Benjamin Négrevergne
- Conservation top 10%
- Information Systems top 10%
- Data Mining Algorithms and Applications 4
-
- Rough Sets and Fuzzy Logic 4
-
- Adversarial Robustness in Machine Learning 2
-
- Constraint Satisfaction and Optimization 1
- Advanced Database Systems and Queries 1
-
- Aesthetic Perception and Analysis 1
-
- Visual Attention and Saliency Detection 1
- Generative Adversarial Networks and Image Synthesis 1
- Co-authors
- Florian YgerAlexandre TermierMarie-Christine RoussetJean‐François MéhautTias GunsYann ChevaleyreAnton DriesSiegfried Nijssen
- Journals
- Data Mining and Knowledge Discovery (1 paper)Knowledge and Information Systems (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
In The Last Decade
Benjamin Négrevergne
8 papers receiving 137 citations
Peers
Comparison fields: 5 of 44
- Conservation 11
- Signal Processing 28
- Computer Graphics and Computer-Aided Design 9
- Information Systems 58
- Computational Theory and Mathematics 40
Countries citing papers authored by Benjamin Négrevergne
This map shows the geographic impact of Benjamin Négrevergne'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 Négrevergne with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Négrevergne more than expected).
Fields of papers citing papers by Benjamin Négrevergne
This network shows the impact of papers produced by Benjamin Négrevergne. 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 Négrevergne. The network helps show where Benjamin Négrevergne may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Benjamin Négrevergne, 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 | 2024 | 6 | |
| 2 | 2021 | 1 | |
| 3 | 2020 | 10 | |
| 4 | Recognizing Art Style Automatically in Painting with Deep Learning | 2017 | 58 |
| 5 | On declarative modeling of structured pattern mining | 2016 | 1 |
| 6 | 2014 | 14 | |
| 7 | 2013 | 17 | |
| 8 | 2013 | 36 |
About Benjamin Négrevergne
Benjamin Négrevergne is a scholar working on Computational Theory and Mathematics, Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 8 papers that have together received 143 indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (4 papers), Data Mining Algorithms and Applications (4 papers), Adversarial Robustness in Machine Learning (2 papers), Constraint Satisfaction and Optimization (1 paper), Aesthetic Perception and Analysis (1 paper), Advanced Database Systems and Queries (1 paper), Visual Attention and Saliency Detection (1 paper) and Generative Adversarial Networks and Image Synthesis (1 paper). The work is most often cited by research in Conservation (11 citations), Signal Processing (28 citations), Computer Graphics and Computer-Aided Design (9 citations), Information Systems (58 citations) and Computational Theory and Mathematics (40 citations). Benjamin Négrevergne has collaborated with scholars based in France and Belgium. Frequent co-authors include Florian Yger, Alexandre Termier, Marie-Christine Rousset, Jean‐François Méhaut, Tias Guns, Yann Chevaleyre, Anton Dries, Siegfried Nijssen, Jamal Atif and Anne Laurent. Their work appears in journals such as Data Mining and Knowledge Discovery, Knowledge and Information Systems, Proceedings of the AAAI Conference on Artificial Intelligence, arXiv (Cornell University) and Base Institutionnelle de Recherche de l'université Paris-Dauphine (BIRD) (University Paris-Dauphine).
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.