EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 656 (December 2021) A&A, 656 (2021) A62 References
Free Access
Issue
A&A
Volume 656, December 2021
Article Number A62
Number of page(s) 18
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/202141193
Published online 03 December 2021
  1. Abazajian, K. N. 2011, JCAP, 03, 010 [NASA ADS] [CrossRef] [Google Scholar]
  2. Abdo, A. A., Ajello, M., Allafort, A., et al. 2013, ApJS, 208, 17 [Google Scholar]
  3. Abdollahi, S., Acero, F., Ackermann, M., et al. 2020, ApJS, 247, 33 [Google Scholar]
  4. Acero, F., Ackermann, M., Ajello, M., et al. 2015, ApJS, 218, 23 [Google Scholar]
  5. Acero, F., Ackermann, M., Ajello, M., et al. 2016a, ApJS, 223, 26 [Google Scholar]
  6. Acero, F., Ackermann, M., Ajello, M., et al. 2016b, ApJS, 224, 8 [NASA ADS] [CrossRef] [Google Scholar]
  7. Agarap, A. F. 2018, Arxiv e-prints [arxiv:1803.08375] [Google Scholar]
  8. Agrawal, S., Barrington, L., Bromberg, C., et al. 2019, Machine Learning for Precipitation Nowcasting from Radar Images [Google Scholar]
  9. Ajello, M., Angioni, R., Axelsson, M., et al. 2020, ApJ, 892, 105 [NASA ADS] [CrossRef] [Google Scholar]
  10. Bartels, R., Storm, E., Weniger, C., & Calore, F. 2018, Nat. Astron., 2, 819 [NASA ADS] [CrossRef] [Google Scholar]
  11. Caldeira, J., Wu, W., Nord, B., et al. 2019, Astron. Comput., 28 [Google Scholar]
  12. Calore, F., Cholis, I., & Weniger, C. 2015, JCAP, 03, 038 [Google Scholar]
  13. Carlson, E., & Profumo, S. 2014, Phys. Rev. D, 90, 023015 [NASA ADS] [CrossRef] [Google Scholar]
  14. Caron, S., Gómez-Vargas, G. A., Hendriks, L., & Ruiz de Austri, R. 2018, JCAP, 5, 58 [Google Scholar]
  15. Chiaro, G., Salvetti, D., La Mura, G., et al. 2016, MNRAS, 462, 3180 [NASA ADS] [CrossRef] [Google Scholar]
  16. Cognard, I., Guillemot, L., Johnson, T. J., et al. 2011, ApJ, 732, 47 [NASA ADS] [CrossRef] [Google Scholar]
  17. Coronado-Blazquez, J., Sanchez-Conde, M. A., Dominguez, A., et al. 2019, JCAP, 07, 020 [Google Scholar]
  18. Cowan, G., Cranmer, K., Gross, E., & Vitells, O. 2011, Eur. Phys. J. C, 71, 1554 [NASA ADS] [CrossRef] [Google Scholar]
  19. Dijkstra, K., van de Loosdrecht, J., Schomaker, L., & Wiering, M. A. 2018, Joint European Conference on Machine Learning and Knowledge Discovery in Databases (Springer), 585 [Google Scholar]
  20. Di Mauro, M., Manconi, S., Zechlin, H.-S., et al. 2018, ApJ, 856, 106 [CrossRef] [Google Scholar]
  21. Górski, K. M., Hivon, E., Banday, A. J., et al. 2005, ApJ, 622, 759 [Google Scholar]
  22. He, S., Li, Y., Feng, Y., et al. 2019, Proc. Nat. Acad. Sci., 116, 13825 [Google Scholar]
  23. Hooper, D., & Goodenough, L. 2011, Phys. Lett. B, 697, 412 [NASA ADS] [CrossRef] [Google Scholar]
  24. Hooper, D., Cholis, I., Linden, T., Siegal-Gaskins, J., & Slatyer, T. 2013, Phys. Rev. D, 88, 083009 [NASA ADS] [CrossRef] [Google Scholar]
  25. Ioffe, S., & Szegedy, C. 2015, Proceedings of Machine Learning Research, ICML’15, (JMLR.org), 448 [Google Scholar]
  26. Kendall, A. & Gal, Y. 2017, in Advances in Neural Information Processing Systems 30, eds. I. Guyon, U. V. Luxburg, S. Bengio, et al. (Curran Associates, Inc.), 5575 [Google Scholar]
  27. Kingma, D. P., & Ba, J. 2014, Arxiv e-prints [arxiv:1412.6980] [Google Scholar]
  28. Krizhevsky, A., Sutskever, I., & Hinton, G. E. 2012, in Advances in Neural Information Processing Systems, eds. F. Pereira, C. J. C. Burges, L. Bottou, & K. Q. Weinberger (Curran Associates, Inc.), 25, 1097 [Google Scholar]
  29. LeCun, Y., Bengio, Y., & Hinton, G. 2015, Nature, 521, 436 [Google Scholar]
  30. Luo, J.-W., & Zhang, B. 2020, Phys. Rev. D, 101, 103015 [NASA ADS] [CrossRef] [Google Scholar]
  31. Mirabal, N. 2013, MNRAS, 436, 2461 [NASA ADS] [CrossRef] [Google Scholar]
  32. Mirabal, N., Nieto, D., & Pardo, S. 2010, ArXiv e-prints [arXiv:1007.2644] [Google Scholar]
  33. Petrović, J., Serpico, P. D., & Zaharijaš, G. 2014, JCAP, 10, 052 [CrossRef] [Google Scholar]
  34. Petrović, J., Serpico, P. D., & Zaharijas, G. 2015, JCAP, 02, 023 [CrossRef] [Google Scholar]
  35. Ronneberger, O., Fischer, P., & Brox, T. 2015, in Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, eds. N. Navab, J. Hornegger, W. M. Wells, & A. F. Frangi (Cham: Springer International Publishing), 234 [Google Scholar]
  36. Saz Parkinson, P., Xu, H., Yu, P., et al. 2016, ApJ, 820, 8 [NASA ADS] [CrossRef] [Google Scholar]
  37. Silburt, A., Ali-Dib, M., Zhu, C., et al. 2018, Icarus, 317 [Google Scholar]
  38. Somalwar, J. J., Chang, L. J., Mishra-Sharma, S., & Lisanti, M. 2021, ApJ, 906, 57 [NASA ADS] [CrossRef] [Google Scholar]
  39. Vafaei Sadr, A., Vos, E. E., Bassett, B. A., et al. 2019, MNRAS, 484, 2793 [CrossRef] [Google Scholar]
  40. Zou, Q., Jiang, H., Dai, Q., et al. 2020, IEEE Trans. Veh. Technol., 69, 41 [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.