Accurate Uncertainties for Deep Learning Using Calibrated Regression

November 2019

tl;dr: Extends NN calibration from classification to regression.

Overall impression

The paper has a great introduction to the background of model calibration, and also summarizes the classification calibration really well.

The method can give calibrated credible intervals given sufficient amount of iid data.

For application of this in object detection, see calibrating uncertainties in object detection and can we trust you.

Key ideas

Technical details


ir = IsotonicRegression() # or LogisticRegression()
ir.fit(p_holdout, y_holdout)
p_calibrated = ir.transform(p_holdout)