Search Results - "sampling algorithm"

Event-based sliding-mode synchronization of delayed memristive neural networks via continuous/periodic sampling algorithm by Wang, Yuxiao, Cao, Yuting, Guo, Zhenyuan, Huang, Tingwen, Wen, Shiping

“…•This paper investigates the problem of event-based sliding-mode synchronization of memristive neural networks with delay through continuous/periodic sampling algorithm…”
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A spectral sampling algorithm in dynamic causal modelling for resting‐state fMRI by Xie, Yuhai, Zhang, Puming, Zhao, Jun

“… A spectral sampling algorithm (SS‐DCM) was proposed to improve the estimation accuracy of the dynamic causal model for rs‐fMRI. In SS‐DCM…”
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Performance and Robustness of the Monte Carlo Importance Sampling Algorithm Using Parallelized S-ADAPT for Basic and Complex Mechanistic Models by Bulitta, Jurgen B., Landersdorfer, Cornelia B.

“…The Monte Carlo Parametric Expectation Maximization (MC-PEM) algorithm can approximate the true log-likelihood as precisely as needed and is efficiently…”
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A suggested sampling algorithm for use with ATP testing in cleanliness measurement by Whiteley, G.S., Glasbey, T.O., Fahey, P.P.

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An improved Bayesian tensor regularization and sampling algorithm to track neuronal fiber pathways in the language circuit by Mishra, Arabinda, Anderson, Adam W., Wu, Xi, Gore, John C., Ding, Zhaohua

“…Purpose: The purpose of this work is to design a neuronal fiber tracking algorithm, which will be more suitable for reconstruction of fibers associated with…”
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Nonparametric function estimation subject to monotonicity, convexity and other shape constraints by Shively, Thomas S., Walker, Stephen G., Damien, Paul

“… A computationally efficient MCMC sampling algorithm is developed that converges faster than previous methods for non-Gaussian models…”
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Research on Reproductive Visual Production Types of Digital Technology Based on Sampling Algorithm by Qing, Liu, Tingxuan, Wang

“… To demonstrate that the reproductive production based on digital technical progress can fully reveal the subject's creative initiative, and is suitable for types of works with stronger creativity…”
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Federated Learning with a Sampling Algorithm under Isoperimetry by Sun, Lukang, Salim, Adil, Richtárik, Peter

“… Federated learning algorithms usually take an optimization approach: they are algorithms for minimizing the training loss subject to communication (and other) constraints…”
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Perfect sampling algorithm for Schur processes by Betea, Dan, Boutillier, Cédric, Bouttier, Jérémie, Chapuy, Guillaume, Corteel, Sylvie, Vuletić, Mirjana

“…) partitions subject to certain interlacing conditions. This class contains several fundamental combinatorial objects as special cases, such as plane partitions, tilings…”
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Kriging-based adaptive Importance Sampling algorithms for rare event estimation by Balesdent, Mathieu, Morio, Jérôme, Marzat, Julien

“…Very efficient sampling algorithms have been proposed to estimate rare event probabilities, such as Importance Sampling or Importance Splitting…”
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M-DeepAssembly: enhanced DeepAssembly based on multi-objective multi-domain protein conformation sampling by Cui, Xinyue, Xia, Yuhao, Hou, Minghua, Zhao, Xuanfeng, Wang, Suhui, Zhang, Guijun

“… Results To alleviate the above challenges, we proposed M-DeepAssembly, a protocol based on multi-objective protein conformation sampling algorithm for multi-domain protein structure prediction…”
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A bias–variance trade-off governs individual differences in on-line learning in an unpredictable environment by Glaze, Christopher M., Filipowicz, Alexandre L. S., Kable, Joseph W., Balasubramanian, Vijay, Gold, Joshua I.

“… For a task requiring decisions about dynamic evidence streams, human subjects with more flexible, history-dependent choices (low bias…”
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Importance Sampling Microfacet-Based BSDFs using the Distribution of Visible Normals by Heitz, E., d'Eon, E.

“…We present a new approach to microfacet‐based BSDF importance sampling. Previously proposed sampling schemes for popular analytic BSDFs typically begin by…”
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Quantification of Uncertainty Associated with Evidence Layers in Mineral Prospectivity Mapping Using Direct Sampling and Convolutional Neural Network by Yang, Fanfan, Wang, Ziye, Zuo, Renguang, Sun, Siquan, Zhou, Bao

“… This study utilizes a hybrid model combining a direct sampling algorithm and a convolutional neural network to quantify the uncertainty associated with the evidence layers in MPM…”
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Hierarchical Network Models for Exchangeable Structured Interaction Processes by Dempsey, Walter, Oselio, Brandon, Hero, Alfred

“… Scientific articles, on the other hand, may have multiple subject areas and multiple authors…”
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Using advanced analysis of multifocal visual-evoked potentials to evaluate the risk of clinical progression in patients with radiologically isolated syndrome by Miguel, J. M., Roldán, M., Pérez-Rico, C., Ortiz, M., Boquete, L., Blanco, R.

“… : number of CWT function maximums). The best features were used as inputs to a RUSBoost boosting-based sampling algorithm to improve the mfVEP diagnostic performance…”
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A test paper generation algorithm based on diseased enhanced genetic algorithm by Cui, JunChuan, Zhou, Ya, Huang, Guimin

“…With the continuous progress of society, tests, and exams appear more and more frequently in people's lives. Faced with the ever-increasing demand for test…”
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A Bayesian approach for subgroup analysis by Li, Nan, Zhu, Wensheng

“…Several penalization approaches have been developed to identify homogeneous subgroups based on a regression model with subject…”
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Bayesian density regression by Dunson, David B., Pillai, Natesh, Park, Ju-Hyun

“… A Gibbs sampling algorithm is developed for posterior computation. The methods are illustrated by using simulated data examples and an epidemiologic application…”
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Intelligent risk stratification of hypertension based on ambulatory blood pressure monitoring and machine learning algorithms by Deng, Muqing, Guo, Junsheng, Li, Boyan, Yang, Jingfen, Zhang, Xiaobo, Liang, Dandan, Wang, Yanjiao, Huang, Xiaoyu

“… . A total of 262 patients with hypertension are enrolled at People's Hospital of Yangjiang, in which 93 subjects are with simple hypertension and 169 subjects have hypertension…”
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