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CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks [article]

Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei
2021 arXiv   pre-print
The proposed Copula Graph Neural Network (CopulaGNN) can take a wide range of GNN models as base models and utilize both representational and correlational information stored in the graphs.  ...  In this paper, we distinguish the representational and the correlational roles played by the graphs in node-level prediction tasks, and we investigate how Graph Neural Network (GNN) models can effectively  ...  We propose a principled solution, the CopulaGNN, to integrate the representational and correlational roles of the graph. 3.  ... 
arXiv:2010.02089v2 fatcat:daddbroownef3axvzdd6ry36ny