GaussianMixtureModel¶

class pycave.bayes.gmm.GaussianMixtureModel(config)[source]¶

PyTorch module for a Gaussian mixture model.

Covariances are represented via their Cholesky decomposition for computational efficiency. The model does not have trainable parameters.

Parameters:: config (GaussianMixtureModelConfig) -- The configuration to use for initializing the module's buffers.

Methods

`forward`	Computes the log-probability of observing each of the provided datapoints for each of the GMM's components.
`reset_parameters`	Resets the parameters of the GMM.
`sample`	Samples the provided number of datapoints from the GMM.

Inherited Methods

`load`	Loads the module's configurations and parameters from files in the specified directory at first.
`save`	Saves the module's configuration and parameters to files in the specified directory.

Attributes

`covariances`	The covariance matrices learnt for the GMM's components.
`component_probs`	The probabilities of each component, buffer of shape `[num_components]`.
`means`	The means of each component, buffer of shape `[num_components, num_features]`.
`precisions_cholesky`	The precision matrices for the components' covariances, buffer with a shape dependent on the covariance type, see `CovarianceType`.