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A Framework for Generalization Analysis of Machine-Learned Interatomic Potentials: A Case Study on Crystalline Defects
Presenter
- Yangshuai Wang
April 9, 2024
IMSI
Unpacking the ingredients of atomic representations: machine learning force fields and beyond
Presenter
- Jigyasa Nigam
April 9, 2024
IMSI
Pyiron: workflows for the development and assessment of interatomic potentials
Presenter
- Jan Janssen
April 8, 2024
IMSI
Physics-Inspired Machine Learning Methods: A Status Report on Predictive Chemistry
Presenter
- Teresa Head-Gordon
April 8, 2024
IMSI
Atomic cluster expansion for modeling local and semilocal atomic interactions
Presenter
- Ralf Drautz
April 8, 2024
IMSI
Matrix Function Networks for learning non local quantum effects.
Presenter
- Ilyes Batatia
April 8, 2024
IMSI
Learning Together: Towards foundation models for machine learning interatomic potentials with meta-learning
Presenter
- Alice Allen
April 8, 2024
IMSI
Bridging Scales in Materials Modeling With Occam-Shaved Machine Learning
Presenter
- Luca Ghiringhelli
March 29, 2024
IMSI
Harnessing The Properties of Equivariant Neural Networks To Understand And Design Atomic Systems
Presenter
- Tess Smidt
March 29, 2024
IMSI
Exploring Compositional and Configurational Chemical Space with Explainable AI
Presenter
- Alexandre Tkatchenko
March 29, 2024
IMSI
Extrapolating Unconverged GW Energies up to the Complete Basis Set Limit with a Linear Model
Presenter
- Fabien Bruneval
March 28, 2024
IMSI