367 citations · 406 across the 13 of their papers we have counts for
5 papers · 1 filter
Convergent regularization in inverse problems and linear plug-and-play denoisers
Andreas Hauptmann, Subhadip Mukherjee, Carola-Bibiane Schönlieb +1
Plug-and-play (PnP) denoising is a popular iterative framework for solving imaging inverse problems using off-the-shelf image denoisers. Their empirical success has motivated a lin…
Domain independent post-processing with graph U-nets: Applications to Electrical Impedance Tomographic Imaging
William Herzberg, Andreas Hauptmann, Sarah J. Hamilton
Reconstruction of tomographic images from boundary measurements requires flexibility with respect to target domains. For instance, when the system equations are modeled by partial…
Joint Activity Detection and Channel Estimation for Clustered Massive Machine Type Communications
Leatile Marata, Onel Luis Alcaraz López, Andreas Hauptmann +2
Compressed sensing multi-user detection (CS-MUD) algorithms play a key role in optimizing grant-free (GF) non-orthogonal multiple access (NOMA) for massive machine-type communicati…
Model-corrected learned primal-dual models for fast limited-view photoacoustic tomography
Andreas Hauptmann, Jenni Poimala
Learned iterative reconstructions hold great promise to accelerate tomographic imaging with empirical robustness to model perturbations. Nevertheless, an adoption for photoacoustic…
Sequential model correction for nonlinear inverse problems
Arttu Arjas, Mikko J. Sillanpää, Andreas Hauptmann
Inverse problems are in many cases solved with optimization techniques. When the underlying model is linear, first-order gradient methods are usually sufficient. With nonlinear mod…