Chun Yu

453 total citations
14 papers, 293 citations indexed

About

Chun Yu is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Chun Yu has authored 14 papers receiving a total of 293 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Statistics and Probability, 7 papers in Artificial Intelligence and 5 papers in Statistics, Probability and Uncertainty. Recurrent topics in Chun Yu's work include Advanced Statistical Methods and Models (6 papers), Bayesian Methods and Mixture Models (5 papers) and Advanced Statistical Process Monitoring (5 papers). Chun Yu is often cited by papers focused on Advanced Statistical Methods and Models (6 papers), Bayesian Methods and Mixture Models (5 papers) and Advanced Statistical Process Monitoring (5 papers). Chun Yu collaborates with scholars based in China, United States and Taiwan. Chun Yu's co-authors include Weixin Yao, Kun Chen, Xue Bai, Chen Chung Liu, Yize Zhao, Robert H. Aseltine, Yan Li, Ling‐Jing Kao, Fengyi Lin and Yi‐Chun Chen and has published in prestigious journals such as Biometrics, Computational Statistics & Data Analysis and International Statistical Review.

In The Last Decade

Chun Yu

13 papers receiving 283 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chun Yu China	6	109	99	37	29	28	14	293
Tiantian Yang China	8	81 0.7×	36 0.4×	24 0.6×	10 0.3×	51 1.8×	19	281
Stephen Bates United States	9	94 0.9×	126 1.3×	14 0.4×	16 0.6×	17 0.6×	14	494
Aldo Corbellini Italy	8	110 1.0×	49 0.5×	11 0.3×	23 0.8×	54 1.9×	22	261
Łukasz Smaga Poland	9	143 1.3×	56 0.6×	5 0.1×	24 0.8×	33 1.2×	50	322
K. D. S. Young United Kingdom	6	112 1.0×	41 0.4×	4 0.1×	25 0.9×	51 1.8×	16	368
W. Robert Stephenson United States	10	109 1.0×	33 0.3×	7 0.2×	7 0.2×	20 0.7×	29	328
Xue Ding China	10	69 0.6×	104 1.1×	10 0.3×	233 8.0×	6 0.2×	33	400
Ziyuan Luo China	8	17 0.2×	59 0.6×	19 0.5×	15 0.5×	8 0.3×	23	254
Chudi Zhong Canada	3	8 0.1×	272 2.7×	33 0.9×	13 0.4×	7 0.3×	3	474
Ana M. Palacios Spain	11	50 0.5×	155 1.6×	11 0.3×	16 0.6×	2 0.1×	33	333

Countries citing papers authored by Chun Yu

Since Specialization

Citations

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

Fields of papers citing papers by Chun Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chun Yu

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

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

1.

Li, Yong, et al.. (2023). Privacy-Preserving Swarm Learning Based on Lightweight Homomorphic Encryption and Blockchain Technology. 692–697.

2.

Li, Yan, Chun Yu, Yize Zhao, et al.. (2021). Pursuing sources of heterogeneity in modeling clustered population. Biometrics. 78(2). 716–729. 4 indexed citations

3.

Kao, Ling‐Jing, Fengyi Lin, & Chun Yu. (2021). Bayesian Behavior Scoring Model. Journal of Data Science. 11(3). 433–450. 3 indexed citations

4.

Yao, Weixin, et al.. (2020). A new class of multivariate goodness of fit tests for multivariate normal mixtures. Communications in Statistics - Simulation and Computation. 51(11). 6635–6648. 4 indexed citations

5.

Yu, Chun, et al.. (2019). UAV 3D modeling with multi-spectral imaging: an example of wax apple tree. 2. 9–9. 1 indexed citations

6.

Yu, Chun, et al.. (2019). A Selective Overview and Comparison of Robust Mixture Regression Estimators. International Statistical Review. 88(1). 176–202. 5 indexed citations

7.

Yu, Chun & Weixin Yao. (2016). Robust linear regression: A review and comparison. Communications in Statistics - Simulation and Computation. 46(8). 6261–6282. 164 indexed citations

8.

Yu, Chun, Weixin Yao, & Kun Chen. (2016). A new method for robust mixture regression. Canadian Journal of Statistics. 45(1). 77–94. 7 indexed citations

9.

Yu, Chun, Kun Chen, & Weixin Yao. (2015). Outlier detection and robust mixture modeling using nonconvex penalized likelihood. Journal of Statistical Planning and Inference. 164. 27–38. 14 indexed citations

10.

Yu, Chun, et al.. (2014). Hamming Code Based Watermarking Scheme for 3D Model Verification. 1095–1098. 14 indexed citations

11.

Yu, Chun, et al.. (2014). A Novel Scheme for the Fovea Localization on Retinal Images. 609–612. 4 indexed citations

12.

Yu, Chun, Weixin Yao, & Xue Bai. (2014). Robust Linear Regression: A Review and Comparison. arXiv (Cornell University). 2 indexed citations

13.

Yu, Chun, et al.. (2014). Automatic Localization of the Optic Disc Based on Iterative Brightest Pixels Extraction. 2. 613–616. 7 indexed citations

14.

Yao, Weixin, et al.. (2013). Robust mixture regression using thet-distribution. Computational Statistics & Data Analysis. 71. 116–127. 64 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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