学术论文：
[1] Qianru Liu, Rui Wang and Yuesheng Xu. Sparsity-guided multi-parameter selection in l1-regularized models via a fixed-point proximity approach. Journal of Scientific Computing, 107(1), 14, 1-50, 2026.
[2] Rui Wang, Yuesheng Xu and Mingsong Yan. Hypothesis spaces for deep learning, Neural Networks, 193, 107995, 1-14, 2026.
[3] Rui Wang, Yuesheng Xu and Mingsong Yan. Sparse representer theorems for learning in reproducing kernel Banach spaces. Journal of Machine Learning Research, 25, 93, 1-45, 2024.
[4] Liu Qianru, Rui Wang, Yuesheng Xu and Mingsong Yan. Parameter choices for sparse regularization with the l1 norm. Inverse Problems, 39(2), 025004, 1-34, 2023.
[5] Rui Wang and Yuesheng Xu. Representer theorems in Banach spaces: minimum norm interpolation, regularized learning and semi-discrete inverse problems. Journal of Machine Learning Research, 22, 225, 1-65, 2021.
[6] Rui Wang and Yuesheng Xu. Functional reproducing kernel Hilbert spaces for non-point-evaluation functional data. Applied and Computational Harmonic Analysis, 46(3) , 569-623, 2019.
[7] Rui Wang and Xiangling Chen. A fast solver for boundary integral equations of the modified Helmholtz equation. Journal of Scientific Computing, 65(2), 553-575,2015.
[8] Xiangling Chen, Rui Wang and Yuesheng Xu. Fast Fourier-Galerkin methods for nonlinear boundary integral equations. Journal of Scientific Computing, 56(3),494-514, 2013.
[9] Jianqiang Liu, Charles A. Micchelli, Rui Wang and Yuesheng Xu. Finite rank kernels for multi-task learning. Advances in Computational Mathematics, 38(2),427-439, 2013.
[10] Tao Qian, Rui Wang, Yuesheng Xu and Haizhang Zhang. Orthonormal bases
with nonlinear phases. Advances in Computational Mathematics, 33(1), 75-95, 2010.
著作教材：
[1] 张然，王蕊，翟起龙，王春朋， 数学分析(第二册),“101计划”核心教材，高等教育出版社，北京，2025.
[2] 王春朋，王蕊，吕俊良，段犇， 数学分析(第三册),“101计划”核心教材，高等教育出版社，北京，2025.
