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Examining graph neural networks for crystal structures: Limitations and opportunities for capturing periodicity
Graph neural networks (GNNs) have recently been used to learn the representations of crystal structures through an end-to-end data-driven approach. However, a systematic top-down approach to evaluate and understand the limitations of GNNs in accurately capturing crystal structures has yet to be esta...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Association for the Advancement of Science
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637739/ https://www.ncbi.nlm.nih.gov/pubmed/37948518 http://dx.doi.org/10.1126/sciadv.adi3245 |