lee-group-cmu / NNKCDE

Nearest Neighbor Kernel Conditional Density Estimation

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NNKCDE: Nearest Neighbor Conditional Density Estimation

Estimates nearest neighbor kernel conditional densities tuned using CDE loss.


  title={ABC-CDE: Towards Approximate Bayesian Computation with Complex High-Dimensional Data and Limited Simulations},
  chapter={Fast implementation of of NN-KCDE},
  author={Izbicki, Rafael and Lee, Ann B and Pospisil, Taylor},
  journal={arXiv preprint arXiv:1805.05480},

       author = {{Dalmasso}, N. and {Pospisil}, T. and {Lee}, A.~B. and {Izbicki}, R. and
         {Freeman}, P.~E. and {Malz}, A.~I.},
        title = "{Conditional density estimation tools in python and R with applications to photometric redshifts and likelihood-free cosmological inference}",
      journal = {Astronomy and Computing},
         year = 2020,
        month = jan,
       volume = {30},
          eid = {100362},
        pages = {100362},
          doi = {10.1016/j.ascom.2019.100362}


Nearest Neighbor Kernel Conditional Density Estimation


Language:Jupyter Notebook 92.5%Language:R 4.0%Language:Python 3.5%