Benoı̂t Cadre
Impact in
- Statistics and Probability top 2%
- Statistical Methods and Inference
- Advanced Statistical Methods and Models
- Statistical Methods and Bayesian Inference
- Mathematical Physics top 10%
- Mathematical Dynamics and Fractals
Papers in
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- Statistical Methods and Inference 16
- Advanced Statistical Methods and Models 8
-
- Bayesian Methods and Mixture Models 11
- Co-authors
- Gérard Biau (8 shared papers)Gérard Biau (6 shared papers)Christophe Abraham (7 shared papers)Bruno Pelletier (4 shared papers)Pierre Jacob (1 shared paper)Ali Gannoun (2 shared papers)Pierre Pudlo (1 shared paper)David Y. Mason (1 shared paper)
In The Last Decade
Benoı̂t Cadre
26 papers receiving 475 citations
Peers
Comparison fields: 5 of 86
- Statistics and Probability 238
- Mathematical Physics 83
- Geometry and Topology 51
- Artificial Intelligence 165
- Statistics, Probability and Uncertainty 33
Countries citing papers authored by Benoı̂t Cadre
This map shows the geographic impact of Benoı̂t Cadre'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 Benoı̂t Cadre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benoı̂t Cadre more than expected).
Fields of papers citing papers by Benoı̂t Cadre
This network shows the impact of papers produced by Benoı̂t Cadre. 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 Benoı̂t Cadre. The network helps show where Benoı̂t Cadre may publish in the future.
Co-authors
The 11 scholars most cited alongside Benoı̂t Cadre, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 91 | |
| 2 | 2004 | 69 | |
| 3 | 2005 | 60 | |
| 4 | 2002 | 41 | |
| 5 | 2003 | 31 | |
| 6 | 2001 | 23 | |
| 7 | 2006 | 23 | |
| 8 | 2008 | 22 | |
| 9 | 2005 | 22 | |
| 10 | 2003 | 19 | |
| 11 | 2007 | 14 | |
| 12 | 2013 | 14 | |
| 13 | 2020 | 13 | |
| 14 | 2004 | 12 | |
| 15 | 2001 | 11 | |
| 16 | 2009 | 10 | |
| 17 | 2004 | 8 | |
| 18 | 2013 | 5 | |
| 19 | 2002 | 4 | |
| 20 | 2011 | 4 |
About Benoı̂t Cadre
Benoı̂t Cadre is a scholar working on Statistics and Probability, Artificial Intelligence, Mathematical Physics, Applied Mathematics and Statistical and Nonlinear Physics, having authored 28 papers that have together received 507 indexed citations. Recurring topics across this work include Statistical Methods and Inference (16 papers), Bayesian Methods and Mixture Models (11 papers), Advanced Statistical Methods and Models (8 papers), Mathematical Dynamics and Fractals (4 papers), Advanced Statistical Process Monitoring (3 papers), Quantum chaos and dynamical systems (3 papers), Point processes and geometric inequalities (3 papers) and Stochastic processes and statistical mechanics (2 papers). The work is most often cited by research in Statistics and Probability (238 citations), Mathematical Physics (83 citations), Geometry and Topology (51 citations), Artificial Intelligence (165 citations) and Statistics, Probability and Uncertainty (33 citations). Benoı̂t Cadre has collaborated with scholars based in France, Russia and Morocco. Frequent co-authors include Gérard Biau, Gérard Biau, Christophe Abraham, Bruno Pelletier, Pierre Jacob, Ali Gannoun, Pierre Pudlo, David Y. Mason, Alain Berlinet and László Györfi. Their work appears in journals such as ESAIM Probability and Statistics, Journal of Mathematical Analysis and Applications, Journal of Multivariate Analysis, The Annals of Statistics and Test.
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.