GitHub - lzfwan150789/VB-MixEF: Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"

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Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"

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Name		Name	Last commit message	Last commit date
Latest commit History 54 Commits
src/matlab		src/matlab
README.md		README.md
poster_main.pdf		poster_main.pdf
poster_workshop.pdf		poster_workshop.pdf
report.pdf		report.pdf

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Code for ICML 2019 paper on Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations

To-do List:
- added a poster and a technical report about the gradient identities used in the paper (To appear at the ICML workshop on Stein's method) [done]
- added a poster of the main paper. [done]
- [skewness] added a Matlab implementation for the toy example using skew Gaussian and exponentially modified Gaussian. [done]
- [multi-modality] added a Matlab implementation for the toy example using MoG. The implementation is based on this repo [done]
- [heavy tails] To add a Matlab implementation for BLR using t-distribution and symmetric normal inverse Gaussian
- To add a Python implementation for Vadam extensions