A machine learning approach to galaxy properties: joint redshift-stellar mass probability distributions with Random Forest Preprint

Mucesh, S, Hartley, WG, Palmese, A et al. (2020). A machine learning approach to galaxy properties: joint redshift-stellar mass probability distributions with Random Forest .

cited authors

  • Mucesh, S; Hartley, WG; Palmese, A; Lahav, O; Whiteway, L; Bluck, AFL; Alarcon, A; Amon, A; Bechtol, K; Bernstein, GM; Rosell, A Carnero; Kind, M Carrasco; Choi, A; Eckert, K; Everett, S; Gruen, D; Gruendl, RA; Harrison, I; Huff, EM; Kuropatkin, N; Sevilla-Noarbe, I; Sheldon, E; Yanny, B; Aguena, M; Allam, S; Bacon, D; Bertin, E; Bhargava, S; Brooks, D; Carretero, J; Castander, FJ; Conselice, C; Costanzi, M; Crocce, M; Costa, LN da; Pereira, MES; Vicente, J De; Desai, S; Diehl, HT; Drlica-Wagner, A; Evrard, AE; Ferrero, I; Flaugher, B; Fosalba, P; Frieman, J; García-Bellido, J; Gaztanaga, E; Gerdes, DW; Gschwend, J; Gutierrez, G; Hinton, SR; Hollowood, DL; Honscheid, K; James, DJ; Kuehn, K; Lima, M; Lin, H; Maia, MAG; Melchior, P; Menanteau, F; Miquel, R; Morgan, R; Paz-Chinchón, F; Plazas, AA; Sanchez, E; Scarpine, V; Schubnell, M; Serrano, S; Smith, M; Suchyta, E; Tarle, G; Thomas, D; To, C; Varga, TN; Wilkinson, RD

authors

publication date

  • December 10, 2020

webpage

keywords

  • astro-ph.CO
  • astro-ph.GA
  • astro-ph.IM
  • cs.LG