Research Interest
Causal Inference
Measurement Errors
Functional Data/Panel Data/Longitudinal Data
Journal Publications
Tan, R., Huang, W., Zhang, Z. and Yin, G. (to appear). Causal effect of functional treatment. JMLR.
Hou, H., Huang, W. and Zheng, Z. (2025). Non-parametric quantile regression and uniform inference with unknown error distribution. JBES, 1 - 23.
Huang, W., Li, S. and Peng, L. (2024). Estimation and Inference for Extreme Continuous Treatment Effects. JBES, 1 - 26. Link
Wang, Y., Huang, W., Gong, M., Geng, X., Liu, T., Zhang, K. and Tao, D. (2024). Identifiability and asymptotics in learning homogeneous linear ODE systems from discrete observations. JMLR, 25, 1 - 50. Link
Huang, L., Huang, W., Linton, O. and Zhang, Z. (2024). Nonparametric estimation of mediation effects with a general treatment. Econometric Reviews. Link
Huang, W. and Zhang, Z. (2023). Nonparametric estimation of continuous treatment effect with measurement error. JRSSB, 85, 474 - 496. Link Appendix Huang's MATLAB codes
Huang, W., Linton, O. and Zhang, Z. (2022). A unified framework for specification tests of continuous treatment effect models. JBES, 40, 1817-1830. Link Appendix Huang's MATLAB codes
Delaigle, A., Hall, P., Huang, W. and Kneip, A. (2021). Estimating the covariance of fragmented and other related types of functional data. JASA, 116, 1383-1401. Link Appendix Huang's MATLAB codes
Delaigle, A., Huang, W. and Lei, S. (2020). Estimation of conditional prevalence from group testing data with missing covariates. JASA, 115, 467-480. Link Appendix Huang's R codes
Conference papers
Wang, M., Huang, W., Gong, M. and Zhang, Z. (2025). Projection Pursuit Density Ratio Estimation. ICML 2025.
Wang, Y., Huang, B., Huang, W., Geng, X. and Gong, M. (2024). Identifiability Analysis of Linear ODE Systems with Hidden Confounders. NeurIPS 2024.
Gao, E., Bondell, H., Huang, W., and Gong, M. (2024). A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error. ICLR 2024. Link Gao's Python codes
Wang, Y., Geng, X., Huang, W., Huang, B. and Gong, M. (2023). Generator Identification for Linear SDEs with Additive and Multiplicative Noise. NeurIPS 2023.
Gao, E., Ng, I., Gong, M., Shen, L., Huang, W., Liu, T., Zhang, K. and Bondell, H. (2022). MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. NeurIPS 2022.