EGNAS: Efficient Graph Neural Architecture Search Through Evolutionary Algorithm
The primary objective of our research is to enhance the efficiency and effectiveness of Neural Architecture Search (NAS) with regard to Graph Neural Networks (GNNs). GNNs have emerged as powerful tools for learning from unstructured network data, compensating for several known limitations of Convolu...
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| Autores principales: | , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI AG
2024-12-01
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| Colección: | Mathematics |
| Materias: | |
| Acceso en línea: | https://www.mdpi.com/2227-7390/12/23/3828 |
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