Meta Propagation Networks for Graph Few-shot Semi-supervised Learning

@inproceedings{Ding2022MetaPN,
  title={Meta Propagation Networks for Graph Few-shot Semi-supervised Learning},
  author={Kaize Ding and Jianling Wang and James Caverlee and Huan Liu},
  booktitle={AAAI},
  year={2022}
}
Inspired by the extensive success of deep learning, graph neural networks (GNNs) have been proposed to learn expressive node representations and demonstrated promising performance in various graph learning tasks. However, existing endeavors predominately focus on the conventional semi-supervised setting where relatively abundant gold-labeled nodes are provided. While it is often impractical due to the fact that data labeling is unbearably laborious and requires intensive domain knowledge… 
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Few-Shot Learning on Graphs
  • Chuxu Zhang, Kaize Ding, Huan Liu
  • Computer Science
    Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
  • 2022
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