Sparse aNETT for Solving Inverse Problems with Deep Learning

We propose a sparse reconstruction framework (aNETT) for solving inverse problems. Opposed to existing sparse reconstruction techniques that are based on linear sparsifying transforms, we train an autoencoder network $D \circ E$ with $E$ acting as a nonlinear sparsifying transform and minimize a Tik...

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Hauptverfasser:	Obmann, Daniel, Nguyen, Linh, Schwab, Johannes, Haltmeier, Markus
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Computer Science - Numerical Analysis Mathematics - Numerical Analysis
Online-Zugang:	Volltext bestellen
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