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L Bisigello, C J Conselice, M Baes, M Bolzonella, M Brescia, S Cavuoti, O Cucciati, A Humphrey, L K Hunt, C Maraston, L Pozzetti, C Tortora, S E van Mierlo, N Aghanim, N Auricchio, M Baldi, R Bender, C Bodendorf, D Bonino, E Branchini, J Brinchmann, S Camera, V Capobianco, C Carbone, J Carretero, F J Castander, M Castellano, A Cimatti, G Congedo, L Conversi, Y Copin, L Corcione, F Courbin, M Cropper, A Da Silva, H Degaudenzi, M Douspis, F Dubath, C A J Duncan, X Dupac, S Dusini, S Farrens, S Ferriol, M Frailis, E Franceschi, P Franzetti, M Fumana, B Garilli, W Gillard, B Gillis, C Giocoli, A Grazian, F Grupp, L Guzzo, S V H Haugan, W Holmes, F Hormuth, A Hornstrup, K Jahnke, M Kümmel, S Kermiche, A Kiessling, M Kilbinger, R Kohley, M Kunz, H Kurki-Suonio, S Ligori, P B Lilje, I Lloro, E Maiorano, O Mansutti, O Marggraf, K Markovic, F Marulli, R Massey, S Maurogordato, E Medinaceli, M Meneghetti, E Merlin, G Meylan, M Moresco, L Moscardini, E Munari, S M Niemi, C Padilla, S Paltani, F Pasian, K Pedersen, V Pettorino, G Polenta, M Poncet, L Popa, F Raison, A Renzi, J Rhodes, G Riccio, H -W Rix, E Romelli, M Roncarelli, C Rosset, E Rossetti, R Saglia, D Sapone, B Sartoris, P Schneider, M Scodeggio, A Secroun, G Seidel, C Sirignano, G Sirri, L Stanco, P Tallada-Crespí, D Tavagnacco, A N Taylor, I Tereno, R Toledo-Moreo, F Torradeflot, I Tutusaus, E A Valentijn, L Valenziano, T Vassallo, Y Wang, A Zacchei, G Zamorani, J Zoubian, S Andreon, S Bardelli, A Boucaud, C Colodro-Conde, D Di Ferdinando, J Graciá-Carpio, V Lindholm, D Maino, S Mei, V Scottez, F Sureau, M Tenti, E Zucca, A S Borlaff, M Ballardini, A Biviano, E Bozzo, C Burigana, R Cabanac, A Cappi, C S Carvalho, S Casas, G Castignani, A Cooray, J Coupon, H M Courtois, J Cuby, S Davini, G De Lucia, G Desprez, H Dole, J A Escartin, S Escoffier, M Farina, S Fotopoulou, K Ganga, J Garcia-Bellido, K George, F Giacomini, G Gozaliasl, H Hildebrandt, I Hook, M Huertas-Company, V Kansal, E Keihanen, C C Kirkpatrick, A Loureiro, J F Macías-Pérez, M Magliocchetti, G Mainetti, S Marcin, M Martinelli, N Martinet, R B Metcalf, P Monaco, G Morgante, S Nadathur, A A Nucita, L Patrizii, A Peel, D Potter, A Pourtsidou, M Pöntinen, P Reimberg, A G Sánchez, Z Sakr, M Schirmer, E Sefusatti, M Sereno, J Stadel, R Teyssier, C Valieri, J Valiviita, M Viel, (2022). Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes andH-band images. Monthly Notices of the Royal Astronomical Society, 520, 3529-3548. ISSN 0035-8711. eISSN . http://dx.doi.org/10.1093/mnras/stac3810
IEEE
L Bisigello, C J Conselice, M Baes, M Bolzonella, M Brescia, S Cavuoti, O Cucciati, A Humphrey, L K Hunt, C Maraston, L Pozzetti, C Tortora, S E van Mierlo, N Aghanim, N Auricchio, M Baldi, R Bender, C Bodendorf, D Bonino, E Branchini, J Brinchmann, S Camera, V Capobianco, C Carbone, J Carretero, F J Castander, M Castellano, A Cimatti, G Congedo, L Conversi, Y Copin, L Corcione, F Courbin, M Cropper, A Da Silva, H Degaudenzi, M Douspis, F Dubath, C A J Duncan, X Dupac, S Dusini, S Farrens, S Ferriol, M Frailis, E Franceschi, P Franzetti, M Fumana, B Garilli, W Gillard, B Gillis, C Giocoli, A Grazian, F Grupp, L Guzzo, S V H Haugan, W Holmes, F Hormuth, A Hornstrup, K Jahnke, M Kümmel, S Kermiche, A Kiessling, M Kilbinger, R Kohley, M Kunz, H Kurki-Suonio, S Ligori, P B Lilje, I Lloro, E Maiorano, O Mansutti, O Marggraf, K Markovic, F Marulli, R Massey, S Maurogordato, E Medinaceli, M Meneghetti, E Merlin, G Meylan, M Moresco, L Moscardini, E Munari, S M Niemi, C Padilla, S Paltani, F Pasian, K Pedersen, V Pettorino, G Polenta, M Poncet, L Popa, F Raison, A Renzi, J Rhodes, G Riccio, H -W Rix, E Romelli, M Roncarelli, C Rosset, E Rossetti, R Saglia, D Sapone, B Sartoris, P Schneider, M Scodeggio, A Secroun, G Seidel, C Sirignano, G Sirri, L Stanco, P Tallada-Crespí, D Tavagnacco, A N Taylor, I Tereno, R Toledo-Moreo, F Torradeflot, I Tutusaus, E A Valentijn, L Valenziano, T Vassallo, Y Wang, A Zacchei, G Zamorani, J Zoubian, S Andreon, S Bardelli, A Boucaud, C Colodro-Conde, D Di Ferdinando, J Graciá-Carpio, V Lindholm, D Maino, S Mei, V Scottez, F Sureau, M Tenti, E Zucca, A S Borlaff, M Ballardini, A Biviano, E Bozzo, C Burigana, R Cabanac, A Cappi, C S Carvalho, S Casas, G Castignani, A Cooray, J Coupon, H M Courtois, J Cuby, S Davini, G De Lucia, G Desprez, H Dole, J A Escartin, S Escoffier, M Farina, S Fotopoulou, K Ganga, J Garcia-Bellido, K George, F Giacomini, G Gozaliasl, H Hildebrandt, I Hook, M Huertas-Company, V Kansal, E Keihanen, C C Kirkpatrick, A Loureiro, J F Macías-Pérez, M Magliocchetti, G Mainetti, S Marcin, M Martinelli, N Martinet, R B Metcalf, P Monaco, G Morgante, S Nadathur, A A Nucita, L Patrizii, A Peel, D Potter, A Pourtsidou, M Pöntinen, P Reimberg, A G Sánchez, Z Sakr, M Schirmer, E Sefusatti, M Sereno, J Stadel, R Teyssier, C Valieri, J Valiviita, M Viel, "Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes andH-band images" in Monthly Notices of the Royal Astronomical Society, vol. 520, pp. 3529-3548, 2022.
10.1093/mnras/stac3810
BIBTEX
@article{60365,
author = {L Bisigello and C J Conselice and M Baes and M Bolzonella and M Brescia and S Cavuoti and O Cucciati and A Humphrey and L K Hunt and C Maraston and L Pozzetti and C Tortora and S E van Mierlo and N Aghanim and N Auricchio and M Baldi and R Bender and C Bodendorf and D Bonino and E Branchini and J Brinchmann and S Camera and V Capobianco and C Carbone and J Carretero and F J Castander and M Castellano and A Cimatti and G Congedo and L Conversi and Y Copin and L Corcione and F Courbin and M Cropper and A Da Silva and H Degaudenzi and M Douspis and F Dubath and C A J Duncan and X Dupac and S Dusini and S Farrens and S Ferriol and M Frailis and E Franceschi and P Franzetti and M Fumana and B Garilli and W Gillard and B Gillis and C Giocoli and A Grazian and F Grupp and L Guzzo and S V H Haugan and W Holmes and F Hormuth and A Hornstrup and K Jahnke and M Kümmel and S Kermiche and A Kiessling and M Kilbinger and R Kohley and M Kunz and H Kurki-Suonio and S Ligori and P B Lilje and I Lloro and E Maiorano and O Mansutti and O Marggraf and K Markovic and F Marulli and R Massey and S Maurogordato and E Medinaceli and M Meneghetti and E Merlin and G Meylan and M Moresco and L Moscardini and E Munari and S M Niemi and C Padilla and S Paltani and F Pasian and K Pedersen and V Pettorino and G Polenta and M Poncet and L Popa and F Raison and A Renzi and J Rhodes and G Riccio and H -W Rix and E Romelli and M Roncarelli and C Rosset and E Rossetti and R Saglia and D Sapone and B Sartoris and P Schneider and M Scodeggio and A Secroun and G Seidel and C Sirignano and G Sirri and L Stanco and P Tallada-Crespí and D Tavagnacco and A N Taylor and I Tereno and R Toledo-Moreo and F Torradeflot and I Tutusaus and E A Valentijn and L Valenziano and T Vassallo and Y Wang and A Zacchei and G Zamorani and J Zoubian and S Andreon and S Bardelli and A Boucaud and C Colodro-Conde and D Di Ferdinando and J Graciá-Carpio and V Lindholm and D Maino and S Mei and V Scottez and F Sureau and M Tenti and E Zucca and A S Borlaff and M Ballardini and A Biviano and E Bozzo and C Burigana and R Cabanac and A Cappi and C S Carvalho and S Casas and G Castignani and A Cooray and J Coupon and H M Courtois and J Cuby and S Davini and G De Lucia and G Desprez and H Dole and J A Escartin and S Escoffier and M Farina and S Fotopoulou and K Ganga and J Garcia-Bellido and K George and F Giacomini and G Gozaliasl and H Hildebrandt and I Hook and M Huertas-Company and V Kansal and E Keihanen and C C Kirkpatrick and A Loureiro and J F Macías-Pérez and M Magliocchetti and G Mainetti and S Marcin and M Martinelli and N Martinet and R B Metcalf and P Monaco and G Morgante and S Nadathur and A A Nucita and L Patrizii and A Peel and D Potter and A Pourtsidou and M Pöntinen and P Reimberg and A G Sánchez and Z Sakr and M Schirmer and E Sefusatti and M Sereno and J Stadel and R Teyssier and C Valieri and J Valiviita and M Viel},
title = {Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes andH-band images},
journal = {Monthly Notices of the Royal Astronomical Society},
year = 2022,
pages = {3529-3548},
volume = 520
}