Neural network-based emulation of interstellar medium models
A&A, 678 (2023) A198
Published online: 2023-10-25
Articles citing this article
The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
Cited article:
This article has been cited by the following article(s):
Neural-network Chemical Emulator for First-star Formation: Robust Iterative Predictions Over a Wide Density Range
Sojun Ono and Kazuyuki SugimuraThe Astrophysical Journal 996 (1) 9 (2026)
https://doi.org/10.3847/1538-4357/ae1ca9
The advancements of astrochemistry models of molecular clouds
继兴 葛, 文仲 蔡, 霞 张, 芳芳 李, 晶晶 王, Ji-Xing Ge, Wen-Zhong Cai, Xia Zhang, Fang-Fang Li and Jing-Jing WangChinese Science Bulletin 70 (30) 5117 (2025)
https://doi.org/10.1360/TB-2024-1141
BEETROOTS: Spatially regularized Bayesian inference of physical parameter maps. Application to Orion
Pierre Palud, Emeric Bron, Pierre Chainais, Franck Le Petit, Pierre-Antoine Thouvenin, Miriam G. Santa-Maria, Javier R. Goicoechea, David Languignon, Maryvonne Gerin, Jérôme Pety, Ivana Bešlić, Simon Coudé, Lucas Einig, Helena Mazurek, Jan H. Orkisz, Léontine Ségal, Antoine Zakardjian, Sébastien Bardeau, Karine Demyk, Victor de Souza Magalhães, Pierre Gratier, Viviana V. Guzmán, Annie Hughes, François Levrier, Jacques Le Bourlot, et al.Astronomy & Astrophysics 698 A311 (2025)
https://doi.org/10.1051/0004-6361/202554266
A complete framework for cosmological emulation and inference with CosmoPower
H T Jense, I Harrison, E Calabrese, A Spurio Mancini, B Bolliet, J Dunkley and J C HillRAS Techniques and Instruments 4 (2025)
https://doi.org/10.1093/rasti/rzaf002
Recovering the properties of the interstellar medium through integrated spectroscopy: Application to the z ∼ 0 ECO volume-limited star-forming galaxy sample
V. Lebouteiller, C. T. Richardson, M. S. Polimera, D. S. Carr, Z. L. Hutchens, S. J. Kannappan, L. Ramambason, A. J. Moffett, M. Varese and S. C. MaddenAstronomy & Astrophysics 695 A31 (2025)
https://doi.org/10.1051/0004-6361/202452103
Mapping synthetic observations to pre-stellar core models: An interpretable machine learning approach
T. Grassi, M. Padovani, D. Galli, N. Vaytet, S. S. Jensen, E. Redaelli, S. Spezzano, S. Bovino and P. CaselliAstronomy & Astrophysics 702 A71 (2025)
https://doi.org/10.1051/0004-6361/202453266
glitterin: Toward Replacing the Role of Lorenz–Mie Theory in Astronomy Using Neural Networks Trained on Light Scattering of Irregularly Shaped Grains
Zhe-Yu Daniel 哲宇 Lin 林, Alycia J. Weinberger, Evgenij Zubko, Jessica A. Arnold and Gorden VideenPublications of the Astronomical Society of the Pacific 137 (12) 124502 (2025)
https://doi.org/10.1088/1538-3873/ae1e2f
Nebular emission from composite star-forming galaxies – I. A novel modelling approach
Christophe Morisset, Stéphane Charlot, Sebastián F Sánchez, Carlos Espinosa-Ponce, Eric Barat and Thomas DautremerMonthly Notices of the Royal Astronomical Society 538 (3) 1884 (2025)
https://doi.org/10.1093/mnras/staf143
Quantifying the informativity of emission lines to infer physical conditions in giant molecular clouds
Lucas Einig, Pierre Palud, Antoine Roueff, Jérôme Pety, Emeric Bron, Franck Le Petit, Maryvonne Gerin, Jocelyn Chanussot, Pierre Chainais, Pierre-Antoine Thouvenin, David Languignon, Ivana Bešlić, Simon Coudé, Helena Mazurek, Jan H. Orkisz, Miriam G. Santa-Maria, Léontine Ségal, Antoine Zakardjian, Sébastien Bardeau, Karine Demyk, Victor de Souza Magalhães, Javier R. Goicoechea, Pierre Gratier, Viviana V. Guzmán, Annie Hughes, et al.Astronomy & Astrophysics 691 A109 (2024)
https://doi.org/10.1051/0004-6361/202451588
MACE: A Machine-learning Approach to Chemistry Emulation
Silke Maes, Frederik De Ceuster, Marie Van de Sande and Leen DecinThe Astrophysical Journal 969 (2) 79 (2024)
https://doi.org/10.3847/1538-4357/ad47a1