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Extensions to torch distributions

Examples:

import torch.distributions as torchd
import probabll.distributions as probd
probd.Kumaraswamy(a=torch.ones(1), b=torch.ones(1))
probd.MixtureOfGaussians(logits=torch.ones(2), components=torchd.Normal(loc=torch.zeros(2), scale=torch.ones(2)))

Installation

  • Dependencies
pip install -r requirements.txt
  • For developers
python setup.py develop
  • For users
pip install .

Sparse relaxations to binary random variables

Sparse distributions for pytorch:

  • HardKumaraswamy
  • Mixture of delta and Exponential

Contributors

Though the history of commits won't necessarily show it, this code base received contributions from:

Citation

If you use HardKumaraswamy please cite this paper:

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Extensions to torch distributions

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