EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 699 (July 2025) A&A, 699 (2025) A36 References
Open Access
Issue
A&A
Volume 699, July 2025
Article Number A36
Number of page(s) 17
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/202453293
Published online 27 June 2025
  1. Alom, M. Z., Taha, T. M., Yakopcic, C., et al. 2018, arXiv e-prints [arXiv:1803.01164] [Google Scholar]
  2. Andreon, S., Gargiulo, G., Longo, G., Tagliaferri, R., & Capuano, N. 2000, MNRAS, 319, 700 [Google Scholar]
  3. Arulkumaran, K., Deisenroth, M. P., Brundage, M., & Bharath, A. A. 2017, IEEE Signal Process. Mag., 34, 26 [Google Scholar]
  4. Axelrod, T., Connolly, A., Ivezic, Z., et al. 2004, in American Astronomical Society Meeting Abstracts, 205, 108.11 [Google Scholar]
  5. Bellm, E. C., Kulkarni, S. R., Barlow, T., et al. 2019, PASP, 131, 068003 [Google Scholar]
  6. Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  7. Beskin, G., Biryukov, A., Gutaev, A., et al. 2023, Photonics, 10, 1352 [Google Scholar]
  8. Bialek, S., Bertin, E., Fabbro, S., et al. 2024, MNRAS, 531, 403 [Google Scholar]
  9. Cabrera-Vives, G., Reyes, I., Förster, F., Estévez, P. A., & Maureira, J.-C. 2017, ApJ, 836, 97 [NASA ADS] [CrossRef] [Google Scholar]
  10. Cao, L., Jia, P., Li, J., et al. 2025, AJ, 169, 215 [Google Scholar]
  11. Casas, J. M., González-Nuevo, J., Bonavera, L., et al. 2022, A&A, 658, A110 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Castro-Tirado, A. J., Soldán, J., Bernas, M., et al. 1999, A&AS, 138, 583 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  13. Deng, J., Dong, W., Socher, R., et al. 2009, in 2009 IEEE Conf. Comput. Vis. Pattern Recognit., 248 [CrossRef] [Google Scholar]
  14. Dyer, M. J., Steeghs, D., Galloway, D. K., et al. 2020, in Ground-based and airborne telescopes VIII, 11445, 1355 [Google Scholar]
  15. Gaia Collaboration 2018, VizieR Online Data Catalog: I [Google Scholar]
  16. Gal-Yam, A., Ofek, E. O., Poznanski, D., et al. 2006, ApJ, 639, 331 [NASA ADS] [CrossRef] [Google Scholar]
  17. Gal-Yam, A., Kasliwal, M. M., Arcavi, I., et al. 2011, ApJ, 736, 159 [NASA ADS] [CrossRef] [Google Scholar]
  18. Girshick, R. 2015, in Proc. IEEE Int. Conf. Comput. Vis., 1440 [Google Scholar]
  19. Gromadzki, M., Hamanowicz, A., Wyrzykowski, L., et al. 2019, A&A, 622, L2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  20. Haigh, C., Chamba, N., Venhola, A., et al. 2021, A&A, 645, A107 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  21. Han, X., Xiao, Y., Zhang, P., et al. 2021, PASP, 133, 065001 [NASA ADS] [CrossRef] [Google Scholar]
  22. Han, K., Wang, Y., Chen, H., et al. 2022, IEEE Trans. Pattern Anal. Mach. Intell., 45, 87 [Google Scholar]
  23. He, K., Gkioxari, G., Dollár, P., & Girshick, R. 2017, in Proc. IEEE Int. Conf. Comput. Vis., 2961 [Google Scholar]
  24. He, Z., Qiu, B., Luo, A.-L., et al. 2021, MNRAS, 508, 2039 [NASA ADS] [CrossRef] [Google Scholar]
  25. Holland, J. H. 1992, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence (MIT press) [Google Scholar]
  26. Ivezić, Ž., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111 [Google Scholar]
  27. Jia, P., Sun, R., Wang, W., Cai, D., & Liu, H. 2017, MNRAS, 470, 1950 [Google Scholar]
  28. Jia, P., Liu, Q., & Sun, Y. 2020, AJ, 159, 212 [NASA ADS] [CrossRef] [Google Scholar]
  29. Jia, P., Wang, W., Ning, R., & Xue, X. 2022, Opt. Express, 30, 21362 [Google Scholar]
  30. Jia, P., Jia, Q., Jiang, T., & Yang, Z. 2023a, Astron. Comput., 44, 100732 [Google Scholar]
  31. Jia, P., Zheng, Y., Wang, M., & Yang, Z. 2023b, Astron. Comput., 42, 100687 [Google Scholar]
  32. Jia, P., Jia, Q., Jiang, T., & Liu, J. 2023c, AJ, 165, 233 [Google Scholar]
  33. Jiang, P., Ergu, D., Liu, F., Cai, Y., & Ma, B. 2022, Procedia Comput. Sci., 199, 1066 [Google Scholar]
  34. Kaiser, N. 2004, in Ground-based Telescopes, 5489, 11 [Google Scholar]
  35. Kou, S. 2019, in AOPC 2019: Space Optics, Telescopes, and Instrumentation, 11341, 99 [Google Scholar]
  36. Lang, D., Hogg, D. W., Mierle, K., Blanton, M., & Roweis, S. 2010, AJ, 139, 1782 [Google Scholar]
  37. Law, N. M., Corbett, H., Galliher, N. W., et al. 2022, PASP, 134, 035003 [Google Scholar]
  38. Liu, J., Soria, R., Wu, X.-F., Wu, H., & Shang, Z. 2021, An. Acad. Bras. Cienc., 93 [Google Scholar]
  39. Lokhorst, D. M., Abraham, R. G., van Dokkum, P., & Chen, S. 2020, in Ground-based and Airborne Telescopes VIII, 11445, 492 [Google Scholar]
  40. Masci, F. J., Laher, R. R., Rusholme, B., et al. 2018, PASP, 131, 018003 [Google Scholar]
  41. Mirjalili, S., & Mirjalili, S. 2019, Evol. Algorithms Neural Netw.: Theory Appl., 43 [Google Scholar]
  42. Myers, A. D., Moustakas, J., Bailey, S., et al. 2023, AJ, 165, 50 [NASA ADS] [CrossRef] [Google Scholar]
  43. Nousiainen, J., Rajani, C., Kasper, M., et al. 2022, A&A, 664, A71 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  44. Osband, I., Blundell, C., Pritzel, A., & Van Roy, B. 2016, Adv. Neural Inf. Process. Syst., 29 [Google Scholar]
  45. Panes, B., Eckner, C., Hendriks, L., et al. 2021, A&A, 656, A62 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  46. Poole, D. L., & Mackworth, A. K. 2010, Artificial Intelligence: Foundations of Computational Agents (Cambridge University Press) [CrossRef] [Google Scholar]
  47. Rau, A., Kulkarni, S. R., Law, N. M., et al. 2009, PASP, 121, 1334 [NASA ADS] [CrossRef] [Google Scholar]
  48. Ren, S., He, K., Girshick, R., & Sun, J. 2015, Adv. Neural Inf. Process. Syst., 28 [Google Scholar]
  49. Rezaei, S., McKean, J. P., Biehl, M., & Javadpour, A. 2022, MNRAS, 510, 5891 [NASA ADS] [CrossRef] [Google Scholar]
  50. Rix, H.-W., Barden, M., Beckwith, S. V., et al. 2004, ApJS, 152, 163 [CrossRef] [Google Scholar]
  51. Russakovsky, O., Deng, J., Su, H., et al. 2015, Int. J. Comput. Vis., 115, 211 [Google Scholar]
  52. Silver, D., Huang, A., Maddison, C. J., et al. 2016, Nature, 529, 484 [CrossRef] [PubMed] [Google Scholar]
  53. Steeghs, D., Galloway, D., Ackley, K., et al. 2022, MNRAS, 511, 2405 [NASA ADS] [CrossRef] [Google Scholar]
  54. Stoppa, F., Bhattacharyya, S., de Austri, R. R., et al. 2023, A&A, 680, A109 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  55. Sun, R.-y., Yu, P.-p., & Zhang, W. 2022, Adv. Space Res., 70, 2315 [Google Scholar]
  56. Sun, R., Jia, P., Sun, Y., et al. 2023, AJ, 166, 235 [Google Scholar]
  57. Tonry, J., Denneau, L., Heinze, A., et al. 2018, PASP, 130, 064505 [NASA ADS] [CrossRef] [Google Scholar]
  58. Turing, A. 2004, Intelligent Machinery (1948), ed. B. Jack Copeland, 395 [Google Scholar]
  59. Udalski, A., Szymański, M. K., & Szymański, G. 2015, arXiv e-prints [arXiv:1504.05966] [Google Scholar]
  60. Wang, Y., Sun, R., Deng, T., et al. 2024, RAA, 24, 075012 [Google Scholar]
  61. Watkins, C. J., & Dayan, P. 1992, Mach. Learn., 8, 279 [Google Scholar]
  62. Xu, Y., Xin, L., Wang, J., et al. 2020, PASP, 132, 054502 [Google Scholar]
  63. Yatawatta, S. 2023, arXiv e-prints [arXiv:2301.03933] [Google Scholar]
  64. Yatawatta, S. 2024, Astron. Comput., 48, 100833 [Google Scholar]
  65. Yatawatta, S., & Avruch, I. M. 2021, MNRAS, 505, 2141 [NASA ADS] [CrossRef] [Google Scholar]
  66. Zhan, Y., Jia, P., Xiang, W., & Li, Z. 2022, in Modeling, Systems Engineering, and Project Management for Astronomy X, 12187, 756 [Google Scholar]
  67. Zhang, M., Jia, P., Li, Z., et al. 2023, Opt. Express, 31, 44054 [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.