MSML2020 Invited Talk by Prof. Anna Gilbert, Yale University

(45:58)

MSML2020 Invited talk by Prof. Weinan E, Princeton University

(42:50)

MSML2020 Invited Talk by Prof. Roberto Car, Princeton University

(46:58)

MSML2020 Invited Talk by Prof. Lexing Ying, Stanford University

(48:11)

MSML2020 Invited Talk by Prof. Nathan Kutz, University of Washington

(56:47)

MSML2020 Invited Talk by Prof. Lenka Zdeborová, CNRS France

(43:33)

MSML2020 Invited Talk by Prof. Stanley Osher, University of California, Los Angeles

(42:26)

MSML2020 Invited Talk by Prof. George Karniadakis, Brown University

(43:43)

MSML2020 Invited Talk by Prof. Stéphane Mallat, Collége de France, ENS Paris, Flatiron Institute

(41:11)

محمد على كلاي رحمه الله يتكلم عن الجنة

(3:22)

Stéphane Mallat, mathématicien | Talents CNRS

(5:17)

The Universal Approximation Theorem for neural networks

(6:25)

Anima Anandkumar - Neural operator: A new paradigm for learning PDEs

(59:56)

Learning Physics Informed Machine Learning Part 2- Inverse Physics Informed Neural Networks (PINNs)

(30:52)

L'apprentissage face à la malédiction de la grande dimension (1) - Stéphane Mallat (2017-2018)

(1:37:16)

An extension of Physics Informed Neural Networks with a modal approach – IVADO Octobre Numérique

(13:16)

International Conference 2019

(3:26)

George Karniadakis - From PINNs to DeepOnets

(1:18:53)

MSML2020 Conference Introduction

(4:15)

MSML2020 Paper Presentation - Hugo Cui

(14:19)

MSML2020 Paper Presentation - Karthik Aadithya

(18:7)