of {{formula:d948f7e9-d7ee-47d2-ad8f-8ec736f8e677}} , we have {{formula:55222a87-6b60-4bd1-b7fa-145d974aed6f}} independent samples for an eigenvalue {{formula:a563c74c-05c9-4fe2-a53d-3c7a57e81df2}} , the order of magnitude of the largest mode {{cite:f293e8b53367e4ce150541f94e133... | d | 989a2720f61ae7649c8dfcacb5c055a2 |
Having such a Gaussian random field at hand, one usually parametrizes
it by means of the Karhunen-Loève (KL) expansion or a polynomial chaos (PC) expansion
{{cite:4c2ab74879e0272da7d2e155fcd98d9b05a8a975}}, which fits to the {{formula:52ee17c9-c66e-425c-b439-caa973dd9fe2}} setting, i.e.,
{{formula:df785e28-8732-4ad8-... | i | a86e3cac283b85ba42b79bbf03348a59 |
In order to improve the interpretability of the discovered physical laws, learning explicit dynamics (e.g., closed-form governing equations or their parameters) has recently become more popular in physical scene understanding. Several hybrid methods take a data-driven approach to estimate real mechanical process from v... | i | 338a273ea81f58995ea6093b80c3d6a1 |
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