Aurélien Larcher
Impact in
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- Model Reduction and Neural Networks
- Computational Mechanics top 5%
- Computational Fluid Dynamics and Aerodynamics
- Fluid Dynamics and Vibration Analysis
- Fluid Dynamics and Turbulent Flows
- Advanced Numerical Methods in Computational Mathematics
Papers in
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- Advanced Numerical Methods in Computational Mathematics 7
- Computational Fluid Dynamics and Aerodynamics 5
- Fluid Dynamics and Heat Transfer 3
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- Model Reduction and Neural Networks 9
- Co-authors
- Elie Hachem (20 shared papers)Jonathan Viquerat (10 shared papers)Jean Rabault (2 shared papers)Alexander Kuhnle (2 shared papers)Hassan Ghraieb (5 shared papers)Philippe Méliga (8 shared papers)Murtazo Nazarov (1 shared paper)Rudy Valette (4 shared papers)
In The Last Decade
Aurélien Larcher
25 papers receiving 784 citations
Aurélien Larcher's Hit Papers
Peers
Comparison fields: 5 of 55
- Statistical and Nonlinear Physics 263
- Computational Mechanics 299
- Aerospace Engineering 179
- Artificial Intelligence 153
- Computational Theory and Mathematics 55
Countries citing papers authored by Aurélien Larcher
This map shows the geographic impact of Aurélien Larcher'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 Larcher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aurélien Larcher more than expected).
Fields of papers citing papers by Aurélien Larcher
This network shows the impact of papers produced by Aurélien Larcher. 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 Larcher. The network helps show where Aurélien Larcher may publish in the future.
Co-authors
The 25 scholars most cited alongside Aurélien Larcher, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A review on deep reinforcement learning for fluid mechanics Hit paper breakdown → | 2021 | 212 |
| 2 | 2020 | 185 | |
| 3 | 2022 | 84 | |
| 4 | 2021 | 60 | |
| 5 | 2021 | 42 | |
| 6 | 2016 | 28 | |
| 7 | 2020 | 24 | |
| 8 | 2019 | 22 | |
| 9 | 2019 | 22 | |
| 10 | 2022 | 17 | |
| 11 | 2019 | 13 | |
| 12 | 2021 | 13 | |
| 13 | 2021 | 13 | |
| 14 | 2023 | 13 | |
| 15 | 2022 | 11 | |
| 16 | 2024 | 8 | |
| 17 | 2023 | 6 | |
| 18 | 2011 | 5 | |
| 19 | 2017 | 5 | |
| 20 | 2022 | 5 |
About Aurélien Larcher
Aurélien Larcher is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics, Neurology, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 25 papers that have together received 804 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (9 papers), Advanced Numerical Methods in Computational Mathematics (7 papers), Computational Fluid Dynamics and Aerodynamics (5 papers), Reinforcement Learning in Robotics (4 papers), Intracranial Aneurysms: Treatment and Complications (3 papers), Fluid Dynamics and Heat Transfer (3 papers), Plasma and Flow Control in Aerodynamics (2 papers) and Advanced Multi-Objective Optimization Algorithms (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (263 citations), Computational Mechanics (299 citations), Aerospace Engineering (179 citations), Artificial Intelligence (153 citations) and Computational Theory and Mathematics (55 citations). Aurélien Larcher has collaborated with scholars based in France, Norway and Germany. Frequent co-authors include Elie Hachem, Jonathan Viquerat, Jean Rabault, Alexander Kuhnle, Hassan Ghraieb, Philippe Méliga, Murtazo Nazarov, Rudy Valette, Anselmo Soeiro Pereira and Thierry Coupez. Their work appears in journals such as Computers & Fluids, Physics of Fluids, Computer Methods in Applied Mechanics and Engineering, Journal of Computational Physics and Journal of Non-Newtonian Fluid Mechanics.
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.