The Calibration Review
Calibration Theory
Latest research
Calibration Theory
Conformal Prediction Coverage Guarantees in Practice
Marginal coverage guarantees mask systematic failures in subgroups and changing conditions.
- Reliability Diagrams for Probabilistic Forecast EvaluationCalibrated probabilities must match observed frequencies, and this diagram reveals when they don't.
- Temperature Scaling vs Platt Scaling for Neural ClassifiersTemperature scaling needs one parameter; Platt scaling needs two.
- Bayesian vs Frequentist Uncertainty in Sequential Decision MakingBayesian updating handles sequential uncertainty better than frequentist methods.
- Calibration Drift Detection in Production ML PipelinesModels can stay accurate while their confidence scores quietly stop being trustworthy.
Calibration Theory
View all →- Conformal Prediction Coverage Guarantees in PracticeMarginal coverage guarantees mask systematic failures in subgroups and changing conditions.
- Reliability Diagrams for Probabilistic Forecast EvaluationCalibrated probabilities must match observed frequencies, and this diagram reveals when they don't.
- Temperature Scaling vs Platt Scaling for Neural ClassifiersTemperature scaling needs one parameter; Platt scaling needs two.
- Bayesian vs Frequentist Uncertainty in Sequential Decision MakingBayesian updating handles sequential uncertainty better than frequentist methods.