Videos

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Bayesian nonparametrics and g-computation for causal inference in observational studies

Presenter
  • Jason Roy
January 15, 2019
ICERM
Machine learning methods for physics and chemistry 2: Deep learning Thumbnail

Machine learning methods for physics and chemistry 2: Deep learning

Presenter
  • Frank Noé
September 15, 2017
IPAM
Machine learning methods for physics and chemistry 1: Regression and Kernel methods Thumbnail

Machine learning methods for physics and chemistry 1: Regression and Kernel methods

Presenter
  • Frank Noé
September 15, 2017
IPAM
Delay and Cooperation in Nonstochastic Bandits Thumbnail

Delay and Cooperation in Nonstochastic Bandits

Presenter
  • Nicolo Cesa-Bianchi
May 17, 2016
IMA
Practically Relevant Theory and Theoretically Relevant Practice of Deep Learning Thumbnail

Practically Relevant Theory and Theoretically Relevant Practice of Deep Learning

Presenter
  • Shai Shalev-Shwartz
May 17, 2016
IMA

Learning how to rank via forbidden patterns - semirankings and the Erdos-Hajnal Conjecture

Presenter
  • Krzysztof Choromanski
February 14, 2014
ICERM
Spectral and geometric methods in learning Thumbnail

Spectral and geometric methods in learning

Presenter
  • Misha Belkin
October 28, 2008
IMA

Topology-Driven Learning for Biomedical Images – Uncertainty, Synthesis, and Prediction

Presenter
  • Chao Chen
May 20, 2026
ICERM

Hong Qin - Machine Learning of Local Confinement and Transport from the International Multi-Tokamak Confinement Profile Database

May 6, 2026
IPAM

Ammar Hakim - BEACONS and BEACONS-FM: Lighting a Path to Modular, Composable, Formally Verified Fusion Foundation Models

April 17, 2026
IPAM

Peter Benner - Discovery and Model Reduction of Hamiltonian Systems

April 15, 2026
IPAM

Li Wang - Suppressing Plasma Instability Through Constrained Optimization

April 14, 2026
IPAM