Andreas Langer
- Computer Vision and Pattern Recognition top 10%
- Computational Mechanics top 10%
- Mathematical Physics top 10%
- Media Technology top 10%
- Geometry and Topology top 10%
- Co-authors
- Michael HintermüllerCarola‐Bibiane SchönliebMassimo FornasierThomas ZinkCarlos N. RautenbergTao WuStanley OsherYunho Kim
- Topics
- Sparse and Compressive Sensing Techniques (10 papers)Image and Signal Denoising Methods (10 papers)Numerical methods in inverse problems (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaSIAM Journal on Numerical AnalysisNumerische Mathematik
- Partner nations
- GermanyAustriaUnited Kingdom
In The Last Decade
Andreas Langer
19 papers receiving 209 citations
Peers
Comparison fields: 5 of 44
- Computer Vision and Pattern Recognition 124
- Computational Mechanics 116
- Mathematical Physics 68
- Media Technology 30
- Geometry and Topology 26
Countries citing papers authored by Andreas Langer
This map shows the geographic impact of Andreas Langer'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 Andreas Langer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Langer more than expected).
Fields of papers citing papers by Andreas Langer
This network shows the impact of papers produced by Andreas Langer. 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 Andreas Langer. The network helps show where Andreas Langer may publish in the future.
Co-authorship network of co-authors of Andreas Langer
This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Langer. A scholar is included among the top collaborators of Andreas Langer 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 Andreas Langer. Andreas Langer 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 | 6 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 10 | |
| 6 | 4 | |
| 7 | Adaptive regularization for image reconstruction from subsampled data | 1 |
| 8 | 17 | |
| 9 | Optimal selection of the regularization function in a generalized total variation model. Part II: Algorithm, its analysis and numerical tests | 1 |
| 10 | 5 | |
| 11 | 3 | |
| 12 | 14 | |
| 13 | 15 | |
| 14 | 39 | |
| 15 | 11 | |
| 16 | 12 | |
| 17 | 26 | |
| 18 | Domain decomposition methods for compressed sensing | 4 |
| 19 | 1 | |
| 20 | 26 |
About Andreas Langer
Andreas Langer is a scholar working on Mathematical Physics, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 21 papers that have together received 229 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (10 papers), Image and Signal Denoising Methods (10 papers) and Numerical methods in inverse problems (6 papers). The work is most often cited by research in Mathematical Physics (68 citations), Computer Vision and Pattern Recognition (124 citations) and Computational Mechanics (116 citations). Andreas Langer has collaborated with scholars based in Germany, Austria and United Kingdom. Frequent co-authors include Michael Hintermüller, Carola‐Bibiane Schönlieb, Massimo Fornasier, Thomas Zink, Carlos N. Rautenberg, Tao Wu, Stanley Osher, Yunho Kim, Thomas A. Klar and Jaroslaw Jacak. Their work appears in journals such as SHILAP Revista de lepidopterología, SIAM Journal on Numerical Analysis and Numerische Mathematik.
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.