Yanlai Chen

34 papers receiving 613 citations

Peers

Yanlai Chen
Comparison fields: 5 of 67
  • Numerical Analysis 174
  • Statistical and Nonlinear Physics 338
  • Computational Mechanics 353
  • Statistics, Probability and Uncertainty 111
  • Computational Theory and Mathematics 95
Replace Jens Berg with:
Jens Berg Sweden
Jens L. Eftang Norway
A.T. Patera United States
Julia Novo Spain
Alvise Sommariva Italy
Kailiang Wu China
T. A. Porsching United States
D. Estep United States
B.B. King United States
Laurent Baratchart France
Yanlai Chen relative to Jens Berg Sweden Jens Berg's profile →
Citations per field
00.5×2×4×5.8×
Jens Berg · 1×
Citations per year

Countries citing papers authored by Yanlai Chen

Since Specialization
Citations

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

Fields of papers citing papers by Yanlai Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yanlai Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yanlai Chen Line = papers co-authored together Yanlai Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200697
2 201079
3 201071
4 201251
5 200936
6 201334
7 202331
8 200826
9 201221
10 201018
11 202118
12 201517
13 201816
14
On uniform effect measure functions and a weighted multi-attribute grey target decision model
201315
15 201214
16 201512
17 202212
18 201711
19 201611
20 201410

About Yanlai Chen

Yanlai Chen is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics, Numerical Analysis, Electrical and Electronic Engineering and Statistics, Probability and Uncertainty, having authored 36 papers that have together received 661 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (25 papers), Advanced Numerical Methods in Computational Mathematics (20 papers), Numerical methods for differential equations (12 papers), Electromagnetic Simulation and Numerical Methods (8 papers), Computational Fluid Dynamics and Aerodynamics (8 papers), Probabilistic and Robust Engineering Design (7 papers), Numerical methods in engineering (5 papers) and Differential Equations and Numerical Methods (3 papers). The work is most often cited by research in Numerical Analysis (174 citations), Statistical and Nonlinear Physics (338 citations), Computational Mechanics (353 citations), Statistics, Probability and Uncertainty (111 citations) and Computational Theory and Mathematics (95 citations). Yanlai Chen has collaborated with scholars based in United States, China and France. Frequent co-authors include Jan S. Hesthaven, Bernardo Cockburn, Yvon Maday, Chen Shen, Jerónimo Rodríguez, Akil Narayan, Sigal Gottlieb, David J. Knezevic, Anthony T. Patera and D.B.P. Huynh. Their work appears in journals such as Journal of Scientific Computing, SIAM Journal on Scientific Computing, Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and Comptes Rendus Mathématique.

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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