Machine Learning of Molecular Electronic Properties in Chemical Compound Space

@article{Montavon2013MachineLO,
  title={Machine Learning of Molecular Electronic Properties in Chemical Compound Space},
  author={Gr'egoire Montavon and M. Rupp and Vivekanand V. Gobre and {\'A}. V{\'a}zquez-Mayagoitia and Katja Hansen and A. Tkatchenko and K. Muller and O. A. V. Lilienfeld},
  journal={New Journal of Physics},
  year={2013},
  volume={15},
  pages={095003}
}
  • Gr'egoire Montavon, M. Rupp, +5 authors O. A. V. Lilienfeld
  • Published 2013
  • Physics
  • New Journal of Physics
    • The combination of modern scientific computing with electronic structure theory can lead to an unprecedented amount of data amenable to intelligent data analysis for the identification of meaningful, novel and predictive structure?property relationships. Such relationships enable high-throughput screening for relevant properties in an exponentially growing pool of virtual compounds that are synthetically accessible. Here, we present a machine learning model, trained on a database of ab initio… CONTINUE READING
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