Author

Mathurin Massias

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#machine learning Preprint Sep 2026

Principled MAP estimation for inverse problems: bridging the gap between convergence and performance

Pretrained denoisers provide a powerful way to incorporate image priors into restoration algorithms. Plug-and-Play and RED approaches exploit fixed-noise-level denoisers within first-order optimization schemes, with convergence guarantees, but often struggle to achieve high-quality reconstruction on severely ill-posed...

Alexandre Lagier, Valentine Tosel, Anne Gagneux et al. · 0 citations

#machine learning Preprint Sep 2026

Beyond the Manifold Hypothesis: Hybrid Spectral Parameterizations for Flow Matching

This analysis identifies two main drivers for differences in source-- data signal-to-noise ratio, and the information bottleneck induced by the neural architecture, and introduces new spectral hybrid parameterizations that adapt across time and data covariance directions.

Ségolène Martin, Anne Gagneux, Quentin Bertrand et al. · 0 citations