Multimodal Deep Learning, Autoencoder, Gan, Vae.
widely used in unsupervised learning for tasks like data generation, image synthesis, and feature learning. They are designed to learn a probabilistic mapping of data to a lower-dimensional latent space, which allows for the generation of new data points that are similar to the training data.