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VBLab is a probabilistic programming software package, currently available in Matlab, allowing automatic variational Bayesian (VB) inference on many pre-defined common statistical models and also user-defined models. Key features:

Name and Value specify additional options using one or more name-value pair arguments. For example, you can specify how many samples used to estimate the lower bound. See: Input Arguments, Output Argument, Examples. The statistical models containing unknown parameters, can be specified as: VBLab model object.

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Official documentation. Contribute to VBayesLab/VBLab development by creating an account on GitHub.

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Run CGVB to obtain VB approximation of the posterior distribution of model parameters. By default, the algorithm will initialize the variational parameters using a normal distribution with a small variance. %% Run Cholesky GVB with random initialization Estmdl_1 = CGVB(Mdl,labour,... 'LearningRate',0.002,... % Learning rate 'NumSample',50,...

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