When using pyABC version >= 0.8, please cite:

  • Schälte, Y., Klinger, E., Alamoudi, E., Hasenauer, J., 2022. pyABC: Efficient and robust easy-to-use approximate Bayesian computation. Journal of Open Source Software.

      title = {pyABC: Efficient and robust easy-to-use approximate Bayesian computation},
      author = {Schälte, Yannik and Klinger, Emmanuel and Alamoudi, Emad and Hasenauer, Jan},
      journal = {Journal of Open Source Software},
      publisher = {The Open Journal},
      year = {2022},
      volume = {7},
      number = {74},
      pages = {4304},
      doi = {10.21105/joss.04304},
      url = {},

When using pyABC version < 0.8 or functionality not introduced in later versions, please (also) cite:

  • Klinger, E., Rickert, D., Hasenauer, J., 2018. pyABC: distributed, likelihood-free inference. Bioinformatics.

      title = {pyABC: distributed, likelihood-free inference},
      author = {Klinger, Emmanuel and Rickert, Dennis and Hasenauer, Jan},
      journal = {Bioinformatics},
      volume = {34},
      number = {20},
      pages = {3591--3593},
      year = {2018},
      publisher={Oxford University Press},

When presenting work that uses pyABC, feel free to use the icons in, which are available under a CCO license.

pyABC has been cited and used in numerous publications, see e.g. Google Scholar.