Gustavo Enrique Batista

Instance-Wise Monotonic Calibration by Constrained Transformation

Deep neural networks often produce miscalibrated probability estimates, leading to overconfident predictions. A common approach for calibration is fitting a post-hoc calibration map on unseen validation data that transforms predicted probabilities. A key desirable property of the calibration map is