Improving Conditional Coverage via Orthogonal Quantile Regression. - Shai Feldman; Stephen Bates; Yaniv Romano (NeurIPS, 2021)

Conformal Prediction is Robust to Dispersive Label Noise. - Shai Feldman; Bat-Sheva Einbinder; Stephen Bates; Anastasios N. Angelopoulos; Asaf Gendler; Yaniv Romano (COPA, 2023)

Calibrated Multiple-Output Quantile Regression with Representation Learning. - Shai Feldman; Stephen Bates; Yaniv Romano (J. Mach. Learn. Res., 2023)

Weisfeiler and Leman Go Infinite: Spectral and Combinatorial Pre-Colorings. - Or Feldman; Amit Boyarski; Shai Feldman; Dani Kogan; Avi Mendelson; Chaim Baskin (Trans. Mach. Learn. Res., 2023)

Achieving Risk Control in Online Learning Settings. - Shai Feldman; Liran Ringel; Stephen Bates; Yaniv Romano (Trans. Mach. Learn. Res., 2023)

Robust Conformal Prediction Using Privileged Information. - Shai Feldman; Yaniv Romano (NeurIPS, 2024)

Conformalized Survival Analysis for General Right-Censored Data. - Hen Davidov; Shai Feldman; Gil Shamai; Ron Kimmel; Yaniv Romano (ICLR, 2025)

Conformal Prediction with Corrupted Labels: Uncertain Imputation and Robust Re-weighting. - Shai Feldman; Stephen Bates; Yaniv Romano (CoRR, 2025)

Calibrated Predictive Lower Bounds on Time-to-Unsafe-Sampling in LLMs. - Hen Davidov; Gilad Freidkin; Shai Feldman; Yaniv Romano (CoRR, 2025)