1 citations · 1 across the 4 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
stat.ML2026
BGM-IV: AI-Powered Bayesian Generative Modeling for Instrumental Variable Regression with High-Dimensional Covariates
Guyue Luo, Qiao Liu, Haidong Lu +1
Instrumental-variable (IV) regression enables causal estimation under endogeneity, but modern IV problems often involve nonlinear structural effects and high-dimensional covariates…
stat.ML2026
Missingness-aware Data Imputation via AI-powered Bayesian Generative Modeling
Qiao Liu
Missing data imputation remains a fundamental challenge in modern data science, especially when uncertainty quantification is essential. In this work, we propose MissBGM, an AI-pow…
stat.ML2026
An AI-powered Bayesian Generative Modeling Approach for Arbitrary Conditional Inference
Qiao Liu, Wing Hung Wong
Modern data analysis increasingly requires flexible conditional inference P(X_B | X_A) where (X_A, X_B) is an arbitrary partition of observed variable X. Existing approaches are ei…