On the equivalence of molecular graph convolution and molecular wave function with poor basis set

1 code implementation • NeurIPS 2020 • Masashi Tsubaki, Teruyasu Mizoguchi

In this study, we demonstrate that the linear combination of atomic orbitals (LCAO), an approximation of quantum physics introduced by Pauling and Lennard-Jones in the 1920s, corresponds to graph convolutional networks (GCNs) for molecules.

Quantum deep field: data-driven wave function, electron density generation, and atomization energy prediction and extrapolation with machine learning

1 code implementation • 16 Nov 2020 • Masashi Tsubaki, Teruyasu Mizoguchi

Deep neural networks (DNNs) have been used to successfully predict molecular properties calculated based on the Kohn--Sham density functional theory (KS-DFT).

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