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      The MolSSI QCA rchive project: An open‐source platform to compute, organize, and share quantum chemistry data

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          Most cited references 32

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          Molpro: a general-purpose quantum chemistry program package

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            Advances in molecular quantum chemistry contained in the Q-Chem 4 program package

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              Is Open Access

              Quantum-chemical insights from deep tensor neural networks

              Learning from data has led to paradigm shifts in a multitude of disciplines, including web, text and image search, speech recognition, as well as bioinformatics. Can machine learning enable similar breakthroughs in understanding quantum many-body systems? Here we develop an efficient deep learning approach that enables spatially and chemically resolved insights into quantum-mechanical observables of molecular systems. We unify concepts from many-body Hamiltonians with purpose-designed deep tensor neural networks, which leads to size-extensive and uniformly accurate (1 kcal mol−1) predictions in compositional and configurational chemical space for molecules of intermediate size. As an example of chemical relevance, the model reveals a classification of aromatic rings with respect to their stability. Further applications of our model for predicting atomic energies and local chemical potentials in molecules, reliable isomer energies, and molecules with peculiar electronic structure demonstrate the potential of machine learning for revealing insights into complex quantum-chemical systems.
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                Author and article information

                Contributors
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                Journal
                WIREs Computational Molecular Science
                WIREs Comput Mol Sci
                Wiley
                1759-0876
                1759-0884
                July 31 2020
                Affiliations
                [1 ]Molecular Sciences Software Institute Blacksburg Virginia USA
                [2 ]Department of Computer and Systems EngineeringAlexandria University Alexandria Egypt
                [3 ]Center for Computational Molecular Science and TechnologySchool of Chemistry and Biochemistry, Georgia Institute of Technology Atlanta Georgia USA
                [4 ]Data Science and Learning Division Argonne National Laboratory Lemont Illinois USA
                [5 ]Department of ChemistryVirginia Tech Blacksburg, Virginia USA
                Article
                10.1002/wcms.1491
                © 2020

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