4 citations · 5 across the 2 of their papers we have counts for
3 papers
stat.CO2018★ 4 cited
Large-Scale Stochastic Sampling from the Probability Simplex
Jack Baker, Paul Fearnhead, Emily B Fox +1
Stochastic gradient Markov chain Monte Carlo (SGMCMC) has become a popular method for scalable Bayesian inference. These methods are based on sampling a discrete-time approximation…
stat.CO2017★ 1 cited
sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo
Jack Baker, Paul Fearnhead, Emily B. Fox +1
This paper introduces the R package sgmcmc; which can be used for Bayesian inference on problems with large datasets using stochastic gradient Markov chain Monte Carlo (SGMCMC). Tr…
stat.CO2017
Control Variates for Stochastic Gradient MCMC
Jack Baker, Paul Fearnhead, Emily B. Fox +1
It is well known that Markov chain Monte Carlo (MCMC) methods scale poorly with dataset size. A popular class of methods for solving this issue is stochastic gradient MCMC. These m…