Weiming Li

410 total citations
34 papers, 219 citations indexed

About

Weiming Li is a scholar working on Statistics and Probability, Artificial Intelligence and Applied Mathematics. According to data from OpenAlex, Weiming Li has authored 34 papers receiving a total of 219 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Statistics and Probability, 10 papers in Artificial Intelligence and 7 papers in Applied Mathematics. Recurrent topics in Weiming Li's work include Random Matrices and Applications (18 papers), Bayesian Methods and Mixture Models (10 papers) and Statistical Methods and Bayesian Inference (6 papers). Weiming Li is often cited by papers focused on Random Matrices and Applications (18 papers), Bayesian Methods and Mixture Models (10 papers) and Statistical Methods and Bayesian Inference (6 papers). Weiming Li collaborates with scholars based in China, Hong Kong and United States. Weiming Li's co-authors include Jianfeng Yao, Zhou Wang, Yingli Qin, Jiang Hu, Chang Liu, Yajun Zhu, Jiwei Zhang, Kun Xu, Zhidong Bai and Yuting Lü and has published in prestigious journals such as Journal of the American Statistical Association, Journal of Computational Physics and IEEE Transactions on Information Theory.

In The Last Decade

Weiming Li

27 papers receiving 209 citations

Peers

Weiming Li
Comparison fields: 5 of 59
  • Statistics and Probability 120
  • Applied Mathematics 64
  • Computational Mechanics 50
  • Artificial Intelligence 47
  • Mathematical Physics 28
Replace Krzysztof Łatuszyński with:
Krzysztof Łatuszyński United Kingdom
N. Etemadi United States
Pierre Calka France
Yulong Lu United States
A. P. Shashkin Russia
Jesús de la Cal Spain
L. Saulis Lithuania
Anthony Réveillac France
Raphaël Lachièze-Rey France
Krzysztof Łatuszyński United Kingdom View profile →
Citations per field, relative to Weiming Li
Weiming Li · 1×
Citations per year, relative to Weiming Li
Weiming Li · 1×

Countries citing papers authored by Weiming Li

Since Specialization
Citations

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

Fields of papers citing papers by Weiming Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weiming Li

This figure shows the co-authorship network connecting the top 25 collaborators of Weiming Li. A scholar is included among the top collaborators of Weiming Li 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 Weiming Li. Weiming Li 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
# Work Indexed citations
1 0
2 6
3 1
4 5
5 1
6 1
7 1
8 1
9 3
10 33
11 17
12 4
13 14
14 11
15 12
16 2
17 19
18 0
19 13
20 3

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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