Open Access
Issue |
A&A
Volume 680, December 2023
|
|
---|---|---|
Article Number | A86 | |
Number of page(s) | 24 | |
Section | Planets and planetary systems | |
DOI | https://doi.org/10.1051/0004-6361/202346085 | |
Published online | 15 December 2023 |
- Abadi, M., Agarwal, A., Barham, P., et al. 2015, TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems, software available from ten-sorflow.org [Google Scholar]
- Absil, O., Milli, J., Mawet, D., et al. 2013, A & A, 559, L12 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Ahmad, F., & Khan, R. A. 2015, Pak. J. Stat. Oper. Res., 11, 331 [CrossRef] [Google Scholar]
- Amara, A., & Quanz, S. P. 2012, MNRAS, 427, 948 [Google Scholar]
- Anderson, T. W., & Darling, D. A. 1952, Ann. Math. Stat., 23, 193 [Google Scholar]
- Beuzit, J.-L., Vigan, A., Mouillet, D., et al. 2019, A & A, 631, A155 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Bohn, A. J., Ginski, C., Kenworthy, M. A., et al. 2021, A & A, 648, A73 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Bonse, M., Garvin, E., Gebhard, T., et al. 2022, Bull. Am. Astron. Soc., 54, 5 [Google Scholar]
- Boureau, Y.-L., Ponce, J., & LeCun, Y. 2010, in International Conference on Machine Learning (ICML), Haifa, Israel, 111 [Google Scholar]
- Bulmer, M. G. 1979, Principles of Statistics (Mineola, New York, USA: Dover Publications) [Google Scholar]
- Cantalloube, F., Mouillet, D., Mugnier, L. M., et al. 2015, A & A, 582, A89 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Cantalloube, F., Dohlen, K., Milli, J., Brandner, W., & Vigan, A. 2019, The Messenger, 176, 25 [NASA ADS] [Google Scholar]
- Cantalloube, F., Gomez-Gonzalez, C., Absil, O., et al. 2020, Proc. SPIE, 11448, 114485A [Google Scholar]
- Chauvin, G., Desidera, S., Lagrange, A.-M., et al. 2017, A & A, 605, L9 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Christiaens, V., Gonzalez, C. A. G., Farkas, R., et al. 2023, J. Open Source Softw., 8, 4774 [NASA ADS] [CrossRef] [Google Scholar]
- D’Agostino, R., & Pearson, E. S. 1973, Biometrika, 60, 613 [Google Scholar]
- Dahlqvist, C.-H., Cantalloube, F., & Absil, O. 2020, A & A, 633, A95 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Dahlqvist, C.-H., Cantalloube, F., & Absil, O. 2021a, A & A, 656, A54 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Dahlqvist, C.-H., Louppe, G., & Absil, O. 2021b, A & A, 646, A49 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Flasseur, O., Denis, L., Thiébaut, É., & Langlois, M. 2018, A & A, 618, A9 [Google Scholar]
- Flasseur, O., Bodrito, T., Mairal, J., et al. 2023, MNRAS, 527, 1534 [NASA ADS] [CrossRef] [Google Scholar]
- Gebhard, T. D., Bonse, M. J., Quanz, S. P., & Schölkopf, B. 2022, A & A, 666, A9 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gneiting, T. 1997, J. Stat. Comput. Simul., 59, 375 [CrossRef] [Google Scholar]
- Goebel, S. B., Guyon, O., Hall, D. N. B., Jovanovic, N., & Atkinson, D. E. 2016, Proc. SPIE, 9909, 417 [Google Scholar]
- Gomez Gonzalez, C., Absil, O., Absil, P.-A., et al. 2016, A & A, 589, A54 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gomez Gonzalez, C., Wertz, O., Absil, O., et al. 2017, AJ, 154, 7 [NASA ADS] [CrossRef] [Google Scholar]
- Gomez Gonzalez, C., Absil, O., & Van Droogenbroeck, M. 2018, A & A, 613, A71 [CrossRef] [EDP Sciences] [Google Scholar]
- Halko, N., Martinsson, P.-G., Shkolnisky, & Tygert, M. 2011, SIAM J. Sci. Comput., 33, 2580 [NASA ADS] [CrossRef] [Google Scholar]
- Hinkley, S., Oppenheimer, B. R., Soummer, R., et al. 2007, ApJ, 654, 633 [NASA ADS] [CrossRef] [Google Scholar]
- Jensen-Clem R. Mawet, D., Gomez Gonzalez, C. A. et al. 2017 AJ 155, 19 [NASA ADS] [CrossRef] [Google Scholar]
- Keppler, M., Benisty, M., Müller, A., et al. 2018, A & A, 617, A44 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Lafreniere D., Marois, C., Doyon, R., Nadeau, D., & Artigau, E. 2007, ApJ 660, 770 [NASA ADS] [CrossRef] [Google Scholar]
- Lilliefors, H. W. 1967, J. Am. Stat. Assoc., 62, 399 [CrossRef] [Google Scholar]
- Lozi, J., Guyon, O., Jovanovic, N., et al. 2018, Proc. SPIE, 10703, 1070359 [Google Scholar]
- Males, J. R., Fitzgerald, M. P., Belikov, R., & Guyon, O. 2021, PASP, 133, 104504 [NASA ADS] [CrossRef] [Google Scholar]
- Marmolejo-Ramos, F., & González-Burgos, J. 2013, Methodology, 9, 137 [CrossRef] [Google Scholar]
- Marois, C., Lafreniere, D., Doyon, R., Macintosh, B., & Nadeau, D. 2006, ApJ, 641, 556 [NASA ADS] [CrossRef] [Google Scholar]
- Marois, C., Lafreniere, D., Macintosh, B., & Doyon, R. 2008a, ApJ, 673, 647 [NASA ADS] [CrossRef] [Google Scholar]
- Marois, C., Macintosh, B., Barman, T., et al. 2008b, Science, 322, 1348 [Google Scholar]
- Marois, C., Zuckerman, B., Konopacky, Q. M., Macintosh, B., & Barman, T. 2010, Nature, 468, 1080 [NASA ADS] [CrossRef] [Google Scholar]
- Marois, C., Correia, C., Galicher, R., et al. 2014, Proc. SPIE, 9148, 91480U [NASA ADS] [CrossRef] [Google Scholar]
- Mawet, D., Serabyn, E., Liewer, K., et al. 2009, ApJ, 709, 53 [Google Scholar]
- Mawet, D., Milli, J., Wahhaj, Z., et al. 2014, ApJ, 792, 97 [Google Scholar]
- Nair, V., & Hinton, G. 2010, in International Conference on Machine Learning (ICML), Haifa, Israël, 807 [Google Scholar]
- Pairet, B., Cantalloube, F., Gomez Gonzalez, C. A., Absil, O., & Jacques, L. 2019, MNRAS, 487, 2262 [CrossRef] [Google Scholar]
- Patricio, M., Ferreira, F., Oliveiros, B., & Caramelo, F. 2017, Commun. Stat. Simul. Comput., 46, 7535 [CrossRef] [Google Scholar]
- Rameau, J., Chauvin, G., Lagrange, A.-M., et al. 2013, ApJ, 772, L15 [Google Scholar]
- Ren, B., Pueyo, L., Zhu, G. B., Debes, J., & Duchêne, G. 2018, ApJ, 852, 1 [Google Scholar]
- Ruffio, J.-B., Macintosh, B., Wang, J. J., et al. 2017, ApJ, 842, 14 [Google Scholar]
- Samland, M., Bouwman, J., Hogg, D. W., et al. 2021, A & A, 646, A24 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Schölkopf, B., Hogg, D. W., Wang, D., et al. 2016, PNAS, 113, 7391 [CrossRef] [Google Scholar]
- Serabyn, E., Huby, E., Matthews, K., et al. 2017, AJ, 153, 43 [NASA ADS] [CrossRef] [Google Scholar]
- Shapiro, S. S., & Wilk, M. B. 1965, Biometrika, 52, 591 [Google Scholar]
- Shi, X., Chen, Z., Wang, H., et al. 2015, in Advances in Neural Information Processing Systems, 1 (NeurIPS), 802 [Google Scholar]
- Skrutskie, M. F., Jones, T., Hinz, P., et al. 2010, Proc. SPIE, 7735, 77353H [NASA ADS] [CrossRef] [Google Scholar]
- Snik, F., Absil, O., Baudoz, P., et al. 2018, Proc. SPIE, 10706, 107062L [NASA ADS] [Google Scholar]
- Soummer, R. 2005, ApJ, 618, L161 [Google Scholar]
- Soummer, R., Ferrari, A., Aime, C., & Jolissaint, L. 2007, ApJ, 669, 642 [Google Scholar]
- Soummer, R., Pueyo, L., & Larkin, J. 2012, ApJ, 755, L28 [Google Scholar]
- Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. 2014 J. Mach. Learn. Res. 15, 1929 [Google Scholar]
- Uhm, T., & Yi, S. 2021, Commun. Stat. Simul. Comput., 1 [Google Scholar]
- Vovk, V., & Wang, R. 2020, Biometrika, 107, 791 [CrossRef] [Google Scholar]
- Wagner, K., Apai, D., Kasper, M., et al. 2016, Science, 353, 673 [NASA ADS] [CrossRef] [Google Scholar]
- Wahhaj, Z., Cieza, L. A., Mawet, D., et al. 2015, A & A, 581, A24 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Wijekularathna, D. K., Manage, A. B. W., & Scariano, S. M. 2019, Commun. Stat. Simul. Comput., 51, 757 [Google Scholar]
- Yap, B. W., & Sim, C. H. 2011, J. Stat. Comput. Simul., 81, 2141 [CrossRef] [Google Scholar]
- Yip, K. H., Nikolaou, N., Coronica, P., et al. 2020, in Lecture Notes in Computer Science, 11908, Joint European Conference on Machine Learning and Knowledge Discovery in Databases (Springer International Publishing), 322 [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.