Statistics

BayesNDE: Bayesian Generative Modeling for Neural Density Estimation

Chenglin Li and Qiao Liu. arXiv, 2026.

Chenglin Li, Qiao Liu

Missingness-aware Data Imputation via AI-powered Bayesian Generative Modeling

Qiao Liu^*. arXiv, 2026.

Missingness-aware Data Imputation via AI-powered Bayesian Generative Modeling

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

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

Density estimation using deep generative neural networks

Qiao Liu, Jiaze Xu, Rui Jiang^*, Wing Hung Wong^*. PNAS, 2021.

Qiao Liu, Jiaze Xu, Rui Jiang, Wing Hung Wong

Density estimation using deep generative neural networks