Generating images from very long baseline interferometric observations poses a difficult,
and generally not unique, inversion problem. This problem is simplified by the introduction of …

Next-generation radio interferometers like the Square Kilometer Array have the potential to
unlock scientific discoveries thanks to their unprecedented angular resolution and …

Context. Very long baseline interferometry (VLBI) is a radio-astronomical technique whereby
the correlated signal from various baselines is combined into an image of the highest …

We propose a Bayesian uncertainty quantification method for large-scale imaging inverse
problems. Our method applies to all Bayesian models that are log-concave, where maximum …

Context. Reconstructing images from very long baseline interferometry (VLBI) data with a
sparse sampling of the Fourier domain (uv-coverage) constitutes an ill-posed deconvolution …

The ability to map and estimate the activity of radiological source distributions in unknown
three-dimensional environments has applications in the prevention and response to …

In this paper we present DMC, a model and associated tool for polarimetric imaging of very
long baseline interferometry data sets that simultaneously reconstructs the full-Stokes …

Context. Imaging in radio interferometry requires solving an ill-posed noisy inverse problem,
for which the most adopted algorithm is the original CLEAN algorithm and its variants …

To date weak gravitational lensing surveys have typically been restricted to small fields of
view, such that the flat-sky approximation has been sufficiently satisfied. However, with …

Deep unrolling is an emerging deep learning-based image reconstruction methodology that
bridges the gap between model-based and purely deep learning-based image …