Summer School — Sampling high-dimensional probability measures: applications in (non)equilibrium molecular dynamics and statistics

Sampling high dimensional probability measures is a key issue in various scientific fields, including molecular dynamics and computational statistical physics (with applications in physics, chemistry, materials science and computational biology), as well as statistics (in particular Bayesian statistics) and more recently machine learning.

Interactions between molecular dynamics and computational statistics have a fruitful and successful history. We believe that a school at the intersection of these two fields will be beneficial to both communities, as the best methods can be transferred to both fields, which would then be able to exchange and share their respective knowledge and expertise. Young researchers are a particularly receptive audience to this end, as we strongly believe that being simultaneously exposed to both fields at an earlier stage of the career will have a long lasting impact on their scientific production.