62 citations · 259 across the 17 of their papers we have counts for
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astro-ph.GA2021★ 22 cited
Inferring galaxy dark halo properties from visible matter with Machine Learning
Rodrigo von Marttens, Luciano Casarini, Nicola R. Napolitano +6
Next-generation surveys will provide photometric and spectroscopic data of millions to billions of galaxies with unprecedented precision. This offers a unique chance to improve our…
astro-ph.GA2021★ 1 cited
Lenses In VoicE (LIVE): Searching for strong gravitational lenses in the VOICE@VST survey using Convolutional Neural Networks
Fabrizio Gentile, Crescenzo Tortora, Giovanni Covone +8
We present a sample of 16 likely strong gravitational lenses identified in the VST Optical Imaging of the CDFS and ES1 fields (VOICE survey) using Convolutional Neural Networks (CN…