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Author

Martin Burger

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Review Aug 2026

A neural operator view on U-Nets for inverse imaging problems

This work reviews common approaches to neural operator learning in architectures that resemble a U-Net, one of the most common classical architectures for inverse imaging problems, and studies how well networks trained for a certain resolution of the discretization generalize to other resolutions.

Alexander Auras, Martin Burger, Samira Kabri et al. · 0 citations
#machine learning Preprint Aug 2026

Selection, Representation, and Execution in Sparse Fourier Neural Operators

This work distinguishes sparsity in the representation, in the stored parameters, in the theoretical operation count, and in measured runtime, and presents an empirical study of several routes toward sparse FNOs that tests each transition between them separately.

A. Ibrahim, Martin Burger · 0 citations

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