Ulrike Baur
- Statistical and Nonlinear Physics top 2%
- Numerical Analysis top 5%
- Statistics, Probability and Uncertainty top 1%
- Control and Systems Engineering top 5%
- Computational Theory and Mathematics top 5%
- Co-authors
- Peter BennerLihong FengChristopher BeattieSerkan GugercinEdda KlippWolfram LiebermeisterAndreas GreinerJan G. Korvink
- Topics
- Model Reduction and Neural Networks (11 papers)Probabilistic and Robust Engineering Design (4 papers)Numerical methods for differential equations (3 papers)
- Journals
- FEBS JournalSIAM Journal on Scientific ComputingJournal of Computational and Applied Mathematics
- Partner nations
- GermanyUnited StatesAzerbaijan
In The Last Decade
Ulrike Baur
13 papers receiving 580 citations
Peers
Comparison fields: 5 of 62
- Statistical and Nonlinear Physics 439
- Numerical Analysis 185
- Statistics, Probability and Uncertainty 181
- Control and Systems Engineering 167
- Computational Theory and Mathematics 111
Countries citing papers authored by Ulrike Baur
This map shows the geographic impact of Ulrike Baur'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 Ulrike Baur with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ulrike Baur more than expected).
Fields of papers citing papers by Ulrike Baur
This network shows the impact of papers produced by Ulrike Baur. 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 Ulrike Baur. The network helps show where Ulrike Baur may publish in the future.
Co-authorship network of co-authors of Ulrike Baur
This figure shows the co-authorship network connecting the top 25 collaborators of Ulrike Baur. A scholar is included among the top collaborators of Ulrike Baur 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 Ulrike Baur. Ulrike Baur is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 202 | |
| 3 | 8 | |
| 4 | 38 | |
| 5 | 140 | |
| 6 | Parametric Model Reduction | 0 |
| 7 | 43 | |
| 8 | Cross-Gramian Based Model Reduction for Data-Sparse Systems | 47 |
| 9 | 24 | |
| 10 | 16 | |
| 11 | Parametric Model Reduction with Sparse Grids | 0 |
| 12 | Parametrische Modellreduktion mit d¨ unnen Gittern | 2 |
| 13 | 35 | |
| 14 | 44 | |
| 15 | 4 |
About Ulrike Baur
Ulrike Baur is a scholar working on Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty and Numerical Analysis, having authored 15 papers that have together received 611 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (11 papers), Probabilistic and Robust Engineering Design (4 papers) and Numerical methods for differential equations (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (439 citations), Numerical Analysis (185 citations) and Computational Mathematics (16 citations). Ulrike Baur has collaborated with scholars based in Germany, United States and Azerbaijan. Frequent co-authors include Peter Benner, Lihong Feng, Christopher Beattie, Serkan Gugercin, Edda Klipp, Wolfram Liebermeister, Andreas Greiner, Jan G. Korvink and Tobias Breiten. Their work appears in journals such as FEBS Journal, SIAM Journal on Scientific Computing and Journal of Computational and Applied 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.