Étienne Birmelé
- Statistical and Nonlinear Physics top 10%
- Artificial Intelligence
- Molecular Biology
- Computational Theory and Mathematics top 10%
- Statistics and Probability top 10%
- Co-authors
- Christophe AmbroisePierre LatoucheJ. A. BondyVittorio PerducaLaura BagliettoMohamed ElatiCéline RouveirolMarie‐France Sagot
- Topics
- Bioinformatics and Genomic Networks (6 papers)Advanced Graph Theory Research (5 papers)Bayesian Methods and Mixture Models (4 papers)
In The Last Decade
Étienne Birmelé
23 papers receiving 214 citations
Peers
Comparison fields: 5 of 69
- Statistical and Nonlinear Physics 78
- Artificial Intelligence 54
- Molecular Biology 53
- Computational Theory and Mathematics 45
- Statistics and Probability 32
Countries citing papers authored by Étienne Birmelé
This map shows the geographic impact of Étienne Birmelé'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 Étienne Birmelé with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Étienne Birmelé more than expected).
Fields of papers citing papers by Étienne Birmelé
This network shows the impact of papers produced by Étienne Birmelé. 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 Étienne Birmelé. The network helps show where Étienne Birmelé may publish in the future.
Co-authorship network of co-authors of Étienne Birmelé
This figure shows the co-authorship network connecting the top 25 collaborators of Étienne Birmelé. A scholar is included among the top collaborators of Étienne Birmelé based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Étienne Birmelé. Étienne Birmelé is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | 2 | |
| 7 | 33 | |
| 8 | 3 | |
| 9 | 2 | |
| 10 | 9 | |
| 11 | 10 | |
| 12 | 6 | |
| 13 | 73 | |
| 14 | Assessing a mixture model for graphs with a non asymptotic approximation of the marginal likelihood | 0 |
| 15 | Overlapping Stochastic Block Models | 6 |
| 16 | Bayesian Methods for Graph Clustering. | 3 |
| 17 | 8 | |
| 18 | 14 | |
| 19 | 1 | |
| 20 | 4 |
About Étienne Birmelé
Étienne Birmelé is a scholar working on Discrete Mathematics and Combinatorics, Medical Laboratory Technology and Statistics and Probability, having authored 26 papers that have together received 221 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (6 papers), Advanced Graph Theory Research (5 papers) and Bayesian Methods and Mixture Models (4 papers). The work is most often cited by research in Discrete Mathematics and Combinatorics (22 citations), Statistical and Nonlinear Physics (78 citations) and Statistics and Probability (32 citations). Étienne Birmelé has collaborated with scholars based in France, Italy and Canada. Frequent co-authors include Christophe Ambroise, Pierre Latouche, J. A. Bondy, Vittorio Perduca, Laura Baglietto, Mohamed Elati, Céline Rouveirol, Marie‐France Sagot, Frédéric Havet and Michele Borassi. Their work appears in journals such as Nature Communications, Bioinformatics and Theoretical Computer Science.
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.