Context-Aware Graph Attention Networks

Graph Neural Networks (GNNs) have been widely studied for graph data representation and learning. However, existing GNNs generally conduct context-aware learning on node feature representation only which usually ignores the learning of edge (weight) representation. In this paper, we propose a novel...

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Veröffentlicht in:	arXiv.org 2019-09
Hauptverfasser:	Jiang, Bo, Wang, Leiling, Tang, Jin, Luo, Bin
Format:	Artikel
Sprache:	eng
Schlagworte:	Graph neural networks Graph theory Graphical representations Semi-supervised learning Weight
Online-Zugang:	Volltext
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