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This variability can be attributed to the known instabilities of large pre-trained language models {{cite:1cd790f9955556830827f7abc6aadce8d33d1ead}}, but this does not explain it all. Choosing a right set of data points is another extremely important factor in few-shot learning that calls for better selection of traini... | d | 942f71fd251b2c112d7700d0052d7e8f |
Figure REF shows the total energy consumption and training speed normalized by the energy and speed of 2-GPU training. The DimeNet We note that the authors of DimeNet have released DimeNet++ {{cite:326505a9c9e876a488becb005222e58b3c7d2eb6}}, which is an optimized architecture with faster training that may alleviate so... | r | 263dc362e9ba0cad2f95e35b191d57ce |
Motivated by the powerful expression and approximation ability of deep neural networks, in particular the great success of convolutional neural networks (CNNs), the deep learning based methods have become the mainstream in crowd counting and made remarkable progress {{cite:27c2686566afc917094fb028406cfb6e2b2cd4e1}}, {{... | i | dd9c81342b6c92f2416a770014e3ae62 |
is small, where {{formula:7171dd6a-4574-4b86-ab17-109373624268}} is a pre-defined value and {{formula:0e225536-e754-4234-a6a3-94cb1b270aec}} is some loss function {{cite:82c8216e773f20963d65d3a564aadf6defa8d030}}. This simplification helps analysis and implementation. In spite of this, the robustness with small {{for... | i | bb5cd9cc453626e73f5b5d62dcacd86a |
We evaluate all methods using three metrics, i.e. {{formula:72b10cfa-e7a0-4ac9-b2cd-3880e21650ad}} , {{formula:46098c7b-70de-4066-ade1-b4526a9d98ed}} and {{formula:483b1b49-674b-45b3-8faa-aa817fce4b95}} . {{formula:60754b3a-c744-4487-a5ec-62986fffba47}} ({{formula:0375eae7-a847-4496-a179-bba244c0290c}} ) denote the c... | r | 6526645e14ec4ae38b15117a0cb84113 |
Colour Normalization: Because the images are from different sources, various lightning conditions change the visual appearance of the skin lesions. Traditional conversion to grayscale images would lead to significant lost of input information, therefore we aimed for colour constancy algorithms. This topic was already c... | m | f5b118de458af51a4ec3a3c33a5c4ace |
The next lemma summarizes comparison theorems
for Gaussian and Rademacher averages, see
{{cite:8cc2accd9b6bd520678dda3306382d245d103123}}.
It will facilitate generalizing
the equality (REF )
to an upper bound for {{formula:3a895ace-3635-43e0-a73d-becd21a8e021}} -norms of
random variables of the form
{{formula:67f1c145-... | r | 939390caa63856eda9a73fcf68b6b4c0 |
The key challenge in our problem setting is that we must optimize the parameters of the encoder and the conditional NeRF MLP in the decoder from a collection of unposed single-view images. Inspired by earlier work {{cite:23e094a3263d0dd8120302660015b158175614fe}}, {{cite:42acafc00a69227d0b474b1bc6272433e345ad27}}, {{ci... | m | 68f428c3fdd5958b1c2f07f1984c7f94 |
Here the energy release by {{formula:ce28c8ce-3cec-4b24-9239-ea0a9097ad00}} O burning is {{formula:78bb62a5-cc1c-4c29-a795-bc72308e1122}} per nucleon {{cite:9287c776cd47f78028eb70f771cc12b44c34e7b8}}, {{cite:1b82394e7c4387758b132d58ae8ce5a5ef44e78a}}. The contraction timescale of the helium
core is the dynamical times... | d | 40555f233ef14f894b4d47b7889ca1a5 |
This brings to one of the future directions. We would like to augment or replace VTP with pruning tecniques that actually consider the importance of a group of weights (dimension in VTP is one type of grouping) for final accuracy. For example, Taylor pruning {{cite:92080eea6d29491443f17ea61f726778951a4b84}} estimates t... | d | a57268ac1880f2c9b1f9bd7d8ddb5240 |
We have studied the quantum integrability and chaos of a {{formula:e6cb42d1-52cb-4310-aaf3-3e0acf533803}} d chiral SY model consisting of N copies of the SU{{formula:c72ea350-d9ad-4b86-8750-1f568a660a98}} chiral WZW models with chiral current-current interactions among each other with coefficients {{formula:074699ab-f... | d | b4d618af06012090dc45b31836cd8637 |
The {{formula:c7fa085d-fed0-4efb-a766-a084115bec8f}} branching fraction {{cite:3704b27aaa6902ca7d8852beb0267d3b84247c61}}, measured by B AB AR {{cite:10fbc21b0e79cea05c1f9008abd3d9bfb7bce8a5}} and Belle {{cite:493f08453dc847a257622eadea9dcff2fd477079}}, is very sensitive to contributions from a charged Higgs boson.
Th... | r | 469bcfa87b030266dc0e41fcc5183144 |
The 5 different neural networks were trained over 3 random seeds, and the best overall performance for each one of them was selected. The evaluation procedure is similar to the AutoML benchmark in {{cite:20b0074da92960defa6b2a5eb682808788c8eb1c}}, {{cite:25d397c362ddf1fb676f937b5172ffbc7e1883ee}}, and the benchmark res... | r | 38be9f57feadbe0af1661b234a6544ea |
We have used our unitary trilinear Hamiltonian model to investigate issues of entanglement between various bipartite divisions of the modes involved for both short-times when energy in the BH is roughly large and constant and at late-times when the BH is evaporating.
Specifically, we have examined the entanglement (via... | d | 037dfca3d92b28568dc18b2d9f82b7ad |
Our analysis has been able to determine that the existence of the islands does not only depend on the microscopic parameters in {{formula:332ef83d-5ca1-4bcd-bb37-986e3ded481b}} , but both on {{formula:0088479d-c92a-465c-bc72-b4689eeb3f67}} , where {{formula:a4bb69d3-a403-4777-8235-a97135b334aa}} is the variation of th... | d | ab192f3daace3e1717f4072cd4936225 |
Our primary contribution is an approach to generating and evaluating personalized content in games in a way that is independent of both agent architecture and game. The agent independence is achieved through using the OpenAI gym interface {{cite:e10aee755ebfe055b923ba35aaaa1143d79d1491}}, which is already widely adopte... | i | d77e338e1e201b0ab9caa7e4bcde64e3 |
Such a crucial rôle of families is reminiscent of the
KM mechanism {{cite:f320b3c3d59074f9113a3ef53f28c897d44773f8}} for CP violation which is non-zero only if all the
three families participate as shown by the Jarlskog determinant {{cite:f31f58b33462e0ca7bfc5fa5801eabe6c2faab3c}}.
| d | 2605a3738017957027cbcd1a659b3a85 |
This article comes last in a series of three articles where we investigated
the conditions for a more biologically plausible self-organization process. In the first article {{cite:d72a5d80fbb4ef302c7e7b38787a688b302bb7a4}}, we introduced the dynamic SOM (DSOM) and showed how the time-dependent learning rate and neighbo... | d | 7fb1fbe5afd9d64366493f283b74b5db |
Our work demonstrates the effectiveness of neural spatial representations in solving time-dependent PDEs and observes empirical convergence under refinement (see 3delasticityconvergence). Future work should consider theoretical analysis {{cite:5d631ce7d8e4412d2b3be9f3cd59619f74595d84}} on convergence and stability. Mor... | d | bda0a5fb975dd4f2bc6ba1c5cb56ca79 |
The method is compared with current state-of-the-art methods to show the effectiveness of the developed parameter optimization. Only methods using RGB-D data are included as these have the highest performance.
We showcase the results using the CosyPose {{cite:cc60376deef68af0cde251c3ef39a41900c2b933}} detector with the... | m | 9d6605335d367be1c57ac6d005dabd27 |
Now we discuss the broad comparison of the band structure and FS topology between ACo{{formula:73e48642-6205-4713-a23c-eb1f124240aa}} As{{formula:1be2b3cb-3591-4474-8f9f-a21e2c821667}} and AFe{{formula:bd8cff21-30fa-4e9e-8c50-6c6c315ff86d}} As{{formula:7b244b92-b500-4d72-a79b-ee8b136a973b}} compounds. Overall, the el... | r | b710a69e74a5099bea66aa0367f82d92 |
While B-tipping can be found and continued in system parameters on applying tools from theory of autonomous bifurcations {{cite:bb932d2915fc51f61f77fbe5e5e9d908819b4a43}}, {{cite:6da4c92a582db8005b16ab0e043e939b69af162b}}, {{cite:73c6da3d3b370238bdca430409e14ea9a608c9c0}} to the autonomous frozen system (REF ), this is... | m | b24f3bf26d9180d9688d5da346be3127 |
Existing observations present a complex and incomplete picture. Many studies have found evidence for a reversal of the star formation-density relation at {{formula:6dd1073e-f7f7-487b-9f0d-7293a09f50c7}} , with enhanced sSFRs relative to field levels in overdense environments {{cite:7543c8ce0dc8e6d8dde355a41e450560b6370... | i | e79e3efc379c6509b573c686d19b4422 |
Another approach to study the non-perturbative QCD effects is the rescattering mechanism.
In this framework, the non-perturbative QCD effects are modeled as an exchange of one particle between two particles generated from the short-distance tree emitted process.
It forms a triangle diagram at hadron level.
The rescatte... | i | acebf6d14b1cf3533d6c53f15e61d270 |
In our results, we evaluated four different matrix inverse calculation for our regression method which are Gaussian Elimination with and without secure computation, Secure Inverse Method for matrix inversion, and regular inverse calculation (without secure computation). We used linear Support Vector Regression (SVR) {{... | r | 7aa04f40a41ff4a0be4dcac98707506b |
Here, we investigate skill transfer from a high-resource language, i.e., English, to a low-resource one, i.e., Bulgarian, for the task of multiple-choice reading comprehension. Most previous work {{cite:a3a235993e7473ed92482cb9f023f7becf900f39}}, {{cite:fe3cc18c8eee0c21b3daf43d7e808af16c7b0c55}}, {{cite:4832967eb6096a8... | i | 8903486823e85bcafb8a5fc8a1541b50 |
Figure REF is the overview of hierarchical Crossover-SGD with hierarchical communication. In this figure, hierarchical Crossover-SGD is presented in three steps. The first step is to reduce the gradients of the worker nodes in each group. In this step, we reduced the gradients for two reasons. First, it utilizes compu... | m | dd4360ade53cf82d757c07dda898724f |
Next, to demonstrate the universality of the proposed concept based on an example, we design a 3-port ({{formula:6251627c-1b90-468c-8c77-f66cb51a4c51}} ) metasurface power combiner. Without loss of generality, we specify the angles of ports 1 and 2 as {{formula:32ea0eb8-f1b6-4695-aa24-4da5073c56b5}} and {{formula:2487... | r | 4906316d4062c653bc5e75f720b2c292 |
According to the manuscript, the Chamfer Distance is with L2 norm.
However, PCN {{cite:b70c1427485ff482a8449b136d6d3d59cad1c642}} adopts the Chamfer Distance with L1 norm as an evaluation metric, which can be formulated as follows
{{formula:5f0535b3-375f-4da3-b465-2df34f71a4d2}}
| r | f930f74da2c2eb8e87fa21a449043082 |
The Brunn-Minkowski inequality is a fundamental geometric inequality in the classical Brunn-Minkowski theory. It gives the log-concavity of the Lebesgue measure and implies the
classical isoperimetric inequality in the Euclidean space. Gardner's excellent survey
article {{cite:3437d79abd37b384663d219026b15923e73973af}}... | i | 5a6913ba060d571df53787ad1f81681b |
{{formula:bd548639-cf5c-4a37-ab50-be2e47281218}} is strongly elliptic with respect to {{formula:d7ab1272-4c3c-4cfe-bab7-1b970cd53e25}} of arbitrary order {{formula:741f5e9a-393e-4d04-9f0b-68b68889138d}} Examples are fractional operators of the form {{formula:6e9e619d-7611-4822-b8c1-92166836b348}} {{formula:e49b1ac... | i | 01cade58edc8e8d122845ffc298dd805 |
In contrast to the standard differential privacy model {{cite:7d44c4344cce59a52d3a9e35cc164780789644b3}}, in which the learner collects the true data while releasing a private output to protect privacy, in the LDP model, the learner only has access to corrupted input data from the users. Hence, LDP often provides a muc... | i | 16a7314c8b5ba2e99b9dd29f6257a2c2 |
In this article, we have derived two analytic RARs (one for the hydrostatic framework and one for the NFW framework), which are applicable for the central region of galaxy clusters. The analytic RARs are particularly good for describing large and massive non-cool-core clusters. In fact, many previous related studies fo... | d | 57f31e9eb090e515e324bebc5c80f67e |
Several methods have been proposed to learn disentangled representations.
Here we are interested in evaluating the benefits of disentangled representations that have been learned through unsupervised learning.
In order to control for potential confounding factors that may arise in using a single model, we use the repre... | m | b410c30082866895b087221aaf255c73 |
Recently, the availability of large annotated training sets and the accessibility of affordable parallel computing resources via GPUs have made it feasible to train “deep” ConvNets (also popularized under the keyword: “deep learning”) for computer vision classification tasks. ConvNets features are trained from the data... | m | fb8a4cdfd71ad88528add658cec44aa2 |
Different data sources. In practical settings, it is of interest to learn the graph from heterogeneous data that may not be independent and identically distributed. Examples include data collected from several related populations that have common structure, and data collected over time. There has been some work to addr... | d | f0e1d62a603e004a446d848b8a3ee3ff |
Our results:
We propose an exact algorithm for the DkConP problem. The running time of the algorithm is {{formula:2d3a7e93-ef2f-462f-8092-ebd1b8de6e97}} , which is an improvement over the previous best exact algorithm (running in {{formula:95761adc-a09a-43fb-af78-b11a03099000}} ) {{cite:6920f87ee41e931613d3d3bbd6762196... | r | 9faa454a9d9ee569619684f584d99260 |
Theorem 4.1 (see {{cite:d3c79b6672a00449ea1f00aaac0bb62dbe9436a4}}) Let {{formula:c718465a-a5da-4d85-aafb-9c669d171db6}} be a proper lower semicontinuous function. Consider a sequence {{formula:c7b766c5-a1a5-4f03-928f-27c0248d4255}} that satisfies Condition (H1)-(H3). If {{formula:d236543c-93b4-451a-8feb-aa77ba57cf7... | r | 86c754e8f6a349f28332e2ab155aa3ea |
If the higher frequency flux densities at 15.5 and 31.4 GHz from
{{cite:c7a2142c54adc2f9f7c61be06437acd3af7bfc48}} are discounted – see
Section – the available flux densities in
Table REF (see Fig. REF ), apart from those from
{{cite:7470045944947c13d0de7e0e8f43a3c34ce064af}} are consistent with a flat radio
spectrum... | d | 7d35f228d0a7c97f3a595047f987c43a |
In this section, we will solve the BS equation numerically and study whether the {{formula:8d6510d8-77d7-489d-8af0-ef865274ac33}} -wave bound states composed of two pseudoscalar mesons exist or not. In our model, there is only one parameter, the cutoff {{formula:65c4b523-816e-4db3-a154-819075f521c4}} , which comes from... | r | e343b959d389680b4fa51f4f3af0ab2e |
Using advantages of both facial and gait analysis, we propose a method to automatically annotate the gender of front-view walking sequences with facial analysis models to generate training data for a gait-based gender recognition system. Through experiments on the popular Front-View Gait (FVG) {{cite:18356d2738ce322e88... | i | 8372a1d45465b9a34cccf8dba8b5da44 |
The final accuracy for each model is reported in Table REF . One can observe that our monolingual French model performs only slightly better than a multilingual model (mBERT), which could be attributed to the characteristics of the PAWS-X dataset. Containing samples with high lexical overlap ratio, this dataset has bee... | r | b6d5a83746858379f3be6507cc2120e4 |
As the first step in the numerical solution process, the initial condition given in (REF ) is used to specify the slip boundary condition (REF ) for the flow problem. The self-propulsion speed {{formula:5e3e77ed-6d67-4f24-8f54-4e61b1f73a86}} at any instant of time {{formula:83b132d8-0246-497f-ab89-422fe6fe5eef}} must... | m | 7036ac77190a58c1adc695235b0860f1 |
In the diffusive limit the Green function can be expanded up to the first two terms of 2D harmonics, namely {{formula:dc1ad96f-cdee-404d-bbfc-f050bd90a52c}} ,
where the zero harmonic is isotropic and its amplitude is larger than the first harmonic.
We substitute this expansion into Eq. (REF ) and perform an integration... | r | d3869e930f3687ef4dd9a3d7273261f0 |
We compare our results with SRC {{cite:39e39cc692cee0d19cd39148b268072ecc141996}}, LC-KSVD {{cite:c8f522b8f1be6040f760b1880f4f0dbd58d0cd31}}, DeepSC {{cite:a0d329756d498233515aec57e24c69b9a00211f2}}, DSN {{cite:67188ddacb60a9cc43b6ba9f3ef9eae9fa6c01a2}} and other state-of-the-art approaches: ScSPM {{cite:d118e8225e5549... | r | 0b5e23d61bd0c369a35402ef2a436400 |
Transformers have revolutionised the natural language processing (NLP) domain with their ability to handle context over long sequences of data and achieving human-level accuracy for various tasks, such as language translation, text summarization, question answering, language modeling, and text generation {{cite:23b1ad8... | i | 25ea3de7e760d87d8bc0680df952056c |
We also implemented two other deep learning architectures with pre-trained word embeddings, Word2Vec and fastText which were extended with GRU, LSTM, and CNN deep network layers. Word2Vec {{cite:a0d721cb2565bbb1bdd6ad71f5f073d10011c136}} has been quite successful for SA across several languages, including Bengali {{cit... | m | cf33f84f5b5b646f23674794453299d4 |
The proposed method was validated both qualitatively and quantitatively on the T1 modality of Brain Tumor Segmentation (BraTS) 2018 databasehttps://www.med.upenn.edu/sbia/brats2018/data.html. From a total of 210 patients each with 150 slices, we randomly selected 16 patients for testing and the remaining subjects were ... | r | 6bf7524d1120bf6b775b3d7e4ab34e37 |
We study Euclidean SU(2) Yang-Mills theory on the hypercubic lattice {{formula:b049f987-34c8-4656-8bb7-24c52cb479a4}}
with dimension {{formula:a9c541d1-b704-4a35-849e-4072e029930f}} . It is widely believed thatSee, for example,
the book {{cite:1f22085d3391a7bbefcf3e9dcb72a80ef7ff39de}}.
the gauge theory shows a quark ... | i | 4e74c3a7ed4fee9d98f703ae43b37dd1 |
Our work builds over an extensive literature on entropy-regularized reinforcement learning {{cite:b0c1985b650cee35bc0931a054c4a458154c841b}}, {{cite:06502b0fb773bdd663d79aba571c975933f8a697}}, {{cite:d9cafec80f6837fba859ed8dc0c055227840d4cd}}, {{cite:e9a6adc603226dbb358fbcf5955aba62f59e2331}}, {{cite:1c7abce49d5b1fc351... | i | a0376319f0c19d237bc7ed4f25329798 |
In the previous section, we showed that the IVA cost function is a special case of the TRINICON cost function up to an additional factor of two originating from the representation of complex-valued random numbers. To this end, we simplified the TRINICON model by relaxation of the linear demixing model to a circulant on... | m | 65a5f6d414cabcfa5f84cd3d2033327c |
(2) Controlling the superfluid in Fig.REF c:
The SF is flowing with a finite velocity {{formula:1ea8d480-6d37-4951-85df-a1845fcda2a5}} . It was discussed in {{cite:1d9c56fcab2db5564e0df7d88416378518d70f9e}}, {{cite:2e1056a8b59673f29b3fcd999f2b347c6d248c1d}} and more recently in {{cite:6216a8bfd27bb3c21ac1be78c2760e750f... | i | 14ab756933838e0307c2f72371582112 |
A key in the analysis is to carefully utilize the design of the stochastic estimator of the gradient. Traditional methods that simply use an unbiased gradient estimator of the objective function are not applicable to many problems and also suffer slow convergence due to large variance of the unbiased stochastic gradien... | i | b1c2e048591a925c0f2faeb59b07f2c9 |
Performance Evaluation of DispNet-B.
To further compare DispNet-B with other stereo matching methods, we evaluate the performance of DispNet-B on the subset of Flying Things 3D (clean pass, disparity {{formula:75244377-1c4f-455d-a560-869140bd6bf2}} 96 pixels) test dataset.
Since we only care about the results of predi... | d | 232e59d788d7be2e97e1fb40673de01d |
We have now extended the renormalization group functions of QCD in the
{{formula:560c781e-f06e-47d0-883d-32541bc9a160}} scheme to five loops. In addition the 2-point functions of the three
fields are also available to four loops in the same scheme. However the results
of more immediate use provided in this article are... | d | c6d494224a6dfe8f4d956cd3a0224703 |
To the best of our knowledge the graphs scaled to in this work are the largest successfully considered by learnt heuristics for Max-Cut – with ECO-DQN {{cite:6a6ff09f19932313a4727bf8b5988c2d43acda51}}, S2V-DQN {{cite:62a0e58d7187907335b55ae9a6496ab6aec9c49d}} and the RL-SA algorithm of {{cite:729268959f596c82901dfa653d... | d | aefa393e15979fc6df5bba6f7948cd88 |
In the imaginary time formalism, the one-loop integral associated with diagrams such as the one shown in Fig. REF is given by {{cite:68e30b4e338f90d55d9799355406f45b927acdfa}}, {{cite:5f2e297d6251eea70839b5e628947092a5b70ad7}}
{{formula:f9d014e3-0b6e-40db-8aba-9f71c27ff3da}}
| m | 8925e0cfab41f5be2bb7276e24a2bc9b |
For the computation of the scalar spectra, we did not create gaps of the temperature time series to distinguish between the gas and liquid phases. This is mainly due to that the response time of the thermistor is comparable to the bubble residence time and the bubbles have similar temperature as the surrounding liquid,... | m | 037fc8027fa105f912413731e55ca952 |
Classification models transform CE into classification {{cite:358bb60246a7550a5e644c599f3ff71e98e19dde}}, {{cite:21a641e84c8415ec82921e9a36ad63b85b65ce0a}}, {{cite:f090763682f1404d5a6fd76ed757953865deea64}}, {{cite:10a931c5242366df05ca079f0f794ea0c0015a0f}} to determine which concept in a predefined set meets hypernym-... | m | 96fe064d59954aa6b47dfc5f3e83bfe0 |
Other pairs of modalities.
We were interested whether the improvements obtained by CrossCLR are specific to video-text retrieval or if the loss generalizes well to other pairs of modalities.
To this end, we compared CrossCLR to the NT-Xent loss {{cite:58d1e77deb9edf83d7346f33345e3e70b1672574}} on various combinations o... | r | 7a2ae8ee3d835300d22e625d7dfcccfc |
The proposed method NeXt, based on the FCM clustering algorithm, outperforms all the other implemented necrosis extraction approaches in terms of both spatial overlap-based and distance-based metrics.
Adaptive thresholding using the Otsu's method {{cite:542cd67e032538b39a89be7f0d6325cb482adfcc}} achieves good segmentat... | m | 031e38b759e8f09f6df31a213b66845d |
The F555W and F814W HST filter exposures provide the deepest CMD of the cluster available to date. The theoretical Padova isochrone ({{cite:c004a43d4305bd9d82b3a5a1532b7c018165264d}}) that best fits our CMD suggests that the distance to the cluster is 10.5 {{formula:33ff6f73-1655-4ad0-92b8-c93ca9ad5720}} 0.4 kpc, it h... | m | 33e1ea2b89dba309b8006c4db9989f7d |
Text Generation for Audio Recognition. In Table REF , we test our model on audio recognition task. With audio only or both audio and image as inputs, we calculate the word error rate (WER) between model's output text and ground truth. The compared methods include several API from Baidu and IBM companies and a state of ... | r | bcf674cfb1e85b0ea4b836de38b8ee28 |
We use PyTorch to implement our tree optimization algorithm, denoted Ult. Tree.All code is publicly available on https://github.com/chens5/tree_learning. We compare the performance of our method with Sinkhorn distance {{cite:aa9b9e314ce8d4ef68b9dedb661036251b6eec2e}}, Flowtree {{cite:4befdd8513869d9a9287ce2211ca213f518... | r | 1fbeba5ff6c3f95aba738b102481eebd |
We conduct simulation studies to demonstrate the performance of our methods. First, we compare our proposed inverse probability weighted (IPW) and multiply robust estimators (MR) to the outcome weighted learning estimator (OWL) of {{cite:582dcbd326a87d736563d6feef137f5031136add}} and the IV-based estimator (IVT) of . I... | m | bd159c176f081896a112b5f5496b6de8 |
Knowledge graph (KG) representation learning is important to the KG inference as well as the downstream tasks {{cite:ff2beddb3968e35ea02e0a5bbc7fe7caf076eb96}}. It has been noticed that the embedding space has significant effects on the performance of KG completion tasks. Previous works have proposed the KG embedding m... | i | ae2638a91edaebc9035d09500585c9dd |
As a first attempt, our studies provide the baseline for the future
investigation on the correlation of helicity polarization
induced by the axial chemical potential, which is a possible signal
of local parity violation proposed by Ref. {{cite:fec3e6efa278cd490e0ab21293224b89b2538734}}, {{cite:5f4276a9aa1c5ddad473ed882... | d | 371b176bdb2de2ed93ff8b097686ad57 |
To further demonstrate the effectiveness of our method, we follow the same setting as that in previous methods {{cite:053082d1aa4936f76f6b5931a0bd3460c148130b}}, {{cite:81396f763af11ed2210cf758904a1de2bcd7163c}}, {{cite:632bc3af727b17087fb5bd06371535cfe3601283}}, {{cite:c61769549817b033f9bf1601a04dc0a813f9cc81}} with d... | m | 4c5eda426e9833cf256b1e98d8af2006 |
One natural question which arises when preparing a neural network is that of model capacity {{cite:d343de2f1fd4efb230d23c51e8325e345c3a2b92}}. A network which does not possess enough cells or layers may be unable to take into account all the complexity of the task. On the other hand, a network with a very large number ... | d | 138efdd82bb66ee5fa5d1679b0f3232b |
By Abreu and his coworkers {{cite:0576680117bb1566b07bdff6ae402fbe2f8490e5}}, {{cite:86013608f855cb3f36e0f5c6d9071a424f6d93b0}},
the DPPs associated with the
Schrödinger representations of
{{formula:370aa221-5822-44bd-a101-0722bd634e18}} are named as
the Weyl–Heisenberg ensembles,
in which {{formula:a41409bf-e175-46fc... | i | 56cdc9dd42229b5c268276f205747196 |
where {{formula:743e4bfb-0693-4ed9-9ee7-af0240815310}} . The above expression could be modulated by a factor {{formula:ada77aa0-9bbe-46ed-be45-2393e64888f6}} , where {{formula:657ff096-3139-4fb8-b3e4-26519798585f}} . However, {{formula:0bfb45c3-e2e5-4588-b325-2a1ae2ce0671}} appears to be the most natural solution whic... | r | d3809b916367c00c1e4b4255af41a391 |
Interpretability techniques should scale to large networks.
Frequently, small networks and simple tasks such as classification on the MNIST dataset {{cite:b72a951535aaabee5e90738b6d3611bf6780f1ed}} are used for testing methods.
However, we stress that simple DNNs performing simple tasks can only be deployed in a limite... | d | 80123b90d74db69257ee50e3afbcec2b |
Recall that {{formula:2002d2d9-4016-4004-9e21-28327de62b76}} .
A critical issue is
that the perturbation bound in {{cite:801d48d65a85ec588953737884d12b079b442bb9}} requires the tensor perturbation to be exceedingly small, namely,
{{formula:147f69ec-0f04-4386-b8b0-2c872fe19fcb}}
| m | 10ba8a3c228dbc6f0586dbe7c35b2b92 |
However, there are some limitations to this study.
One is the validation of whether our approach can extract true dynamical properties if used as an equation-free method, which cannot confirm the true dynamical properties (e.g. frequencies with growth/decay rate), as well as in the previous works {{cite:c22e05f89f19121... | d | fdc80427d64adab2154ab010c578bca0 |
As we are unable to distribute the GPT-3 version of Godel{{formula:d7a62772-c4f0-4b7a-8403-dce04c5ab730}} (Godel{{formula:1f5dbc2c-8b77-4fa4-b680-5164de7a602b}} below), we instead release Godel{{formula:14e00ca6-81c5-4184-b4e0-06d63d1500ce}} based on GPT-J {{cite:20fc3f092ce0dd7e68d7bf6f627495c2bae3b084}}, {{cite:60... | r | ce4209faf772662a2cae44eebe122ee6 |
Dark matter makes up approximately {{formula:34a59c1e-9fad-460a-b529-583464f3b6da}} of the non-relativistic matter in our cosmos {{cite:701b7f000ac37c68fcb4ac4953d774677fe167ef}}, but its detailed nature remains uncertain. For example, the mass of the fundamental particles making up dark matter can range from {{formul... | i | 35a3af19ee961d7983080a679e6cfc9d |
Post-hoc interpretation methods seek to explain why a model makes a specific prediction for a given input. At a very high level, these methods assign an important score to each token in the input.
There are mainly three types of interpretations: gradient-based saliency maps ({{cite:f6aa407b761bc757255cc2f426005b7f62250... | m | 3bbe7fdb2824758fc83b366de8109ba7 |
In this section, we first introduce a Full Self-Attention (FSA) module for discriminative feature extraction in 3D object detection that aims to produce more powerful and robust representations by exploiting global context. Next, inspired by 2D deformable convolutions {{cite:17d34a00495d50095c2797b52c5a4db93f96935f}} w... | m | 9e97bfdc315d6d19cf2198c97fb4c46a |
Our present work demonstrates that MSAs are not merely generalized Convs, but rather generalized spatial smoothings that complement Convs.
MSAs help NNs learn strong representations by ensembling feature map points and flattening the loss landscape.
Since the main objective of this work is to investigate the nature of ... | d | 4213d89cddf7d8ec38412b17f59df0b4 |
Set {{formula:b6059da6-61f8-46e4-a84e-da0137b239fc}} -Covering: {{cite:e0bf4bfdbcd98250396c352d5e78747fb56ecb22}} shows Compact Set {{formula:b252fbdd-e6ba-425a-bb02-866537a5dbfb}} -Covering is W[1]-hard; however, their reduction does not give tight ETH-hardness. On the other hand,
{{cite:b9d9a230d52fd153bfcdc861b33d7... | r | 30d425f1a83f6017d7d28f4e5e73cc80 |
First, it is important to note is that, for the best of our knowledge, all existent algorithms exhibits negligible finite size effects for {{formula:a5dcbfef-485d-4ac2-a573-dafca031f5a5}} . Indeed, it is claimed that the empirical behavior of algorithms matches with the theoretical behavior for {{formula:ccccf65f-bd6b-... | d | 2445b0d558fcc5cfaaa3f98a45639f14 |
In order to preserve the privacy of both the data and the model, there are several privacy techniques utilized in the literature. One of these techniques is differential privacy (DiP) introduced by {{cite:d595211392756c1b6809aa52dd3633b45a65269d}}. In DiP, to protect the privacy of the components involved in the proces... | i | d8a1184db4d6ab57aedb118e0778709f |
It is interesting to note that skyrmion crystals have been experimentally observed in various materials {{cite:49320b00bb977a138f76d3bd62eb144c7fa65ea7}}, {{cite:ee7ead88023b989faa23b3b339ab4b579b416620}}, {{cite:50b3cb385bd549a25c5f2b15ac432c25dbd108c6}}, {{cite:ee486745c09976630884ca2d637639adf23b2e2a}}, but the most... | i | 1b4430d9d82bb972363e441644b0705c |
We tested our network on several challenging real-world high-dimensional input time-series classification datasets: BasicMotion and ERing, which are taken from the UEA Multivariate Time Series database {{cite:d63bec668bba290ac890760a7cfd8708ef4be8bc}} and are freely and publicly available online. The results are shown ... | r | b35c4b62d813126a07573a3605713cbf |
In this paper, we have studied Einstein-Gauss-Bonnet(EGB) gravity coupled to a bumblebee field. We obtain an exactly black hole solution and cosmological solutions in four dimensional spacetime by a regularization scheme. The bumblebee field doesn't affect the locations of the black hole horizon. This black hole is dif... | d | 808ca20b9333da36011944cb4d88c5b2 |
The lower semi-continuity of {{formula:4386fed6-d10c-4674-9288-2de32fe915c3}} follows from the uniform bounded moments, Assumption REF and Lemma REF . The lower semi-continuity of {{formula:96bded70-bc52-46b2-b9ea-d3ce3e893522}} follows from {{cite:9e670280588ad337d8c1fcacf3b67d118d2f3aa6}}, since {{formula:52701446... | r | ee74c5df1559227b9e8addf7b1d18788 |
In order to evaluate the proposed method on a variety of state-of-art classification models,
we applied our approach to the CIFAR-10 and CIFAR-100 datasets {{cite:4eda5209139475b9f3243ace37f0c2cd66254d74}},
which are labeled by 10 and 100 classes color images, respectively, with 50k for training and 10k for testing.
Al... | d | d76a4290c8c60c254681c69db1df9d3e |
Safety, framed as the forward-invariance of a safe set, has become a dominant definition in control theory. Several methods have been introduced which provide guarantees of safety including model predictive control (MPC) {{cite:789b4e04d10d38f94554f4186e3e9373019a3007}}, optimal reachability-based methods {{cite:52e486... | i | 15e9ab0185363a7e96665be9fde89910 |
In the qualitative results we compare our proposed method PhysXNet, with LBS method and TailorNet {{cite:4e9a70ccdcbc3a400beb767a4f7b223571f125ef}} when possible. Moreover, we show the performance under changes of human shape and different cloth topologies that have never been seen by the network.
| r | 11d9ee606c69fb006cd39689638352a1 |
In the cases of (iii) and (iv), we explicitly model both the {{formula:bd53e812-0be7-455f-a2f1-96570314279c}} and {{formula:a8382a62-44ba-4c10-b245-f1f7ad2b84be}}
regressions, and also explicitly build in symmetry into the test statistics
to reflect the symmetry of the null hypothesis. The first two examples,
which r... | d | 42354e585376d0ac26dabc11b8afbf44 |
To further illustrate the effectiveness of the MCQ algorithm, we conduct more experiments on 4 maze2d "-v1" datasets and 8 Adroit "-v0" datasets from D4RL benchmarks. We compare MCQ against behavior cloning (BC), BEAR {{cite:18733e6c3c019e8215f9ced41f3845b14f5ed822}}, CQL {{cite:a93755ef3f2ca6620071fad9460212669b226e64... | r | c0d05498c23937741d6bcb027c309865 |
If the mask pattern is unknown, reconstruction approaches can be designed by incorporating several properties of the encoding mask. Correlation-based approaches can be used for recovery as the pseudorandom masks have approximately a delta function as their autocorrelation. The autocorrelation of a CA image is equivalen... | d | 5c479189849ea0471ff35683fb634960 |
For the {{formula:00db3ae9-bdaf-45ad-b377-333fe05fbac6}} -continuous, {{formula:93511f8c-99f2-4647-a8c4-8dda6886287c}} remains invariant on applying Eq. (REF ) {{cite:b1ca0d0969bfad7b262634699f10a5661f6cfbe4}}. When {{formula:861cb906-a53e-4e72-9a4a-46a942b5815f}} is sampled discretely, a variety of available numeric... | d | ce2e7a693b9ba8c32807de1c58964d78 |
Guiding an FCNN to the correct image features is a much more complex goal. The explicit ROI extraction is an approach followed by RV segmentation {{cite:cd1c5a9f22c3079c261563a9be209c28bea1024d}} and many medical applications {{cite:ba5d8e95520516ef77b0f6d818f947d81bcd639a}}, {{cite:573fdd6826e1d65d922dbee348fc6a2e455d... | i | 96513fe920a79d3d0bef1e96016a2cc6 |
For the {{formula:538d5318-f12f-4c78-9ef1-f97a2333b605}} interaction, no {{formula:2fee96a7-6136-409c-905d-831b86a3980d}} -channel vector meson exchange is allowed. Therefore no dynamically generated {{formula:623ede35-e8d7-49f8-b27a-083d65dbd697}} is found around {{formula:370d1899-6e2d-4007-a9fd-d1a90e677c8f}} thr... | r | 5136de91edf21cc6b2be4118ed224cb4 |
Whereas, HNNs directly predict the scalar value of the Hamiltonian {{cite:77e546b6f4f0f2ef8813f3f44fcffbfeb5386412}}, L-HNNs precit {{formula:8204428f-fe45-48e4-b5a9-85d51a5b3915}} latent variables whose sum is defined as the scalar Hamiltonian. Introduction of these latent variables improves expressivity and reduces ... | m | c7220f507c097cf3052a5e86f2ffebbb |
Third, we compare Prune and Tune Ensembles to state-of-the-art low cost ensemble learning methods with a large training budget of 200 total epochs. Along with accuracy, we report uncertainty estimations on corrupted versions of the CIFAR datasets {{cite:441b4e205e32d080df882d54a331490098e656a0}}, {{cite:bee46ec19444082... | r | dcca42a98330b727793c38560502f74a |
The proposed framework is depicted in Fig. REF .
We first process each view separately. In particular, we employ a 3D-CNN architecture with residual connections and spatio-temporal convolutions across frames {{cite:ec01d6e8907a483de62abe979ca55a122a28a179}} using a ResNet-18 as the model backbone {{cite:5fef4302cecdaee... | m | 216c2a7746c195cba70a7171a1c02600 |
Visual recognition has been dominated by convolutional neural networks (CNNs) {{cite:eb4dddcd8efdb171b91eb697fb102b0e04806b20}}, {{cite:3742e5684f875569e480ace6364eb53b876b036e}}, {{cite:c9093cbb4acad549c0a1a9deff35da8e5459a7a6}}, {{cite:1d406b3ef5c9257702191933d36eaa441017ca94}}, {{cite:a9b8870d1ec5b234141709e44b3de39... | i | a3981bc8d0ae7bf5b919c2228b44a688 |
Figure REF shows the cross-sections for all events, and for the same events divided into three classes. The top-left panel shows the total measured {{formula:496c30a2-e76e-4f7d-ac6c-86599b098792}} cross-section, compared to five models. STARlight is based on parameterized HERA {{formula:d16343ed-2051-4f72-a5c0-e90e36... | r | b0d63185421b21a85f08c3a44155fc97 |
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