Jonathan Viquerat

1.0k citations
33 papers · 640 indexed · 1 hit paper · h-index 13
Topics
Model Reduction and Neural Networks (14 papers)Fluid Dynamics and Turbulent Flows (11 papers)Electromagnetic Simulation and Numerical Methods (11 papers)
Journals
SHILAP Revista de lepidopterologíaScientific ReportsJournal of Computational Physics
Partner nations
FranceGermanyChina

In The Last Decade

Jonathan Viquerat

30 papers receiving 625 citations

Hit Papers

A review on deep reinforcement learning for fluid mechanics2021202620222024202150100150

Peers

Jonathan Viquerat
Comparison fields: 5 of 72
  • Computational Mechanics 357
  • Statistical and Nonlinear Physics 303
  • Aerospace Engineering 141
  • Electrical and Electronic Engineering 97
  • Mechanical Engineering 78
Replace Pao‐Hsiung Chiu with:
Pao‐Hsiung Chiu Singapore
Nathaniel Trask United States
Xinshuai Zhang China
Hanwen Wang China
Youngkyu Kim United States
Michel Speetjens Netherlands
Philippe Méliga France
Chengping Rao United States
Jonathan Viquerat relative to Pao‐Hsiung Chiu Singapore Pao‐Hsiung Chiu's profile →
Citations per field
00.5×1.5×
Pao‐Hsiung Chiu · 1×
Citations per year

Countries citing papers authored by Jonathan Viquerat

Since Specialization
Citations

This map shows the geographic impact of Jonathan Viquerat'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 Jonathan Viquerat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Viquerat more than expected).

Fields of papers citing papers by Jonathan Viquerat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Viquerat. 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 Jonathan Viquerat. The network helps show where Jonathan Viquerat may publish in the future.

Co-authorship network of co-authors of Jonathan Viquerat

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Viquerat. A scholar is included among the top collaborators of Jonathan Viquerat 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 Jonathan Viquerat. Jonathan Viquerat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 2
5 7
6 8
7 1
8 5
9 5
10 12
11 1
12 37
13 48
14 51
15 1
16 2
17 6
18 15
19 13
20 1

About Jonathan Viquerat

Jonathan Viquerat is a scholar working on Computational Mathematics, Statistical and Nonlinear Physics and Computational Mechanics, having authored 33 papers that have together received 640 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (14 papers), Fluid Dynamics and Turbulent Flows (11 papers) and Electromagnetic Simulation and Numerical Methods (11 papers). The work is most often cited by research in Statistical and Nonlinear Physics (303 citations), Computational Mechanics (357 citations) and Aerospace Engineering (141 citations). Jonathan Viquerat has collaborated with scholars based in France, Germany and China. Frequent co-authors include Elie Hachem, Aurélien Larcher, Jean Rabault, Alexander Kuhnle, Philippe Méliga, Stéphane Lanteri, Zhizhao Che, A. Moreau, Stéphane Descombes and Thomas Liebig. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Computational Physics.

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.

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