On Architecture Selection for Linear Inverse Problems with Untrained Neural Networks

In recent years, neural network based image priors have been shown to be highly effective for linear inverse problems, often significantly outperforming conventional methods that are based on sparsity and related notions. While pre-trained generative models are perhaps the most common, it has additi...

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Autores principales: Yang Sun, Hangdong Zhao, Jonathan Scarlett
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/b575e333a26d494baf46747b142feca2
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