Open Access
Issue
A&A
Volume 700, August 2025
Article Number A259
Number of page(s) 9
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/202555620
Published online 26 August 2025
  1. Alam, S., Albareti, F. D., Prieto, C. A., et al. 2015, ApJS, 219, 12 [NASA ADS] [CrossRef] [Google Scholar]
  2. Asadi, V., Zonoozi, A. H., Haghi, H., et al. 2025, ApJ, in press, [arXiv:2506.21067] [Google Scholar]
  3. Bellstedt, S., Driver, S. P., Robotham, A. S., et al. 2020, MNRAS, 496, 3235 [NASA ADS] [CrossRef] [Google Scholar]
  4. Breiman, L. 2001, Mach. Learn., 45, 5 [Google Scholar]
  5. Cavuoti, S., Brescia, M., D’Abrusco, R., Longo, G., & Paolillo, M. 2014, MNRAS, 437, 968 [NASA ADS] [CrossRef] [Google Scholar]
  6. Celebi, M. E., Kingravi, H. A., & Vela, P. A. 2013, Expert Syst. Appl., 40, 200 [CrossRef] [Google Scholar]
  7. Chaini, S., Bagul, A., Deshpande, A., et al. 2023, MNRAS, 518, 3123 [Google Scholar]
  8. Chawla, N. V., Bowyer, K. W., Hall, L. O., & Kegelmeyer, W. P. 2002, J. Artif. Intell. Res., 16, 321 [CrossRef] [Google Scholar]
  9. Christen, P., Hand, D. J., & Kirielle, N. 2023, ACM Comput. Surv., 56, 1 [Google Scholar]
  10. Clarke, A., Scaife, A., Greenhalgh, R., & Griguta, V. 2020, A&A, 639, A84 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  11. Coil, A. L., Blanton, M. R., Burles, S. M., et al. 2011, ApJ, 714, 8 [Google Scholar]
  12. Cook, T. L., Bandi, B., Philipsborn, S., et al. 2024, MNRAS, 535, 2129 [Google Scholar]
  13. Cool, R. J., Moustakas, J., Blanton, M. R., et al. 2013, ApJ, 767, 118 [NASA ADS] [CrossRef] [Google Scholar]
  14. Cunha, P., & Humphrey, A. 2022, A&A, 666, A87 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  15. Cutri, R., Wright, E., Conrow, T., et al. 2013, Explanatory Supplement to the AllWISE Data Release Products [Google Scholar]
  16. de Jong, J. T., Kleijn, G. A. V., Boxhoorn, D. R., et al. 2015, A&A, 582, A62 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  17. Dey, A., Schlegel, D. J., Lang, D., et al. 2019, ApJ, 157, 168 [CrossRef] [Google Scholar]
  18. Edge, A., Sutherland, W., Kuijken, K., et al. 2013, The Messenger, 154, 32 [NASA ADS] [Google Scholar]
  19. Emmanuel, T., Maupong, T., Mpoeleng, D., et al. 2021, J. Big data, 8, 1 [Google Scholar]
  20. Fotopoulou, S. 2024, Astron. Comput., 48, 100851 [Google Scholar]
  21. Fotopoulou, S., & Paltani, S. 2018, A&A, 619, A14 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  22. Garilli, B., Guzzo, L., Scodeggio, M., et al. 2014, A&A, 562, A23 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  23. Geurts, P., Ernst., D., & Wehenkel, L. 2006, Mach. Learn., 63, 3 [Google Scholar]
  24. Gupta, S., & Gupta, A. 2019, Procedia Comput. Sci., 161, 466 [Google Scholar]
  25. Hastie, T., Tibshirani, R., & Friedman, J. 2008, The elements of statistical learning: data mining, inference, and prediction, 337 [Google Scholar]
  26. Hewett, P. C., & Wild, V. 2010, MNRAS, 405, 2302 [NASA ADS] [Google Scholar]
  27. Hudelot, P., Cuillandre, J.-Ch., Withington, K., et al. 2012, VizieR Online Data Catalog: 2317, II [Google Scholar]
  28. Ivezić, Ž., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111 [Google Scholar]
  29. James, G., Witten, D., Hastie, T., Tibshirani, R., & Taylor, J. 2023, An introduction to statistical learning, 503 [Google Scholar]
  30. Jarvis, M. J., Bonfield, D. G., Bruce, V., et al. 2013, MNRAS, 428, 1281 [CrossRef] [Google Scholar]
  31. Jones, D. H., Saunders, W., Colless, M., et al. 2004, MNRAS, 355, 747 [NASA ADS] [CrossRef] [Google Scholar]
  32. Jones, D. H., Read, M. A., Saunders, W., et al. 2009, MNRAS, 399, 683 [Google Scholar]
  33. Krakowski, T., Małek, K., Bilicki, M., et al. 2016, A&A, 596, A39 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  34. Kurcz, A., Bilicki, M., Solarz, A., et al. 2016, A&A, 592, A25 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  35. Lawlor, D., Budavári, T., & Mahoney, M. W. 2016, ApJ, 833, 26 [Google Scholar]
  36. Le Fèvre, O., Cassata, P., Cucciati, O., et al. 2013, A&A, 559, A14 [Google Scholar]
  37. Liske, J., Baldry, I. K., Driver, S. P., et al. 2015, MNRAS, 452, 2087 [Google Scholar]
  38. Logan, C., & Fotopoulou, S. 2020, A&A, 633, A154 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  39. Lourens, M., Trager, S., Kim, Y., Telea, A., & Roerdink, J. 2024, A&A, 690, A224 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  40. Maćkiewicz, A., & Ratajczak, W. 1993, Comput. Geosci., 19, 303 [CrossRef] [Google Scholar]
  41. MacQueen, J. 1967, Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, 1, 281 [Google Scholar]
  42. Mainzer, A., Bauer, J., Grav, T., et al. 2011, ApJ, 731, 53 [Google Scholar]
  43. McInnes, L. 2017, J. Open Source Softw., 2, 2052 [Google Scholar]
  44. McInnes, L., Healy, J., Saul, N., & Großberger, L. 2018, stat, 1050, 6 [Google Scholar]
  45. Nakoneczny, S., Bilicki, M., Solarz, A., et al. 2019, A&A, 624, A13 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  46. Nakoneczny, S., Bilicki, M., Pollo, A., et al. 2021, A&A, 649, A81 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  47. Pantoja, R., Catelan, M., Pichara, K., & Protopapas, P. 2022, MNRAS, 517, 3660 [Google Scholar]
  48. Policar, P. G., Stražar, M., & Zupan, B. 2021, Mach. Learn., 112, 721 [Google Scholar]
  49. Reddy, Y., Viswanath, P., & Reddy, B. E. 2018, Int. J. Eng. Technol, 7, 81 [Google Scholar]
  50. Richards, G. T., Fan, X., Schneider, D. P., et al. 2001, ApJ, 121, 2308 [Google Scholar]
  51. Settles, B. 2009, Active Learning Literature Survey, Technical Report, University of Wisconsin-Madison Department of Computer Sciences [Google Scholar]
  52. Slijepcevic, I. V., Scaife, A. M., Walmsley, M., et al. 2022, MNRAS, 514, 2599 [NASA ADS] [CrossRef] [Google Scholar]
  53. Stehman, S. V. 1997, Rem. Sens. Environ., 62, 77 [NASA ADS] [CrossRef] [Google Scholar]
  54. Stern, D., Assef, R. J., Benford, D. J., et al. 2012, ApJ, 753, 30 [Google Scholar]
  55. Van Engelen, J. E., & Hoos, H. H. 2020, Mach. Learn., 109, 373 [Google Scholar]
  56. Villar, V. A., Hosseinzadeh, G., Berger, E., et al. 2020, ApJ, 905, 94 [NASA ADS] [CrossRef] [Google Scholar]
  57. von Marttens, R., Marra, V., Quartin, M., et al. 2024, MNRAS, 527, 3347 [Google Scholar]
  58. Wright, E. L., Eisenhardt, P. R., Mainzer, A. K., et al. 2010, ApJ, 140, 1868 [Google Scholar]
  59. Zeraatgari, F. Z., Hafezianzadeh, F., Zhang, Y., et al. 2024, MNRAS, 527, 4677 [Google Scholar]
  60. Zhou, Z.-H. 2025, Ensemble methods: foundations and algorithms (CRC Press) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.