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Fast and accurate modeling of molecular atomization energies with machine learning.
Physical review letters, no. 5 (2012): 058301-058301
We introduce a machine learning model to predict atomization energies of a diverse set of organic molecules, based on nuclear charges and atomic positions only. The problem of solving the molecular Schrödinger equation is mapped onto a nonlinear statistical regression problem of reduced complexity. Regression models are trained on and com...More
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