Author

Joseph W. Abbott

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Preprint Oct 2026

Overcoming the limitations of body-ordered potentials for atomistic machine learning

Machine-learning interatomic potentials have become indispensable tools in atomistic simulations. The most popular models rely heavily on physical priors, such as locality, smoothness and symmetry, that are assumed to improve the accuracy and transferability of the trained models. However, recent evidence suggests that...

Filippo Bigi, M. Domina, Maximilian L. Ach et al. · 0 citations

#machine learning Preprint Sep 2026

A strategic roadmap for an atomistic machine-learning ecosystem

Data-driven machine learning (ML) techniques have become an essential tool in many domains of science. Their application to atomistic simulations of matter is particularly widespread and impactful. This success is due largely to the existence of a well-developed and established physics-based modeling framework, ranging...

Jörg Behler, Michele Ceriotti, Cecilia Clementi et al. · 0 citations