Project details for Variation Gaussian Approximate Inference for Bayesian Generalized Linear Models

Logo Variation Gaussian Approximate Inference for Bayesian Generalized Linear Models 1.0

by ed - April 9, 2011, 15:32:27 CET [ BibTeX BibTeX for corresponding Paper Download ]

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Description:

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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