EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 591 (July 2016) A&A, 591 (2016) A54 References
Free Access
Issue
A&A
Volume 591, July 2016
Article Number A54
Number of page(s) 10
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/201628660
Published online 10 June 2016
  1. Robitaille, T. P., Tollerud, E. J., Astropy Collaboration, et al. 2013, A&A, 558, A33 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  2. Avila, R., et al. 2016, ACS Instrument Handbook, version 15.0 (Baltimore: STScI) [Google Scholar]
  3. Bengio, Y. 2009, Foundations and trendsR◯in Machine Learning, 2, 1 [Google Scholar]
  4. Bishop, C. M. 1995, Neural Networks for Pattern Recognition (New York, NY, USA: Oxford University Press, Inc.) [Google Scholar]
  5. Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, in Interstellar Dust, eds. L. J. Allamandola, & A. G. G. M. Tielens, IAU Symp., 135, 5 [Google Scholar]
  6. Chabrier, G. 2003, PASP, 115, 763 [NASA ADS] [CrossRef] [Google Scholar]
  7. Cropper, M., Hoekstra, H., Kitching, T., et al. 2013, MNRAS, 431, 3103 [NASA ADS] [CrossRef] [Google Scholar]
  8. Cypriano, E. S., Amara, A., Voigt, L. M., et al. 2010, MNRAS, 405, 494 [NASA ADS] [Google Scholar]
  9. de Bruijne, Allen, M., Azaz, S., et al. 2015, A&A, 576, A74 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  10. Ford, H. C., Feldman, P. D., Golimowski, D. A., et al. 1996, in Space Telescopes and Instruments IV, Proc. SPIE, 2807, 184 [Google Scholar]
  11. Gentile, M., Courbin, F., & Meylan, G. 2013, A&A, 549, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Graff, P., Feroz, F., Hobson, M. P., & Lasenby, A. 2014, MNRAS, 441, 1741 [NASA ADS] [CrossRef] [Google Scholar]
  13. Hastie, T., Tibshirani, R., & Friedman, J. 2009, The elements of statistical learning: data mining, inference and prediction, 2nd edn. (Springer) [Google Scholar]
  14. Hunter, J. 2007, Comput. Sci. Eng., 9, 90 [Google Scholar]
  15. Ivezić, Ž., Connolly, A., Vanderplas, J., & Gray, A. 2014, Statistics, Data Mining and Machine Learning in Astronomy (Princeton University Press) [Google Scholar]
  16. Jarvis, M., & Jain, B. 2004, ArXiv e-prints [arXiv:astro-ph/0412234] [Google Scholar]
  17. Krist, J. E., Hook, R. N., & Stoehr, F. 2011, in SPIE Conf. Ser., 8127, 0 [Google Scholar]
  18. Kuntzer, T., Courbin, F., & Meylan, G. 2016, A&A, 586, A74 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  19. Laureijs, R., Amiaux, J., Arduini, S., et al. 2011, Euclid Study Report, ArXiv e-prints [arXiv:1110.3193] [Google Scholar]
  20. Massey, R., Hoekstra, H., Kitching, T., et al. 2013, MNRAS, 429, 661 [Google Scholar]
  21. Ness, M., Hogg, D. W., Rix, H.-W., Ho, A. Y. Q., & Zasowski, G. 2015, ApJ, 808, 16 [NASA ADS] [CrossRef] [Google Scholar]
  22. Nguyen, A., Yosinski, J., & Clune, J. 2015, in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Google Scholar]
  23. Nielsen, M. 2015, Neural Networks and Deep Learning (Determination Press) [Google Scholar]
  24. Niemi, S.-M., Kitching, T. D., & Cropper, M. 2015, MNRAS, 454, 1221 [NASA ADS] [CrossRef] [Google Scholar]
  25. Nissen, S. 2003, Report, Department of Computer Science University of Copenhagen (DIKU), 31 [Google Scholar]
  26. Pearson, K. 1901, Philosophical Magazine Series 6, 559 [Google Scholar]
  27. Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, J. Mach. Learn. Res., 12, 2825 [Google Scholar]
  28. Pickles, A. J. 1998, PASP, 110, 863 [CrossRef] [Google Scholar]
  29. Robin, A. C., Reylé, C., Derrière, S., & Picaud, S. 2003, A&A, 409, 523 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  30. Schlafly, E. F., & Finkbeiner, D. P. 2011, ApJ, 737, 103 [NASA ADS] [CrossRef] [Google Scholar]
  31. Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 525 [NASA ADS] [CrossRef] [Google Scholar]
  32. Semboloni, E., Hoekstra, H., Huang, Z., et al. 2013, MNRAS, 432, 2385 [NASA ADS] [CrossRef] [Google Scholar]
  33. Shlens, J. 2014, ArXiv e-prints [arXiv:1404.1100] [Google Scholar]
  34. Sirianni, M., Jee, M. J., Benítez, N., et al. 2005, PASP, 117, 1049 [NASA ADS] [CrossRef] [Google Scholar]
  35. Smiljanic,Korn, A. J., Bergemann, M., et al. 2014, A&A, 570, A122 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  36. Spergel, D., Gehrels, N., Baltay, C., et al. 2015, ArXiv e-prints [arXiv:1503.03757] [Google Scholar]
  37. van der Walt, S., Colbert, S., & Varoquaux, G. 2011, Comp. Sci. Eng., 13, 22 [Google Scholar]
  38. Voigt, L. M., Bridle, S. L., Amara, A., et al. 2012, MNRAS, 421, 1385 [NASA ADS] [CrossRef] [Google Scholar]
  39. Yang, T., & Li, X. 2015, MNRAS, 452, 158 [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.