Videos

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New deep neural networks solving non-linear inverse problems Thumbnail

New deep neural networks solving non-linear inverse problems

Presenter
  • Matti Lassas
April 20, 2020
IPAM
Learning Controllable Representations Thumbnail

Learning Controllable Representations

Presenter
  • Richard Zemel
April 2, 2020
IAS
Trustworthy deep learning Thumbnail

Trustworthy deep learning

Presenter
  • Stanley Osher
January 27, 2020
IPAM
Understanding deep networks and its role played in prioritized search Thumbnail

Understanding deep networks and its role played in prioritized search

Presenter
  • Yuandong Tian
November 7, 2019
IAS
Interpreting Deep Neural Networks Thumbnail

Interpreting Deep Neural Networks

Presenter
  • Bin Yu
October 17, 2019
IAS
Structured Deep Generative Models Thumbnail

Structured Deep Generative Models

Presenter
  • Adji Bousso Dieng
October 16, 2019
IPAM
Why Deep Learning Works: Heavy-Tailed Random Matrix Theory as an Example of Physics Informed Machine Learning Thumbnail

Why Deep Learning Works: Heavy-Tailed Random Matrix Theory as an Example of Physics Informed Machine Learning

Presenter
  • Michael Mahoney
October 14, 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
Geometric deep learning for 3D shape analysis (Part 2/2) Thumbnail

Geometric deep learning for 3D shape analysis (Part 2/2)

Presenter
  • MIchael Bronstein
March 12, 2019
IPAM
Geometric deep learning for 3D shape analysis (Part 1/2) Thumbnail

Geometric deep learning for 3D shape analysis (Part 1/2)

Presenter
  • Michael Bronstein
March 12, 2019
IPAM

Collapse of deep and narrow neural nets

Presenters
  • Lu Lu
  • Yeonjong Shin
January 28, 2019
ICERM
Scalable deep learning: using parallel algorithms and HPC systems to train large models on big data set Thumbnail

Scalable deep learning: using parallel algorithms and HPC systems to train large models on big data set

Presenter
  • Brian Van Essen
September 17, 2018
IPAM