This 3-week meeting aims at gathering physicists and mathematicians working on stochastic sampling. The overall goal is to foster new interdisciplinary collaborations to answer the challenges encountered while sampling probability distributions presenting high-energy barriers and/or a large number of metastable states. Such challenges are faced by researchers working in a diverse range of fields in science, from fundamental problems in statistical mechanics to large-scale simulations of materials; in recent years significant progress has been made on several aspects, including :
● design of Markov processes which break free from a random-walk behavior,
● numerical methods for dimensionality reduction of input data,
● mode-hopping non-local moves by generative models,
● density region detection,
● and analytical derivations of robustness guarantees. By bringing together established experts and early-career researchers across a wide range of disciplines we aim to find new synergies to answer important and general questions, including
● How to associate fastest local mixing strategies with mode-hopping moves?
● What physics can we preserve and extract along the dynamics?
● How to build reduced representations that can detect previously unseen events or regions ?