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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
Presenter
- Xiaochuan Tian
May 15, 2024
IMSI
Learning the committor, free energy profile, and rates with ML-driven path sampling simulations
Presenter
- Roberto Covino
April 22, 2024
IMSI
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
Presenter
- Boris Kozinsky
April 17, 2023
IPAM
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
Presenter
- Kevin Kelly
December 2, 2022
IPAM
Anouar Benali - multideterminant many-body methods to describe ground and excited state properties
Presenter
- Anouar Benali
May 25, 2022
IPAM
Robert Webber - Approximate matrix eigenvalues, subspace iteration w/ repeated random sparsification
Presenter
- Robert Webber
May 25, 2022
IPAM