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https://github.com/JavierOrjuela/BayesianNeuralNets_CMB
https://github.com/JavierOrjuela/BayesianNeuralNets_CMB
Last synced: 4 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/JavierOrjuela/BayesianNeuralNets_CMB
- Owner: JavierOrjuela
- Created: 2019-11-06T10:58:03.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-09-23T13:20:37.000Z (almost 4 years ago)
- Last Synced: 2024-01-16T10:46:33.546Z (5 months ago)
- Language: Python
- Size: 896 KB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Lists
- awesome-stars - JavierOrjuela/BayesianNeuralNets_CMB - (Python)
README
# Bayesian Neural Networks for inference in Astrophysics and Cosmology
Thank you for your interest in our papers:
Hector J. Hortua, et.al
Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks
arXiv:1911.08508, https://arxiv.org/abs/1911.08508
Hector J. Hortua, et.al
Constraining the reionization history using Bayesian normalizing flows,Mach. Learn.: Sci. Technol. 1 035014, 2020
https://doi.org/10.1088/2632-2153/aba6f1
Please consider citing the paper when any of the material is used for your research.
Data_generator provide a dataset for either CMB Temperature(+Polarization) or 21cm maps. Additionally, the DropourBNN_example.py shows an example of BNN using Dropout. For a more general treatment of BNN, download the Argo library https://github.com/rist-ro/argo
Chains.zip and PS_POL...npy, PS_TT...npy are the chains generated from Cobaya and BNNs(Argo Lib.) respectively reported in the Sec.II of the paper "Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks".