2 papers
stat.ME2026
Causal Inference with Categorical Unobserved Confounder via Mixture Learning
Aytijhya Saha, Stephen Bates, Devavrat Shah
Unobserved confounding is a fundamental challenge for estimating causal effects. To address unobserved confounding, recent literature has turned to two different approaches -- prox…
stat.ML2026
Isotonic Survival Regression: Calibrated Survival Distributions from Deep Cox Models
Anchit Jain, Kevin Zhang, Stephen Bates
Time-to-event data is widespread across the life sciences and engineering, but it is typically encountered together with censoring, which complicates the application of standard ma…