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PhyGCN: Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning
Hypergraphs are powerful tools for modeling complex interactions across various domains, including biomedicine. However, learning meaningful node representations from hypergraphs remains a challenge. Existing supervised methods often lack generalizability, thereby limiting their real-world applicati...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Cold Spring Harbor Laboratory
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10592843/ https://www.ncbi.nlm.nih.gov/pubmed/37873233 http://dx.doi.org/10.1101/2023.10.01.560404 |