11 citations · 30 across the 21 of their papers we have counts for
5 papers · 1 filter
Risk-Sensitive Stochastic Optimal Control as Rao-Blackwellized Markovian Score Climbing
Hany Abdulsamad, Sahel Iqbal, Adrien Corenflos +1
Stochastic optimal control of dynamical systems is a crucial challenge in sequential decision-making. Recently, control-as-inference approaches have had considerable success, provi…
Parallel-in-Time Probabilistic Numerical ODE Solvers
Nathanael Bosch, Adrien Corenflos, Fatemeh Yaghoobi +3
Probabilistic numerical solvers for ordinary differential equations (ODEs) treat the numerical simulation of dynamical systems as problems of Bayesian state estimation. Aside from…
Debiasing Piecewise Deterministic Markov Process samplers using couplings
Adrien Corenflos, Matthew Sutton, Nicolas Chopin
Monte Carlo methods -- such as Markov chain Monte Carlo (MCMC) and piecewise deterministic Markov process (PDMP) samplers -- provide asymptotically exact estimators of expectations…
Variational Gaussian filtering via Wasserstein gradient flows
Adrien Corenflos, Hany Abdulsamad
We present a novel approach to approximate Gaussian and mixture-of-Gaussians filtering. Our method relies on a variational approximation via a gradient-flow representation. The gra…
Auxiliary MCMC and particle Gibbs samplers for parallelisable inference in latent dynamical systems
Adrien Corenflos, Simo Särkkä
Sampling from the full posterior distribution of high-dimensional non-linear, non-Gaussian latent dynamical models presents significant computational challenges. While Particle Gib…