2 citations · 4 across the 9 of their papers we have counts for
5 papers · 1 filter
Flower: A Flow-Matching Solver for Inverse Problems
Mehrsa Pourya, Bassam El Rawas, Michael Unser
We introduce Flower, a solver for linear inverse problems. It leverages a pre-trained flow model to produce reconstructions that are consistent with the observed measurements. Flow…
Multivariate Fields of Experts for Convergent Image Reconstruction
Stanislas Ducotterd, Michael Unser
We introduce the multivariate fields of experts, a new framework for the learning of image priors. Our model generalizes existing fields of experts methods by incorporating multiva…
Universal Architectures for the Learning of Polyhedral Norms and Convex Regularizers
Michael Unser, Stanislas Ducotterd
This paper addresses the task of learning convex regularizers to guide the reconstruction of images from limited data. By imposing that the reconstruction be amplitude-equivariant,…
DEALing with Image Reconstruction: Deep Attentive Least Squares
Mehrsa Pourya, Erich Kobler, Michael Unser +1
State-of-the-art image reconstruction often relies on complex, highly parameterized deep architectures. We propose an alternative: a data-driven reconstruction method inspired by t…
Comparison of 2D Regular Lattices for the CPWL Approximation of Functions
Mehrsa Pourya, Maïka Nogarotto, Michael Unser
We investigate the approximation error of functions with continuous and piecewise-linear (CPWL) representations. We focus on the CPWL search spaces generated by translates of box s…