Hugging Face Trending Papers
Jun 10

Conformal Bayes under Label Shift: Post-Hoc Calibration vs. In-Training Adaptation

Conformal Bayes combines Bayesian posterior predictives with conformal calibration to produce prediction sets that are both statistically valid and geometrically efficient. We study conformal Bayes under label shift from a unified perspective, identifying two complementary approaches that restore nominal target-domain coverage through importance-weighted conformal calibration but operate through independent mechanisms.