Summer 2022

Interpreting Machine Learning From the Perspective of Nonequilibrium Systems

Wednesday, Jun. 29, 2022 11:00 am11:30 am PDT

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David Limmer (University of California, Berkeley)


Calvin Lab Auditorium

In this talk, I will discuss the connections between physical nonequilibrium systems and common algorithms employed in machine learning. I will report how machine learning has been used to expand the scope of physical nonequilibrium systems that can be effectively studied computationally. The interpretation of the optimization procedure as a nonequilibrium dynamics will be also examined. Specific examples in reinforcement learning will be highlighted.