CI

BGM-IV: AI-Powered Bayesian Generative Modeling for Instrumental Variable Regression with High-Dimensional Covariates

Guyue Luo, Haidong Lu, Andrew J. Loza, and Qiao Liu. arXiv, 2026.

Guyue Luo, Haidong Lu, Andrew J. Loza, Qiao Liu

A Bayesian Generative Modeling Approach for Arbitrary Conditional Inference

Qiao Liu^* and Wing Hung Wong. arXiv, 2026.

Qiao Liu, Wing Hung Wong

A Bayesian Generative Modeling Approach for Arbitrary Conditional Inference

Leveraging genomic foundation models to identify genotype-brain-clinical pathways in Alzheimer's disease

Qiao Liu^†,*, Zhaoyang Zhang^†, Haochen Wang, Heping Zhang, Hongtu Zhu, Lexin Li^*, Wing Hung Wong^*. medRxiv, 2026.

Qiao Liu, Zhaoyang Zhang, Haochen Wang, Heping Zhang, Hongtu Zhu, Lexin Li, Wing Hung Wong

Leveraging genomic foundation models to identify genotype-brain-clinical pathways in Alzheimer's disease

An AI-powered Bayesian generative modeling approach for causal inference in observational studies

Qiao Liu^* and Wing Hung Wong. Journal of the American Statistical Association, 2026.

Qiao Liu, Wing Hung Wong

An encoding generative modeling approach to dimension reduction and covariate adjustment in causal inference with observational studies

Qiao Liu, Zhongren Chen, Wing Hung Wong^*. PNAS, 2024.

Qiao Liu, Zhongren Chen, Wing Hung Wong

An encoding generative modeling approach to dimension reduction and covariate adjustment in causal inference with observational studies