collaborators

12 papers

stat.ML2026

Co-optimization for Adaptive Conformal Prediction

Xiaoyi Su, Zhixin Zhou, Rui Luo

Conformal prediction (CP) provides finite-sample, distribution-free marginal coverage, but standard conformal regression intervals can be inefficient under heteroscedasticity and s…

stat.ML2026

Fast Conformal Prediction using Conditional Interquantile Intervals

Naixin Guo, Rui Luo, Zhixin Zhou

We introduce Conformal Interquantile Regression (CIR), a conformal regression method that efficiently constructs near-minimal prediction intervals with guaranteed coverage. CIR lev…

cs.LG2025

Residual Reweighted Conformal Prediction for Graph Neural Networks

Zheng Zhang, Jie Bao, Zhixin Zhou +3

Graph Neural Networks (GNNs) excel at modeling relational data but face significant challenges in high-stakes domains due to unquantified uncertainty. Conformal prediction (CP) off…

cs.LG2025

Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliability

Jie Bao, Chuangyin Dang, Rui Luo +2

As deep learning models are increasingly deployed in high-risk applications, robust defenses against adversarial attacks and reliable performance guarantees become paramount. Moreo…

cs.LG2025

Conditional Conformal Risk Adaptation

Rui Luo, Zhixin Zhou

Uncertainty quantification is becoming increasingly important in image segmentation, especially for high-stakes applications like medical imaging. While conformal risk control gene…

cs.LG2025

Enhanced Route Planning with Calibrated Uncertainty Set

Lingxuan Tang, Rui Luo, Zhixin Zhou +1

This paper investigates the application of probabilistic prediction methodologies in route planning within a road network context. Specifically, we introduce the Conformalized Quan…