67 citations · 140 across the 4 of their papers we have counts for
4 papers
MLJ: A Julia package for composable machine learning
Anthony D. Blaom, Franz Kiraly, Thibaut Lienart +3
MLJ (Machine Learing in Julia) is an open source software package providing a common interface for interacting with machine learning models written in Julia and other languages. It…
Piecewise Deterministic Markov Processes for Scalable Monte Carlo on Restricted Domains
Joris Bierkens, Alexandre Bouchard-Côté, Arnaud Doucet +5
Piecewise Deterministic Monte Carlo algorithms enable simulation from a posterior distribution, whilst only needing to access a sub-sample of data at each iteration. We show how th…
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…
Expectation Particle Belief Propagation
Thibaut Lienart, Yee Whye Teh, Arnaud Doucet
We propose an original particle-based implementation of the Loopy Belief Propagation (LPB) algorithm for pairwise Markov Random Fields (MRF) on a continuous state space. The algori…