{"id":"W1531674615","doi":"10.1021/acs.jpclett.5b00831","title":"Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space","year":2015,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry Letters","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":856,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Argonne National Laboratory; Natural Sciences and Engineering Research Council of Canada; Office of Science; Einstein Stiftung Berlin; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; U.S. Department of Energy; National Research Foundation of Korea; Deutsche Forschungsgemeinschaft; European Research Council; National Science Foundation","keywords":"Polarizability; Chemical space; Quantum nonlocality; Statistical physics; Representation (politics); Pairwise comparison; Molecule; Simple (philosophy); Density functional theory; Chemical bond; Space (punctuation); Computational chemistry; Chemistry; Chemical physics; Physics; Computer science; Quantum mechanics; Artificial intelligence; Quantum; Drug discovery","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null}