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Steve Brunton - Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics
Presenter
- Steve Brunton
January 24, 2023
IPAM
Rafael Gomez Bombarelli - End-to-end learning and auto-differentiation: forces, uncertainties, etc.
Presenter
- Rafael Gomez-Bombarelli
January 24, 2023
IPAM
Kristin Persson - Data-Driven Design for Energy Materials - IPAM at UCLA
Presenter
- Kristin Persson
January 24, 2023
IPAM
Tommi Jaakola - Diffusion based distributional modeling of conformers, blind docking and proteins
Presenter
- Tommi Jaakola
January 24, 2023
IPAM
Mark Tuckerman - From A to B via a synthesis of rare-event sampling and machine learning
Presenter
- Mark Tuckerman
January 24, 2023
IPAM
Frank Noe - Advancing molecular simulation with deep learning - IPAM at UCLA
Presenter
- Frank Noe
January 23, 2023
IPAM
Patrick Riley - Symbolic Regression for Discovery of a DFT Functional - IPAM at UCLA
Presenter
- Patrick Riley
January 23, 2023
IPAM
Mohammed AlQuraishi - OpenFold: Lessons and insights from rebuilding and retraining AlphaFold2
Presenter
- Mohammed AlQuraishi
January 23, 2023
IPAM
Payel Das - Design and Evaluation of Foundation Models and Generative AI in Molecular Space
Presenter
- Payel Das
January 23, 2023
IPAM
Cecelia Clementi - Coarse-graining classical and quantum systems - IPAM at UCLA
Presenter
- Cecelia Clementi
January 23, 2023
IPAM
Vince Calhoun - Maximizing Information in neuroimaging: approaches for analysis and visualization
Presenter
- Vince Calhoun
January 13, 2023
IPAM
Pamela Douglas - Exploring XAI Techniques for Neuroimaging - IPAM at UCLA
Presenter
- Pamela Douglas
January 13, 2023
IPAM