Machine-learned force fields for molecular simulation

This lecture covers the development and application of machine-learned force fields for molecular simulation, focusing on supervised learning methods to predict energy and forces in quantum chemistry. It also discusses the speed-accuracy tradeoff in quantum chemistry simulations and the solution of the electronic Schrödinger equation using machine learning techniques.