Data-driven many-body representations with chemical accuracy for molecular simulations from the gas to the condensed phase

Hydrogen bonding: Ab initio accuracy from fast interatomic Gaussian approximation potentials

Searching for the Holy Grail: Fast and accurate force fields

Thermodynamics of CuPt nanoalloys (vol 8, 9150, 2018)

Understanding the thermal properties of amorphous solids using machine-learning-based interatomic potentials

Machine-Learning Based Potential For Iron: Plasticity and Phase Transition

Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions.

Gaussian approximation potential modeling of lithium intercalation in carbon nanostructures.

Nested Transition Path Sampling

Thermodynamics of CuPt nanoalloys.