Speaker
Miranda Cheng
(University of Amsterdam)
Description
Machine learning has the potential of becoming, among other things, a major computational tools in physics, making possible what was not. In this talk I focus on one specific example of using this new tool on concrete computational problems. I will summarise my recent paper (2110.02673) with de Haan, Rainone, and Bondesan, where we use a continuous flow model to help ameliorate the numerical difficulties in sampling in lattice field theories, which for instance hampers high-precision computations in LQCD.
Primary author
Miranda Cheng
(University of Amsterdam)
