Samuel Vaiter
- Computational Mechanics top 10%
- Computer Vision and Pattern Recognition top 10%
- Mathematical Physics top 10%
- Biomedical Engineering
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Gabriel PeyréJalal FadiliCharles‐Alban DeledalleQuentin KlopfensteinMohammad GolbabaeeJoseph SalmonNicolas PapadakisAntonin Chambolle
- Topics
- Sparse and Compressive Sensing Techniques (13 papers)Numerical methods in inverse problems (11 papers)Statistical Methods and Inference (6 papers)
- Partner nations
- FranceUnited StatesMorocco
In The Last Decade
Samuel Vaiter
13 papers receiving 197 citations
Peers
Comparison fields: 5 of 47
- Computational Mechanics 144
- Computer Vision and Pattern Recognition 69
- Mathematical Physics 56
- Biomedical Engineering 42
- Radiology, Nuclear Medicine and Imaging 24
Countries citing papers authored by Samuel Vaiter
This map shows the geographic impact of Samuel Vaiter'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 Samuel Vaiter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel Vaiter more than expected).
Fields of papers citing papers by Samuel Vaiter
This network shows the impact of papers produced by Samuel Vaiter. 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 Samuel Vaiter. The network helps show where Samuel Vaiter may publish in the future.
Co-authorship network of co-authors of Samuel Vaiter
This figure shows the co-authorship network connecting the top 25 collaborators of Samuel Vaiter. A scholar is included among the top collaborators of Samuel Vaiter 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 Samuel Vaiter. Samuel Vaiter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 11 | |
| 6 | 1 | |
| 7 | Optimality of 1-norm regularization among weighted 1-norms for sparse recovery: a case study on how to find optimal regularizations | 0 |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 14 | |
| 11 | 18 | |
| 12 | 18 | |
| 13 | 58 | |
| 14 | Partly Smooth Regularization of Inverse Problems | 1 |
| 15 | Model Selection with Piecewise Regular Gauges | 2 |
| 16 | The degrees of freedom of the Group Lasso for a General Design | 1 |
| 17 | 4 | |
| 18 | 67 |
About Samuel Vaiter
Samuel Vaiter is a scholar working on Mathematical Physics, Statistics and Probability and Computational Mechanics, having authored 18 papers that have together received 207 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (13 papers), Numerical methods in inverse problems (11 papers) and Statistical Methods and Inference (6 papers). The work is most often cited by research in Computational Mechanics (144 citations), Mathematical Physics (56 citations) and Computer Vision and Pattern Recognition (69 citations). Samuel Vaiter has collaborated with scholars based in France, United States and Morocco. Frequent co-authors include Gabriel Peyré, Jalal Fadili, Charles‐Alban Deledalle, Jalal Fadili, Quentin Klopfenstein, Mohammad Golbabaee, Joseph Salmon, Nicolas Papadakis, Antonin Chambolle and Ch. Dossal. Their work appears in journals such as IEEE Transactions on Information Theory, Machine Learning and SIAM Journal on Optimization.
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.