Machine Learning for Many-Particle Systems
Month: February 2015
Date: February 23--27
Name: Machine Learning for Many-Particle Systems
Location: Institute for Pure and Applied Mathematics (IPAM), UCLA, Los Angeles, California.
This workshop will address the reaches and limitations of ML as applied to many-particle systems and highlight examples where physical models can be successfully combined with ML algorithms. The workshop aims to create novel synergistic collaborations between researchers in two different fields: modeling of many-particle (quantum and classical) systems and machine learning. Interactions between many constituent particles generally give rise to collective (or emergent) phenomena in matter. Even when the interactions between the particles are well defined and the governing equations of the system are understood, the collective behavior of the system as a whole does not trivially emerge from these equations.
Applications are due January 1, 2015. Consult the webpage for more information.