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Batched Graph Classification with DGL

Graph classification is an important problem with applications across many fields – bioinformatics, chemoinformatics, social network analysis, urban computing and cyber-security. Applying graph neural networks to this problem has been a popular approach recently (Ying et al., 2018, Cangea et al., 2018, Knyazev et al., 2018, Bianchi et al., 2019, Liao et al., 2019, Gao et al., 2019).

This tutorial is a demonstration for

  • batching multiple graphs of variable size and shape with DGL
  • training a graph neural network for a simple graph classification task

Simple Graph Classification Task

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