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Force-field-enhanced neural network interactions: from local equivariant embedding to atom-in-molecule properties and long-range effects
We introduce FENNIX (Force-Field-Enhanced Neural Network InteraXions), a hybrid approach between machine-learning and force-fields. We leverage state-of-the-art equivariant neural networks to predict local energy contributions and multiple atom-in-molecule properties that are then used as geometry-d...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society of Chemistry
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10646944/ https://www.ncbi.nlm.nih.gov/pubmed/38020379 http://dx.doi.org/10.1039/d3sc02581k |