most citedPSFGAN: a generative adversarial network system for separating quasar point sources and host galaxy light

23 citations · 40 across the 3 of their papers we have counts for

collaborators

3 papers

astro-ph.GA2022★ 4 cited

Using Machine Learning to Determine Morphologies of AGN Host Galaxies in the Hyper Suprime-Cam Wide Survey

Chuan Tian, C. Megan Urry, Aritra Ghosh +9

We present a machine-learning framework to accurately characterize morphologies of Active Galactic Nucleus (AGN) host galaxies within . We first use PSFGAN to decouple host ga…

astro-ph.GA2022★ 13 cited

GaMPEN: A Machine Learning Framework for Estimating Bayesian Posteriors of Galaxy Morphological Parameters

Aritra Ghosh, C. Megan Urry, Amrit Rau +11

We introduce a novel machine learning framework for estimating the Bayesian posteriors of morphological parameters for arbitrarily large numbers of galaxies. The Galaxy Morphology…

astro-ph.GA2018★ 23 cited

PSFGAN: a generative adversarial network system for separating quasar point sources and host galaxy light

Dominic Stark, Barthelemy Launet, Kevin Schawinski +7

The study of unobscured active galactic nuclei (AGN) and quasars depends on the reliable decomposition of the light from the AGN point source and the extended host galaxy light. Th…