Robin Genuer

4.0k total citations · 2 hit papers
14 papers, 2.6k citations indexed

About

Robin Genuer is a scholar working on Artificial Intelligence, Statistics and Probability and Computer Vision and Pattern Recognition. According to data from OpenAlex, Robin Genuer has authored 14 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Statistics and Probability and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Robin Genuer's work include Statistical Methods and Inference (4 papers), Statistical Methods and Bayesian Inference (3 papers) and Neural Networks and Applications (3 papers). Robin Genuer is often cited by papers focused on Statistical Methods and Inference (4 papers), Statistical Methods and Bayesian Inference (3 papers) and Neural Networks and Applications (3 papers). Robin Genuer collaborates with scholars based in France, Mexico and Australia. Robin Genuer's co-authors include Jean‐Michel Poggi, Christine Tuleau-Malot, Marie Chavent, Jérôme Saracco, Cécile Proust‐Lima, Catherine Helmer, Karine Pérès, Catherine Féart, Hélène Amieva and Maturin Tabué-Teguo and has published in prestigious journals such as Statistics in Medicine, The Journals of Gerontology Series A and Human Brain Mapping.

In The Last Decade

Robin Genuer

13 papers receiving 2.5k citations

Hit Papers

Variable selection using random forests 2010 2026 2015 2020 2010 2015 500 1000 1.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Variable selection using random forests
    2010 1.9k citations Robin Genuer, Jean‐Michel Poggi et al. Pattern Recognition Letters profile →
  2. VSURF: An R Package for Variable Selection Using Random Forests
    2015 445 citations Robin Genuer, Jean‐Michel Poggi et al. The R Journal profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Robin Genuer France 9 516 453 441 403 232 14 2.6k
Christine Tuleau-Malot France 6 505 1.0× 447 1.0× 420 1.0× 353 0.9× 230 1.0× 11 2.4k
Jean‐Michel Poggi France 17 536 1.0× 496 1.1× 552 1.3× 491 1.2× 232 1.0× 47 3.5k
Thomas Augustin Germany 21 461 0.9× 387 0.9× 327 0.7× 840 2.1× 245 1.1× 127 4.4k
Brian J. Reich United States 39 681 1.3× 867 1.9× 768 1.7× 774 1.9× 392 1.7× 214 5.3k
Miron B. Kursa Poland 12 448 0.9× 354 0.8× 484 1.1× 596 1.5× 139 0.6× 24 4.6k
Robert A. Rigby United Kingdom 22 384 0.7× 941 2.1× 257 0.6× 432 1.1× 325 1.4× 51 5.2k
Elizabeth A. Peck United States 5 428 0.8× 448 1.0× 359 0.8× 422 1.0× 327 1.4× 7 5.0k
Witold R. Rudnicki Poland 14 454 0.9× 348 0.8× 475 1.1× 660 1.6× 137 0.6× 44 4.7k
D. Stasinopoulos United Kingdom 15 325 0.6× 830 1.8× 207 0.5× 330 0.8× 269 1.2× 28 4.4k
Ioannis Dimopoulos Greece 11 402 0.8× 298 0.7× 511 1.2× 328 0.8× 358 1.5× 22 2.2k

Countries citing papers authored by Robin Genuer

Since Specialization
Citations

This map shows the geographic impact of Robin Genuer'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 Robin Genuer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robin Genuer more than expected).

Fields of papers citing papers by Robin Genuer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robin Genuer. 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 Robin Genuer. The network helps show where Robin Genuer may publish in the future.

Co-authorship network of co-authors of Robin Genuer

This figure shows the co-authorship network connecting the top 25 collaborators of Robin Genuer. A scholar is included among the top collaborators of Robin Genuer 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 Robin Genuer. Robin Genuer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Helmer, Catherine, et al.. (2024). Functional Principal Component Analysis as an Alternative to Mixed‐Effect Models for Describing Sparse Repeated Measures in Presence of Missing Data. Statistics in Medicine. 43(26). 4899–4912. 1 indexed citations
2.
Catoire, P., Robin Genuer, & Cécile Proust‐Lima. (2023). Causal inference from observational data in emergency medicine research. European Journal of Emergency Medicine. 30(2). 67–69.
3.
Helmer, Catherine, et al.. (2023). Random survival forests with multivariate longitudinal endogenous covariates. Statistical Methods in Medical Research. 32(12). 2331–2346. 7 indexed citations
4.
Genuer, Robin, et al.. (2022). Individual dynamic prediction of clinical endpoint from large dimensional longitudinal biomarker history: a landmark approach. BMC Medical Research Methodology. 22(1). 188–188. 8 indexed citations
5.
Dartigues, Jean‐François, Maturin Tabué-Teguo, Mélanie Le Goff, et al.. (2022). Co-Occurrence of Geriatric Syndromes and Diseases in the General Population: Assessment of the Dimensions of Aging. The journal of nutrition health & aging. 26(1). 37–45. 14 indexed citations
6.
Genuer, Robin & Jean‐Michel Poggi. (2020). Random Forests with R. HAL (Le Centre pour la Communication Scientifique Directe). 118 indexed citations
7.
Genuer, Robin, Jean‐Michel Poggi, & Christine Tuleau-Malot. (2019). Variable Selection Using Random Forests [R package VSURF version 1.1.0]. 3 indexed citations
8.
Chavent, Marie, Robin Genuer, & Jérôme Saracco. (2019). Combining clustering of variables and feature selection using random forests. Communications in Statistics - Simulation and Computation. 50(2). 426–445. 38 indexed citations
9.
Tabué-Teguo, Maturin, Leslie Grasset, José Alberto Ávila‐Funes, et al.. (2017). Prevalence and Co-Occurrence of Geriatric Syndromes in People Aged 75 Years and Older in France: Results From the Bordeaux Three-city Study. The Journals of Gerontology Series A. 73(1). 109–116. 45 indexed citations
10.
Zago, Laure, et al.. (2017). Predicting hemispheric dominance for language production in healthy individuals using support vector machine. Human Brain Mapping. 38(12). 5871–5889. 22 indexed citations
11.
Arlot, Sylvain & Robin Genuer. (2016). Comments on: A random forest guided tour. Test. 25(2). 228–238. 9 indexed citations
12.
Genuer, Robin, Jean‐Michel Poggi, & Christine Tuleau-Malot. (2015). VSURF: An R Package for Variable Selection Using Random Forests. The R Journal. 7(2). 19–19. 445 indexed citations breakdown →
13.
Genuer, Robin. (2012). Variance reduction in purely random forests. Journal of nonparametric statistics. 24(3). 543–562. 48 indexed citations
14.
Genuer, Robin, Jean‐Michel Poggi, & Christine Tuleau-Malot. (2010). Variable selection using random forests. Pattern Recognition Letters. 31(14). 2225–2236. 1852 indexed citations breakdown →

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.

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