Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions
Machine learning models can accurately predict atomistic chemical properties but do not provide access to the molecular electronic structure. Here the authors use a deep learning approach to predict the quantum mechanical wavefunction at high efficiency from which other ground-state properties can b...
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Autores principales: | K. T. Schütt, M. Gastegger, A. Tkatchenko, K.-R. Müller, R. J. Maurer |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
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Materias: | |
Acceso en línea: | https://doaj.org/article/23a7395375c64d40967fed2e3eac6dc0 |
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