Open Access
Issue
A&A
Volume 710, June 2026
Article Number A131
Number of page(s) 14
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/202557715
Published online 05 June 2026
  1. Abadi, M., Agarwal, A., Barham, P., et al. 2015, TensorFlow: Large-scale machine learning on heterogeneous systems [Google Scholar]
  2. Abdollahi, S., Acero, F., Ackermann, M., et al., 2020, ApJS, 247, 33 [Google Scholar]
  3. Acciarri, R., Adams, C., Andreopoulos, C., et al. 2021, Front. Artif. Intell., 4, 649917 [Google Scholar]
  4. Acero, F., Ackermann, M., Ajello, M., et al. 2016, ApJS, 223, 26 [Google Scholar]
  5. Akhlaghi, M., & Ichikawa, T. 2015, ApJS, 220, 1 [Google Scholar]
  6. Atwood, W. B., Abdo, A. A., Ackermann, M., et al. 2009, ApJ, 697, 1071 [CrossRef] [Google Scholar]
  7. Bellm, E. C., Kulkarni, S. R., Graham, M. J., et al. 2018, PASP, 131, 018002 [Google Scholar]
  8. Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393 [Google Scholar]
  9. Caron, S., Eckner, C., Hendriks, L., et al. 2023, J. Cosmology Astropart. Phys., 2023, 013 [Google Scholar]
  10. Chollet, F., et al. 2015, Keras, https://keras.io [Google Scholar]
  11. Croitoru, F.-A., Hondru, V., Ionescu, R. T., & Shah, M. 2023, IEEE Trans. Pattern Anal. Mach. Intell., 45, 10850 [Google Scholar]
  12. Dey, A., Schlegel, D. J., Lang, D., et al. 2019, AJ, 157, 168 [Google Scholar]
  13. Ehlert, S., Chen, C.-T., Swartz, D., et al. 2022, MNRAS, 515, 5185 [Google Scholar]
  14. Gheller, C., & Vazza, F. 2021, MNRAS, 509, 990 [NASA ADS] [CrossRef] [Google Scholar]
  15. Groot, P. J., Bloemen, S., Vreeswijk, P., et al. 2024, PASP, 136, 115003 [NASA ADS] [CrossRef] [Google Scholar]
  16. Haigh, C., Chamba, N., Venhola, A., et al. 2021, A&A, 645, A107 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  17. Heymans, C., Van Waerbeke, L., Miller, L., et al. 2012, MNRAS, 427, 146 [Google Scholar]
  18. Ho, J., Jain, A., & Abbeel, P. 2020, NeurIPS, 33, 6840 [Google Scholar]
  19. Huber, P. 1964, Ann. Math. Stat., 35, 73 [CrossRef] [Google Scholar]
  20. Ivezić, Ž., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111 [Google Scholar]
  21. Jia, P., Lv, J., Ning, R., et al. 2023, MNRAS, 527, 6581 [Google Scholar]
  22. Kingma, D. P., & Ba, J. 2014, arXiv preprint [arXiv:1412.6980] [Google Scholar]
  23. Loshchilov, I., & Hutter, F. 2017, in ICLR [Google Scholar]
  24. Maas, A. L., Hannun, A. Y., & Ng, A. Y. 2013, ICML, 30 [Google Scholar]
  25. Oktay, O., Schlemper, J., Folgoc, L. L., et al. 2018, arXiv preprint [arXiv:1804.03999] [Google Scholar]
  26. Panes, B., Eckner, C., Hendriks, L., et al. 2021, A&A, 656, A62 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  27. Robotham, A. S. G. 2018, MNRAS, 476, 3137 [NASA ADS] [CrossRef] [Google Scholar]
  28. Ronneberger, O., Fischer, P., & Brox, T. 2015, in MICCAI-2015 (Springer International Publishing), 234 [Google Scholar]
  29. Roscani, V., Tozza, S., Castellano, M., et al. 2020, A&A, 643, A43 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  30. Rowe, B. T., Jarvis, M., Mandelbaum, R., et al. 2015, Astron. Comput., 10, 121 [NASA ADS] [CrossRef] [Google Scholar]
  31. Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., & Ganguli, S. 2015, in ICML, PMLR, 2256 [Google Scholar]
  32. Song, Y., Sohl-Dickstein, J., Kingma, D. P., et al. 2020, ICML [Google Scholar]
  33. Stetson, P. B. 1987, PASP, 99, 191 [Google Scholar]
  34. Stoppa, F., Vreeswijk, P., Bloemen, S., et al. 2022, A&A, 662, A109 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  35. Stoppa, F., Bhattacharyya, S., de Austri, R. R., et al. 2023a, A&A, 680, A109 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  36. Stoppa, F., de Austri, R. R., Vreeswijk, P., et al. 2023b, A&A, 680, A108 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  37. Tian, C., Fei, L., Zheng, W., et al. 2020, Neural Netw., 131, 251 [Google Scholar]
  38. Tung, Y.-C., Li, J., et al. 2024, Nucl. Instrum. Methods Phys. Res. A, 1059, 169010 [Google Scholar]
  39. van den Oetelaar, C., Bhattacharyya, S., Panes, B., et al. 2021, PoS, ICRC, 663 [Google Scholar]
  40. Vaswani, A., Shazeer, N., Parmar, N., et al. 2017, NeurIPS, 30 [Google Scholar]
  41. Vojtekova, A., Lieu, M., Valtchanov, I., et al. 2020, MNRAS, 503, 3204 [Google Scholar]
  42. Wolf, T. N., Jones, B. A., & Bowler, B. P. 2024, AJ, 167, 92 [Google Scholar]
  43. Zackay, B., & Ofek, E. O. 2017a, ApJ, 836, 187 [Google Scholar]
  44. Zackay, B., & Ofek, E. O. 2017b, ApJ, 836, 188 [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.