An End-to-End Multiplex Graph Neural Network for Graph Representation Learning

Research on graph classification tasks based on graph neural networks has attracted wide attention. The graphs to be classified may have various graph sizes (i.e., different numbers of nodes and edges) and have various graph properties (e.g., average node degree, diameter, and clustering coefficient...

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Bibliographic Details
Main Authors: Yanyan Liang, Yanfeng Zhang, Dechao Gao, Qian Xu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9393892/