353 citations · 1.9k across the 37 of their papers we have counts for
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astro-ph.GA2022★ 11 cited
Improving machine learning-derived photometric redshifts and physical property estimates using unlabelled observations
A. Humphrey, P. A. C. Cunha, A. Paulino-Afonso +5
In the era of huge astronomical surveys, machine learning offers promising solutions for the efficient estimation of galaxy properties. The traditional, `supervised' paradigm for t…
astro-ph.GA2022★ 6 cited
An investigation of the star-forming main sequence considering the nebular continuum emission at low-z
Henrique Miranda, Ciro Pappalardo, Polychronis Papaderos +7
The code FADO is the first publicly available population spectral synthesis tool that treats the contribution from ionised gas to the observed emission self-consistently. We study…