Results 41 to 50 of about 183,644 (280)
Bayesian Inference for Finite Mixture Regression Model Based on Non-Iterative Algorithm
Mathematics, 2021 Finite mixtures normal regression (FMNR) models are widely used to investigate the relationship between a response variable and a set of explanatory variables from several unknown latent homogeneous groups.
Ang Shan, Fengkai Yang
doaj +1 more source
A Note on the Folding Coupler [PDF]
, 2006 Perfect Gibbs sampling is a method to turn Markov Chain Monte Carlo (MCMC) samplers into exact generators for independent random vectors. We show that a perfect Gibbs sampling algorithm suggested in the literature is not always generating from the ...
Hörmann, Wolfgang, Leydold, Josef
core
Advanced Functional Materials, EarlyView.In this study, the interplay of dipolar dynamics and ionic charge transport in MOF compounds is investigated. Synthesizing the novel structure CFA‐25 with integrated freely rotating dipolar groups, local and macroscopic effects, including interactions with Cs cations are explored.
Ralph Freund +6 more
wiley +1 more source
Italian Journal of Animal Science, 2022 The Italian National Pig Breeders Association (ANAS) manages the breeding programs of the Italian Large White (ILW), Landrace (IL), and Duroc (ID) breeds, mainly oriented to the production of PDO hams.
M. Cappelloni, M. Gallo, A Cesarani
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Particle Gibbs sampling for Bayesian phylogenetic inference [PDF]
Bioinformatics, 2020 Abstract Motivation The combinatorial sequential Monte Carlo (CSMC) has been demonstrated to be an efficient complementary method to the standard Markov chain Monte Carlo (MCMC) for Bayesian phylogenetic tree inference using biological sequences.
Shijia Wang, Liangliang Wang
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Advanced Functional Materials, EarlyView.In this work, a magnetic core‐shell catalyst (HOF‐on‐Fe3O4/ZIF‐67) is successfully synthesized, consisting of a metal–organic framework (ZIF‐67) with magnetic Fe3O4 as the core and a porous hydrogen‐bonded organic framework (HOF) as the shell. The catalyst efficiently activated peroxymonosulfate, resulting in rapid and effective removal of water ...
Yingying Du +4 more
wiley +1 more source
Learnable Markov Chain Monte Carlo Sampling Methods for Lattice Gaussian Distribution
IEEE Access, 2019 As a key ingredient of machine learning and artificial intelligence, the sampling algorithms with respect to lattice Gaussian distribution has emerged as an important problem in coding and decoding of wireless communications.
Zheng Wang, Shanxiang Lyu, Ling Liu
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Biclustering microarray data by Gibbs sampling [PDF]
Bioinformatics, 2003 Abstract Motivation: Gibbs sampling has become a method of choice for the discovery of noisy patterns, known as motifs, in DNA and protein sequences. Because handling noise in microarray data presents similar challenges, we have adapted this strategy to the biclustering of discretized microarray data.
Qizheng, Sheng +2 more
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Incorporating Discriminator in Sentence Generation: a Gibbs Sampling Method
, 2018 Generating plausible and fluent sentence with desired properties has long been a challenge. Most of the recent works use recurrent neural networks (RNNs) and their variants to predict following words given previous sequence and target label.
Huang, Xuanjing +3 more
core +1 more source
Atomic Size Misfit for Electrocatalytic Small Molecule Activation
Advanced Functional Materials, EarlyView.This review explores the application and mechanisms of atomic size misfit in catalysis for small molecule activation, focusing on how structural defects and electronic properties can effectively lower the energy barriers of chemical bonds in molecules like H2O, CO2, and N2.
Ping Hong +3 more
wiley +1 more source