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Luis Barroso-Luque

2 accepted papers

2025

Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction

ICML 2025oral

Machine learning interatomic potentials (MLIPs) have become increasingly effective at approximating quantum mechanical calculations at a fraction of the computational cost. However, lower errors on held out test sets do not always translate to improved results on downstream physical property predict…

Cited by 6SourcePDFScholar
2025

UMA: A Family of Universal Models for Atoms

NeurIPS 2025spotlight

The ability to quickly and accurately compute properties from atomic simulations is critical for advancing a large number of applications in chemistry and materials science including drug discovery, energy storage, and semiconductor manufacturing. To address this need, we present a family of Univers…

Cited by 0SourceScholar