Mathematical and Computational Aspects of Machine Learning

7 October 2019 - 11 October 2019

Invited Speakers

[table view]

Jean Barbier

ICTP Trieste
Course: Mean field theory of high-dimensional Bayesian inference

Philipp Grohs

University of Vienna
Course: Approximation theory, Numerical Analysis and Deep Learning

Gabriel Peyré

ENS and CNRS, Paris
Course: Optimal Transport for Data Science

Lars Ruthotto

Emory University
Course: Numerical Methods for Deep Learning

Stefano Soatto (with Alessandro Achille)

UCLA
Course: Representation Learning