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20222026
most citedBeyond Gaussian Noise: A Generalized Approach to Likelihood Analysis with non-Gaussian Noise

22 citations · 55 across the 19 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

astro-ph.GA2023★ 1 cited

Unraveling the Mysteries of Galaxy Clusters: Recurrent Inference Deconvolution of X-ray Spectra

Carter Rhea, Julie Hlavacek-Larrondo, Ralph Kraft +3

In the realm of X-ray spectral analysis, the true nature of spectra has remained elusive, as observed spectra have long been the outcome of convolution between instrumental respons…

astro-ph.IM2023★ 1 cited

Bayesian Imaging for Radio Interferometry with Score-Based Priors

Noe Dia, M. J. Yantovski-Barth, Alexandre Adam +5

The inverse imaging task in radio interferometry is a key limiting factor to retrieving Bayesian uncertainties in radio astronomy in a computationally effective manner. We use a sc…

astro-ph.IM2023

Echoes in the Noise: Posterior Samples of Faint Galaxy Surface Brightness Profiles with Score-Based Likelihoods and Priors

Alexandre Adam, Connor Stone, Connor Bottrell +3

Examining the detailed structure of galaxy populations provides valuable insights into their formation and evolution mechanisms. Significant barriers to such analysis are the non-t…

astro-ph.GA2023

The search for the lost attractor

Mario Pasquato, Syphax Haddad, Pierfrancesco Di Cintio +8

N-body systems characterized by inverse square attractive forces may display a self similar collapse known as the gravo-thermal catastrophe. In star clusters, collapse is halted by…

astro-ph.IM2023★ 22 cited

Beyond Gaussian Noise: A Generalized Approach to Likelihood Analysis with non-Gaussian Noise

Ronan Legin, Alexandre Adam, Yashar Hezaveh +1

Likelihood analysis is typically limited to normally distributed noise due to the difficulty of determining the probability density function of complex, high-dimensional, non-Gauss…

astro-ph.IM2023★ 12 cited

Pixelated Reconstruction of Foreground Density and Background Surface Brightness in Gravitational Lensing Systems using Recurrent Inference Machines

Alexandre Adam, Laurence Perreault-Levasseur, Yashar Hezaveh +1

Modeling strong gravitational lenses in order to quantify the distortions in the images of background sources and to reconstruct the mass density in the foreground lenses has been…