Topics in Deep Learning Theory

Speaker: Don Rubin (Harvard Statistics) Title: Essential concepts of Causal inference—a remarkable history Abstract: I believe that a deep understanding of cause and effect, and how to estimate causal effects from data, complete with the associated mathematical notation and expressions, only evolved in the twentieth century.  The crucial idea of randomized experiments was apparently first proposed in 1925 in the context of […]

Speaker: Tom Hou, Caltech Title: Computer-assisted analysis of singularity formation of a regularized 3D Euler equation  

Speaker: Richard Kenyon, Brown Title: Harmonic functions and the chromatic polynomial