Probability Zoo

The Probability Zoo is a community repository for pre-trained probabilistic models. It includes any parameters to the model as well as parameters to its inferred posterior (such as a variational approximation or posterior samples).

  • Under construction. Check back soon!

To contribute a pre-trained model to the repository, please submit a pull request. The parameters should be preferably stored in a TensorFlow checkpoint file.

Footnotes

The Probability Zoo is inspired by the model zoo in Caffe (Jia et al., 2014), which provides many pre-trained discriminative neural networks. It is also inspired by Forest (Stuhlmüller, 2012), which provides examples of probabilistic programs.

References

Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., … Darrell, T. (2014). Caffe: Convolutional architecture for fast feature embedding. ArXiv Preprint ArXiv:1408.5093.

Stuhlmüller, A. (2012). Forest: A repository for generative models. Retrieved from http://forestdb.org