Stéphane Gaïffas
Impact in
- Statistics and Probability top 5%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Advanced Statistical Methods and Models
-
- Bayesian Methods and Mixture Models
- Data Stream Mining Techniques
Papers in
-
- Statistical Methods and Inference 8
- Advanced Causal Inference Techniques 3
-
- Domain Adaptation and Few-Shot Learning 2
- Co-authors
- Agathe Guilloux (5 shared papers)Guillaume Lecué (2 shared papers)Emmanuel Bacry (4 shared papers)Erwan Scornet (2 shared papers)Fabienne Comte (1 shared paper)Émile Richard (1 shared paper)Nicolas Vayatis (1 shared paper)Anne‐Sophie Jannot (2 shared papers)
- Journals
- Electronic Journal of Statistics (2 papers)Journal of Machine Learning Research (2 papers)IEEE Transactions on Information Theory (2 papers)BMC Medical Research Methodology (1 paper)International Journal of Medical Informatics (1 paper)
- Partner nations
- FranceUnited StatesBurundi
In The Last Decade
Stéphane Gaïffas
18 papers receiving 208 citations
Peers
Comparison fields: 5 of 82
- Statistics and Probability 73
- Artificial Intelligence 82
- Computational Mathematics 1
- Applied Mathematics 16
- Statistics, Probability and Uncertainty 9
Countries citing papers authored by Stéphane Gaïffas
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
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-authors
The 18 scholars most cited alongside Stéphane Gaïffas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | tick: a Python Library for Statistical Learning, with an emphasis on Hawkes Processes and Time-Dependent Models | 2018 | 42 |
| 2 | 2007 | 25 | |
| 3 | 2012 | 24 | |
| 4 | 2011 | 21 | |
| 5 | 2021 | 20 | |
| 6 | Link Prediction in Graphs with Autoregressive Features | 2012 | 15 |
| 7 | 2018 | 12 | |
| 8 | 2019 | 10 | |
| 9 | 2011 | 9 | |
| 10 | 2007 | 9 | |
| 11 | 2019 | 7 | |
| 12 | 2018 | 6 | |
| 13 | Universal consistency and minimax rates for online Mondrian Forests | 2017 | 4 |
| 14 | 2015 | 3 | |
| 15 | 2017 | 2 | |
| 16 | 2011 | 2 | |
| 17 | 2021 | 2 | |
| 18 | 2023 | 1 | |
| 19 | 2020 | 0 |
About Stéphane Gaïffas
Stéphane Gaïffas is a scholar working on Statistics and Probability, Artificial Intelligence, Computational Mechanics, Finance and Computational Theory and Mathematics, having authored 19 papers that have together received 214 indexed citations. Recurring topics across this work include Statistical Methods and Inference (8 papers), Advanced Causal Inference Techniques (3 papers), Sparse and Compressive Sensing Techniques (3 papers), Financial Risk and Volatility Modeling (2 papers), Topological and Geometric Data Analysis (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Point processes and geometric inequalities (1 paper) and Control Systems and Identification (1 paper). The work is most often cited by research in Statistics and Probability (73 citations), Artificial Intelligence (82 citations), Computational Mathematics (1 citation), Applied Mathematics (16 citations) and Statistics, Probability and Uncertainty (9 citations). Stéphane Gaïffas has collaborated with scholars based in France, United States and Burundi. Frequent co-authors include Agathe Guilloux, Guillaume Lecué, Emmanuel Bacry, Erwan Scornet, Fabienne Comte, Émile Richard, Nicolas Vayatis, Anne‐Sophie Jannot, Henri‐Jean Aubin and Amine Benyamina. Their work appears in journals such as Electronic Journal of Statistics, Journal of Machine Learning Research, IEEE Transactions on Information Theory, BMC Medical Research Methodology and International Journal of Medical Informatics.
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.