Conditional density estimation tools in python and R with applications to photometric redshifts and likelihood-free cosmological inference

Niccolò Dalmasso, Taylor Pospisil, Ann B. Lee, Rafael Izbicki, Peter E. Freeman, Alex I. Malz. Conditional density estimation tools in python and R with applications to photometric redshifts and likelihood-free cosmological inference. Astron. Comput., 30:100362, 2020. [doi]

@article{DalmassoPLIFM20,
  title = {Conditional density estimation tools in python and R with applications to photometric redshifts and likelihood-free cosmological inference},
  author = {Niccolò Dalmasso and Taylor Pospisil and Ann B. Lee and Rafael Izbicki and Peter E. Freeman and Alex I. Malz},
  year = {2020},
  doi = {10.1016/j.ascom.2019.100362},
  url = {https://doi.org/10.1016/j.ascom.2019.100362},
  researchr = {https://researchr.org/publication/DalmassoPLIFM20},
  cites = {0},
  citedby = {0},
  journal = {Astron. Comput.},
  volume = {30},
  pages = {100362},
}