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Authors
Silke Maes (0000-0003-4159-9964), Frederik De Ceuster (0000-0001-5887-8498), Marie Van de Sande (0000-0001-9298-6265), Leen Decin (0000-0002-5342-8612)
Citation
Maes et al., (2025). MACE: a Machine-learning Approach to Chemistry Emulation. Journal of Open Source Software, 10(108), 7148, https://doi.org/10.21105/joss.07148
@article{Maes2025,
doi = {10.21105/joss.07148},
url = {https://doi.org/10.21105/joss.07148},
year = {2025},
publisher = {The Open Journal},
volume = {10},
number = {108},
pages = {7148},
author = {Silke Maes and Frederik De Ceuster and Marie Van de Sande and Leen Decin},
title = {MACE: a Machine-learning Approach to Chemistry Emulation},
journal = {Journal of Open Source Software}
}
Tags
astrophysics chemistry surrogate model stellar winds
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