期刊：
Wang, Z. , and Zhu, Z. (2025+), Resampling Method for Generalized One-per-Stratum Sampling Designs, Statistica Sinica, (To appear soon).
Zhang, X., Ren, C., Wang, Z., Li, X. and Zhang, Y. (2025), Gap-filling GRACE and GRACE-FO data with a climate adjustment scheme using Singular Spectrum analysis, Journal of Hydrology, 132782.
Gang, M., Wang, X., Wang, Z. and Zhong, W. (2024), Probability-Weighted Clustered Coefficient Regression Models in Complex Survey Sampling, Electronic Journal of Statistics, 18(2), 4198–4234
Mao, X., Wang, H., Wang, Z. , and Yang, S. (2024), Mixed Matrix Completion in Complex Survey Sampling under Heterogeneous Missingness, Journal of Computational and Graphical Statistics, 33(4), 1320-1328.
Zhan, T., Mao, X., Wang, J. and Wang, Z. (2024), Collective Matrix Completion via Graph Extraction, IEEE Signal Processing Letters, 31, 2620-2624.
He, X., Mao, X., and Wang, Z. (2024), Nonparametric augmented probability weighting with sparsity, Computational Statistics & Data Analysis, 191, 107890.
Kim, J.K., Rao, J.N.K., and Wang, Z. (2024), Hypotheses Testing from Complex Survey Data Using Bootstrap Weights: A Unified Approach, Journal of the American Statistical Association, 119(546), 1229–1239.
Mao, X., Wang, Z. and Yang, S. (2023), Matrix completion under complex survey sampling, Annals of the Institute of Statistical Mathematics, 75, 463-492.
Wang, Z., Kim, H.J. and Kim, J.K. (2023), Survey data integration for regression analysis using model calibration, Survey Methodology, 49(1), 89-115.
Wang, Z. and Kim, J.K. (2022), Comments on "Statistical inference with non-probability survey samples", Survey Methodology, 48(2), 361-366.
Wang, Z., Peng, L., and Kim, J.K. (2022), Bootstrap Inference for the Finite Population Mean under Complex Sampling Designs, Journal of the Royal Statistical Society Series B (Statistical Methodology), 84(4), 1150-1174.
Mao, X., Peng, L., and Wang, Z.. (2022), Nonparametric Feature Selection by Random Forests and Deep Neural Networks, Computational Statistics & Data Analysis, 170, 107436.
Zhang, X., Wang, Y.P., Rayner, P.J. et al. (2021), A small climate-amplifying effect of climate-carbon cycle feedback, Nature Communications, 12, 2952.
Wang, Z.. (2019), Monte Carlo Sampling Using Reservoir, Computational Statistics & Data Analysis, 139, 64-74.
Wang, Z. and Zhu, Z. (2019). Spatiotemporal Balanced Sampling Design for Longitudinal Area Survey, Journal of Agriculture, Biological and Environmental Statistics, 24(2), 245-263.
Kim, J.K. and Wang, Z. (2018). Sampling Techniques for Big Data Analysis, International Statistics Review, 84(S1), S177-S191.
Wang, Z., Kim J. K. and Yang, S. (2018). Approximate Bayesian Inference under Informative Sampling, Biometrika, 105(1), 91-102.
Yin, S., Wang, Z., Zhu, Z., Zou, X. and Wang, W. (2018). Using Kriging with a Heterogeneous Measurement Error to Improve the Accuracy of Extreme Precipitation Return Level Estimation, Journal of Hydrology, 562, 518-529.
Kim, J.K., Wang, Z., Zhu, Z.and Cruze, N.(2018). Combining survey and non-survey data for improved sub-area prediction using a multi-level model, Journal of Agriculture, Biological and Environmental Statistics, 23(2), 175-189.
Huang, C., Zheng, X., Tail, A. et al. (2014), On using smoothing spline and residual correction to fuse rain gauge observations and remote sensing data, Journal of Hydrology, 508(16), 410-417
Li, T., Zheng, X., Dai, Y. et al. (2014), Mapping near-surface air temperature, pressure, relative humidity and wind speed over Mainland China with high spatiotemporal resolution, Advances in Atmospheric Sciences, 31(5), 1127-1135
Gu, B., Zheng, S., Mao, X., and Wang, Z. (2025+) Transfer Learning via Functional Balancing in Reproducing Kernel Hilbert Spaces, ICASSP (CCF B), (To appear soon).
Wang, H., Zhang, Y., Mao, X., and Wang, Z. (2023) Transductive Matrix Completion with Calibration for Multi-Task Learning, ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-5.
Pu, Y., Feng, Z., Wang, Z., Yang, Z. and Li, J. (2021). Anomaly Detection for In situ Marine Plankton Images, ICCV Workshop in Computer Vision in the Ocean.
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