Andrew J. Humphrey
Investigador

Este investigador deixou o CAUP em 31 outubro 2014

Telefone
+351 226 089 846

Email
Andrew.Humphrey@astro.up.pt

Publicações
ADS
Últimas publicações no CAUP/IA
W. Wang, D. Wylezalek, J. Vernet, C. de Breuck, B. Gullberg, A. M. Swinbank, M. Villar Martín, M. D. Lehnert, G. Drouart, F. Arrigoni-Battaia et al. (including: A. Humphrey, P. Lagos), 2023,
3D tomography of the giant Lyα nebulae of z≈3–5 radio-loud AGN,
Astronomy & Astrophysics, 680, 44
>> Abstract
R. Carvajal, I. Matute, J. Afonso, R. P. Norris, K. J. Luken, P. Sánchez-Sáez, P. A. C. Cunha, A. Humphrey, H. Messias, S. Amarantidis et al. (including: H. Miranda, A. Paulino-Afonso, C. Pappalardo), 2023,
Selection of powerful radio galaxies with machine learning,
Astronomy & Astrophysics, 679, 24
>> Abstract
Euclid Collaboration, L. Bisigello, C. J. Conselice, M. Baes, M. Bolzonella, M. Brescia, S. Cavuoti, O. Cucciati, A. Humphrey, L. K. Hunt et al. (including: E. Branchini, M. Cropper, A. N. Taylor, C. S. Carvalho), 2023,
Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images,
Monthly Notices of the Royal Astronomical Society, 520, 19
>> Abstract
L. Binette, Y. Krongold, S. A. R. Haro-Corzo, A. Humphrey, S. G. Morais, 2023,
Optimized Spectral Energy Distribution for Seyfert Galaxies,
Revista Mexicana de Astronomía y Astrofísica, 53, 9
>> Abstract
A. Humphrey, P. A. C. Cunha, A. Paulino-Afonso, S. Amarantidis, R. Carvajal, J. M. Gomes, I. Matute, P. Papaderos, 2023,
Improving machine learning-derived photometric redshifts and physical property estimates using unlabelled observations,
Monthly Notices of the Royal Astronomical Society, 520, 305 - 313
>> Abstract
Euclid Collaboration, A. Humphrey, L. Bisigello, P. A. C. Cunha, M. Bolzonella, S. Fotopoulou, K. Caputi, C. Tortora, G. Zamorani, P. Papaderos et al. (including: J. Brinchmann, A. C. da Silva, I. Tereno, C. S. Carvalho), 2023,
Euclid preparation
XXII. Selection of quiescent galaxies from mock photometry using machine learning
,
Astronomy & Astrophysics, 671, 36
>> Abstract