Peter Maaß
Impact in
- Mathematical Physics top 1%
- Numerical methods in inverse problems
- Spectroscopy top 2%
- Mass Spectrometry Techniques and Applications
- Advanced Proteomics Techniques and Applications
Papers in
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- Numerical methods in inverse problems 35
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- Image and Signal Denoising Methods 32
- Co-authors
- Bangti Jin (10 shared papers)Simon Arridge (8 shared papers)Ozan Öktem (2 shared papers)Carola‐Bibiane Schönlieb (6 shared papers)Andreas Rieder (8 shared papers)Alfred Karl Louis (9 shared papers)Theodore Alexandrov (11 shared papers)Herbert Thiele (9 shared papers)
- Journals
- Inverse Problems (10 papers)Analytical Chemistry (3 papers)Advances in Computational Mathematics (3 papers)Bioinformatics (2 papers)European Journal of Cancer (2 papers)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Peter Maaß
131 papers receiving 3.5k citations
Peter Maaß's Hit Papers
Peers
Comparison fields: 5 of 170
- Mathematical Physics 637
- Spectroscopy 594
- Computational Mechanics 656
- Computer Vision and Pattern Recognition 657
- Applied Mathematics 300
Countries citing papers authored by Peter Maaß
This map shows the geographic impact of Peter Maaß'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 Peter Maaß with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Maaß more than expected).
Fields of papers citing papers by Peter Maaß
This network shows the impact of papers produced by Peter Maaß. 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 Peter Maaß. The network helps show where Peter Maaß may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Maaß, 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 144 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Solving inverse problems using data-driven models Hit paper breakdown → | 2019 | 434 |
| 2 | 2010 | 172 | |
| 3 | Wavelets: Theory and Applications | 1997 | 159 |
| 4 | 2012 | 118 | |
| 5 | 2012 | 111 | |
| 6 | 2011 | 102 | |
| 7 | 2008 | 102 | |
| 8 | 2008 | 89 | |
| 9 | 2012 | 84 | |
| 10 | 2007 | 83 | |
| 11 | 1999 | 81 | |
| 12 | 2008 | 74 | |
| 13 | 2011 | 73 | |
| 14 | 2013 | 66 | |
| 15 | 1992 | 61 | |
| 16 | 2015 | 58 | |
| 17 | 2009 | 57 | |
| 18 | 2003 | 57 | |
| 19 | 2012 | 56 | |
| 20 | 2010 | 53 |
About Peter Maaß
Peter Maaß is a scholar working on Mathematical Physics, Computer Vision and Pattern Recognition, Applied Mathematics, Geophysics and Computational Mechanics, having authored 144 papers that have together received 3.7k indexed citations. Recurring topics across this work include Numerical methods in inverse problems (35 papers), Image and Signal Denoising Methods (32 papers), Sparse and Compressive Sensing Techniques (15 papers), Mass Spectrometry Techniques and Applications (14 papers), Electrical and Bioimpedance Tomography (13 papers), Medical Imaging Techniques and Applications (13 papers), Advanced Proteomics Techniques and Applications (11 papers) and Photoacoustic and Ultrasonic Imaging (11 papers). The work is most often cited by research in Mathematical Physics (637 citations), Spectroscopy (594 citations), Computational Mechanics (656 citations), Computer Vision and Pattern Recognition (657 citations) and Applied Mathematics (300 citations). Peter Maaß has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Bangti Jin, Simon Arridge, Ozan Öktem, Carola‐Bibiane Schönlieb, Andreas Rieder, Alfred Karl Louis, Theodore Alexandrov, Herbert Thiele, Hamid Reza Karimi and Dirk A. Lorenz. Their work appears in journals such as Inverse Problems, Analytical Chemistry, Advances in Computational Mathematics, Bioinformatics and European Journal of Cancer.
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.