Silvia Gandy
Impact in
- Computational Mathematics top 0.2%
- Tensor decomposition and applications
- Computational Mechanics top 2%
- Sparse and Compressive Sensing Techniques
- Advanced Adaptive Filtering Techniques
Papers in
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- Sparse and Compressive Sensing Techniques 4
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- Medical Image Segmentation Techniques 1
- Image and Signal Denoising Methods 1
- Co-authors
- Isao Yamada (4 shared papers)Benjamin Recht (1 shared paper)Julio I. de Vicente (2 shared papers)Jorge Sánchez-Ruiz (2 shared papers)Masao Yamagishi (1 shared paper)Kazuhiro Yokoyama (1 shared paper)Hirokazu Anai (1 shared paper)
- Journals
- Inverse Problems (1 paper)Mathematics in Computer Science (1 paper)Institutional Repositories DataBase (IRDB) (1 paper)Kyushu University Institutional Repository (QIR) (Kyushu University) (1 paper)INFM-OAR (INFN Catania) (1 paper)
In The Last Decade
Silvia Gandy
7 papers receiving 555 citations
Silvia Gandy's Hit Papers
Peers
Comparison fields: 5 of 54
- Computational Mathematics 366
- Computational Mechanics 404
- Computer Vision and Pattern Recognition 206
- Signal Processing 76
- Numerical Analysis 26
Countries citing papers authored by Silvia Gandy
This map shows the geographic impact of Silvia Gandy'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 Silvia Gandy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Silvia Gandy more than expected).
Fields of papers citing papers by Silvia Gandy
This network shows the impact of papers produced by Silvia Gandy. 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 Silvia Gandy. The network helps show where Silvia Gandy may publish in the future.
Co-authors
The 7 scholars most cited alongside Silvia Gandy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Tensor completion and low-n-rank tensor recovery via convex optimization Hit paper breakdown → | 2011 | 535 |
| 2 | Convex optimization techniques for the efficient recovery of a sparsely corrupted low-rank matrix | 2010 | 15 |
| 3 | Information entropy of Gegenbauer polynomials of integer parameter | 2007 | 10 |
| 4 | 2011 | 10 | |
| 5 | 2011 | 4 | |
| 6 | 2010 | 3 | |
| 7 | 2007 | 1 |
About Silvia Gandy
Silvia Gandy is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Signal Processing and Biomedical Engineering, having authored 7 papers that have together received 578 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (4 papers), Blind Source Separation Techniques (2 papers), Statistical Mechanics and Entropy (2 papers), Photoacoustic and Ultrasonic Imaging (2 papers), Advanced Thermodynamics and Statistical Mechanics (1 paper), Numerical Methods and Algorithms (1 paper), Medical Image Segmentation Techniques (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Computational Mathematics (366 citations), Computational Mechanics (404 citations), Computer Vision and Pattern Recognition (206 citations), Signal Processing (76 citations) and Numerical Analysis (26 citations). Silvia Gandy has collaborated with scholars based in Japan, Germany and Spain. Frequent co-authors include Isao Yamada, Benjamin Recht, Julio I. de Vicente, Jorge Sánchez-Ruiz, Masao Yamagishi, Kazuhiro Yokoyama and Hirokazu Anai. Their work appears in journals such as Inverse Problems, Mathematics in Computer Science, Institutional Repositories DataBase (IRDB), Kyushu University Institutional Repository (QIR) (Kyushu University) and INFM-OAR (INFN Catania).
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.