Speaker
Gabriel Stoltz
((CERMICS, Ecole des Ponts & Project-team MATHERIALS, Inria Paris)
Description
I will provide a brief introduction to molecular dynamics (the computational implementation of the theory of statistical physics) and relate it to Bayesian inference, as these are two situations where sampling a high dimensional probability measure is required. Average properties for these two applications are typically obtained through ergodic averages of discretizations of certain stochastic differential equations. I will provide an introduction to the most popular stochastic dynamics to this end and their numerical analysis -- in particular error estimates on the timestep discretization bias, and estimates on the statistical error.
Primary author
Gabriel Stoltz
((CERMICS, Ecole des Ponts & Project-team MATHERIALS, Inria Paris)
