Publications (alphabetical order. * indicates the corresponding author. # represents supervised students)
1. Bensoussan A., Yam S. C. P.,* and Zhang Z. (2015). Well-posedness of Mean-field Type Forward-backward Stochastic Differential Equations. Stochastic Processes and their Applications. 125(9), 3327-3354.
2. Chan K. C. G*., Yam S. C. P., and Zhang Z. (2016). Globally Efficient Non-parametric Inference of Average Treatment Effects by Empirical Balancing Calibration Weighting. Journal of the Royal Statistical Society: Series B. 78(3), 673-700. [Supplemental Material]
3. Wright J. A.*, Yam S. C. P., and Zhang Z. (2018). Enlargement of Filtration on Poisson Space: A Malliavin Calculus Approach. Stochastics. 90(5), 682-700.
4. Privault N., Yam S. C. P.*, and Zhang Z. (2019). Poisson Discretizations of Wiener Functionals and Malliavin Operators with Wasserstein Estimates. Stochastic Processes and their Applications. 129(9), 3376-3405.
5. Hamori S., Motegi K.* and Zhang Z. (2019). Calibration Estimation of Semiparametric Copula Models with Data Missing at Random. Journal of Multivariate Analysis. 173, 85-109. [Supplemental Material]
6. Hamori S., Motegi K. and Zhang Z.* (2020). Copula-based Regression Models with Data Missing at Random. Journal of Multivariate Analysis. 180, #104654. [Supplemental Material]
7. Ai C., Linton O. and Zhang Z.* (2020). A Simple and Efficient Estimation Method for Models with Non-ignorable Missing Data. Statistica Sinica. 30, 1949-1970. [Supplemental Material]
8. Ai C., Huang L.# and Zhang Z.* (2020). A Mann-Whitney Test of Distributional Effects in A Multivalued Treatment. Journal of Statistical Planning and Inference. 209,85-100. [Supplemental Material]
9. Ai. C., Linton O., Motegi K. and Zhang Z*. (2021). A Unified Framework for Efficient Estimation of General Treatment Models. Quantitative Economics. 12(3),779-816.
10. Ai. C., Linton O., and Zhang Z.* (2022). Estimation and Inference for the Counterfactual Distribution and Quantile Functions in Continuous Treatment Models. Journal of Econometrics. 228(1), 39-61.
11. Ai C., Huang L.# and Zhang Z.* (2022). A Simple and Efficient Estimation of Average Treatment Effects in Models with Unmeasured Confounders. Statistica Sinica. 32(3).
12. Huang W., Linton O., and Zhang Z.* (2022). A Unified Framework for Specification Tests of Continuous Treatment Effect Models. Journal of Business & Economic Statistics. 40(4), 1817-1830.
13. Huang W. and Zhang Z.* (2023). Nonparametric Estimation of Continuous Treatment Effect with Measurement Error. Journal of the Royal Statistical Society: Series B. 85(2), 474–496.
14. Ai. C., Sun L., Zhang Z.* and Zhu L. (2024). Testing Unconditional and Conditional Independence via Mutual Information. Journal of Econometrics. 240(2), 105335.
15. Chen X., Liu Y., Ma S*. and Zhang Z*. (2024). Causal Inference of General Treatment Effects Using Neural Networks with A Diverging Number of Confounders. Journal of Econometrics. 238(1).
16. Huang L.# Huang W., Linton O, and Zhang Z.* (2024). Nonparametric Estimation of Mediation Effects with A General Treatment. Econometric Reviews. 43(2-4).
17. Xiao F., Ji C., Zhang Z., and Wang R.* (2025). Decouple-and-Couple Learning in Multi-modal Brain Tumor Segmentation. IEEE Journal of Biomedical and Health Informatics.
18. Hou H.#, Huang W., and Zhang Z.* (2025). Non-parametric Quantile Regression and Uniform Inference with Unknown Error Distribution. Journal of Business & Economic Statistics. 1-23.
19. Wang M.#, Huang W., Gong M., and Zhang Z.* (2025). Projection Pursuit Based Density Ratio Estimation. International Conference on Machine Learning. Accepted.
20. Tan R., Huang W.*, Zhang Z.*, and Yin G. (2025). Causal Effect of Functional Treatment. Journal of Machine Learning Research. 26 (91), 1-39.