https://elizavetasemenova.github.io/prob-epi
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To correct typos, please make pull requests on GitHub. If these notes ever get published, I will list your name in Acknowledgements.
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For more substantial suggestions about the course content, such as desired topics, please use issues on GitHub or email them to
elizaveta [dot] p [dot] [insert my surname] [at] gmail [dot] com. -
If you enjoyed the content and / or learnt from it, please leave a 'star' to the book's GitHub repository.
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If you are creating a written document (a paper, report, book chapter) where you use what you've learnt here, please cite
@software{Semenova_Bayesian_Modelling_and_2024,
author = {Semenova, Elizaveta},
doi = {10.5281/zenodo.11550659},
month = jun,
title = {{Bayesian Modelling and Probabilistic Programming with Numpyro, and Deep Generative Surrogates for Epidemiology.}},
url = {https://github.com/elizavetasemenova/prob-epi},
version = {v1.0.0},
year = {2024}
}
To run the code examples from the course, the recommended Conda environemnt can be created as follows:
conda create -n aims python=3.9
conda activate aims
conda install -c conda-forge jupyter-book
conda install conda-forge::matplotlib
conda install numpy
conda install conda-forge::ghp-import
conda install conda-forge::numpyro
conda install conda-forge::jax
pip install sphinxcontrib-tikz
conda install conda-forge::geopandas
conda install conda-forge::arviz
conda install anaconda::seaborn
pip install pyppeteer