2022 11 17 DeepMath Day 2 Ben Shaul

2022 11 17 DeepMath Day 2 Galanti

2022 11 17 DeepMath Day 2 Solla

2022 11 17 DeepMath Day 2 Soudry

2022 11 17 DeepMath Day 2 Tarmoun

2022 11 17 DeepMath Day 1 Bach

2022 11 17 DeepMath Day 1 Bombari

2022 11 17 DeepMath Day 1 Ghosh

2022 11 17 DeepMath Day 1 Kiani

DeepMath 2021: Day 1 Session 1 (Opening Remarks, Mallat, Gauthier)

DeepMath 2021: Day 1 Session 2 (Singh, Bordelon, Zhu)

DeepMath 2021: Day 1 Session 3 (Ergen & Pilanci, Willett)

DeepMath 2021: Day 2 Session 1 (Uhler, Kevrekidis, Loureiro)

DeepMath 2021: Day 2 Session 2 (Arora, Wang)

DeepMath 2021: Day 2 Session 3 (Refinetti, Chaudhuri)

Lenka Zdeborova - Insights on gradient-based algorithms in high-dimensional non-convex learning

Francesa Mignacco - Dynamical Mean-Field Theory for SGD in Gaussian Mixture Classification

Stefanie Jegelka - Representation and Learning in Graph Neural Networks

Rika Antonova - Analytic Manifold Learning with Neural Networks

Yi Sun - Data Augmentation as Stochastic Optimization

Rene Vidal - Keynote: Mathematics of Deep Learning

Gitta Kutyniok - Spectral Graph Convolutional Neural Networks Do Generalize

Maksim Maydanskiy - Spatial Transformations in Convolutional Networksand Invariant Recognition

Stéphane d'Ascoli - Reconciling Double Descent With Older Ideas

Demba Ba - Deeply-Sparse Signal Representations

Eero Simoncelli - Making use of the Prior Implicit in a Denoiser

Melanie Weber - Learning a Robust Large-Margin Classifier in Hyperbolic Space

Amartya Mitra - LEAD: Least Action Dynamics forMin-Max Optimization

Sejun Park - Expressive Power of Narrow Networks

Abdulkadir Canatar - Statistical Mechanics of Generalization in Kernel Regression