Miroslav Kuchta

1.2k citations
22 papers · 727 indexed · 2 hit papers · h-index 11
Topics
Advanced Numerical Methods in Computational Mathematics (7 papers)Advanced Mathematical Modeling in Engineering (7 papers)Model Reduction and Neural Networks (5 papers)

In The Last Decade

Miroslav Kuchta

22 papers receiving 705 citations

Hit Papers

Artificial neural networks trained through deep reinforce...201920262021202320192023100200300

Peers

Miroslav Kuchta
Comparison fields: 5 of 84
  • Computational Mechanics 346
  • Statistical and Nonlinear Physics 275
  • Aerospace Engineering 133
  • Cellular and Molecular Neuroscience 107
  • Mechanical Engineering 61
Replace L. Marple with:
L. Marple United States
Fuqiang Wu China
Georg May Germany
Laiping Zhang China
Mathieu Galtier France
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J.G. Harris United States
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Miroslav Kuchta relative to L. Marple United States L. Marple's profile →
Citations per field
00.5×10.6×
L. Marple · 1×
Citations per year

Countries citing papers authored by Miroslav Kuchta

Since Specialization
Citations

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

Fields of papers citing papers by Miroslav Kuchta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miroslav Kuchta

This figure shows the co-authorship network connecting the top 25 collaborators of Miroslav Kuchta. A scholar is included among the top collaborators of Miroslav Kuchta 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 Miroslav Kuchta. Miroslav Kuchta 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
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5 7
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Sleep cycle-dependent vascular dynamics in male mice and the predicted effects on perivascular cerebrospinal fluid flow and solute transportbreakdown →
82
7 1
8 31
9 5
10 17
11 5
12 77
13 19
14
Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow controlbreakdown →
347
15
An Artificial Neural Network trained through Deep Reinforcement Learning achieves Active Flow Control of the 2D Karman Vortex Street behind a Cylinder at moderate Reynolds number
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16 11
17 11
18 21
19 64
20 5

About Miroslav Kuchta

Miroslav Kuchta is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics and Computational Theory and Mathematics, having authored 22 papers that have together received 727 indexed citations. Recurring topics across this work include Advanced Numerical Methods in Computational Mathematics (7 papers), Advanced Mathematical Modeling in Engineering (7 papers) and Model Reduction and Neural Networks (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (275 citations), Computational Mechanics (346 citations) and Cellular and Molecular Neuroscience (107 citations). Miroslav Kuchta has collaborated with scholars based in Norway, United States and Germany. Frequent co-authors include Atle Jensen, Jean Rabault, Nicolas Cerardi, Kent‐André Mardal, Simon W. Funke, Karoline Horgmo Jæger, Aslak Tveito, Marie E. Rognes, Mikael Mortensen and Céline Cunen. Their work appears in journals such as Nature Communications, PLoS ONE and Journal of 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.

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