1 citations · 1 across the 1 of their papers we have counts for
2 papers
stat.ME2024
Metropolis--Hastings with Scalable Subsampling
Estevão Prado, Christopher Nemeth, Chris Sherlock
The Metropolis-Hastings (MH) algorithm is one of the most widely used Markov Chain Monte Carlo schemes for generating samples from Bayesian posterior distributions. The algorithm i…
stat.CO2022★ 1 cited
SwISS: A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy
Callum Vyner, Christopher Nemeth, Chris Sherlock
Divide-and-conquer strategies for Monte Carlo algorithms are an increasingly popular approach to making Bayesian inference scalable to large data sets. In its simplest form, the da…