Teger is a backbone-agnostic structured uncertainty module that uses discrete Forman curvature for spatial graph rewiring inside a low-rank-plus-diagonal covariance head to mitigate over-squashing and improve residual error propagation in spatio-temporal forecasting.
Bronstein, and Francesco Di Giovanni
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A survey compiling graph rewiring techniques for mitigating over-squashing and over-smoothing in GNNs.
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Improving Spatio-Temporal Residual Error Propagation by Mitigating Over-Squashing
Teger is a backbone-agnostic structured uncertainty module that uses discrete Forman curvature for spatial graph rewiring inside a low-rank-plus-diagonal covariance head to mitigate over-squashing and improve residual error propagation in spatio-temporal forecasting.
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Graph Rewiring in GNNs to Mitigate Over-Squashing and Over-Smoothing: A Survey
A survey compiling graph rewiring techniques for mitigating over-squashing and over-smoothing in GNNs.