A step-function score transformation I_w = w·1{s≥w} reduces the estimated-coverage gap in Backward Conformal Prediction from about 4.2% to 1.1% on CIFAR-10, CIFAR-100, and Tiny-ImageNet.
Conformal prediction for deep classifier via label ranking
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Improving Backward Conformal Prediction via Non-Conformity Score Transformation
A step-function score transformation I_w = w·1{s≥w} reduces the estimated-coverage gap in Backward Conformal Prediction from about 4.2% to 1.1% on CIFAR-10, CIFAR-100, and Tiny-ImageNet.