Learning Together: Towards foundation models for machine learning interatomic potentials with meta-learning

Alice Allen
April 8, 2024

Matrix Function Networks for learning non local quantum effects.

Ilyes Batatia
April 8, 2024

Pyiron: workflows for the development and assessment of interatomic potentials

Jan Janssen
April 8, 2024

Atomic cluster expansion for modeling local and semilocal atomic interactions

Ralf Drautz
April 8, 2024

Physics-Inspired Machine Learning Methods: A Status Report on Predictive Chemistry

Teresa Head-Gordon
April 8, 2024

Exploring Compositional and Configurational Chemical Space with Explainable AI

Alexandre Tkatchenko
March 29, 2024

Bridging Scales in Materials Modeling With Occam-Shaved Machine Learning

Luca Ghiringhelli
March 29, 2024

Harnessing The Properties of Equivariant Neural Networks To Understand And Design Atomic Systems

Tess Smidt
March 29, 2024

Extrapolating Unconverged GW Energies up to the Complete Basis Set Limit with a Linear Model

Fabien Bruneval
March 28, 2024