513 citations · 3.3k across the 57 of their papers we have counts for
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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…
Stellar Populations in type Ia supernova host galaxies at intermediate-high redshift: Star formation and metallicity enrichment histories
I. Millan-Irigoyen, M. G. del Valle-Espinosa, R. Fernández-Aranda +5
We present a summary of our project that studies galaxies hosting type Ia supernova (SN Ia) at different redshifts. We present Gran Telescopio de Canarias (GTC) optical spectroscop…
Revisiting stellar properties of star-forming galaxies with stellar and nebular spectral modelling
Leandro S. M. Cardoso, Jean Michel Gomes, Polychronis Papaderos +5
Spectral synthesis is a powerful tool for interpreting the physical properties of galaxies by decomposing their spectral energy distributions into the main luminosity contributors…