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[ascl:2306.015] Mangrove: Infer galaxy properties using dark matter merger trees

Mangrove uses Graph Neural Networks to regress baryonic properties directly from full dark matter merger trees to infer galaxy properties. The package includes code for preprocessing the merger tree, and training the model can be done either as single experiments or as a sweep. Mangrove provides loss functions, learning rate schedulers, models, and a script for doing the training on a GPU.

Code site:
https://github.com/astrockragh/Mangrove
Described in:
https://ui.adsabs.harvard.edu/abs/2022ApJ...941....7J
Bibcode:
2023ascl.soft06015J
Preferred citation method:

Please see citation information at https://github.com/astrockragh/Mangrove/blob/main/CITATION.md


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ascl:2306.015
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