Videos

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Learning of neural networks w/ quantum computers & learning of quantum states with graphical models Thumbnail

Learning of neural networks w/ quantum computers & learning of quantum states with graphical models

October 16, 2023
IPAM
Interpretability and explainability from a causal lens Thumbnail

Interpretability and explainability from a causal lens

Presenter
  • Judea Pearl
October 16, 2019
IPAM

Steve Cowley - Multi-scale Plasma Turbulence — the key to fusion power

April 13, 2026
IPAM
Sanjoy Dasgupta - Neural machines: From fruit flies to embedded devices - IPAM at UCLA Thumbnail

Sanjoy Dasgupta - Neural machines: From fruit flies to embedded devices - IPAM at UCLA

Presenter
  • Sanjoy Dasgupta
November 4, 2024
IPAM
Large Scale Kriging by Substituting Optimization for Inversion Thumbnail

Large Scale Kriging by Substituting Optimization for Inversion

Presenter
  • Matthew Plumlee
September 1, 2022
IMSI
Daniel Schwen - MOOSE: Parallel sampling for rare event probabilities & inverse Bayesian inference Thumbnail

Daniel Schwen - MOOSE: Parallel sampling for rare event probabilities & inverse Bayesian inference

Presenter
  • Daniel Schwen
March 30, 2023
IPAM
Max Kleiman-Weiner - Multi-Agent Common Sense Thumbnail

Max Kleiman-Weiner - Multi-Agent Common Sense

Presenter
  • Max Kleiman-Weiner
February 16, 2022
IPAM

ML and AI in Combinatorics Research: Some Examples

Presenter
  • Blake Jackson
September 19, 2025
ICERM
Optimization, Sampling and Generative Modeling in Non-Euclidean Spaces Thumbnail

Optimization, Sampling and Generative Modeling in Non-Euclidean Spaces

Presenter
  • Molei Tao
May 15, 2024
IMSI
Machine Learning Density Functionals Thumbnail

Machine Learning Density Functionals

Presenter
  • Kieron Burke
March 26, 2024
IMSI
Machine Learning Summer School: Geometrical and Topological Data Analysis Thumbnail

Machine Learning Summer School: Geometrical and Topological Data Analysis

Presenters
  • Ery Arias-Castro
  • Yusu Wang
July 5, 2023
SLMath
Machine Learning Summer School: Theoretical and Methodological Aspects of Deep Learning Thumbnail

Machine Learning Summer School: Theoretical and Methodological Aspects of Deep Learning

Presenters
  • Mikhail Belkin
  • Lily Weng
June 27, 2023
SLMath