Self-Supervised Node Classification with Strategy and Actively Selected Labeled Set

To alleviate the impact of insufficient labels in less-labeled classification problems, self-supervised learning improves the performance of graph neural networks (GNNs) by focusing on the information of unlabeled nodes. However, none of the existing self-supervised pretext tasks perform optimally o...

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Detalles Bibliográficos
Autores principales: Kang, Yi, Liu, Ke, Cao, Zhiyuan, Zhang, Jiacai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857737/
https://www.ncbi.nlm.nih.gov/pubmed/36673172
http://dx.doi.org/10.3390/e25010030

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857737/
https://www.ncbi.nlm.nih.gov/pubmed/36673172
http://dx.doi.org/10.3390/e25010030

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