20 citations · 76 across the 13 of their papers we have counts for
5 papers · 1 filter
Optimized Algorithms to Sample Determinantal Point Processes
Nicolas Tremblay, Simon Barthelme, Pierre-Olivier Amblard
In this technical report, we discuss several sampling algorithms for Determinantal Point Processes (DPP). DPPs have recently gained a broad interest in the machine learning and sta…
Bounding errors of Expectation-Propagation
Guillaume P Dehaene, Simon Barthelmé
Expectation Propagation is a very popular algorithm for variational inference, but comes with few theoretical guarantees. In this article, we prove that the approximation errors ma…
The Poisson transform for unnormalised statistical models
Simon Barthelmé, Nicolas Chopin
Contrary to standard statistical models, unnormalised statistical models only specify the likelihood function up to a constant. While such models are natural and popular, the lack…
Fast matrix computations for functional additive models
Simon Barthelme
It is common in functional data analysis to look at a set of related functions: a set of learning curves, a set of brain signals, a set of spatial maps, etc. One way to express rel…
Discussions on "Riemann manifold Langevin and Hamiltonian Monte Carlo methods"
Simon Barthelme, Magali Beffy, Nicolas Chopin +5
This is a collection of discussions of `Riemann manifold Langevin and Hamiltonian Monte Carlo methods" by Girolami and Calderhead, to appear in the Journal of the Royal Statistical…