The applications of Machine Learning methods to classical and quantum problems in non-equilibrium

This project will be about applying advanced machine learning methods to the study of complex collective non-equilibrium dynamics, both in classical stochastic systems and in open quantum systems. It will establish connections with approaches for sampling rare events, such as those based on large deviation theory. A particular focus will be the application of tensor network techniques and their integration to ML methods.