Stéphane Gaïffas

665 total citations
19 papers, 209 citations indexed

About

Stéphane Gaïffas is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Stéphane Gaïffas has authored 19 papers receiving a total of 209 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Statistics and Probability, 8 papers in Artificial Intelligence and 3 papers in Computational Mechanics. Recurrent topics in Stéphane Gaïffas's work include Statistical Methods and Inference (8 papers), Sparse and Compressive Sensing Techniques (3 papers) and Advanced Causal Inference Techniques (3 papers). Stéphane Gaïffas is often cited by papers focused on Statistical Methods and Inference (8 papers), Sparse and Compressive Sensing Techniques (3 papers) and Advanced Causal Inference Techniques (3 papers). Stéphane Gaïffas collaborates with scholars based in France, Burundi and United States. Stéphane Gaïffas's co-authors include Agathe Guilloux, Guillaume Lecué, Emmanuel Bacry, Erwan Scornet, Fabienne Comte, Émile Richard, Nicolas Vayatis, Anne‐Sophie Jannot, Amine Benyamina and Henri‐Jean Aubin and has published in prestigious journals such as IEEE Transactions on Information Theory, Journal of the Royal Statistical Society Series B (Statistical Methodology) and Journal of Machine Learning Research.

In The Last Decade

Stéphane Gaïffas

17 papers receiving 203 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stéphane Gaïffas France 9 83 71 19 17 16 19 209
Tengyuan Liang United States 8 96 1.2× 67 0.9× 40 2.1× 28 1.6× 5 0.3× 24 211
Hannes Sieling Germany 4 47 0.6× 114 1.6× 8 0.4× 13 0.8× 50 3.1× 5 209
Jussi Klemelä Germany 11 124 1.5× 165 2.3× 25 1.3× 38 2.2× 15 0.9× 27 320
Bert van Es Netherlands 12 105 1.3× 225 3.2× 12 0.6× 14 0.8× 6 0.4× 23 341
Claire Lacour France 9 74 0.9× 182 2.6× 19 1.0× 25 1.5× 12 0.8× 21 255
Gertraud Malsiner‐Walli Austria 6 134 1.6× 87 1.2× 2 0.1× 12 0.7× 23 1.4× 15 228
Mohamed Hebiri France 7 70 0.8× 96 1.4× 65 3.4× 20 1.2× 30 1.9× 13 242
Xiequan Fan China 9 47 0.6× 79 1.1× 5 0.3× 9 0.5× 17 1.1× 38 216
Tingni Sun United States 6 91 1.1× 200 2.8× 35 1.8× 9 0.5× 53 3.3× 9 279

Countries citing papers authored by Stéphane Gaïffas

Since Specialization
Citations

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

Fields of papers citing papers by Stéphane Gaïffas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stéphane Gaïffas

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

All Works

19 of 19 papers shown
1.
Gaïffas, Stéphane, et al.. (2023). Robust supervised learning with coordinate gradient descent. Statistics and Computing. 33(5).
2.
Gaïffas, Stéphane, et al.. (2021). A Review on Contrastive Learning Methods and Applications to Roof-Type Classification on Aerial Images. HAL (Le Centre pour la Communication Scientifique Directe). 4960–4963. 2 indexed citations
3.
Gaïffas, Stéphane, et al.. (2021). AMF: Aggregated Mondrian Forests for Online Learning. Journal of the Royal Statistical Society Series B (Statistical Methodology). 83(3). 505–533. 20 indexed citations
4.
Gaïffas, Stéphane, et al.. (2020). SCALPEL3: A scalable open-source library for healthcare claims databases. International Journal of Medical Informatics. 141. 104203–104203.
5.
Bacry, Emmanuel, et al.. (2019). ConvSCCS: convolutional self-controlled case-seris model for lagged adverser event detection. HAL (Le Centre pour la Communication Scientifique Directe). 7 indexed citations
6.
Veil, Raphaël, Anita Burgun, Stéphane Gaïffas, et al.. (2019). Comparison of methods for early-readmission prediction in a high-dimensional heterogeneous covariates and time-to-event outcome framework. BMC Medical Research Methodology. 19(1). 50–50. 10 indexed citations
7.
Bacry, Emmanuel, et al.. (2018). tick: a Python Library for Statistical Learning, with an emphasis on Hawkes Processes and Time-Dependent Models. Journal of Machine Learning Research. 18(214). 1–5. 42 indexed citations
8.
9.
Guilloux, Agathe, et al.. (2018). C-mix: A high-dimensional mixture model for censored durations, with applications to genetic data. Statistical Methods in Medical Research. 28(5). 1523–1539. 6 indexed citations
10.
Gaïffas, Stéphane, et al.. (2017). Universal consistency and minimax rates for online Mondrian Forests. Neural Information Processing Systems. 30. 3758–3767. 4 indexed citations
11.
Bacry, Emmanuel, Stéphane Gaïffas, & Jean–François Muzy. (2017). Concentration inequalities for matrix martingales in continuous time. Probability Theory and Related Fields. 170(1-2). 525–553. 2 indexed citations
12.
Gaïffas, Stéphane, et al.. (2015). Learning the Intensity of Time Events With Change-Points. IEEE Transactions on Information Theory. 61(9). 5148–5171. 3 indexed citations
13.
Richard, Émile, Stéphane Gaïffas, & Nicolas Vayatis. (2012). Link Prediction in Graphs with Autoregressive Features. Journal of Machine Learning Research. 15(1). 565–593. 15 indexed citations
14.
Gaïffas, Stéphane & Agathe Guilloux. (2012). High-dimensional additive hazards models and the Lasso. Electronic Journal of Statistics. 6(none). 24 indexed citations
15.
Delattre, Sylvain & Stéphane Gaïffas. (2011). Nonparametric regression with martingale increment errors. Stochastic Processes and their Applications. 121(12). 2899–2924. 2 indexed citations
16.
Comte, Fabienne, et al.. (2011). Adaptive estimation of the conditional intensity of marker-dependent counting processes. Annales de l Institut Henri Poincaré Probabilités et Statistiques. 47(4). 21 indexed citations
17.
Gaïffas, Stéphane & Guillaume Lecué. (2011). Sharp Oracle Inequalities for High-Dimensional Matrix Prediction. IEEE Transactions on Information Theory. 57(10). 6942–6957. 9 indexed citations
18.
Gaïffas, Stéphane & Guillaume Lecué. (2007). Optimal rates and adaptation in the single-index model using aggregation. Electronic Journal of Statistics. 1(none). 23 indexed citations
19.
Gaïffas, Stéphane. (2007). On pointwise adaptive curve estimation based on inhomogeneous data. ESAIM Probability and Statistics. 11. 344–364. 8 indexed citations

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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