arXiv Machine Learning July 27, 2026 By Rachid Caich, Yassine Abbahaddou

Local-Global Geometric Insights for Graph Neural Networks via Entropic Curvature

Read the original on arXiv Machine Learning →

arXiv:2607. 22381v1 Announce Type: new Abstract: Curvature notions on graphs, particularly Ollivier-Ricci and Forman, have emerged as powerful tools for addressing fundamental issues in Graph Neural Networks (GNNs) such as oversmoothing and oversquashing, but rely almost exclusively on local edge-level comparisons and therefore fail to certify how information actually propagates over long distances.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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