Videos

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Feature purification: How adversarial training can perform robust deep learning Thumbnail

Feature purification: How adversarial training can perform robust deep learning

Presenter
  • Yuanzhi Li
March 16, 2020
IAS

Tutorial - Introductory Talk - Data-Driven Reduced Order Models As Deep Prior Neural Networks In Inverse Scattering

Presenter
  • Mikhail Zaslavsky
February 7, 2020
ICERM
MR image acquisition and reconstruction in the era of deep learning Thumbnail

MR image acquisition and reconstruction in the era of deep learning

Presenter
  • Florian Knoll
January 30, 2020
IPAM
Machine learning with neural networks: the importance of data structure Thumbnail

Machine learning with neural networks: the importance of data structure

Presenter
  • Marc Mezard
November 21, 2019
IPAM
Covariant neural network architectures for learning physics Thumbnail

Covariant neural network architectures for learning physics

Presenter
  • Risi Kondor
November 18, 2019
IPAM
Reinforcement Learning, Deep Learning,?and the Role of Policy Gradient Methods Thumbnail

Reinforcement Learning, Deep Learning,?and the Role of Policy Gradient Methods

Presenter
  • Sham Kakade
October 18, 2019
IAS
From Classical Statistics to Modern ML: the Lessons of Deep Learning Thumbnail

From Classical Statistics to Modern ML: the Lessons of Deep Learning

Presenter
  • Mikhail Belkin
October 16, 2019
IAS
Exploiting the 3D Geometry and the Structure of the World in Deep Learning Thumbnail

Exploiting the 3D Geometry and the Structure of the World in Deep Learning

Presenter
  • Ersin Yumer
May 24, 2019
IPAM
Topological transitions (and symmetries) of input representations in Deep Learning Thumbnail

Topological transitions (and symmetries) of input representations in Deep Learning

Presenter
  • Naftali Tishby
May 1, 2019
IPAM
Towards demystifying over-parameterization and early stopping in deep learning Thumbnail

Towards demystifying over-parameterization and early stopping in deep learning

Presenter
  • Mahdi Soltanolkotabi
May 1, 2019
IPAM
Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling and computation under uncertainty Thumbnail

Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling and computation under uncertainty

Presenter
  • Paris Perdikaris
September 28, 2018
IPAM
Representations of High Dimensional Data 07/13/18 - Introduction to Deep Learning Thumbnail

Representations of High Dimensional Data 07/13/18 - Introduction to Deep Learning

July 13, 2018
SLMath