Schreier-Coset Graph Rewiring
The information flow in the graph neural networks (GNNs) is fundamentally constrained by over-squashing, where structural bottlenecks impede long range information propagation. Graph-rewiring methods, which modify graph topology, have been extensively used to alleviate this. However, existing approaches often introduce prohibitive structural and computational bottlenecks, fail to preserve the critical properties of original graphs, and increase the edge counts massively. We introduce a novel method Schreier-Coset Graph Rewiring , a group-theoretic rewiring method that augments the input graph with a Schreier-Coset graph derived from a special linear group. Our method provides theoretical ...
| Authors | Aryan Mishra, Randy Martinez, Lizhen Lin |
|---|---|
| Primary category | cs.LG |
| Published | 29 July 2026 |
| Last updated at source | 29 July 2026 |
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