3 papers
stat.ME2026
Testing the Validity of Instrumental Variable Sets in Causal Additive Models with Non-Constant Effects
Xichen Guo, Feng Xie, Bingbing Tang +5
Instrumental variable (IV) methods are powerful for causal effect estimation with unmeasured confounding, but in practice researchers often face a set of candidate IVs whose validi…
cs.LG2026
A Recursive Decomposition Framework for Causal Structure Learning in the Presence of Latent Variables
Zheng Li, Feng Xie, Shenglan Nie +3
Constraint-based causal discovery is widely used for learning causal structures, but heavy reliance on conditional independence (CI) testing makes it computationally expensive in h…
stat.ME2024
Testability of Instrumental Variables in Additive Nonlinear, Non-Constant Effects Models
Xichen Guo, Zheng Li, Biwei Huang +3
We address the issue of the testability of instrumental variables derived from observational data. Most existing testable implications are centered on scenarios where the treatment…