Massively parallel fitting of Gaussian approximation potentials

Origins of structural and electronic transitions in disordered silicon

(2021) Volker L. Deringer et al.   NATURE

Uncertainty estimation for molecular dynamics and sampling

(2021) Giulio Imbalzano et al.   JOURNAL OF CHEMICAL PHYSICS

Gaussian Process Regression for Materials and Molecules

(2021) Volker L. Deringer et al.   CHEMICAL REVIEWS

On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events

(2020) Jonathan Vandermause et al.   npj Computational Materials

An accurate and transferable machine learning potential for carbon

(2020) Patrick Rowe et al.   JOURNAL OF CHEMICAL PHYSICS

Towards better efficiency of interatomic linear machine learning potentials

(2019) Alexandra M. Goryaeva et al.   COMPUTATIONAL MATERIALS SCIENCE

SchNet – A deep learning architecture for molecules and materials

(2018) K. T. Schütt et al.   JOURNAL OF CHEMICAL PHYSICS

Machine Learning a General-Purpose Interatomic Potential for Silicon

(2018) Albert P. Bartók et al.   Physical Review X

An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO 2

(2016) Nongnuch Artrith et al.   COMPUTATIONAL MATERIALS SCIENCE

Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials

(2016) Alexander V. Shapeev   MULTISCALE MODELING & SIMULATION

Reproducibility in density functional theory calculations of solids

(2016) K. Lejaeghere et al.   SCIENCE

Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties

(2015) O. Anatole von Lilienfeld et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

(2015) A.P. Thompson et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Molecular Dynamics with On-the-Fly Machine Learning of Quantum-Mechanical Forces

(2015) Zhenwei Li et al.   PHYSICAL REVIEW LETTERS

On representing chemical environments

(2013) Albert P. Bartók et al.   PHYSICAL REVIEW B

Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons

(2010) Albert P. Bartók et al.   PHYSICAL REVIEW LETTERS

CUR matrix decompositions for improved data analysis

(2009) Michael W. Mahoney et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA