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SLGAT: Soft Labels Guided Graph Attention Networks

Graph convolutional neural networks have been widely studied for semi-supervised classification on graph-structured data in recent years. They usually learn node representations by transforming, propagating, aggregating node features and minimizing the prediction loss on labeled nodes. However, the...

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Detalles Bibliográficos
Autores principales:	Wang, Yubin, Zhang, Zhenyu, Liu, Tingwen, Guo, Li
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	2020
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206162/ http://dx.doi.org/10.1007/978-3-030-47426-3_40

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