Videos

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Solving Quantum Many-Body Problems with Deep Neural Networks Thumbnail

Solving Quantum Many-Body Problems with Deep Neural Networks

Presenter
  • Han Pu
September 27, 2019
IPAM
Physics-Informed (and -informative) Generative Modelling in Astronomy Thumbnail

Physics-Informed (and -informative) Generative Modelling in Astronomy

Presenter
  • Joshua Bloom
September 23, 2019
IPAM
Bridging Deep Neural Networks and Differential Equations for Image Analysis and Beyond Thumbnail

Bridging Deep Neural Networks and Differential Equations for Image Analysis and Beyond

Presenter
  • Bin Dong
May 1, 2019
IPAM
Infinite-Width Bounded-Norm Networks: A View from Function Space Thumbnail

Infinite-Width Bounded-Norm Networks: A View from Function Space

Presenter
  • Nathan Srebro
April 30, 2019
IPAM
Deep Geometric Prior for Surface Reconstruction Thumbnail

Deep Geometric Prior for Surface Reconstruction

Presenter
  • Joan Bruna
April 4, 2019
IPAM
Tutorial on Spectral and Graph ConvNets (Part 2/2) Thumbnail

Tutorial on Spectral and Graph ConvNets (Part 2/2)

Presenter
  • Xavier Bresson
March 15, 2019
IPAM
Tutorial on Spectral and Graph ConvNets (Part 1/2) Thumbnail

Tutorial on Spectral and Graph ConvNets (Part 1/2)

Presenter
  • Xavier Bresson
March 15, 2019
IPAM
Non-local macroscopic models accounting for the presence of autonomous vehicles Thumbnail

Non-local macroscopic models accounting for the presence of autonomous vehicles

Presenter
  • Paola Goatin
February 27, 2019
IPAM
Rank optimality for the Burer-Monteiro factorization Thumbnail

Rank optimality for the Burer-Monteiro factorization

Presenter
  • Irène Waldspurger
February 12, 2019
IPAM
High-Performance Communication for Machine Learning Thumbnail

High-Performance Communication for Machine Learning

Presenter
  • Torsten Hoefler
November 5, 2018
IPAM
Is non-convex optimization really hard? A couple of recent stories Thumbnail

Is non-convex optimization really hard? A couple of recent stories

Presenter
  • Emmanuel Candès
September 26, 2018
IPAM
Hierarchical Bayesian Models for Inverse Problems and Uncertainty Quantification Thumbnail

Hierarchical Bayesian Models for Inverse Problems and Uncertainty Quantification

August 20, 2018
SAMSI