References

Citations

If you use MadMiner, please cite our main publication,

@article{Brehmer:2019xox,
      author         = "Brehmer, Johann and Kling, Felix and Espejo, Irina and
                        Cranmer, Kyle",
      title          = "{MadMiner: Machine learning-based inference for particle
                        physics}",
      year           = "2019",
      eprint         = "1907.10621",
      archivePrefix  = "arXiv",
      primaryClass   = "hep-ph",
      SLACcitation   = "%%CITATION = ARXIV:1907.10621;%%"
}

The code itself can be cited as

@misc{MadMiner_code,
      author         = "Brehmer, Johann and Kling, Felix and Espejo, Irina and Cranmer, Kyle",
      title          = "{MadMiner}",
      doi            = "10.5281/zenodo.1489147",
      url            = {https://github.com/diana-hep/madminer}
}

The main references for the implemented inference techniques are the following:

Acknowledgements

We are immensely grateful to all contributors and bug reporters! In particular, we would like to thank Zubair Bhatti, Lukas Heinrich, Alexander Held, and Samuel Homiller.

The SCANDAL inference method is based on Masked Autoregressive Flows, and our implementation is a pyTorch port of the original code by George Papamakarios et al., which is available at https://github.com/gpapamak/maf.

The setup.py was adapted from https://github.com/kennethreitz/setup.py.