Benjamin Guedj
Impact in
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- Statistical Methods and Inference
Papers in
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- Machine Learning and Algorithms 6
- Machine Learning and Data Classification 3
- Bayesian Modeling and Causal Inference 2
- Data Stream Mining Techniques 2
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- Forecasting Techniques and Applications 2
- Co-authors
- G. Guillot (1 shared paper)Pierre Alquier (2 shared papers)Shi Zhou (2 shared papers)Alexandre Vignot (1 shared paper)Gérard Biau (1 shared paper)James D. Malley (1 shared paper)Pierre Latouche (1 shared paper)Fredrik Hellström (1 shared paper)
- Journals
- Machine Learning (2 papers)Physical review. E (1 paper)Molecular Ecology Resources (1 paper)Applied Network Science (1 paper)Bioresource Technology (1 paper)
- Partner nations
- FranceUnited KingdomCanada
In The Last Decade
Benjamin Guedj
18 papers receiving 117 citations
Peers
Comparison fields: 5 of 59
- Statistics and Probability 14
- Computational Mathematics 1
- Human-Computer Interaction 9
- Artificial Intelligence 42
- Statistical and Nonlinear Physics 14
Countries citing papers authored by Benjamin Guedj
This map shows the geographic impact of Benjamin Guedj'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 Benjamin Guedj with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Guedj more than expected).
Fields of papers citing papers by Benjamin Guedj
This network shows the impact of papers produced by Benjamin Guedj. 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 Benjamin Guedj. The network helps show where Benjamin Guedj may publish in the future.
Co-authors
The 21 scholars most cited alongside Benjamin Guedj, 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 | 2011 | 25 | |
| 2 | 2017 | 13 | |
| 3 | 2021 | 12 | |
| 4 | 2007 | 12 | |
| 5 | 2015 | 11 | |
| 6 | 2022 | 7 | |
| 7 | 2015 | 6 | |
| 8 | 2021 | 5 | |
| 9 | An Oracle Inequality for Quasi-Bayesian Non-Negative Matrix Factorization | 2017 | 5 |
| 10 | 2025 | 5 | |
| 11 | 2024 | 4 | |
| 12 | 2020 | 3 | |
| 13 | A Quasi-Bayesian Perspective to Online Clustering | 2016 | 3 |
| 14 | 2021 | 2 | |
| 15 | 2017 | 2 | |
| 16 | 2023 | 1 | |
| 17 | 2022 | 1 | |
| 18 | 2023 | 1 | |
| 19 | 2024 | 0 | |
| 20 | 2022 | 0 |
About Benjamin Guedj
Benjamin Guedj is a scholar working on Artificial Intelligence, Management Science and Operations Research, Statistics and Probability, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 20 papers that have together received 118 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (6 papers), Statistical Methods and Inference (3 papers), Machine Learning and Data Classification (3 papers), Face and Expression Recognition (2 papers), Sparse and Compressive Sensing Techniques (2 papers), Forecasting Techniques and Applications (2 papers), Bayesian Modeling and Causal Inference (2 papers) and Data Stream Mining Techniques (2 papers). The work is most often cited by research in Statistics and Probability (14 citations), Computational Mathematics (1 citation), Human-Computer Interaction (9 citations), Artificial Intelligence (42 citations) and Statistical and Nonlinear Physics (14 citations). Benjamin Guedj has collaborated with scholars based in France, United Kingdom and Canada. Frequent co-authors include G. Guillot, Pierre Alquier, Shi Zhou, Alexandre Vignot, Gérard Biau, James D. Malley, Pierre Latouche, Fredrik Hellström, Maxim Raginsky and ChopinNicolas. Their work appears in journals such as Machine Learning, Physical review. E, Molecular Ecology Resources, Applied Network Science and Bioresource Technology.
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.