Masayuki Yano
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- Model Reduction and Neural Networks 23
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- Probabilistic and Robust Engineering Design 7
- Numerical Analysis top 5%
- Numerical methods for differential equations 10
- Computational Mechanics top 2%
- Advanced Numerical Methods in Computational Mathematics 18
- Computational Fluid Dynamics and Aerodynamics 8
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- Electromagnetic Simulation and Numerical Methods 6
- Plasma Diagnostics and Applications 4
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- Numerical methods in engineering 6
- Co-authors
- David DarmofalAnthony T. PateraYvon MadayMitchell L. R. WalkerA.T. PateraOlga MulaKarsten UrbanTommaso Taddei
- Journals
- SHILAP Revista de lepidopterología (1 paper)Journal of Computational Physics (3 papers)Computer Methods in Applied Mechanics and Engineering (10 papers)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
Masayuki Yano
42 papers receiving 705 citations
Peers
Comparison fields: 5 of 65
- Statistical and Nonlinear Physics 413
- Statistics, Probability and Uncertainty 183
- Numerical Analysis 112
- Computational Mechanics 404
- Computer Graphics and Computer-Aided Design 36
Countries citing papers authored by Masayuki Yano
This map shows the geographic impact of Masayuki Yano'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 Masayuki Yano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masayuki Yano more than expected).
Fields of papers citing papers by Masayuki Yano
This network shows the impact of papers produced by Masayuki Yano. 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 Masayuki Yano. The network helps show where Masayuki Yano may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Masayuki Yano, 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 | 2024 | 2 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 2 | |
| 4 | 2022 | 3 | |
| 5 | 2021 | 16 | |
| 6 | 2021 | 14 | |
| 7 | 2020 | 2 | |
| 8 | 2019 | 4 | |
| 9 | 2019 | 2 | |
| 10 | 2018 | 15 | |
| 11 | 2018 | 8 | |
| 12 | 2017 | 18 | |
| 13 | 2016 | 27 | |
| 14 | A SPACE-TIME CERTIFIED REDUCED BASIS METHOD FOR BURGERS' EQUATION | 2014 | 1 |
| 15 | 2014 | 50 | |
| 16 | 2013 | 9 | |
| 17 | On Dual-Weighted Residual Error Estimates for p-Dependent Discretizations | 2011 | 5 |
| 18 | 2010 | 2 | |
| 19 | 2009 | 7 | |
| 20 | 1984 | 7 |
About Masayuki Yano
Masayuki Yano is a scholar working on Statistical and Nonlinear Physics, Numerical Analysis and Computational Mechanics, having authored 45 papers that have together received 736 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (23 papers), Advanced Numerical Methods in Computational Mathematics (18 papers), Numerical methods for differential equations (10 papers), Computational Fluid Dynamics and Aerodynamics (8 papers), Probabilistic and Robust Engineering Design (7 papers), Electromagnetic Simulation and Numerical Methods (6 papers), Numerical methods in engineering (6 papers) and Plasma Diagnostics and Applications (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (413 citations), Statistics, Probability and Uncertainty (183 citations) and Numerical Analysis (112 citations). Masayuki Yano has collaborated with scholars based in United States, Canada and France. Frequent co-authors include David Darmofal, Anthony T. Patera, Yvon Maday, Mitchell L. R. Walker, A.T. Patera, Yvon Maday, Olga Mula, Karsten Urban, Tommaso Taddei and Matthew J. Zahr. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Computational Physics and Computer Methods in Applied Mechanics and Engineering.
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.