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Image Credit: Arxiv

Contextualized Messages Boost Graph Representations

  • Graph neural networks (GNNs) are being used to process data represented as graphs.
  • A new perspective on the representational capability of GNNs is explored.
  • A soft-injective function and a soft-isomorphic relational graph convolution network (SIR-GCN) are proposed.
  • Experiments show that SIR-GCN outperforms comparable models in prediction tasks.

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