DOI: 10.1039/c6sc05720a ISSN:
ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost
J. S. Smith, O. Isayev, A. E. Roitberg- General Chemistry
We demonstrate how a deep neural network (NN) trained on a data set of quantum mechanical (QM) DFT calculated energies can learn an accurate and transferable atomistic potential for organic molecules containing H, C, N, and O atoms.