Discrete gradients for computational Bayesian inference
Discrete gradients for computational Bayesian inference
In this paper, we exploit the gradient flow structure of continuous-time formulations of Bayesian inference in terms of their numerical time-stepping. We focus on two particular examples, namely, the continuous-time ensemble Kalmanā€“Bucy filter and a particle discretisation of the Fokkerā€“Planck equation associated to Brownian dynamics. Both formulations can lead to ā€¦