Videos

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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
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 at the mesoscale: advances in analyzing and coarse-graining via data-driven approaches Thumbnail

Machine learning at the mesoscale: advances in analyzing and coarse-graining via data-driven approaches

Presenter
  • Rose Cersonsky
April 11, 2024
IMSI
Machine Learning (UC San Diego) Summer School: Geometrical and Topological Data Analysis Thumbnail

Machine Learning (UC San Diego) Summer School: Geometrical and Topological Data Analysis

June 26, 2023
SLMath

Operator Learning For Solving PDE-related Problems.

Presenter
  • zecheng zhang
June 7, 2023
ICERM

Multifidelity Deep Operator Networks

Presenter
  • Amanda Howard
June 7, 2023
ICERM

Machine-Learned Finite Element Exterior Calculus for Linear and Nonlinear Problems

Presenter
  • Jonas Actor
June 6, 2023
ICERM

Transfer learning for surrogate models of PDEs

Presenter
  • Adrienne Propp
June 6, 2023
ICERM

On Learning Operators

Presenter
  • Siddhartha Mishra
June 6, 2023
ICERM
Tradeoffs between Robustness and Accuracy Thumbnail

Tradeoffs between Robustness and Accuracy

Presenter
  • Percy Liang
April 16, 2020
IAS
Machine Learning in Materials Science: Recent Progress and Critical Next Steps Thumbnail

Machine Learning in Materials Science: Recent Progress and Critical Next Steps

Presenter
  • Rampi Ramprasad
September 26, 2016
IPAM
Diverse data generation for machine learning potentials Thumbnail

Diverse data generation for machine learning potentials

Presenter
  • Danny Perez
April 9, 2024
IMSI