Monte Carlo sampling: beyond the diffusive regime

The workshop will bring together researchers from different fields to discuss recent advances in Monte Carlo sampling algorithms. Monte Carlo methods have had a profound impact on science and technology for the past 70 years, facilitating major breakthroughs in such diverse areas as statistical physics, computational chemistry and drug discovery, statistical inference and machine learning, econometrics and theoretical computer science, as well as many others.

Topics: The workshop is part of a 6 month programme exploring stochastic systems and anomalous diffusion. Anomalous diffusion within the context of sampling refers to the non-Brownian regime. Such anomalous (or non-diffusive) behaviour can be achieved by various means, such as non-reversibility, boundaries and constraints, trapping and intelligent use of gradients. These advances and more will be explored at the workshop.