116 citations · 415 across the 17 of their papers we have counts for
4 papers · 1 filter
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server
Leonard Hasenclever, Stefan Webb, Thibaut Lienart +4
This paper makes two contributions to Bayesian machine learning algorithms. Firstly, we propose stochastic natural gradient expectation propagation (SNEP), a novel alternative to e…
An iterative technique for bounding derivatives of solutions of Stein equations
Christian Döbler, Robert E. Gaunt, Sebastian J. Vollmer
We introduce a simple iterative technique for bounding derivatives of solutions of Stein equations , where is a linear differential operator and is the…
The Bouncy Particle Sampler: A Non-Reversible Rejection-Free Markov Chain Monte Carlo Method
Alexandre Bouchard-Côté, Sebastian J. Vollmer, Arnaud Doucet
Markov chain Monte Carlo methods have become standard tools in statistics to sample from complex probability measures. Many available techniques rely on discrete-time reversible Ma…
(Non-) asymptotic properties of Stochastic Gradient Langevin Dynamics
Sebastian J. Vollmer, Konstantinos C. Zygalakis, and Yee Whye Teh
Applying standard Markov chain Monte Carlo (MCMC) algorithms to large data sets is computationally infeasible. The recently proposed stochastic gradient Langevin dynamics (SGLD) me…