Jon Warren
- Statistics and Probability top 2%
- Random Matrices and Applications 9
- Markov Chains and Monte Carlo Methods 9
- Mathematical Physics top 5%
- Stochastic processes and statistical mechanics 16
- Mathematical Dynamics and Fractals 6
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- Stochastic processes and financial applications 6
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- Gene Regulatory Network Analysis 4
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- Point processes and geometric inequalities 3
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- Bayesian Methods and Mixture Models 2
- Co-authors
- A. B. DiekerNeil O’ConnellSaul JackaJonathan P. KeatingMichael PrähoferAlexei BorodinTomohiro SasamotoYueyun Hu
- Journals
- Advances in Applied Probability (4 papers)Stochastic Processes and their Applications (4 papers)Electronic Journal of Probability (4 papers)
- Partner nations
- United KingdomUnited StatesIreland
In The Last Decade
Jon Warren
22 papers receiving 183 citations
Peers
Comparison fields: 5 of 26
- Statistics and Probability 154
- Mathematical Physics 156
- Discrete Mathematics and Combinatorics 53
- Condensed Matter Physics 27
- Finance 21
Countries citing papers authored by Jon Warren
This map shows the geographic impact of Jon Warren'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 Jon Warren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jon Warren more than expected).
Fields of papers citing papers by Jon Warren
This network shows the impact of papers produced by Jon Warren. 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 Jon Warren. The network helps show where Jon Warren may publish in the future.
Co-authorship network
The 10 scholars most cited alongside Jon Warren, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 5 | |
| 2 | 2021 | 12 | |
| 3 | 2020 | 3 | |
| 4 | 2019 | 0 | |
| 5 | 2015 | 16 | |
| 6 | 2009 | 4 | |
| 7 | 2009 | 17 | |
| 8 | 2009 | 4 | |
| 9 | 2009 | 24 | |
| 10 | 2008 | 11 | |
| 11 | 2008 | 15 | |
| 12 | 2007 | 43 | |
| 13 | 2006 | 5 | |
| 14 | 2006 | 4 | |
| 15 | 2005 | 3 | |
| 16 | 2005 | 3 | |
| 17 | 2005 | 2 | |
| 18 | 2005 | 3 | |
| 19 | 2005 | 2 | |
| 20 | 2002 | 3 |
About Jon Warren
Jon Warren is a scholar working on Mathematical Physics, Statistics and Probability, Finance, Discrete Mathematics and Combinatorics and Applied Mathematics, having authored 23 papers that have together received 194 indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (16 papers), Random Matrices and Applications (9 papers), Markov Chains and Monte Carlo Methods (9 papers), Mathematical Dynamics and Fractals (6 papers), Stochastic processes and financial applications (6 papers), Gene Regulatory Network Analysis (4 papers), Point processes and geometric inequalities (3 papers) and Bayesian Methods and Mixture Models (2 papers). The work is most often cited by research in Statistics and Probability (154 citations), Mathematical Physics (156 citations), Discrete Mathematics and Combinatorics (53 citations), Condensed Matter Physics (27 citations) and Finance (21 citations). Jon Warren has collaborated with scholars based in United Kingdom, United States and Ireland. Frequent co-authors include A. B. Dieker, Neil O’Connell, Saul Jacka, Jonathan P. Keating, Michael Prähofer, Alexei Borodin, Tomohiro Sasamoto, Yueyun Hu, Patrik L. Ferrari and Shinzo Watanabe. Their work appears in journals such as Advances in Applied Probability, Stochastic Processes and their Applications, Electronic Journal of Probability, Annales de l Institut Henri Poincaré Probabilités et Statistiques and Mathematics of Operations Research.
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.