Bayesian and Equivariant Force Fields for the Description of Metals in their Bulk, Surface, and Nano-Scale Forms

Cameron Owen
April 10, 2024

Information-theoretic approach to atomic cluster expansion (ACE)

Cas van der Oord
April 10, 2024

Machine-learning of long-range, non-bonded interactions

Michele Ceriotti
April 10, 2024

Lightning Talks for Junior Participants

April 10, 2024

A MACE force field for all of materials chemistry

Gábor Csanyi
April 9, 2024

Unpacking the ingredients of atomic representations: machine learning force fields and beyond

Jigyasa Nigam
April 9, 2024

Environment-adaptive machine learning potentials for atomistic simulations of materials under extreme conditions

Ngoc-Cuong Nguyen
April 9, 2024

A Framework for Generalization Analysis of Machine-Learned Interatomic Potentials: A Case Study on Crystalline Defects

Yangshuai Wang
April 9, 2024

Lightning Talks for Junior Participants

April 9, 2024