MLinPL Keynote: Some fun examples from the intersection of machine learning and physics

Abstract: Machine learning and physics have a long history of interactions. Many machine learning techniques have roots in physics, and machine learning techniques have been applied to problems in physics for years. But this interaction has intensified recently, and the interplay touches on many of the most interesting contemporary topics in deep learning including understanding of generalization, generative models, causality, inductive bias, and inference. I will describe some of the results and exploratory work that is being done in this direction.