Videos

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Machine Learning for discrete optimization: Graph Neural Networks, generalization under shifts, and loss functions

Presenter
  • Stefanie Jegelka
April 26, 2023
ICERM
Stefanie Jegelka - Two aspects of learning algorithms: generalization under shifts & loss functions Thumbnail

Stefanie Jegelka - Two aspects of learning algorithms: generalization under shifts & loss functions

Presenter
  • Stefanie Jegelka
March 2, 2023
IPAM

Stephan Garcia - LatMath 2022 - IPAM's Latinx in the Mathematical Sciences Conference

Presenter
  • Stephan Garcia
July 9, 2022
IPAM

Stochastic gradient descent for noise with ML-type scaling

Presenter
  • Stephan Wojtowytsch
July 9, 2021
ICERM
Learning in Graph Neural Networks Thumbnail

Learning in Graph Neural Networks

Presenter
  • Stefanie Jegelka
April 15, 2021
IMSI
Task structure and generalization in graph neural networks Thumbnail

Task structure and generalization in graph neural networks

Presenter
  • Stefanie Jegelka
February 25, 2021
IPAM

Supercharacters and their superpowers- the graphic nature of exponential sums

Presenter
  • Stephan Garcia
October 23, 2019
ICERM
Improving PDE solvers and PDE-constrained optimization with deep learning and differentiable programming Thumbnail

Improving PDE solvers and PDE-constrained optimization with deep learning and differentiable programming

Presenter
  • Stephan Hoyer
October 18, 2019
IPAM
Representational Power of Graph Neural Networks Thumbnail

Representational Power of Graph Neural Networks

Presenter
  • Stefanie Jegelka
October 18, 2019
IAS
Limit Theorems for PCA Like Analysis on Non-Euclidean Spaces Thumbnail

Limit Theorems for PCA Like Analysis on Non-Euclidean Spaces

Presenter
  • Stephan Huckemann
April 2, 2019
IPAM

Three bases and other tricks to replace Hankel and Toeplitz

Presenter
  • Stefanie Petermichl
June 7, 2018
ICERM
Arithmetic theta series Thumbnail

Arithmetic theta series

Presenter
  • Stephan Kudla
March 8, 2018
IAS