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Author

Timo Gerkmann

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#machine learning Preprint Sep 2026

Livin'on a Prior: Likelihood Score Approximation for Inverse Problems

Generative models have found great success as data-driven methods of solving inverse problems. Two popular approaches work either by combining a pretrained generative prior with a known degradation model, or by training a conditional generative model directly from paired data. We target a setting that spans both regime...

Rostislav Makarov, Tal Peer, Danilo de Oliveira et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Test-time adaptation for speech enhancement with an autoregressive speech prior

Test-time adaptation (TTA) offers a promising direction for improving speech enhancement models under mismatched acoustic conditions, without requiring access to labeled target data. In this work, we propose a single-utterance TTA method that regularizes a pretrained speech enhancement model using an autoregressive pri...

S. Kammoun, Simon Leglaive, Xavier Alameda-Pineda et al. · 1 citation

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