353 citations · 1k across the 59 of their papers we have counts for
11 papers · 1 filter
Warm-Starting in Message Passing algorithms
Nikolajs Skuratovs, Mike E. Davies
Vector Approximate Message Passing (VAMP) provides the means of solving a linear inverse problem in a Bayes-optimal way assuming the measurement operator is sufficiently random. Ho…
Divergence Estimation in Message Passing algorithms
Nikolajs Skuratovs, Michael Davies
Many modern imaging applications can be modeled as compressed sensing linear inverse problems. When the measurement operator involved in the inverse problem is sufficiently random,…
Inexact Gradient Projection and Fast Data Driven Compressed Sensing
Mohammad Golbabaee, Mike E. Davies
We study convergence of the iterative projected gradient (IPG) algorithm for arbitrary (possibly nonconvex) sets and when both the gradient and projection oracles are computed appr…
Compressed sensing in Hilbert spaces
Yann Traonmilin, Gilles Puy, Rémi Gribonval +1
In many linear inverse problems, we want to estimate an unknown vector belonging to a high-dimensional (or infinite-dimensional) space from few linear measurements. To overcome the…
Recipes for stable linear embeddings from Hilbert spaces to R^m
Gilles Puy, Mike Davies, Rémi Gribonval
We consider the problem of constructing a linear map from a Hilbert space (possibly infinite dimensional) to that satisfies a restricted isometry prope…
Compressed Quantitative MRI: Bloch Response Recovery through Iterated Projection
Mike Davies, Gilles Puy, Pierre Vandergheynst +1
Inspired by the recently proposed Magnetic Resonance Fingerprinting technique, we develop a principled compressed sensing framework for quantitative MRI. The three key components a…