Exploring Effects of Modified Machine Learning Pipelines of Astrochemical Inventories
Machine learning pipelines for astrochemical inventories have been introduced as a useful addition to the astrochemist toolbox, having first been used to model and predict column densities in the Taurus Molecular Cloud (TMC-1). Rapid changes in the field of machine learning have provided new tools i...
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| Main Authors: | Hannah Toru Shay, Haley N. Scolati, Gabi Wenzel, Kin Long Kelvin Lee, Aravindh N. Marimuthu, Brett A. McGuire |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | The Astrophysical Journal |
| Subjects: | |
| Online Access: | https://doi.org/10.3847/1538-4357/adc80b |
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