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Weighted Data Sampling The long-tailed nature of the PBVS-MAVOC challenge dataset makes it very hard for the network to recognize and predict the tail class images. The network over-fits on the head classes as the number of images in the head classes are approximately more than 10 times the number of images in the tail... | m | 11179a17ce05cf29cf914789d7e4fc47 |
Considering the {{formula:3c8a31f5-73c2-452a-9fb5-3605ac81c1a3}} images, a texture analysis method based on entropy is proposed to quantify the patterns of different activities profiles. Entropy is a statistical measure of randomness and is formulated based on Shannon's equation {{cite:53b0e3d5fee87efd0f6138fafb8501b6... | m | 52be1975316b827b73c3832268c31d1c |
For model-free methods, we can first observe that the overall performance of the SOTA methods is much worse than their performance on in-the-lab datasets like the CASIA-B {{cite:ecee290065a2e5ade7b215a29fb6fad643d28a54}} and OU-ISIR series {{cite:89b97d5e6b09b434e20e6af81c4cb580aa5a3a9f}}, {{cite:ab29a3657aed63ebe29d5e... | r | 77c5aa3478d7c2747a76a0243de9cb90 |
Cell-free massive MIMO has been recently recognized as an alternative to co-located massive MIMO for future wireless networks owing to its substantial improvement of connectivity, spectral and energy efficiencies {{cite:24dcdb3146bbf8f232bfc96e4fc11143a3b13886}}. In cell-free massive MIMO, there are no cell boundaries ... | i | 97f334861be7063e7f8196580751883b |
We compare our FASeg with state-of-the-art semantic segmentation methods on ADE20K val {{cite:adb34ffd531484d96fc676a075b8808c3b88376a}} (Table REF ) and Cityscapes val {{cite:dc25fa666df91dd28b915c13e5b8255ac5cbadf1}} (Table REF ). Specifically, we show FASeg with two {{formula:54a1d542-6490-4aad-925f-c38266c0d975}} ... | r | 28df7edbc098ba44f8dfb6afa726f968 |
To reduce variance while preserving the stability and convergence properties of on-policy Monte Carlo policy gradient algorithms, various variance reduction techniques for policy gradient methods have been investigated in the literature; with the goal to reduce the variance of the gradient without introducing bias. The... | m | 4dd04dce6c2b0f5b39f73f9dc5c2dc39 |
Diagnosing entanglement in quantum materials out of equilibrium would be particularly impactful, as ultrafast lasers have led to the synthesis of nontrivial states of matter without equilibrium analogues {{cite:cce99f9895c09d2f526067369d0b538caf14d3b9}}, {{cite:70b78e55b006f1724402f521d65ece2ee05b229d}}, {{cite:9507dc7... | i | 67b91c504c90c94a0231974414c0952b |
Automatic Adjoint Differentiation (AAD) is a rapidly-growing field with a variety of applications ranging from biology {{cite:4d9e3012dc49ad1f80eefc0c0783825682d82f42}} to machine learning {{cite:4ed9786318432a44f317f8b112bbb4500fe5503f}}. It has recently become popular in financial applications for calculating sensiti... | i | c29ce7b12ad6e52b56f2ec308819ea9a |
In our works, we use the Tensorflow 1.13.1 {{cite:30113313c602eb6b649950b03b5945dc653b8ce6}} for implementing our algorithms. We deploy the UAV at {{formula:0e31d8d1-2c7d-4085-8bcc-fc890793ad40}} , the RIS at {{formula:86026878-a976-4055-8cee-203da12bc4e7}} and assume {{formula:d4939e63-1750-4d44-a23e-4e386311e654}} ... | r | 691ed285e1137afdb0f511141a348e67 |
The structure of rationale models guarantees that causal relationship between the rationale features and the model prediction, but this does not necessarily imply its usefulness to model understanding. Specifically, it could highlight {{formula:4385c5ad-6ffd-41da-98c1-9ea6a5d6a50c}} only barely, while including lots o... | d | 65a788d1574e8015318533cb19750710 |
In order to demonstrate the applicability of the results using NRF on a larger scale, we perform an experiment on the ImageNet-1K dataset {{cite:7ecd29e68d1ba3078c27d2c49e043f73acf517a7}}. The dataset contains around 1.2M training images from 1000 classes. A linear classifier on the original input images (150K features... | r | 818930676a44844e759196a9c2907adf |
In {{cite:6741d1c35dec7ad187f78c837e5298e8181edcca}}, the time-dependent Hamiltonian simulation problem (REF ) is addressed using the Dyson-series technique, giving query and gate complexity that scales with the {{formula:59b13896-6de4-4aae-aa84-a59999cc6cb8}} -norm of the interaction Hamiltonian {{formula:cf948f4c-128... | m | b9f17e5f80416ac774fca753abab255c |
Fig.REF reveals the influence of the pump-wave intensity ({{formula:4e3f2baf-7ba0-4e17-847c-a7a8c540c006}}{{formula:493027f4-a54a-4a94-8163-4836c76d677b}}{{formula:abf0c90e-389c-41a6-89f7-ca59d1d52949}} ) on the resonance parameters. The power broadening of the resonance is shown in fig.REF a. The zero power limit giv... | d | 8d776eab015bb372022fa20fd97a65c2 |
Due to computational restrictions, we were not able to run our method with RoBERTa-base and the same configuration proposed in {{cite:fbd481abf9d24f132d9130597f28b38fe4cb64ca}}.
However, we should expect some improvement when using RoBERTa-base (110M) compared to BERT-med ({{formula:4e6151a1-cb41-41a5-b3ed-c55542cd5dfb... | r | 84c8faa7a803f5733b5cd19fa32745d6 |
xg(x1)-xg(x2)Lgx1-x2, x1,x2X,
where {{formula:cb0a5a97-6756-4e06-826b-ff58b6f44ce2}} and {{formula:88bb3470-c0af-4af3-8b07-c9ce39a876f7}} represent {{formula:a115f746-9b76-4730-ba12-d29c7c3d1000}} and {{formula:35d7be56-d989-410c-af9f-e750d007d04c}} , respectively. Note that {{formula:e1baa983-ceff-40c6-b6b8-e6... | r | c8d65c04765e462e234b5b73ead02897 |
In the following, we show how to obtain a ready-to-be-implemented version incorporating ideas from the semi-naïve evaluation of Datalog programs.
Semi-naïve evaluation of Datalog, as described in {{cite:9dbe911605a33d1df322badc7acb16abb8eb5ed5}} introduces a number of ideas aiming at improving the efficiency of the naï... | m | 790be68c7c64105159bf2f0ad6ca5bcf |
The delay embedding dimension {{formula:16756fd3-14fe-43ef-b951-c65b82f7ae77}} and the time step {{formula:3d52a121-3c15-45f3-99c5-9fa7bfe2ff51}} are chosen to satisfy the equality {{formula:f0853a56-13a3-4f63-8cfc-9636dbd2f1d0}} , such that the delay embedding of {{formula:c877daaa-017a-43e8-b46c-c26c80057d51}} is ... | r | 4495e0f93f21419f7e83954b117a9d37 |
These methods, which are visualisations of the spatial variation in importance of input images with respect to prediction, provide post-hoc explanations. These methods can be categorised into three types namely function, signal and attribution visualisation. These groups of methods present different information about m... | m | 88d161e3205dea837305b036ec15b828 |
through an extra requirement that both {{formula:a6d48ef4-2381-4a7b-b881-2447c74a7218}} and {{formula:94a1f952-4ae7-4d8f-8965-b2a7c68a3eb0}} can not be too large.
This can be readily observed on the Petersen graph as shown in Fig. REF ,
and also implies that the anti-Cheeger cut problem may be harder than maxcut.
Act... | i | 47e832df63086350e46c7e32189bbe15 |
In case of Question Answering (QA) task which is one of the promising areas in NLP, however, models outperforming human on SQuAD {{cite:32e5b8c4a98d3f6e13d0c65b7f1c2c9074556a70}} cannot generalize well to other datasets. Models rather overfit to a specific dataset and require additional training on other dataset to ada... | i | 6a457d98fb534f81d4733ae55f6114ea |
where {{formula:4bcb82dd-d2d8-446b-afa8-b633f9f94853}} the validation set, the subscript {{formula:93697de7-1398-420f-9061-5387dd3fae5d}} denotes the class index.
After {{formula:713234bd-8151-4a89-9a5b-fd16f7d8a955}} is trained, we close the gradient computation for {{formula:db8b3317-32db-4012-8ddf-8207ff86ead7}}... | m | 8a5fe64486ca667977ae08f361d97809 |
In {{cite:0933bc06707dce20fef77ff2c19e3eb5dccd8a2d}} the author proved the following result, which can be seen as the analog of Hamilton's identity for Ricci solitons. The latter plays a fundamental role to Ricci soliton's theory, as one can see for example in {{cite:4ef4b441b8e65598ea29a272325ef70d7b0a978b}}, {{cite:0... | r | 53103e6a453a5f971662047c8ed5bcdc |
We present a framework called spatial prior attention (SPAN) that builds upon self-supervised Vision Transformers {{cite:1e864f01b4214691fa2a0d8b35d55c5891bc09fe}} and leads to more interpretable attention heads, higher downstream classification task performance as well as performance improvements when little annotated... | i | a7a44b37bbbf208d599743fef168fb89 |
We present a scheme to completely distinguish 64 hyper-Bell states in spatial, polarization, and time-bin DOFs assisted by QD-cavity systems. In the present scheme, the time interval {{formula:aa16c902-96fb-4fad-831d-9c71ed0294a4}} between the two incident photons and the cavity photon lifetime ({{formula:071ede15-8b5... | d | c5005048ba129bb895be1b6f6bd18046 |
On the other hand, in a recent follow-up to their earlier study, {{cite:5cafb581adf131bb27e1e898fd852866b61cf9cd}}, argue that the learning curve for the case when very large models are trained to convergence (so that performance is bottlenecked by amount of data) poses a lower bound to the optimal-compute learning cur... | d | 414dbfd1b830d56cf7601eb1fcbb67c6 |
We adapted the inspiring work
by {{cite:8eee5261b0238a6f64b55ca690f84cda47c8757f}} to work better in our setting and efficiently learned expert
models for non-IID client data. Sending all cluster models in each iteration introduces more
communication overhead. We addressed this by removing converged cluster models
from... | d | 4e8efa366d5517332e92969c601dba70 |
The starting point to this paper is the definitions of MSE and bias which differ between fields. Classical statistics define the metrics as a function of the unknown {{formula:3f677c10-0d14-4445-af6b-e0619406492b}} (see for example Eq. 2.25 in {{cite:0c4a8206f82a2fa533d925249ce86ed8d3d9ecfc}}, Chapter 2 in. {{cite:28d... | i | b9e8f7f0a6e8439055e5d70ec97a1a98 |
Fig. REF shows style transfer when the content image has more objects than that of the style image. It is worth noting that merging lake object with sky or building would result in a high content mismatch. Neural style {{cite:1c4cc3e647ec084cc171d4e9fc3f341fe2f255fc}} spreads the style features disregarding the object... | r | a014e6b389e94c60d723ad342e4777b5 |
From section 2 in {{cite:e65c2ad7cda00001b626e940b810b13f8a3d31df}}: {{formula:5663061c-ab59-42b2-b5a7-39cfd49124e6}} . Using this we compute the cumulative functional dependence measure of {{formula:db536839-9b29-4f78-ae7e-2cd9bb6a41be}} as:
{{formula:188062b5-85f3-44d1-8604-16e63c1f3531}}
| r | 7b9df97891c2db846519752a81c7b0a7 |
A key limitation of pulse-shaping devices is their ability to generate time-continuous controls. They are therefore usually replaced by piecewise constant pulses in experiments with a minimum sampling period over which the controls remain constant. This hybrid situation is characterized by a digital control which evolv... | i | 12e660ad234fc50a7aa89b68cb7a4350 |
Figure shows learning curves of six individual runs, split into three shorter and three longer runsLocal evaluation performance is significantly lower than on competition evaluation servers for unknown reasons. Other competition participants have reported the same (private communication).. We include longer runs to co... | r | 2f61f341583f6cb0919dd56cace8b657 |
We adopt the definition of an MDP given in {{cite:117eb2463f35d7dcf6a06a21f671bc35b059db44}}. Let {{formula:876b331e-3bc8-46fe-b3b4-3d96f061bd58}} denote the source MDP, where {{formula:8aac5545-9fb5-4f73-a293-2a009165d4cc}} denotes the state space, {{formula:b269609d-2cf1-4cfb-b264-8baf21a82acf}} denotes the action... | m | 5878d269069df9b69a5c7a2ee550ae9e |
The performance of SAGAN has been studied with different CFA Patterns (i.e., Nona-Bayer and Bayer CFA patterns) and compared with state-of-the-art reconstruction methods. We included deep Bayer joint demosaicking and denoising methods like Deepjoint {{cite:7c7a86f3740415e8e9e844fe908d50b5de7147ee}}, Kokkinos {{cite:f80... | m | 9e6b840fff89f28c1e5d1faee95dd4b3 |
In order to further assess the role of BAO + FS data, we also perform an MCMC analysis without considering them, and use the data set P18 + SN + {{formula:c9e3d41c-6292-44f3-95f5-82fcd027892e}}. The results are presented in Fig. REF and Table REF . As can be seen, removing BAO and FS data leads to a somewhat larger va... | r | 2ff2e5926ce9b30f226965d5207b045a |
where {{formula:54374ba4-d678-4042-8add-ee395da3ea9c}} and the sum is restricted over nearest neighboring sites of a two-dimensional square lattice. The critical temperature is given by {{formula:df9b16f5-0376-496d-b26c-5c61bb2c4c66}} {{cite:e4f5ced9b78a6dad72d74f6d1bd55826158e32ae}}. The correlation lengthLengths ar... | r | 299464ca28025d40eea9faedfcef3a47 |
Theorem 7 (Maximum over a finite set, {{cite:365b7a9e1c224b2448fab3798e54a79d09affdf3}})
Let {{formula:2862923e-f2ea-4c77-874d-be093df4a26a}} be centered {{formula:f0234974-1a26-4100-963c-c63ba1fe2795}} -sub-Gaussian random variables. (i.e. {{formula:df9b60b1-f4f0-4133-803f-c2542140f796}} ). Then,
{{formula:48935bad-... | r | eba15cb61c65ffc66f39a8838ab6a5a7 |
Mechanical systems composed of coupled bistable units have been explored in recent years for applications in soft robotics, shape memory, and information processing {{cite:0d7da45106f968230a4d44c8f35a84a46c91807e}}, {{cite:1f42ba596bfeee13e3d772124f052eaa97d4d157}}, {{cite:caa17323126d2ddaf5ece0d8b4f63f0cb0c3742d}}, {{... | i | fea88f46698edb2b28098106fe018159 |
SW networks are generated using Newman-Watts-Strogatz small-world model (NWS) {{cite:23105e8534d08b4580066d37841c05b3030549bb}}. In each experiment, we chose the number of nodes {{formula:0f5ee0ef-8a97-46be-98f4-adf91f1f8ab7}} , {{formula:20a8a149-0ab0-45dd-92a6-c61976dd5345}} neighbors with which connect each node {{... | m | 7851f00de43150d8a50bf4fd25ef3a06 |
Bias Identification
Three SSD Mobilenet V1 models are iteratively implemented and trained on increasingly corrupted training data to study the effect of training image quality on precision of ODs. For all models, an SGD optimizer with a learning rate of 1 x 10−3 and a batch size 16 is used. Various experiments are car... | r | 7b02f82233e858caa972404fb6cf4329 |
Sometimes, when compared to more traditional SARL, cooperative MARL can be characterised by the additional challenge of the environment being partially observable. Formally, this corresponds to agents interacting in a decentralised partially observable Markov decision process (Dec-POMDP) {{cite:a9727b8a671d9bf54d352496... | i | 0420788145b5f18f3bcc318cf26a147d |
To this end, we introduce a novel technique called uncertainty-aware mixup (UMix), by reweighting the mixed samples according to uncertainty within the mini-batch while mitigating overfitting.
Specifically, we employ the well-known mixup technique to produce “mixed” augmented samples. Then we train the model on these m... | i | 6e8ca13ef3b57487e753aece6163ec0b |
There has been extensive computational research about controversy in online discussions.
To quantify controversy, {{cite:990b97fef0387a11076fc534f9a99790b53eb22a}} (2010)
used the ratio of positive and negative sentiment words;
{{cite:8891eb699d5d6b82f3a9e227449ba01d375ced4e}} ({{cite:8891eb699d5d6b82f3a9e227449ba01d37... | d | 6df9d6efa3aee998dd5b3cfaac8557b9 |
Discriminative correlation filter (DCF) is widely used in object tracking due to its competitive performance and computational efficiency enabled by fast Fourier transform (FFT). DCF produces filters by minimizing the output sum of squared error {{cite:bd1ffd05c09f3fcb1e88a0cda9cd08ff4cf533d3}} for all circular shifts ... | m | 6a0d87afd50a35ffd9e064aa49f5608c |
The resulting gamma-ray line fluxes on a timescale of {{formula:11f4eaa0-ed4f-405e-99cd-d03bd2a6f1a7}} days are {{formula:57d35b7a-b811-4812-9a60-86d2963fbd98}} ph cm{{formula:13bdc53a-e884-4e33-aa71-4c0252a12a4e}} s{{formula:249dd189-5124-4c82-8c7e-bfccc4a92961}} in the photon energy range of {{formula:db593388-37... | d | 09b3b1a12723697b28a74a57def62b76 |
Studies of the temporal variations in solar differential rotation (DR) and solar activity are important for understanding how the solar magnetic cycle is generated. Sunspots and sunspot groups have very often been used as tracers to investigate temporal variations in solar rotation using the Greenwich Photoheliographic... | i | 230a3846aaf18a5898aafd6098e30616 |
Decades of research has explored geometric models of image structure that can be used to regularize solutions to this inverse problem, including {{cite:bb785596a1eebc14b6a890b7aab8b14458ec2392}}, {{cite:198a3c71077f2b2da71996be4082d764f9096c7e}}, {{cite:aaa4ea3cb52056f1c1ee5233b004a253755c5f68}} and many others. More r... | i | 78f5c6803ea091e4eac0ad3dd6888836 |
For continuous waves, thermalization is suppressed in a many-body-localized system, which is necessary to realize a discrete time crystal.{{cite:aa782aa8a751eda847cf4fd02c727516879c618c}}, {{cite:444d750fb26a7169c4a305a21cd1a97497252631}} The time evolution operators for the two-site one-fermion model that is referred ... | d | d8d758a325e62ca18af5196a742f5cdf |
We addressed the task of goal-oriented navigation in a two-fold way for each scenario and each approach. In the first one, the vehicle was set to start in the air and diving to an underwater target, while in the second one it was placed underwater and should navigate upwards to an aerial target. We set a fixed starting... | r | fb28043cb5beaa219aaed30d4ef418f7 |
To address the safety issue in real-world RL training, we present the Intervention Aided Reinforcement Learning (IARL) framework. Intervention is commonly used in many automatic control systems in real world for safety insurance. It is also regarded as an important evaluation criteria for autonomous navigation systems,... | i | 246cde70a4bc783d2541ebc2dc51ed2a |
Our ASWL training pipeline was implemented in TensorFlow {{cite:0acf2ca181b58ff93ee69f8b6f864eb30b311a01}}. All models are trained on a computer with Intel i7 8700K CPU, 16GB RAM, and two NVIDIA RTX 2080 Ti graphic cards, each of which has 11GB of GDDR SDRAM. The source code of this work is available in the supplementa... | r | dc04aa01ad09396afe2e5d8ee766cdf2 |
Our analysis stops at a normalization batch size of 2.
The relation to InstanceNorm {{cite:f7e2b923490a2a6037da69ecb938c783326669f0}} will be discussed separately in Appendix REF .
| d | 15f50153844bee0eb25790a2377e4329 |
Asymptotically AdS black holes have been extensively studied during the past 25 years
or so, mostly in connection with AdS/CFT correspondence and its various extensions
such as AdS/CMT (condensed matter theory)
{{cite:abeb6ad715f07d70b5be32c0a2a2c17a931cdcd1}}, {{cite:a56021623a1c4e9810c3b65acf13c38f0fbfc80b}}, {{cite:... | d | 1ba4c542fa4a655f0ce7e7df7d022170 |
CRF First proposed by {{cite:3eb3b716a91f8e75dfab0578508bfe10faf52ddd}}, conditional random field (CRF) is a type of probabilistic graphical model to model sequential data such as labels and words in sentences. During training, CRF will determine the weights of hand-crafted feature functions to predict the labels. We ... | m | a3a5ed5b923e177ca22aa013e79ee9f0 |
Fig. REF displays the non-collinear ground-state magnetic spin configurations calculated self-consistently for the nanostructures described above.
The ground state spin moments of the NW
exhibits an (ortho) helical-spin-spiral along the [{{formula:8647efa7-e367-4293-97dd-a6ea1ce175aa}} ] direction, with a periodicity ... | r | 15e5ddeaa958de88fe8500f0c1cd4aaf |
Third, the planner cannot scale up to a large number of states. A planner cannot work well on a large-scale scenario such as the game GO {{cite:69ae2ed3b556a936431290473ec76f5263faf252}}.
| d | dec32aebf377766b289d00345e0b80a7 |
While DeepSTI shares similarities to the ideas proposed in {{cite:f2c9ec05fe243eeae6272eafd1a6a848f1e9fcd5}}, there are several differences. First, instead of training on estimated ground-truth images from COSMOS, we developed a phantom-based training scheme that addresses the issue of lacking ground-truth samples from... | d | 4be3726df5b581590dcab6190d9b6243 |
We start by illustrating the proposed general framework for text-to-image generation. Our framework is shown in Figure REF , which consists of three key components: (1) a pre-trained image encoder that maps images to their embeddings; (2) a decoder that generates images from the corresponding embeddings; and (3) a prio... | m | 3a24c6f97fbac65682ccd2adc94c93fb |
In particle physics, the fundamental interactions of the standard model, the electroweak and the QCD interactions, are described by non-abelian gauge theories. The presence of a gauge symmetry implies the appearance of unphysical degrees of freedom in the Lagrangian, which stand in the way of the usual quantization met... | i | 8e77a34e9cf0b2538701f7d343d6ba6f |
In our proof, at no point do we need to approximate a continuous map by smooth maps.
Instead, the proof relies on a result about Čech nerves of open coverings from {{cite:733f254c60aeceb665b515fdfe5d07a578c3a9fd}}, a version of the Nerve Theorem, see e.g. {{cite:562985e04db02fbe1452fc742ba954cf719c8bb9}}, {{cite:f932b3... | i | 331fcd0b53dc5746fbdaff26e0fc6252 |
LIME. {{cite:176cafc1f4571e04e162b8b830dd0c4b99b40c9f}} propose a system to explain why a classifier makes a prediction by identifying useful tokens of the input. They use a linear model {{formula:d9228e1c-7597-463c-a723-97ffe888ab33}} as the interpretation model to approximate the evaluated model locally. And they us... | m | 25df702cac2ac7067f227cfcaaf0a00e |
To fit the parameters for quadratic potential, we first took the
spin averaging over {{formula:f465e3af-adff-4e9e-9022-43e00b6a7823}} to obtain the value of {{formula:cb5f8389-6c14-4079-8462-f8441885775a}} and {{formula:b680ba40-20f1-456f-9560-c0940b615c73}}
for the set of mesons {{formula:53fc5be0-d5fc-4772-8dfd-40... | r | a636058e5e1afcc384a74463ee12bb98 |
Through theoretical analysis and experiments, we rigorously investigate why MLE with SRLMC could converge to an EBM with wrong density estimates,
and reveal that it is caused by a combination of two heuristic modifications to LMC introduced by previous works: (a) early termination of LMC in short-run LMC and (b) using... | i | 31003b875b6aab3d4d16440e6d7054b3 |
1. When evaluated in two (or better three) dimensions in the Bertsch-Pratt
system, a small elongation of the emission region (better region of
homogeneity {{cite:0522d585a2cf494907896af326396fec71d7c109}} is observed along the event axis in all types of
collisions (hadron-hadron {{cite:4fbc3f9e4f7e2f3688191372eedb42b14... | r | 5574090cb1294a438ef19bd561c40ef0 |
Deep Neural Networks (DNNs) have shown outstanding results in solving linear inverse imaging problems. On the one hand, end-to-end approaches provide extremely fast reconstruction. They are widespread in other imaging communities {{cite:6ca8680e7581c3f803fde3e9a9554705957052f6}}, {{cite:2fbb9bc10f6a5a6166e06fdd205d88d1... | i | c7ecd45275f34a6372b0957711ced0e2 |
gives Eq. (11) as a hypergeometric type equation {{cite:20d67d6eaed0d36bda7b9bed723ac5de4927e02c}}
{{formula:b1bffff4-0255-4405-9400-b8990742e7b7}}
| m | 17b093a725f1a9744612bed38a012619 |
Learning with noisy labels has imposed additional challenges. Sometimes the data quality is known a priori {{cite:c02f48cd1283e3620d69dfdb2e84b024a33e71d2}}, {{cite:86b61f3581b97722d99600de4abc4bdb9679fb27}}, {{cite:c3689be1ca407659d6c3b40d3968ccc1ba679e2c}}, but a more common scenario is that, the data available is a ... | i | a65d510b902b5bbb6aae0ac8132a82ae |
Regularization.
Overfitting is considered to be one of the major culprits of membership exposure {{cite:da0f5c71c3e275412ff4c83bb56e742bdc659757}}, {{cite:a1e465ae8a5f5434ecc74c92c5456f87ee69aa73}}, {{cite:f03e4f8c8501b21b9775c707a218306faa60f592}}.
Therefore, the regularization technique may be feasible to defend aga... | d | 6b0c36d1afcfd4f5fb234342a955d4d3 |
Kinetic transport equations have been proposed to model the run-and-tumble motion of chemotactic bacteria {{cite:7ec4a62d4038fb1112d94dcc3a446f1e3543e422}}, {{cite:474bc7e27549d1e1a0471f3bc80c1eb90b358c00}}, {{cite:aa5c8e361eabe60605a4fc997aa612a144debc14}}, {{cite:d801d4101c019bc1ebb5924cf1bf69ab21a25efe}}, {{cite:ae8... | i | e57653712f75a6fe897c7e385e99b251 |
The currently most popular and well-known method used for simulating samples from known distributions is the inverse transformation method (also known as inverse transform sampling) {{cite:5e387f213f796783262f1c6921245788c24e7ef4}}).
| m | e4e56639612666c5139163f96dca6047 |
However, this solution strategy is known to be extremely slow for quantum chemical systems {{cite:b41452d7feca8a9e4a8828c0a49a039f2131c177}}, {{cite:6b98c1cd7d3eb2b411411ef2b514603a87540fd6}}. In order to apply the Hamiltonian, a time evolution operator of the form {{formula:fa85c77a-c54f-49e3-93ae-59dac544b931}} must... | i | d6b9f0f3f227e569d83611409a2d91dd |
The baselines used can be grouped into several distinct categories: human evaluations – traditional machine learning approaches (SVM) – classical deep learning approaches (CNN {{cite:16bf62d9030ae6df487007c8416e3588aee30591}}, BiGRU {{cite:578147b5643fe2cba0fb5e9bd81fab69e0240630}} , and HAN {{cite:2e316d1e7736ee32af55... | m | d84a53090bd3c700bff434661f2979e0 |
As shown in Tabel REF , we have compared our proposed method with those SOTAs semi-supervised semantic segmentation counterparts, including Re-Seg {{cite:554c7f34bfae788e4d6aa76ba07d82ab947fedeb}}, EC-Seg {{cite:49c22ad1e16345a4c80cc3249ed09e98951d6941}}, High-Low-Cons {{cite:e20f338de264bc0b36918217409ea5314f8bf77f}},... | m | 24d8e6e7d5302d13ba74c8af2ce45c19 |
Although the results are promising, the required processing time used for iterative MAP inference is currently too high for real-time application. Although not the focus of this work, one avenue to explore is the use of deep unfolding {{cite:d4d05c66d41db5214260798b69e3a55a02a85b87}}, in which the iterations of the alg... | d | 97ed9a5feea8e2d4d321e35238b06707 |
We showed that a model of counting based on the ESBN architecture, and trained with reinforcement learning, exhibited a developmental trajectory qualitatively similar to the one observed in humans learning to count, as well as the capacity for systematic extrapolation. A model that implemented only the retrieval operat... | d | 11fe85920c0218fd9084f7020a794c2f |
Diffusion models {{cite:490667a20861f5118e8f93fd26a7d30811c926bb}}, {{cite:b49e5283dea37345ef00c9049bcff8c04bd1a981}}, a recent family of generative models, have achieved remarkable image generation performance. Diffusion models have been rapidly studied, as they offer several desirable properties for image synthesis, ... | i | 1d4e3b47d473093c76a15a1bcdf4632d |
According to the model, CAG has several parameters that can be investigated to assess their effect on the agent population, with particular interest for the density of miners.
Starting with the temperature {{formula:d15aa1ea-c9ee-49ce-9673-4313ce559656}} , we consider a population with 2500 agents, to analyse the outco... | r | 18d074641b05be64667a8c1edbb7798e |
In this section, an additional discussion regarding the results of the case studies is added. In the case studies, theour proposed method (GP-MBDoE) was compared with two alternative methods, a method that deals with parametric only uncertainty (MC-MBDoE) and a disturbance based estimation method (DE-MBDoE). The GP-MBD... | d | abc822c59d039e6504f4445a069f4438 |
The appropriate classical 3-point amplitude has been argued to be fixed to all orders in the BH spin at tree level {{cite:09726a228e671094fde9f93a7cd8971bc34f55ca}}, {{cite:99d0987db9a4fe539509b850d8fbbb5300c20f30}}, {{cite:c7405f072552c3d13f7b661f9cf3243c0bc8bdad}}, {{cite:ebe74f0f033ad516dc1c40c1ce5054fcdc431b7b}} by... | i | d9b2e9692d71bc245eb23def5b088ffb |
Based on our previous result, the statement can be traced back to existing results in
the literature. Since {{formula:7564c06b-5a53-4c48-9468-20e1c2bf15af}} is a KKT point of REF , we know
that the bi-active set {{formula:a3608ee5-d390-41dd-8356-6424b5078209}} is empty. Therefore, it
follows from assumption {{formula... | m | 574781bcbb8bd6277afd8618f17743d8 |
All models used the PaiNN architecture {{cite:41faa3b40f207c9273b52b8cc9a8c7becf78346b}} and were implemented in PyTorch {{cite:9f3d313c43fa65f16b7c3e1bd0ef0947be39c7f0}}. As in our previous work, we used five convolutions instead of the three used originally, as this substantially improved model performance {{cite:85a... | m | a7c8612cc8d04c23eff28c01c4e3460d |
As this method does not require any clean counterpart of the real-noisy image, it is more suitable to compare with the denoising algorithms, which also do not require noisy-clean pair and can only operate on a single real-noisy observation of an image. Hence, 4 such widely-used denoising algorithms, namely: BM3D {{cite... | r | f51dfa6afb58c407b8be13f4b090d9d6 |
DeepTaylor {{cite:d0e2b97374523061376d72c2dc30e9208c5fc7d1}} has provided an approach to generating specific positive evidence for a given prediction. The deepTaylor approach of XAI is useful for justifying CNN-based classification. It explains without changing underlying architecture, this property makes it an effecti... | m | dfe0351eff4c501a8ddae8e133abcdd5 |
where {{formula:42df64b0-e25d-4dd5-93f5-507637db544c}} denotes the Hilbert space dimension
corresponding to states residing in {{formula:cf6ebbe7-f7c6-4d98-9c58-2d9a9d558c0f}} with open boundary condition
and the states {{formula:415cd7b6-fbd7-4e99-bb94-09b2e7b3914a}} and {{formula:7645bcdc-e03a-4e13-bb54-2a12cbf259... | m | c65d9af3b351fd22b6c1bc703d4bc84a |
We selected 100 images, 10 from each of 10 fruit categories including Banana, Custard Apple, Fig, Granny Smith, Jackfruit, Lemon, Orange, Pineapple, Pomegranate, and Strawberry (images were randomly picked using web search). All of these categories exist in the ImageNet dataset {{cite:71bd693d9157dc2dff1c50260c5e6382bb... | r | 49dcbb1a34eae97ce0d4a35952895379 |
Previously, Soloduchin & Shamir investigated rhythmogenesis using the framework of two neuronal populations with reciprocal inhibition and short term adaptation in the form of firing rate adaptation {{cite:bb2c48225d5957ae0f66f6cda65b6f3be80c897a}}, {{cite:1d3253f7137b881a56bab39446849e719aa2b4f5}}. The network motif o... | d | 6be47f6e0d7d302a662ff0bf06f05759 |
In order to allow for a general construction of the auxiliary cross section, the aforementioned color and spin correlations are implemented into the factorization formula by realizing the splitting functions {{formula:231b5142-0170-4d7c-82b9-fa56d897ec8f}} as operators that act on matrix elements which are defined as ... | m | 2cc21b56f0d47655de7989290832f5a6 |
For {{formula:80730ed1-a28d-43aa-859b-a8879a5335c5}} , the system (REF ) becomes the Hunter-Saxton (HS) equation {{cite:338b527f9af8a134fb64c58a87f8eea464f0daf6}},
which models the propagation of weakly nonlinear orientation waves in a massive
nematic liquid crystal director field.
Here, {{formula:60cfa02e-323d-4f1f-9f... | i | e90be5fb9100c6628382ccaec939eebc |
Branching fractions are determined relative to {{formula:fb698e43-df54-4b26-8557-7d89743aca1f}}
and the known value {{cite:7cffa256bc39b95f8ab5b623dbf1695c7d451708}} is used to determine the absolute branching fractions.
Efficiency corrections and corrections due to the fragmentation fraction ({{formula:b6118fa9-8687-... | r | 58a64f0d13f0f93da9988b85a29a19fb |
Thirdly, Yan et al. proposes a end-to-end offline trained RGB-D tracker DeT {{cite:fbc8b65274b5ead5d110e26b2321b73fb458f316}} based on the framework of the RGB-only trackers ATOM {{cite:8ecf609506dc3ff2fb676d551ed39e5d55edefef}} and DiMP {{cite:32265959567b9ad5742fcffbb11313ad593ff6b2}}, using a additional feature fusi... | m | be754a61da947fd9f5046918291fd0af |
Following the standard evaluation protocol {{cite:b5cff9fa58ba6951c0c98ea08635dd27486ace60}}, {{cite:74fc6deba21d6e5298df948921acfc7fdc32ca8c}} for incremental object detection, we group classes from Pascal VOC 2007 {{cite:9acc9ad699c1cbffefbc97d13b1983cf1267ab7f}} into two tasks. Three different task combinations are ... | r | 7d7a1450a157d1a1380a3b4879dc88a9 |
This work generalizes one of the most important archetype of quantum interferometry – namely, the single MZI with coherent{{formula:10958e77-cd62-45f9-b9d9-cd3685b48ee2}} squeezed-vacuum light {{cite:484928206899a56bfc4f2ec6ef689bfb783b29bc}}, {{cite:590d20e0b59cca712c6e424b6308896bbcff1a89}}, {{cite:9df78077aeb7a2cf29... | d | e4f4c284a893b006727070b16fd975fe |
For large baths, as defined by eqs. (REF ) and (REF ), the minimal late-time RT surfaces connect the boundary points by crossing the brane. From the brane perspective, this corresponds to the formation of a quantum extremal island in the gravitating region, as described in {{cite:78098cb492e5284d4e22db2209282878a65d299... | d | 062dec0e5ee663967ff1090e922cc710 |
MuRP {{cite:4355d93232b99307d5c9f753c438c55b57c0cb35}}: By establishing a comparison with word analogies through hyperbolic distances {{cite:679bc75c53257df2a6fdf4e8374a9a4fa41c2454}}, the authors propose a scoring function based on relation-specific Möbius multiplication on the head entity, and Möbius addition {{cite:... | m | 87903c9532f5ce525e2cef7653f334ac |
The effectiveness of our proposed model is evaluated by comparing with several existing baselines such as Textrank {{cite:f6413248136c66f26a03d5abac94320f9afb1385}}, LexRank {{cite:f6b65e65e166617afae31479d08cb440b277c980}}, SumBasic {{cite:c82c19f0bd647fc76c77c6ada8ff829609a7c10a}}, and KL Greedy {{cite:d13053e652cc3... | r | 217e31b22485be884a0adf98ae3d6d1f |
This result is essentially due to Tanguy {{cite:fe4eaf37c72ffca5499884ba29c2ba7f8d04d318}}, although he proved it under the additional assumption that the covariance kernel {{formula:52574191-785a-43b1-9b96-7a318f619b91}} is non-increasing, and hence only for processes which are positively-correlated. Since we wish to... | r | 215da755a52c3e78f1741fd3c92486be |
On the other hand, MONAH significantly outperformed Jefferson in Kinesics (body movements or postures, H3B). We refer the reader to {{cite:c349ba5aa2cc074765a1077754477340cd0ff9d7}} for the method of automatic extraction of body movement and posture. Some participants made suggestions of additional automatic extraction... | r | 623208f864f9e2b5e089feb07026afc1 |
In addition, we find that the tracking performance is easily affected by the challenge of sudden camera motion, which frequently occurs in RGBT tracking task.
The major reason is that under such challenge search windows are hardly cover target objects, which would lead to tracking failure.
Common attempts are to expand... | i | 1a4f679f1b8bc3d19864b52331a65935 |
Let us mention that currently QAOA and Quantum Annealing are the two prominent and competing methods for solving combinatorial optimization with quantum hardware. While quantum annealers have currently a remarkable number of qubits (over 5600 by D-Wave) compared to the largest gate-based quantum computer (289 qubits by... | d | ee89d350875b1ce6ece22583f7309e76 |
As shown in Tab. REF -Tab. REF , we provide the results of four benchmark datasets (Office + Caltech-10, Office-31, Office-Home and VisDA-2017). In this experiment, C {{formula:21786f13-1e9e-48cc-8404-a781860bbed8}} A means learning from existing domain C, and transferring knowledge to classify domain A. These results... | r | 5e4cc8d39f89f22cc3e207d26d4d75f2 |
Multiwavelength observations by both IACTs and Fermi satellite may provide some special cases. For example, GRB 190829A was clearly detected by HESS but not detected by Fermi-LAT {{cite:391c72e40aa4cb44af293a114339cadc6bc9d0eb}}. {{cite:afe2d388545fc1fd4101dcffca78cc00d9128637}} and {{cite:7a7b14c018a3172ad02b2553099f2... | d | cae25630c35d7c93a8030c3c4ef53296 |
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