Maolin Che

1.2k total citations
43 papers, 848 citations indexed

About

Maolin Che is a scholar working on Computational Mathematics, Computational Theory and Mathematics and Computational Mechanics. According to data from OpenAlex, Maolin Che has authored 43 papers receiving a total of 848 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Computational Mathematics, 22 papers in Computational Theory and Mathematics and 17 papers in Computational Mechanics. Recurrent topics in Maolin Che's work include Tensor decomposition and applications (37 papers), Matrix Theory and Algorithms (22 papers) and Sparse and Compressive Sensing Techniques (15 papers). Maolin Che is often cited by papers focused on Tensor decomposition and applications (37 papers), Matrix Theory and Algorithms (22 papers) and Sparse and Compressive Sensing Techniques (15 papers). Maolin Che collaborates with scholars based in China, Hong Kong and Australia. Maolin Che's co-authors include Yimin Wei, Xuezhong Wang, Liqun Qi, Hong Yan, Andrzej Cichocki, Xi-Le Zhao, Chaoqian Li, Guofeng Zhang, Yonghe Liu and Changjiang Bu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Neurocomputing and Journal of Computational and Applied Mathematics.

In The Last Decade

Maolin Che

40 papers receiving 827 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Maolin Che China	18	712	456	216	153	125	43	848
Ziyan Luo China	12	538 0.8×	445 1.0×	157 0.7×	205 1.3×	97 0.8×	41	849
André Uschmajew Germany	16	522 0.7×	262 0.6×	311 1.4×	109 0.7×	168 1.3×	35	758
Christine Tobler Switzerland	9	569 0.8×	363 0.8×	284 1.3×	91 0.6×	244 2.0×	11	803
Weiyang Ding China	11	609 0.9×	433 0.9×	98 0.5×	129 0.8×	97 0.8×	24	705
Giorgio Ottaviani Italy	20	510 0.7×	380 0.8×	129 0.6×	78 0.5×	65 0.5×	65	1.1k
Christopher J. Hillar United States	11	478 0.7×	302 0.7×	302 1.4×	65 0.4×	52 0.4×	42	933
Shenglong Hu China	19	781 1.1×	710 1.6×	133 0.6×	416 2.7×	64 0.5×	60	1.1k
Chaoqian Li China	18	590 0.8×	726 1.6×	83 0.4×	356 2.3×	127 1.0×	95	1.0k
Guang‐Jing Song China	14	203 0.3×	359 0.8×	197 0.9×	66 0.4×	109 0.9×	43	716

Countries citing papers authored by Maolin Che

Since Specialization

Citations

This map shows the geographic impact of Maolin Che's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Maolin Che with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maolin Che more than expected).

Fields of papers citing papers by Maolin Che

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maolin Che. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Maolin Che. The network helps show where Maolin Che may publish in the future.

Co-authorship network of co-authors of Maolin Che

This figure shows the co-authorship network connecting the top 25 collaborators of Maolin Che. A scholar is included among the top collaborators of Maolin Che based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Maolin Che. Maolin Che is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Wu, Chong, Maolin Che, & Hong Yan. (2025). The CUR Decomposition of Self-Attention Matrices in Vision Transformers. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(4). 4792–4809.

Wu, Chong, et al.. (2025). ELFATT: Efficient Linear Fast Attention for Vision Transformers. 9140–9149. 1 indexed citations

Che, Maolin, Yimin Wei, & Hong Yan. (2025). Gradient neural network models for approximate Tucker decomposition of time-dependent tensors. Neurocomputing. 640. 130330–130330.

Che, Maolin, Yimin Wei, & Hong Yan. (2025). Efficient Randomized Algorithms for Fixed Precision Problem of Approximate Tucker Decomposition. SIAM Journal on Matrix Analysis and Applications. 46(1). 256–297. 3 indexed citations

Che, Maolin, Yimin Wei, & Hong Yan. (2025). Efficient algorithms for Tucker decomposition via approximate matrix multiplication. Advances in Computational Mathematics. 51(3). 3 indexed citations

Zhao, Xi-Le, et al.. (2024). A Fast Algorithm for Rank-(L, M, N) Block Term Decomposition of Multi-Dimensional Data. Journal of Scientific Computing. 101(1). 1 indexed citations

Che, Maolin, Yimin Wei, & Hong Yan. (2024). Sketch-based multiplicative updating algorithms for symmetric nonnegative tensor factorizations with applications to face image clustering. Journal of Global Optimization. 89(4). 995–1032.

Li, Chaoqian, et al.. (2023). Randomized block Krylov subspace algorithms for low-rank quaternion matrix approximations. Numerical Algorithms. 96(2). 687–717. 7 indexed citations

Che, Maolin, Xuezhong Wang, Yimin Wei, & Xi-Le Zhao. (2022). Fast randomized tensor singular value thresholding for low‐rank tensor optimization. Numerical Linear Algebra with Applications. 29(6). 13 indexed citations

10.

Wang, Xuezhong, et al.. (2022). Solving the system of nonsingular tensor equations via randomized Kaczmarz-like method. Journal of Computational and Applied Mathematics. 421. 114856–114856. 21 indexed citations

11.

Wang, Xuezhong, Maolin Che, & Yimin Wei. (2020). Preconditioned tensor splitting AOR iterative methods for ℋ‐tensor equations. Numerical Linear Algebra with Applications. 27(6). 14 indexed citations

12.

Che, Maolin, Yimin Wei, & Hong Yan. (2020). The Computation of Low Multilinear Rank Approximations of Tensors via Power Scheme and Random Projection. SIAM Journal on Matrix Analysis and Applications. 41(2). 605–636. 32 indexed citations

13.

Che, Maolin & Yimin Wei. (2020). Multiplicative Algorithms for Symmetric Nonnegative Tensor Factorizations and Its Applications. Journal of Scientific Computing. 83(3). 7 indexed citations

14.

Wang, Xuezhong, Maolin Che, & Yimin Wei. (2019). Existence and uniqueness of positive solution for H+-tensor equations. Applied Mathematics Letters. 98. 191–198. 19 indexed citations

15.

Wang, Xuezhong, Maolin Che, & Yimin Wei. (2019). Neural network approach for solving nonsingular multi-linear tensor systems. Journal of Computational and Applied Mathematics. 368. 112569–112569. 35 indexed citations

16.

Wang, Xuezhong, Maolin Che, & Yimin Wei. (2019). Global uniqueness and solvability of tensor complementarity problems for $\mathcal {H}_{+}$-tensors. Numerical Algorithms. 84(2). 567–590. 22 indexed citations

17.

Che, Maolin, Guoyin Li, Liqun Qi, & Yimin Wei. (2017). Pseudo-spectra theory of tensors and tensor polynomial eigenvalue problems. Linear Algebra and its Applications. 533. 536–572. 7 indexed citations

18.

Wang, Xuezhong, Maolin Che, & Yimin Wei. (2017). Partial orthogonal rank-one decomposition of complex symmetric tensors based on the Takagi factorization. Journal of Computational and Applied Mathematics. 332. 56–71. 10 indexed citations

19.

Che, Maolin, Liqun Qi, & Yimin Wei. (2016). Iterative algorithms for computing US- and U-eigenpairs of complex tensors. Journal of Computational and Applied Mathematics. 317. 547–564. 10 indexed citations

20.

Che, Maolin & Yimin Wei. (2016). An Inequality for the Perron Pair of an Irreducible and Symmetric Nonnegative Tensor with Application. Journal of the Operations Research Society of China. 5(1). 65–82. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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