Decoupled Conformal Optimisation: Efficient Prediction Sets via Independent Tuning and Calibration
We show that optimisation and calibration can be decoupled for Conformal Prediction while maintaining valid marginal coverage guarantee.
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🔥 Selected Talk on WUML 2026
Selected talk speaker and poster presentation, Workshop on Uncertainty in Machine Learning (WUML), Tartu, Estonia.
Bayesian Conformal Prediction as a Decision Risk Problem
We present a unified Bayesian decision-theoretic framework for conformal prediction (CP) that integrates Bayesian posterior predictive scores with risk minimization via Bayesian …