Maud Delattre
- Molecular Biology
- Statistics and Probability top 5%
- Public Health, Environmental and Occupational Health
- Physiology
- Finance top 10%
- Co-authors
- Marc LavielleStéphane RobinTristan Mary‐HuardCéline Lévy‐LeducValentine Genon‐CatalotMarion TharreyFrançois MariottiGary E. Fraser
- Topics
- Statistical Methods and Inference (8 papers)Statistical Methods and Bayesian Inference (7 papers)Bayesian Methods and Mixture Models (6 papers)
- Partner nations
- FranceUnited StatesLuxembourg
In The Last Decade
Maud Delattre
23 papers receiving 463 citations
Peers
Comparison fields: 5 of 108
- Molecular Biology 136
- Statistics and Probability 123
- Public Health, Environmental and Occupational Health 71
- Physiology 61
- Finance 52
Countries citing papers authored by Maud Delattre
This map shows the geographic impact of Maud Delattre'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 Maud Delattre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maud Delattre more than expected).
Fields of papers citing papers by Maud Delattre
This network shows the impact of papers produced by Maud Delattre. 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 Maud Delattre. The network helps show where Maud Delattre may publish in the future.
Co-authorship network of co-authors of Maud Delattre
This figure shows the co-authorship network connecting the top 25 collaborators of Maud Delattre. A scholar is included among the top collaborators of Maud Delattre 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 Maud Delattre. Maud Delattre is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 31 | |
| 6 | 2 | |
| 7 | 97 | |
| 8 | 13 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | Parametric Estimation in Mixed-Effects Stochastic Differential Equations [R package MsdeParEst version 1.7] | 1 |
| 12 | 6 | |
| 13 | 10 | |
| 14 | 4 | |
| 15 | 76 | |
| 16 | 103 | |
| 17 | Coupling the SAEM algorithm and the extended Kalman filter for maximum likelihood estimation in mixed-effects diffusion models | 0 |
| 18 | 21 | |
| 19 | 15 | |
| 20 | 8 |
About Maud Delattre
Maud Delattre is a scholar working on Statistics and Probability, Mathematical Physics and Finance, having authored 24 papers that have together received 482 indexed citations. Recurring topics across this work include Statistical Methods and Inference (8 papers), Statistical Methods and Bayesian Inference (7 papers) and Bayesian Methods and Mixture Models (6 papers). The work is most often cited by research in Statistics and Probability (123 citations), Finance (52 citations) and Public Health, Environmental and Occupational Health (71 citations). Maud Delattre has collaborated with scholars based in France, United States and Luxembourg. Frequent co-authors include Marc Lavielle, Stéphane Robin, Tristan Mary‐Huard, Céline Lévy‐Leduc, Valentine Genon‐Catalot, Marion Tharrey, François Mariotti, Gary E. Fraser, Andrew Mashchak and Pierre Barbillon. Their work appears in journals such as Bioinformatics, Scientific Reports and International Journal of Epidemiology.
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.