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Payel Das - Design and Evaluation of Foundation Models and Generative AI in Molecular Space
Presenter
- Payel Das
January 23, 2023
IPAM
Frank Noe - Advancing molecular simulation with deep learning - IPAM at UCLA
Presenter
- Frank Noe
January 23, 2023
IPAM
Maxim Ziatdinov - Bits and Atoms: Exploring the Intersection of Machine Learning and Microscopy
Presenter
- Maxim Ziatdinov
January 27, 2023
IPAM
Kyunghyun Cho - Lab-in-the-loop de novo antibody design - what are we missing from machine learning?
Presenter
- Kyunghyun Cho
January 25, 2023
IPAM
Cecelia Clementi - Coarse-graining classical and quantum systems - IPAM at UCLA
Presenter
- Cecelia Clementi
January 23, 2023
IPAM
Steve Brunton - Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics
Presenter
- Steve Brunton
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
Rafael Gomez Bombarelli - End-to-end learning and auto-differentiation: forces, uncertainties, etc.
Presenter
- Rafael Gomez-Bombarelli
January 24, 2023
IPAM
Xavier Bresson - Graph MLP-Mixer for Molecular Analysis - IPAM at UCLA
Presenter
- Xavier Bresson
January 25, 2023
IPAM
Jutta Rogal - Machine learning collective variables for sampling of structural transformations
Presenter
- Jutta Rogal
January 26, 2023
IPAM
Kyle Cranmer - Connections and cross pollination from quarks to the cosmos - IPAM at UCLA
Presenter
- Kyle Cranmer
January 26, 2023
IPAM
Bruno Correia - Exploring new molecular representations for the design of biological function
Presenter
- Bruno Correia
January 26, 2023
IPAM