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Developing an ideal emotion model for AEI is a complex problem. Existing models either do not provide enough coverage {{cite:313a51cea15a32262b08a56b60ddd73cfe6e48d4}} or include excessive, overlapping labels to describe the space {{cite:98e677cfaed65973834486a5d3453ecb5532a35b}}, {{cite:cf18193a8e73e17a283e7d80bec6fd5... | i | aa2e7ae9ef18863a68317ae4343b72b1 |
{{formula:e9cf07c1-88c6-4c38-9b66-837dcfb4425d}}
classic All samples of target domain (size is 2000) are positive samples and texts generated by DARL with same size are negative samples. The processes of pre-training and training follow the work{{cite:5e5a833ed233e67ac1d0ddeba59c12064bc131e0}} with {{formula:4806a2ef-d... | d | d5aec150121bd353e338f6c0cf388d30 |
In this section, we present the results of utilising a Punzi-net in a search for {{formula:e8bb20f8-5568-4b5b-814f-83e1ae9fedb7}} signals amongst various common backgrounds found in {{formula:141c4972-345d-41e1-b7e5-b3dce80659ee}} collider experiments. At the Belle II experiment, this search was performed with the co... | r | af8c28e1978162eb2d48a853d217b861 |
For this task, some of the most successul methods are successors of xNetMF: SEGK and RiWalk. Both methods generalize the structural connectivity measure between nodes beyond degree alone, which RiWalk notes can be ambiguous {{cite:f28b25ac9ab40678652b00dab6a3b682a9686990}}. In particular, both methods use the Weisfeile... | r | 283b44663dac85fd58132a66892684fc |
Transfer learning and fine-tuning aim at reusing the pre-trained weights of a CNN as an initialization for a new task of interest. The CNN model Inception-v3 {{cite:cbfceea48338288f9d7d5fde51f47e046f356101}} devised a new module named "The inception module" which is a 4 parallel pathway of 1x1, 3x3 and 5x5 convolution ... | m | 4a70b38725b8ea972b91013b64543a15 |
Deep neural networks (DNNs) achieve cutting edge performance in many problems and tasks. Yet, it has been shown that small perturbations of the network, which in many cases are indistinguishable to a human observer, may alter completely the network output {{cite:4d4a3b15cf406bb3e1ed9518548b8746569a1030}}, {{cite:8732f4... | i | 27cc407b6a13c9c8e6db9b243e1531e1 |
A major challenge that arises when maximizing the objective in Equation REF , particularly in applications with high-dimensional spaces, is that it becomes trivial for each skill to find a sub-region of the state space where it is easy to be recognised by {{formula:1b41db0c-77e7-4491-af0e-4801153c4aec}} . In preliminar... | m | 3e66d9c946c51f7339d7199cd595bc28 |
Prinzipiell basieren alle Analysemethoden für Big-Data-Probleme auf etablierten Datenanalysemethoden, die seit Jahrzehnten erfolgreich eingesetzt werden. Diese Methoden stammen sowohl aus der klassischen Statistik {{cite:d429ddb16de6f9bd94bff970e65a718fce4859fc}}, {{cite:089384a5d862c6b1b10347b91e8ba633c0c14ab2}} als ... | m | c0904a00a6272723af303f997db09f11 |
Anomaly detection has always been considered to be a difficult problem due to its subjectivity. {{cite:04c6e0eb97992ea40e111e82f921f84bfa41ca7a}} clearly stated in their classic book on the subject that the major problem in outlier study remains even after surveying the vast literature: “It is a matter of subjective ju... | i | 9b09001337055f146ace231c9b9ea64e |
Although mathematically simple, the {{formula:94f627f8-4266-4011-8f0e-a4b410e483e5}} CDM model provides an excellent fit to a wide range of cosmological data. However, an exception is emerging in the Hubble constant {{formula:dc7a7733-845a-4147-8398-2c73e8e37a26}} . In 2018, the Planck satellite measured a {{formula:84... | i | 695131850d87785c8c84d0f92d4bd3e2 |
In this paper,
drawing on the analytical learning theory {{cite:3e16d5d48956f5f81a37e0ee603b1a59ad7d920e}}, we rationalize that
1) disentangling and 2) self-ensembling over the stochastic latent space
will improve the generalization ability of the model.
Based on this rationale,
we investigate using unsupervised disent... | i | 94f4757bb0dcb05af259124cf71aaf1c |
The algorithms in this paper bend themselves to a broad family of problems which have been considered in the quantum computing world. We have illustrated the solution of time-dependent partial differential equations, but the same techniques can be extended to stationary problems. This way, the MPS-simulated quantum reg... | d | 278f932aafdd3af91ec3a470ce52b906 |
Lastly, a fertile ground for exploration is extending
BORE with classifier designs suitable for BO more sophisticated paradigms,
such as in the
multi-task {{cite:131a6cb37524b1595f790d8c99b0e97c760e0a0b}},
multi-fidelity {{cite:eb371cdf56a0da15458baf1daf906759e72142dc}}, and
multi-objective settings {{cite:bda81dc0a8f1... | d | c8a15abef7867b09642dd447200288d8 |
may be computed explicitly, to become part of integrable probability. Here {{formula:79c30f4d-ff23-4c96-b2a3-6aafefc36ee3}} stands for the time 0 whole-plane map from {{formula:a66655da-24c3-4815-803b-60e64991c211}} to the slit plane in the corresponding Loewner process. Note that complex values of {{formula:0832193d... | i | 36a45b89318abb84fe7cb161a4841378 |
Our techniques have certain advantages and disadvantages compared to simulation with the stabiliser formalism, and its elaborations in Refs. {{cite:05362caed4f0d8a63e1cbfa1fef482ae01d3317a}}, {{cite:0516594436d0970c40ccb0535884cd1d4561d58d}}, {{cite:31b41c315383ca3746e4b0d29b3a1ebfd8a6b845}}.
Those techniques uniformly... | d | da8590cfc6d336de2f15d2fa3ff70b18 |
Ablation Study.
We conduct ablation studies on several vital components of the proposed method: dual-path attention network (DPAN), dynamic deep linear kernel (DDLK) and DCLS deconvolution. The baseline model uses DPAN architecture and estimates a single layer kernel (SLK), and adopts the kernel stretching strategy fol... | d | fbc34dd11fd668f63234db5cc9ecef9d |
Based on the above two key observations, we introduce an interactive explanation framework, CX-ToM. Unlike current XAI methods that model the explanation as a single shot response, in CX-ToM, we pose the explanation generation as an iterative process of communication between the human and the machine. Central to our ap... | i | 1b930ea9ddf751f8c11209eaeee4f5dc |
However, other co-citation frequencies do exceed the seemingly modest frequencies noted for delayed co-citations. For example, {{cite:c70f387f2c4f14095f7c84fb3f61fba88160272d}} and {{cite:b3f49258c84b8767192a047ae6ed685f78cb6af9}}, a pair of articles from the field of physical chemistry, have been co-cited over 51,000 ... | r | b785fa0deaee1eec6395ddf88e529a7a |
With more accessibility to computational power, several variants of BERT have been proposed for different domains. For example, BERTweet {{cite:b175824ad6c15b6120cc13ea4fbfad38c0efa7e3}} is a bidirectional transformer model trained on twitter data and can be particularly useful for analyzing social media data. CT-BERT ... | i | 7bd3532daecfbfaf99e3ea07e75bb74a |
In this section, we review the fundamental rsults for abstract linear evolution equations by semigroup theory; see e.g. {{cite:1759d685cd81b039e14a84e5ac642fc857a4c595}}, {{cite:732b5162b824c3a21e73e3e9b6642d5465a1f585}} for more details. We consider the non-autonomous Cauchy problem (NCP) as follows
{{formula:08940bc4... | m | 8e3edc923df1d6eaa5b4914601c62702 |
In addition, we can explain the latent space of our VAE model by a post-ad-hoc method: mapping an observation to the latent variable and reconstructing the observation by a sample from the neighborhood of the mapped image {{cite:76aa9857f6b1ab61340a07cc6cb053756438b062}}. Since each observation has its own representati... | i | 80618ac6ce7a07b29aa3b6c305dff3dc |
Although these two model classes can generate similar sets of neural trajectories, different approaches are typically used for fitting them to neural data: parameters of LDS models are in general inferred by variants of the expectation-maximization algorithm {{cite:deb3702c9d9ce5009eaf80b879813376c6f1cef4}}, {{cite:3d9... | d | 3e589e140f4fd209dd2420f1e52dfab1 |
Deep reinforcement learning (RL) algorithms are in principle capable of learning policies from high-dimensional observations, such as camera images {{cite:04b8311caa7bca7dd0eb4c6564ea1d340771404c}}, {{cite:36846e7958e40d5fcd26b154d740356c04a2aa31}}, {{cite:75b20921939ca2e28091ee00eb307f13ec364f94}}. However, policy lea... | i | d51723d4202c3410eedcbb7b04c5581d |
Recently, some works {{cite:f231965e3ab1c116cc94ece2b6aa1b1c71b23c26}}, {{cite:4565332c0f3e38b110f7770da2747b3146bd8305}}, {{cite:e9a3cf2bc8067e2918945bf923e5ed3e894f84a8}}, {{cite:9f85512db259efd0791844531797f301c1c7794d}} used Fisher information, natural language, active learning and deep reinforcement learning to de... | d | 0e4589eaa18e4e85c9d0f8aa3f9a34ab |
Another limitation of most DA methods is that they are not guaranteed to satisfy the governing equations and conservation laws. A possible remedy to this is to use physics-informed neural networks (PINN) {{cite:3c9230f9c9d4ecaf4cf4d3538ac2f844c42400d8}}. In recent work, PINN has been used for superresolution and denois... | d | d39c92f538d4b08ec022d5deba47c6ab |
Baraniuk et al {{cite:c4a1b8da3586da5abdb016f98b6c72172e3ad530}} provides a bound on RICs for a set of random matrices from concentration of measure. For these random measurement matrices, Theorem 5.2 of {{cite:c4a1b8da3586da5abdb016f98b6c72172e3ad530}} shows that
for positive integer {{formula:4938913e-63ba-44a7-b09d-... | d | 2408dd89b56460753648ecd91c82d6d6 |
Attention mechanism {{cite:4e09ebb01dcf59a3fd62fa4b4738c37e5172c46d}} has shown remarkable success in human body {{cite:9fc8feb25bc469d3af568eb1cd0b083c6e0c7e7f}}, {{cite:f42afc3ede109fa06da6a33e1bd8a28eb16dc67c}} and hand pose {{cite:15619b5e6ff31f977223fe0fafbc2fbe2df4a4af}} estimation as it can effectively model lon... | m | f81470bb56ac194f3593b7f22f9cde49 |
Theorem 2.5 ({{cite:2e9c37505b4923ccc96bdda0b75e396053cfd891}})
Let V be a complete metric space and {{formula:86c199e7-6995-4d10-a5a5-61ad1309867e}} be a lower semicontinuous functional on {{formula:bc52c497-bf4c-4e00-ae58-e16801a06c71}} , that is bounded below and not identically equal to {{formula:e5d428c4-f8a6-4b2... | r | 2b76c2671d64d517bbdecdcbe368d307 |
In conclusion, we have demonstrated a strongly localized and almost radiation-free magnonic defect state introduced by a point defect in a on-chip magnetic array that is coupled in a long range mediated by the surface acoustic waves of the substrate. Such a defect state is demonstrated to be even inertial to the non-He... | d | f0f1dad14366de4ce40c3a469f76c6b9 |
To examine and compare representations from different models, we need to design a fair method to learn these models and collect respective representations. To that end we consider three types of models: discriminative – {{formula:f01a7707-7dfc-4451-bddd-e674227965e0}} , generative based on Autoencoder – {{formula:84762... | m | 76cc1ea908f057c5ffd7c2bbee4006b5 |
We now recall second order estimates for admissible solutions from {{cite:695ed9ce09bcd6055bbe4a4219ef48e5b8bcf5bb}} and {{cite:1dc9ec9ee361977d16dd05528d270c1e188d8f46}}.
| r | ad153c7bbe5c562c27ae000511efeb3c |
Proximal Parameter {{formula:a7836c39-8c9c-4d75-831a-b4faf18f5983}}. To counter client drift in non-IID data distributions, FedADMM and FedProx both use a quadratic proximal term for the local training problem. The proximal coefficient {{formula:eb933d4f-783b-428d-84ce-c76b2e015177}} in FedProx has to be carefully tun... | r | 1d9bed5d73e685f952ac77a200ce480f |
and {{formula:01aa3db9-ac3a-4a69-b99b-118d85a2b58f}} was obtained in Refs. {{cite:e10b1cece7e895f5b34f7a4990e4f1ecd9c725af}}, {{cite:e8095ff050b83975954420bc77f7219d392ffcae}} as
{{formula:a9892728-994c-49cf-9803-844ceb5b2614}}
| d | c395d5d6c46b70c1980d0a094e0561b4 |
We shall impose more assumptions on our domain. For both the “free boundary" and the “direct" results, we will assume that {{formula:7f44bafd-f93f-4166-9c65-91db77815b87}} is a 1-sided Chord Arc Domain (see Definition REF ). For the “direct" result, we will rely on the assumption that {{formula:6d995b86-44f3-4a81-bd52... | r | 55ca7165ee1a0c9fa4a95242afafc725 |
Effective model complexity is a relatively new, promising and useful problem in deep learning.
Detecting effective model complexity during training helps to investigate the usefulness of optimization algorithms {{cite:dba7cf5ea21a48bde1510caa659d72ccc4bc89a4}}, the role of regularizations {{cite:63ef9ec4c4713c1dc9a15d6... | d | afe8f447709ed556f23b3be294a9eb5c |
As shown in Figure REF , Figure REF , Figure REF , Figure REF and Figure REF , we provide qualitative results on all the benchmarks, which includes PASCAL-5{{formula:81e9ac9f-788b-47ea-ac30-b39954c7b027}} {{cite:b7daf20240bd8f388508ad25d9fae9ab94b37fca}}, COCO-20{{formula:c95ec50b-2197-4e6e-86b7-89fe67819597}} {{cit... | r | e4f5903c980029445e15f811b2492ca7 |
The proposed adaptive distillation method can be combined with most existing distillation methods. We combine the proposed method with ten state-of-the-art distillation methods to demonstrate the superiority of the proposed method, including FitNets {{cite:ee007c375454b286b48c3850188e725586f79254}}, AT {{cite:8e5a3f69e... | m | 8e46c57cf7d28dc6d2c05ef522e83537 |
A space {{formula:96f7d349-d5cc-4da6-b17a-48575b2c863c}} is called countably compact if any open cover of {{formula:55e42291-e38d-4a6e-9a9a-6d5d5fb8fe60}} has a numerable subcover. Since each Tychonoff countably compact space is pseudocompact (see {{cite:1fcca68422436ee18bf5d7411a799932ad649027}}), then Corollary REF... | r | b704269caf4a206e658b0ce2bfac2035 |
Remark 1.19 We should note the difference between our Generalized Mountain Pass Lemma (GMPL) and the following
theorem of Struwe( {{cite:2c565a4539977685e98ebba5a5962966c8645448}}): Suppose {{formula:a4dc569c-1c4f-468d-9ec3-b4fc60a3e914}} is a closed convex subset of a Banach space
{{formula:16c747cf-141b-4b1d-a66e-29... | i | 3c33d788854147310d0d9658474518b8 |
These are the solutions studied by Landau and Lifschitz in {{cite:9310cb1f6db2f9df38a047c1ec6ac87fada3e128}}.
| d | 37f205722c5f24d8445642da3dab73c1 |
Our algorithm relies on oblivious sorting, which dominates the asymptotic computational complexity.
For oblivious sorting, we use Batcher’s bitonic sorting networks {{cite:e634f494b03e455ebeecc4a942320da50f61da58}}, which has {{formula:3c24c9da-6b28-4dc3-a7e5-5528ac37abc6}} time complexity.
Although it can be improved... | m | a92c41eb5f626bd6722d62a484652adb |
We explored white-box attacks neural networks trained with gradient descent. In our experiments on the large QMNIST dataset (200,000 training examples),
Deep CNNs such as ResNet seem to exhibit both good Utility and Privacy in their “native form”, according to our white-box attacker.
We were pleasantly surprised of our... | d | 0282d7cce56dd942e76617117c04fdc6 |
We used nnU-net as a proxy for extensive hyperparameter tuning, as it also integrates hyperparameter selection for medical image segmentation. Whenever possible, DL practitioners should use improved hyperparameter optimization strategies other than grid search. For instance, simple strategies like random search{{cite:1... | d | 9ae3038199a2ee4c43a28a52936fc7bd |
By Proposition REF , it suffices to consider the {{formula:e5b4bc96-bc92-4ec9-8d55-5088128d4b7b}} distribution. Let
{{formula:9f2937d8-205d-4c3e-9c9f-6dd94f61400a}} be its density function, i.e., {{formula:622117ef-703c-42cb-9f85-e7dccf3ae1d7}} as in (REF ).
Fix {{formula:49da6c01-d249-4e17-83e3-f151be03c627}} . To ... | r | 4e61e2521a99c534183512f486a55b04 |
Many complex processes can be viewed as dynamical systems on an underlying network structure. Network with the dynamics on it is a powerful approach for modeling a wide range of phenomena in real-world systems, where the elements are regarded as nodes and the interactions as edges{{cite:88003113759ade809e5dc4f87efd5e41... | i | 99018e0e7b2cc71a553098e1c4842721 |
According to Ariel V {{cite:86bfe0414dc1bb31ec3d4c23fbd794e5eb3f9bea}}, CGRO/BATSE {{cite:0b990289e9e6f535d737069fbc1d916a5be5786d}} and Swift/BAT observations, the time separation of {{formula:548cd92d-d912-4ae2-b12a-d1ef78f801cc}} 17 years between the detection of each outburst for 1A 1118–615 suggests that the neut... | d | afaa685d057fbb6d7070f42318051fd2 |
where {{formula:a609d09f-6baa-466e-81e6-be3527f5c433}} is the quadrature truncation order defined in each subdomain, and {{formula:ff06d91d-2ea0-4a91-9b5c-8abd2351e13b}} denote the values of the integrand at the quadrature collocation points assumed to be the Legendre-Gauss-Lobatto points {{cite:fddb0139a8b014b3e0c2a... | r | d48a3340978305fd5ca1d83780891ef5 |
Despite the advantages of collaborative learning, there are two major concerns input data privacy and vulnerability of locally trained models to information leakage. For example, model-inversion attacks {{cite:6b594202c77c744a3df9d6e7677c1fb59926ca6b}}, {{cite:265dbda88f245343b35119c22da78a7232b04f50}} are able to rest... | i | cc211d31977c0ccecb9878a48daac93e |
Paired GANs cannot handle such unpaired I2I translation problem (Fig. REF a).
To combat this challenge, researchers have proposed various unpaired GANs, by using the cycle consistency loss {{cite:9d087780906c0a8754025f54d5f5cc039c556aff}}, {{cite:631701e6df286db3dec6bb4d3cc8e8685d57956c}} or learning disentangled repre... | i | 894c3de5055964c2a2861ab6c10d5423 |
Third, in addition to testing, analysis techniques should also developed to understand the root cause of the system violations. To achieve this, more research efforts on the fault localization and repair are necessary.
Threats to Validity. In terms of construct validity, one potential threat is that the evaluation metr... | d | 46b028ff26dc2bb61577d1922df634be |
According to the long-term photometry, another properties have come out in this case. Although there are some small variations, the main shapes of the light curves are usually the same. There are always two minima, and they are almost constant according to each other. The analyses demonstrated that one of the effects o... | r | 6e14e09edd9f2399c966349c00782c50 |
[Proof of coro:1]
When {{formula:1a0ee85e-e274-4f7e-a9fe-d480016d6b13}} in (REF ) is true, {{formula:dbaecffa-d169-40b3-b2ee-79be52cfa472}} is an independent copy of {{formula:2b7d4a74-9345-45bb-b91f-580c577e980c}} for {{formula:651c4b44-cacf-4825-bddf-8fdeb244aa29}} , which, along with the fact that {{formula:73acf... | r | b2eb46d610481f48840751fdc446d17f |
Strongly interacting holographic systems have proved a very useful arena for understanding chaotic dynamics of large-{{formula:e23a89fb-77a7-45b5-ac28-a376480758d1}} theories and phenomena related to thermalization. These have in turn developed our understanding of quantum gravity dual to such strongly coupled systems... | i | dd0d6cf549bb6f1543378bb03b14ebdd |
Designing separate dnn-aided edge devices to form a deep ensemble is a consideration that has to be accounted for in the training of the models. For once, the individual dnn have to be different from one another in order to benefit from collaboration {{cite:0f99dd943e0d2b52bd801adec4f0950f7cf0305e}}. This can be achiev... | d | cb3ab80df92596ca0326e985fd0f3b5a |
In Fig. REF , we compare our method with two recent proposed stroke-based image-to-painting translation methods: 1) “Learning-to-Paint” {{cite:5fbd490b33c1bcec3f0de9233bbad91ff8af126c}}, and 3) “SPIRAL” {{cite:bd16ee7ad6b9988dc0d4a7e5148986a71fa9c171}}, where both of them trains RL agent to paint. We can see our method... | m | 7596edf7793df0eb439e57389ae4f1c6 |
Due to the non-stationary between individual sessions and subjects of EEG signals {{cite:e6ab9f6ec61fb9685539ece3ae3c61279fa828ee}}, it is still challenging to get a model that is shareable to different subjects and sessions in EEG-based emotion recognition scenarios, which elicits two scenarios: cross-subject and cros... | i | 6fc3154d16564b8f74cf32ebdab8b1c5 |
The first attempt to overcome this dimensionality curse was the {{formula:d8b17633-b146-46c3-94d0-63a3e80d9eb8}} -tree {{cite:5cb9db75ce997152699a1fb714441d8e1face83d}} that subdivides a subset of the reference set {{formula:a27f3561-6aa3-4133-b6fc-1074c73b40af}} at every recursion step into two subsets instead of {{f... | i | 84a13b88ff99f706177923e1eb751297 |
The loss function, as expressed in Isola et al., 2017 {{cite:f3b0c45ec931d3634d2fd1a16acb1fa1f436e159}}:
{{formula:64ea86cc-8085-4dc1-a504-7a8fc3c96deb}}
{{formula:ca53e3da-4b7b-4f27-8811-33d20603efb4}}
| m | 83a8d861072eef521053a623c6852f87 |
In this section, we set K=3.
To be specific, the lengths are set to 16bits, 32bits and 64bits, respectively.
For fair comparison, the experimental settings of our model and other methods are the same as that of DCMH (please note that the experimental settings of this section are different from Section REF , more detail... | m | b23a652d7fa0a418c81a87c03a9d202c |
Visualization of Feature Distributions. In Figure REF (b), we visualize the distributions of the features using t-SNE {{cite:fc4f1ee19406be73162fc2722ac53354401e6e09}} on MSMT17. We compare the feature distribution with the baseline scheme of All, and observe that the features of different identities are better clearl... | r | 59c0985a4f4ac8cfe4d565468f91f8c8 |
Model. We build our models based on ELECTRA {{cite:a52ccfd062ba5931b5ef658d15b31c43253c04c8}}, since it is shown to perform well across a range of NLP tasks recently.
We introduce randomly initialized task-specific parameters designed for each task following prior work on each dataset, and finetune these models on each... | r | 44da9825bda491b44ef8cb658c6b335b |
Despite the past three decades of thick-disk studies, there is still no consensus on models for
the formation and evolution of thick disk.
The proposed simulations of thick disk formation can be generally
divided into four groups: (a) accretion from disrupted satellite galaxies {{cite:dd190df89fa8826a5ddda5bc1522c109ec... | i | 6d2b4c86b028a3ee3e77370c97df7219 |
We are well into the era of gravitational wave (GW) astronomy with
the rapidly growing catalog of GW events detected by the LIGO-Virgo collaboration {{cite:a16009cc8246474bb73036203f438927eecf2265}}, {{cite:8e897cc197ac5480aaf0db20c1a909fed5bb976d}}.
| i | c9bd7884d0af2ba03397f25e171ef6ca |
Language is not static, it evolves continuously {{cite:b8346ac26e2564b72131194ba70dab2c3d3c1a31}}, {{cite:8f0914bc5994b06a6ed12c44deedaa448d1f9839}}. Social and technological changes are paralleled by changes in the language used to describe them. In the nineteenth century, who or what was performing work was changing ... | d | afdc19a2a009898e21ba300772d8b203 |
Third, pooling of treatment estimates can be done in several other ways than presented.
In general, the pooled treatment effect over clusters is a weighted combination of cluster-specific estimates, where the weights aim to balance aspects that influence estimation and are imbalanced over clusters (e.g. cluster size or... | d | 600f951980664fd9ff7e8b5530d9491c |
Next the NN will update its weight values in the policy network based on the gradient descent and back propagation algorithms. We will keep repeating this process time after time for many episodes until we sufficiently minimize the loss {{cite:55f841f286d6d7c20c1b9ce11d32ab8250279597}}.
| m | d0f3b9fca46e1f137e26e323b88f31c7 |
These models {{cite:5cece5899561e931007ea04483404065e8eabbd4}}, {{cite:61111a20831b686fb0ecaa4e6aaf71608b1658cc}}, {{cite:61111a20831b686fb0ecaa4e6aaf71608b1658cc}}, {{cite:13e0da0d60d9ae278ead8d4bddc31abae10b08c2}}, {{cite:5205db0dc479702347d12eeecd362232aa4a31a2}}, {{cite:13e0da0d60d9ae278ead8d4bddc31abae10b08c2}} pe... | m | 00f6947a4e6ceda22136bde7a172f097 |
Network assortativity is computed through the Pearson correlation coefficient {{formula:4d15c5fb-1887-431d-9349-0e77fce5dab4}} between two nodes connected by a link with positive {{formula:d6937da8-7905-4b46-84e9-afbc35d042b7}} with a value in the range {{formula:2ce14eaf-7928-4edc-a0e4-53300289b8b7}} ; while in case... | d | 6ba3b03491a49136f1124d056d8448b4 |
The BNNT, filled and annealed samples were all characterized by Raman spectroscopy with excitation by multiple laser sources (see Figure S1, Supporting Information). In most cases, the Raman spectrum was buried under the photoluminescence background originating from color centers present in defective or strained boron ... | r | 145b904853e0bcfe17245193d7ce5d78 |
There are some works employing other distributional approaches to semantic shifts detection. For instance, there is a strong vein of research based on dynamic topic modeling {{cite:61acf271292767940db647dd168ca772d2187278}}, {{cite:bd49392e0cfe498624c7e5c73070e9532dae61ac}}, which learns the evolution of topics over ti... | m | a0dfce504fe156f83a0a9d93e36f6951 |
Beyond the previously mentioned technical limitations and challenges, the methodology does not provide information about a lower limit to the true error, as it would be required for judging the sharpness of the error estimator {{cite:5812f54f220561bda8a07c547529dc7f8434435f}}.
| d | 957470d047f0682ad7008a55ffd9599f |
We have studied the dynamics and propagation of jets launched from a MS star moving through the envelope of a RG star. We followed, using 3D HD simulations, a set of jet models (either self-regulated or constantly powered, and with different kinetic luminosities) in three phases: when the MS is grazing the RG, when the... | d | 89f79d83e7b5f35901d0c731d9680b05 |
We now turn to the implications of our results on the surface charge. The observed hole depletion and electron accumulation signifies a positively charged surface,
suggesting the presence of empty, positively charged donor states. The change of the surface charge to negative under illumination with blue light
requires ... | d | bb0e1278bd87d17df338c12c04737051 |
We further find that mergers are important for the formation of the most massive clusters. Mergers are much more frequent in Region 1, enabling massive clusters to form on shorter timescales, compared to Region 2, where they are minimal. We see similar findings in Rieder et al., submitted, where again mergers are more ... | d | 4ab1b389ae3c95d68cbe78ac252727c3 |
To show how different steps affect final performance, we also conduct an ablation study in Tab. REF (step one is required). We find step two is more important than step three in improving final accuracy (90.8% v.s. 89.8%), but both contribute to final performance. To intuitively present adaptation performance and the ... | d | bc92af71b099ce55b284503a01c01c99 |
For each {{formula:7277feaf-54e7-44f4-9dd4-3ac056c50243}} , the {{formula:b9f5ca6b-9b20-4a49-ba92-768d7a9321eb}} is swept from 1025 to generate {{formula:912193a1-334d-4ba6-9e58-62d90678df19}} {{formula:7d383a62-a35c-4e8e-9d7d-fe4de176804e}} values and {{formula:b83435e8-a056-45ef-b1f1-c80df2f73163}} {{formula:2085... | m | fb8abb87e823ad4cc5afe3aeaac8c8e0 |
In conclusion, we list the main results of this review and discuss problems that have not yet been solved. Among these problems, the most important one concerns finding a sufficient condition for collapse. Recall that for the focusing NLSE, such a criterion was first obtained in the two-dimensional case by Vlasov, Petr... | i | 0edb9323f218647fae5048b2b7cb39b5 |
To closely examine what the weakly and fully supervised ResNet models are learning, we plotted Class Activation Maps {{cite:71cd360c973795a3e658693370793627a01ab73e}} of a normal and PVC beats in Fig. REF . It is evident that to discriminate between PVCs and other beats, our models are primarily paying attention to the... | r | eb03ddfba2e49c9e8c4d219ad2b34065 |
From Figs REF and REF one can see that for times {{formula:d6740c43-42d6-43c5-989b-cb3586efac24}}
there are such time intervals shorter than {{formula:d2aaca3a-d3eb-4897-a96b-11cdd4f5163e}} , that {{formula:7ae62e53-cd82-4173-9efc-01556d3f2a69}} is positive at some of them and negative for the others. In general {{... | d | 8eae170dc36edc0b9775d220bddd933f |
VGG-13.
The VGG-13 {{cite:8dac97487066fd90891ec95759ed3acf731170ae}} model, which is trained from scratch, achieves an accuracy of {{formula:961107e0-4e01-463c-9d97-011e0122d05d}} on FER 2013 and an accuracy of {{formula:05897d1a-282c-4cb1-8cd6-591f156f7a93}} on FER+. Since the input of the VGG-13 architecture is {{f... | r | fe355ae459b941d5e0feff94837182a4 |
ANNs based on photonic technologies developed for telecom applications {{cite:7aab735e3565f2bd292beefc3a98dce1a42a0c48}}, {{cite:dad1df8647e3ea12215e430da3bbedc1fcfd86e2}} can represent a valid alternative to conventional electronic hardware for the achievement of a significant reduction of the operational power and in... | i | 312a1ba494f637085979810341b2e922 |
For each theorem, we randomly generated 100000 sample distributions (observational data and experimental data) compatible with the causal diagram (see the appendix for the generating algorithm). Each sample distribution represents a different instantiate of the population-specific characteristics {{formula:61784e08-243... | r | 5662946f95d0901c8e97ee9e209db4af |
Observations of compact quiescent galaxies, `red-nuggets', at {{formula:ea52687f-850b-481c-a96f-6774574b2240}} have triggered a fruitful debate over the onset of star formation quenching and the factors that may affect it in the early Universe {{cite:638418a1a671c7f7786347e8bf9fa3e84a4ce6e0}}, {{cite:39a15a935b49109f7... | d | fcfaf61fd79c46bb2e806788d1a48fad |
Additionally, we have investigated an important limitation of our method: accurate predictions require similar mesh connectivity, i.e. our method is sensitive to remeshing of the input surface. We hypothesise that this limitation can be alleviated by data augmentation. We find that PointNet++ is more robust to remeshin... | d | 7581f61244abd6eb10ca15c9afb8d589 |
Let us then recapitulate the present work briefly. The study of precision cosmology is not possible in GR frame work until we completely know the physical system, but it provides a way to model the deviations in Einstein-Hilbert GR action. Deviations from Einstein GR theory are indeed predicted mostly in various extra-... | d | 015c3f247068d1fa5adb370c395fa115 |
Popularity of this GKLS master equation, many times referred just
as Lindblad master equation after one of the inventors, has been
and is remarkably extending in many fields in non-relativistic quantum
physics. It is understood as a Markovian effective equation of
open quantum systems {{cite:5b4760336195cdddb26c882091c... | i | d5e3f83ce9dbf0cf217831ca94a18782 |
Despite these uncertainties one particular object of interest in the first catalogue of gravitational wave transients is GW170729 {{cite:72a737c7bd929f8fd9f23ad0751f19ca2dad31eb}}, for which the effective spin was reported to be {{formula:76c3afa3-2920-4b5f-a02a-30c36c03560f}} with a mass of the primary BH of {{formul... | d | e3f98928d62fa33fda18894133b36e59 |
Matched-filter based analysis defines the False Alarm Rate (FAR) of each detection as the number of false positive detections with an equal or higher ranking statistic, where ranking is assigned to each positive trigger that passes the SNR threshold of the detection pipeline and inter-site travel time requirement {{cit... | r | 924520f84583f24d01b4244ea7ac6178 |
The use of handcrafted ORB features, extensively used for SLAM {{cite:ef14116b0652264a435ef5b1fd20d632ae336c2f}}, performs well in between the storage aisles (e.g., view 2 in Fig. REF ) but can also perform poorly at the end of the aisles, where lighting conditions suddenly change, leading to unreliable feature matchin... | r | ae3be212acfbd0861cce35f1ae9678ad |
Beyond our framework design and the compelling motion capture results demonstrated above, there are still something to be discussed or improved.
First, since both video-based Human3.6M and 3DPW do not provide global trajectory for training, our video encoder cannot encode the global motion trajectory information, like ... | d | 67ada5bc3539d444f8bd3ff2a1d05fd0 |
Involving different kinds of noises, the dynamics of the density matrix {{formula:420f40af-1d15-413b-880b-536d8938eb0a}} is govern by the well-known Lindblad equation {{cite:0380a3f64e32d8dbdf338393dddf83730fda123c}}:
{{formula:21658f1a-0d04-486a-b4a7-59f20e9612c5}} . Here, {{formula:3969a2e9-1390-450f-a4da-2b128076b3... | r | 302c13c2430f1a6077cb5ebf52cbcb25 |
Figure REF shows the impact of stellar rotation of the Stromlo models on the ionizing photon output. The rotating and non-rotating stars show broad agreement with each other; discrepancies between the (non)rotating models are only significant at the highest energies shortward of 228 Å. The minimal impact of the stella... | d | c30906d7a828f926ecfcbf6a5a23c06b |
High dimensional graphical models have become increasingly popular, over the last several decades, for understanding independence and conditional independence relationships
among components of high dimensional random vectors. The challenges posed by the estimation and statistical analysis of a graphical model with many... | i | 3a4d6211b9543ed13e17133670362e05 |
A first implication of underspecification is that ERM is insufficient to guarantee OOD generalization.
Identified cases of underspecification point at the need for additional task-specific information in the design of reliable learning methods.
If such information cannot be integrated, learned models are at risk of une... | d | 7a1075119396c82777b0fcc24f310321 |
Recently, a multitude of machine learning methods have been proposed to enhance and accelerate physics based numerical solvers in the context of electronic chip simulations. For example, a Deep Neural Networks (DNN) based fast static thermal solver has been proposed in {{cite:163862bad49bacde2fbd910f49c74bb66d7c9087}} ... | i | 9f6ff5f0989ec1bbed2db230ef15c28b |
We test denoising performances on the images corrupted with noise-levels {{formula:1a67ab4d-1a11-453e-b271-c8446014f327}} , on three famous denoising datasets for color images: CBSD68 {{cite:56ba3b5e57e5ab8c957fd2a4855b1c3ca6eb422c}}, Kodak24, and Urban100 {{cite:a3bdb6103e00eb29dfa7c8ae264439a27276fcef}}.
Importantly,... | r | 251eda221cd0fc8a642d0b1e3e00570f |
In this section, we evaluate the performance of the proposed algorithm.
There are {{formula:6f8801a5-c056-4a98-b5e9-428d40e63681}} users uniformly distributed in a square area of size 500 m {{formula:8bbcba86-5860-4b29-9ff5-62138fa49da9}} 500 m with the BS located at its center.
The large-scale pathloss model is {{fo... | r | bb41969e0f61826d70d429789bf3388d |
Due to the large number of possible labels, using standard Transformer models is not feasible. Instead, we cast the type prediction task as an extreme multi-label text classification (XMC) problem: given a question as input text, return the top-{{formula:7c10edf9-35ba-4da1-bd4f-a93af474c3e0}} most relevant types from ... | m | b47117f02c05378299544a453da2a142 |
There are two main unresolved issues with regard to the application of CNNs for medical image segmentation. The first issue has to do with the training procedures and training data. Specifically, the number of manually-labeled images that are available for training is typically very small compared with many non-medical... | i | 7b527480b429abf33add07d5223b742d |
using some scalar {{formula:153db040-b326-451b-b3cf-f093679958f9}} . Alternatively, and more accurately, we can use a method akin to automatic differentiation {{cite:604927793700293c746622d7c9ea437fcecd6a72}}
to compute the Hessian-vector product.
| m | 16328d5ff6a98016b7181d79cc70dbb2 |
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