95 citations · 243 across the 10 of their papers we have counts for
3 papers · 1 filter
Invert to Learn to Invert
Patrick Putzky, Max Welling
Iterative learning to infer approaches have become popular solvers for inverse problems. However, their memory requirements during training grow linearly with model depth, limiting…
i-RIM applied to the fastMRI challenge
Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen +4
We, team AImsterdam, summarize our submission to the fastMRI challenge (Zbontar et al., 2018). Our approach builds on recent advances in invertible learning to infer models as pres…
Data-Driven Reconstruction of Gravitationally Lensed Galaxies using Recurrent Inference Machines
Warren R. Morningstar, Laurence Perreault Levasseur, Yashar D. Hezaveh +6
We present a machine learning method for the reconstruction of the undistorted images of background sources in strongly lensed systems. This method treats the source as a pixelated…