36 citations · 163 across the 27 of their papers we have counts for
4 papers · 1 filter
A Piecewise Deterministic Markov Process via swaps in hyperspherical coordinates
Alexander Terenin, Daniel Thorngren
Recently, a class of stochastic processes known as piecewise deterministic Markov processes has been used to define continuous-time Markov chain Monte Carlo algorithms with a numbe…
Comment: A brief survey of the current state of play for Bayesian computation in data science at Big-Data scale
David Draper, Alexander Terenin
We wish to contribute to the discussion of "Comparing Consensus Monte Carlo Strategies for Distributed Bayesian Computation" by offering our views on the current best methods for B…
GPU-accelerated Gibbs sampling: a case study of the Horseshoe Probit model
Alexander Terenin, Shawfeng Dong, David Draper
Gibbs sampling is a widely used Markov chain Monte Carlo (MCMC) method for numerically approximating integrals of interest in Bayesian statistics and other mathematical sciences. M…
Asynchronous Gibbs Sampling
Alexander Terenin, Daniel Simpson, David Draper
Gibbs sampling is a Markov Chain Monte Carlo (MCMC) method often used in Bayesian learning. MCMC methods can be difficult to deploy on parallel and distributed systems due to their…