Videos

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Deep Neural Networks Motivated By Differential Equations (Part 1/2) Thumbnail

Deep Neural Networks Motivated By Differential Equations (Part 1/2)

Presenter
  • Lars Ruthotto
September 9, 2019
IPAM
Covariant neural networks for learning physical systems Thumbnail

Covariant neural networks for learning physical systems

Presenter
  • Imre Risi Kondor
May 1, 2019
IPAM
Convolutional neural networks in phase space and inverse problems for nonlinear wave equations Thumbnail

Convolutional neural networks in phase space and inverse problems for nonlinear wave equations

Presenter
  • Yiran Wang
January 30, 2019
IPAM

Deep Neural Networks for Data-Driven Turbulence Models

Presenter
  • Andrea Beck
January 30, 2019
ICERM

Deep Neural Networks and Partial Differential Equations - Approximation Theory and Structural Properties

Presenter
  • Philipp Petersen
January 29, 2019
ICERM

Deep Neural Network, Finite Element and Multigrid

Presenter
  • Jinchao Xu
January 28, 2019
ICERM

Which ReLU Net Architectures Give Rise to Exploding and Vanishing Gradients

Presenter
  • Boris Hanin
January 28, 2019
ICERM
Convolutional Neural Networks on Graphs Thumbnail

Convolutional Neural Networks on Graphs

Presenter
  • Xavier Bresson
February 7, 2018
IPAM
Interpretable Neural Network Models for Granger Causality Discovery Thumbnail

Interpretable Neural Network Models for Granger Causality Discovery

Presenter
  • Emily Fox
February 5, 2018
IPAM

Lipschitz bounds for general convolutional neural networks

Presenter
  • Dongmian Zou
September 26, 2017
IMA
Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy? Thumbnail

Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?

Presenter
  • Alex Bronstein
February 8, 2016
IPAM
Deriving neural circuits from first principles Thumbnail

Deriving neural circuits from first principles

Presenter
  • Mitya Chklovskii
October 5, 2015
SLMath