Peter Eichelsbacher

646 citations
39 papers · 276 · h-index 10

Impact in

Papers in

Peter Eichelsbacher

37 papers receiving 248 citations

Peers

Peter Eichelsbacher
Comparison fields: 5 of 45
  • Statistics and Probability 179
  • Mathematical Physics 133
  • Discrete Mathematics and Combinatorics 38
  • Applied Mathematics 68
  • Finance 59
Replace Vladimir Rotar with:
Vladimir Rotar Russia
Eugene Lytvynov United Kingdom
Guillaume Poly France
Н. В. Цилевич Russia
Bero Roos Germany
Vitali Wachtel Germany
Christoph Thäle Germany
Benedek Valkó United States
V. Čekanavičius Lithuania
Steven Kalikow United States
Peter Eichelsbacher relative to Vladimir Rotar Russia Vladimir Rotar's profile →
Citations per field
00.5×2.6×
Vladimir Rotar · 1×
Citations per year

Countries citing papers authored by Peter Eichelsbacher

Since Specialization
Citations

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

Fields of papers citing papers by Peter Eichelsbacher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Peter Eichelsbacher, 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 Peter Eichelsbacher Line = papers co-authored together Peter Eichelsbacher links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201426
2 200325
3 201025
4 200821
5 201521
6 200818
7 199513
8 199912
9 200211
10 200211
11 19989
12 20039
13 20138
14 20228
15 20027
16 19976
17 20235
18 20095
19 20044
20
Large deviations for products of empirical measures of dependent sequences
20013

About Peter Eichelsbacher

Peter Eichelsbacher is a scholar working on Statistics and Probability, Mathematical Physics, Finance, Artificial Intelligence and Applied Mathematics, having authored 39 papers that have together received 276 indexed citations. Recurring topics across this work include Random Matrices and Applications (14 papers), Stochastic processes and statistical mechanics (13 papers), Statistical Methods and Inference (10 papers), Stochastic processes and financial applications (8 papers), Bayesian Methods and Mixture Models (8 papers), Markov Chains and Monte Carlo Methods (6 papers), Theoretical and Computational Physics (5 papers) and Probability and Risk Models (5 papers). The work is most often cited by research in Statistics and Probability (179 citations), Mathematical Physics (133 citations), Discrete Mathematics and Combinatorics (38 citations), Applied Mathematics (68 citations) and Finance (59 citations). Peter Eichelsbacher has collaborated with scholars based in Germany, United Kingdom and Switzerland. Frequent co-authors include Christoph Thäle, Matthias Löwe, Uwe Schmock, Wolfgang König, Gesine Reinert, Małgorzata Roos, Tim Zajic, Neil O’Connell, Yuliy Baryshnikov and J. E. Yukich. Their work appears in journals such as Electronic Journal of Probability, Stochastic Processes and their Applications, Bernoulli, ESAIM Probability and Statistics and Probability Theory and Related Fields.

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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