Decoder_weights         Extract decoder-only weights from a trained
                        Keras model
Encoder_weights         Extract encoder-only weights from a trained
                        Keras model
Latent_sample           Sample from the latent space
VAE_train               Train an AutoTab VAE on mixed-type tabular data
decoder_model           Builds the decoder graph for an AutoTab VAE
encoder_decoder_information
                        Specifying Encoder and Decoder Architectures
                        for 'VAE_train()'
encoder_latent          Rebuild the encoder graph to export z_mean and
                        z_log_var
extracting_distribution
                        Build the 'feat_dist' data frame for AutoTab
feat_reorder            Reorder 'feat_dist' rows to match preprocessed
                        data
get_feat_dist           Get the stored feature distribution
min_max_scale           Min–max scale continuous variables
mog_prior               Mixture-of-Gaussians (MoG) prior in AutoTab
reset_seeds             Reset all random seeds across R, TensorFlow,
                        and Python
set_feat_dist           Set the feature distribution for AutoTab
