Corpus ID: 3290366

Graph Partition Neural Networks for Semi-Supervised Classification

@article{Liao2018GraphPN,
  title={Graph Partition Neural Networks for Semi-Supervised Classification},
  author={Renjie Liao and Marc Brockschmidt and Daniel Tarlow and Alexander L. Gaunt and R. Urtasun and R. Zemel},
  journal={ArXiv},
  year={2018},
  volume={abs/1803.06272}
}
  • Renjie Liao, Marc Brockschmidt, +3 authors R. Zemel
  • Published 2018
  • Computer Science, Mathematics
  • ArXiv
  • We present graph partition neural networks (GPNN), an extension of graph neural networks (GNNs) able to handle extremely large graphs. GPNNs alternate between locally propagating information between nodes in small subgraphs and globally propagating information between the subgraphs. To efficiently partition graphs, we experiment with several partitioning algorithms and also propose a novel variant for fast processing of large scale graphs. We extensively test our model on a variety of semi… CONTINUE READING
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