2021
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning
ICLR 2021poster
Post-hoc multi-class calibration is a common approach for providing high-quality confidence estimates of deep neural network predictions. Recent work has shown that widely used scaling methods underestimate their calibration error, while alternative Histogram Binning (HB) methods often fail to prese…