lee-group-cmu / DeepCDE

Neural networks for conditional density estimation

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DeepCDE: Neural Networks Conditional Density Estimation

Tensorflow and PyTorch code Conditional density estimation via deep neural network using CDE loss.

Authors: Taylor Pospisil, Nic Dalmasso

Citation

@article{dalmasso2020cdetools,
       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}
}

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Neural networks for conditional density estimation

License:MIT License


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Language:Jupyter Notebook 95.1%Language:Python 4.9%