A quantum parallel Markov chain Monte Carlo. [PDF]
J 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.
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Quantum annealing enhanced Markov-Chain Monte Carlo [PDF]
Scientific ReportsIn this study, we propose quantum annealing-enhanced Markov Chain Monte Carlo (QAEMCMC), where QA is integrated into the MCMC subroutine. QA efficiently explores low-energy configurations and overcomes local minima, enabling the generation of proposal ...
Shunta Arai, Tadashi Kadowaki
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Markov chain Monte Carlo for active module identification problem [PDF]
BMC 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
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Posterior-based proposals for speeding up Markov chain Monte Carlo [PDF]
Royal 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
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Etymologia: Markov Chain Monte Carlo [PDF]
Emerging Infectious Diseases, 2019 Ronnie Henry
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Comparison between pystan and numpyro in Bayesian item response theory: evaluation of agreement of estimated latent parameters and sampling performance [PDF]
PeerJ 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
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Multiparameter Approximation Model of Temperature Conditions of Marine Diesel Generator Sets, Based on Markov Chain Monte Carlo [PDF]
TransNav, 2022 In the article we propose a multi-parameter approximation model, based on Markov chain Monte Carlo, which describes the relationship between the temperature regime, operating conditions and electromechanical parameters of marine diesel generator sets ...
Volodymyr Myrhorod +2 more
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Antithetic Magnetic and Shadow Hamiltonian Monte Carlo
IEEE 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
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Parameter Estimation in Population Balance through Bayesian Technique Markov Chain Monte Carlo [PDF]
Journal 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
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Event-Chain Monte-Carlo Simulations of Dense Soft Matter Systems
Frontiers 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
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