1. Minka, T., Winn, J.M., Guiver, J.P., Webster, S., Zaykov, Y., Yangel, B., Spengler, A., Bronskill, J.: Infer.NET 2.5. Microsoft Research, Cambridge (2013). http://research.microsoft.com/infernet
2. Tehrani, N.K., Arora, N.S., Noursi, D., Tingley, M., Torabi, N., Lippert, E.: Bean machine: a declarative probabilistic programming language for efficient programmable inference. In: PGM (2020)
3. Modeling Censored Time-to-Event Data Using Pyro (2019). https://eng.uber.com/modeling-censored-time-to-event-data-using-pyro/
4. Flaxman, S., Mishra, S., Gandy, A., Unwin, H.J.T., Mellan, T.A., Coupland, H., Whittaker, C., Zhu, H., Berah, T., Eaton, J.W., et al.: Estimating the effects of non-pharmaceutical interventions on Covid-19 in Europe. Nature, 1–5 (2020)
5. Gelman, A.: Stan being used to study and fight coronavirus. Stan Forums (2020). https://discourse.mc-stan.org/t/stan-being-used-to-study-and-fight-coronavirus/14296