Aurélien Bibaut
Impact in
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- Advanced Neural Network Applications
- Digital Imaging for Blood Diseases
- Artificial Intelligence top 10%
- AI in cancer detection
- Domain Adaptation and Few-Shot Learning
- Anomaly Detection Techniques and Applications
Papers in
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- Advanced Causal Inference Techniques 4
- Statistical Methods and Inference 2
- Statistical Methods in Clinical Trials 2
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- Advanced Bandit Algorithms Research 2
- Co-authors
- Mark van der Laan (1 shared paper)Cheng Ju (1 shared paper)Mark J. van der Laan (2 shared papers)Nikos Vlassis (2 shared papers)Lazarus Juziwelo (1 shared paper)Aboulaye Meïté (1 shared paper)Ricardo Andrade-Pacheco (1 shared paper)Hugh J. W. Sturrock (1 shared paper)
- Journals
- Scientific Reports (1 paper)Annual Review of Statistics and Its Application (1 paper)Journal of Applied Statistics (1 paper)Computational Statistics (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesIvory CoastFrance
In The Last Decade
Aurélien Bibaut
6 papers receiving 279 citations
Peers
Comparison fields: 5 of 107
- Computer Vision and Pattern Recognition 69
- Artificial Intelligence 107
- Radiology, Nuclear Medicine and Imaging 59
- Health Informatics 3
- Media Technology 19
Countries citing papers authored by Aurélien Bibaut
This map shows the geographic impact of Aurélien Bibaut'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 Aurélien Bibaut with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aurélien Bibaut more than expected).
Fields of papers citing papers by Aurélien Bibaut
This network shows the impact of papers produced by Aurélien Bibaut. 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 Aurélien Bibaut. The network helps show where Aurélien Bibaut may publish in the future.
Co-authors
The 15 scholars most cited alongside Aurélien Bibaut, 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 | 2018 | 252 | |
| 2 | 2020 | 20 | |
| 3 | On the Design of Estimators for Bandit Off-Policy Evaluation | 2019 | 7 |
| 4 | 2019 | 4 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2025 | 0 |
About Aurélien Bibaut
Aurélien Bibaut is a scholar working on Statistics and Probability, Management Science and Operations Research, Computer Networks and Communications, Computer Vision and Pattern Recognition and Epidemiology, having authored 7 papers that have together received 285 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (4 papers), Statistical Methods and Inference (2 papers), Advanced Bandit Algorithms Research (2 papers), Statistical Methods in Clinical Trials (2 papers), Zoonotic diseases and public health (1 paper), Distributed Sensor Networks and Detection Algorithms (1 paper), Machine Learning and Data Classification (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (69 citations), Artificial Intelligence (107 citations), Radiology, Nuclear Medicine and Imaging (59 citations), Health Informatics (3 citations) and Media Technology (19 citations). Aurélien Bibaut has collaborated with scholars based in United States, Ivory Coast and France. Frequent co-authors include Mark van der Laan, Cheng Ju, Mark J. van der Laan, Nikos Vlassis, Lazarus Juziwelo, Aboulaye Meïté, Ricardo Andrade-Pacheco, Hugh J. W. Sturrock, Benjamin F. Arnold and Jean Frantz Lemoine. Their work appears in journals such as Scientific Reports, Annual Review of Statistics and Its Application, Journal of Applied Statistics, Computational Statistics and arXiv (Cornell University).
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.