577 citations · 1.1k across the 24 of their papers we have counts for
25 papers
JESSNet: Joint dEconvolution and Sparse Separation Network for HI 21 cm foreground cleaning
Athanasia Gkogkou, Victor Bonjean, Jean-Luc Starck +3
Foreground cleaning is a major challenge for H\,{\sc i} 21 cm intensity mapping, particularly in the presence of a chromatic instrumental beam that couples angular foreground struc…
Mitigating baryonic effects in weak lensing with higher-order statistics
Andreas Tersenov, Sacha Guerrini, Jean-Luc Starck +1
Weak gravitational lensing is a premier cosmological probe, but its small-scale statistical power is compromised by baryonic feedback. Higher-order statistics capture non-Gaussian…
Point spread function wavefront recovery from in-focus stellar observations
Ezequiel Centofanti, Samuel Farrens, Jean-Luc Starck +1
Recovering the wavefront error (WFE) field of an optical system from intensity in-focus observations is a challenging inverse problem with broad implications for telescope point sp…
Cosmology with Intensity Mapping via Statistics Beyond the Power Spectrum in the SKAO Era
Suman Majumdar, Debanjan Sarkar, Leon Noble +38
The cosmological distribution of neutral hydrogen (HI) during the post-reionization era is highly non-Gaussian due to the underlying non-linear structure formation, complex galaxy…
Deep and Sparse Denoising Benchmarks for Spectral Data Cubes of High-z Galaxies: From Simulations to ALMA observations
Arnab Lahiry, Tanio Díaz-Santos, Jean-Luc Starck +4
Beyond cosmic noon, galaxies appear as faint whispers amid noise, yet this epoch is key to understanding massive galaxy assembly. ALMA's sensitivity to cold dust and [C II] emissio…
CHEM: Estimating and Understanding Hallucinations in Deep Learning for Image Processing
Jianfei Li, Ines Rosellon-Inclan, Gitta Kutyniok +1
Deep learning-based methods have recently achieved significant success in image reconstruction problems. However, challenges have emerged, as these methods may generate unrealistic…