Results 1 to 10 of about 198,078 (301)

A quantum parallel Markov chain Monte Carlo. [PDF]

open access: yesJ Comput Graph Stat, 2023
We propose a novel hybrid quantum computing strategy for parallel MCMC algorithms that generate multiple proposals at each step. This strategy makes the rate-limiting step within parallel MCMC amenable to quantum parallelization by using the Gumbel-max trick to turn the generalized accept-reject step into a discrete optimization problem.
Holbrook AJ.
europepmc   +4 more sources

Markov chain Monte Carlo for active module identification problem [PDF]

open access: yesBMC Bioinformatics, 2020
Background Integrative network methods are commonly used for interpretation of high-throughput experimental biological data: transcriptomics, proteomics, metabolomics and others.
Nikita Alexeev   +4 more
doaj   +2 more sources

Applying diffusion-based Markov chain Monte Carlo. [PDF]

open access: yesPLoS ONE, 2017
We examine the performance of a strategy for Markov chain Monte Carlo (MCMC) developed by simulating a discrete approximation to a stochastic differential equation (SDE). We refer to the approach as diffusion MCMC.
Radu Herbei, Rajib Paul, L Mark Berliner
doaj   +2 more sources

Posterior-based proposals for speeding up Markov chain Monte Carlo [PDF]

open access: yesRoyal Society Open Science, 2019
Markov chain Monte Carlo (MCMC) is widely used for Bayesian inference in models of complex systems. Performance, however, is often unsatisfactory in models with many latent variables due to so-called poor mixing, necessitating the development of ...
C. M. Pooley   +3 more
doaj   +2 more sources

Introduction to Markov Chain Monte Carlo Simulations and their Statistical Analysis [PDF]

open access: greenIn Markov Chain Monte Carlo, W.S. Kendall et al. Editors, Lecture Notes Series, Institute for Mathematical Sciences, National University of Singapore, Vol.7, p.1 ff., World Scientific, 2005, 2004
This article is a tutorial on Markov chain Monte Carlo simulations and their statistical analysis. The theoretical concepts are illustrated through many numerical assignments from the author's book on the subject. Computer code (in Fortran) is available for all subjects covered and can be downloaded from the web.
Bernd A. Berg
arxiv   +3 more sources

Comparison between pystan and numpyro in Bayesian item response theory: evaluation of agreement of estimated latent parameters and sampling performance [PDF]

open access: yesPeerJ Computer Science, 2023
Purpose The purpose of this study is to compare two libraries dedicated to the Markov chain Monte Carlo method: pystan and numpyro. In the comparison, we mainly focused on the agreement of estimated latent parameters and the performance of sampling using
Mizuho Nishio   +5 more
doaj   +2 more sources

Parameter Estimation in Population Balance through Bayesian ‎Technique Markov Chain Monte Carlo [PDF]

open access: yesJournal of Applied and Computational Mechanics, 2021
In this work, the Markov Chain Monte Carlo is applied to estimate parameters that represent mechanisms that describe particles' dynamics in particulate systems from the literature's proposed models.
Carlos H.R. Moura   +5 more
doaj   +1 more source

Antithetic Magnetic and Shadow Hamiltonian Monte Carlo

open access: yesIEEE Access, 2021
Hamiltonian Monte Carlo is a Markov Chain Monte Carlo method that has been widely applied to numerous posterior inference problems within the machine learning literature. Markov Chain Monte Carlo estimators have higher variance than classical Monte Carlo
Wilson Tsakane Mongwe   +2 more
doaj   +1 more source

Event-Chain Monte-Carlo Simulations of Dense Soft Matter Systems

open access: yesFrontiers in Physics, 2021
We discuss the rejection-free event-chain Monte-Carlo algorithm and several applications to dense soft matter systems. Event-chain Monte-Carlo is an alternative to standard local Markov-chain Monte-Carlo schemes, which are based on detailed balance, for ...
Tobias Alexander Kampmann   +4 more
doaj   +1 more source

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