Citations

To cite pymc-learn in publications, please use the following:

Emaasit, Daniel (2018). Pymc-learn: Practical probabilistic machine
learning in Python. arXiv preprint arXiv:1811.00542.

Or using BibTex as follows:

@article{emaasit2018pymc,
  title={Pymc-learn: Practical probabilistic machine learning in {P}ython},
  author={Emaasit, Daniel and others},
  journal={arXiv preprint arXiv:1811.00542},
  year={2018}
}

If you want to cite pymc-learn for its API, you may also want to consider this reference:

Carlson, Nicole (2018). Custom PyMC3 models built on top of the scikit-learn
API. https://github.com/parsing-science/pymc3_models

Or using BibTex as follows:

@article{Pymc3_models,
  title={pymc3_models: Custom PyMC3 models built on top of the scikit-learn API,
  author={Carlson, Nicole},
  journal={},
  url={https://github.com/parsing-science/pymc3_models}
  year={2018}
}

Papers using pymc-learn

Emaasit, D., and D, Jones. (2018). Custom PyMC3 nonparametric models built on top of scikit-learn API. The Inaugural International Conference on Probabilistic Programming

@InProceedings{ emaasit2018custom,
  author    = { Emaasit, Daniel, and Jones, David },
  title     = { Custom PyMC3 nonparametric models built on top of scikit-learn API},
  booktitle = { The Inaugural International Conference on Probabilistic Programming },
  pages     = {  },
  year      = { 2018 },
  editor    = {  }
}