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Quantum Machine Learning in Chemical Compound Space

Type of publication Peer-reviewed
Publikationsform Other publication (peer-review)
Author von Lilienfeld O. Anatole,
Project Sampling chemical space with alchemical perturbation theory
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Other publication (peer-review)

Publisher Wiley, Germany
Volume (Issue) 57(16)
Page(s) 4164 - 4169
Title of proceedings Angewandte Chemie International Edition
DOI 10.1002/anie.201709686

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.
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