Web: http://arxiv.org/abs/2206.05431

Sept. 15, 2022, 1:14 a.m. | Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb

cs.CV updates on arXiv.org arxiv.org

In recent years, deep learning has achieved remarkable empirical success for
image reconstruction. This has catalyzed an ongoing quest for precise
characterization of correctness and reliability of data-driven methods in
critical use-cases, for instance in medical imaging. Notwithstanding the
excellent performance and efficacy of deep learning-based methods, concerns
have been raised regarding their stability, or lack thereof, with serious
practical implications. Significant advances have been made in recent years to
unravel the inner workings of data-driven image recovery methods, challenging …

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