This is a reduced package of SchNetPack. Please, if you would like to use the original package go to SchNetPack
pip install nnpackage
This package is not intended to use directly, but via NNmeta
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[1] K.T. Schütt. F. Arbabzadah. S. Chmiela, K.-R. Müller, A. Tkatchenko.
Quantum-chemical insights from deep tensor neural networks. Nature Communications 8. 13890 (2017)
10.1038/ncomms13890 -
[2] K.T. Schütt. P.-J. Kindermans, H. E. Sauceda, S. Chmiela, A. Tkatchenko, K.-R. Müller.
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions. Advances in Neural Information Processing Systems 30, pp. 992-1002 (2017) link -
[3] K.T. Schütt. P.-J. Kindermans, H. E. Sauceda, S. Chmiela, A. Tkatchenko, K.-R. Müller.
SchNet - a deep learning architecture for molecules and materials. The Journal of Chemical Physics 148(24), 241722 (2018) 10.1063/1.5019779 -
[4] M. Gastegger, L. Schwiedrzik, M. Bittermann, F. Berzsenyi, P. Marquetand. wACSF—Weighted atom-centered symmetry functions as descriptors in machine learning potentials. The Journal of Chemical Physics, 148(24), 241709. (2018) 10.1063/1.5019667
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[5] J. Behler, M. Parrinello. Generalized neural-network representation of high-dimensional potential-energy surfaces. Physical Review Letters, 98(14), 146401. (2007) 10.1103/PhysRevLett.98.146401