# Publications

No. of Publications: 50

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## A deep neural network for molecular wave functions in quasi-atomic minimal basis representation

### A deep neural network for molecular wave functions in quasi-atomic minimal basis representation

M. Gastegger, A. McSloy, M. Luya, K. T. Schütt, R. J. Maurer, **J. Chem. Phys **153, 044123 (2020)

##### "We present an adaptation of the recently proposed SchNet for Orbitals (SchNOrb) deep convolutional neural network model [Nature Commun. 10, 5024 (2019)] for electronic wave functions in an optimised quasi-atomic minimal basis representation. For five organic molecules ranging from 5 to 13 heavy atoms, the model accurately predicts molecular orbital energies and wavefunctions and provides access to derived properties for chemical bonding analysis. Particularly for larger molecules, the model outperforms the original atomic-orbital-based SchNOrb method in terms of accuracy and scaling. "

## Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions

### Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions

Kristof T. Schütt, Michael Gastgger, Alexandre Tkatchenko, Klaus-Robert Müller, Reinhard J. Maurer, **Nature Commun.** 10, 5024 (2019)