3 papers
cs.LG2026
Calibrated Multivariate Distributional Regression with Pre-Rank Regularization
Aya Laajil, Elnura Zhalieva, Naomi Desobry +1
The goal of probabilistic prediction is to issue predictive distributions that are as informative as possible, subject to being calibrated. Despite substantial progress in the univ…
stat.ML2025
Enforcing Calibration in Multi-Output Probabilistic Regression with Pre-rank Regularization
Naomi Desobry, Elnura Zhalieva, Souhaib Ben Taieb
Probabilistic models must be well calibrated to support reliable decision-making. While calibration in single-output regression is well studied, defining and achieving multivariate…
stat.ML2025
A Unified Comparative Study with Generalized Conformity Scores for Multi-Output Conformal Regression
Victor Dheur, Matteo Fontana, Yorick Estievenart +2
Conformal prediction provides a powerful framework for constructing distribution-free prediction regions with finite-sample coverage guarantees. While extensively studied in univar…