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Federated learning of molecular properties with graph neural networks in a heterogeneous setting
Chemistry research has both high material and computational costs to conduct experiments. Intuitions are interested in differing classes of molecules, creating heterogeneous data that cannot be easily joined by conventional methods. This work introduces federated heterogeneous molecular learning. Fe...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9214329/ https://www.ncbi.nlm.nih.gov/pubmed/35755872 http://dx.doi.org/10.1016/j.patter.2022.100521 |