LDC-GAT: A Lyapunov-Stable Graph Attention Network with Dynamic Filtering and Constraint-Aware Optimization
Graph attention networks are pivotal for modeling non-Euclidean data, yet they face dual challenges: training oscillations induced by projection-based high-dimensional constraints and gradient anomalies due to poor adaptation to heterophilic structure. To address these issues, we propose LDC-GAT (Ly...
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| Autores principales: | , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI AG
2025-06-01
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| Colección: | Axioms |
| Materias: | |
| Acceso en línea: | https://www.mdpi.com/2075-1680/14/7/504 |
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