Tuomo Valkonen
- Computational Mechanics top 5%
- Computer Vision and Pattern Recognition top 5%
- Mathematical Physics top 10%
- Computational Theory and Mathematics top 10%
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Carola‐Bibiane SchönliebKristian BrediesFlorian KnöllJuan Carlos De los ReyesDirk A. LorenzJan LellmannKarl KunischMartin Benning
- Topics
- Sparse and Compressive Sensing Techniques (15 papers)Numerical methods in inverse problems (12 papers)Advanced Optimization Algorithms Research (9 papers)
- Journals
- Journal of Mathematical Analysis and ApplicationsSIAM Journal on Applied MathematicsNonlinear Analysis
- Partner nations
- FinlandUnited KingdomEcuador
In The Last Decade
Tuomo Valkonen
37 papers receiving 387 citations
Peers
Comparison fields: 5 of 60
- Computational Mechanics 196
- Computer Vision and Pattern Recognition 170
- Mathematical Physics 115
- Computational Theory and Mathematics 70
- Radiology, Nuclear Medicine and Imaging 66
Countries citing papers authored by Tuomo Valkonen
This map shows the geographic impact of Tuomo Valkonen'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 Tuomo Valkonen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tuomo Valkonen more than expected).
Fields of papers citing papers by Tuomo Valkonen
This network shows the impact of papers produced by Tuomo Valkonen. 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 Tuomo Valkonen. The network helps show where Tuomo Valkonen may publish in the future.
Co-authorship network of co-authors of Tuomo Valkonen
This figure shows the co-authorship network connecting the top 25 collaborators of Tuomo Valkonen. A scholar is included among the top collaborators of Tuomo Valkonen 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 Tuomo Valkonen. Tuomo Valkonen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 6 | |
| 6 | 6 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 9 | |
| 10 | 1 | |
| 11 | Preconditioned Proximal Point Methods and Notions of Partial Subregularity | 3 |
| 12 | 6 | |
| 13 | 39 | |
| 14 | 91 | |
| 15 | 4 | |
| 16 | 29 | |
| 17 | 1 | |
| 18 | 3 | |
| 19 | 1 | |
| 20 | Diff-convex combinations of Euclidean distances: a search for optima | 6 |
About Tuomo Valkonen
Tuomo Valkonen is a scholar working on Computational Mathematics, Numerical Analysis and Mathematical Physics, having authored 39 papers that have together received 413 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (15 papers), Numerical methods in inverse problems (12 papers) and Advanced Optimization Algorithms Research (9 papers). The work is most often cited by research in Mathematical Physics (115 citations), Computational Mathematics (7 citations) and Computational Mechanics (196 citations). Tuomo Valkonen has collaborated with scholars based in Finland, United Kingdom and Ecuador. Frequent co-authors include Carola‐Bibiane Schönlieb, Kristian Bredies, Florian Knöll, Juan Carlos De los Reyes, Dirk A. Lorenz, Jan Lellmann, Karl Kunisch, Martin Benning, Lynn F. Gladden and Daniel J. Holland. Their work appears in journals such as Journal of Mathematical Analysis and Applications, SIAM Journal on Applied Mathematics and Nonlinear Analysis.
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.