24 citations · 102 across the 17 of their papers we have counts for
5 papers · 1 filter
Signal Inpainting from Fourier Magnitudes
Louis Bahrman, Marina Krémé, Paul Magron +1
Signal inpainting is the task of restoring degraded or missing samples in a signal. In this paper we address signal inpainting when Fourier magnitudes are observed. We propose a ma…
Algorithms for audio inpainting based on probabilistic nonnegative matrix factorization
Ondřej Mokrý, Paul Magron, Thomas Oberlin +1
Audio inpainting, i.e., the task of restoring missing or occluded audio signal samples, usually relies on sparse representations or autoregressive modeling. In this paper, we propo…
A majorization-minimization algorithm for nonnegative binary matrix factorization
Paul Magron, Cédric Févotte
This paper tackles the problem of decomposing binary data using matrix factorization. We consider the family of mean-parametrized Bernoulli models, a class of generative models tha…
Learning the Proximity Operator in Unfolded ADMM for Phase Retrieval
Pierre-Hugo Vial, Paul Magron, Thomas Oberlin +1
This paper considers the phase retrieval (PR) problem, which aims to reconstruct a signal from phaseless measurements such as magnitude or power spectrograms. PR is generally handl…
A Sparsity-promoting Dictionary Model for Variational Autoencoders
Mostafa Sadeghi, Paul Magron
Structuring the latent space in probabilistic deep generative models, e.g., variational autoencoders (VAEs), is important to yield more expressive models and interpretable represen…