Philipp Petersen
Impact in
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- Model Reduction and Neural Networks
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- Advanced Vision and Imaging
- Image and Signal Denoising Methods
- Advanced Image and Video Retrieval Techniques
Papers in
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- Neural Networks and Applications 8
- Machine Learning and ELM 2
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- Model Reduction and Neural Networks 6
- Co-authors
- Ganesh Sundaramoorthi (1 shared paper)Stefano Soatto (1 shared paper)V. S. Varadarajan (1 shared paper)Felix Voigtlaender (4 shared papers)Gitta Kutyniok (3 shared papers)Christoph Schwab (2 shared papers)Holger Boche (1 shared paper)Robert Calderbank (1 shared paper)
- Journals
- Analysis and Applications (3 papers)Applied and Computational Harmonic Analysis (2 papers)The Annals of Applied Probability (1 paper)Advances in Computational Mathematics (1 paper)Foundations of Computational Mathematics (1 paper)
- Partner nations
- AustriaGermanyUnited Kingdom
In The Last Decade
Philipp Petersen
15 papers receiving 89 citations
Peers
Comparison fields: 5 of 52
- Statistical and Nonlinear Physics 25
- Computer Vision and Pattern Recognition 30
- Computer Graphics and Computer-Aided Design 4
- Acoustics and Ultrasonics 1
- Computational Mechanics 21
Countries citing papers authored by Philipp Petersen
This map shows the geographic impact of Philipp Petersen'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 Philipp Petersen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philipp Petersen more than expected).
Fields of papers citing papers by Philipp Petersen
This network shows the impact of papers produced by Philipp Petersen. 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 Philipp Petersen. The network helps show where Philipp Petersen may publish in the future.
Co-authors
The 18 scholars most cited alongside Philipp Petersen, 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 | 2009 | 24 | |
| 2 | 2019 | 18 | |
| 3 | 2022 | 14 | |
| 4 | 2022 | 6 | |
| 5 | 2022 | 6 | |
| 6 | 2023 | 6 | |
| 7 | 2023 | 5 | |
| 8 | 2019 | 5 | |
| 9 | 2019 | 3 | |
| 10 | 2019 | 2 | |
| 11 | 2017 | 2 | |
| 12 | 2017 | 2 | |
| 13 | 2024 | 1 | |
| 14 | 2015 | 1 | |
| 15 | 2019 | 1 | |
| 16 | 2025 | 0 |
About Philipp Petersen
Philipp Petersen is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Computational Mechanics and Applied Mathematics, having authored 16 papers that have together received 96 indexed citations. Recurring topics across this work include Neural Networks and Applications (8 papers), Model Reduction and Neural Networks (6 papers), Image and Signal Denoising Methods (3 papers), Machine Learning in Materials Science (2 papers), Advanced Numerical Analysis Techniques (2 papers), Mathematical Analysis and Transform Methods (2 papers), Sparse and Compressive Sensing Techniques (2 papers) and Machine Learning and ELM (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (25 citations), Computer Vision and Pattern Recognition (30 citations), Computer Graphics and Computer-Aided Design (4 citations), Acoustics and Ultrasonics (1 citation) and Computational Mechanics (21 citations). Philipp Petersen has collaborated with scholars based in Austria, Germany and United Kingdom. Frequent co-authors include Ganesh Sundaramoorthi, Stefano Soatto, V. S. Varadarajan, Felix Voigtlaender, Gitta Kutyniok, Christoph Schwab, Holger Boche, Robert Calderbank, Rudolf Mathar and Giuseppe Caire. Their work appears in journals such as Analysis and Applications, Applied and Computational Harmonic Analysis, The Annals of Applied Probability, Advances in Computational Mathematics and Foundations of Computational 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.