Paul Breiding
- Computational Mathematics top 1%
- Computational Theory and Mathematics top 10%
- Computational Mechanics
- Statistical and Nonlinear Physics
- Artificial Intelligence
- Co-authors
- Nick VannieuwenhovenBernd SturmfelsMateusz MichałekCarlos BeltránOded ZilberbergJavier del PinoPeter Bürgisser
- Topics
- Tensor decomposition and applications (10 papers)Polynomial and algebraic computation (8 papers)Advanced Numerical Analysis Techniques (7 papers)
In The Last Decade
Paul Breiding
25 papers receiving 145 citations
Peers
Comparison fields: 5 of 37
- Computational Mathematics 93
- Computational Theory and Mathematics 61
- Computational Mechanics 52
- Statistical and Nonlinear Physics 24
- Artificial Intelligence 23
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-authorship network of co-authors of Paul Breiding
This figure shows the co-authorship network connecting the top 25 collaborators of Paul Breiding. A scholar is included among the top collaborators of Paul Breiding 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 Paul Breiding. Paul Breiding 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 | 3 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | 2 | |
| 9 | 5 | |
| 10 | 12 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 7 | |
| 14 | 9 | |
| 15 | HomotopyContinuation.jl - a package for solving systems of polynomial equations in Julia | 1 |
| 16 | 26 | |
| 17 | A Riemannian trust region method for the canonical tensor rank approximation problem | 26 |
| 18 | 11 | |
| 19 | The average number of critical rank-one-approximations to a symmetric tensor | 1 |
| 20 | 11 |
About Paul Breiding
Paul Breiding is a scholar working on Computational Mathematics, Computational Theory and Mathematics and Discrete Mathematics and Combinatorics, having authored 27 papers that have together received 157 indexed citations. Recurring topics across this work include Tensor decomposition and applications (10 papers), Polynomial and algebraic computation (8 papers) and Advanced Numerical Analysis Techniques (7 papers). The work is most often cited by research in Computational Mathematics (93 citations), Computational Theory and Mathematics (61 citations) and Computational Mechanics (52 citations). Paul Breiding has collaborated with scholars based in Germany, Belgium and Sweden. Frequent co-authors include Nick Vannieuwenhoven, Bernd Sturmfels, Mateusz Michałek, Carlos Beltrán, Oded Zilberberg, Javier del Pino and Peter Bürgisser. Their work appears in journals such as Transactions of the American Mathematical Society, Numerische Mathematik and Advances in 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.