Videos

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Quantum Machine Learning Thumbnail

Quantum Machine Learning

Presenter
  • Anatole von Lilienfeld
October 17, 2019
IPAM
Model Interpretability for Building Confidence and Sparking Insight in Scientific Applications Thumbnail

Model Interpretability for Building Confidence and Sparking Insight in Scientific Applications

Presenter
  • Julia Ling
October 14, 2019
IPAM
Background reduction in searches for gravitational-wave signals from supernovae: A machine learning approach Thumbnail

Background reduction in searches for gravitational-wave signals from supernovae: A machine learning approach

Presenter
  • Marco Cavaglia
February 1, 2019
IPAM

Nonlinear reduced-order modeling - Using machine learning to enable extreme-scale simulation for many-query problems

Presenter
  • Kevin Carlberg
January 29, 2019
ICERM
Stochastic Surface Walking Method for Reaction Sampling and the Combination with Machine Learning Thumbnail

Stochastic Surface Walking Method for Reaction Sampling and the Combination with Machine Learning

Presenter
  • Zhi-Pan Liu
October 20, 2017
IPAM
Using machine learning to map the structure and predict the properties of materials and molecules Thumbnail

Using machine learning to map the structure and predict the properties of materials and molecules

Presenter
  • Michele Ceriotti
September 27, 2016
IPAM
Intelligent learning: similarity control and knowledge transfer Thumbnail

Intelligent learning: similarity control and knowledge transfer

Presenter
  • Vladimir Vapnik
March 30, 2015
IAS
High-throughput Data and New representations for Models and Machine Learning Thumbnail

High-throughput Data and New representations for Models and Machine Learning

Presenter
  • Gus Hart
February 24, 2015
IPAM
Statistical Learning and Bayesian Inference and Topology Thumbnail

Statistical Learning and Bayesian Inference and Topology

Presenter
  • Sayan Mukherjee
October 2, 2013
IMA
A Mathematical Perspective On Contrastive Learning Thumbnail

A Mathematical Perspective On Contrastive Learning

Presenter
  • Ricardo Baptista
October 7, 2025
IMSI
Guang Lin - Scalable algorithms for Bayesian deep learning via stochastic gradient Monte Carlo Thumbnail

Guang Lin - Scalable algorithms for Bayesian deep learning via stochastic gradient Monte Carlo

Presenter
  • Guang Lin
July 16, 2025
IPAM
A Neural Network Approach to Learning Steady States and Their Stability of Parametric Dynamical Systems Thumbnail

A Neural Network Approach to Learning Steady States and Their Stability of Parametric Dynamical Systems

Presenter
  • Xiaochuan Tian
May 15, 2024
IMSI