Radio astronomy is currently thriving with new large ground-based radio
...
The accurate modelling of the Point Spread Function (PSF) is of paramoun...
As the volume and quality of modern galaxy surveys increase, so does the...
We present a new scheme to compensate for the small-scales approximation...
In astronomy, upcoming space telescopes with wide-field optical instrume...
Weak lensing mass-mapping is a useful tool to access the full distributi...
Recurrent models have gained popularity in deep learning (DL) based vide...
We propose a paradigm shift in the data-driven modeling of the instrumen...
We perform a qualitative analysis of performance of XPDNet, a
state-of-t...
In recent years, implicit deep learning has emerged as a method to incre...
Video super-resolution (VSR) aims to reconstruct a sequence of
high-reso...
Deep neural networks have recently been thoroughly investigated as a pow...
Accelerating MRI scans is one of the principal outstanding problems in t...
Deep neural networks have proven extremely efficient at solving a wide
r...
We present a modular cross-domain neural network the XPDNet and its
appl...
Machine Learning in general and Deep Learning in particular has gained m...
Supervised Dictionary Learning has gained much interest in the recent de...
Deconvolution of large survey images with millions of galaxies requires ...
In this paper, we propose a semi-supervised dictionary learning method t...
Based on the DUSTGRAIN-pathfinder suite of simulations, we investigate
o...
This article introduces a new non-linear dictionary learning method for
...
Blind source separation (BSS) is a very popular technique to analyze
mul...
In large-scale spatial surveys, such as the forthcoming ESA Euclid missi...
Non-negative blind source separation (non-negative BSS), which is also
r...
Non-negative blind source separation (BSS) has raised interest in variou...
Astronomical images suffer a constant presence of multiple defects that ...
By a "covering" we mean a Gaussian mixture model fit to observed data.
A...
We show the potential for classifying images of mixtures of aggregate, b...