200 citations · 1.2k across the 13 of their papers we have counts for
3 papers · 1 filter
Path-integral dynamics of water using curvilinear centroids
George Trenins, Michael J. Willatt, Stuart C. Althorpe
We develop a path-integral dynamics method for water that resembles centroid molecular dynamics (CMD), except that the centroids are averages of curvilinear, rather than cartesian,…
Atomic-scale representation and statistical learning of tensorial properties
Andrea Grisafi, David M. Wilkins, Michael J. Willatt +1
This chapter discusses the importance of incorporating three-dimensional symmetries in the context of statistical learning models geared towards the interpolation of the tensorial…
Machine-learning of atomic-scale properties based on physical principles
Michele Ceriotti, Michael J. Willatt, Gábor Csányi
We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the li…