Bernard Haasdonk
- Statistical and Nonlinear Physics top 0.5%
- Computational Mechanics top 1%
- Statistics, Probability and Uncertainty top 0.5%
- Computer Vision and Pattern Recognition top 2%
- Numerical Analysis top 2%
- Co-authors
- Mario OhlbergerH. BürkhardtClaus BahlmannElżbieta PękalskaGabriele SantinDaniel KeysersHans BurkhardtGianluigi Rozza
- Topics
- Model Reduction and Neural Networks (56 papers)Numerical methods for differential equations (27 papers)Advanced Numerical Methods in Computational Mathematics (22 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceBioresource TechnologyThe Journal of Physical Chemistry A
- Partner nations
- GermanyItalyUnited States
In The Last Decade
Bernard Haasdonk
88 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 121
- Statistical and Nonlinear Physics 1.0k
- Computational Mechanics 705
- Statistics, Probability and Uncertainty 430
- Computer Vision and Pattern Recognition 365
- Numerical Analysis 364
Countries citing papers authored by Bernard Haasdonk
This map shows the geographic impact of Bernard Haasdonk'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 Bernard Haasdonk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernard Haasdonk more than expected).
Fields of papers citing papers by Bernard Haasdonk
This network shows the impact of papers produced by Bernard Haasdonk. 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 Bernard Haasdonk. The network helps show where Bernard Haasdonk may publish in the future.
Co-authorship network of co-authors of Bernard Haasdonk
This figure shows the co-authorship network connecting the top 25 collaborators of Bernard Haasdonk. A scholar is included among the top collaborators of Bernard Haasdonk 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 Bernard Haasdonk. Bernard Haasdonk is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 15 | |
| 6 | 0 | |
| 7 | 6 | |
| 8 | 22 | |
| 9 | 2 | |
| 10 | 5 | |
| 11 | 6 | |
| 12 | Interpolation with uncoupled separable matrix-valued kernels | 4 |
| 13 | 13 | |
| 14 | 7 | |
| 15 | A Vectorial Kernel Orthogonal Greedy Algorithm | 22 |
| 16 | 6 | |
| 17 | Effiziente und gesicherte Modellreduktion für parametrisierte dynamische Systeme (Efficient and Certified Model Reduction for Parametrized Dynamical Systems). | 1 |
| 18 | 67 | |
| 19 | Using transformation knowledge for the classification of Raman spectra of biological samples | 7 |
| 20 | 200 |
About Bernard Haasdonk
Bernard Haasdonk is a scholar working on Numerical Analysis, Statistical and Nonlinear Physics and Statistics, Probability and Uncertainty, having authored 92 papers that have together received 2.0k indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (56 papers), Numerical methods for differential equations (27 papers) and Advanced Numerical Methods in Computational Mathematics (22 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.0k citations), Numerical Analysis (364 citations) and Statistics, Probability and Uncertainty (430 citations). Bernard Haasdonk has collaborated with scholars based in Germany, Italy and United States. Frequent co-authors include Mario Ohlberger, H. Bürkhardt, Claus Bahlmann, Elżbieta Pękalska, Gabriele Santin, Daniel Keysers, Hans Burkhardt, Gianluigi Rozza, David Amsallem and D. C. Sorensen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Bioresource Technology and The Journal of Physical Chemistry A.
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.