Michaël Defferrard
Impact in
- Signal Processing top 10%
- Music and Audio Processing
- Speech and Audio Processing
-
- Music Technology and Sound Studies
Papers in
-
- Advanced Vision and Imaging 1
- Data Visualization and Analytics 1
- Human Pose and Action Recognition 1
- Music Technology and Sound Studies 1
- Co-authors
- Nathanaël Perraudin (2 shared papers)Raphaël Sgier (1 shared paper)T. Kacprzak (1 shared paper)Pierre Vandergheynst (2 shared papers)Kirell Benzi (1 shared paper)Xavier Bresson (1 shared paper)David Pascucci (1 shared paper)Gijs Plomp (1 shared paper)
- Journals
- Astronomy and Computing (1 paper)NeuroImage (1 paper)PLoS Computational Biology (1 paper)Infoscience (Ecole Polytechnique Fédérale de Lausanne) (2 papers)arXiv (Cornell University) (2 papers)
- Partner nations
- SwitzerlandItalyNorway
In The Last Decade
Michaël Defferrard
7 papers receiving 183 citations
Peers
Comparison fields: 5 of 48
- Signal Processing 46
- Computer Vision and Pattern Recognition 70
- Computational Mathematics 2
- Cognitive Neuroscience 43
- Computer Graphics and Computer-Aided Design 7
Countries citing papers authored by Michaël Defferrard
This map shows the geographic impact of Michaël Defferrard'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 Michaël Defferrard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michaël Defferrard more than expected).
Fields of papers citing papers by Michaël Defferrard
This network shows the impact of papers produced by Michaël Defferrard. 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 Michaël Defferrard. The network helps show where Michaël Defferrard may publish in the future.
Co-authors
The 19 scholars most cited alongside Michaël Defferrard, 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 | 2019 | 90 | |
| 2 | 2017 | 48 | |
| 3 | 2020 | 34 | |
| 4 | 2020 | 6 | |
| 5 | 2020 | 5 | |
| 6 | 2022 | 4 | |
| 7 | Structured Auto-Encoder with application to Music Genre Recognition | 2015 | 1 |
About Michaël Defferrard
Michaël Defferrard is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 7 papers that have together received 188 indexed citations. Recurring topics across this work include Music and Audio Processing (2 papers), Advanced Vision and Imaging (1 paper), Diverse Musicological Studies (1 paper), Advanced Neuroimaging Techniques and Applications (1 paper), Neural dynamics and brain function (1 paper), Data Visualization and Analytics (1 paper), Human Pose and Action Recognition (1 paper) and Music Technology and Sound Studies (1 paper). The work is most often cited by research in Signal Processing (46 citations), Computer Vision and Pattern Recognition (70 citations), Computational Mathematics (2 citations), Cognitive Neuroscience (43 citations) and Computer Graphics and Computer-Aided Design (7 citations). Michaël Defferrard has collaborated with scholars based in Switzerland, Italy and Norway. Frequent co-authors include Nathanaël Perraudin, Raphaël Sgier, T. Kacprzak, Pierre Vandergheynst, Kirell Benzi, Xavier Bresson, David Pascucci, Gijs Plomp, Margherita Carboni and Katharina Glomb. Their work appears in journals such as Astronomy and Computing, NeuroImage, PLoS Computational Biology, Infoscience (Ecole Polytechnique Fédérale de Lausanne) and arXiv (Cornell University).
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.