593 citations · 992 across the 23 of their papers we have counts for
23 papers
Stratification of uncertainties recalibrated by isotonic regression and its impact on calibration error statistics
Pascal Pernot
Abstract Post hoc recalibration of prediction uncertainties of machine learning regression problems by isotonic regression might present a problem for bin-based calibration error s…
Properties of the ENCE and other MAD-based calibration metrics
Pascal Pernot
The Expected Normalized Calibration Error (ENCE) is a popular calibration statistic used in Machine Learning to assess the quality of prediction uncertainties for regression proble…
Validation of uncertainty quantification metrics: a primer based on the consistency and adaptivity concepts
Pascal Pernot
The practice of uncertainty quantification (UQ) validation, notably in machine learning for the physico-chemical sciences, rests on several graphical methods (scattering plots, cal…
Comparison of recent estimators of uncertainty on the mean for small measurement samples with normal and non-normal error distributions
Pascal Pernot, Jean-Paul Berthet
We review the alternative proposals introduced recently in the literature to update the standard formula to estimate the uncertainty on the mean of repeated measurements, and we co…
Confidence curves for UQ validation: probabilistic reference vs. oracle
Pascal Pernot
Confidence curves are used in uncertainty validation to assess how large uncertainties () are associated with large errors (). An oracle curve is commonly used as referen…
Prediction uncertainty validation for computational chemists
Pascal Pernot
Validation of prediction uncertainty (PU) is becoming an essential task for modern computational chemistry. Designed to quantify the reliability of predictions in meteorology, the…