Free Access
Issue
A&A
Volume 624, April 2019
Article Number A13
Number of page(s) 15
Section Catalogs and data
DOI https://doi.org/10.1051/0004-6361/201834794
Published online 01 April 2019
  1. Abadi, M., Agarwal, A., Barham, P., et al. 2015, TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems, Software available from: https://www.tensorflow.org/ [Google Scholar]
  2. Abolfathi, B., Aguado, D. S., Aguilar, G., et al. 2018, ApJS, 235, 42 [NASA ADS] [CrossRef] [Google Scholar]
  3. Assef, R. J., Stern, D., Kochanek, C. S., et al. 2013, ApJ, 772, 26 [NASA ADS] [CrossRef] [Google Scholar]
  4. Assef, R. J., Stern, D., Noirot, G., et al. 2018, ApJS, 234, 23 [NASA ADS] [CrossRef] [Google Scholar]
  5. Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  6. Bilicki, M., Hoekstra, H., Brown, M. J. I., et al. 2018, A&A, 616, A69 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  7. Blanton, M. R., Bershady, M. A., Abolfathi, B., et al. 2017, AJ, 154, 28 [NASA ADS] [CrossRef] [Google Scholar]
  8. Bovy, J., Hennawi, J. F., Hogg, D. W., et al. 2011, ApJ, 729, 141 [NASA ADS] [CrossRef] [Google Scholar]
  9. Bovy, J., Myers, A. D., Hennawi, J. F., et al. 2012, ApJ, 749, 41 [NASA ADS] [CrossRef] [Google Scholar]
  10. Breiman, L. 1996, Mach. Learn., 24, 123 [Google Scholar]
  11. Breiman, L. 2001, Mach. Learn., 45, 5 [CrossRef] [Google Scholar]
  12. Brescia, M., Cavuoti, S., & Longo, G. 2015, MNRAS, 450, 3893 [NASA ADS] [CrossRef] [Google Scholar]
  13. Capaccioli, M., Schipani, P., de Paris, G., et al. 2012, Science from the NextGeneration Imaging and Spectroscopic Surveys, 1 [Google Scholar]
  14. Carrasco, D., Barrientos, L. F., Pichara, K., et al. 2015, A&A, 584, A44 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  15. Chen, T., & Guestrin, C. 2016, Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’16 (New York, NY, USA: ACM), 785 [Google Scholar]
  16. Chollet, F. 2015, keras, https://github.com/fchollet/keras [Google Scholar]
  17. Croom, S. M., Smith, R. J., Boyle, B. J., et al. 2004, MNRAS, 349, 1397 [NASA ADS] [CrossRef] [Google Scholar]
  18. Croom, S. M., Richards, G. T., Shanks, T., et al. 2009, MNRAS, 392, 19 [NASA ADS] [CrossRef] [Google Scholar]
  19. Cuoco, A., Bilicki, M., Xia, J.-Q., & Branchini, E. 2017, ApJS, 232, 10 [NASA ADS] [CrossRef] [Google Scholar]
  20. Cutri, R. M., et al. 2013, VizieR Online Data Catalog: II/328 [Google Scholar]
  21. Dawson, K. S., Schlegel, D. J., Ahn, C. P., et al. 2013, AJ, 145, 10 [Google Scholar]
  22. de Jong, J. T. A., Kuijken, K., Applegate, D., et al. 2013, The Messenger, 154, 44 [NASA ADS] [Google Scholar]
  23. de Jong, J. T. A., Verdoes Kleijn, G. A., Boxhoorn, D. R., et al. 2015, A&A, 582, A62 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. de Jong, J. T. A., Verdoes Kleijn, G. A., Erben, T., et al. 2017, A&A, 604, A134 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  25. de Jong, R. 2011, The Messenger, 145, 14 [NASA ADS] [Google Scholar]
  26. DESI Collaboration (Aghamousa, A., et al.) 2016, ArXiv e-prints [arXiv:1611.00036] [Google Scholar]
  27. DiPompeo, M. A., Myers, A. D., Hickox, R. C., Geach, J. E., & Hainline, K. N. 2014, MNRAS, 442, 3443 [NASA ADS] [CrossRef] [Google Scholar]
  28. DiPompeo, M. A., Bovy, J., Myers, A. D., & Lang, D. 2015, MNRAS, 452, 3124 [NASA ADS] [CrossRef] [Google Scholar]
  29. DiPompeo, M. A., Hickox, R. C., & Myers, A. D. 2016, MNRAS, 456, 924 [NASA ADS] [CrossRef] [Google Scholar]
  30. DiPompeo, M. A., Hickox, R. C., Eftekharzadeh, S., & Myers, A. D. 2017, MNRAS, 469, 4630 [NASA ADS] [CrossRef] [Google Scholar]
  31. Edelson, R., & Malkan, M. 2012, ApJ, 751, 52 [NASA ADS] [CrossRef] [Google Scholar]
  32. Edge, A., Sutherland, W., Kuijken, K., et al. 2013, The Messenger, 154, 32 [NASA ADS] [Google Scholar]
  33. Eftekharzadeh, S., Myers, A. D., White, M., et al. 2015, MNRAS, 453, 2779 [NASA ADS] [CrossRef] [Google Scholar]
  34. Fotopoulou, S., & Paltani, S. 2018, A&A, 619, A14 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  35. Gaia Collaboration (Prusti, T., et al.) 2016, A&A, 595, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  36. Gaia Collaboration (Brown, A. G. A., et al.) 2018a, A&A, 616, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  37. Gaia Collaboration (Mignard, F., et al.) 2018b, A&A, 616, A14 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  38. Harrell, F. 2001, Chapter 5: Resampling, Validating, and Simplifying the Model, 3, 88 [Google Scholar]
  39. Haykin, S. 1998, Neural Networks: A Comprehensive Foundation, 2nd edn. (Upper Saddle River, NJ, USA: Prentice Hall PTR) [Google Scholar]
  40. Heintz, K. E., Fynbo, J. P. U., Ledoux, C., et al. 2018, A&A, 615, A43 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  41. Hernitschek, N., Schlafly, E. F., Sesar, B., et al. 2016, ApJ, 817, 73 [NASA ADS] [CrossRef] [Google Scholar]
  42. Ho, S., Agarwal, N., Myers, A. D., et al. 2015, JCAP, 5, 040 [NASA ADS] [CrossRef] [Google Scholar]
  43. Jarrett, T. H., Cohen, M., Masci, F., et al. 2011, ApJ, 735, 112 [NASA ADS] [CrossRef] [Google Scholar]
  44. Jarrett, T. H., Cluver, M. E., Magoulas, C., et al. 2017, ApJ, 836, 182 [NASA ADS] [CrossRef] [Google Scholar]
  45. Kauffmann, G., Heckman, T. M., Tremonti, C., et al. 2003, MNRAS, 346, 1055 [Google Scholar]
  46. Kewley, L. J., Maier, C., Yabe, K., et al. 2013, ApJ, 774, L10 [Google Scholar]
  47. Kluyver, T., Ragan-Kelley, B., Pérez, F., et al. 2016, Positioning and Power in Academic Publishing: Players, Agents and Agendas, 20th International Conference on Electronic Publishing, Göttingen, Germany, June 7–9, 2016, 87 [Google Scholar]
  48. Kohonen, T. (ed.) 1997, in Self-organizing Maps (Berlin, Heidelberg: Springer-Verlag) [Google Scholar]
  49. Kormendy, J., & Ho, L. C. 2013, ARA&A, 51, 511 [Google Scholar]
  50. Kuijken, K. 2008, A&A, 482, 1053 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  51. Kuijken, K. 2011, The Messenger, 146, 8 [NASA ADS] [Google Scholar]
  52. Kuijken, K., Heymans, C., Hildebrandt, H., et al. 2015, MNRAS, 454, 3500 [NASA ADS] [CrossRef] [Google Scholar]
  53. Kurcz, A., Bilicki, M., Solarz, A., et al. 2016, A&A, 592, A25 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  54. Laurent, P., Eftekharzadeh, S., Le Goff, J.-M., et al. 2017, JCAP, 7, 017 [CrossRef] [Google Scholar]
  55. Leistedt, B., Peiris, H. V., & Roth, N. 2014, Phys. Rev. Lett., 113, 221301 [NASA ADS] [CrossRef] [Google Scholar]
  56. Lindegren, L., Hernández, J., Bombrun, A., et al. 2018, A&A, 616, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  57. Maddox, N., Hewett, P. C., Warren, S. J., & Croom, S. M. 2008, MNRAS, 386, 1605 [NASA ADS] [CrossRef] [Google Scholar]
  58. Maddox, N., Hewett, P. C., Péroux, C., Nestor, D. B., & Wisotzki, L. 2012, MNRAS, 424, 2876 [NASA ADS] [CrossRef] [Google Scholar]
  59. Masci, F. J., Hoffman, D. I., Grillmair, C. J., & Cutri, R. M. 2014, AJ, 148, 21 [NASA ADS] [CrossRef] [Google Scholar]
  60. Masters, D., Capak, P., Stern, D., et al. 2015, ApJ, 813, 53 [NASA ADS] [CrossRef] [Google Scholar]
  61. Möller, A., Ruhlmann-Kleider, V., Leloup, C., et al. 2016, JCAP, 12, 008 [NASA ADS] [CrossRef] [Google Scholar]
  62. Pâris, I., Petitjean, P., Aubourg, É., et al. 2018, A&A, 613, A51 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  63. Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, J. Mach. Learn. Res., 12, 2825 [Google Scholar]
  64. Peth, M. A., Ross, N. P., & Schneider, D. P. 2011, AJ, 141, 105 [NASA ADS] [CrossRef] [Google Scholar]
  65. Piramuthu, S., & Sikora, R. T. 2009, Expert Syst. Appl., 36, 3401 [CrossRef] [Google Scholar]
  66. Richards, G. T., Fan, X., Newberg, H. J., et al. 2002, AJ, 123, 2945 [NASA ADS] [CrossRef] [Google Scholar]
  67. Richards, G. T., Nichol, R. C., Gray, A. G., et al. 2004, ApJS, 155, 257 [NASA ADS] [CrossRef] [Google Scholar]
  68. Richards, G. T., Myers, A. D., Gray, A. G., et al. 2009a, ApJS, 180, 67 [NASA ADS] [CrossRef] [Google Scholar]
  69. Richards, G. T., Deo, R. P., Lacy, M., et al. 2009b, AJ, 137, 3884 [NASA ADS] [CrossRef] [Google Scholar]
  70. Richards, G. T., Myers, A. D., Peters, C. M., et al. 2015, ApJS, 219, 39 [NASA ADS] [CrossRef] [Google Scholar]
  71. Scranton, R., Ménard, B., Richards, G. T., et al. 2005, ApJ, 633, 589 [NASA ADS] [CrossRef] [Google Scholar]
  72. Secrest, N. J., Dudik, R. P., Dorland, B. N., et al. 2015, ApJS, 221, 12 [NASA ADS] [CrossRef] [Google Scholar]
  73. Sherwin, B. D., Das, S., Hajian, A., et al. 2012, Phys. Rev. D, 86, 083006 [NASA ADS] [CrossRef] [Google Scholar]
  74. Spiniello, C., Agnello, A., Napolitano, N. R., et al. 2018, MNRAS, 480, 1163 [NASA ADS] [CrossRef] [Google Scholar]
  75. Stern, D., Assef, R. J., Benford, D. J., et al. 2012, ApJ, 753, 30 [NASA ADS] [CrossRef] [Google Scholar]
  76. Stölzner, B., Cuoco, A., Lesgourgues, J., & Bilicki, M. 2018, Phys. Rev. D, 97, 063506 [NASA ADS] [CrossRef] [Google Scholar]
  77. Strauss, M. A., Weinberg, D. H., Lupton, R. H., et al. 2002, AJ, 124, 1810 [NASA ADS] [CrossRef] [Google Scholar]
  78. Taylor, M. B. 2005, in Astronomical Data Analysis Software and Systems XIV, eds. P. Shopbell, M. Britton, & R. Ebert, ASP Conf. Ser., 347, 29 [Google Scholar]
  79. van der Maaten, L., & Hinton, G. 2008, J. Mach. Learn. Res., 9, 2579 [Google Scholar]
  80. Venemans, B. P., Verdoes Kleijn, G. A., Mwebaze, J., et al. 2015, MNRAS, 453, 2259 [NASA ADS] [CrossRef] [Google Scholar]
  81. Warren, S. J., Hewett, P. C., & Foltz, C. B. 2000, MNRAS, 312, 827 [NASA ADS] [CrossRef] [Google Scholar]
  82. Wright, E. L., Eisenhardt, P. R. M., Mainzer, A. K., et al. 2010, AJ, 140, 1868 [NASA ADS] [CrossRef] [Google Scholar]
  83. Wu, X.-B., Hao, G., Jia, Z., Zhang, Y., & Peng, N. 2012, AJ, 144, 49 [NASA ADS] [CrossRef] [Google Scholar]
  84. Yèche, C., Petitjean, P., Rich, J., et al. 2010, A&A, 523, A14 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  85. York, D. G., Adelman, J., Anderson, Jr., J. E., et al. 2000, AJ, 120, 1579 [CrossRef] [Google Scholar]

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