{
  "institution" : "Fritz Haber Institute of the Max Planck Society",
  "department" : "Theory",
  "link-rel-canonical-url" : "https://openkim.org/profile/mrupp",
  "email" : "",
  "last-name" : "Rupp",
  "city" : "Berlin",
  "username" : "mrupp",
  "state" : "",
  "first-name" : "Matthias",
  "profile-picture" : "matthias_rupp.jpg",
  "title" : "Dr.",
  "page-title" : "Matthias Rupp",
  "bio" : "",
  "website" : "https://www.mrupp.info",
  "published-name" : "Matthias Rupp",
  "location-merged" : "Berlin, Germany",
  "description-of-work" : "Kernel-based machine learning models for fast and accurate estimation of electronic structure calculations outcomes.\r\n\r\nBibliography\r\n* Matthias Rupp: Machine Learning for Quantum Mechanics in a Nutshell, International Journal of Quantum Chemistry, 115(16): 1058–1073, 2015. DOI http://dx.doi.org/10.1002/qua.24954\r\n* Matthias Rupp, Raghunathan Ramakrishnan, O. Anatole von Lilienfeld: Machine Learning for Quantum Mechanical Properties of Atoms in Molecules, Journal of Physical Chemistry Letters, 6(16): 3309–3313, 2015. DOI http://dx.doi.org/10.1021/acs.jpclett.5b01456\r\n* John C. Snyder, Matthias Rupp, Katja Hansen, Klaus-Robert Müller, Kieron Burke: Finding Density Functionals with Machine Learning, Physical Review Letters, 108(25): 253002, 2012. DOI http://dx.doi.org/10.1103/PhysRevLett.108.253002\r\n* Matthias Rupp, Alexandre Tkatchenko, Klaus-Robert Müller, O. Anatole von Lilienfeld: Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning, Physical Review Letters, 108(5): 058301, 2012. DOI http://dx.doi.org/10.1103/PhysRevLett.108.058301\r\n\r\nComplete list at https://mrupp.info/publications.html",
  "country" : "DE",
  "openkim-user-id" : "a4c773d3-7e18-4c57-b2c0-176f0e630843"
}