This seminar and working session is held every Tuesdays from 11 a.m.-12 p.m. ET. It is associated with the project on Mathematics for Deep Learning. The goal of each session is to present a topic and open research questions in this area. It will serve as a backbone for the formation of spontaneous working groups around some of these questions.
Each session is either a presentation of 40 minutes followed by a discussion of 20 minutes or two presentations of 20 minutes followed by discussions of 10 minutes each. The slides and a bibliography of few papers is provided.
|November 10, 2020||David Donoho (Stanford), Chair Stephane Mallat (CCM)||Prevalence of Neural Collapse during the terminal phase of deep learning training||To be added|
|November 17, 2020||Joan Bruna (Flatiron CCM, NYU), Chair TBA||On depth separation for neural networks|
|November 24, 2020||Stefanie Jegelka (MIT), Chair Joan Bruna||Learning in Graph Neural Networks|
|December 1, 2020||Eric Vanden-Eijnden (NYU), Chair TBA|
|December 8, 2020||Lexing Ying (Stanford), Chair TBA|
|December 15, 2020||Eero Simoncelli (Flatiron CCN, NYU), Chair Stephane Mallat|