3 citations · 3 across the 2 of their papers we have counts for
3 papers
stat.ML2025
PAC-Causal Learnability: From Identification to Finite-Sample Guarantees
Mian Wei, Somesh Jha, David Page
Causal identification asks whether a causal target can be recovered from the observational distribution in an idealized infinite-data setting. In practice, only finite samples are…
stat.ME2020★ 3 cited
Stable discovery of interpretable subgroups via calibration in causal studies
Raaz Dwivedi, Yan Shuo Tan, Briton Park +4
Building on Yu and Kumbier's PCS framework and for randomized experiments, we introduce a novel methodology for Stable Discovery of Interpretable Subgroups via Calibration (StaDISC…
stat.ME2014
Additive Models for Conditional Copulas
Avideh Sabeti, Mian Wei, Radu V. Craiu
Conditional copulas are flexible statistical tools that couple joint conditional and marginal conditional distributions. In a linear regression setting with more than one covariate…