Videos

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Carlos Bravo Prieto - Understanding quantum machine learning also requires rethinking generalization Thumbnail

Carlos Bravo Prieto - Understanding quantum machine learning also requires rethinking generalization

Presenter
  • Carlos Prieto
October 19, 2023
IPAM
Validation and Reproducibility by Geometry, for Unsupervised Learning Thumbnail

Validation and Reproducibility by Geometry, for Unsupervised Learning

Presenter
  • Marina Meila
October 31, 2019
IPAM
Interpretability for everyone Thumbnail

Interpretability for everyone

Presenter
  • Been Kim
April 15, 2020
IAS
Towards a Digital Twin Framework with Uncertainty Quantification: Machine Learning, Bayesian Optimization and Model Predictive Control Thumbnail

Towards a Digital Twin Framework with Uncertainty Quantification: Machine Learning, Bayesian Optimization and Model Predictive Control

Presenter
  • Wei Chen
April 23, 2025
IMSI
Deep Gaussian Process Surrogates for Computer Experiments Thumbnail

Deep Gaussian Process Surrogates for Computer Experiments

Presenter
  • Robert Gramacy
August 31, 2022
IMSI
Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning Thumbnail

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

Presenter
  • Daniel Kuhn
February 26, 2020
IPAM
Generative and variational modeling for quantum many-body physics Thumbnail

Generative and variational modeling for quantum many-body physics

Presenter
  • Giuseppe Carleo
September 27, 2019
IPAM
Learning from Conjugated Polymers: Statistical Data Mining from 50 Million and Counting Thumbnail

Learning from Conjugated Polymers: Statistical Data Mining from 50 Million and Counting

Presenter
  • Geoffrey Hutchison
December 6, 2016
IPAM
Learning with Few Labeled Data Thumbnail

Learning with Few Labeled Data

Presenter
  • Pratik Chaudhari
May 7, 2020
SLMath
Learning with few labeled data Thumbnail

Learning with few labeled data

Presenter
  • Pratik Chaudhari
April 23, 2020
IPAM
Simultaneous exploring and learning PES Thumbnail

Simultaneous exploring and learning PES

Presenter
  • Alexander Shapeev
October 31, 2017
IPAM
Extracting insight from large networks: small-scale structures, large-scale structures, and their implications for machine learning and data analysis Thumbnail

Extracting insight from large networks: small-scale structures, large-scale structures, and their implications for machine learning and data analysis

Presenter
  • Michael Mahoney
October 25, 2011
IMA