2 papers
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…
stat.ML2026
An AI-powered Bayesian generative modeling approach for causal inference in observational studies
Qiao Liu, Wing Hung Wong
Causal inference in observational studies with high-dimensional covariates presents significant challenges. We introduce CausalBGM, an AI-powered Bayesian generative modeling appro…