Learning Force Fields from Stochastic Trajectories

Explore the intricacies of force field inference from stochastic trajectories in this comprehensive 56-minute lecture from the Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC). Delve into key concepts such as noise-deterministic systems, Brownian Dynamics, and empirical measures. Examine the inference problem, relative error analysis, and the role of diffusion coefficients in stochastic processes. Investigate entropy production and its significance in understanding complex systems. Conclude with a summary of the main points and engage in thought-provoking discussion questions to reinforce your understanding of force field learning from stochastic trajectories.

Introduction
Welcome
Noise
deterministic
Brownian Dynamics
Inference Problem
empirical measure
relative error
diffusion coefficient
entropy production
summary
discussion questions