https://github.com/JavierOrjuela/BayesianNeuralNets_CMB

https://github.com/JavierOrjuela/BayesianNeuralNets_CMB

Last synced: 3 months ago
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• Host: GitHub
• URL: https://github.com/JavierOrjuela/BayesianNeuralNets_CMB
• Owner: JavierOrjuela
• Created: 2019-11-06T10:58:03.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2020-09-23T13:20:37.000Z (about 4 years ago)
• Last Synced: 2024-07-04T02:13:05.145Z (4 months ago)
• Language: Python
• Size: 896 KB
• Stars: 5
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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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".