2 papers
cs.AI2026
Disentangled Instrumental Variables for Causal Inference with Networked Observational Data
Zhirong Huang, Debo Cheng, Guixian Zhang +3
Instrumental variables (IVs) are crucial for addressing unobservable confounders, yet their stringent exogeneity assumptions pose significant challenges in networked data. Existing…
stat.ML2025
Structural DID with ML: Theory, Simulation, and a Roadmap for Applied Research
Yile Yu, Anzhi Xu, Yi Wang
Causal inference in observational panel data has become a central concern in economics,policy analysis,and the broader social sciences.To address the core contradiction where tradi…