Niklas Koep
Impact in
-
- Blind Source Separation Techniques
Papers in
-
- Sparse and Compressive Sensing Techniques 6
- Advanced Numerical Analysis Techniques 2
-
- Image and Signal Denoising Methods 4
- Co-authors
- Rudolf Mathar (7 shared papers)James T. Townsend (1 shared paper)Sebastian Weichwald (1 shared paper)Arash Behboodi (4 shared papers)Dirk Heberling (1 shared paper)Anke Schmeink (1 shared paper)Bernhard Kainz (1 shared paper)Benjamin Hou (1 shared paper)
- Journals
- Journal of Machine Learning Research (1 paper)Applied and Computational Harmonic Analysis (1 paper)IEEE Access (1 paper)Proceedings of the Python in Science Conferences (1 paper)Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) (1 paper)
- Partner nations
- GermanyUnited KingdomFrance
In The Last Decade
Niklas Koep
9 papers receiving 84 citations
Peers
Comparison fields: 5 of 42
- Computational Mathematics 2
- Signal Processing 13
- Computational Mechanics 24
- Numerical Analysis 6
- Aerospace Engineering 21
Countries citing papers authored by Niklas Koep
This map shows the geographic impact of Niklas Koep'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 Niklas Koep with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Niklas Koep more than expected).
Fields of papers citing papers by Niklas Koep
This network shows the impact of papers produced by Niklas Koep. 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 Niklas Koep. The network helps show where Niklas Koep may publish in the future.
Co-authors
The 13 scholars most cited alongside Niklas Koep, 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 | 2016 | 36 | |
| 2 | Pymanopt: a python toolbox for optimization on manifolds using automatic differentiation | 2016 | 33 |
| 3 | 2018 | 5 | |
| 4 | 2022 | 3 | |
| 5 | 2020 | 3 | |
| 6 | 2019 | 3 | |
| 7 | 2019 | 2 | |
| 8 | Binary Iterative Hard Thresholding for Frequency-Sparse Signal Recovery | 2017 | 1 |
| 9 | 2019 | 1 |
About Niklas Koep
Niklas Koep is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Applied Mathematics, Biomedical Engineering and Electrical and Electronic Engineering, having authored 9 papers that have together received 87 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (6 papers), Image and Signal Denoising Methods (4 papers), Photoacoustic and Ultrasonic Imaging (2 papers), Advanced Numerical Analysis Techniques (2 papers), Mathematical Analysis and Transform Methods (2 papers), Error Correcting Code Techniques (1 paper), Computational Physics and Python Applications (1 paper) and Advanced Wireless Communication Techniques (1 paper). The work is most often cited by research in Computational Mathematics (2 citations), Signal Processing (13 citations), Computational Mechanics (24 citations), Numerical Analysis (6 citations) and Aerospace Engineering (21 citations). Niklas Koep has collaborated with scholars based in Germany, United Kingdom and France. Frequent co-authors include Rudolf Mathar, James T. Townsend, Sebastian Weichwald, Arash Behboodi, Dirk Heberling, Anke Schmeink, Bernhard Kainz, Benjamin Hou, Susan Holmes and Nina Miolane. Their work appears in journals such as Journal of Machine Learning Research, Applied and Computational Harmonic Analysis, IEEE Access, Proceedings of the Python in Science Conferences and Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft).
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.