17 citations · 51 across the 17 of their papers we have counts for
4 papers · 1 filter
Generative modelling for mass-mapping with fast uncertainty quantification
Jessica J. Whitney, Tobías I. Liaudat, Matthew A. Price +2
Understanding the nature of dark matter in the Universe is an important goal of modern cosmology. A key method for probing this distribution is via weak gravitational lensing mass-…
Using conditional GANs for convergence map reconstruction with uncertainties
Jessica Whitney, Tobías Liaudat, Matt Price +2
Understanding the large-scale structure of the Universe and unravelling the mysteries of dark matter are fundamental challenges in contemporary cosmology. Reconstruction of the cos…
The future of cosmological likelihood-based inference: accelerated high-dimensional parameter estimation and model comparison
Davide Piras, Alicja Polanska, Alessio Spurio Mancini +2
We advocate for a new paradigm of cosmological likelihood-based inference, leveraging recent developments in machine learning and its underlying technology, to accelerate Bayesian…
A covariant formulation for cosmological radiative transfer of the 21-cm line
Jennifer Y. H. Chan, Qin Han, Kinwah Wu +1
The 21-cm hyperfine line of neutral hydrogen is a useful tool to probe the conditions of the Universe during the Dark Ages, Cosmic Dawn, and the Epoch of Reionisation. In most of t…