Graph Multihead Attention Pooling with Self-Supervised Learning

Graph neural networks (GNNs), which work with graph-structured data, have attracted considerable attention and achieved promising performance on graph-related tasks. While the majority of existing GNN methods focus on the convolutional operation for encoding the node representations, the graph pooli...

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Detalles Bibliográficos
Autores principales: Wang, Yu, Hu, Liang, Wu, Yang, Gao, Wanfu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777688/
https://www.ncbi.nlm.nih.gov/pubmed/36554149
http://dx.doi.org/10.3390/e24121745

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777688/
https://www.ncbi.nlm.nih.gov/pubmed/36554149
http://dx.doi.org/10.3390/e24121745

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