Videos

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Understanding diffusion in complex materials using machine learning and a variational approach Thumbnail

Understanding diffusion in complex materials using machine learning and a variational approach

Presenter
  • Dallas Trinkle
May 16, 2024
IMSI
Upscaling of dislocation dynamics via automated on-the-fly active learning workflows from atomistics Thumbnail

Upscaling of dislocation dynamics via automated on-the-fly active learning workflows from atomistics

Presenter
  • Soumendu Bagchi
May 14, 2024
IMSI
Algorithms, Approximation, and Learning in Market and Mechanism Design: "Algorithmic Contract Design" Thumbnail

Algorithms, Approximation, and Learning in Market and Mechanism Design: "Algorithmic Contract Design"

November 8, 2023
SLMath
Set Chasing, with an application to online shortest path Thumbnail

Set Chasing, with an application to online shortest path

Presenter
  • Sébastien Bubeck
April 18, 2022
IAS
The absorption method, and an application to an old Ramsey problem Thumbnail

The absorption method, and an application to an old Ramsey problem

Presenter
  • Matija Bucic
March 29, 2022
IAS
Relative quantum cohomology and other stories Thumbnail

Relative quantum cohomology and other stories

Presenter
  • Sara Tukachinsky
April 9, 2021
IAS
Yang-Mills Instantons, Quivers and Bows Thumbnail

Yang-Mills Instantons, Quivers and Bows

Presenter
  • Sergey Cherkis
April 5, 2021
IAS
Differential Operators for Generating Structured Adversarial Examples Thumbnail

Differential Operators for Generating Structured Adversarial Examples

Presenter
  • Hossein Mobahi
April 22, 2020
IPAM
Equality Alone Does not Simulate Randomness Thumbnail

Equality Alone Does not Simulate Randomness

Presenter
  • Marc Vinyals
January 27, 2020
IAS
Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity II Thumbnail

Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity II

Presenter
  • Russell Impagliazzo
November 14, 2017
IAS
Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity I Thumbnail

Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity I

Presenter
  • Russell Impagliazzo
November 13, 2017
IAS

Extending Levelt's Propositions to perceptual multistability involving interocular grouping

Presenter
  • Yunjiao Wang
January 28, 2016
MBI