22 citations · 78 across the 7 of their papers we have counts for
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physics.chem-ph2021★ 20 cited
SPAM: the Spectrum of Approximated Hamiltonian Matrices representations
Alberto Fabrizio, Ksenia R. Briling, Clemence Corminboeuf
Physics-inspired molecular representations are the cornerstone of similarity-based learning applied to solve chemical problems. Despite their conceptual and mathematical diversity,…
physics.chem-ph2021★ 6 cited
Impact of quantum-chemical metrics on the machine learning prediction of electron density
Ksenia R. Briling, Alberto Fabrizio, Clemence Corminboeuf
Machine learning (ML) algorithms have undergone an explosive development impacting every aspect of computational chemistry. To obtain reliable predictions, one needs to maintain th…