Jean‐Michel Marin
- Genetics top 1%
- Statistics and Probability top 0.2%
- Artificial Intelligence top 1%
- Molecular Biology top 10%
- Ecology top 2%
- Co-authors
- Christian P. RobertJean‐Marie CornuetPierre PudloArnaud EstoupMark BeaumontMathieu GautierRaphaël LebloisRobin Ryder
- Topics
- Bayesian Methods and Mixture Models (29 papers)Markov Chains and Monte Carlo Methods (22 papers)Statistical Methods and Bayesian Inference (12 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Statistical AssociationBioinformatics
- Partner nations
- FranceUnited KingdomItaly
In The Last Decade
Jean‐Michel Marin
56 papers receiving 4.1k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Genetics 1.5k
- Statistics and Probability 1.2k
- Artificial Intelligence 1.2k
- Molecular Biology 885
- Ecology 687
Countries citing papers authored by Jean‐Michel Marin
This map shows the geographic impact of Jean‐Michel Marin'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 Jean‐Michel Marin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jean‐Michel Marin more than expected).
Fields of papers citing papers by Jean‐Michel Marin
This network shows the impact of papers produced by Jean‐Michel Marin. 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 Jean‐Michel Marin. The network helps show where Jean‐Michel Marin may publish in the future.
Co-authorship network of co-authors of Jean‐Michel Marin
This figure shows the co-authorship network connecting the top 25 collaborators of Jean‐Michel Marin. A scholar is included among the top collaborators of Jean‐Michel Marin 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 Jean‐Michel Marin. Jean‐Michel Marin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 8 | |
| 3 | ABC model choice via random forests | 5 |
| 4 | Bayesian Essentials with R (2nd ed.) | 4 |
| 5 | 41 | |
| 6 | 1 | |
| 7 | 81 | |
| 8 | 315 | |
| 9 | Modèles réduits à partir d’expériences numériques | 1 |
| 10 | 212 | |
| 11 | 28 | |
| 12 | Some difficulties with some posterior probability approximations | 1 |
| 13 | 14 | |
| 14 | ABC methods for model choice in Gibbs random fields | 3 |
| 15 | Approximating the marginal likelihood in mixture models | 2 |
| 16 | Bayesian Core: A Practical Approach to Computational Bayesian Statistics (Springer Texts in Statistics) | 23 |
| 17 | Sélection bayésienne de variables en régression linéaire | 8 |
| 18 | Estimation bayésienne approximative par échantillonnage préférentiel | 0 |
| 19 | Population Monte Carlo for Ion Channel Restoration | 5 |
| 20 | 13 |
About Jean‐Michel Marin
Jean‐Michel Marin is a scholar working on Statistics and Probability, General Decision Sciences and Artificial Intelligence, having authored 57 papers that have together received 4.3k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (29 papers), Markov Chains and Monte Carlo Methods (22 papers) and Statistical Methods and Bayesian Inference (12 papers). The work is most often cited by research in Statistics and Probability (1.2k citations), Ecological Modeling (249 citations) and Genetics (1.5k citations). Jean‐Michel Marin has collaborated with scholars based in France, United Kingdom and Italy. Frequent co-authors include Christian P. Robert, Jean‐Marie Cornuet, Pierre Pudlo, Arnaud Estoup, Mark Beaumont, Mathieu Gautier, Raphaël Leblois, Robin Ryder, J. M. Cornuet and Thomas Guillemaud. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Statistical Association and Bioinformatics.
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.