Xiuyuan Cheng

1.1k total citations
42 papers, 413 citations indexed

About

Xiuyuan Cheng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistics and Probability. According to data from OpenAlex, Xiuyuan Cheng has authored 42 papers receiving a total of 413 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 10 papers in Statistics and Probability. Recurrent topics in Xiuyuan Cheng's work include Topological and Geometric Data Analysis (6 papers), Model Reduction and Neural Networks (5 papers) and Random Matrices and Applications (4 papers). Xiuyuan Cheng is often cited by papers focused on Topological and Geometric Data Analysis (6 papers), Model Reduction and Neural Networks (5 papers) and Random Matrices and Applications (4 papers). Xiuyuan Cheng collaborates with scholars based in United States, China and France. Xiuyuan Cheng's co-authors include E Weinan, Pingwen Zhang, Ling Lin, An‐Chang Shi, Amit Singer, Ruaidhrí Jackson, Esen Sefik, Ofir Lindenbaum, Yuval Kluger and Ariel Jaffe and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nature Biotechnology.

In The Last Decade

Xiuyuan Cheng

38 papers receiving 399 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiuyuan Cheng United States 10 103 75 65 47 43 42 413
Vasileios Maroulas United States 13 93 0.9× 57 0.8× 115 1.8× 23 0.5× 42 1.0× 57 582
Sjoerd Dirksen Germany 11 38 0.4× 224 3.0× 49 0.8× 36 0.8× 44 1.0× 27 660
Jonas Köhler Germany 8 236 2.3× 234 3.1× 129 2.0× 13 0.3× 46 1.1× 23 564
José A. Cañizo Spain 12 37 0.4× 78 1.0× 24 0.4× 26 0.6× 8 0.2× 42 750
Cyril Furtlehner France 11 64 0.6× 77 1.0× 141 2.2× 7 0.1× 71 1.7× 24 481
Peter Müller Germany 12 65 0.6× 57 0.8× 14 0.2× 19 0.4× 4 0.1× 53 448
Timo Aspelmeier Germany 18 181 1.8× 127 1.7× 17 0.3× 40 0.9× 14 0.3× 44 765
Ralf Banisch Germany 8 66 0.6× 119 1.6× 24 0.4× 15 0.3× 5 0.1× 14 243
Maxime Clusel France 10 143 1.4× 26 0.3× 118 1.8× 16 0.3× 5 0.1× 17 528
Adam M. Johansen United Kingdom 14 20 0.2× 80 1.1× 346 5.3× 212 4.5× 15 0.3× 42 709

Countries citing papers authored by Xiuyuan Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Xiuyuan Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiuyuan Cheng

This figure shows the co-authorship network connecting the top 25 collaborators of Xiuyuan Cheng. A scholar is included among the top collaborators of Xiuyuan Cheng 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 Xiuyuan Cheng. Xiuyuan Cheng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cheng, Xiuyuan, et al.. (2025). Deep Spatiotemporal Point Processes: Advances and New Directions. Annual Review of Statistics and Its Application. 13(1). 201–224.
2.
Cheng, Xiuyuan, et al.. (2024). Research on the online prediction method of coarse aggregates packing void ratio based on particle shape and grading. Construction and Building Materials. 458. 139698–139698. 2 indexed citations
3.
Cheng, Xiuyuan, et al.. (2024). The G-invariant graph Laplacian Part I: Convergence rate and eigendecomposition. Applied and Computational Harmonic Analysis. 71. 101637–101637.
4.
Qu, Rihao, Xiuyuan Cheng, Esen Sefik, et al.. (2024). Gene trajectory inference for single-cell data by optimal transport metrics. Nature Biotechnology. 43(2). 258–268. 12 indexed citations
5.
Lee, Jonghyeok, et al.. (2024). Flow-Based Distributionally Robust Optimization. IEEE Journal on Selected Areas in Information Theory. 5. 62–77. 1 indexed citations
6.
Zhang, Yuan, et al.. (2022). Statistical inference using GLEaM model with spatial heterogeneity and correlation between regions. Scientific Reports. 12(1). 16630–16630. 1 indexed citations
7.
Cheng, Xiuyuan & Alexander Cloninger. (2022). Classification Logit Two-Sample Testing by Neural Networks for Differentiating Near Manifold Densities. IEEE Transactions on Information Theory. 68(10). 6631–6662. 6 indexed citations
8.
Cheng, Xiuyuan, et al.. (2022). Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation. Applied and Computational Harmonic Analysis. 61. 132–190. 6 indexed citations
9.
Zhao, Jun, Ariel Jaffe, Ofir Lindenbaum, et al.. (2021). Detection of differentially abundant cell subpopulations in scRNA-seq data. Proceedings of the National Academy of Sciences. 118(22). 68 indexed citations
10.
Cheng, Xiuyuan, et al.. (2021). Graph Convolution with Low-rank Learnable Local Filters. International Conference on Learning Representations. 1 indexed citations
11.
Wang, Ze, et al.. (2021). Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks. Neural Information Processing Systems. 34. 3 indexed citations
12.
Cheng, Xiuyuan & Hau‐Tieng Wu. (2021). Convergence of graph Laplacian with kNN self-tuned kernels. Information and Inference A Journal of the IMA. 11(3). 889–957. 9 indexed citations
13.
Li, Yingzhou, Xiuyuan Cheng, & Jianfeng Lu. (2020). Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks. Communications in Computational Physics. 28(5). 1838–1885. 2 indexed citations
14.
Qiu, Qiang, Xiuyuan Cheng, A.R. Calderbank, & Guillermo Sapiro. (2018). DCFNet: Deep Neural Network with Decomposed Convolutional Filters. International Conference on Machine Learning. 9. 4198–4207. 4 indexed citations
15.
Yan, Bowei, Purnamrita Sarkar, & Xiuyuan Cheng. (2017). Exact Recovery of Number of Blocks in Blockmodels. arXiv (Cornell University). 2 indexed citations
16.
Cheng, Xiuyuan, Gal Mishne, & Stefan Steinerberger. (2017). The geometry of nodal sets and outlier detection. Journal of Number Theory. 185. 48–64. 5 indexed citations
17.
Cheng, Xiuyuan, et al.. (2016). A Graph Partitioning Approach to Simultaneous Angular Reconstitution. IEEE Transactions on Computational Imaging. 2(3). 323–334. 9 indexed citations
18.
Boumal, Nicolas & Xiuyuan Cheng. (2014). Concentration of the Kirchhoff index for Erdős–Rényi graphs. Systems & Control Letters. 74. 74–80. 3 indexed citations
19.
Boumal, Nicolas & Xiuyuan Cheng. (2013). Expected performance bounds for estimation on graphs from random relative measurements.. arXiv (Cornell University). 1 indexed citations
20.
Cheng, Xiuyuan, Ling Lin, E Weinan, Pingwen Zhang, & An‐Chang Shi. (2010). Nucleation of Ordered Phases in Block Copolymers. Physical Review Letters. 104(14). 148301–148301. 107 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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