225 citations · 242 across the 2 of their papers we have counts for
2 papers
cond-mat.str-el2020★ 17 cited
Gaussian Process States: A data-driven representation of quantum many-body physics
Aldo Glielmo, Yannic Rath, Gabor Csanyi +2
We present a novel, non-parametric form for compactly representing entangled many-body quantum states, which we call a `Gaussian Process State'. In contrast to other approaches, we…
physics.chem-ph2016★ 225 cited
Accurate Interatomic Force Fields via Machine Learning with Covariant Kernels
Aldo Glielmo, Peter Sollich, Alessandro De Vita
We present a novel scheme to accurately predict atomic forces as vector quantities, rather than sets of scalar components, by Gaussian Process (GP) Regression. This is based on mat…