Mauro Maggioni

Learning Interaction Kernels from Collective Steady States

This work proposes a learning procedure for system identification in interacting particle systems from single-snapshot observations of collective behaviors, unlike existing approaches that rely on observations of trajectories, and test it on a variety of representative models with steady-state and quasi-stationary patt...