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...
Asıl Yazarlar: | Syed, S, Bouchard-Cote, A, Deligiannidis, G, Doucet, A |
---|---|
Materyal Türü: | Journal article |
Dil: | English |
Baskı/Yayın Bilgisi: |
Wiley
2021
|
Benzer Materyaller
-
Clone MCMC: Parallel high-dimensional Gaussian gibbs sampling
Yazar:: Bǎrbos, A, ve diğerleri
Baskı/Yayın Bilgisi: (2018) -
On the Parallelization of MCMC for Community Detection
Yazar:: Wanye, Frank, ve diğerleri
Baskı/Yayın Bilgisi: (2023) -
Scalable Metropolis-Hastings for exact Bayesian inference with large datasets
Yazar:: Cornish, R, ve diğerleri
Baskı/Yayın Bilgisi: (2019) -
An adaptive parallel tempering algorithm
Yazar:: Miasojedow, B, ve diğerleri
Baskı/Yayın Bilgisi: (2013) -
Parallel Local Approximation MCMC for Expensive Models
Yazar:: Conrad, Patrick Raymond, ve diğerleri
Baskı/Yayın Bilgisi: (2019)