Open Access
| Issue |
A&A
Volume 703, November 2025
|
|
|---|---|---|
| Article Number | A99 | |
| Number of page(s) | 15 | |
| Section | The Sun and the Heliosphere | |
| DOI | https://doi.org/10.1051/0004-6361/202555839 | |
| Published online | 10 November 2025 | |
- Abduallah, Y., & Wang, J. T. L. 2024, ArXiv e-prints [arXiv:2405.16080] [Google Scholar]
- Ahmad, T., Munir, A., Bhatti, S. H., Aftab, M., & Raza, M. A. 2017, PLoS ONE, 12, 1 [Google Scholar]
- Ahmadzadeh, A., Aydin, B., Georgoulis, M. K., et al. 2021, ApJS, 254, 23 [NASA ADS] [CrossRef] [Google Scholar]
- Angryk, R. A., Martens, P. C., Aydin, B., et al. 2020, Sci. Data, 7, 227 [NASA ADS] [CrossRef] [Google Scholar]
- Aschwanden, M. J., Johnson, J. R., & Nurhan, Y. I. 2021, ApJ, 921, 166 [Google Scholar]
- Barnes, G., Leka, K. D., Schrijver, C. J., et al. 2016, ApJ, 829, 89 [NASA ADS] [CrossRef] [Google Scholar]
- Bloomfield, D. S., Higgins, P. A., McAteer, R. T. J., & Gallagher, P. T. 2012, ApJ, 747, L41 [CrossRef] [Google Scholar]
- Bobra, M. G., & Couvidat, S. 2015, ApJ, 798, 135 [Google Scholar]
- Bobra, M. G., Sun, X., Hoeksema, J. T., et al. 2014, Sol. Phys., 289, 3549 [Google Scholar]
- Boser, B. E., Guyon, I. M., & Vapnik, V. N. 1992, Proceedings of the Fifth Annual Workshop on Computational Learning Theory, COLT ’92 (New York: Association for Computing Machinery), 144 [Google Scholar]
- Boteler, D. H. 2001, Geophys. Monogr. Ser., 125, 347 [Google Scholar]
- Breiman, L. 2001, Mach. Learn., 45, 5 [Google Scholar]
- Chaddad, A., Hassan, L., Katib, Y., & Bouridane, A. 2023, IEEE J. Transl. Eng. Health Med., 11, 223 [Google Scholar]
- Chen, Y., Manchester, W. B., Hero, A. O., et al. 2019, Space Weather, 17, 1404 [NASA ADS] [CrossRef] [Google Scholar]
- Cox, D. R. 1972, J. Roy. Stat. Soc.: Ser. B (Methodol.), 34, 187 [Google Scholar]
- Cox, D. R. 1975, Biometrika, 62, 269 [Google Scholar]
- Daley, D. J., & Vere-Jones, D. 2007, An Introduction to the Theory of Point Processes: Volume II: General Theory and Structure (Springer Science& Business Media) [Google Scholar]
- Deng, Z., Wang, F., Deng, H., et al. 2021, ApJ, 922, 232 [Google Scholar]
- Faraggi, D., & Simon, R. 1995, Stat. Med., 14, 73 [Google Scholar]
- Francisco, G., Guastavino, S., Barata, T., Fernandes, J., & Del Moro, D. 2024, ArXiv e-prints [arXiv:2410.16116] [Google Scholar]
- Georgoulis, M. K., Rust, D. M., Pevtsov, A. A., Bernasconi, P. N., & Kuzanyan, K. M. 2009, ApJ, 705, L48 [NASA ADS] [CrossRef] [Google Scholar]
- Gupta, V., Bedathur, S., Bhattacharya, S., & De, A. 2022, ACM Trans. Intell. Syst. Technol., 13, 103 [Google Scholar]
- Heagerty, P. J., Lumley, T., & Pepe, M. S. 2004, Biometrics, 56, 337 [Google Scholar]
- Hostetter, M., Ahmadzadeh, A., Aydin, B., et al. 2019, IEEE International Conference on Big Data, 4960 [Google Scholar]
- Hu, S., Fridgeirsson, E., Wingen, G. V., & Welling, M. 2021, Proc. Mach. Learn. Res., 146, 132 [Google Scholar]
- Ishwaran, H., Kogalur, U. B., Blackstone, E. H., & Lauer, M. S. 2008, Ann. Appl. Stat., 2, 841 [Google Scholar]
- Jiao, Z., Sun, H., Wang, X., et al. 2020, Space Weather, 18, e02440 [Google Scholar]
- Katzman, J. L., Shaham, U., Cloninger, A., et al. 2018, BMC Med. Res. Methodol., 18, 24 [Google Scholar]
- Kingma, D. P., & Ba, J. 2014, CoRR, https://api.semanticscholar.org/CorpusID:6628106 [Google Scholar]
- Kleint, L. 2017, ApJ, 834, 26 [Google Scholar]
- Knottenbelt, W., McGough, W., Wray, R., et al. 2025, Bioinformatics, 41 [Google Scholar]
- Krausmann, E., Andersson, E., Murtagh, W., & Mitchison, N. 2014, EGU General Assembly Conference Abstracts, 12584 [Google Scholar]
- Krzyziński, M., Spytek, M., Baniecki, H., & Biecek, P. 2023, Knowledge-Based Systems, 262, 110234 [Google Scholar]
- Kvamme, H., & Borgan, Ø. 2021, Lifetime Data Anal., 27, 710 [Google Scholar]
- Kvamme, H., Hart, B., Pati, S., & Sellereite, N. 2024, pycox (GitHub), https://github.com/havakv/pycox [Google Scholar]
- Lee, C., Zame, W., Yoon, J., & van der Schaar, M. 2018, Proceedings of the AAAI Conference on Artificial Intelligence, 32 [Google Scholar]
- Leka, K. D., & Barnes, G. 2003, ApJ, 595, 1277 [CrossRef] [Google Scholar]
- Leka, K. D., & Barnes, G. 2007, ApJ, 656, 1173 [NASA ADS] [CrossRef] [Google Scholar]
- Leka, K. D., Park, S.-H., Kusano, K., et al. 2019, ApJS, 243, 36 [NASA ADS] [CrossRef] [Google Scholar]
- Lemen, J. R., Title, A. M., Akin, D. J., et al. 2012, Sol. Phys., 275, 17 [Google Scholar]
- Li, C., Zhong, S. J., Xu, Z. G., et al. 2018, MNRAS, 479, L139 [NASA ADS] [CrossRef] [Google Scholar]
- Li, D., Feng, S., Su, W., & Huang, Y. 2020, A&A, 639, L5 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Li, X., Krivtsov, V., & Arora, K. 2022, Reliab. Eng. Syst. Safety, 217, 108033 [Google Scholar]
- Lin, D. Y. 2007, Lifetime Data Anal., 13, 471 [Google Scholar]
- Liu, H., Liu, C., Wang, J. T. L., & Wang, H. 2019, ApJ, 877, 121 [NASA ADS] [CrossRef] [Google Scholar]
- Liu, S., Idrees, S., Liu, D., & Zeng, S. G. 2025, Sol. Phys., 300, 51 [Google Scholar]
- Loshchilov, I., & Hutter, F. 2017a, ArXiv e-prints [arXiv:1711.05101] [Google Scholar]
- Loshchilov, I., & Hutter, F. 2017b, ArXiv e-prints [arXiv:1608.03983] [Google Scholar]
- MacDonald, I. L., & Pienaar, E. A. D. 2023, React. Kinet. Mech. Catal., 136, 1757 [Google Scholar]
- Mei, H., & Eisner, J. M. 2017, Advances in Neural Information Processing Systems (Curran Associates, Inc.), 30 [Google Scholar]
- Nishizuka, N., Sugiura, K., Kubo, Y., et al. 2017, ApJ, 835, 156 [NASA ADS] [CrossRef] [Google Scholar]
- Nishizuka, N., Sugiura, K., Kubo, Y., Den, M., & Ishii, M. 2018, ApJ, 858, 113 [NASA ADS] [CrossRef] [Google Scholar]
- Nurhan, Y. I., Johnson, J. R., Homan, J. R., Wing, S., & Aschwanden, M. J. 2021, Geophys. Res. Lett., 48, e94348 [Google Scholar]
- Pandey, C., Angryk, R. A., Georgoulis, M. K., & Aydin, B. 2023, Discovery Science (Cham: Springer), 567 [Google Scholar]
- Panos, B., Kleint, L., & Zbinden, J. 2023, A&A, 671, A73 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Platt, J., Cristianini, N., & Shawe-Taylor, J. 1999, Advances in Neural Information Processing Systems (MIT Press), 12 [Google Scholar]
- Pölsterl, S. 2020, J. Mach. Learn. Res., 21, 1 [Google Scholar]
- Pulkkinen, A., Lindahl, S., Viljanen, A., & Pirjola, R. 2005, Space Weather, 3, S08C03 [Google Scholar]
- Puttanawarut, C., Looareesuwan, P., Wabina, R. S., & Saowaprut, P. 2024, Inf. Med. Unlocked, 49 [Google Scholar]
- Reeves, M., & Bhat, H. S. 2023, 2023 SICE International Symposium on Control Systems (SICE ISCS), 76 [Google Scholar]
- Rosenblatt, F. 1957, The Perceptron A Perceiving and Recognizing Automaton, Tech. Rep. 85–460-1 (Ithaca, New York: Cornell Aeronautical Laboratory) [Google Scholar]
- Rumelhart, D. E., Hinton, G. E., & Williams, R. J. 1986, Nature, 323, 533 [Google Scholar]
- Rumelhart, D. E., Hinton, G. E., & Williams, R. J. 1988, Readings in Cognitive Science (Morgan Kaufmann), 399 [Google Scholar]
- Schou, J., Scherrer, P. H., Bush, R. I., et al. 2012, Sol. Phys., 275, 229 [Google Scholar]
- Schrijver, C. J. 2007, ApJ, 655, L117 [Google Scholar]
- Shain, C. 2021, Proc. of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) (Online: Association for Computational Linguistics), 3718 [Google Scholar]
- Shain, C., & Schuler, W. 2024, Open Mind, 8, 235 [Google Scholar]
- Sun, Z., Bobra, M. G., Wang, X., et al. 2022, ApJ, 931, 163 [Google Scholar]
- Sun, D., Huang, X., Zhao, Z., & Xu, L. 2023, ApJS, 266, 8 [NASA ADS] [CrossRef] [Google Scholar]
- Tian, L. R., & Liu, Y. 2003, A&A, 406, 337 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Toriumi, S., & Wang, H. 2019, Liv. Rev. Sol. Phys., 16, 3 [Google Scholar]
- Welsch, B. T., Li, Y., Schuck, P. W., & Fisher, G. H. 2009, ApJ, 705, 821 [NASA ADS] [CrossRef] [Google Scholar]
- Wiegrebe, S., Kopper, P., Sonabend, R., Bischl, B., & Bender, A. 2024, Artif. Intell. Rev., 57, 65 [Google Scholar]
- Xu, L., & Guo, C. 2023, Expert Syst. Appl., 227, 120218 [Google Scholar]
- Zapletal, D. 2025, Mathematics, 13 [Google Scholar]
- Zbinden, J., Kleint, L., & Panos, B. 2024, A&A, 689, A72 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Zeng, L., Zhang, J., Chen, W., & Ding, Y. 2024, J. Roy. Stat. Soc. Ser. C: Appl. Stat., 74, 187 [Google Scholar]
- Zhong, Q., Mueller, J. W., & Wang, J. L. 2021, Advances in Neural Information Processing Systems (Curran Associates, Inc.), 34, 15111 [Google Scholar]
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