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A universal framework for accurate and efficient geometric deep learning of molecular systems
Molecular sciences address a wide range of problems involving molecules of different types and sizes and their complexes. Recently, geometric deep learning, especially Graph Neural Networks, has shown promising performance in molecular science applications. However, most existing works often impose...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628308/ https://www.ncbi.nlm.nih.gov/pubmed/37932352 http://dx.doi.org/10.1038/s41598-023-46382-8 |