Implicitly perturbed Hamiltonian as a class of versatile and general-purpose molecular representations for machine learning

Abstract

Molecular representations are fundamental tools for machine-learning models. The current work introduces a new set of molecular representations demonstrated to enable accurate predictions of molecular conformational energy and solvation free energy.