About Workshop

The aim of this workshop was to discuss stochastic, geometric, and algebraic approaches to signatures and rough paths, including developments in machine learning applications. The study of signatures have highlighted interactions between these fields, including approximation theorems in path spaces, path development (parallel transport) based methods in ML, algebraic approaches to signature tensors, among many others. One focus of this workshop was the theory and applications of multi-parameter signatures, which builds upon these interactions. We brought together experts in these fields, as well as researchers interested in the theory and application of signatures, in order to discuss these developments and explore further relationships across these disciplines.