Matthieu Kowalski

1.6k total citations
26 papers, 817 citations indexed

About

Matthieu Kowalski is a scholar working on Computational Mechanics, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Matthieu Kowalski has authored 26 papers receiving a total of 817 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computational Mechanics, 10 papers in Signal Processing and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Matthieu Kowalski's work include Blind Source Separation Techniques (10 papers), Image and Signal Denoising Methods (9 papers) and Sparse and Compressive Sensing Techniques (9 papers). Matthieu Kowalski is often cited by papers focused on Blind Source Separation Techniques (10 papers), Image and Signal Denoising Methods (9 papers) and Sparse and Compressive Sensing Techniques (9 papers). Matthieu Kowalski collaborates with scholars based in France, Canada and United States. Matthieu Kowalski's co-authors include Alexandre Gramfort, Matti Hämäläinen, Bruno Torrésani, Daniel Strohmeier, Jens Haueisen, Monika Dörfler, Kai Siedenburg, Hau‐Tieng Wu, Rémi Gribonval and Emmanuel Vincent and has published in prestigious journals such as NeuroImage, IEEE Transactions on Signal Processing and Physics in Medicine and Biology.

In The Last Decade

Matthieu Kowalski

23 papers receiving 790 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Matthieu Kowalski France 12 318 315 216 205 107 26 817
İlker Bayram Türkiye 15 323 1.0× 228 0.7× 89 0.4× 454 2.2× 70 0.7× 39 986
Gaetano Scarano Italy 20 206 0.6× 372 1.2× 217 1.0× 324 1.6× 48 0.4× 149 1.4k
Qiu‐Hua Lin China 16 90 0.3× 431 1.4× 354 1.6× 176 0.9× 183 1.7× 64 1.2k
Rongjie Lai United States 18 396 1.2× 134 0.4× 51 0.2× 399 1.9× 130 1.2× 60 1.0k
Xi-Lin Li United States 18 199 0.6× 796 2.5× 386 1.8× 60 0.3× 112 1.0× 50 1.1k
Adam S. Charles United States 12 165 0.5× 80 0.3× 168 0.8× 132 0.6× 47 0.4× 38 638
Chaitanya Ekanadham United States 7 147 0.5× 209 0.7× 152 0.7× 443 2.2× 29 0.3× 13 851
Athanasios P. Liavas Greece 13 255 0.8× 374 1.2× 91 0.4× 69 0.3× 37 0.3× 40 850
Temujin Gautama Belgium 12 68 0.2× 187 0.6× 198 0.9× 245 1.2× 39 0.4× 25 847
V.C. Soon United States 9 152 0.5× 697 2.2× 96 0.4× 42 0.2× 62 0.6× 19 873

Countries citing papers authored by Matthieu Kowalski

Since Specialization
Citations

This map shows the geographic impact of Matthieu Kowalski'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 Matthieu Kowalski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthieu Kowalski more than expected).

Fields of papers citing papers by Matthieu Kowalski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthieu Kowalski. 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 Matthieu Kowalski. The network helps show where Matthieu Kowalski may publish in the future.

Co-authorship network of co-authors of Matthieu Kowalski

This figure shows the co-authorship network connecting the top 25 collaborators of Matthieu Kowalski. A scholar is included among the top collaborators of Matthieu Kowalski 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 Matthieu Kowalski. Matthieu Kowalski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kowalski, Matthieu, et al.. (2024). From Convolutional Sparse Coding To *-NMF Factorization of Time-Frequency Coefficients. SPIRE - Sciences Po Institutional REpository. 5530–5534.
2.
Kowalski, Matthieu & Alexandre Gramfort. (2019). A priori par normes mixtes pour les problèmes inverses. DSpace (Centre National De La Recherche Scientifique). 1 indexed citations
3.
Févotte, Cédric & Matthieu Kowalski. (2018). Estimation With Low-Rank Time–Frequency Synthesis Models. IEEE Transactions on Signal Processing. 66(15). 4121–4132. 7 indexed citations
4.
Kowalski, Matthieu, et al.. (2018). Hybrid Projective Nonnegative Matrix Factorization With Drum Dictionaries for Harmonic/Percussive Source Separation. IEEE/ACM Transactions on Audio Speech and Language Processing. 26(9). 1499–1511. 5 indexed citations
5.
Kowalski, Matthieu, et al.. (2018). Revisiting sparse ICA from a synthesis point of view: Blind Source Separation for over and underdetermined mixtures. Signal Processing. 152. 165–177. 14 indexed citations
6.
Kowalski, Matthieu, et al.. (2018). Underdetermined Reverberant Blind Source Separation: Sparse Approaches for Multiplicative and Convolutive Narrowband Approximation. IEEE/ACM Transactions on Audio Speech and Language Processing. 27(2). 442–456. 29 indexed citations
7.
Kowalski, Matthieu, et al.. (2016). Convex Optimization approach to signals with fast varying instantaneous frequency. Applied and Computational Harmonic Analysis. 44(1). 89–122. 35 indexed citations
8.
Schmidt, Florian M., et al.. (2014). Analytical Model and Spectral Correction of Vibration Effects on PFS Fourier Transform Spectrometer. LPI. 1752.
9.
Balázs, Péter, et al.. (2013). Adapted and Adaptive Linear Time-Frequency Representations: A Synthesis Point of View. IEEE Signal Processing Magazine. 30(6). 20–31. 21 indexed citations
10.
Schmidt, Frédéric, et al.. (2013). Toward a numerical deshaker for PFS. Planetary and Space Science. 91. 45–51. 1 indexed citations
11.
Gramfort, Alexandre, Daniel Strohmeier, Jens Haueisen, Matti Hämäläinen, & Matthieu Kowalski. (2013). Time-frequency mixed-norm estimates: Sparse M/EEG imaging with non-stationary source activations. NeuroImage. 70. 410–422. 161 indexed citations
12.
Schmidt, Frédéric, et al.. (2013). Analytical model and spectral correction of vibration effects on Fourier transform spectrometer. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8890. 88900S–88900S.
13.
Gramfort, Alexandre, Matthieu Kowalski, & Matti Hämäläinen. (2012). Mixed-norm estimates for the M/EEG inverse problem using accelerated gradient methods. Physics in Medicine and Biology. 57(7). 1937–1961. 132 indexed citations
14.
Gramfort, Alexandre, Daniel Strohmeier, Jens Haueisen, Matti Hämäläinen, & Matthieu Kowalski. (2011). Functional Brain Imaging with M/EEG Using Structured Sparsity in Time-Frequency Dictionaries. Lecture notes in computer science. 22. 600–611. 33 indexed citations
15.
Kowalski, Matthieu, Emmanuel Vincent, & Rémi Gribonval. (2010). Beyond the Narrowband Approximation: Wideband Convex Methods for Under-Determined Reverberant Audio Source Separation. IEEE Transactions on Audio Speech and Language Processing. 18(7). 1818–1829. 29 indexed citations
16.
Kowalski, Matthieu. (2009). Sparse regression using mixed norms. Applied and Computational Harmonic Analysis. 27(3). 303–324. 172 indexed citations
17.
Gramfort, Alexandre & Matthieu Kowalski. (2009). Improving M/EEG source localization with an inter-condition sparse prior. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
18.
Smith, William R., et al.. (2009). Refrigeration cycle design by molecular simulation.. 2 indexed citations
19.
Kowalski, Matthieu & Bruno Torrésani. (2008). Random Models for Sparse Signals Expansion on Unions of Bases With Application to Audio Signals. IEEE Transactions on Signal Processing. 56(8). 3468–3481. 10 indexed citations
20.
Hunter, G., et al.. (1999). Fermion quasi-spherical harmonics. Journal of Physics A Mathematical and General. 32(5). 795–803. 1 indexed citations

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.

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