Open Access
| Issue |
A&A
Volume 708, April 2026
|
|
|---|---|---|
| Article Number | A118 | |
| Number of page(s) | 25 | |
| Section | Stellar atmospheres | |
| DOI | https://doi.org/10.1051/0004-6361/202558595 | |
| Published online | 03 April 2026 | |
- Abdurro’uf, Accetta, K., Aerts, C., et al. 2022, ApJS, 259, 35 [NASA ADS] [CrossRef] [Google Scholar]
- Aguilera-Gómez, C., Ramírez, I., & Chanamé, J., 2018, A&A, 614, A55 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Amarsi, A. M., Nissen, P. E., & Skúladóttir, A., 2019, A&A, 630, A104 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Amarsi, A. M., Lind, K., Osorio, Y., et al. 2020, A&A, 642, A62 [EDP Sciences] [Google Scholar]
- Amarsi, A. M., Ogneva, D., Buldgen, G., et al. 2024, A&A, 690, A128 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Ardizzone, L., Kruse, J., Rother, C., & Köthe, U., 2019a, in International Conference on Learning Representations [Google Scholar]
- Ardizzone, L., Lüth, C., Kruse, J., Rother, C., & Köthe, U., 2019b, CoRR, abs/1907.02392 [arXiv:1907.02392] [Google Scholar]
- Asplund, M., 2005, ARA&A, 43, 481 [Google Scholar]
- Asplund, M., Amarsi, A. M., & Grevesse, N., 2021, A&A, 653, A141 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Bagnulo, S., Jehin, E., Ledoux, C., et al. 2003, The Messenger, 114, 10 [Google Scholar]
- Bensby, T., Bergemann, M., Rybizki, J., et al. 2019, The Messenger, 175, 35 [NASA ADS] [Google Scholar]
- Bergemann, M., 2011, MNRAS, 413, 2184 [NASA ADS] [CrossRef] [Google Scholar]
- Bergemann, M., & Cescutti, G., 2010, A&A, 522, A9 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Bergemann, M., & Gehren, T., 2008, A&A, 492, 823 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Bergemann, M., & Hoppe, R., 2025, arXiv e-prints [arXiv:2511.04254] [Google Scholar]
- Bergemann, M., & Nordlander, T., 2014, in Determination of Atmospheric Parameters of B, eds. E. Niemczura, B. Smalley, & W. Pych (Berlin: Springer), 169 [Google Scholar]
- Bergemann, M., Pickering, J. C., & Gehren, T., 2010, MNRAS, 401, 1334 [CrossRef] [Google Scholar]
- Bergemann, M., Hansen, C. J., Bautista, M., & Ruchti, G. 2012a, A&A, 546, A90 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Bergemann, M., Lind, K., Collet, R., Magic, Z., & Asplund, M., 2012b, MNRAS, 427, 27 [Google Scholar]
- Bergemann, M., Kudritzki, R.-P., Würl, M., et al. 2013, ApJ, 764, 115 [NASA ADS] [CrossRef] [Google Scholar]
- Bergemann, M., Collet, R., Amarsi, A. M., et al. 2017, ApJ, 847, 15 [NASA ADS] [CrossRef] [Google Scholar]
- Bergemann, M., Gallagher, A. J., Eitner, P., et al. 2019, A&A, 631, A80 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Bergemann, M., Hoppe, R., Semenova, E., et al. 2021, MNRAS, 508, 2236 [NASA ADS] [CrossRef] [Google Scholar]
- Bestenlehner, J. M., Enßlin, T., Bergemann, M., et al. 2024, MNRAS, 528, 6735 [CrossRef] [Google Scholar]
- Bishop, C. M., 2009, Pattern Recognition and Machine Learning, 8th edn., Information science and statistics (New York: Springer), XX, 738 [Google Scholar]
- Bister, T., Erdmann, M., Köthe, U., & Schulte, J., 2022, Euro. Phys. J. C, 82, 171 [Google Scholar]
- Blanco-Cuaresma, S., Soubiran, C., Jofré, P., & Heiter, U., 2014, A&A, 566, A98 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Bond-Taylor, S., Leach, A., Long, Y., & Willcocks, C. G., 2022, IEEE Trans. Pattern Anal. Mach. Intell., 44, 7327 [Google Scholar]
- Buder, S., Kos, J., Wang, X. E., et al. 2025, PASA, 42, e051 [Google Scholar]
- Caffau, E., Ludwig, H.-G., Steffen, M., & Bonifacio, P., 2010, IAU Symp., 268, 329 [Google Scholar]
- Candebat, N., Sacco, G. G., Magrini, L., et al. 2024, A&A, 692, A228 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Casamiquela, L., Soubiran, C., Jofré, P., et al. 2026, A&A, 705, A167 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Christlieb, N., Beers, T. C., Thom, C., et al. 2005, A&A, 431, 143 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Cvrček, V., Romaniello, M., Šára, R., Freudling, W., & Ballester, P., 2025, A&A, 693, A256 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- de Jong, R. S., Agertz, O., Berbel, A. A., et al. 2019, The Messenger, 175, 3 [NASA ADS] [Google Scholar]
- De Silva, G. M., Freeman, K. C., Bland-Hawthorn, J., et al. 2015, MNRAS, 449, 2604 [NASA ADS] [CrossRef] [Google Scholar]
- Dinh, L., Krueger, D., & Bengio, Y., 2015, in 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7–9, 2015, Workshop Track Proceedings, eds. Y. Bengio, & Y. LeCun [Google Scholar]
- Dinh, L., Sohl-Dickstein, J., & Bengio, S., 2017, in International Conference on Learning Representations [Google Scholar]
- Eisert, L., Pillepich, A., Nelson, D., et al. 2023, MNRAS, 519, 2199 [Google Scholar]
- Eitner, P., Bergemann, M., Hoppe, R., et al. 2025, A&A, 703, A199 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Ezzeddine, R., Merle, T., Plez, B., et al. 2018, A&A, 618, A141 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Fuhrmann, K., 1998, A&A, 338, 161 [NASA ADS] [Google Scholar]
- Fuhrmann, K., Axer, M., & Gehren, T., 1993, A&A, 271, 451 [NASA ADS] [Google Scholar]
- Gaia Collaboration (Prusti, T., et al.,) 2016, A&A, 595, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gallagher, A. J., Bergemann, M., Collet, R., et al. 2020, A&A, 634, A55 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- García Pérez, A. E., Sánchez-Blázquez, P., Vazdekis, A., et al. 2021, MNRAS, 505, 4496 [CrossRef] [Google Scholar]
- Gebran, M., & Bentley, I., 2025, Astronomy, 4, 13 [Google Scholar]
- Gebran, M., Farah, W., Paletou, F., Monier, R., & Watson, V., 2016, A&A, 589, A83 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gehren, T., Liang, Y. C., Shi, J. R., Zhang, H. W., & Zhao, G., 2004, A&A, 413, 1045 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gehren, T., Shi, J. R., Zhang, H. W., Zhao, G., & Korn, A. J., 2006, A&A, 451, 1065 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gent, M. R., Bergemann, M., Serenelli, A., et al. 2022, A&A, 658, A147 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gent, M. R., Eitner, P., Serenelli, A., et al. 2024, A&A, 683, A74 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gerber, J. M., Magg, E., Plez, B., et al. 2023, A&A, 669, A43 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gilmore, G., Randich, S., Asplund, M., et al. 2012, The Messenger, 147, 25 [NASA ADS] [Google Scholar]
- Gilmore, G., Randich, S., Worley, C. C., et al. 2022, A&A, 666, A120 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., et al. 2014, in Advances in Neural Information Processing Systems, eds. Z. Ghahramani, M. Welling, C. Cortes, N. Lawrence, & K. Weinberger (USA: Curran Associates, Inc.), 27 [Google Scholar]
- Goodfellow, I., Bengio, Y., & Courville, A., 2016, Deep Learning (Cambridge: MIT Press) [Google Scholar]
- Guiglion, G., Matijevič, G., Queiroz, A. B. A., et al. 2020, A&A, 644, A168 [EDP Sciences] [Google Scholar]
- Guiglion, G., Nepal, S., Chiappini, C., et al. 2024, A&A, 682, A9 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gustafsson, B., Edvardsson, B., Eriksson, K., et al. 2008, A&A, 486, 951 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Haldemann, J., Ksoll, V., Walter, D., et al. 2023, A&A, 672, A180 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Heiter, U., Jofré, P., Gustafsson, B., et al. 2015, A&A, 582, A49 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Heiter, U., Lind, K., Bergemann, M., et al. 2021, A&A, 645, A106 [EDP Sciences] [Google Scholar]
- Hubeny, I., & Lanz, T., 2011, Astrophysics Source Code Library [record ascl:1109.022] [Google Scholar]
- Isola, P., Zhu, J.-Y., Zhou, T., & Efros, A. A., 2016, Doi: https://ui.adsabs.harvard.edu/abs/2016arXiv161107004I [Google Scholar]
- Jin, S., Trager, S. C., Dalton, G. B., et al. 2024, MNRAS, 530, 2688 [NASA ADS] [CrossRef] [Google Scholar]
- Jofré, P., Heiter, U., Soubiran, C., et al. 2014, A&A, 564, A133 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Kang, D. E., Pellegrini, E. W., Ardizzone, L., et al. 2022, MNRAS, 512, 617 [CrossRef] [Google Scholar]
- Kang, D. E., Klessen, R. S., Ksoll, V. F., et al. 2023a, MNRAS, 520, 4981 [NASA ADS] [CrossRef] [Google Scholar]
- Kang, D. E., Ksoll, V. F., Itrich, D., et al. 2023b, A&A, 674, A175 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Kang, D. E., Itrich, D., Ksoll, V. F., et al. 2025, A&A, 697, A39 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Kingma, D. P., & Dhariwal, P., 2018, in Advances in Neural Information Processing Systems, eds. S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. Cesa-Bianchi, & R. Garnett (USA: Curran Associates, Inc.), 31 [Google Scholar]
- Kingma, D. P., & Welling, M., 2013, arXiv e-prints [arXiv:1312.6114] [Google Scholar]
- Kobyzev, I., Prince, S. J., & Brubaker, M. A., 2021, IEEE Trans. Pattern Anal. Mach. Intell., 43, 3964 [NASA ADS] [CrossRef] [Google Scholar]
- Kollmeier, J. A., Rix, H.-W., Aerts, C., et al. 2026, AJ, 171, 52 [Google Scholar]
- Korn, A. J., Shi, J., & Gehren, T., 2003, A&A, 407, 691 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Kovalev, M., Bergemann, M., Ting, Y.-S., & Rix, H.-W., 2019, A&A, 628, A54 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Ksoll, V. F., Ardizzone, L., Klessen, R., et al. 2020, MNRAS, 499, 5447 [NASA ADS] [CrossRef] [Google Scholar]
- Ksoll, V. F., Reissl, S., Klessen, R. S., et al. 2024, A&A, 683, A246 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Li, L., Jamieson, K., DeSalvo, G., Rostamizadeh, A., & Talwalkar, A., 2018, J. Mach. Learn. Res., 18, 1 [Google Scholar]
- Lind, K., & Amarsi, A. M., 2024, ARA&A, 62, 475 [Google Scholar]
- Lind, K., Asplund, M., Barklem, P. S., & Belyaev, A. K., 2011, A&A, 528, A103 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Lind, K., Bergemann, M., & Asplund, M., 2012, MNRAS, 427, 50 [Google Scholar]
- Liu, T., & Regier, J., 2020, arXiv e-prints [arXiv:2006.10175] [Google Scholar]
- Liu, W., Cao, S., Yu, X.-C., et al. 2024, ApJS, 271, 53 [Google Scholar]
- Luck, R. E., 2017, AJ, 153, 21 [Google Scholar]
- Magg, E., Bergemann, M., Serenelli, A., et al. 2022, A&A, 661, A140 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Majewski, S. R., APOGEE Team, & APOGEE-2 Team. 2016, Astron. Nachr., 337, 863 [NASA ADS] [CrossRef] [Google Scholar]
- Majewski, S. R., Schiavon, R. P., Frinchaboy, P. M., et al. 2017, AJ, 154, 94 [NASA ADS] [CrossRef] [Google Scholar]
- Manteiga, M., Santoveña, R., Álvarez, M. A., et al. 2025, A&A, 694, A326 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Mashonkina, L., Zhao, G., Gehren, T., et al. 2008, A&A, 478, 529 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Mashonkina, L., Jablonka, P., Sitnova, T., Pakhomov, Y., & North, P., 2017, A&A, 608, A89 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Mayor, M., Pepe, F., Queloz, D., et al. 2003, The Messenger, 114, 20 [NASA ADS] [Google Scholar]
- Mirza, M., & Osindero, S., 2014, arXiv e-prints [arXiv:1411.1784] [Google Scholar]
- Ness, M., Hogg, D. W., Rix, H. W., Ho, A. Y. Q., & Zasowski, G., 2015, ApJ, 808, 16 [NASA ADS] [CrossRef] [Google Scholar]
- Ness, M., Zasowski, G., Johnson, J. A., et al. 2016, ApJ, 819, 2 [NASA ADS] [CrossRef] [Google Scholar]
- Pal, T., Khan, I., Worthey, G., Gregg, M. D., & Silva, D. R., 2023, ApJS, 266, 41 [NASA ADS] [CrossRef] [Google Scholar]
- Paszke, A., Gross, S., Chintala, S., et al. 2017, in NIPS Autodiff Workshop [Google Scholar]
- Plez, B., 2012, Astrophysics Source Code Library [record ascl:1205.004] [Google Scholar]
- Randich, S., Gilmore, G., & Gaia-ESO Consortium 2013, The Messenger, 154, 47 [NASA ADS] [Google Scholar]
- Randich, S., Gilmore, G., Magrini, L., et al. 2022, A&A, 666, A121 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Reetz, J. K., 1991, Diploma Thesis, Universität München, Germany [Google Scholar]
- Rezende, D., & Mohamed, S., 2015, Proc. Mach. Learn. Res., 37, 1530 [Google Scholar]
- Rezende, D. J., Mohamed, S., & Wierstra, D., 2014, Proc. Mach. Learn. Res., 32, 1278 [Google Scholar]
- Ryabchikova, T., Piskunov, N., Kurucz, R. L., et al. 2015, Phys. Scr, 90, 054005 [Google Scholar]
- Santoveña, R., Dafonte, C., & Manteiga, M., 2024, arXiv e-prints [arXiv:2411.05960] [Google Scholar]
- Semenova, E., Bergemann, M., Deal, M., et al. 2020, A&A, 643, A164 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Sneden, C. A., 1973, PhD thesis, University of Texas, Austin [Google Scholar]
- Sohn, K., Lee, H., & Yan, X., 2015, in Advances in Neural Information Processing Systems, eds. C. Cortes, N. Lawrence, D. Lee, M. Sugiyama, & R. Garnett (USA: Curran Associates, Inc.), 28 [Google Scholar]
- Soubiran, C., Brouillet, N., & Casamiquela, L., 2022, A&A, 663, A4 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Soubiran, C., Creevey, O. L., Lagarde, N., et al. 2024, A&A, 682, A145 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Steinmetz, M., Guiglion, G., McMillan, P. J., et al. 2020, AJ, 160, 83 [NASA ADS] [CrossRef] [Google Scholar]
- Stonkuté, E., Chorniy, Y., Tautvaišienė, G., et al. 2020, AJ, 159, 90 [Google Scholar]
- Storm, N., & Bergemann, M., 2023, MNRAS, 525, 3718 [NASA ADS] [CrossRef] [Google Scholar]
- Storm, N., Barklem, P. S., Yakovleva, S. A., et al. 2024, A&A, 683, A200 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Tabak, E., & Turner, C., 2013, Commun. Pure Appl. Math., 66, 145 [CrossRef] [Google Scholar]
- Tabak, E., & Vanden-Eijnden, E., 2010, Commun. Math. Sci., 8, 217 [CrossRef] [Google Scholar]
- Ting, Y.-S., Conroy, C., Rix, H.-W., & Cargile, P., 2019, ApJ, 879, 69 [Google Scholar]
- Voronov, Y. V., Yakovleva, S. A., & Belyaev, A. K., 2022, ApJ, 926, 173 [NASA ADS] [CrossRef] [Google Scholar]
- Wehrhahn, A., Piskunov, N., & Ryabchikova, T., 2023, A&A, 671, A171 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Wheeler, A. J., Abruzzo, M. W., Casey, A. R., & Ness, M. K., 2023, AJ, 165, 68 [NASA ADS] [CrossRef] [Google Scholar]
- Yakovleva, S. A., Belyaev, A. K., & Bergemann, M., 2020, Atoms, 8, 34 [NASA ADS] [CrossRef] [Google Scholar]
- Zhao, G., Zhao, Y.-H., Chu, Y.-Q., Jing, Y.-P., & Deng, L.-C., 2012, Res. Astron. Astrophys., 12, 723 [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.