Search Results for author: Matthieu Kowalski

Found 5 papers, 2 papers with code

Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals

2 code implementations10 Mar 2023 Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy, Lucas Drumetz, Thomas Moreau, Matthieu Kowalski, Nicolas Courty

When dealing with electro or magnetoencephalography records, many supervised prediction tasks are solved by working with covariance matrices to summarize the signals.

Brain Computer Interface Computational Efficiency +5

Understanding approximate and unrolled dictionary learning for pattern recovery

1 code implementation ICLR 2022 Benoît Malézieux, Thomas Moreau, Matthieu Kowalski

Dictionary learning consists of finding a sparse representation from noisy data and is a common way to encode data-driven prior knowledge on signals.

Dictionary Learning Rolling Shutter Correction

Estimation with Low-Rank Time-Frequency Synthesis Models

no code implementations25 Apr 2018 Cédric Févotte, Matthieu Kowalski

In this paper we instead propose a synthesis approach, where low-rankness is imposed to the synthesis coefficients of the data signal over a given t-f dictionary (such as a Gabor frame).

Audio Signal Processing Compressive Sensing

Social-sparsity brain decoders: faster spatial sparsity

no code implementations21 Jun 2016 Gaël Varoquaux, Matthieu Kowalski, Bertrand Thirion

Spatially-sparse predictors are good models for brain decoding: they give accurate predictions and their weight maps are interpretable as they focus on a small number of regions.

Brain Decoding General Classification

Low-Rank Time-Frequency Synthesis

no code implementations NeurIPS 2014 Cédric Févotte, Matthieu Kowalski

Many single-channel signal decomposition techniques rely on a low-rank factorization of a time-frequency transform.

Audio Signal Processing Speech Enhancement

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