Videos

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Using autoencoders as generative models to create forecast ensembles for data assimilation Thumbnail

Using autoencoders as generative models to create forecast ensembles for data assimilation

Presenter
  • Ian Grooms
October 31, 2022
IMSI
Accelerated Parametric Uncertainty Quantification and Optimal Data Acquisition in an Idealized Global Atmosphere Model Thumbnail

Accelerated Parametric Uncertainty Quantification and Optimal Data Acquisition in an Idealized Global Atmosphere Model

Presenter
  • Oliver Dunbar
October 31, 2022
IMSI
Machine learning for atomic and molecular simulations Thumbnail

Machine learning for atomic and molecular simulations

Presenter
  • Michele Ceriotti
November 18, 2019
IPAM
Machine-learning for materials and physics discovery through symbolic regression and kernel methods Thumbnail

Machine-learning for materials and physics discovery through symbolic regression and kernel methods

Presenter
  • Richard Hennig
September 26, 2019
IPAM
Machine Learning Models for Feature Selection and Classification of Traffic Anomalies Thumbnail

Machine Learning Models for Feature Selection and Classification of Traffic Anomalies

Presenter
  • Ljiljana Trajkovic
September 5, 2012
IMA
Interpretable machine learning for analysis and prediction of weather and climate extremes Thumbnail

Interpretable machine learning for analysis and prediction of weather and climate extremes

Presenter
  • Alex Cannon
March 3, 2025
IMSI

Transfer learning in deep operator networks

Presenter
  • Somdatta Goswami
June 7, 2023
ICERM
Machine learning-enabled enhanced sampling in biomolecular simulation and data-driven design of self-assembling photonic crystals and optoelectonic π-conjugated oligopeptides Thumbnail

Machine learning-enabled enhanced sampling in biomolecular simulation and data-driven design of self-assembling photonic crystals and optoelectonic π-conjugated oligopeptides

Presenter
  • Andrew Ferguson
September 9, 2019
IPAM
Maria Molina - Learning Without Labels: New Insights into Climate and Extremes - IPAM at UCLA Thumbnail

Maria Molina - Learning Without Labels: New Insights into Climate and Extremes - IPAM at UCLA

Presenter
  • Maria Molina
February 4, 2026
IPAM
Michael Scherbela - High accuracy wavefunctions using deep-learning-based variational Monte Carlo Thumbnail

Michael Scherbela - High accuracy wavefunctions using deep-learning-based variational Monte Carlo

Presenter
  • Michael Scherbela
May 27, 2022
IPAM
Julia Westermayr - Physically inspired machine learning for excited states Thumbnail

Julia Westermayr - Physically inspired machine learning for excited states

Presenter
  • Julia Westermayr
May 27, 2022
IPAM
Ilyes Batatia - Unified understanding of E(3)-Equivariant Interatomic Potentials Theory/Applications Thumbnail

Ilyes Batatia - Unified understanding of E(3)-Equivariant Interatomic Potentials Theory/Applications

Presenter
  • Ilyes Batatia
May 27, 2022
IPAM