Paul Breiding
Impact in
- Computational Mathematics top 1%
- Tensor decomposition and applications
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- Matrix Theory and Algorithms
- Polynomial and algebraic computation
Papers in
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- Polynomial and algebraic computation 7
- Matrix Theory and Algorithms 3
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- Tensor decomposition and applications 10
- Co-authors
- Nick Vannieuwenhoven (10 shared papers)Mateusz Michałek (2 shared papers)Oded Zilberberg (1 shared paper)Carlos Beltrán (1 shared paper)Bernd Sturmfels (2 shared papers)Javier del Pino (1 shared paper)Peter Bürgisser (1 shared paper)
In The Last Decade
Paul Breiding
24 papers receiving 146 citations
Peers
Comparison fields: 5 of 33
- Computational Mathematics 96
- Computational Theory and Mathematics 61
- Computational Mechanics 53
- Numerical Analysis 13
- Statistical and Nonlinear Physics 26
Countries citing papers authored by Paul Breiding
This map shows the geographic impact of Paul Breiding'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 Paul Breiding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Breiding more than expected).
Fields of papers citing papers by Paul Breiding
This network shows the impact of papers produced by Paul Breiding. 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 Paul Breiding. The network helps show where Paul Breiding may publish in the future.
Co-authors
The 7 scholars most cited alongside Paul Breiding, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Riemannian trust region method for the canonical tensor rank approximation problem | 2018 | 27 |
| 2 | 2018 | 27 | |
| 3 | 2023 | 13 | |
| 4 | 2017 | 11 | |
| 5 | 2017 | 11 | |
| 6 | 2021 | 10 | |
| 7 | 2019 | 9 | |
| 8 | 2018 | 8 | |
| 9 | 2023 | 7 | |
| 10 | 2023 | 5 | |
| 11 | 2023 | 4 | |
| 12 | 2022 | 4 | |
| 13 | 2024 | 3 | |
| 14 | 2023 | 3 | |
| 15 | 2023 | 2 | |
| 16 | 2019 | 2 | |
| 17 | 2024 | 2 | |
| 18 | 2023 | 1 | |
| 19 | The average number of critical rank-one-approximations to a symmetric tensor | 2017 | 1 |
| 20 | 2022 | 1 |
About Paul Breiding
Paul Breiding is a scholar working on Computational Theory and Mathematics, Computational Mathematics, Computational Mechanics, Geometry and Topology and Radiology, Nuclear Medicine and Imaging, having authored 26 papers that have together received 156 indexed citations. Recurring topics across this work include Tensor decomposition and applications (10 papers), Polynomial and algebraic computation (7 papers), Advanced Numerical Analysis Techniques (6 papers), Sparse and Compressive Sensing Techniques (4 papers), Advanced Optimization Algorithms Research (3 papers), Matrix Theory and Algorithms (3 papers), Point processes and geometric inequalities (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Computational Mathematics (96 citations), Computational Theory and Mathematics (61 citations), Computational Mechanics (53 citations), Numerical Analysis (13 citations) and Statistical and Nonlinear Physics (26 citations). Paul Breiding has collaborated with scholars based in Germany, Belgium and Sweden. Frequent co-authors include Nick Vannieuwenhoven, Mateusz Michałek, Oded Zilberberg, Carlos Beltrán, Bernd Sturmfels, Javier del Pino and Peter Bürgisser. Their work appears in journals such as SIAM Journal on Optimization, IMA Journal of Numerical Analysis, Applied and Computational Harmonic Analysis, ACM Transactions on Mathematical Software and Journal de Mathématiques Pures et Appliquées.
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.