Over the last decade, deep generative modelling has emerged as a powerful probabilistic tool in machine learning. The idea behind generative modelling is simple: transform noise to create new data that matches a given ...

The general subject of the conference was geometric group theory, that is the study of groups via suitable actions on spaces endowed with additional structures, for instance a distance, a measure (class), or both of them ...

In machine learning, a field addressing the extraction of information and structure from finite data with the means of computer science and mathematics, maps from finite-dimensional spaces of data or computations into ...

Set theory has experienced rapid development in the recent years, both in pure set theory and in its applications to other fields of mathematics. We have seen breakthroughs in combinatorial set theory, forcing, inner models, ...