Electron-Density-Informed Molecular Property Prediction Using Surrogate Functionals
Machine learning methods are increasingly used to predict chemical properties directly from the molecular structure to bypass the often prohibitive cost of quantum mechanical calculations. Recent work has shown that including the ground-state electron density as input to the machine learning model can improve accuracy...
M. V. Klockow, Simon Wagner, Roman Remme et al.
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