Machine Learning for High Energy Physics on and off the Lattice

Abstract: The field of machine learning and artificial intelligence has seen enormous progress in the last few years, and much of this progress has come in the form of Deep Learning. There have been dramatic improvements in performance on several challenging problems, an extension of the types of tasks that are being addressed, and progress into the theory of why deep learning works as well as it does. Many of these advances are directly relevant for physics, and many of the techniques have their origins in physics. I will give an overview of these developments and their potential in physics by highlighting some recent examples and commenting on the machine learning techniques from a physicist’s perspective. I will also introduce the ECT* workshop with the same focus scheduled for Sept. 2021.

Video here: https://youtu.be/YXl5VyyPx4s