Non-reversible parallel tempering: a scalable highly parallel MCMC scheme
Parallel tempering (PT) methods are a popular class of Markov chain Monte Carlo schemes used to sample complex high-dimensional probability distributions. They rely on a collection of N interacting auxiliary chains targeting tempered versions of the target distribution to improve the exploration of...
Main Authors: | Syed, S, Bouchard-Cote, A, Deligiannidis, G, Doucet, A |
---|---|
Formato: | Journal article |
Idioma: | English |
Publicado: |
Wiley
2021
|
Títulos similares
-
Clone MCMC: Parallel high-dimensional Gaussian gibbs sampling
por: Bǎrbos, A, et al.
Publicado: (2018) -
On the Parallelization of MCMC for Community Detection
por: Wanye, Frank, et al.
Publicado: (2023) -
Scalable Metropolis-Hastings for exact Bayesian inference with large datasets
por: Cornish, R, et al.
Publicado: (2019) -
An adaptive parallel tempering algorithm
por: Miasojedow, B, et al.
Publicado: (2013) -
Parallel Local Approximation MCMC for Expensive Models
por: Conrad, Patrick Raymond, et al.
Publicado: (2019)