62 citations · 293 across the 18 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
astro-ph.GA2023★ 8 cited
Selection of powerful radio galaxies with machine learning
R. Carvajal, I. Matute, J. Afonso +12
We developed and trained a pipeline of three machine learning (ML) models than can predict which sources are more likely to be an AGN and to be detected in specific radio surveys.…
astro-ph.IM2023
Measuring photometric redshifts for high-redshift radio source surveys
Kieran J. Luken, Ray P. Norris, X. Rosalind Wang +3
With the advent of deep, all-sky radio surveys, the need for ancillary data to make the most of the new, high-quality radio data from surveys like the Evolutionary Map of the Unive…