In our recent study, we propose using machine learning (ML) to correct differences in properties calculated at two quantum chemical (QC) methods with different accuracy. In the Δ-ML approach ML model is trained on differences between some property calculated at …

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We propose using machine learning (ML) for improving semiempirical Hamiltonian. Given sufficiently large training set ML can be used to correct parameters of semiempirical quantum chemical (SQC) method individually for any target molecule. Such automatic parametrization technique (APT) stands in …

Machine Learning of Semiempirical Parameters Read more »