Open Access
Issue
A&A
Volume 706, February 2026
Article Number A242
Number of page(s) 18
Section Catalogs and data
DOI https://doi.org/10.1051/0004-6361/202452293
Published online 13 February 2026
  1. Abadi, M., Agarwal, A., Barham, P., et al. 2015, TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems, software available from https://tensorflow.org [Google Scholar]
  2. Alves, J., Lombardi, M., & Lada, C. J. 2007, A&A, 462, L17 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  3. Alves de Oliveira, C., Schneider, N., Merín, B., et al. 2014, A&A, 568, A98 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  4. André, P., Di Francesco, J., Ward-Thompson, D., et al. 2014, in Protostars and Planets VI, eds. H. Beuther, R. S. Klessen, C. P. Dullemond, & T. Henning, 27 [Google Scholar]
  5. Angus Comrie, Kuo-Song Wang, Shou-Chieh Hsu, et al. 2021, CARTA: The Cube Analysis and Rendering Tool for Astronomy [Google Scholar]
  6. Astropy Collaboration (Robitaille, T. P., et al.) 2013, A&A, 558, A33 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  7. Astropy Collaboration (Price-Whelan, A. M., et al.) 2018, AJ, 156, 123 [Google Scholar]
  8. Astropy Collaboration (Price-Whelan, A. M., et al.) 2022, ApJ, 935, 167 [NASA ADS] [CrossRef] [Google Scholar]
  9. Ay, M., Özbakır, L., Kulluk, S., et al. 2023, Expert Syst. Appl., 211, 118656 [Google Scholar]
  10. Basu, S., Banerjee, A., & Mooney, R. J. 2002, in Machine Learning, Proceedings of the Nineteenth International Conference (ICML 2002), University of New South Wales, Sydney, Australia, July 8–12, 2002 [Google Scholar]
  11. Benedettini, M., Traficante, A., Olmi, L., et al. 2021, A&A, 654, A144 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Bergin, E. A., & Tafalla, M. 2007, ARA&A, 45, 339 [Google Scholar]
  13. Berry, D. S. 2015, Astron. Comput., 10, 22 [Google Scholar]
  14. Beuther, H., Linz, H., Henning, T., et al. 2011, A&A, 531, A26 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  15. Beuther, H., Tackenberg, J., Linz, H., et al. 2012, ApJ, 747, 43 [Google Scholar]
  16. Blitz, L., & Williams, J. P. 1999, The Origin of Stars and Planetary Systems, eds. C. J. Lada & N. D. Kylafis, 540, 3 [Google Scholar]
  17. Caron, M., Bojanowski, P., Joulin, A., & Douze, M. 2018, in Proceedings of the European Conference on Computer Vision (ECCV) [Google Scholar]
  18. Chen, Z., Sun, W., Chini, R., et al. 2021, ApJ, 922, 90 [NASA ADS] [CrossRef] [Google Scholar]
  19. Cheng, T.-Y., Conselice, C. J., Aragón-Salamanca, A., et al. 2020, MNRAS, 493, 4209 [Google Scholar]
  20. Clark, P. C., Klessen, R. S., & Bonnell, I. A. 2007, MNRAS, 379, 57 [NASA ADS] [CrossRef] [Google Scholar]
  21. Colombo, D., Hughes, A., Schinnerer, E., et al. 2014, ApJ, 784, 3 [NASA ADS] [CrossRef] [Google Scholar]
  22. Cunha, P. A. C., Humphrey, A., Brinchmann, J., et al. 2024, A&A, 687, A269 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  23. Demianenko, M., Malanchev, K., Samorodova, E., et al. 2023, A&A, 677, A16 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Eden, D. J., Moore, T. J. T., Currie, M. J., et al. 2020, MNRAS, 498, 5936 [NASA ADS] [CrossRef] [Google Scholar]
  25. Elia, D., Merello, M., Molinari, S., et al. 2021, MNRAS, 504, 2742 [NASA ADS] [CrossRef] [Google Scholar]
  26. Faesi, C. M., Lada, C. J., & Forbrich, J. 2016, ApJ, 821, 125 [NASA ADS] [CrossRef] [Google Scholar]
  27. Han, J., Kamber, M., & Pei, J. 2012, in Data Mining, third edn., eds. J. Han, M. Kamber, & J. Pei, The Morgan Kaufmann Series in Data Management Systems (Boston: Morgan Kaufmann), 497 [Google Scholar]
  28. He, Z., Qiu, B., Luo, A. L., et al. 2021, MNRAS, 508, 2039 [NASA ADS] [CrossRef] [Google Scholar]
  29. Heyer, M., & Dame, T. 2015, ARA&A, 53, 583 [NASA ADS] [CrossRef] [Google Scholar]
  30. Jackson, J. M., Rathborne, J. M., Shah, R. Y., et al. 2006, ApJS, 163, 145 [NASA ADS] [CrossRef] [Google Scholar]
  31. Ji, Q., & Haralick, R. M. 2002, Pattern Recognit., 35, 689 [Google Scholar]
  32. Jiang, Y., Chen, Z., Zheng, S., et al. 2023, ApJS, 267, 32 [NASA ADS] [CrossRef] [Google Scholar]
  33. Karpfinger, C. 2022, Polynomial and Spline Interpolation (Berlin, Heidelberg: Springer Berlin Heidelberg), 311 [Google Scholar]
  34. Kerton, C. R., Arvidsson, K., & Alexander, M. J. 2013, AJ, 145, 78 [Google Scholar]
  35. Khan, S., Pandian, J. D., Lal, D. V., et al. 2022, A&A, 664, A140 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  36. Krumholz, M. R., & McKee, C. F. 2005, ApJ, 630, 250 [Google Scholar]
  37. Liu, L., Bureau, M., Li, G.-X., et al. 2022, MNRAS, 517, 632 [NASA ADS] [CrossRef] [Google Scholar]
  38. Luo, X., Zheng, S., Huang, Y., et al. 2022, Res. Astron. Astrophys., 22, 015003 [CrossRef] [Google Scholar]
  39. Luo, X., Zheng, S., Jiang, Z., et al. 2024a, A&A, 683, A104 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  40. Luo, X., Zheng, S., Jiang, Z., et al. 2024b, Res. Astron. Astrophys., 24, 055018 [Google Scholar]
  41. Medina, S. N. X., Urquhart, J. S., Dzib, S. A., et al. 2019, A&A, 627, A175 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  42. Mège, P., Russeil, D., Zavagno, A., et al. 2021, A&A, 646, A74 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  43. Molinari, S., Schisano, E., Elia, D., et al. 2016, A&A, 591, A149 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  44. Motte, F., Bontemps, S., & Louvet, F. 2018, ARA&A, 56, 41 [NASA ADS] [CrossRef] [Google Scholar]
  45. Nakanishi, H., Fujita, S., Tachihara, K., et al. 2020, PASJ, 72, 43 [CrossRef] [Google Scholar]
  46. Ohashi, S., Sanhueza, P., Chen, H.-R. V., et al. 2016, ApJ, 833, 209 [NASA ADS] [CrossRef] [Google Scholar]
  47. Ooyama, K. V. 2002, Monthly Weather Rev., 130, 2392 [Google Scholar]
  48. Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, J. Mach. Learn. Res., 12, 2825 [Google Scholar]
  49. Rani, R., Moore, T. J. T., Eden, D. J., et al. 2023, MNRAS, 523, 1832 [NASA ADS] [CrossRef] [Google Scholar]
  50. Rathborne, J. M., Johnson, A. M., Jackson, J. M., Shah, R. Y., & Simon, R. 2009, ApJS, 182, 131 [NASA ADS] [CrossRef] [Google Scholar]
  51. Reid, M. J., Menten, K. M., Brunthaler, A., et al. 2014, ApJ, 783, 130 [Google Scholar]
  52. Rigby, A. J., Moore, T. J. T., Plume, R., et al. 2016, MNRAS, 456, 2885 [NASA ADS] [CrossRef] [Google Scholar]
  53. Rigby, A. J., Moore, T. J. T., Eden, D. J., et al. 2019, A&A, 632, A58 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  54. Rojas, K., Savary, E., Clément, B., et al. 2022, A&A, 668, A73 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  55. Rosolowsky, E. 2005, PASP, 117, 1403 [NASA ADS] [CrossRef] [Google Scholar]
  56. Rosolowsky, E. W., Pineda, J. E., Kauffmann, J., & Goodman, A. A. 2008, ApJ, 679, 1338 [Google Scholar]
  57. Schuller, F., Csengeri, T., Urquhart, J. S., et al. 2017, A&A, 601, A124 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  58. Smartt, S. J., & Rolleston, W. R. J. 1997, ApJ, 481, L47 [Google Scholar]
  59. Su, Y., Sun, Y., Li, C., et al. 2016, ApJ, 828, 59 [Google Scholar]
  60. Su, Y., Yang, J., Zhang, S., et al. 2019, ApJS, 240, 9 [Google Scholar]
  61. Takekoshi, T., Fujita, S., Nishimura, A., et al. 2019, ApJ, 883, 156 [NASA ADS] [CrossRef] [Google Scholar]
  62. Tremblin, P., Schneider, N., Minier, V., et al. 2014, A&A, 564, A106 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  63. Umemoto, T., Minamidani, T., Kuno, N., et al. 2017, PASJ, 69, 78 [Google Scholar]
  64. Urquhart, J. S., König, C., Colombo, D., et al. 2024, MNRAS, 528, 4746 [Google Scholar]
  65. Williams, J. P., de Geus, E. J., & Blitz, L. 1994, ApJ, 428, 693 [Google Scholar]
  66. Williams, J. P., Blitz, L., & McKee, C. F. 2000, in Protostars and Planets IV, eds. V. Mannings, A. P. Boss, & S. S. Russell, 97 [Google Scholar]
  67. Wurster, J., & Rowan, C. 2023, MNRAS, 523, 3025 [NASA ADS] [CrossRef] [Google Scholar]
  68. Yoo, H., Lee, C. W., Chung, E. J., et al. 2023, ApJ, 957, 94 [Google Scholar]
  69. Zhang, Q., Wang, Y., Pillai, T., & Rathborne, J. 2009, ApJ, 696, 268 [Google Scholar]
  70. Zhang, S., Zavagno, A., López-Sepulcre, A., et al. 2021, A&A, 646, A25 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  71. Zinnecker, H., & Yorke, H. W. 2007, ARA&A, 45, 481 [Google Scholar]

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