Weiyang Ding

1.1k total citations
24 papers, 705 citations indexed

About

Weiyang Ding is a scholar working on Computational Mathematics, Computational Theory and Mathematics and Signal Processing. According to data from OpenAlex, Weiyang Ding has authored 24 papers receiving a total of 705 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computational Mathematics, 11 papers in Computational Theory and Mathematics and 6 papers in Signal Processing. Recurrent topics in Weiyang Ding's work include Tensor decomposition and applications (14 papers), Matrix Theory and Algorithms (11 papers) and Blind Source Separation Techniques (4 papers). Weiyang Ding is often cited by papers focused on Tensor decomposition and applications (14 papers), Matrix Theory and Algorithms (11 papers) and Blind Source Separation Techniques (4 papers). Weiyang Ding collaborates with scholars based in China, Hong Kong and Canada. Weiyang Ding's co-authors include Yimin Wei, Liqun Qi, Ziyan Luo, Michael K. Ng, Tong Wei, Hong Yan, Guang‐Jing Song, Jinjie Liu, Liang Du and Saijun Zhang and has published in prestigious journals such as Nature Communications, Pattern Recognition Letters and Applied Mathematics and Computation.

In The Last Decade

Weiyang Ding

22 papers receiving 683 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Weiyang Ding China	11	609	433	129	98	97	24	705
Maolin Che China	18	712 1.2×	456 1.1×	153 1.2×	216 2.2×	125 1.3×	43	848
Chen Ling China	16	439 0.7×	455 1.1×	254 2.0×	109 1.1×	59 0.6×	41	739
Chaoqian Li China	18	590 1.0×	726 1.7×	356 2.8×	83 0.8×	127 1.3×	95	1.0k
Haifeng Ma China	15	132 0.2×	470 1.1×	180 1.4×	61 0.6×	94 1.0×	54	622
Guang‐Jing Song China	14	203 0.3×	359 0.8×	66 0.5×	197 2.0×	109 1.1×	43	716
Qingzhi Yang China	13	505 0.8×	1.2k 2.7×	787 6.1×	229 2.3×	27 0.3×	49	1.4k
Nick Vannieuwenhoven Belgium	10	303 0.5×	133 0.3×	30 0.2×	129 1.3×	41 0.4×	30	381
Jonas Ballani Germany	8	226 0.4×	135 0.3×	29 0.2×	97 1.0×	123 1.3×	12	343
Zhuo‐Heng He China	20	201 0.3×	989 2.3×	253 2.0×	44 0.4×	167 1.7×	51	1.2k

Countries citing papers authored by Weiyang Ding

Since Specialization

Citations

This map shows the geographic impact of Weiyang Ding'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 Weiyang Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weiyang Ding more than expected).

Fields of papers citing papers by Weiyang Ding

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Weiyang Ding. 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 Weiyang Ding. The network helps show where Weiyang Ding may publish in the future.

Co-authorship network of co-authors of Weiyang Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Weiyang Ding. A scholar is included among the top collaborators of Weiyang Ding 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 Weiyang Ding. Weiyang Ding 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

Liu, Qingyang, et al.. (2025). Cross-spatial scale processing of hierarchical auditory sequences in human brains revealed using 7 T magnetic resonance imaging. Nature Communications. 17(1). 639–639.

Ding, Weiyang, et al.. (2024). Perturbation Analysis on T-Eigenvalues of Third-Order Tensors. Journal of Optimization Theory and Applications. 202(2). 668–702. 6 indexed citations

Wei, Tong, Weiyang Ding, & Yimin Wei. (2024). Singular Value Decomposition of Dual Matrices and its Application to Traveling Wave Identification in the Brain. SIAM Journal on Matrix Analysis and Applications. 45(1). 634–660. 26 indexed citations

Du, Liang, et al.. (2023). Rethinking precision of pseudo label: Test-time adaptation via complementary learning. Pattern Recognition Letters. 177. 96–102. 8 indexed citations

Ding, Weiyang, et al.. (2023). Noda iteration for computing generalized tensor eigenpairs. Journal of Computational and Applied Mathematics. 432. 115284–115284. 5 indexed citations

Ding, Weiyang & Jie Li. (2023). Higher Order Extended Dynamic Mode Decomposition Based on the Structured Total Least Squares. SIAM Journal on Scientific Computing. 45(2). A985–A1011.

Du, Liang, et al.. (2022). Modify Self-Attention via Skeleton Decomposition for Effective Point Cloud Transformer. Proceedings of the AAAI Conference on Artificial Intelligence. 36(1). 808–816. 4 indexed citations

Zhang, Saijun, et al.. (2021). Prediction of ductile fracture for DP590 high-strength steel with a new semi-coupled ductile fracture criterion. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 44(1). 8 indexed citations

Ding, Weiyang, Jinjie Liu, Liqun Qi, & Hong Yan. (2020). Elasticity M-tensors and the strong ellipticity condition. Applied Mathematics and Computation. 373. 124982–124982. 16 indexed citations

10.

Ding, Weiyang, Michael K. Ng, & Wenxing Zhang. (2019). A Peaceman–Rachford Splitting Method with Monotone Plus Skew-Symmetric Splitting for Nonlinear Saddle Point Problems. Journal of Scientific Computing. 81(2). 763–788. 1 indexed citations

11.

Ding, Weiyang, Ziyan Luo, & Liqun Qi. (2018). P-tensors, P0-tensors, and their applications. Linear Algebra and its Applications. 555. 336–354. 51 indexed citations

12.

Liu, Jinjie, Weiyang Ding, Liqun Qi, & Wennan Zou. (2018). Isotropic polynomial invariants of Hall tensor. Applied Mathematics and Mechanics. 39(12). 1845–1856. 4 indexed citations

13.

Ding, Weiyang, et al.. (2018). High performance hardware architecture for singular spectrum analysis of Hankel tensors. Microprocessors and Microsystems. 64. 120–127. 3 indexed citations

14.

Ding, Weiyang, et al.. (2017). Computing the p-Spectral Radii of Uniform Hypergraphs with Applications. Journal of Scientific Computing. 75(1). 1–25. 16 indexed citations

15.

Ding, Weiyang, Michael K. Ng, & Yimin Wei. (2017). Fast computation of stationary joint probability distribution of sparse Markov chains. Applied Numerical Mathematics. 125. 68–85. 7 indexed citations

16.

Ding, Weiyang, Liqun Qi, & Yimin Wei. (2016). Inheritance properties and sum-of-squares decomposition of Hankel tensors: theory and algorithms. BIT Numerical Mathematics. 57(1). 169–190. 8 indexed citations

17.

Ding, Weiyang & Yimin Wei. (2016). Solving Multi-linear Systems with $$\mathcal {M}$$ M -Tensors. Journal of Scientific Computing. 68(2). 689–715. 153 indexed citations

18.

Ding, Weiyang, Liqun Qi, & Yimin Wei. (2015). Fast Hankel tensor–vector product and its application to exponential data fitting. Numerical Linear Algebra with Applications. 22(5). 814–832. 41 indexed citations

19.

Ding, Weiyang & Yimin Wei. (2015). Generalized Tensor Eigenvalue Problems. SIAM Journal on Matrix Analysis and Applications. 36(3). 1073–1099. 42 indexed citations

20.

Ding, Weiyang, Liqun Qi, & Yimin Wei. (2013). M-tensors and nonsingularM-tensors. Linear Algebra and its Applications. 439(10). 3264–3278. 206 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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