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

Diverse data generation for machine learning potentials

Danny Perez
April 9, 2024

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