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...
Váldodahkkit: | Syed, S, Bouchard-Cote, A, Deligiannidis, G, Doucet, A |
---|---|
Materiálatiipa: | Journal article |
Giella: | English |
Almmustuhtton: |
Wiley
2021
|
Geahča maid
-
Clone MCMC: Parallel high-dimensional Gaussian gibbs sampling
Dahkki: Bǎrbos, A, et al.
Almmustuhtton: (2018) -
On the Parallelization of MCMC for Community Detection
Dahkki: Wanye, Frank, et al.
Almmustuhtton: (2023) -
An adaptive parallel tempering algorithm
Dahkki: Miasojedow, B, et al.
Almmustuhtton: (2013) -
Scalable Metropolis-Hastings for exact Bayesian inference with large datasets
Dahkki: Cornish, R, et al.
Almmustuhtton: (2019) -
Parallel Local Approximation MCMC for Expensive Models
Dahkki: Conrad, Patrick Raymond, et al.
Almmustuhtton: (2019)