CALIBURN integrates Bayesian change-point detection, isotonic calibration, cost-sensitive thresholding, conformal risk control, and burn-rate alerting into a single streaming substrate, showing that calibration and CRC performance is strongly regime-dependent on attack prevalence.
Conformal inference for online prediction with arbitrary distribution shifts
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RareCP improves interval efficiency for time series conformal prediction by retrieving and weighting regime-specific calibration examples while adapting to drift and maintaining coverage.
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CALIBURN: Operationally Calibrated Streaming Intrusion Detection with Regime-Dependent Conformal Risk Control
CALIBURN integrates Bayesian change-point detection, isotonic calibration, cost-sensitive thresholding, conformal risk control, and burn-rate alerting into a single streaming substrate, showing that calibration and CRC performance is strongly regime-dependent on attack prevalence.
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RareCP: Regime-Aware Retrieval for Efficient Conformal Prediction
RareCP improves interval efficiency for time series conformal prediction by retrieving and weighting regime-specific calibration examples while adapting to drift and maintaining coverage.
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A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
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