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For present day various types of space-frequency distributions are successfully
used for the analysis of nonstationary signals {{cite:1c768296eece59eb72e080586ae0fac5676bd0f1}}, {{cite:52a7eebcc44ea0aaeb073a0b2da3927bdbb4ca43}}. Many of such
distributions are characterized by advantages as well as by disadvantages in
u... | i | 37e3c954a85d507d3554c1c07cb797e3 |
In this paper, we propose a new practical way to enhance the security of PUFs using quantum communication technology. First, we classify the adversaries into adaptive and weak adversaries based on the querying capability of a PUF device. In the PUF-based authentication protocol, one important issue (in the case of both... | d | 0f958cabc6ff7b9861217df9a29fd222 |
Understanding how events will affect the world is the essence of intelligence {{cite:85f6e5edc42d994e038ef4cfb5b09af81684cdc9}}.
Procedural text understanding, aiming to track the state changes (e.g., create, move, destroy) and locations (a span in the text) of entities throughout the whole procedure, is a representati... | i | 0fe6b5637275e9d482829d62d64d1107 |
For quantitative evaluation, we use the synthetic stereo videos from the MPI Sintel dataset {{cite:a76a45aaa6f7a7f217d934f1614b13ccce01bdc6}}.
We select 6 videos that show a variety of characteristics in terms of scene motion, camera motion, and the size of moving subjects.
We use the left video to train our models and... | r | 8b71728c4986c161bdd0ebd99a29ddba |
Considering that the objective of our project is to identify individuals with a face mask, we applied a transfer learning technique where a model developed on another face recognition task will apply to our specific project. We use transfer learning on a convolutional neural network-based model, in this case, a ResNet-... | m | e7a6df58ba7c3a08f25dc8d1508670f4 |
HMC generates a proposal in three steps. Given the current state {{formula:3005d9b2-9225-455d-aedc-8c6ffdf42c88}} , a {{formula:40ef06a9-4e57-4bda-996b-41273f43005b}} is sampled from {{formula:3e39275c-2646-4f0d-9a93-b2672767aebf}} . Then, Hamilton's equations: {{formula:699141f3-5ae7-4486-910e-c2a4e420978d}} , {{form... | i | 853309c1833f37b9864217e879df8616 |
As shown in Fig. REF , our domain adaptation framework works in a teacher-student mode. The teacher network can be any existing source dehazing models (e.g. FFA-Net {{cite:45c7464106457a0a00169efb31366f1c2fda5cc7}}, MSBDN {{cite:539a54ebb71e3436a913936034f2fd46688b792b}}, we choose MSBDN as the source model by default)... | m | 6036eeea6e6b27fc017b35dc9ac9d217 |
The success rate of the attack is the ratio of the times that Mozilla DeepSpeech {{cite:9ef9f2300a5092069779371a179cf193dd41e69c}} The Mozilla DeepSpeech ASR is the current audio adversarial robustness benchmark {{cite:fd150c4ea70648ff5998ba26cd1a05ac388f2096}}, {{cite:24f8dbd98af64c38f97d03a76101540c090b117c}}, {{cite... | d | 3ef97708c1428a436962b3ce30cf04bc |
We experiment by integrating two sub-tasks of personal health mention detection and emotion detection in a multitask learning setting. This section gives an overview of our multitask learning framework and the parameter sharing scheme (Multitask Learning), with a graphical illustration of our framework in Fig. REF . We... | m | 1023ffc56fd757bac0176ff4a0ed9b1e |
for all {{formula:42a3a80e-7e17-43e0-8e47-0d264d787655}} and {{formula:ce49abaf-44f7-422f-b4a2-d6eadb14e3af}} . The process {{formula:4f97adf3-ed8e-4db6-9678-2db7d9d46e9e}} is called common component, the process {{formula:c48d5e96-4336-419c-93a3-13a945d7465f}} is called idiosyncratic component. Representation (REF ... | r | 66797050bd476c4015f377aaf106425a |
The paper is laid out as follows. In Section we recall how we
have obtained the Kähler two-forms on the Siegel–Jacobi disk {{formula:80bf2c9a-ee1d-41a1-a4c2-f34ce93b7638}}
and on the Siegel–Jacobi upper half-plane {{formula:c2df6c10-aa60-4001-aa57-38a8d87cddc7}} , specifying
the FC-transforms. Section describes the ... | i | 9bffb66c4e3e1089cc368152d637420f |
The mobile operator's goal is to provide QoS Internet services for large populations of clients, while minimizing the overall computing-plus-communication energy consumption. Hence, a trade-off is required between QoS and energy savings.
Future MNs are expected to learn the diverse characteristics of users behavior, as... | m | ca9b48138e2ebdc67df6876b4739c524 |
Our model aims to achieve better {{formula:ae7c5421-6f67-41a0-997f-a0796740c0ed}} and {{formula:116b4352-f9b7-4127-ab33-21d6a50348ba}} than other state-of-the-art deblurring models so that real-time deblurring could be deployed on machines with limited computational resources such as embedded computer on UAVs or auto... | m | 6b9d886e53c1fb2475885e69bb1c9b04 |
The integral part in the right hand side is actually the nonlocal Laplacian operator, reflecting the non-Gaussian Lévy fluctuations {{cite:2fceb13d858a84288d893819041906637c5f3e3b}}. The equation fulfills an initial condition
{{formula:40f62f82-e711-426a-a951-4ceb3baf8c0a}}
| m | 02eb3bbac1702ac3c821c48775a7d70b |
After some calibration, setting the correct parameters to minimize the RRMS error (see details in{{cite:3ed266e4f697574edd2bf6929aa8fbb7a837d94d}}), HODMD was applied using the following parameters: the number of snapshots {{formula:211b262e-f3bf-42f2-ba6b-5dfddeccf786}} was set to 100 snapshot in all of the cases exc... | r | 34d2a3c9a4ece330f5a80b277f3ca070 |
Remark 3.1
(a) In some scenarios, one cannot compute the Lipschitz constant of
{{formula:80669866-2c8c-4bd2-b521-2cce6b6b7c8e}} , instead of an upper estimation for it. In the rest of this paper,
we denote by {{formula:17c0077e-3d62-48b2-b489-9253836c1add}} an upper estimation for it.
Next we show that Algorithm is ... | m | 85018de71024ee1703c1597aa3df5df8 |
Blockage: The BS-UE link is often assumed to be much weaker than the BS-RIS and BS-UE links, which is motivated by the following observations. On the one hand, coverage extension to areas where the direct link is blocked is an important application use case for RIS deployment. On the other hand, for cases where the dir... | d | 0b3f40a6130547773644c4eeea27f014 |
Detection methods consist of input, backbone, neck, and head. The input can be images, patches, or image pyramids. The backbone can be different CNN architectures such as VGG16, ResNet50, ResNext-101, and Darknet. The neck is the subset of the backbone network, which could consist of FPN, PANet, and Bi-FPN. The head is... | m | c486e58ee4f33d8e40f2238be785d4f9 |
Recently, Transformers (e.g., vision Transformer {{cite:918fed72bcbe8d68bb2b6b4bcea5d4b11c9a2fa0}}) became a de-facto choice for modelling long-range dependencies in computer vision, inspired by their success with self-attention mechanism in natural language processing.
Compared to CNN methods, Transformer models have ... | i | fdc167d47079e5bf3cbf115206bf9b12 |
Statistics showed that a large amount of the data traffic is generated from a small amount of most popular content files. These popular files are requested by a large amount of users, which results in duplicated transmissions of the same content files on the fronthaul and backhaul links. Therefore, content caching in R... | i | 21986d31a71840ec50083e0ddf4445c6 |
Corrected images with DeshadowGAN did not exhibit strong artifacts that can often be observed with adaptive compensation such as: inverted shadows, hyper-reflective spots, noise over-amplification at high depth (see examples in Figure REF ), and hypo-reflective retinal layers. For this latter case, we found that compen... | d | 979f20951ecf507edb38647ee8dad34b |
We propose Tetrahedral Diffusion Models, a 3D shape generation model that extends denoising diffusion models to tetrahedral meshes. By combining the flexibility and structure of tetrahedral meshes with the generative modelling power of DDMs, our model overcomes some of the limitations of existing 3D DDM frameworks. A k... | i | ccab0cbde824f5a898b63ff6f13f56ac |
BALD {{cite:626fe7f826e69c008208e663ed1822bc4832bbcd}}. All strategies are evaluated on several image classification tasks, including CIFAR-10/100 {{cite:a036a83532140d96e6af49410cb95049dc647fbe}}, TinyImageNet {{cite:ee358cf1e89e73a2f5219b6835125e27d12a01fd}} and ImageNet-50/100/200, which are subsets of ImageNet {{c... | m | 2799b69fa9fc50158a9bda67c0d1ab0a |
Real-world applications of model predictive control using Gaussian processes (GP-MPC), such as vision-based robot path-tracking {{cite:4e08cb15b82df4ab88219314fe55bcbffc22b377}}, trajectory tracking using a robotic arm {{cite:cf150ccf4529b32cf9070e3d2ab717f156156d94}}, autonomous racing {{cite:9b962859ba37eafbcbef5dde3... | i | 49e01137d41153bc8e2bfdffec44d04b |
We now present numerical results for both synthetic and real data to illustrate the proposed approach. In synthetic data examples the ground truth is known and this allows for assessment of the efficacy of various approaches. In real data examples where the ground truth is unknown, our goal is visualization and explora... | r | 2850670dd7b178f47f7733803ee69597 |
We simulated the model on a complete graph and several regular lattices, and found that the qualitative behavior is similar in all these interaction topologies. As the temperature {{formula:fc562b6d-1806-4171-b079-21a260e40a1f}} is varied, we observed that the system exhibits a quite rich variety of behaviors. For {{f... | d | ff6162e493686206a8b0459a644da9d8 |
Gradient-based algorithms iteratively update the primal and dual variables where {{formula:866b3fec-bc49-4073-9e9c-63e82fc2bd7f}} acts as a learned penalty coefficient in the objective, leading to a constraint-satisfying solution {{cite:a4327573f663978607f5a5b875012e16bf808168}}.
| m | cfcef534b031cbbce1df231540662335 |
Distributed model training plays a key role in the success of modern machine learning systems. Data parallel training, a popular variant of distributed training, has demonstrated massive speedups in real-world machine learning applications and systems {{cite:4497af28f1c3bc4508f325df676c351c33803c34}}, {{cite:db61fb5564... | i | 12cca6e10d2bb696a5a373a5e5a6f825 |
We present cosmological models with dark energy described by the RHDE in the DGP brane-world cosmology with and without interaction between among the cosmic fluids in the universe. Both models accommodate the present accelerating phase and share a lot of common features. It is found that both the cosmologies accommodat... | d | 4d790377e103b1b35d3998122f5a26e3 |
We close this introduction by discussing the
{{formula:81ebdc68-9798-457c-ac95-61b0d7e63d75}} -completeness of this theory. Gravity theories with a finite number of higher derivatives generically
suffer from various pathologies, as the presence of unphysical ghost modes
in the spectrum.Counter examples are the Starobin... | i | a1e41502c6c764adc90545b9fec151d9 |
We implemented the numerical solver for 3D Maxwell's equations with FreeFem++ (see {{cite:b8a03ef9393f472233359747b305db1e5b452078}}). Our test domain {{formula:9717122a-936d-4147-8a1d-a0fb1fe60ac5}} is the unit ball of {{formula:ddf490f6-f0b8-4558-b9c8-abe131b767b2}} . We consider a tetrahedral mesh {{formula:6c26165... | r | dc281e3aa8a2dcc09bb4b50f22baf9e5 |
We first pretrained a DenseNet {{cite:4f146f73708fbf928db7f148418d29198e67c780}} classifier on a Positive vs. Healthy binary setting per pathology in the dataset. Both the Generator and the Discriminator will then be conditioned on the class labels {{formula:b52da8d3-230d-4965-aeca-dbc3c8af14c6}} predicted from the cl... | m | 194495d814484c99400c5ca588aff141 |
In Declarative PM, the de-facto standard for expressing process properties
is Declare {{cite:1d4e6b1091ff7072daa4d79b95edaac109b00420}}, a temporal logic consisting in
a set of
template formulas of the Linear-time Temporal Logic over finite
traces (ltl{{formula:076dde7e-a200-4e1e-9881-98b45761f046}} ) {{cite:080e0ef98... | i | 5e7f6e99888a8b029517ca5b4f970d4e |
Here we have only treated pure gravity and thus to properly address the cosmological constant problem we should understand the situation when matter is coupled to gravity {{cite:cfb7b7419e8b0716fa0c6cf8c7201291209205f3}}. Indeed, arguably there was never a cosmological constant problem in pure gravity since if we adopt... | d | 477e62956f07be1bff5e94b00a7a4920 |
Let {{formula:a9f6262c-b8d2-4d69-8a45-3d066fa69b7e}} be a piercing vector field for {{formula:679fba77-ccde-44c9-8083-8d3f64101e91}} normalized to {{formula:3e8f51dc-02cf-4393-ada8-38ee9818d0f1}} where {{formula:dc545f2c-a138-47b8-9ef7-a14ac8b9b4b4}} is a background complete Riemannian metric on {{formula:a1f48f19-... | r | c211e2cdf29894ec4e8d2aa2863a3fb5 |
Few-Shot Segmentation (FSS) comes to the rescue by leveraging approaches like metric learning {{cite:c370a3c5b404b18c8d0b048f8f30a1c3f0ba2c23}}, {{cite:f9e6120cfb40c1063d8b2372e754d656d3b36ec8}}, {{cite:cafa8600a90b6f0128c409baf71a4c3c35982416}}, {{cite:5f58cb40873eec77614ddcf2c4ecab07d522b07d}} (e.g. Prototypical Lear... | i | b5d7413d8d8522a20c2f9295f2008b1a |
It should be emphasized that the total dc current due to the group velocity modification vanishes for a fully occupied band, so it is not of interest for electronic insulators. Instead, here we study an analog of the circular photogalvanic effect for neutral bosonic atoms in an optical lattice, where they occupy the lo... | i | cdb5da1104483fa4bfc328d906015494 |
From the experimental perspective, the obtained systems from our {{formula:ae4e5acb-09fe-4ee2-b64d-d2822163033e}} th-rooting procedure are expected to be implementable with the same setups employed for realizing their parent models. To this end, the additional degrees of freedom required in our {{formula:a6e7d542-a2e1-... | d | d8ffc1b236fa6d6aadf054855eb899c7 |
Proof of Statement 3: We are now in the position of bounding the computation cost of Algorithm REF . Let {{formula:653ac88a-26c9-42bc-b457-9f56fbafb15e}} be the computation cost for implementing the unbiased MCMC subroutine {{formula:4c58dade-3950-4928-b0f7-57758f3ddfe8}} once. It is shown in {{cite:58aacd9c342362367... | r | b75efa44e20428147e2bd237104901d4 |
The normalization of this distribution gives {{formula:ce2c3347-202c-49e0-8ff9-b3b8c620552e}} .
We assume that all binaries initially have circular orbits, as the outcome of the interactions of
systems with the same semilatus rectum is almost independent of eccentricity {{cite:0deba11a3ecb9706c1c75d554d967a4c8ce57408}}... | m | f4b4b115d8ae1c6e605ad7a42a5bee06 |
Blind demixing in a single random graph. fig:singlegraph shows the results of demixing with a single diffusing graph of varying {{formula:76a60a6d-4a01-412c-94c0-4ea7fc569628}} and {{formula:7ab29489-246c-4559-9661-6d6f8bff9e18}} . Random graphs are drawn according to the Erdős-Rényi model {{cite:c9b2be6ad086c43f01469... | r | 27636c810c47ed4b5e9e12a7cbb8fe58 |
Normalization methods are used to improve the trainability of deep neural networks. In this section we will show that four commonly used normalization methods—batch normalization {{cite:dc32fa586a02c99b725d05e9de56245e6eb06717}}, layer normalization {{cite:5f3bb68ebfcbfa7375500e90cf1e1fade9632c60}}, weight normalizatio... | m | 6c3305469921b0954ea3acff10ea574b |
The performance of CAN is reported in Table REF , along with those of graph kernel methods: Random Walk Kernel (RWK, {{cite:75598028d04dcf70072577dc90c58579c5663f02}}),
Graph Kernel (GK, {{cite:e6a4eb72da39b50d989eb0eb145f68e5943f5324}}),
Propagation Kernels (PK, {{cite:96668a5ea5978ccc6acecdc6936f01773a16532d}}),
Weis... | r | 5247a34265379ea1ff0d7689d9343564 |
In the first two experiments, we observe better generalization capabilities in policies using iGibson's domain randomization. For PointGoal navigation based on depth images, the performance goes from 0.27 to 0.40 SPL {{cite:21133a369e09daf5207ffbfd8a5c86c8a200139e}} and from 31.25% to 44.75% success rate when using ran... | r | 902ae734baf057d765e0b302455ca1f9 |
where {{formula:1f3c5192-5f94-4619-a6a3-81fa8451a4d0}} is a generator of an analytic semigroup on a Banach space {{formula:90abf8a1-a3ee-4171-a727-1aad20e8843b}} and {{formula:f96d4b66-6613-43ef-8e42-7ebef537b469}} is a locally Lipschitz function with {{formula:f9337b47-78fb-4af4-9d5c-f78779fdd2c4}} , {{formula:ede... | i | 13085034d517d08eeb94a9e7a060ab53 |
According to {{formula:3f48c5e1-86f2-4124-be7b-4ce6de8fc6ed}} {{cite:c64fc652bc94e386e21084295c4a72a547476114}}, we obtain {{formula:4d5445bb-cce9-46eb-8fb2-d33541ecf5b5}} and {{formula:9ad66dc6-678c-4563-a537-4217dd145229}} .
| r | 61c7e521336b900c1412ba8b6c856036 |
The heuristic technology is calculated according to the characteristics of the graph structure, and the key is to calculate the similarity calculation score for the neighborhood of the two target nodes {{cite:9f93d5d8c0b68c08add04a3d131188fd1a38ffd4}}, {{cite:cdc94bbaee2b51ff92a6e8270726506f10235e4c}}. As shown in Figu... | m | 18c66b371e552463daf2e6fe6aa22ed5 |
In recent years, there are two lines of research on SLU. One aims to improve the prediction accuracy of
ID and SF. These models often learn ID and SF jointly by regarding ID as an utterance classification
problem and SF as a sequence labeling problem. Following this Classify-Label framework, various
joint models have b... | i | a5077478c1ceec5f96c61d6747709b31 |
Finally, a sequence of recent papers characterize the asymptotics of the Bayes-optimal
estimation error in the two models described above {{cite:8f2f2f993439a053cb4cbb51cc18ec1c929ac453}}, {{cite:66bc2beb2dc1d44f19860cef4104ec21295865bb}}.
It was conjectured that, in this context, no polynomial-time algorithm can outpe... | d | 5cec1075cd1f1128bf50ce1b1d095bc4 |
The entirety of theory and algorithms for numerically solving optimization problems like (REF ) can not be covered in this thesis.
We focus on the essential techniques and point to {{cite:bde5bce9950f1511843826c3b7ca742b2eefeee0}} for further reading.
In the sequel, we review iterative optimization methods for finding ... | m | e4cbe9b3c52717645f721769690ce70f |
Topic eSignature (1.5%) contains discussion about different issues and customization for electronic signature of documents, i.e., docusign about collecting user's agreement/permission for sales or account opening. For example, there are questions such as “Auto Add Document to DocuSign [Platform] Using Custom Button” in... | r | c613f4f7ed774aa6ef3f3393cbb9e16f |
We have also shown that both the 1 and 2 technologies can
realize nearly identical low frequency sensitivities for CE2. While this is
true for high frequencies as well, achieving the specified quantum and thermal
noise performance for both technologies requires further research and
development not discussed in this pap... | d | 546382d858a46f105db7093348d76479 |
Equation (REF ) can be obtained by lightcone bootstrap techniques, which we review and apply to this case in section . In section , we derive a Lorentzian inversion formula for the defect OPE (REF ), analogous to the one obtained in {{cite:031c9dc64a5acd667d331449b0c9dc0ebeadfee6}} for the four-point function of local ... | i | 0983aaa7aa86ed0ac6dbc7b6890ca265 |
On the D4RL benchmarks, we compare RvS learning to (i) value-based methods and (ii) prior supervised learning methods and behavioral cloning baselines. For (i), we include CQL {{cite:30b13a809a96167e739d459b1de259ddb84acdd5}} as well as the more recent TD3+BC {{cite:1537e591a995fb60635aa1815a204b5fff039c0b}} and Oneste... | m | 2fb74fa6a9b8a8884dd2bb8531d7c0a4 |
Backgrounds. Expected and almost sure convergence results have been extensively studied for convex optimization; see, e.g., {{cite:c577a317faaf9674f2f30573c4b799e9876224b2}}, {{cite:4e5f076758ef38c14183512fc2a36e4fb763d66a}}, {{cite:0fdc6a78caef527261b98359e8e459757ef0a8ef}}, {{cite:765d1e53f57bc986c1f5f2b7c8cca35bd087... | i | 7812ed8a0463c7e16291ab641cb475ad |
The third finding regards the information-based acquisition functions. Through the range of different simulations PI and EI failed to find good results for the Ackley function. The reason for this is the large area of the parameter space where all response values are identical and thus the response surface is flat. As ... | d | b85f21d63ad0d9537d880bc0faa9f640 |
In the more general setting of Markov chain Monte Carlo (MCMC) algorithms
{{cite:243730d7f975bb7e304f322a6456dc6e2847614b}}, further results characterise
the improvement brought by Rao–Blackwellization. Let us briefly recall that the concept behind
MCMC is to create a Markov sequence {{formula:27a25620-3fec-446f-9ee7-5... | m | 724ad4a43262c362ec3d34d5f45727ab |
Several recent works have investigated the nature of modern Deep Neural Networks (DNNs) past the point of zero training error {{cite:8b78d534e605a22f2784c4654f3f3b1648dd77ad}}, {{cite:41c1692c69c1e2bf6057db4ab4c08fec76978929}}, {{cite:20f7a292eda6fc6a5085096496d326647fd7b36f}}, {{cite:cc2ec48b3c86cc5f003af9303547bef274... | i | bb67c74db4af4230d2be1cd1969bdc04 |
Extracting stress mentions from posts. We applied a state-of-the-art NLP deep-learning tool {{cite:2908a5e175b5054a03a21c9da15e092814cf0ed9}}. The tool uses deep recurrent neural networks {{cite:f1836a2b4b5b0d84cd0de1fe0a6bb4d55cda478c}} and contextual embeddings {{cite:0f3d7a49df86a12e42cdd51353f158af2c0b6b19}}, and i... | m | 0d41e2555646e0b7d7d567e2c4340ab4 |
iWTA is compatible with other models that approximate brain computation through connected areas represented as binary vectors like in {{cite:285819cc35f831ab53ecd08a6293d558d7cc2d38}} and {{cite:c1789a652c045c22c93482b727a31b265cc201d7}}. However, with iWTA, different areas can selectively influence the output encoding... | d | 8d75b8bcc34b73aba7fcba324b629e95 |
Techniques.
Computing frequency-based functions is challenging simply because we don't have enough space to store all the exact frequencies. However, there are efficient small-space algorithms—e.g., Misra-Gries algorithm {{cite:344de7cf58dc01b789d37d9fc75e5f4345726cf9}}, Count-Median Sketch {{cite:73b66ce0934ae233f563... | r | d766deae762cc4c3bc3e3f1ce458c457 |
had no bias, and the PAC-Bayesian priors were chosen in a completely data-independent fashion (they coincided with the distribution of the network at initialization, as suggested by {{cite:89bbc421c81989a08a94081983ad063dcadb6880}}, {{cite:ac4bab43908d6aa91b761c1e1daf397a7e96b6e0}}). We leave for future work a more com... | r | d1fd018a967101faf1c8517b489bb80d |
Nowadays an increasing amount of large-scale unlabelled visual data has been made available. However, most existing learning algorithms are either designed for supervised learning where the ground truth is known, or for unsupervised learning using distance measurements. As for supervised approaches, manual annotation i... | i | d0999dfb5b627bf0c799a9dcee9cc43c |
Example 5
Let {{formula:f4e2e4bc-61a9-40c2-ae2f-132d3e5542af}} and
{{formula:d0ff2176-d6e3-4748-9755-b28853758e21}} , where {{formula:b43ea341-96fd-44de-a231-9bf19ff934e5}} and {{formula:8a3d7e2c-0fc9-41b0-bb78-c87b68cb1b37}} are {{formula:c4e0c5d9-d320-4c01-bf0b-b1fd37b84686}} functions such that, for each {{form... | r | f8f403f3819749ce6b8bbd0bff1e0a7c |
In this section, we evaluate our method on the Bonn dataset and the SSW dataset {{cite:7de623139fd31e00344d00c5041600f297fbfdf3}}. For comparison, we also report the experimental results on various existing deep learning models, including Multi-Layer Perceptron (MLP) {{cite:c07dfbc76ce18a6af37085dea9b8039039782ca5}}, G... | d | e41077f0a18ec90f85085637d00be3a5 |
We report the performance of EQFace on the widely used LFW {{cite:7a7d35e0c9a26421c3a562c164335b9ce719a92d}} dataset, and the CALFW {{cite:dbed7b1155df64707ad2993f53e6b1711f36a862}}, CPLFW {{cite:77f5e702f1fbe761ccafd368b77c2977c76920b5}} and CFP-FP {{cite:ab2cdce0c3e7155ee56adfa5e4235dcf539e9c6f}} datasets. Furthurmor... | r | 6888b33a2cdde37a0c298dcaa752ee82 |
There are basically two distinct ways of SSI solutions, namely
`direct synthesis' and
`recognition-and-synthesis' {{cite:77da433aea571fa5a159271c740f8a5a458d5ed2}}. In the first case,
the speech signal is generated without an intermediate step,
directly from the articulatory data, typically using vocoders
{{cite:1bb4e... | i | e897d6a460b9f146e681b40862e781d1 |
We verify that OFA can achieve competitive performance in downstream tasks of language and vision.
On natural language understanding tasks, while {{cite:b0c2dbf8037f034076f165396be3d9d4605900a4}} report the results of the Base-size SimVLM, we also conduct experiments on the Base-size OFA and compare with baselines of t... | r | 3b528737145c37065868845578e7c8a0 |
Now, we state a sublinear convergence guarantee that generalizes the original result–Theorem 2 in {{cite:6b1ad8a04caaef70a72f7bf663d483dbd5beb7af}} for Nesterov's dual extrapolation method and the newly developed result–Theorem 7.4 in {{cite:d23acec64ff23b43d3ccee73decc9608e2a171ae}} for UMP.
| m | b2b2ed24ef5bb034b92ee14c81ac4d84 |
In order to explain the various points of views we find useful, we start with simple examples and work our way up.
In section we start with a CFT computation to leading order in {{formula:b54664c7-b30a-430d-98b1-615f4ed3e1b1}} of the action of {{formula:955686e9-1ea1-4ec1-86d5-8b7c45522789}} on a scalar bulk operato... | i | 345616cba542297e3e3c4638b8cd8944 |
In this study, we compare nonlinear dimension reduction methods isometric feature mapping (ISOMAP) {{cite:f1e3445a55920fd3302d2674463fb367386aae47}}, diffusion map (DIFFMAP) {{cite:65e5867231cf8a54d0c8c0880e0ffd50b182a3d0}}, t-distributed stochastic neighborhood embedding (t-SNE) {{cite:a603926c404d17beb144121700b72a3a... | m | 412bd65fde348a4ab79206e282bdfcc8 |
Mutli-agent systems have received significant attention from researchers and have gained more attraction due to their various applications. One of the significant applications of multi-agent systems is the formation control which has been inspired by nature. In {{cite:9eb53e900bb9ec2e1501703c4886cdb52dea4150}}, differe... | i | 9bcb6eff72567e9b6bdc0fbec86e989d |
The study of the AdS/CFT correspondence in low dimensions has seen renewed interest in the last few years {{cite:50ff4b5565deab2e37bb2c18312735c8ebfe9187}}-{{cite:0de6555621e19577a5adc425369ef05db47d1cfd}}. On the AdS side of the correspondence, a plethora of new AdS{{formula:1fa4f18b-2341-4251-8bd3-0cf80f4d3fc4}} and... | i | ed2e9177e98e5a80c964184d8c6db1db |
We prove the following chain of implications
{{formula:dce031a8-537f-448f-81c8-a9b707da8884}}
The first two
implications are trivial.
(1) {{formula:32c534e5-bf42-4d9f-8fb9-c8ea86864071}} (4) is {{cite:c159d7f0027ffb08111eb75889f82d548fbb29d1}}.
(4) {{formula:3ad6f544-50fe-41c4-85be-4eeb2ee40e94}} (5) is trivial.
(5)... | r | a445b59a3c645bc2ad10b864d321079d |
We validate the efficacy of Cascaded-C4Synth and Recurrent-C4Synth by comparing it with GAN-INT-CLS {{cite:a5890aa4a757d854578d0111b637a9c7ddf23351}}, GAWWN {{cite:65b26cb2813f3550d5a3cbdc99ca0dd058cac3ad}}, StackGAN {{cite:728d357caa6497c32ffa57f9407d1c241d62554c}}, StackGAN++ {{cite:22af2c99950986bff7caaf352f69af012d... | r | ab945bdaf455e7ba4f490f2b7e631f71 |
Given these image pairs, we can train a deep network with the encoder-decoder architecture (see Fig.REF ). In this network, image features are extracted by three dense depth-wise separable convolution (DDSC) modules after the image is down-sampled twice by a factor of 2 to gradually reduce spatial resolution and extend... | m | d2ac1e7c68ab88616edc807ea8820f64 |
{{formula:de43f71a-dae9-47a6-b46c-2e5a2953f592}} production is a probe of the hot and dense medium created in ultrarelativistic heavy-ion collisions {{cite:f5fa1857cd4609f5f51e56224adc6904d5cb9c91}}, {{cite:e646d8747e32ae595598e25bdd712df40a2e49d7}}. Moreover, it is also sensitive to nuclear effects not related to the... | i | 1484fb9107aa28dff7d9a64fa3834481 |
In this section, we validate the performance of the proposed method and compare it with recently proposed state-of-the-art denoising methods, including BM3D {{cite:db5ba86a7866d0cbb609bae2515a25798f01a8f8}}, NCSR {{cite:ce177dd8259ebac01253971fc536f32d70675960}}, WNNM {{cite:4178a5b884cd691da38e8c0dde362becfb047b2e}}, ... | r | 13539fbaed8493342e65cb2846ba2edd |
The constitutive relation of the NLG permits a different cosmic expansion history as compared to the prediction of the standard {{formula:df890b5d-703c-43e3-ba0d-99f938049a8b}} CDM benchmark model. Consequently, the modified TEGR cosmological models can give rise to a rich phenomenology to be confronted with observatio... | d | 4fa4d8e3f0a2b88c80e777ac4ee94e7a |
We remind that Theorem REF says that a closed ancient flow must converge to a shrinker after rescaling if {{formula:05bc550f-404b-4556-aec9-882eef4a0bef}} . In the super-affine-critical case {{formula:a5a488ec-fa25-41fd-8ea4-af503ecf8fe8}} , a closed convex {{formula:f2d7e04d-a0f7-4638-82c0-eeef4df40ad3}} -CSF must co... | i | 832d347c28a4e071fbfd269ec1888c6d |
As shown in Table REF , we compared the performance of the proposed model SPFNet against the other state-of-the-art models in terms of FLOPS, parameters, speed. We run the experiments with the training set and validation set. The input resolution is reduced from 2048 × 1024 into half to train our models. We evaluate th... | r | 39a765af21ef5bcd52049df4994d9f1c |
Surrogate methods were studied in depth by {{cite:54ee9e528981fcc41b50227a202195fee7cf9ee2}}, who proposed a generic framework to relate the excess of the original risk to the excess of surrogate risk through an inequality of the type
{{formula:ab38ac78-3358-4568-a73d-824384d83daa}}
| m | ed298ec26c4b06e7c5d1bf38419dd6be |
On the classification side, we note that classifiers are sensitive to GAN reconstructions; accuracy on the reconstructions tends to be lower than that of the dataset images, requiring an ensemble weighting hyperparameter to merge the predictions of the image and the GAN outputs at test time. In most cases, we find that... | d | c52fea3b625ff06e8c8976ba537564b8 |
We remark that previous data structures handling failures in {{formula:8c3dd3be-4148-4c82-b630-215f8ef1f9c9}} time either
work only for the single-source version of the problem (see dominator trees, or {{cite:d6860fc36ff653af7b5572e3fa21be6d5d985356}} for two failures),
or work only on undirected graphs (see, e.g., {{... | r | 31cbe890c2d545d2ed07c360238bd685 |
A recent work {{cite:2774fa7c7bb19d38ea3d063b7e593ef71b98b128}} argues that previous WSOL methods in fact do not outperform the pioneering class activation map (CAM) {{cite:dcc1ca584ad247deaa83f2480715407b33a92e91}} method, and further claims that WSOL is an ill-posed problem when it is not given any location annotatio... | i | 80f2f853617d73e8ad4a0a788d33bcbd |
From the first relation in eq. (REF ) and the {{formula:2fe6e8ea-a0dc-4bbc-843e-11db9216048c}}
range of {{formula:dabad573-01a6-48e9-ade8-a29a31022a1a}} from Ref. {{cite:9f6a332e35a4d3939502bf702ba9f4ec83ebe698}}, we deduce that {{formula:d7d7274a-36e3-4115-bfee-01136bc95e8d}} lies in the range {{formula:acf35d56-98... | r | 79b199d053ea8e1584f4717fd919ffe6 |
be a non-zero cuspidal Hecke eigenform of half-integral weight {{formula:8e6ddb00-cc0a-4bb8-b92a-9c21d28489eb}} and level {{formula:890e36a4-fb27-4913-968c-22fb96b3eac6}} with Dirichlet character {{formula:1c3961fd-7463-4b76-b1ff-c00edc74a8fc}} , and let {{formula:996bffca-7c9e-4f5e-9c58-602b669261a3}} be a square-f... | r | 0abad5d7fd93258be659bca03fe9848d |
From tables REF and REF , it can be found that the branching fractions obtained based on S2 are generally much larger than the ones based on S1 because relatively larger decay constant of {{formula:cd57e8c3-43a8-4df7-b733-f5ddfcc1af47}} and form factors of {{formula:1d997ef4-6654-4917-bc1c-3f20a07076fc}} transition... | r | 233feaac62a6e7b33a28aae804c34f47 |
We have comprehensively searched for the {{formula:0b4ec994-e4b5-46b9-adfa-ff1e8381b88e}} modular invariant lepton and quark models with the lowest possible number of free parameters. After heavy numerical analysis, we find that the minimal lepton models make use of five real couplings together with the modulus {{form... | d | fb673ddd799bc0f785cc4edfeb72835e |
Over-relaxation steps are made of non-local moves (REF ) and (REF ), which flip the signs of Polyakov lines {{formula:38929ff9-e084-4312-87d1-22a945357368}} and Polyakov planes {{formula:89c0c0e6-625c-4e9b-be6c-b16de257bc14}} , respectively. Since such transformations do not change the value of the action of a given c... | m | c2bd4f6e29afe31359fe681a763312ca |
A natural next step would be to produce similar VEB methods for
non-Gaussian (i.e., generalized) linear models
{{cite:c0ee4a6cefeba3116d8f7f7b9f506a49f74a042e}}. Extension of our methods to logistic
regression should be possible via additional approximations that allow
for efficient analytic computations {{cite:7cafd4e... | d | 96cd0154ea20adce160aa8106910627b |
In addition to circuit depth, another metric associated with boosters is the success probability.
In the case of ideal boosters (not the truncated boosters analyzed in Fig. REF ), the more that a booster suppresses high-energy eigenstates, the lower the success probability will be.
In our numerical simulations, we had ... | d | b24cc801bf557b75232619703f43c80d |
A theme that has emerged recently in reinforcement learning-based multi-agent control {{cite:007bcfccc504db28d07d23a70a1b49eab9c131c7}}, {{cite:dc6c07a560fa4a9eefd0cd0a3ef517b8fe8a63f4}}, {{cite:688d0f0201f5104adf9305abf2fb6753e518b3d1}} is to obtain decentralized, cooperative policies {{cite:034da0c5def3fd2986b383b899... | d | d1669a3d390a3a64ddec61d83f533f79 |
We used the entire 3D lung scan with both the right and left lungs to identify clusters within our images. We used a similar CAE as in our simulations, but changed the 2D convolutional layers to 3D and reduced the second convolutional layer from a stride length of 1 to 2, to reduce the number of learned parameters whic... | m | 2e98d92329fc9207dc74ca41a3afa853 |
where {{formula:a73ead71-cd08-4d30-a40c-8f7a2224868a}} are the neighbors of {{formula:77a5b4ea-1224-423d-8eab-c83d3fa420b9}} .
Shortest path based heuristics are generally more expensive to calculate than neighborhood similarity as they require global knowledge of the graph to compute exactly.
The Katz index takes in... | m | a4a443b8a86e8b137aa9fb16ad4baaea |
The precision control available in ultracold atomic gas experiments has opened up a platform where models of condensed matter physics can be simulated in a relatively defect-free environment. In particular, ultracold atoms trapped in optical lattices are described by Hubbard models {{cite:a09270b65f16d9d7b4ac61d77f6474... | i | 2411b56ec936ceeab268ec95da087e26 |
with {{formula:4d6f9ea2-dda4-453a-805c-a3b7a744eb19}} and a one-to-one correspondence between the cosmic
time {{formula:f88b787d-a0c2-47e7-88b9-dc0ec2858e5c}} and redshift {{formula:bcbe8297-cf85-45a7-b887-1fbe3c17f4ba}} {{cite:03a856d18e491067e4f2c8eca765204a2de24550}}. Such simple relation,
which was first used to... | m | e6fee940faf8d45a45ba9a6e11ab8866 |
Logic programming {{cite:1d95a4d99fe673069d56b32a1e3eea8dd5113cc2}} has been applied to many areas such as fault diagnosis, databases, planning, natural language processing, knowledge representation and reasoning. During decades of exploration, researchers have developed various semantics for solving different reasonin... | i | 8fde53201afd7115c0557614892a73d7 |
Theorem REF ensures that, given a suitable penalty {{formula:b74e307f-f73b-4016-9637-2e18b582f538}} , one can carry out the valuation procedure with finite number of basis functions and obtain the same convergence result as {{formula:d3adeb9f-9c38-403e-b984-2c407416f2eb}} increases. Furthermore, the number of basis f... | r | 63b23399821828dd32f36f086fdd8cc4 |
where {{formula:9f523d0b-b13e-4c7d-9951-9e2cbd816132}} and {{formula:e37f2f15-4bc6-4d7c-827e-050bfcb74136}} are the assimilated solution and the truth, respectively, at time {{formula:03f17a9c-0bc0-43e3-a460-0b747b04ac36}} . The time averages of the assimilated and the true time series are denoted by {{formula:8f735b... | r | 7d3081a013cbfbbf206d7a92dee50372 |
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