Speakers
Lukas Weigand
(Helmholtz Imaging, DESY)
Samira Kabri
(Helmholtz Imaging, DESY)
Tim Roith
(Helmholtz Imaging, DESY)
Description
In the second part of the tutorial we learn about deep learning for inverse problems. We start with an end-to-end approach emplyoing a U-Net to then introduce the concept of plug-and-play regularization. We finally introduce the basics of sampling and uncertainty quantification. Again, these insights are applied to CT reconstruction in small hands on tasks.
Primary authors
Lukas Weigand
(Helmholtz Imaging, DESY)
Samira Kabri
(Helmholtz Imaging, DESY)
Tim Roith
(Helmholtz Imaging, DESY)
