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的个人主页 http://shi.buaa.edu.cn/xingwei/zh_CN/index.htm
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[1] .• Triantafyllidis, V., Xing, W., Shah, A. A., & Nair, P. B. (2016). Neural network emulation of spatio-temporal data using linear and nonlinear dimensionality reduction. In Advanced Computer and Communication Engineering Technology (pp. 1015-1029). Springer, Cham.
[2] .• Xing, W.W., Triantafyllidis, V., Shah, A.A., Nair, P.B. and Zabaras, N., 2016. Manifold learning for the emulation of spatial fields from computational models. Journal of Computational Physics, 326, pp.666-690. （中科院分区Q2，JCR Q1）
[3] .• Shah, A. A., Xing, W. W., & Triantafyllidis, V. (2017). Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 473(2200), 20160809. (中科院分区Q2，JCR Q2)
[4] .• Xing, W., Shah, A. A., Urasinska-Wojcik, B., & Gardner, J. W. (2017, October). Prediction of impurities in hydrogen fuel supplies using a thermally-modulated CMOS gas sensor: Experiments and modelling. In 2017 IEEE SENSORS (pp. 1-3). IEEE.
[5] .• Triantafyllidiis, V., Xing, W. W., Leung, P. K., Rodchanarowan, A., & Shah, A. A. (2018, June). Probabilistic sensitivity analysis for multivariate model outputs with applications to Li-ion batteries. In Journal of Physics: Conference Series (Vol. 1039, No. 1, p. 012020). IOP Publishing.
[6] .• Gadd, C., Xing, W., Nezhad, M. M., & Shah, A. A. (2019). A surrogate modelling approach based on nonlinear dimension reduction for uncertainty quantification in groundwater flow models. Transport in porous media, 126(1), 39-77. （中科院分区Q2，JCR Q2）
[7] .• Zhe, S., Xing, W., & Kirby, R. M. (2019, April). Scalable High-Order Gaussian Process Regression. In The 22nd International Conference on Artificial Intelligence and Statistics (pp. 2611-2620). （中国计算机学会B类会议，统计学习业内顶级会议，接收率30%)
[8] .• Wang, J., Xing, W#., Kirby, R. M., & Zhang, M. (2019, June). Data-Driven Model Order Reduction for Diffeomorphic Image Registration. In International Conference on Information Processing in Medical Imaging (pp. 694-705). Springer, Cham. (#equal contributions to the first author)（医学图像处理最顶级会议，接收率25%，论文获得2019年会议最佳学术海报奖）
[9] .• Xing, W., Elhabian, S., Zhe, S, and Kirby, R.M, 2019, Infinite ShapeOdds: A Nonlinear Generative Model for Grid-Structured Shapes. The Thirty-four AAAI (Association for the Advancement of Artificial Intelligence) conference for artificial intelligence. （中国计算机学会A类会议，接收率20%)
[10] .• Xing, W., Elhabian, Vahid, K. and Kirby, R.M, 2019, Shared-GP: Learning Interpretable Shared Hidden Structure Across Data Spaces for Design Space Analysis and Exploration. Journal of mechanical design, 2020,1-16（中科院分区Q2，JCR Q2）

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