Two papers accepted at NeurIPS 2026

I am delighted to announce that two of our papers have been accepted at NeurIPS 2026 (Main Track):

–History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes
–Proximal Difference-in-Differences for Long-Term Causal Learning under Confounding and Outcome Drift

Congratulations to all coauthors—looking forward to sharing this work at NeurIPS!

— Shu Yang