Multimodal Deep Learning, Autoencoder, Gan, Vae.
and the decoded output, just like a standard autoencoder. The “regularization term,” often represented as the Kullback-Leibler (KL) divergence, which enforces the latent space to be regularized. It encourages the distribution of latent representations to be close to a standard normal distribution.