Isabel Beichl

31 papers receiving 358 citations

Peers

Isabel Beichl
Comparison fields: 5 of 93
  • Statistics and Probability 68
  • Computer Graphics and Computer-Aided Design 27
  • Condensed Matter Physics 77
  • Mathematical Physics 45
  • Statistics, Probability and Uncertainty 31
Replace Francis E. Sullivan with:
Francis E. Sullivan United States
Braxton Osting United States
Zhou Yu China
Kwok Yip Szeto Hong Kong
Vasileios Maroulas United States
Alexander E. Holroyd United States
Dennis G. Zill United States
Shintaro Mori Japan
Doochul Kim South Korea
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Isabel Beichl relative to Francis E. Sullivan United States Francis E. Sullivan's profile →
Citations per field
00.5×3.9×
Francis E. Sullivan · 1×
Citations per year

Countries citing papers authored by Isabel Beichl

Since Specialization
Citations

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

Fields of papers citing papers by Isabel Beichl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000113
2 1995104
3 199928
4 199922
5 199322
6 199218
7 200111
8 19979
9 20086
10 19966
11 19975
12 20065
13 20084
14 19964
15 20123
16 20083
17 19993
18 20033
19
Generating Network Models Using the S-Metric
20082
20 19962

About Isabel Beichl

Isabel Beichl is a scholar working on Statistics and Probability, Computer Networks and Communications, Condensed Matter Physics, Mathematical Physics and Statistical and Nonlinear Physics, having authored 37 papers that have together received 389 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (11 papers), Stochastic processes and statistical mechanics (8 papers), Theoretical and Computational Physics (8 papers), Complex Network Analysis Techniques (5 papers), Advanced Chemical Physics Studies (4 papers), Computational Geometry and Mesh Generation (4 papers), Opinion Dynamics and Social Influence (4 papers) and Advanced Database Systems and Queries (3 papers). The work is most often cited by research in Statistics and Probability (68 citations), Computer Graphics and Computer-Aided Design (27 citations), Condensed Matter Physics (77 citations), Mathematical Physics (45 citations) and Statistics, Probability and Uncertainty (31 citations). Isabel Beichl has collaborated with scholars based in United States, Egypt and Russia. Frequent co-authors include Frank Sullivan, James L. Blue, Enrico Puppo, T. L. Einstein, Maria Carla Tesi, Attilio L. Stella, Dianne P. O’Leary, Enzo Orlandini, David G. Harris and Francis Sullivan. Their work appears in journals such as Computing in Science & Engineering, Journal of Computational Physics, Algorithmica, Physical Review Letters and Computational Statistics.

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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