Stéphane Mallat
Impact in
- Computer Vision and Pattern Recognition top 0.01%
- Image and Signal Denoising Methods
- Advanced Data Compression Techniques
- Medical Image Segmentation Techniques
- Advanced Image Processing Techniques
- Media Technology top 0.01%
- Advanced Image Fusion Techniques
Papers in
-
- Image and Signal Denoising Methods 78
- Medical Image Segmentation Techniques 21
- Advanced Image Processing Techniques 17
- Advanced Data Compression Techniques 10
-
- Advanced Image Fusion Techniques 26
- Co-authors
- Zhifeng Zhang (1 shared paper)Wen-Liang Hwang (5 shared papers)Gabriel Peyré (10 shared papers)Saishang Zhong (4 shared papers)Joan Bruna (5 shared papers)Erwan Le Pennec (9 shared papers)Guoshen Yu (7 shared papers)Joakim Andén (8 shared papers)
- Journals
- IEEE Transactions on Signal Processing (8 papers)Applied and Computational Harmonic Analysis (7 papers)The Annals of Statistics (4 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (4 papers)IEEE Transactions on Image Processing (4 papers)
- Partner nations
- FranceUnited StatesAustralia
In The Last Decade
Stéphane Mallat
143 papers receiving 54.8k citations
Stéphane Mallat's Hit Papers
Peers
Comparison fields: 5 of 222
- Computer Vision and Pattern Recognition 30.3k
- Media Technology 9.8k
- Signal Processing 10.5k
- Computational Mechanics 8.3k
- Applied Mathematics 3.4k
Countries citing papers authored by Stéphane Mallat
This map shows the geographic impact of Stéphane Mallat'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 Stéphane Mallat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stéphane Mallat more than expected).
Fields of papers citing papers by Stéphane Mallat
This network shows the impact of papers produced by Stéphane Mallat. 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 Stéphane Mallat. The network helps show where Stéphane Mallat may publish in the future.
Co-authors
The 25 scholars most cited alongside Stéphane Mallat, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 147 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A theory for multiresolution signal decomposition: the wavelet representation Hit paper breakdown → | 1989 | 16608 |
| 2 | A Wavelet Tour of Signal Processing Hit paper breakdown → | 1999 | 12815 |
| 3 | Matching pursuits with time-frequency dictionaries Hit paper breakdown → | 1993 | 6838 |
| 4 | Singularity detection and processing with wavelets Hit paper breakdown → | 1992 | 3027 |
| 5 | Characterization of signals from multiscale edges Hit paper breakdown → | 1992 | 2066 |
| 6 | A Wavelet Tour of Signal Processing : The Sparse Way Hit paper breakdown → | 2008 | 2040 |
| 7 | Multiresolution approximations and wavelet orthonormal bases of 𝐿²(𝑅) Hit paper breakdown → | 1989 | 1619 |
| 8 | Multifrequency channel decompositions of images and wavelet models Hit paper breakdown → | 1989 | 1565 |
| 9 | Wavelet zoom Hit paper breakdown → | 1999 | 1243 |
| 10 | Invariant Scattering Convolution Networks Hit paper breakdown → | 2013 | 1112 |
| 11 | Adaptive greedy approximations Hit paper breakdown → | 1997 | 850 |
| 12 | Multiresolution Approximations and Wavelet Orthonormal Bases of L 2 (R) Hit paper breakdown → | 1989 | 738 |
| 13 | Group Invariant Scattering Hit paper breakdown → | 2012 | 663 |
| 14 | Sparse geometric image representations with bandelets Hit paper breakdown → | 2005 | 651 |
| 15 | Zero-crossings of a wavelet transform Hit paper breakdown → | 1991 | 548 |
| 16 | A Theory for Multiresolution Signal Decomposition: The Wavelet Representation Hit paper breakdown → | 2009 | 506 |
| 17 | Deep Scattering Spectrum Hit paper breakdown → | 2014 | 475 |
| 18 | Solving Inverse Problems With Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity Hit paper breakdown → | 2011 | 447 |
| 19 | Understanding deep convolutional networks Hit paper breakdown → | 2016 | 440 |
| 20 | Phase recovery, MaxCut and complex semidefinite programming Hit paper breakdown → | 2013 | 378 |
About Stéphane Mallat
Stéphane Mallat is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Signal Processing, Computational Mechanics and Applied Mathematics, having authored 147 papers that have together received 58.9k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (78 papers), Advanced Image Fusion Techniques (26 papers), Sparse and Compressive Sensing Techniques (22 papers), Medical Image Segmentation Techniques (21 papers), Advanced Image Processing Techniques (17 papers), Speech and Audio Processing (11 papers), Advanced Data Compression Techniques (10 papers) and Blind Source Separation Techniques (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (30.3k citations), Media Technology (9.8k citations), Signal Processing (10.5k citations), Computational Mechanics (8.3k citations) and Applied Mathematics (3.4k citations). Stéphane Mallat has collaborated with scholars based in France, United States and Australia. Frequent co-authors include Zhifeng Zhang, Wen-Liang Hwang, Gabriel Peyré, Saishang Zhong, Joan Bruna, Erwan Le Pennec, Guoshen Yu, Joakim Andén, Geoffrey M. Davis and Manuel Avellaneda. Their work appears in journals such as IEEE Transactions on Signal Processing, Applied and Computational Harmonic Analysis, The Annals of Statistics, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.
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.