A Hierarchy of Graph Neural Networks Based on Learnable Local Features

13 Nov 2019Michael Lingzhi LiMeng DongJiawei ZhouAlexander M. Rush

Graph neural networks (GNNs) are a powerful tool to learn representations on graphs by iteratively aggregating features from node neighbourhoods. Many variant models have been proposed, but there is limited understanding on both how to compare different architectures and how to construct GNNs systematically... (read more)

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