Conformal Bayes under Continuous Label Shift: Sensitivity Analysis and the Limits of Exact Validity
Conformal Bayes combines Bayesian posterior predictive scores with conformal calibration, but under continuous label shift both the score and calibration weight depend on the unknown response-marginal density ratio. Existing methods typically estimate one shift parameter from pseudo-labels or predictive samples and plug it into calibration. We instead propose Joint Tilt-Sensitivity Conformal Bayes (JTS-CB), which performs sensitivity analysis over a prespecified set of plausible tilts; its split-conformal realization is JTS-SCB. Each tilt jointly determines the Bayesian conformal score and conformal importance weight. JTS-SCB forms a bounded sensitivity envelope over candidate tilts, but ...
| Authors | Seungjin Choi |
|---|---|
| Primary category | stat.ML |
| Published | 24 August 2026 |
| Last updated at source | 24 August 2026 |
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