This package implements variational Gaussian Kullback-Leibler approximate inference for Bayesian generalized linear models. It is an implementation of the methods described in:
E. Challis and D. Barber. Gaussian Kullback-Leibler Approximate Inference. Journal of Machine Learning Research, vol. 14, 2013, pg. 2239-2286. http://jmlr.org/papers/v14/challis13a.html.
- Changes to previous version:
Code restructure and bug fix.
- BibTeX Entry: Download
- Corresponding Paper BibTeX Entry: Download
- Supported Operating Systems: Agnostic
- Data Formats: Matlab
- Tags: Classification, Approximate Inference, Sparse Learning, Variational Inference, Logistic Regression, Gaussian Processes, Generalized Linear Models, Bayesian Inference
- Archive: download here
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