A self-explainable neural network for quantum chemistry at orbital level.
Significant parts of the code have been taken from SchNetPack and SchNOrb.
[1] K. T. Schütt, M. Gastegger, A. Tkatchenko, K.-R. Müller, and R. J. Maurer. “Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions”. In: Nature Communications 10, 5024 (2019).
[2] K.T.Schütt, P.-J. Kindermans, H. E. Sauceda, S. Chmiela, A. Tkatchenko, and K.-R. Müller. “SchNet: a continuous-filter convolutional neural network for modeling quantum interactions”. In: Proceedings of the 31st International Conference on Neural Information Processing Systems. 2017, pp. 992–1002.
[3] K. T. Schütt, O. T. Unke, and M. Gastegger. “Equivariant message passing for the prediction of tensorial properties and molecular spectra”. In: Proceedings of the 38th International Conference on Machine Learning. Vol. 139. PMLR, 2021, pp. 9377–9388.