Benjamin Unger
Impact in
- Numerical Analysis top 5%
- Numerical methods for differential equations
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- Model Reduction and Neural Networks
Papers in
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- Model Reduction and Neural Networks 20
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- Control and Stability of Dynamical Systems 6
- Control Systems and Identification 4
- Co-authors
- Philipp Schulze (7 shared papers)Volker Mehrmann (1 shared paper)Serkan Gugercin (3 shared papers)Jörg Fehr (1 shared paper)Christopher Beattie (1 shared paper)Tobias Breiten (1 shared paper)Robert Altmann (3 shared papers)Stephan Trenn (1 shared paper)
- Journals
- SIAM Journal on Control and Optimization (2 papers)Advances in Computational Mathematics (2 papers)Electronic Journal of Linear Algebra (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)BIT Numerical Mathematics (1 paper)
- Partner nations
- GermanyUnited StatesNetherlands
In The Last Decade
Benjamin Unger
22 papers receiving 268 citations
Peers
Comparison fields: 5 of 40
- Numerical Analysis 92
- Statistical and Nonlinear Physics 187
- Statistics, Probability and Uncertainty 47
- Control and Systems Engineering 130
- Computational Mathematics 2
Countries citing papers authored by Benjamin Unger
This map shows the geographic impact of Benjamin Unger'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 Benjamin Unger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Unger more than expected).
Fields of papers citing papers by Benjamin Unger
This network shows the impact of papers produced by Benjamin Unger. 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 Benjamin Unger. The network helps show where Benjamin Unger may publish in the future.
Co-authors
The 12 scholars most cited alongside Benjamin Unger, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 44 | |
| 2 | 2022 | 40 | |
| 3 | 2017 | 37 | |
| 4 | 2016 | 28 | |
| 5 | 2020 | 25 | |
| 6 | 2019 | 22 | |
| 7 | 2022 | 15 | |
| 8 | 2023 | 10 | |
| 9 | 2018 | 10 | |
| 10 | 2022 | 9 | |
| 11 | 2018 | 9 | |
| 12 | 2021 | 8 | |
| 13 | 2024 | 4 | |
| 14 | 2019 | 4 | |
| 15 | 2021 | 3 | |
| 16 | 2024 | 3 | |
| 17 | 2021 | 2 | |
| 18 | 2022 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2024 | 1 |
About Benjamin Unger
Benjamin Unger is a scholar working on Statistical and Nonlinear Physics, Control and Systems Engineering, Numerical Analysis, Statistics, Probability and Uncertainty and Mechanics of Materials, having authored 24 papers that have together received 280 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (20 papers), Numerical methods for differential equations (8 papers), Control and Stability of Dynamical Systems (6 papers), Probabilistic and Robust Engineering Design (5 papers), Control Systems and Identification (4 papers), Numerical methods in engineering (3 papers), Nuclear reactor physics and engineering (2 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Numerical Analysis (92 citations), Statistical and Nonlinear Physics (187 citations), Statistics, Probability and Uncertainty (47 citations), Control and Systems Engineering (130 citations) and Computational Mathematics (2 citations). Benjamin Unger has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Philipp Schulze, Volker Mehrmann, Serkan Gugercin, Jörg Fehr, Christopher Beattie, Tobias Breiten, Robert Altmann, Stephan Trenn, Jan Heiland and Bernard Haasdonk. Their work appears in journals such as SIAM Journal on Control and Optimization, Advances in Computational Mathematics, Electronic Journal of Linear Algebra, IEEE Transactions on Neural Networks and Learning Systems and BIT Numerical Mathematics.
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.