Gilles Wainrib
- Artificial Intelligence top 2%
- Cognitive Neuroscience top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Molecular Biology
- Cancer Research top 10%
- Co-authors
- Mathieu GaltierPierrick J. ArnalStanislas ChambonAlexandre GramfortThomas ClozelMikhail ZaslavskiyPierre CourtiolMatahi Moarii
- Topics
- stochastic dynamics and bifurcation (9 papers)Neural dynamics and brain function (8 papers)Advanced Thermodynamics and Statistical Mechanics (5 papers)
- Partner nations
- FranceBurundiUnited States
In The Last Decade
Gilles Wainrib
34 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Artificial Intelligence 558
- Cognitive Neuroscience 465
- Radiology, Nuclear Medicine and Imaging 454
- Molecular Biology 234
- Cancer Research 198
Countries citing papers authored by Gilles Wainrib
This map shows the geographic impact of Gilles Wainrib'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 Gilles Wainrib with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gilles Wainrib more than expected).
Fields of papers citing papers by Gilles Wainrib
This network shows the impact of papers produced by Gilles Wainrib. 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 Gilles Wainrib. The network helps show where Gilles Wainrib may publish in the future.
Co-authorship network of co-authors of Gilles Wainrib
This figure shows the co-authorship network connecting the top 25 collaborators of Gilles Wainrib. A scholar is included among the top collaborators of Gilles Wainrib 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 Gilles Wainrib. Gilles Wainrib is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 13 | |
| 3 | 57 | |
| 4 | 200 | |
| 5 | 14 | |
| 6 | Deep learning-based classification of mesothelioma improves prediction of patient outcomebreakdown → | 314 |
| 7 | 1 | |
| 8 | 47 | |
| 9 | A deep learning architecture for temporal sleep stage classification\n using multivariate and multimodal time seriesbreakdown → | 433 |
| 10 | 7 | |
| 11 | 8 | |
| 12 | 35 | |
| 13 | 1 | |
| 14 | The asymptotic performance of linear echo state neural networks | 3 |
| 15 | 1 | |
| 16 | 23 | |
| 17 | 74 | |
| 18 | 12 | |
| 19 | 14 | |
| 20 | 3 |
About Gilles Wainrib
Gilles Wainrib is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Discrete Mathematics and Combinatorics, having authored 35 papers that have together received 1.7k indexed citations. Recurring topics across this work include stochastic dynamics and bifurcation (9 papers), Neural dynamics and brain function (8 papers) and Advanced Thermodynamics and Statistical Mechanics (5 papers). The work is most often cited by research in Health Informatics (70 citations), Cognitive Neuroscience (465 citations) and Radiology, Nuclear Medicine and Imaging (454 citations). Gilles Wainrib has collaborated with scholars based in France, Burundi and United States. Frequent co-authors include Mathieu Galtier, Pierrick J. Arnal, Stanislas Chambon, Alexandre Gramfort, Thomas Clozel, Mikhail Zaslavskiy, Pierre Courtiol, Matahi Moarii, Elodie Pronier and Jonathan Touboul. Their work appears in journals such as Physical Review Letters, Nature Medicine and Nature Communications.
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.