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A fundamental solution is an operator-valued function which can be found with the help of Laplace transform technique.
Let {{formula:a23090ea-b8ed-4e05-9741-12b138555df9}} . Then,
applying Laplace integral transform each side of (REF ) with unit initial conditions and using integration by substitution formula for opera... | r | 26c4c53e6a9fa9c2a5ecc47033553564 |
Despite being seemingly a minor change, LDET demonstrates remarkable gains in open-world instance segmentation and detection. On COCO {{cite:0b83d82126ddbb27485908f4e8ccf32a37cb6258}}, LDET trained on VOC categories improves the average recall by 14.1 points when evaluated on non-VOC categories. Surprisingly, LDET achi... | i | 830ec207fbade9e9afaa781902ef4dc2 |
For dimensions {{formula:2e7cd601-ae49-4817-9f5c-7b0d541e8a4d}} and any particle density {{formula:6e5bbd3f-c2db-4f13-912d-a3043e655d1e}} , the excess particle mass density {{formula:b780417b-6bd3-44c3-a324-f48f14c4d7db}} is interpreted as the density of the Bose-Einstein condensate. One of the most prominent open pr... | d | 21bcf131eddbe008fec1fb43720605f2 |
A sweet spot of the bias-variance trade-off is to perform TTT while remembering the training data in some way.
In deep learning, this is usually done by initializing with a trained model for SGD, like for our paper and {{cite:7b51f35fa4865077dfc0314b49ac8ad5d85e41ac}}.
In this section, we retain memory by using part of... | r | 8008434cfa8cfb4e0e13fae9708c7465 |
The number of AI systems put into production has steadily increased over the last few years. This is because advanced techniques of Machine Learning (ML) and Deep Learning (DL) have brought significant improvements over previous state-of-the-art (SOTA) methods in many areas such as finance {{cite:9967b805fcf718a913e5c9... | i | 153d6f27b3da6da88d585610d8df2a4c |
We evaluate our method, delft, with glove embedding {{cite:7eb6109e51d3dc3389deede52212f1362c8d9d1a}} and bert embeddings.
{{table:657f29cf-9bd1-45de-90b2-504417e45d84}}Implementation
{{table:4abfd39e-1514-4594-a1d9-5c70c6792578}}Our implementation uses PyTorch {{cite:10d81a13b6f222941bf8069ade5f53a0913ee7c7}} and its ... | m | 30509e23a934f42de1da9f5771c35e48 |
Recently, multi-task neural networks have shown superior performance to other individual neural network architectures on different medical imaging applications {{cite:252ce3c55f813ca499698f9c952dc50c9cddc4d3}}, {{cite:e73e8f7982b17c8879695f23d5c159f2066a8e3d}}. This type of neural networks simultaneously integrates dif... | i | dc71630ca02b500075c3e8139cc23ec5 |
we can readily factor out the logarithms in the binding energy out of the integral, yielding a contribution to the radial action proportional toMore generally, within the realm of the PM expansion, this is due to the fact that the pole from radiation modes in the tail effect is accompanied by a factor of {{formula:17d8... | d | 9a0a7f73d9fe0b509a16e60efd3f6cb3 |
The investigation discussed in this paper could be further extended in several directions. Previous studies have shown that different kinds of networks, such as directed {{cite:ae48c0f2286dc9680187404c2b93db0e8ce2d84b}} or non-normal ones {{cite:954fda75bb28c59b22d3782de4ce91ae70a373d6}}, {{cite:e30d593ab65fa81cc2aca05... | d | db8ea5da45fa4b74347b02c70be5d051 |
We conclude this section with three preliminary results: the folklore sampling Lemma by {{cite:5a696d596f0e03df7d2642cd101ebd774b1c8b7e}}, a combinatorial Lemma we derived from the well known Hall's Marriage Theorem and a graph theoretical result from {{cite:ff11e6d74c40017a6029a568c1021da97f9e5655}}. While the first L... | r | 8b1280d4e0f3919db759b046708eb691 |
In order to corroborate the conclusions of our DFT-rVV10 calculations
and better elucidate screening effects,
we have also studied some of our systems by an alternative approach, namely
the Self-Consistent Screening scheme (SCS){{cite:8a79d679d9ce8fdb79cb48e224b895329b80286a}}.
The SCS approach maps the dipole polariza... | m | 2a48e27f02a056821ca3a6a91122c25d |
Outlier Exposure (OE) {{cite:f742a4a5714b034cae7963353160cf0e3428b85d}} corresponds to Exp{{formula:2959e90c-29ce-4561-ba94-c07a855ae2d1}} in Section REF .
The results show that using OOD in training with this mechanism can gain an advantage beyond other baselines.
| r | 7b21a72756f991ccf0a36fef770000fc |
In the early studies of Poincaré series for gravity {{cite:0c1065503f396561311998ca3862de176aa8adaa}}, it was assumed that the “seed” for the series is the identity module, corresponding to thermal AdS{{formula:be6d1633-75ab-48f3-b9ce-1f6966900ca3}} on the gravity side. Later studies, notably {{cite:20df17f568c2aef35a... | d | 1adafe3c2b46d2d5983b88f94f0019ca |
Lemma 14 (Chernoff bound for Bernoulli variable {{cite:9136671d0b712488abe2bb8f512bf917d188cf24}})
Let {{formula:324e239f-d80a-47dc-8357-06abc9536b36}} be independent random variables taking values in {{formula:14e33774-6f7f-4fdc-804b-6c56ab7c1b28}} . Let {{formula:cdcd941b-7834-41f1-bd6e-32d481de1ff4}} and {{formul... | r | 0654c37c530e68515d5c3b3704c3204a |
To solve this problem, many recent works focus on deep neural networks with hierarchical structures to model the conversational data {{cite:95e11061049f47c73ed29c4798282af3615d7983}}, {{cite:0f8570d1dab1427a9153e1c8240de28bbcb8c2f1}}, {{cite:6096303146b1e06f58fbe1aceb7129cf97f121dc}}, {{cite:48ac74c6f7ae6f23786f387b74b... | i | 88b83d0abb56a4bb1da1a71669d5c3e4 |
The landscape illustrated by deep neural networks
A comprehensive understanding would help understand why the parameters do not stray far from initialization in the case where a 0 training risk solution clearly exists, but EMC is below data complexity.
How do redundant parameters in deep neural network help in learni... | d | 7e5f6243445e810b51a9ee252024f6c2 |
Recently, we introduced a novel synchronous technique called Anytime
Minibatch (AMB) in {{cite:3e3641bb324754b75e4bf70cdf1f3fed4337b875}}. Our main idea was to fix the
per-epoch compute time across all workers rather than fixing the job
size as is typical. Since workers progress at different rates, fixing
the compute t... | i | 7414adf94735ef9d7309ab7bcece6416 |
Flow-based models {{cite:b19dd15db1c2fc9358457b9ab90a1784854c2079}}, or normalizing flow based methods, consist of a sequence of invertible transformations which can convert a simple distribution (e.g., Gaussian) into a more complex one with the same dimension. While flow based methods have not been widely applied to i... | m | 643bc01bb7e610ed310646f51c830760 |
Social media provide crucial data for understanding how large audiences perceive and react to events {{cite:b0c45cb5fa30f97b2288920884f4444329863cd8}}, {{cite:88f42bb171339cd00951fe82037ca51725e633bf}}. Past approaches used social media traffic for inferring electoral outcomes in massive voting events {{cite:3dedd232d7... | d | e83253081d98bcac23f00f665f67e988 |
In our experiment, high-order harmonics are generated by focusing a 30 fs IR pulse in a cell filled with neon gas, resulting in the emission of an XUV comb of odd harmonics of the laser central frequency. The central wavelength of the IR field is chosen so that the 39th harmonic is resonant with the 2s2p resonance in H... | r | e41d1a42e1cf2a1da8939124d50b04c5 |
We also emphasize that, in practice, it can become a storage problem that the BFGS method stores the Hessian approximation as an {{formula:e878039e-68dc-4aa1-94f4-2916e89d2370}} matrix.
For these cases, there exist limited-memory variants of the BFGS method (L-BFGS) {{cite:c79cedd285ce7824a23b2324cac625ae902ab901}}, w... | m | 2f70113aae2a626709de70606708570f |
Thus, for a system of {{formula:39536c70-75c1-419a-861e-7f96a7ef8c45}} point particles (positions {{formula:1c344bd3-3390-4113-a7ac-b7df355d0e87}} , linear momenta
{{formula:55bd146e-4bb9-4a7f-884b-79ba19170116}} (as usual, dots denote time derivative), {{formula:140792b8-e7df-48c1-bc58-d66eb9670b2f}} of {{formula:0... | d | 8405c43af0b32dbe71320d411f122267 |
The distribution function {{formula:21499842-83f3-4e6c-aa46-fad507e92f84}} determines the polaron shift
{{formula:b5a8d12c-e6c9-4e21-911d-000036d893dd}} defined in Eq. (REF ). In the lower panel of Fig.
REF , we plot {{formula:2ffdb278-056c-4d3e-ac5b-6d1e1dbfd444}} as a function of the particle density
by using diff... | r | 41de40302b31e5473b199a3876ad138d |
Bi |wii|p*s1dx)pp*s1 c 2i(N+s1p+p-1) 1p-1 (
Bi (wi)p dx)1,
where we have used the relation
{{formula:029f0ef5-aba6-4e7f-b68d-777e2a650129}} .
Now, we estimate the left hand side term as {{cite:33516d5cb257d8332d2bca07154b88928e48e7ab}}:
{{formula:47dbdbf2-180e-4b7b-b219-fb7511cb0d4b}}
| r | 9b27680840d82a254c73768537e91702 |
From the aspect of applications, we can easily adapt the protein embeddings learned by S2F to other protein problems, such as protein annotation and protein stability prediction. For future works, it is possible to use the high-quality computed protein structures from AlphaFold2 to increase the multimodality data size ... | d | ccbf00794eb66e013e9bc7e27d3ed8c0 |
A value for {{formula:25ed730a-0f46-449e-8d58-d1d2a5a52fd4}} has to be predetermined for use in {{formula:ddcb755a-231e-4813-ab8e-5148bb2af0aa}} -means. Traditional indices for calculating the optimal number of clusters for k-means clustering, such as the silhouette index{{cite:a29c7037eb9f994f9f287a5965b260ae83bbddbe... | r | 4a91640eff1333c0d4e5c2bf56b05321 |
Related to the problem of generative modeling, our model does not incorporate sampling into the learning process.
Generative variational models use sampling during training to regularize the learned latent spaces toward a simplified prior distribution {{cite:4e788fd628499381b0bd7805a907040da5175cbb}}.
As there were no ... | d | 34b750b94f0ce6718356ad844761af28 |
To justify the proposed benchmark FedChem, we compare our results with MoleculeNet (MolNet) for centralized training {{cite:17da75fa2e39e7bdd6731b212fc16552121b8574}}. To validate the effectiveness of FLIT(+), we compare FLIT(+) with Federated Averaging (FedAvg) {{cite:825d6fd5e543e918b06420287acb993d6dd4a462}} and Fed... | m | e64d32040365d43c73f14bbdeb120c9a |
In conclusion, we hope that the results from our present theoretical investigation may be helpful in understanding the nonlinear
phenomena in astrophysical compact objects (viz. white dwarf and neutron stars {{cite:9e46c83a9765763e2f182a06b22601c331a3eaa9}}, {{cite:845854db48cd9eccc5ffb79683ddc333cc1a6fec}}, {{cite:6d9... | d | 8d6896e146c201904a524380863a3803 |
We now show that ultracold Bose gases of {{formula:93ccb328-d89e-4522-8e0b-b8db8dc3f860}} Rb atoms are a candidate for observing the predicted atomic-molecular vortices. By initially using a large atomic BEC of {{formula:3b870831-6bfd-4372-9969-39df62269b13}} Rb (the atom number is up to {{formula:7bd9ef53-99dd-48ef-85... | d | 1a91e5bce5c4c1bdbd59237770537d12 |
Smart voice assistants have come into our lives. At present, many smart devices will integrate smart voice assistants, such as Samsung's Bixby, Apple's Siri, and Microsoft's Cortana. These smart voice assistants can provide personalized services to users by recognizing their voices. Automatic speaker verification (ASV)... | i | ce251d5b5581c5da5863ecfad9d17e43 |
Limitations.
The proposed method for building models with better generalization is only a partial solution since it requires an external model selection procedure.
New methods for model selection {{cite:dbecb567c243986c988344171466fe2086705dca}}, {{cite:0076bf333934dff26087c4d898eaa6e0ffa92cc5}}, {{cite:0e5d8d954832ffa... | d | eb16a5b412dae6061f613e44d4749e7c |
Lemma 2 (Hoeffding's Inequality, {{cite:0709b88a080a9c1ccb86a2516a9c32e61cebd4ba}})
Let {{formula:b5ed2997-0101-40b6-81f1-9bce11adc420}} be i.i.d. random variables in [0,1]. Then, we have,
{{formula:a8d7be03-aeaa-4a36-ac8d-4ecd95874815}}
| r | 88a5cc7918445a339f897b307f017902 |
Most of the existing BED studies focus on the explicit models {{cite:6ba7dfaceaf69b316d49346a3590c331cab61bb9}}, {{cite:0e8f76b98e91236d1960d69e766e69de2311d80c}}, {{cite:d9dbde520ebcddfc881b3daf67536bd10711be44}}, {{cite:2e5211ab92cf38ddce29b37cf9c465db37cd0f04}} in which the likelihood is analytically known, but in n... | i | e11f36c3c1fb988f79ce9b2ee730853f |
At each iteration, the communication cost includes the broadcast of {{formula:7ceadeb9-d49b-4fa3-86c8-870804e9e815}} and {{formula:1bc6e396-bfaa-4764-b757-f8d0e48c42d9}} to every {{formula:dd096878-f090-4338-8485-6d7969daf98b}} and the transmissions of {{formula:c4195db0-0f91-40d7-9f85-096ab529c267}} between neighb... | m | 6d981cef40e0727597e33e897b64784c |
Theoretical analysis of policy gradient methods has a long history {{cite:8cdfe57b42f197f7830e2dac9d65ac3202ecbe9b}}, {{cite:5b28969645c7ee2e9ea4c77c5c1d2b07f0a07daa}}, {{cite:494ec34932ca2b4abe472b994fcdef8ce92c5fef}}, {{cite:a55e8367c802e7d7e204257ec12ee03e775a049d}}, {{cite:ec1960e8269150952e30a7e7edc6240fc481004a}}... | m | 033400988c3ca3a2ac5d5fa8ba384d13 |
We have established a variational formulation for the role of depth in random neural networks with batch normalization: The entropy of hidden representations increases with depth up to constants. Is this entropy increase achieved by a gradient flow in the space of probability measures? This question is inspired by the ... | d | fc3d941f0245e14449bb872e1abc837c |
To handle the black-box constraints, we need to modify the acquisition function to show improvement only when {{formula:81f91a92-cac9-4c5e-96c9-4e0e14976828}} holds. Similarly to the objective, we model the constraint function {{formula:4fe1e10d-4b85-4eac-8deb-142f7bfe9cfd}} with a GP prior whose evaluations are corr... | m | 921279c012018c762cfa7fbfa1956b3f |
Block ciphers should be designed to resist all classical attacks. S-boxes are the core components of block ciphers. The primary purpose of S-boxes is to produce confusion inside block ciphers.
Such S-boxes are nonlinear functions over {{formula:84255e03-0e1d-4b82-afed-33c43ea5132d}} . Such functions should have low dif... | i | a0a1d0206fcdb6c08acb83a2379e5369 |
Different constraints are contained in the matching-based methods instead of using traditional stereo matching methods. Heber et al. {{cite:31c489341aec78ae8e73a01f084f784df51513df}} estimated the depth by matching the central view with other sub-aperture images, but they didn’t use all the sub-aperture image pairs. To... | m | b7d0c3e6c46473024097c92956859826 |
Here, the CNN parameters {{formula:65aacb78-4966-41ce-b4e2-c11e0023a921}} are initialized with random values and are optimized such that (REF ) is minimized. We note that CNN models often have high representation power; they can represent noise when trained with adequate epochs. Because the measurements {{formula:2845... | m | 886836d12b9e93798cb454d02787d5c6 |
Using frequency domain decomposition and residual connections, {{cite:4dae6b645b624326063bcd16d98be820dec2dcd7}} first employs a three-layer CNN to extract rain streaks form the detail layer. Thereafter, advancing network modules are introduced, such as residual block {{cite:1e4b528efc84eeb4512d5c70cf0cb7616530c575}}, ... | m | dc178d39c5b8d3c3d265cdffa4a9d379 |
Separating.
In terms of sample complexity, Corollary REF gives that a generic max filter bank of size {{formula:535ddae2-81f5-464a-bbca-a0bc238ae50c}} separates all {{formula:1d4cb5ef-fcb0-4bc7-a2e8-1033411b0e49}} -orbits in {{formula:1d010072-3852-4412-ae40-243812cc052f}} provided {{formula:9a8b4d6b-efb5-480c-a5a7-... | d | f7f12f7b3035bc654789406b6598b911 |
In this work, we show that this simple method can be a very competitive baseline that either outperforms or is on par with most state-of-the-art methods on two popular benchmarks, (DomainNet {{cite:102ed3b60a275ba7a703ec2f9f4d22a6d603e56c}} and VisDa-17 {{cite:1ebfc7ad8810ee04fc2bfce2e216feebaa8defe9}}). Note that most... | i | 836d00d85336b513b064a53431bfd598 |
Blind demixing with multiple brain graphs. fig:brain depicts the rate of successful recovery using up to five different brain graphs corresponding to different people. The graphs belong to a dataset of six undirected graphs of the human brain, consisting of {{formula:27a5e093-d666-4430-ad62-2b9982f6234f}} regions of i... | r | f11c7568c3f3d5525b39f18f6f030225 |
To validate the effectiveness of MAE pretraining for the transformer denoising model, the following state-of-the-art models are investigated: REDCNN {{cite:f31d3fe6a651a1e53ade2dd9bafee6fbda25a7db}}, MAPNN {{cite:00154e1f95131de3a31c1c30341360f936de4da5}}, and SwinIR {{cite:c95e5c000af5af31dfd5347d4d94692dfe8ad5f6}}. P... | r | f420af421281a852ab2cb0e0b3e2232d |
It is well-known that there is a relationship between an asymptotically hyperbolic Einstein metric on a smooth manifold and the conformal structure on the boundary. The research has become the main theme in the study of conformal geometry since the introduction of the AdS/CFT correspondence in the quantum theory of gra... | i | 4a7320be25183472124e248c429858bc |
We note that this result also begins to give us an explanation of the criticality hypothesis vis-à-vis neuroscience {{cite:f4453718fbe48cbe2ab2cef9eb0f0ad90e59c17c}}, {{cite:6a288db8c7896666984f94fa260721c515c84efb}}, {{cite:205c2753e0e69bfd96f5983cff1811bf6212499b}}. That is, at the critical threshold, with the emerge... | d | 1b551445c76c4ae9422af06c28757e2e |
Towards an ultimate visual object classification, this paper addresses three inherent handicaps of supervised learning approaches. The first one is the dependence on the availability of labeled training data. When object categories grow in number, sufficient annotations cannot be guaranteed for all objects beyond simpl... | i | 483395bc52da689c73890426094100d9 |
We compare our proposed FairReprogram with four additional baselines,
and we show the full results with variance in Tab. REF .
We further compare our method with MMD methods where {{formula:d84114d6-7936-4618-93f8-cf5090d40942}} in Eq. (REF ) is replaced with Maximum Mean Discrepancy regularization {{cite:92fbb54dd140... | r | 9cecbf86c19eecb1be6311d131f2c0da |
The numerical results using a Julia {{cite:b0b5ed7f50d77e58e194c0a2ee7da1035cb17196}} homemade code are summarized in the following figures with {{formula:fabb9a61-73f5-4a3f-af1a-5150b32236d0}} , {{formula:0d7f47c0-6009-41f7-81a2-1150d36671e8}} and {{formula:ee1f974f-dae2-426b-bbc2-1b5f9bdfa8ab}} . The atomic PAW func... | r | 7e17f70d82af8f82411d4b1c35ada0ad |
Style Discriminator
We employ a Siamese network as the primary discriminator for the GAN. The function of the discriminator is authorship verification – taking in two pieces of text and identifying whether they are by the same author. We select an authorship-verification approach for the discriminator over an authorshi... | m | aba4dceabe89d86786076456c1d1d32a |
In this paper we have discussed a generalization of the notion
of the quantum operations and the quantum time evolution.
The generalization depends on extending the linearity of quantum operations
to the quasi-linearity condition.
This condition is motivated by the appearance of such operations in a
“hidden” form (e.g.... | d | 1713396a4057dcb09935b3cf14292971 |
The structure and properties of the toposes {{formula:947b57f3-8ea3-446b-8b78-1468e282d1e6}} remain
mysterious for the moment, and in future work we want to explore which kind
of properties of {{formula:0c8dbfd3-e2d6-44a7-a09d-d3a2cad1b4a2}} are reflected in {{formula:02e70fba-facb-42c1-8769-287ad07fe613}} . In the s... | d | cc0dff5f24f06c6001345a7ccb635d5f |
Tab. REF compares detection measures (mAP, Recall, Precision) and tracking measures (HOTA, ATA, TEM) in the case of six sequences extracted from MOT17 and MOT20 datasets for for two detection sets of Faster R-CNN {{cite:03a17e3aeb73d93b96ccf3fe5abd53a0207f67d6}} and the SORT tracker {{cite:1935a603f494c4e6d10dfa8c31ce... | r | 87386947cdb879e842e47deb810b5f7e |
Table REF presents the performance comparison of our proposed system with several prior approaches for the three experimental setups (i.e., Exp 1, 2, and 3) described in Section . The results are obtained using the combined system that utilizes the ResNet model with the statistics pooling layer trained using the trans... | r | 1ac473694d7932f82c1b476baeeaf50f |
where {{formula:18a6f9f5-5af0-4986-a36d-7751780c9ed9}} denotes an under-sampled Fourier encoding matrix controlling the acceleration factor (AF). {{formula:67dd3447-986e-4dc0-8777-bc09cfa67cd4}} represents the additive acquisition noise. {{formula:ed427dc7-0978-4299-a40a-524d95d5ca0d}} and {{formula:0291ad7d-e9e6-48... | m | 733b09ddd05e075c571399dcbf63b84e |
Here, each {{formula:f06c12a0-4ea6-4889-b16b-434b36e399c6}} is a number {{formula:10f54430-219d-47b4-842b-59b4cea6be88}} -matrix, and {{formula:0afafa36-299f-4398-a6f3-ad9d3550bb8a}} is an
{{formula:097e09fd-0d5c-42f8-a1bd-8d3edd21257b}} -matrix-valued function formed by scalar functions that are of bounded variation... | r | 03699ee3726a03db721f4edb034cf254 |
For the model architecture itself, we use stacked ResNet blocks with convolutional layers {{cite:96ea4baae6ed612d66bb6e80e7e71ff3158b3c64}}. CNN-based architectures have proven effective at natural language tasks including sentiment analysis and question classification {{cite:34526a73bff2ace5ba81ccfcaf6f023808d5a721}}.... | m | d23fcb49534c0eb469b2cf0e07c75dd4 |
The composite systems (Complexes –A, –B, and –C) were equilibrated/thermalized within an NVT ensemble at 300, 600, and 1000 K using the Nosé-Hoover thermostat {{cite:7697aec3cd0134eb86e200b5359db9770bd0d1f5}}. The equilibration is initially performed to eliminate any residual stress. The atomic arrangement during the s... | m | 8afc74e65bd7a6b6409818d179c0fe74 |
Having defined network modules, we turn to specifying the inputs and outputs of the modules. The latent code {{formula:a8e23d71-23f4-472d-8399-c24f09237c42}} comes from a simple prior distribution {{formula:d3305206-fafe-4c64-b8dd-707b03a32795}} (multivariate uniform in our case) – it makes sampling random codes {{fo... | m | 42a50360ec014e1248a90fe4e09b25ca |
One principled model-free framework for learning-based control is reinforcement learning (RL) {{cite:6e7db3a5cd0e9bb1fcbb2ae5c35c762cc4823c0c}}.
In RL, the agent observes feedback in the forms of costs from interactions with an environment, uses this information to update its current behaviour, and aims to discover the... | i | 24bf2346a27a7a27cfb8340da7c56bb3 |
In this section we present our algorithm, {{formula:4d7445ea-1257-4968-b189-ff5fae0c4503}} -learning with UCB-Hoeffding and Max-Optimal Initialization, a modified version of Algorithm 1 from {{cite:c845c5942897c06a5967309846ef016a73ab3ce0}}. We also introduce a theorem that shows the total regret of our algorithm is {{... | r | 498d946b3f006cecf224a99e8090f06d |
However, local energy conditions, including NEC, are generically violated in quantum field theory (QFT), even though they can be satisfied in an averaged sense (see, e.g., {{cite:2ac95528028e1c05c82f7089937964b9f5e64de5}}, {{cite:1bae249ad0ec8ce8e46eee7efa08466f4cd8525b}}, {{cite:bd173efb15e7478f19e7873d32273e269609b26... | i | 26e644465404df1daa635a08c8f2ceb9 |
To ensure the reliability of our main results, we report results as described in {{cite:e5124768a2800af883f5f9bc265789e673ac885f}} to account for the uncertainty. We present results in Fig. REF , where, surprisingly, our method obtains state-of-the-art performance on the URLB benchmark {{cite:ac00cb384f35e97638fa7996a4... | r | 6a8b59a41df991f8b452c448a5bde0b4 |
Based on our analysis, it is clear that state-of-the-art models have a high training cost in conversational recommendation systems. The high computational cost to train complex neural architectures does also exist in other research domains.
This has led to an increasing interest in knowledge distillation {{cite:3905761... | d | e5d182e518763b1198050cd3a08dd41c |
One can distinguish dark{{cite:f324e3cc8e0c6d8bd3e214df89e2baa99344677a}}, bright{{cite:f324e3cc8e0c6d8bd3e214df89e2baa99344677a}}, and semidark{{cite:25756e4578860aacbe8cd59381bddab8b86359ff}} charge-carrier complexes in TMDs. In dark complexes (Fig.REF a), radiative e-h recombination is not allowed due to spin and/or... | i | 30f9c46a94da536dfd331b947b7a78b9 |
In {{cite:7e6d456bdcf41b990e4e694ee35c35c3e20608bb}} and {{cite:020b1a082c7d3493179f10191d48daa84feb70b4}}, Ringel realized {{formula:f9746b23-86d1-48cf-bc3d-cd7b1cb07aac}} by (twisted) Hall algebras. Let {{formula:009399bf-beef-4aa5-a1cd-0a21e6a3dc05}} be the finite filed of order {{formula:08f52f39-4868-40a2-b4eb-f... | i | fb56af14f06e0120a2e700d6e6c4c3e4 |
Moreover, considering the Swift-XRT monitoring of other 10 bright {{formula:5e358845-06d8-4989-8357-a1fe32db3545}} -ray BL Lacs during 2004 December–2012 August, only Mrk 421 has shown a variability amplitude {{cite:e28ef95b622e3899ed0e0b5a20b87a43ea3a609c}} larger than the value estimated in 2020 for BL Lacertae. Howe... | d | a92b4597a2950cf011e426b602db1ea2 |
For {{cite:f6852e9b5e4ce7dcd53322482ff565ea2baaac4d}}, semantic communications must be shaped to effectively compress the exchanged data between communicating parties, improve the communication robustness by incorporating semantic information to the classical Level A communication scheme. This is possible by exploiting... | i | 4fa5d85b43542ef908864b68c32b7e20 |
In this section, we discuss the feasibility of detecting the
quantumness of gravity in our proposal. Let us suppose an experiment
being performed using an {{formula:7a2ecf8d-662c-4ceb-bbc8-f5b104d88dd9}} quantum clock
{{cite:500d5bc5b4206e65c01a3066b6e1562ac408b337}} with a probe laser wavelength
{{formula:8435b027-70... | d | df48c5b85b97026669ac6b131bcc5db1 |
From subsection REF , we know that the solution {{formula:43c69274-97a8-49d5-9a87-91417d49fef6}} of the
generalized continuous Newton flow (REF ) has the nice global convergence
property. On the other hand, when the Jacobian matrix {{formula:7e8e3101-9a4c-4079-958c-c991cd60abcf}} is singular or nearly
singular, the O... | m | 2eaed511deb408598c549df994fc0d6f |
In fact, two further aspects concerning the estimation of {{formula:0d2d4f9f-1af6-4ad4-a65f-eff0a50bfd73}} need to be accounted for, concerning the selection of the kernel function {{formula:f5f6728b-ece7-4cf4-b930-757be1107db6}} and the smoothing vector {{formula:a6cb0025-02fe-4d88-ad43-cd0b56847589}} . With respect... | d | 4cb83ea893bc24ad5f9a0643d122a263 |
In solving the problem of Thomas precession, we used a coordinate–free approach to the problem, which allows us to identify an skew–symmetric tensor {{formula:0218afbb-dbe9-4308-91a6-0104a183749f}} , the generator of Fermi–Walker transport, depending only on the intrinsic geometry of the worldline of the accelerated pa... | r | 4be2cb7079f3ad8c2092a20449205d71 |
In Fig. REF we present for scenario 1 scatter plots showing the GW peak position as a function of the strength of the phase transitions {{formula:18cef857-e253-45e9-a871-975feaa243c1}} in the colour scale (left) and the corresponding signal-to-noise (SNR) ratio for the phase transition (right) for a mission profile o... | r | 521b0c47c83ee4be7d4d2e03e3ea77b2 |
Actually (see, e.g., {{cite:e37620466d933a624807c72a559ab881240ba3f3}}), for any non-zero {{formula:cd350cb7-23e1-469d-aa2f-7d28d9e7b20d}} satisfying {{formula:e02d8650-979f-4809-82a5-ee639e954a4c}} (under (REF )-(REF )) the corresponding {{formula:d823cff2-95ad-45a9-98e0-5067c175fbe0}} has the properties {{formula:... | r | f69014a487859d41bd53bb04423294ef |
In this work we consider the model-free null hypothesis of conditional mean independence, that is {{formula:5e6a2d34-1c77-4d5e-89a9-770fd05ecb05}} ; in words, {{formula:be7bae1d-37cb-45aa-9378-d0a07a76a0dd}} does not feature in the regression function of {{formula:d7deb09c-019a-4941-911a-82af59d4b0ed}} on {{formula:0... | i | ef151aa2c0e7ceef8d3bb1b6014893da |
Other possible future directions can be found by revisiting our modeling choices. While GHL consensus is defined for higher dimensions, we restricted our simulations to the {{formula:fcbddabf-410b-475d-bb76-da0d160203b9}} case for simplicity. It is worth investigating not only GHL-{{formula:8f6a7a56-4dc0-42db-9f30-bb4... | d | 6fa8e918d6881171133d8b86188dfa8d |
Other practical use cases of WAFL may be realized in the context of transfer learning with very deep neural networks such as VGG{{cite:d596a11da977000d8404619cf6701009807e3386}} and ResNet{{cite:8f25a97475b44687da1f978022a38fbe420a6701}}.
Transfer learning uses pre-trained models, and only around the output layers are ... | d | 4f08e595848870ba2382c0ee41defc31 |
The calculations discussed in the foregoing section for spin waves were confined to the simple cubic lattice. It is, however, straightforward task to extend these evaluations to body-centered cubic and face-centered cubic lattice with nearest neighbor interaction. Also, the computations presented in Section REF corres... | d | e0554d82bb4598cdbdef097e77cefa6f |
This section provides results of the neural network against the perception algorithm {{cite:784a096ed85826b120bddbe7be85e99d74f85236}}, the brilliantly performing isolation forest algorithm {{cite:532454d4b0c774b13dbdb500603fd0a6d237e7dc}} (sklearn implementation {{cite:b4d83b65602c972d210769f68c3b52d6f104938a}}), and ... | r | 90deb8726d57cd3ab40adf205a7a8ad1 |
Note that any subset of an Alexander system is also an Alexander system and that we do not require the surface {{formula:bd01e8b9-f83c-4788-b796-49812c20b898}} in the preceding definition to be of infinite type. The following result is the infinite-type surface version of Proposition 2.8 in {{cite:e37dd2e10afcc06c09d7... | m | 20cc29b49e8db650b042609831e93df3 |
An iso-surface has a fractal dimension given by {{formula:4f0d7dac-44ea-4432-978d-229e7fa9aad0}} =(Euclidean dimension)- 1/2 (exponent of the variance) proposed by {{cite:9cf626fdd76df797846c8a7a073a8b34cf40b947}} . Thus {{formula:efe29a85-c20b-42b8-a803-e58c63107261}} for an isotherm, considering a two-dimensional s... | d | 43065a10de913bf9a48f04e34d382402 |
The current approaches{{cite:25daa560ff158c4f9ebb5804efd31e0f43c4759c}}, {{cite:ac2054723ffcece165da9c054dc2f3013ff88911}} to pose estimation typically fail when faced with real-world challenges like cluttered backgrounds, occlusions, truncation, different lighting, dark objects, glossiness, and shiny objects. Figure R... | i | 305d794067d11bcbfc4bdc8b881db571 |
Figures REF and REF illustrate the estimations of the original distributions of location data from San Francisco and Paris, respectively. We sanitize the original distribution using shuffle model giving a tight differential privacy guarantee with parameters {{formula:ac99ed9f-24c9-498d-9225-3c2bfaf2f132}} and {{form... | r | af313eeccf55deda3cc731549fc9c646 |
Networked control systems have been playing a crucial role in modeling, analysis, and operation of real-world large-scale interconnected systems such as power systems, transportation networks, and water distribution networks.
Those systems consist of multiple interconnected subsystems which generally communicate with e... | i | 33476816148cc34739430a70a65d7aec |
Vanilla ViT. For the Lottery Ticket, we use the model DeiT-Small and DeiT-Tiny {{cite:a53396e5cc66b17febd8518b92e86f6e0283dfad}} to validate the existence of winning tickets. We test our proposed LTH-ViTs definition using DeiT-Tiny and DeiT-Small.
The overview of our method is shown in Figure REF .
① We pretrain the m... | m | 8891e7d8b45b9248ef980102999c3730 |
We have presented the concept of Fourier-domain dedispersion and
shown that this direct incoherent dedispersion algorithm is a
viable alternative to the traditional time-domain dedispersion. We
have implemented the Fourier-domain dedispersion algorithm (fdd)
in the dedisp library by {{cite:61a3a3cbaad5f621cb1a5bd52f8cc... | d | b827c296cf6afa11f6b7014e3e36bec5 |
We briefly recall the situation for scalar drift-diffusion equations.
The first proof of exponential convergence to equilibrium in a degenerate parabolic equations
of the type {{formula:b38e9e8b-81cb-4b11-8af6-278d12de040f}} has been given
in the case {{formula:6d54cb82-6212-46a5-a6f5-a0d0ec09efcc}} and {{formula:42d... | r | 8ca3c37ec32ba077d9a0150bd2d5cec5 |
Existing literature in few-shot object segmentation has mainly relied on manually labelled segmentation masks. A few recent works {{cite:e299c8528c1df4f84e09eb906d691fb9a393d630}}, {{cite:b0bcb2551f498fb4d00019f90e9dfe5b167f9253}}, {{cite:88fa8f64bd7e974677b984dc46e2826993c8812c}} started to conduct experiments using w... | i | 9a2902d7f47ba6f5667ec8ff5124b74f |
Comparison with I2L-MeshNet {{cite:879257d7c465fdaa3fdf24dca934a618bbdbf3e0}} and Pose2Mesh {{cite:f7cf39110c14621ab049316f4ad171a62c5d1947}}.
Figure REF shows the qualitative comparison between 3DCrowdNet, I2L-MeshNet {{cite:879257d7c465fdaa3fdf24dca934a618bbdbf3e0}}, and Pose2Mesh {{cite:f7cf39110c14621ab049316f4ad1... | r | 271c58df9ac05529705838d3df1fa177 |
An event {{formula:00f5c8dc-cabc-434e-bc80-9fb84fcb2f87}} is interpreted as a tuple {{formula:303b73ac-000b-4ead-9354-9768d31d7808}} , where {{formula:e928af70-fc6a-4cb3-9870-befc51cd79b7}} is the pixel coordinate, {{formula:1a0d53ec-c0f6-45df-ab1c-858e5534bf91}} is the timestamp, and {{formula:c1e8f06b-063f-477c-... | m | 274969aa309df489352ff1f0ff6d1ade |
Thus, for every {{formula:48cbaac1-d863-4f92-8958-d5e6879356c8}} , {{formula:40fbafff-4f7b-41d5-8d5b-4a66dd0e4564}} is a {{formula:0933b684-380f-4e86-9a4c-f2ff3073c5c6}} -semigroup of operators on {{formula:744c5ee5-dbd4-4dc8-85c0-6ac35c3e3435}} whose infinitesimal generator is {{formula:598265d8-28e1-4986-8818-17924... | i | d88d0b661259bc17cce6ac158eb83986 |
Furthermore, we note that given that our bounds for universal unforgeability are not tight, it leaves a space for exploring the possibility of universal unforgeability under more efficient challenge sets. We will show an example of this in the next chapter. Finding tight bounds for the unforgeability of qPUFs and more ... | d | b4d9d91e44a6b99d2f72c064f606e9b8 |
In conclusion, we look at the issue of obtaining unconditional convergence rates/concentration bounds, as opposed to ours which is conditioned on the iterate being in the domain of attraction of a given equilibrium. An unconditional estimate will be a product of our estimate times the probability that the conditioning ... | d | 0a07e5a388d0bec808959348fe7ea5fd |
Quantitative results on the COCO WholeBody dataset {{cite:1db5801f079434c2aab1c6d31041e7ca67d322ec}} are
shown in Table REF .
Our result is based on a single model that is evaluated for all (WB) or
a subset of the predicted keypoints.
Our method outperforms previous methods and achieves
especially high precision on fin... | r | de6e250770d16a2df2f412f25e20d723 |
The Multi-agent PPO Reinforcement Learning actor-critic framework is based on the traditional actor-critic framework proposed by Sutton et al. {{cite:86923f31e6f5fd2783ef31e311457f2006c7e1de}}.
Specifically, the decision-making of each agent in the environment is based on local information. In particular, the agent use... | m | 003a3da391f389d330acca9f39bb1720 |
IDL (https://www.l3harrisgeospatial.com/Software-Technology/IDL),
SolarSoft {{cite:f00003977afe2e0b142443e8cef974498116d7ba}},
PINTofALE {{cite:42c16c8a2e4d3c89a3e0840b1ce5fb75d0a89db6}} and
EBTEL {{cite:a8f75fc56fc1059ab0eecb11fcba45748613bc07}}, {{cite:e5771080f06925642041945a145e2675b394de1d}}
| d | efc38c8e441754bb1faed86ed28e8097 |
The proof of Theorem REF relies on using Lemma REF along with {{cite:8532ae934d4306af37b219c34726ca4a586ac959}}. Inspecting the proof of Theorem REF , one can see that any {{formula:00ebe4e1-bf00-4515-b67a-6699e0a1d4c2}} can replace {{formula:7b178ffe-6b46-4f38-9925-e7a463f6f56e}}The proof does not rely on specific ... | r | 8b312cb3b43e550807adcd0588404a0c |
There are several ongoing observations of neutron stars
such as the ones with two-solar-mass {{cite:b1867b49e3d88268e4c5188c131f457363bc1efe}}, , , {{cite:4ad1a205e497a3dfe16970f559f64b44cf1df699}}, {{cite:57c3b046f1e01e6792f5c8f086b02b2d73b35e5b}}, probed by gravitational wave
detectors {{cite:84a0457401a8da72ef95eb54... | i | a5f436fa51058a485bbd50ae9c774be4 |
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