Samuel Vaiter

13 papers receiving 197 citations

Peers

Samuel Vaiter
Comparison fields: 5 of 47
  • Computational Mechanics 144
  • Mathematical Physics 56
  • Computer Vision and Pattern Recognition 69
  • Numerical Analysis 16
  • Statistics and Probability 23
Replace Guohui Song with:
Guohui Song United States
Andrew Thompson United Kingdom
J.-C. Pesquet France
François Malgouyres France
Figen Öztoprak Türkiye
Hakop Hakopian Armenia
Thomas Yu United States
Boris Hanin United States
Federica Porta Italy
Aissam Hadri Morocco
Samuel Vaiter relative to Guohui Song United States Guohui Song's profile →
Citations per field
00.5×1.5×
Guohui Song · 1×
Citations per year

Countries citing papers authored by Samuel Vaiter

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

The 15 scholars most cited alongside Samuel Vaiter, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Samuel Vaiter Line = papers co-authored together Samuel Vaiter links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 201267
2 201458
3 201518
4 201618
5 201614
6 202111
7 201710
8 20124
9
Model Selection with Piecewise Regular Gauges
20132
10 20231
11
The degrees of freedom of the Group Lasso for a General Design
20121
12 20201
13
Partly Smooth Regularization of Inverse Problems
20141
14 20181
15 20230
16
Optimality of 1-norm regularization among weighted 1-norms for sparse recovery: a case study on how to find optimal regularizations
20180
17 20230
18 20220

About Samuel Vaiter

Samuel Vaiter is a scholar working on Computational Mechanics, Mathematical Physics, Statistics and Probability, Biomedical Engineering and Computer Vision and Pattern Recognition, 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), Statistical Methods and Inference (6 papers), Photoacoustic and Ultrasonic Imaging (3 papers), Markov Chains and Monte Carlo Methods (2 papers), Electrical and Bioimpedance Tomography (2 papers), Complex Network Analysis Techniques (1 paper) and Face and Expression Recognition (1 paper). The work is most often cited by research in Computational Mechanics (144 citations), Mathematical Physics (56 citations), Computer Vision and Pattern Recognition (69 citations), Numerical Analysis (16 citations) and Statistics and Probability (23 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 Edouard Pauwels. Their work appears in journals such as Journal of Mathematical Imaging and Vision, SIAM Journal on Optimization, Electronic Journal of Statistics, Journal of Optimization Theory and Applications and SIAM Journal on Imaging Sciences.

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.

Explore authors with similar magnitude of impact