How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

  title={How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision},
  author={Dongkwan Kim and Alice H. Oh},
Attention mechanism in graph neural networks is designed to assign larger weights to important neighbor nodes for better representation. However, what graph attention learns is not understood well, particularly when graphs are noisy. In this paper, we propose a self-supervised graph attention network (SuperGAT), an improved graph attention model for noisy graphs. Specifically, we exploit two attention forms compatible with a self-supervised task to predict edges, whose presence and absence… 

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Sparse Graph Attention Networks

  • Yang YeShihao Ji
  • Computer Science
    IEEE Transactions on Knowledge and Data Engineering
  • 2021
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