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annfore-results's Introduction

Reproducing the Results from the Paper:

Biazzo, I., Braunstein, A., Dall'Asta, L., & Mazza, F. (2022). A Bayesian generative neural network framework for epidemic inference problems. Scientific Reports, 12(1), 19673. https://doi.org/10.1038/s41598-022-20898-x

This repository contains the code and resources necessary to reproduce the results presented in the paper.

Getting Started

To set up the environment and reproduce the results, follow these steps:

  1. Clone the epigen repository:

    The epigen repository contains the core epidemic inference framework. Clone and install it using pip:

    git clone https://github.com/sibyl-team/epigen
    cd epigen
    pip install .
  2. Clone the annfore repository: The annfore repository provides the neural network models used in the study. Clone and install it, preferably with the -e option to enable editable mode:

git clone https://github.com/ocadni/annfore
cd annfore
pip install -e .
  1. You’re ready to go: After completing the installations, you can run the provided scripts and notebooks to reproduce the paper's results.

Citation

If you use this code in your research, please cite the following paper:

Biazzo, I., Braunstein, A., Dall’Asta, L., & Mazza, F. (2022). A Bayesian generative neural network framework for epidemic inference problems. Scientific Reports, 12(1), 19673. DOI: 10.1038/s41598-022-20898-x

annfore-results's People

Contributors

fabmazz avatar ocadni avatar

Watchers

Alfredo Braunstein avatar  avatar  avatar

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