Many-Body Coarse-Grained Interactions Using Gaussian Approximation Potentials

Constant-pressure nested sampling with atomistic dynamics.

Data-driven learning of total and local energies in elemental boron

A Machine Learning Potential for Graphene

Symmetry-Adapted Machine-Learning for Tensorial Properties of Atomistic Systems

Exploring structural space searching for carbon allotropes

Polytypism in the ground state structure of the Lennard-Jonesium.

Structural Simplicity as a Restraint on the Structure of Amorphous Silicon

Achieving DFT accuracy with a machine-learning interatomic potential: thermomechanics and defects in bcc ferromagnetic iron

Structural Simplicity as a Restraint on the Structure of Amorphous Silicon