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A Block-Based Adaptive Decoupling Framework for Graph Neural Networks

Graph neural networks (GNNs) with feature propagation have demonstrated their power in handling unstructured data. However, feature propagation is also a smooth process that tends to make all node representations similar as the number of propagation increases. To address this problem, we propose a n...

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Detalles Bibliográficos
Autores principales: Shen, Xu, Zhang, Yuyang, Xie, Yu, Wong, Ka-Chun, Peng, Chengbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497978/
https://www.ncbi.nlm.nih.gov/pubmed/36141076
http://dx.doi.org/10.3390/e24091190

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