Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ... Nature Machine Intelligence 3 (3), 199-217, 2021 | 876 | 2021 |
Euclid preparation-VII. Forecast validation for Euclid cosmological probes A Blanchard, S Camera, C Carbone, VF Cardone, S Casas, S Clesse, ... Astronomy & Astrophysics 642, A191, 2020 | 266 | 2020 |
Euclid preparation-I. The Euclid wide survey R Scaramella, J Amiaux, Y Mellier, C Burigana, CS Carvalho, ... Astronomy & Astrophysics 662, A112, 2022 | 242 | 2022 |
The VLA-COSMOS 3 GHz Large Project: Evolution of specific star formation rates out to z∼ 5 SK Leslie, E Schinnerer, D Liu, B Magnelli, H Algera, A Karim, I Davidzon, ... The Astrophysical Journal 899 (1), 58, 2020 | 117 | 2020 |
Euclid preparation: IX. EuclidEmulator2 – power spectrum emulation with massive neutrinos and self-consistent dark energy perturbations Euclid Collaboration, M Knabenhans, J Stadel, D Potter, J Dakin, ... Monthly Notices of the Royal Astronomical Society 505 (2), 2840-2869, 2021 | 111 | 2021 |
COSMOS-Web: an overview of the JWST Cosmic Origins Survey CM Casey, JS Kartaltepe, NE Drakos, M Franco, S Harish, L Paquereau, ... The Astrophysical Journal 954 (1), 31, 2023 | 86 | 2023 |
Euclid preparation-X. The Euclid photometric-redshift challenge G Desprez, S Paltani, J Coupon, I Almosallam, A Alvarez-Ayllon, V Amaro, ... Astronomy & Astrophysics 644, A31, 2020 | 63 | 2020 |
Horizon-AGN virtual observatory–1. SED-fitting performance and forecasts for future imaging surveys C Laigle, I Davidzon, O Ilbert, J Devriendt, D Kashino, C Pichon, P Capak, ... Monthly Notices of the Royal Astronomical Society 486 (4), 5104-5123, 2019 | 63 | 2019 |
Chandra centres for COSMOS X-ray galaxy groups: differences in stellar properties between central dominant and offset brightest group galaxies G Gozaliasl, A Finoguenov, M Tanaka, K Dolag, F Montanari, ... Monthly Notices of the Royal Astronomical Society 483 (3), 3545-3565, 2019 | 60 | 2019 |
Mining the gap: evolution of the magnitude gap in X-ray galaxy groups from the 3-square-degree XMM coverage of CFHTLS G Gozaliasl, A Finoguenov, HG Khosroshahi, M Mirkazemi, M Salvato, ... Astronomy & Astrophysics 566, A140, 2014 | 48 | 2014 |
Euclid preparation-XVIII. The NISP photometric system M Schirmer, K Jahnke, G Seidel, H Aussel, C Bodendorf, F Grupp, ... Astronomy & Astrophysics 662, A92, 2022 | 47 | 2022 |
Full-sky photon simulation of clusters and active galactic nuclei in the soft X-rays for eROSITA J Comparat, D Eckert, A Finoguenov, R Schmidt, J Sanders, D Nagai, ... arXiv preprint arXiv:2008.08404, 2020 | 45 | 2020 |
Euclid preparation-XVII. Cosmic Dawn Survey: Spitzer Space Telescope observations of the Euclid deep fields and calibration fields A Moneti, HJ McCracken, M Shuntov, OB Kauffmann, P Capak, I Davidzon, ... Astronomy & Astrophysics 658, A126, 2022 | 42 | 2022 |
Group connectivity in COSMOS: a tracer of mass assembly history E Darragh Ford, C Laigle, G Gozaliasl, C Pichon, J Devriendt, A Slyz, ... Monthly Notices of the Royal Astronomical Society 489 (4), 5695-5708, 2019 | 37 | 2019 |
Euclid preparation-XIX. Impact of magnification on photometric galaxy clustering F Lepori, I Tutusaus, C Viglione, C Bonvin, S Camera, FJ Castander, ... Astronomy & Astrophysics 662, A93, 2022 | 33 | 2022 |
Euclid preparation-XV. Forecasting cosmological constraints for the Euclid and CMB joint analysis S Ilić, N Aghanim, C Baccigalupi, JR Bermejo-Climent, G Fabbian, ... Astronomy & Astrophysics 657, A91, 2022 | 32 | 2022 |
Stellar mass–halo mass relation for the brightest central galaxies of X-ray clusters since z∼ 0.65 G Erfanianfar, A Finoguenov, K Furnell, P Popesso, A Biviano, S Wuyts, ... Astronomy & Astrophysics 631, A175, 2019 | 32 | 2019 |
Two massive, compact, and dust-obscured candidate galaxies discovered by JWST HB Akins, CM Casey, N Allen, MB Bagley, M Dickinson, SL Finkelstein, ... arXiv preprint arXiv:2304.12347, 2023 | 27 | 2023 |
Euclid preparation. XIV. The complete calibration of the color–redshift relation (C3R2) survey: data release 3 SA Stanford, D Masters, B Darvish, D Stern, JG Cohen, P Capak, ... The Astrophysical Journal Supplement Series 256 (1), 9, 2021 | 25 | 2021 |
Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ... arXiv preprint arXiv:2008.06388, 2020 | 24 | 2020 |