GAN for time series prediction, data assimilation and uncertainty quantification

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).

Data Assimilation Predictive GAN (DA-PredGAN): applied to determine the spread of COVID-19.

GAN for time series prediction, data assimilation and uncertainty quantification.

Directories:

• PredGAN: 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.

Requirements

To install requirements:

 $ conda env create -f environment.yml 
 $ conda activate py3ml
 $ python -m ipykernel install --user --name=python3

Finally, start Jupyter:

 $ jupyter notebook