OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany

Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa Eichel, Till Bärnighausen, Ullrich Köthe. OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany. PLoS Computational Biology, 17(10), 2021. [doi]

@article{RadevGCMEBK21,
  title = {OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany},
  author = {Stefan T. Radev and Frederik Graw and Simiao Chen and Nico T. Mutters and Vanessa Eichel and Till Bärnighausen and Ullrich Köthe},
  year = {2021},
  doi = {10.1371/journal.pcbi.1009472},
  url = {https://doi.org/10.1371/journal.pcbi.1009472},
  researchr = {https://researchr.org/publication/RadevGCMEBK21},
  cites = {0},
  citedby = {0},
  journal = {PLoS Computational Biology},
  volume = {17},
  number = {10},
}