RR-GNN uses a residual-predicting GNN and graph clustering to produce tighter conformal prediction intervals for GNN outputs while preserving marginal coverage guarantees.
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Residual Reweighted Conformal Prediction for Graph Neural Networks
RR-GNN uses a residual-predicting GNN and graph clustering to produce tighter conformal prediction intervals for GNN outputs while preserving marginal coverage guarantees.