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 |
---|---|
פורמט: | Journal article |
שפה: | English |
יצא לאור: |
Wiley
2021
|
פריטים דומים
-
Clone MCMC: Parallel high-dimensional Gaussian gibbs sampling
מאת: Bǎrbos, A, et al.
יצא לאור: (2018) -
On the Parallelization of MCMC for Community Detection
מאת: Wanye, Frank, et al.
יצא לאור: (2023) -
Scalable Metropolis-Hastings for exact Bayesian inference with large datasets
מאת: Cornish, R, et al.
יצא לאור: (2019) -
Parallel Local Approximation MCMC for Expensive Models
מאת: Conrad, Patrick Raymond, et al.
יצא לאור: (2019) -
Parallel and distributed MCMC inference using Julia
מאת: Yu, Angel
יצא לאור: (2018)