Uwe Einmahl

1.3k citations
33 papers · 831 · h-index 14

Impact in

    • Statistical Methods and Inference
    • Statistical Methods and Bayesian Inference
  • Finance top 5%
    • Stochastic processes and financial applications
    • Financial Risk and Volatility Modeling

Papers in

Uwe Einmahl

31 papers receiving 725 citations

Peers

Uwe Einmahl
Comparison fields: 5 of 59
  • Statistics and Probability 501
  • Finance 237
  • Management Science and Operations Research 269
  • Mathematical Physics 188
  • Numerical Analysis 102
Replace Tien-Chung Hu with:
Tien-Chung Hu Taiwan
Víctor Peña United States
Ya. Yu. Nikitin Russia
V. Bentkus Lithuania
Miguel A. Arcones United States
R. J. Serfling United States
Mikhail Lifshits Russia
Vygantas Paulauskas Lithuania
S. V. Nagaev Russia
Jérôme Dedecker France
Uwe Einmahl relative to Tien-Chung Hu Taiwan Tien-Chung Hu's profile →
Citations per field
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Tien-Chung Hu · 1×
Citations per year

Countries citing papers authored by Uwe Einmahl

Since Specialization
Citations

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

Fields of papers citing papers by Uwe Einmahl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 5 scholars most cited alongside Uwe Einmahl, 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 Uwe Einmahl Line = papers co-authored together Uwe Einmahl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005189
2 1989108
3 2000104
4 198772
5 199738
6 198737
7 200834
8 198931
9 200529
10 199220
11 199318
12 200617
13 199613
14 198913
15 200912
16 200710
17 19919
18 20019
19 19939
20 19958

About Uwe Einmahl

Uwe Einmahl is a scholar working on Management Science and Operations Research, Statistics and Probability, Mathematical Physics, Finance and Numerical Analysis, having authored 33 papers that have together received 831 indexed citations. Recurring topics across this work include Probability and Risk Models (20 papers), Mathematical Approximation and Integration (7 papers), Stochastic processes and financial applications (7 papers), Stochastic processes and statistical mechanics (7 papers), Random Matrices and Applications (7 papers), Statistical Methods and Inference (6 papers), Bayesian Methods and Mixture Models (6 papers) and Statistical Distribution Estimation and Applications (5 papers). The work is most often cited by research in Statistics and Probability (501 citations), Finance (237 citations), Management Science and Operations Research (269 citations), Mathematical Physics (188 citations) and Numerical Analysis (102 citations). Uwe Einmahl has collaborated with scholars based in United States, Belgium and Germany. Frequent co-authors include David M. Mason, Deli Li, J. Kuelbs, David M. Mason and Victor Goodman. Their work appears in journals such as Probability Theory and Related Fields, The Annals of Probability, Journal of Theoretical Probability, Transactions of the American Mathematical Society and Electronic Journal of Probability.

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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