Videos

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Implicit Regularization in Deep Learning: Lessons Learned from Matrix and Tensor Factorization Thumbnail

Implicit Regularization in Deep Learning: Lessons Learned from Matrix and Tensor Factorization

Presenter
  • Nadav Cohen
March 31, 2021
IPAM
Graph Nets: The Next Generation Thumbnail

Graph Nets: The Next Generation

Presenter
  • Max Welling
July 21, 2020
IAS
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems Thumbnail

A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems

Presenter
  • Sammy Wu Fung
May 5, 2020
SLMath
A mean-field theory of lazy training in two-layer neural nets: entropic regularization and controlled McKean-Vlasov dynamics Thumbnail

A mean-field theory of lazy training in two-layer neural nets: entropic regularization and controlled McKean-Vlasov dynamics

Presenter
  • Maxim Raginsky
April 21, 2020
IPAM

Understanding and mitigating gradient flow pathologies in physics-informed neural networks

Presenter
  • Paris Perdikaris
April 21, 2020
ICERM
Splines and imaging: From compressed sensing to deep neural networks Thumbnail

Splines and imaging: From compressed sensing to deep neural networks

Presenter
  • MIchael Unser
January 27, 2020
IPAM
On the existence of wide flat minima in neural network landscapes: analytic and algorithm approaches Thumbnail

On the existence of wide flat minima in neural network landscapes: analytic and algorithm approaches

Presenter
  • Carlo Baldassi
November 20, 2019
IPAM
Capacity-resolution trade-off in the optimal learning of multiple low-dimensional manifolds by attractor neural networks Thumbnail

Capacity-resolution trade-off in the optimal learning of multiple low-dimensional manifolds by attractor neural networks

Presenter
  • Remi Monasson
November 18, 2019
IPAM
Curiosity, unobserved rewards and neural networks: On recent progress in building solid foundations for RL Thumbnail

Curiosity, unobserved rewards and neural networks: On recent progress in building solid foundations for RL

Presenter
  • Csaba Szepesvari
November 7, 2019
IAS
Automatic Feature Extraction from Hyperspectral Imagery using Deep Recurrent Neural Networks Thumbnail

Automatic Feature Extraction from Hyperspectral Imagery using Deep Recurrent Neural Networks

Presenter
  • Joshua Agar
September 25, 2019
IPAM
Deep Learning Opening Workshop: A Survey of Statistical Research in Neural Networks and Deep Learning, Xiaoming Huo Thumbnail

Deep Learning Opening Workshop: A Survey of Statistical Research in Neural Networks and Deep Learning, Xiaoming Huo

August 12, 2019
SAMSI

Partial Differential Equations Approaches to Optimization and Regularization of Deep Neural Networks

Presenter
  • Adam Oberman
November 2, 2018
ICERM