AdaCal-GNN: Adaptive Confidence Calibration for Graph Neural Networks
Graph Neural Networks (GNNs) often produce poorly calibrated predictions, where the predicted probabilities do not accurately reflect the true likelihood of correctness. Recent studies indicate that miscalibration in GNNs exhibits a heterogeneous pattern: while neighborhood aggregation induces an overall underconfidenc...