You can find here some educational materials focused on teaching Machine Learning applications in Variational Monte Carlo methods for ab-initio quantum simulations.
Video Lectures
The following video lectures provide comprehensive coverage of the theoretical foundations and practical applications. Those are a series of lectures i gave at ICTP in 2023 and that turned out, in my opinion, very well.
Introduction to Variational Monte Carlo and stochastic optimization of ground states - Covers the fundamental concepts of VMC and optimization techniques for finding quantum ground states.
Stochastic Reconfiguration/Natural gradient optimization, fast computation of gradients with vector-jacobian products, minSR, encoding symmetries - Advanced topics including natural gradient methods, efficient gradient computation, and symmetry considerations in quantum simulations.
Overview of NetKet and doing calculations yourself - Practical introduction to NetKet framework and hands-on computational exercises.
These materials are designed to provide both theoretical understanding and practical skills for implementing ML-based VMC methods in quantum physics research.
