satyam-cyc / sivi

Use neural network to construct expressive hierarchical distribution with a novel bound; A fast and robust variational method to estimate posterior uncertainty as accurate as MCMC. ICML 2018

Semi-Implicit Variational Inference (SIVI)

Code to reproduce the results in Semi-Implicit Variational Inference.

Data sets

The data for SIVI_1d.py, SIVI_2d.py, SIVI_NB.py are self-generated in the python script.
The "waveform" data for SIVI_LR.py is in the data folder.
The MNIST data for SIVAE.py is self-contained.
Or of course, just try SIVI with your own datasets and probabilistic models.

Citations

Below are the paper to cite if you find the algorithms in this repository useful in your own research:

@inproceedings{yin2018semi,
  title={Semi-Implicit Variational Inference},
  author={Yin, Mingzhang and Zhou, Mingyuan},
  booktitle={International Conference on Machine Learning},
  pages={5646--5655},
  year={2018}
}

License Info

This code is offered under the MIT License.