Learning from small data sets: patch-based regularizers in inverse problems for image reconstruction

DOI10.1002/gamm.202470002MaRDI QIDQ6664951

Gabriele Drauschke, Andrea Walther, Moritz Piening, Unnamed Author, Paul Hagemann, Johannes Hertrich

Publication date: 16 January 2025

Published in: GAMM-Mitteilungen (Search for Journal in Brave)

zbMATH Keywords

computed tomographyinverse problemsuncertainty quantificationWasserstein distancessuper-resolutioninpaintingsmall data setszero-shot learninggenerative neural networksLangevin Monte Carlo sampling

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Bayesian inference (62F15) Image analysis in multivariate analysis (62H35) Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

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