Hierarchical Graph Representation Learning with Differentiable Pooling

@article{Ying2018HierarchicalGR,
  title={Hierarchical Graph Representation Learning with Differentiable Pooling},
  author={Rex Ying and Jiaxuan You and Christopher Morris and Xiang Ren and William L. Hamilton and Jure Leskovec},
  journal={CoRR},
  year={2018},
  volume={abs/1806.08804}
}
Recently, graph neural networks (GNNs) have revolutionized the field of graph representation learning through effectively learned node embeddings, and achieved state-of-the-art results in tasks such as node classification and link prediction. However, current GNN methods are inherently flat and do not learn hierarchical representations of graphs—a… CONTINUE READING