Mu-Fa Chen

1.8k citations
67 papers · 1.1k · h-index 19

Impact in

Papers in

Mu-Fa Chen

63 papers receiving 1.0k citations

Peers

Mu-Fa Chen
Comparison fields: 5 of 71
  • Mathematical Physics 512
  • Statistics and Probability 447
  • Applied Mathematics 392
  • Computational Theory and Mathematics 252
  • Finance 157
Replace Xiaowen Zhou with:
Xiaowen Zhou Canada
Patrick Cattiaux France
Jaime San Martı́n Chile
Alain‐Sol Sznitman Switzerland
Jürgen Gärtner Germany
Nobuaki Obata Japan
Erwin Bolthausen Switzerland
Edwin Perkins Canada
Jean Bertoin France
Laurent Miclo France
Mu-Fa Chen relative to Xiaowen Zhou Canada Xiaowen Zhou's profile →
Citations per field
00.5×2.9×
Xiaowen Zhou · 1×
Citations per year

Countries citing papers authored by Mu-Fa Chen

Since Specialization
Citations

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

Fields of papers citing papers by Mu-Fa Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Mu-Fa 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 Mu-Fa Chen Line = papers co-authored together Mu-Fa Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004138
2 198987
3 200064
4 199762
5 199660
6 199750
7 200046
8 201040
9 199932
10 200030
11 200128
12 200028
13 199426
14 199725
15 199324
16 199124
17 199121
18 198621
19 199918
20 199915

About Mu-Fa Chen

Mu-Fa Chen is a scholar working on Mathematical Physics, Computational Theory and Mathematics, Statistics and Probability, Applied Mathematics and Statistical and Nonlinear Physics, having authored 67 papers that have together received 1.1k indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (17 papers), Stochastic processes and statistical mechanics (15 papers), Spectral Theory in Mathematical Physics (14 papers), Advanced Mathematical Modeling in Engineering (13 papers), Nonlinear Partial Differential Equations (10 papers), Matrix Theory and Algorithms (9 papers), Numerical methods in inverse problems (7 papers) and Geometric Analysis and Curvature Flows (6 papers). The work is most often cited by research in Mathematical Physics (512 citations), Statistics and Probability (447 citations), Applied Mathematics (392 citations), Computational Theory and Mathematics (252 citations) and Finance (157 citations). Mu-Fa Chen has collaborated with scholars based in China, Italy and United States. Frequent co-authors include Feng‐Yu Wang, Yuhui Zhang, Yingzhe Wang, Xu Zhang, E. Scacciatelli, Yun Gang Lu, Yuhui Zhang, Zhigang Jia, Hong‐Kui Pang and Rong‐Rong Chen. Their work appears in journals such as The Annals of Probability, Journal of Applied Probability, Frontiers of Mathematics in China, Acta Mathematica Sinica English Series and Stochastic Processes and their Applications.

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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