Open Access
Issue |
A&A
Volume 688, August 2024
|
|
---|---|---|
Article Number | A88 | |
Number of page(s) | 15 | |
Section | Numerical methods and codes | |
DOI | https://doi.org/10.1051/0004-6361/202449568 | |
Published online | 08 August 2024 |
- Asensio Ramos, A., & Díaz Baso, C. J. 2019, A&A, 626, A102 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Asensio Ramos, A., & Olspert, N. 2021, A&A, 646, A100 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Asensio Ramos, A., Esteban Pozuelo, S., & Kuckein, C. 2023, Sol. Phys., 298, 91 [Google Scholar]
- Cornillère, V., Djelouah, A., Yifan, W., Sorkine-Hornung, O., & Schroers, C. 2019, ACM Transac. Graphics, 38, 1 [CrossRef] [Google Scholar]
- Deng, J., Dong, W., Socher, R., et al. 2009, in CVPR09 [Google Scholar]
- Denis, L., Thiébaut, É., Soulez, F., Becker, J.-M., & Mourya, R. 2015, Int. J. Comput. Vision, 115, 253 [CrossRef] [Google Scholar]
- Denker, C. J., Verma, M., Wiśniewska, A., et al. 2023, J. Astron. Telesc. Instrum. Syst., 9, 015001 [NASA ADS] [CrossRef] [Google Scholar]
- Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357 [NASA ADS] [CrossRef] [Google Scholar]
- Hirsch, M., Sra, S., Schölkopf, B., & Harmeling, S. 2010, in Proceedings of the 23rd IEEE Conference on Computer Vision and Pattern Recognition, MaxPlanck-Gesellschaft (Piscataway, NJ, USA: IEEE), 607 [Google Scholar]
- Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 [NASA ADS] [CrossRef] [Google Scholar]
- Ioffe, S., & Szegedy, C. 2015, in Proceedings of the 32Nd International Conference on International Conference on Machine Learning, 37, 448 [Google Scholar]
- Karhunen, K. 1947, Ann. Acad. Sci. Fennicae. Ser. A. I. Math.-Phys., 37, 1 [Google Scholar]
- Kingma, D. P., & Ba, J. 2014, arXiv e-prints [arXiv:1412.6980] [Google Scholar]
- Lauer, T. R. 2002, in SPIE Astronomical Telescopes + Instrumentation (USA: NASA) [Google Scholar]
- Lee, D., & Seung, H. 2001, Advances in Neural Information Processing Systems, eds. T. K., Leen, T. G., Dietterich, & V., Tresp (Cambridge, Massachusetts: MIT Press) [Google Scholar]
- Loève, M. M. 1955, Probability Theory (Princeton: Van Nostrand Company) [Google Scholar]
- Löfdahl, M. G., & Scharmer, G. B. 1994, A&A, 107, 243 [Google Scholar]
- Löfdahl, M. G., Hillberg, T., de la Cruz Rodríguez, J., et al. 2021, A&A, 653, A68 [Google Scholar]
- Loshchilov, I., & Hutter, F. 2017, in 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings (OpenReview.net) [Google Scholar]
- Loshchilov, I., & Hutter, F. 2019, in 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019 (OpenReview.net) [Google Scholar]
- Micikevicius, P., Narang, S., Alben, J., et al. 2018, in 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings (OpenReview.net) [Google Scholar]
- Molina, R., Nunez, J., Cortijo, F. J., & Mateos, J. 2001, IEEE Signal Process. Magazine, 18, 11 [CrossRef] [Google Scholar]
- Nagy, J. G., & O’Leary, D. P. 1998, SIAM J. Sci. Comput., 19, 1063 [NASA ADS] [CrossRef] [Google Scholar]
- Paatero, P., & Tapper, U. 1994 Environmetrics, 5, 111 [Google Scholar]
- Paszke, A., Gross, S., Massa, F., et al. 2019, in Advances in Neural Information Processing Systems 32, eds. H. Wallach, H. Larochelle, A. Beygelzimer, et al. (UK: Curran Associates, Inc.), 8024 [Google Scholar]
- Perez, E., Strub, F., de Vries, H., Dumoulin, V., & Courville, A. 2017, arXiv e-prints [arXiv:1709.07871] [Google Scholar]
- Quintero Noda, C., Schlichenmaier, R., Bellot Rubio, L. R., et al. 2022, A&A, 666, A21 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Rimmele, T. R., Warner, M., Keil, S. L., et al. 2020, Sol. Phys., 295, 172 [Google Scholar]
- Roddier, N. 1990, Opt. Eng., 29, 1174 [NASA ADS] [CrossRef] [Google Scholar]
- Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. 2022, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 10684 [Google Scholar]
- Ronneberger, O., Fischer, P., & Brox, T. 2015, arXiv e-prints [arXiv:1505.04597] [Google Scholar]
- Sakai, Y., Yamada, S., Sato, T., et al. 2023, ApJ, 951, 59 [NASA ADS] [CrossRef] [Google Scholar]
- Scharmer, G. 2017, in SOLARNET IV: The Physics of the Sun from the Interior to the Outer Atmosphere, 85 [Google Scholar]
- Scharmer, G. B., Narayan, G., Hillberg, T., et al. 2008, ApJ, 689, L69 [Google Scholar]
- Starck, J. L., Donoho, D. L., Fadili, M. J., & Rassat, A. 2013, A&A, 552, A133 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Stein, R. F. 2012, Liv. Rev. Sol. Phys., 9, 4 [Google Scholar]
- Stein, R. F., & Nordlund, Å. 2012, ApJ, 753, L13 [NASA ADS] [CrossRef] [Google Scholar]
- van Noort, M., Rouppe van der Voort, L., & Löfdahl, M. G. 2005, Sol. Phys., 228, 191 [Google Scholar]
- Zernike, v. F. 1934, Physica, 1, 689 [NASA ADS] [CrossRef] [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.