Videos

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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
Learning the committor, free energy profile, and rates with ML-driven path sampling simulations Thumbnail

Learning the committor, free energy profile, and rates with ML-driven path sampling simulations

Presenter
  • Roberto Covino
April 22, 2024
IMSI
Introductory Workshop: Algorithms, Fairness, and Equity: "Epistemic Uncertainty, the AI Problem Understanding Gap and the Necessity of Structured Societal Context Knowledge for Safe, Robust AI" Thumbnail

Introductory Workshop: Algorithms, Fairness, and Equity: "Epistemic Uncertainty, the AI Problem Understanding Gap and the Necessity of Structured Societal Context Knowledge for Safe, Robust AI"

Presenter
  • Donald Martin
August 30, 2023
SLMath
Gabor Csányi - Machine learning potentials: from polynomials to message passing networks Thumbnail

Gabor Csányi - Machine learning potentials: from polynomials to message passing networks

Presenter
  • Gabor Csányi
April 17, 2023
IPAM
Boris Kozinsky - Uncertainty-aware machine learning models of many-body atomic interactions Thumbnail

Boris Kozinsky - Uncertainty-aware machine learning models of many-body atomic interactions

Presenter
  • Boris Kozinsky
April 17, 2023
IPAM
Tutorial on Conformal Prediction and Distribution-Free Uncertainty Quantification Thumbnail

Tutorial on Conformal Prediction and Distribution-Free Uncertainty Quantification

Presenter
  • Anastasios Angelopoulos
March 31, 2023
IMSI
Kevin Kelly - Machine Learning Enhanced Compressive Hyperspectral Imaging - IPAM at UCLA Thumbnail

Kevin Kelly - Machine Learning Enhanced Compressive Hyperspectral Imaging - IPAM at UCLA

Presenter
  • Kevin Kelly
December 2, 2022
IPAM
Anouar Benali - multideterminant many-body methods to describe ground and excited state properties Thumbnail

Anouar Benali - multideterminant many-body methods to describe ground and excited state properties

Presenter
  • Anouar Benali
May 25, 2022
IPAM