Generalized Conformal Predictive Systems Under Distributional Shifts

• URL: http://arxiv.org/abs/2606.11044v1
• Date: Tue, 09 Jun 2026 16:12:20 GMT
• Title: Generalized Conformal Predictive Systems Under Distributional Shifts
• Abstract summary: Conformal predictive systems (CPS) output bands of CDFs under exchangeability.<n>We extend CPS to non-exchangeable settings by encoding distributional shifts through observation-specific permutation weights.<n>We derive efficient computation for conformity-measure CPS, conformal binning, and conformal isotonic distributional regression.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Conformal predictive systems (CPS) output calibrated bands of CDFs under exchangeability. We extend generalized CPS to non-exchangeable settings by encoding distributional shifts through observation-specific permutation weights. This yields shift-aware predictive systems that remain valid whenever the test point is, conditionally on the unordered sample, a weighted draw from the observed atoms. Since such weights are typically estimated, we introduce weight-uncertainty boxes and construct robust CPS envelopes with finite-sample or asymptotic confidence guarantees. We derive efficient computation for conformity-measure CPS, conformal binning, and conformal isotonic distributional regression. Experiments under covariate shift and feedback-driven biomolecular design show calibrated predictive bands that widen under stronger shifts and tighten as sample size increases.

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