781 citations · 1.6k across the 27 of their papers we have counts for
4 papers · 1 filter
A Posteriori Error Estimate and Adaptivity for QM/MM Models of Crystalline Defects
Yangshuai Wang, James R. Kermode, Christoph Ortner +1
Hybrid quantum/molecular mechanics (QM/MM) models play a pivotal role in molecular simulations. These models provide a balance between accuracy, surpassing pure MM models, and comp…
Massively Parallel Fitting of Gaussian Approximation Potentials
Sascha Klawohn, James R. Kermode, Albert P. Bartók
We present a data-parallel software package for fitting Gaussian Approximation Potentials (GAPs) on multiple nodes using the ScaLAPACK library with MPI and OpenMP. Until now the ma…
Uncertainty quantification design principles for machine learning interatomic potentials: lessons learned from hierarchical Bayesian inference
Albert P. Bartók, Brennon L. Shanks, James. R. Kermode +1
Reliable uncertainty quantification (UQ) remains a major challenge for machine learning interatomic potentials (MLIPs). Here, we benchmark UQ strategies for message passing neural…
Shared Metadata for Data-Centric Materials Science
Luca M. Ghiringhelli, Carsten Baldauf, Tristan Bereau +32
The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps r…