Minicourse on Machine Learning for Many-Body Physics, Sept 25 – 29, 2017 São Paulo, Brazil
This course will introduce modern machine learning techniques for studying classical and quantum many-body problems encountered in condensed matter, quantum information, and related fields of physics. Lectures will emphasize relations between statistical physics and machine learning, while tutorials will include hands-on experience in programming with applications.
Topics to be covered include lattice models for statistical physics, Monte Carlo methods, supervised and unsupervised learning, neural networks, Boltzmann machines, and deep learning. It would be useful if participants had basic knowledge of programming in any language.
The included Tutorials, written in Python and TensorFlow, are intended for use with the lectures