Quantum Machine Learning in Chemical Compound Space

Abstract

Rather than numerically solving the computationally demanding equations of quantum or statistical mechanics, machine learning methods can infer approximate solutions, interpolating previously acquired property data sets of molecules and materials. The case is made for quantum machine learning: An inductive molecular modeling approach which can be applied to quantum chemistry problems.

Keywords: artificial intelligence; computational chemistry; machine learning; quantum mechanics.