8 citations · 8 across the 1 of their papers we have counts for
4 papers
BlackJAX: Composable Bayesian inference in JAX
Alberto Cabezas, Adrien Corenflos, Junpeng Lao +19
BlackJAX is a library implementing sampling and variational inference algorithms commonly used in Bayesian computation. It is designed for ease of use, speed, and modularity by tak…
Efficient and Generalizable Tuning Strategies for Stochastic Gradient MCMC
Jeremie Coullon, Leah South, Christopher Nemeth
Stochastic gradient Markov chain Monte Carlo (SGMCMC) is a popular class of algorithms for scalable Bayesian inference. However, these algorithms include hyperparameters such as st…
Ensemble sampler for infinite-dimensional inverse problems
Jeremie Coullon, Robert J Webber
We introduce a new Markov chain Monte Carlo (MCMC) sampler for infinite-dimensional inverse problems. Our new sampler is based on the affine invariant ensemble sampler, which uses…
MCMC for a hyperbolic Bayesian inverse problem in traffic flow modelling
Jeremie Coullon, Yvo Pokern
As a Bayesian approach to fitting motorway traffic flow models remains rare in the literature, we explore empirically the sampling challenges this approach offers which have to do…