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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. This tutorial is a demonstration for: (1) batching multiple graphs of variable size and shape with DGL (2) training a graph neural network for a simple graph classification task