6 papers · 1 filter
A distributed resource-adaptive implementation of the widefield radio-interferometric measurement model for scalable image formation
Arwa Dabbech, Yves Wiaux
Modern image formation algorithms in radio interferometry rely on repeated applications of the operator Φ modelling the measurement process and its adjoint {Phi^\dagger} to enforc…
HyperAIRI: a plug-and-play algorithm for precise hyperspectral image reconstruction in radio interferometry
Chao Tang, Arwa Dabbech, Adrian Jackson +1
The next-generation radio-interferometric (RI) telescopes require imaging algorithms capable of forming high-resolution high-dynamic-range images from large data volumes spanning w…
Toward a Robust R2D2 Paradigm for Radio-interferometric Imaging: Revisiting Deep Neural Network Training and Architecture
Amir Aghabiglou, Chung San Chu, Chao Tang +2
The R2D2 Deep Neural Network (DNN) series was recently introduced for image formation in radio interferometry. It can be understood as a learned version of CLEAN, whose minor cycle…
R2D2 image reconstruction with model uncertainty quantification in radio astronomy
Amir Aghabiglou, Chung San Chu, Arwa Dabbech +1
The ``Residual-to-Residual DNN series for high-Dynamic range imaging'' (R2D2) approach was recently introduced for Radio-Interferometric (RI) imaging in astronomy. R2D2's reconstru…
The R2D2 deep neural network series paradigm for fast precision imaging in radio astronomy
Amir Aghabiglou, Chung San Chu, Arwa Dabbech +1
Radio-interferometric (RI) imaging entails solving high-resolution high-dynamic range inverse problems from large data volumes. Recent image reconstruction techniques grounded in o…
CLEANing Cygnus A deep and fast with R2D2
Arwa Dabbech, Amir Aghabiglou, Chung San Chu +1
A novel deep learning paradigm for synthesis imaging by radio interferometry in astronomy was recently proposed, dubbed "Residual-to-Residual DNN series for high-Dynamic range imag…