text stringlengths 54 548k | label stringclasses 4
values | id_ stringlengths 32 32 |
|---|---|---|
In this study, we find that in a large and successful software company, communication patterns have a strong association with organizational structure and that communication between employees increases with their organizational proximity, both globally across the organization (Figure REF ) and locally within teams (Fig... | d | 067cdca117f18db973f0bdf86e5fcea0 |
A frame is a generalization of an orthonormal basis that provides painless nonorthogonal expansions {{cite:272014fb719dd95adb25b9adb748bef89101e711}}. Frames
have properties similar to bases, but they offer more flexibility to accommodate specific
design requirements, and their redundancy allows for protection against ... | i | 9240fd234f01fd4a75d10e18eb92845f |
However, in the second stage of preheating, backreaction might increase the frequency of oscillations of the inflaton field, which makes the process even more efficient. Another issue is that a model with the quantum scalar field {{formula:ee49fd90-84e8-4775-ab28-1f8d9cb44767}} non-minimally coupled to gravity is anot... | d | 6ac5299c9aa2a4cb533f38724997bd0d |
In Table REF , we compare DA results with more augmentation methods in Something-Something-v2 and UCF-101 datasets, such as, RMS {{cite:83ce614a53e2f5053fca2c42077d50fabb850e75}}, MixUp {{cite:bb56f2cddb81e77226f84329d93ddc73f8f77911}}, VideoMix {{cite:4fdfd793f79c46123e66e42c5548a422896c1b78}}, and AutoAugment (AA) {{... | r | 5c4ef023d7b0056a289a4173320c69b3 |
Due to the complex, nonlinear nature of the turbulent energy cascade, direct numerical simulations (DNS) are likely the best means to investigate the role of magnetic reconnection in the energy transfer across scales and how it changes the turbulent energy spectra. To date, no evidence for a new range of the turbulent ... | i | db10bd9ef3bab3efcc0786cc9b1732ca |
is known in the analyses of the anomalous Hall effect {{cite:33ad2c346b037bac04b75a508bc33f7fc5d5fe2e}} and the spin Hall effect {{cite:408034c9d8c9942860cee59c33e844d83a9f6282}}.
This effective Hamiltonian of the two-level crossing for the generic {{formula:704187ea-c371-4b1f-9f33-0945769911df}} (Bloch momentum) has ... | d | a708781798394478b11077fb57629a7a |
The real merit of our algorithm is that it is able to produce BBP-type formulas to non-integer bases, while still producing formulas with integer coefficients. We have not been able to find examples of this in literature, though Adegoke {{cite:d8cbde1b21d64122f11dcc10fb901d88a2312c8a}} does have BBP-type formulas in ba... | r | bfd4ac2b9a00aec6ada8636eb989d8f6 |
At the time of the acceptance of this paper, we notice that there is a concurrent work {{cite:7155ad7a0158bde7427edf6af27791593014db4f}} related to our research. We exploit first-order derivative as the criterion for data selection, whereas they use both first-order and second-order derivative (i.e. in Hessian). In the... | d | 1acfd25160c3acc17eb6dc75ce4c9caa |
Theorem 2.6 ({{cite:6d5533bdd533e3e276263133951e8102e4004946}})
Suppose that {{formula:79240957-317c-414d-9f7c-953c984ee19d}} is a reflexive Banach space with norm {{formula:e987c280-1108-4f71-ad04-d7294dac3294}} and let
{{formula:d9b19f64-65ee-4046-a954-d3b5c8b20f88}} be a weakly closed subset of {{formula:7fe9829... | r | c86b5331b8f79e82f91c74af5a267a40 |
In Figure REF we illustrate the behaviour of a MuRel network with three shared cells.
Iterations through the MuRel cell tend to gradually discard regions, keeping only the most relevant ones.
As explained in Section REF , the regions that are most involved in the pairwise modeling process are shown in green and red.
B... | r | ab5b407971d5fdeaf41fad3a44e5830b |
Comparing with the other TBOs, we notice that this TBO is a small-amplitude oscillation. In the cooling wake scenario, the behavior of TBO in the burst decay phase is related to the latitude at which the burst ignites, since the first ignition spot being the first cooling spot {{cite:b16759670fd628053673ce66b9361298b72... | d | 6c850d7895f268bc8e97b0272eaba8f7 |
For the numerical simulation and analysis of the nonlinear {{formula:b71927f6-68a8-45d2-978a-7b1dd9297e14}} -propagation
dynamics of ultrashort laser pulses we use the generalized nonlinear
Schrödinger equation (GNLS) {{cite:e812487928bb0fe843d3a137030d5f229f1ad996}}, {{cite:f9197034cd507af0ed95d3275ba5364c1efb853d}}
{... | m | ec70e31fabed3269f455865c6f2e28a5 |
While an exhaustive grid search is simple to implement, it is infeasible for most practical problems because the number of sample points increases exponentially with the number of hyperparameters {{cite:12e77a8ed74ad4504e8569964e8967597a534c3a}}, {{cite:f868c855724ab3e415c89b8c8792fe8c991c928f}}.
In order to compare ou... | m | 2f1ae986bb1b90213d5c5908a83f03d3 |
To compute the similarity between 2 or more macromolecule graphs, we used GED and graph kernel (Figure REF B, Section ). GED {{cite:f90a7e2c6397b82f8d4f082669f092194c2c1a50}} computes the similarity between two graphs by assigning node and edge substitution scores, similar to local sequence alignment methods, such as B... | r | 1441debb5222888e1b76bca30e7040a0 |
Next, we evaluate on an unseen dataset (not used in training), which is EgoDexter {{cite:d4160607beeac7bd2eb16fe241ef7e42edfbd3ec}}, to compare the generality of our method with several existing pose estimation methods {{cite:f41a58e312cbc52c16116bbe10418142f553d734}}, {{cite:3083c1a76d6326b6d2df21e78da069af043d21dd}},... | m | 0818233f82bfe3a08c53a064972e9b84 |
Building on the analogy between Feynman graph polynomials and those of electrical circuits, we then formulated a second class of parametric representations. For these, the integration variables represent the effective resistances between vertices of the simplex,
rather than
the conductivities
(i.e., the inverse Schwing... | d | b690d4fc206f32da53ffcc1057d07c3d |
The lines in the list were adjusted in order of their depth, starting with the deepest ones. For each line, a 0.8Å wavelength range was considered, unless the line had HFS components. In the latter case, the wavelength range was extended 0.4Å beyond the bluest and reddest components of the HFS families. Parameters for... | m | c025636c266d91d479d801675f7f48bd |
To further demonstrate the effectiveness of our proposed model and the training scheme, a large and complicated dataset RadioML 2018.01A {{cite:ab46048021689ce2ee7447742f4679872fc14d67}} is utilized.
The RadioML 2018.01A contains 24 kinds of modulations under an SNR range from {{formula:6f7175a2-a1ec-4fe2-ad02-eadc26ed... | r | d3c513ef8b958159d7a247b39c769fe0 |
Fig. REF shows the NMSE versus number of beam training when {{formula:0797b3e6-2f99-4eff-bcb3-d543ebb129af}} and {{formula:7f52b359-ae53-40b7-beae-7449fb90316b}} . The SNR is set to 0 dB. To show that the training beamwidth adaptation ensures robust channel estimation when there is less beam training, the NMSE of the... | r | ce4475a2a6f057195eb2320928018fa4 |
We test representations trained with different proxy tasks of self-supervised learning,
including baselines such as rotation {{cite:74908b8e8276bda369cb370b1208468f31eaaa15}}, Cutout or scar predictions, the proposed CutPaste, CutPaste-Scar predictions, and using both with 3-way classification.
We also compare with pre... | r | 475d2f69c0f3ebc842fb150287e4ec08 |
Matching problem is an important problem, and it appears in many fields such as biology information, chemistry molecule, pattern recognition and computer vision. Especially in the computer vision, matching problem is a crucial issue and frequently occur in stereo matching{{cite:ecf8be5cc04ae26b92606a92e515590b40719627}... | i | d9056b54c60ffc661156a55e817e539a |
The current unbiased LTR theory lacks the ability to properly analyze the unbiasedness and consistency of click modelling methods.
These limitations do not undermine the value of the unbiased LTR field: its usefulness and effectiveness is very evident by a multitude empirical results {{cite:c37ff46fe1b04ebbd7a7fd193ee... | d | 83e55c495f1064b4cdb93974c1445ee2 |
In this paper, we analyzed zeroth-order algorithms for deterministic and stochastic nonconvex minimax optimization problems. Specifically, we considered two types of algorithms: the standard single-step gradient descent ascent algorithm and a modified version with multiple ascent steps following each descent step. We o... | d | 5a85a135ca817f591cf45c23f51c690e |
Learning GHP from observed heterogeneous event sequences requires us to infer and align the corresponding Hawkes processes with respect to the underlying graphon, for which traditional methods like maximum likelihood estimation are infeasible.
To overcome this problem, we design a novel learning algorithm based on the ... | i | 119d25fd1b71d8ed8e0586752e9bd025 |
Figure REF shows the correlation bands at {{formula:e54d34a0-78ec-4a2a-aacf-aa67ee6dd9dc}} for the pairs {{formula:5caa49c9-2183-42f4-ab76-25fbc25ddc99}} and {{formula:b591012f-68b3-4859-8aeb-c1f5c510a44e}} in linear scales,
including only the constraints from oscillation data, for NO and IO taken separately
(i.e.,... | r | a7b650186b198f00e5d717084e480f60 |
Several works have made their attempts to remedy these issues.
DHSL {{cite:c1867cae6353238e9c325839c60ef9c5301b9b3f}}
proposes to use the initial raw graph
to update the hypergraph structure, but it fails to capture high-order relations among features. Also, the optimization algorithm in DHSL could be expensive cost an... | i | b0008ef6d0bbce8bb23ebba1afd12e7e |
Neuronal circuits in the brain are highly complex. Even for the retina, a relatively simple neuronal circuit, the underlying structure and, in particular, its functional characteristics are still not completely understood. However, the retina serves as a typical model for both deciphering the structure of neuronal circ... | i | 3e77fc2b7171f47006e62583ef71a153 |
In this paper, we present a new neural architecture called EfficientSeg, which can be counted as a modified version of the classic U-Net architecture{{cite:1db651f2ffcad977ad2c396f3af0fecf58306c1d}} by alternating the blocks with inverted residual blocks which are presented in MobileNetV3{{cite:8aa186f2a5c8677c2c586745... | m | e396ce75dfbd795aeee373356d78f653 |
Although the S-G setup has already been widely used {{cite:48a64d7b532a56d1dc353c00f65fd7f5e690d872}}, {{cite:c08fd2340d337e738b73d227f716750c50237d55}}, {{cite:31d1da4a5a3be81e74dab30c0f5b79ffb0144cf4}}, the realization of the sequential S-G setup, however, is not as easy as it seems. Extremely accurate calibration a... | i | e111cc4767466348237f02f9dcd132af |
One of the advantages of the present approach is that the density matrix captures this information in the corner term (proportional to the codim-2 area), thus explaining that the Jafferis-Lewkowycz-Maldacena-Suh (JLMS) {{cite:cdb97185f0712eb9fece8b07f929e05dfff8d3b5}} proposal for the gravitational modular Hamiltonian ... | i | cd1a38e80eb1f1c505340f9197b09416 |
We have also assumed that the quantum computing chip {{formula:0b194cc4-9316-49f5-a87e-973c31bc7ac1}} is sparse.
Our method is superior to the direct fidelity estimation method {{cite:897e1cb30008acad606496ad35f00b4ec8e52a12}} even when the graph {{formula:3ad6ca1c-ba33-4bd0-8ef8-893ce3c53e32}} corresponding to the c... | d | 574dbd412ca1566810216f07a90ba013 |
Strangely, the Odd Path Polyhedron (the “dominant” of odd paths, and the related integer minimax theorem {{cite:363182dc6a6c77f3a7a007c90bec4218b2f542ca}}, see also {{cite:3b3dfc70ba1038548e58d22c39fc3c23ce107a4b}}) have been determined much later.
| r | 288da6dd98dd890bfc99c724aca175a6 |
We have achieved the conclusion that in our theory the minimal group should
be the entire conformal group. On mathematical side the conformal group has
been investigated thoroughly from different aspects {{cite:00132a8dd01089c030cac7042b6bd48e8e5959a7}}, and its
application to physics especially to quantum field once w... | d | 14ada5f35f3697a46afdb472d493bf2c |
The simplicity and generality of the DISK framework enable scaling of any spatial model. For example, recent applications have confirmed that the NNGP prior requires modifications if scalability is desired for even a few millions of locations {{cite:d0d1dc8402f66890b89a31e1774f18ebed730915}}. In future, we aim to scale... | d | 42833935c00732941418ca4c5a1fd163 |
As a consequence, recent attempts {{cite:ce5b5f05a442c7e3f8b7c849cad6310480ef9afa}}, {{cite:81da3daf8c2c6374bcb886f58d25737020f5acf1}}, {{cite:77c3b20abb9cbddfaa3757dd464ff7824fd1bb8b}}, {{cite:4cf82af19fb075cd58c4c7ea1275eab043787922}} aim to migrate this power to real image editing by inverting an image to the latent... | i | 54030bb8c4f4ef6a306d06b957c14395 |
Although many approaches {{cite:7cdd5df27b48057d1538b07bec447612240e39ef}}, {{cite:2ed0444cd2ece43fc1caa148e08dcaa363e37cdf}}, {{cite:275646f1f07669c49a3e87b64b15cc2cc320b03c}} have been proposed to handle noisy labels, they cannot be directly adopted in DML since these methods mainly focus on classification task using... | m | d6f42a991db1fd6da8d081b7b186a744 |
In an EIV model, however, errors in both {{formula:b8eda672-467f-41c2-9ab5-da1ccca042ef}} and {{formula:998fa3ce-a91d-495e-a146-026d07d2b088}} are considered; e.g., see {{cite:c49e9240ffcc02089ad6f44d7daa5cecd781739d}}. Total least squares formulation is a well-known EIV model, where the goal is to solve the followin... | i | c03872d1e521636bc44a626c93469049 |
where {{formula:89808d11-1125-41e8-8852-aea0514b3a97}} is the number of time-steps, {{formula:9dc7bf81-06e9-47a9-b82e-43455d9b915a}} is the number of joints and the sum over {{formula:2ccd9067-fc78-4e76-bb82-df23d28b3892}} accumulates the error in the {{formula:fe0fdc03-c2a7-49de-87a1-e48865f424f4}} , {{formula:7207... | r | bef5ac330304ade0ef9a30bafd56d38d |
However, the dynamics of a large class of Boolean models does not have an absorbing state.
In the present manuscript, we analyse the stochastic dynamics of linear threshold models, formulated in terms of {{formula:c9b43bbc-b777-4fad-8e18-70a5e55b2ca5}} variables, and discuss extensions to threshold models with multi-n... | i | 9c72c2ccb9e4618aba7590ec7df3aa6d |
Paraphrase is a restatement of the meaning of a text using other words.
Many natural language generation tasks are paraphrase-orientated.
For example, abstractive summarization is to use a condensed description to summarize the main idea of a document, while text simplification is to simplify the grammar and vocabulary... | i | c41f11047ea7fb9c8b097c0b853767e7 |
Next, we study the per-user throughput performance. Specifically, we consider the following per-user net throughput expression, which takes into account the channel estimation overhead {{cite:8c7e9f5b4422d712ba31999f46ed23bf27cc5db2}}:
{{formula:25cb5b3d-2b09-46a9-92de-6313c1ae4ef4}}
| r | b1d07a418d185bcfcca42be4e28f6c48 |
Injecting node involves generating discrete graph data, such as adjacency matrices or feature matrices, that gradient-based approaches handle poorly in many circumstances.
This phenomenon could be further aggravated by the black-box setting where gradient information from the surrogate model might not be accurate.
More... | m | 61937614c99a6cf7f619a7656e28b018 |
In {{cite:eedd9674823a37415588eab2f820bcb1ef1e7321}}, it was shown that {{formula:71c20f0e-7780-45db-884d-dacef7c795bb}} has infinitely many path components for any spin manifold {{formula:f4d7ff88-a889-4319-ac37-769170bb7df6}} admitting a psc metric that satisfies certain topological conditions (explained below in S... | r | 1d8642315e4504c9d30bbf680b850586 |
Our analysis of the complexity of operators generated by the Heisenberg and SU(1,1) groups has many interesting applications.
For example, coherent and squeezed states of light are essential building blocks of quantum optics {{cite:0344eadd873f6bb8a75f2820c842a569f5540749}}, {{cite:cd3de6c45540fc52dd9c52fae72b163dd34b6... | d | 7c4518883b5a4e2ccbc3577c964e49af |
However, as shown in Figures REF and REF , these reductions in active users and visits to different categories do not account for all of the reduction in income diversity, and indicates that more microscopic changes in human behavior have contributed to a further decrease in income diversity in cities during the pande... | r | f2a1717e9fea11e5ea1849d365c8786b |
In this work, we propose to use available off-the-shelf models to help in the unconditional GAN training. Our method significantly improves the quality of generated images, especially in the limited-data setting. While the use of multiple pre-trained models as discriminators improves the generator, it has a few limitat... | d | f5c50f16492cbb8b72895a471be695b2 |
While we mainly focused on the popular IM-based SFDA methods, our proposed uncertainty-guided adaptation is also applicable to other SFDA frameworks, e.g., neighbourhood clustering {{cite:7f3e950f1c1b2c7c3d0f07a0201319556491bb4e}} or extensions to the multi-source SFDA problem. Moreover, the principles we build upon ar... | d | 8cae98eb76f6a3d5efb9b32d9448ffc6 |
There are a number of avenues for future work that extend our proof-of-principle experiments here. Apart from exploring different CNN architectures, such as those tailored to segmentation tasks {{cite:6e6ffb05de3def3301c756df2da58a21e984266f}}, we could consider other types of annotation appropriate for cell-counting t... | d | 7e22ff3dd65cedec3f32e787f93fc62f |
Mahalanobis and Gram Matrices.
We identify two potential reasons for these two feature-based scoring mechanisms.
First, although it is unclear how this can affect the detection, we note that both methods are evaluated under a low input dimensionality (i.e., {{formula:841487b4-352c-4b57-8d96-551653686e27}} ) in their or... | d | 67226d17fb097469c4c4ec5e8115d06f |
In this study, we replaced the neural vocoder with MelGAN {{cite:359936a2fe484ca9b1a2002b2ad5578faaff8b3d}}. To train MelGAN, we used spontaneous monologue speech of 361 speakers in the Corpus of Spontaneous Japanese {{cite:b9ecad30a4ff8eeb07dbad482b7ae1c73d8450d5}}.
| m | c444617723073ebd3e6dfdf8307a485c |
In practice, the video is scaled down to 640{{formula:ddd7e564-0806-4d43-88ad-412bf6e82e65}} 480 resolution to achieve a frame rate of 20 FPS. Intrinsics of the camera are acquired following the calibration guide of {{cite:906761eec3065baf30e7ea183da11d698b47a0de}}. Extrinsic calibration between IMU and camera is estab... | r | 4e1fa571cd5cbfd502a32231d069e32d |
Phenomenologically, it is suggested that the light mesons could be grouped
into the following Regge trajectories {{cite:669aac3a63138a8df159879a5e3e824559bf72f4}}, {{cite:bea025c8cf3caf2d745acd26bc7cea8b07e89abb}}, {{cite:d58af2760c6a2e62fe10c3918e80a83884b7b2ed}},
{{formula:bd82c882-2a89-4ef9-8baa-e03d5a60ec0e}}
| r | c408fc0aaf724f0e028c940171f25a64 |
ScanNet.
2D depth metrics and 3D geometry metrics are used on the ScanNet dataset.
The 3D geometry evaluation results are shown in Tab. REF .
Our method produces much better performance than recent learning-based methods and achieves slightly better results than COLMAP.
We believe that the improvements come from the j... | r | 46b58ec3f8ed68b7660a66e35fa36f6d |
As described in previous sections, we analysed four nights of observations: three in multi-order mode, with only HD 189733b in the slit (referred to as 'short-slit nights') and one night in L-band with single order, long-slit set up, observing HD 189733b and a fainter reference star simultaneously. While the long-slit ... | m | 4a68270a48156b7c6ac9b05f076d03d9 |
One usually consider the quantum systems with two levels (namely, qubits) in quantum information and quantum computation. To describe a quantum system with two levels, one can use the Grassmann representation of Fermi operators in fermionic phase spaces.
Since quantum phase spaces are some kinds of noncommutative space... | i | 92ef0eea5a95d50864021c5a448f950a |
In this method (see e.g. {{cite:559729727006e27d3d2e6ba10b99508b794f6a64}}, {{cite:b8acda884394b02190eb6e028da3ef5250749ac6}}, {{cite:57f6fe15406d625385c414ff950e3e6c7af89949}}, {{cite:016f9b3d572d3bb10412ef9b2d352511ef55fb98}}, {{cite:fa3c919144418c12a87a2279d7479f31ba035eab}}), one brings the dynamical equations into... | m | 9e45888fbefdb9286c6edb7e3746e6ab |
The class of Neural Differential Equation methods {{cite:4dfebe7b8ab1381fb66a82dc6369b48d59bb9309}}, {{cite:26999d8abf6124d7d3e3481f1db3549446655f67}}, {{cite:ecaf39a356e9e2529b8241a56fb929aa82d494b0}} were developed to account for irregular time series with missing values and have demonstrated high performance in pred... | d | de6d5345ea8b40ac0f8f62d86427ede3 |
We calculate the full {{formula:ae196caa-ed47-493a-ba90-7b122cbaa86b}} spectrum at {{formula:24d9ca2b-b36c-4641-960b-ae4cfd9f399e}} and {{formula:81154060-9e58-4e25-823f-edc4b1dc0d8b}} using the {{formula:240d0332-347c-4e7f-9094-4fbd824a5a6d}} -jet (N)LO
calculation from MCFM8 {{cite:a2ca5ddac0a6211b6d90ccd258fb6343... | r | 9bedb40ecab552ac63b65191b2e1f507 |
For the synthetic benchmark datasets comparisons, we use two synthetic datasets: the GoPro{{cite:7e0a93fdea8a450363bed8f6a82245814fe1e6bb}} and the HIDE{{cite:ed37a6aecefb8ca8da592e69ddc2ad1fdbb4960a}}, and compare our method with fourteen state-of-the-art SIDSBD methods (Xu et al.{{cite:1618dc4050100071d38c6f96753e50d... | m | 7730645ad88a5d4ac6e3381eab0fb208 |
For {{formula:476e68d8-6ec4-4d4f-9072-853a35d05919}} , the {{formula:c2759786-54e4-45a4-a040-91c6c132df61}} -stable Lévy process {{formula:8b2c3168-30a8-4989-bf0e-4560c08263cf}} has a heavy-tailed distribution{{cite:88a8b6e8b31cc14d3ad2872cd36fc8b3b29cae6f}}
{{formula:68cd0e49-7740-4022-adc9-85b83d9002c7}}
| m | 8859bd77feb7519e2f121319d30bae10 |
{{formula:0ade4118-9ff2-4223-9502-13c40ab74d2e}} is sampled from {{formula:bcf4909a-890a-4074-ae0d-541efed34b97}} .
Theorem 2
Let {{formula:8c5ded64-2aba-489d-a34b-cbd6287ae4b6}} be a sufficiently large constant.
Fix {{formula:0b78d020-51e3-4bcd-9149-2dab235d9d1b}} and {{formula:3e6282e5-7a2c-4e57-8e87-725f8aeb928... | i | ae8de1dff4cdeca36bc4fe5150cbf1c5 |
Remark 6.9
If {{formula:56b26a2c-75d4-476e-bd78-64d0e2b306b0}} is an irreducible matrix with non-negative off-diagonal entries,
then the corresponding Laplacian {{formula:e9fa1fac-b546-4118-b5d0-ad491de2cc4a}} has a simple eigenvalue 0. This result is known, but less so in our general setting. To see that it still h... | r | ade8610ed9a0920a4e586ce5bd59464d |
This section will empirically evaluate the proposed method. In the experiments, we utilized FIVE types of real-world datasets coming with distinct nature: 1) structured datasets from different domains {{cite:d34a5cfd6f3f6547fb6ef077b999bf8bbebdb1b5}}; 2) medical image dataset {{cite:5337ae10ce77e86733647dcf1ecc39a9bd0b... | r | de35ed534e1388520465c704ba187a85 |
Mask Memory Unit for Consistent Saliency Maps.
A common problem with perturbation-based methods {{cite:d2e2655007e854e60e8a11f88b6bd6cf062190ff}}, {{cite:8235e259f675ce24e1b039ba49938db467b3a0ac}}, {{cite:733a8b836c5c48ad71eb3da86b5554ff4e7a29ca}} is high variance between explanations, even given the same inputs multip... | m | 05aa29025180b2d66e1842606ec651da |
Their experiments on real-world images from the DPED dataset show that their model outperforms state-of-the-art methods such as EDSR {{cite:6121a2a0d388c660b17220de585fbbad6c7d64a1}}, ESRGAN {{cite:c25ecb9bebd0aa299ac5d41985d6bb12370f4b04}}, ZSSR {{cite:8866ca7e29d97af45be24075c7c76faa9b725f3b}}, and K-ZSSR, resulting ... | m | bb02f6b16eb23a10092744b4ca3e8789 |
The proof of the theorem can be found in, for example, chapter 3 of Ref. {{cite:9c4600c5d4987c529c1b0d198d089e37aa3b57e4}}.
| r | 25284ffb0a33c247327649889ad823cc |
The structure of multipartite entanglement is far more complex than that in bipartite systems. There are various inequivalent entanglement classes {{cite:8a13ce64fb8726f8a5dc9e6365842e5aa6f2eff3}}, {{cite:923ceab185a6a52907389d262ff4b27f3c55d3f0}}. There are also such peculiar properties as monogamy relations {{cite:9d... | i | 7ba170ba1283c02207eea4c394a2a22a |
In our work, we consider the same LQR setup as in {{cite:ba7f48697fbcdbde7126233207e997354d95df57}}. That is, we also consider a deterministic policy rather than a stochastic policy, a randomly distributed initial state, and noiseless dynamics. Note that it is known {{cite:2bf776cff3d5637aa95179870544f91d86507280}} tha... | m | e5587abcd47ab9ec3a1aab4d3f00b966 |
{{formula:d36641bf-bd2c-4a0e-b80f-64eb5fa60852}}
Base: Minimap2 {{cite:bc6f87d020c653c85947c911657c2f1461b78f2b}} is a state-of-the-art software read mapper baseline for both short and long reads. GenCache {{cite:0d892bb6d56b93b852bfbaef6c0d30f35b478422}} and Darwin {{cite:9e3ded56a8c953edc536d51448ce7cea30c9d835}} are... | m | 2d2689e6ce3055b0cf4c65d2165f7b5d |
In Tab. REF , it shows the PSNR metric between cover images {{formula:4fbb79f6-b391-4614-8fc6-ed47e6075a30}} and watermarked images {{formula:9b78de16-05e8-499e-8d96-a3d81aa5eb9c}} produced by 6 specialized models against the corresponding noises and 1 combined model.
Moreover, Fig. REF illustrates the bit accuracy ... | r | 2fcf9ff0d9315aa702974590a2b4f821 |
Even though this methodology can be extended to any nonlinear elasticity problem unlike {{cite:2b8686fd50d9800e0d89614fa9182d9f5b577f83}}, for the purpose of simplicity, we have limited our explanation to the scenario of truss undergoing small deformations. This problem when formulated like in {{cite:014c3ab12401567905... | m | 587e9a6b8a037d89ad52b788f22ab92f |
First we recall the semidefinite program for finding least Euclidean distortion
embeddings of finite metric spaces. Suppose we consider a
finite metric space {{formula:4d62f976-4ad0-43d2-a68a-a0fbed027128}} with distance function {{formula:37720972-b68b-40bc-ba2d-a873a2a69a24}} . Then, as first
observed by Linial, Lon... | m | 2165fa6b05c03116bf8138da52c7309e |
The survival-incorporated median is simpler to compute and requires fewer assumptions than the SACE. Aside from the monotonicity assumption described in Section , identification and estimation of the SACE require additional assumptions. {{cite:df2e6c48f27482c7b346183336ecf268c0eed6f2}} assumed that with a randomized se... | d | d5c3e53a70dd3f2f02f6ba079734ea8f |
Sharp video reconstruction is an ill-posed problem because there are infinitely many motion trajectories whose temporal averages correspond to the same blurry frame. To compensate for the ambiguity, previous works {{cite:046f83fbbc2868e1c8e9e15181a776f9b762cdda}}, {{cite:17a05f21c72d0b783481068ae9576898d0f49c5b}}, {{ci... | i | e043fc9d21f34535cae1683b4b5a8199 |
Recently, deep learning-based methods have been applied to automatic retinal blood vessel segmentation and have accomplished very promising results. Although the vast majority of existing deep learning based methods for retinal vessel segmentation employ UNet{{cite:8031680193484383a2d622fb7c5c3229ab452ced}} shape netwo... | m | c448e1d2dd66d8c2a47b7cd115bd6681 |
Effect of high-frequency adversarial learning.
In this experiment, we show the effectiveness of the proposed high-frequency adversarial learning. For the generator network, we use the 3D U-Net for standard adversarial learning, and frequency-supervised synthesis network for our high-frequency adversarial learning, as s... | r | 9bf5fb8db44a9e84b2ff0a34d8e88989 |
Several methods that treat the rotation of nuclei have been developed.
As a microscopic theory, the cranking model {{cite:5c0050f392c0c0927d15d407bcdc6066c17bfbc2}} has been proposed.
The Inglis formula {{cite:b7244cc8972c84c99b336227d433686d26a4ada0}} and the Belyaev formula {{cite:cfcf19224a00b209a5a818579c97654b957c... | i | 3da5ff9eea362e213537a653f8d72cc0 |
The common neural network architectures that achieve the state-of-the-art results usually have tens of billions of trainable parameters {{cite:bea37ad128a79853241d9a45a3ba230c813e60e3}}, {{cite:22da8a6e1797df320d57badca79c76fefae94fb1}}, {{cite:c784f1091f7daa32d11a1835e18f384b79a1142a}}, leading to a problem that train... | i | f642d7222fa64ef6643748d734057f3a |
In Fig. REF , we sketch the phase diagram of two-flavor QCD in the
the {{formula:5fcaeb7a-a9b0-4b98-b658-5966a558d94b}} –{{formula:06a1f322-07cb-44e7-ac7a-6fc8354d2f42}} plane. In the lower left region, we have the hadronic phase
where chiral symmetry is broken and quarks are confined.
As the temperature increases, on... | i | 20f5f2ace81a2624183dc050187d6578 |
Along with the increase of the count rates, the model above is also attempted to fit the obsids with count rate {{formula:6958a72b-e06a-4ef5-94a9-3fda390fbc46}} 40. However, the parameters derived from the above model is unreasonable, e.g., the blackbody radius {{formula:241b6dc8-6e27-4611-9b28-3bafef0f1a8b}} is much... | r | 9940c095337facfb8d994db5e56c9fe8 |
A number of RT investigations focused on the K i D lines were carried out in the past
{{cite:9ed6236672aa9b68069c35a0eff1f32eca4375eb}}, {{cite:8beb681c3b9afa1b242a4360157610f17f1a58c2}}, {{cite:0128685aeaf9fbe2e3d76f42e8d4cdac34db6d3e}}, {{cite:d96254380a957b0798a992d46f914d8f1809ce84}}, although they did not take sca... | i | 50a1694a16e0381cff5c382885bde9c3 |
For agents with equal entitlement (and additive valuations over chores), we show that allocation mechanisms not based on picking sequences provide better approximations with respect to the APS than those achievable by picking sequences (for which we present a lower bound in Theorem REF ). We consider algorithm AlgChore... | r | 545bf02864d9efe7b45e6eae4ebc6f58 |
Nevertheless, a ML-based NN has a few advantages over the existing pipelines that warrent it future studying. First of all, as multiple authors have pointed out (see, e.g., Refs. {{cite:e8f72f4f8020c2494e4743de18747885170208c5}}, {{cite:144ffcf336e97a8640d8d9d830ee728cf54215b7}}, {{cite:8903bc8d869280d9acada325227c2d8e... | d | 16a9404e985605d08dafba383a837299 |
Pre-training is also a realistic assumption. We have argued that application domains (e.g., computer vision and natural language understanding) have vast amounts of curated data and increasingly available pre-trained models that CL algorithms could readily exploit. Additionally, we demonstrated in sec:expmimg that pre-... | d | 7fc108204ff730254c904e72c3b4021e |
Figure REF (right hand side) shows results of our numerical scan. The ic86 event rate is plotted against the mass of the dark matter particle. We see two groups of models: The lower group consists mainly of models with a large mass splitting between {{formula:2ff90c9d-8531-4fe4-a20d-3fb522913b2d}} and {{formula:0bcaa... | r | acf5819272009a12c7e5c4802de8c0ab |
We have interpreted bursts as a simple combination of pulses, without taking
account of the temporal variation of the Lorentz factor {{formula:6b43bd7d-8185-4636-9323-d0513da91b92}} of the jet.
If this is accounted for,
each pulse may have different {{formula:4c9598a1-de18-454e-a03b-5fee9bed29f6}} but the same
{{form... | d | dcc690efb30d384c58cac346e86c7f21 |
This section provides details about the three major steps in the proposed accident detection framework.
These steps involve detecting interesting road-users by applying the state-of-the-art YOLOv4 {{cite:c665eef45e55ae6ff7998a250eb012eaa877c775}} method with a pre-trained model based on deep convolutional neural networ... | m | 430d8dfb92cdd521f7ab0ceba1556744 |
The {{formula:58269b9e-3f88-42e6-9454-e0682f65fb95}} parameter is measured to be {{formula:5baed2ab-6a79-437d-b51a-34cd4ac73fff}} , consistent with no direct {{formula:d37f78b6-eaed-4046-b315-db975382289d}} violation ({{formula:a0c6fe70-37f0-4a71-b14b-b0925c676259}} ).
The average of the heavy and light mass eigenst... | r | a3101dc12b6b2253aa0919093d48a1ba |
In the modified nonrelativistic quark model, we determine two parameters, {{formula:ab0d3425-ffdf-4e2a-a56b-f65ea44e225a}} GeV of Eq. (REF ) and {{formula:6c01c5cc-4532-4932-9034-0e64f38c0820}} GeV of Eq. (REF ), by fitting the masses of the bottom mesons {{formula:f3a279f3-d76a-49d6-ba21-1fc3ac32faab}} and {{formul... | r | 63deb73a276662b68465082564b5a0f3 |
CVD growth of graphene on Ge (001) and Cu foils. We use two preparations of graphene: graphene that is grown by chemical vapor deposition (CVD) directly on Ge (001), and graphene that is grown by CVD on Cu foils and then layer transferred onto Ge (001) or GaAs (001). For CVD graphene growth on Ge (001) we followed grow... | m | 65c707102f03e5606695d041baca9d18 |
The extracted knowledge will then be incorporated to a downstream task for better recommendation quality. Our downstream model is aligned to the production deployment, which includes several effective components such as target attention, search-based interest modeling {{cite:9dac5777548f3dd56c758e1db4eaec754c9d2063}} a... | m | 408dd73d68ede24d16e6f6d8e9d3e994 |
In this section, we discuss empirical results to validate our theoretical findings. First, we compare the Gaussian predictions with the output distribution of the nodes of a wide stochastic network. Then we report the results obtained by training a stochastic network on MNIST, and on a binary version of it, with PAC-Ba... | r | 1ddc57417d4be7b81126bb961a8d7084 |
For {{formula:c94c5c73-db55-45d3-ac78-4a3ddae04809}} we recover {{formula:e23fb481-ac56-488e-a2dd-c1e68716a845}} as previously described. For {{formula:ae0b257a-249b-475a-9f54-69fb5aed8195}} , the term {{formula:7a99e736-8223-4393-9b05-379a6def29c2}} will dominate for large {{formula:31585640-caab-41cc-bd49-9bbe75e9... | r | 212ee22eae494780ef581b0dd9198e00 |
To show that, we use the following change-of-measure inequality, which is also known as the transportation lemma {{cite:5200e243eeb727b751747c4221a62a7f06dac3c3}}, {{cite:5a6c380dcbb121cb866f901dd0c2f9919d16964d}}, {{cite:99a4f7e27d380765561e40ffcfdfb3a8bf8c8da7}}.
| d | ac15afaf227c8269860c2fb0ab2aa873 |
Fig. 2 illustrates the outage probability versus the CSI uncertainty level.
As seen from Fig. 2,
the outage probabilities of both “CSI/Nonrobust HWI of {{cite:a5530f5a44a826be9bc578a2c64d14f850c765b8}}” and “HWI/Nonrobust CSI of {{cite:03c5bffc0436a6a77ecfafdea4256c24ebbe9202}}” gradually increase with the increase of
... | r | 851ffccb4333640cd3877e96a0e242a0 |
In this work, we present a novel one-shot GDA method, i.e., DiFa, for diverse generation and faithful adaption.
In terms of faithful adaption, we consider both attributes and styles.
For global-level adaptation, we define the domain-gap direction as the difference between the CLIP embedding of reference image and the m... | i | 62064005f43d9915dcc09d5d016539ea |
This investigation is an exploratory venture into developing and applying deep learning techniques to tasks involving digital signal processing, specifically for the selection of digital filtering methods. For the task of removing noise from ECG signals we investigate the wavelet filter, as proposed by various studies ... | d | d7c4f96ff01763608635a17dc223a1fa |
For the models with dropout, we use the uncertainty methods described in Gal and Ghahramani {{cite:21b9c2f845517f8a31d87eaf006c34c1651c4ce2}} to create the spike and slab prior setting our dropout rate to 0.5.
The target models which use differential privacy are optimized using the default DPSGD optimizer as described ... | m | 12ff9966ae6e5740269450601f4bdcf6 |
For CIFAR and Mini-ImageNet datasets, a modified ResNet {{cite:e5d660adc35a70db662e828aaf269e822656be7f}} architecture is used, which is 10 layers deep and has fewer number of feature maps in each of the four residual blocks ({{formula:93c35786-8927-4154-803a-9601b40f72f4}} ). This reduces the number of parameters from... | r | 548b6bafb1911a1197e800ced19eebf4 |
Recent directions in segmentation include weakly-supervised semantic segmentation {{cite:2245d611bf34b3b975fe2b831f1a876b59650d98}}, {{cite:e15492e6f16bbec9dda029103e760ab35009efd2}}, domain adaptation {{cite:9dbd238de26f2c13ca1c077128592feffa457575}}, {{cite:047ceee96551193e7f6a4b70ceefe3af3e8ea1dc}}, multi-modal data... | m | 21765b98bca5d2352e5e40ac2a8822a7 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.