V-ECE: Estimating General Expected Calibration Errors
This work extends variational methods to estimate general Lp calibration errors for binary and multiclass problems. It decomposes the calibration error into components, allowing separation of over- and under-confidence. Using cross-validation provides a lower bound on the true error, preventing overestimation by fitting a recalibration function.