This repository is the official implementation of:
Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic (for the Predictive GAN).
- PredGAN (outdated see DA-PredGAN/UQ-PredGAN folder): Prediction using GAN - applied to the spatio-temporal spread of COVID-19 in an idealized town.
- DA-PredGAN: Data assimilation using GAN - applied to the spatio-temporal spread of COVID-19 in an idealized town.
- UQ-PredGAN: Uncertainty quantification using GAN - applied to the spatio-temporal spread of COVID-19 in an idealized town.
- datasets: Datasets of the spatio-temporal spread of COVID-19 in an idealized town.
- GAN_evaluation: New way of evaluating the GAN training.
- Regularization: Regularization to improve the GAN-based Reduced Order Model.
- MCMC: Comparison between the UQ-PredGAN and the Markov chain Monte Carlo (MCMC) methods.
To install requirements:
$ conda env create -f environment.yml
$ conda activate py3ml
$ python -m ipykernel install --user --name=python3 (optional)
Finally, start Jupyter:
$ jupyter notebook