Machine Learning Meets Many-Particle Problems

September 26, 2016 - September 30, 2016

Institute for Pure and Applied Mathematics (IPAM), UCLA, Los Angeles, CA.

This workshop will set the stage and define research directions for the rest of the program. The idea is to achieve a healthy mix between mathematicians, computer scientists, physicists, and chemists and establish common grounds that will enable rational applications of machine learning techniques to many-particle problems. One prominent outcome of this workshop will be the establishment of a common repository of datasets corresponding to different many-particle problems (structures and energies of molecules and materials, protein structures and dynamics, spectroscopic signatures of complex systems, etc.). These datasets can be used to assess the performance of different ML techniques during the IPAM program and beyond. The application deadline for funding is August 1, 2016.