mlsanityData to 7 Oct 2026

On Addressing the Limitations of Graph Neural Networks

arXiv 2306.12640 ↗First posted 22 Jun 2023cs.LGcited by 1

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Abstract (arXiv)

This report gives a summary of two problems about graph convolutional networks (GCNs): over-smoothing and heterophily challenges, and outlines future directions to explore.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 44 of its 72 references that are in the map. First posted on arXiv 22 Jun 2023.

Builds on

44 of 72 references.

References · 44

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32 more
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Citing papers per year: 2024: 1.

1 paper.

  1. 2024Transfer Entropy in Graph Convolutional Neural Networkscited by 1