Variational Autoencoder
An autoencoder that learns a smooth, samplable latent space.
A VAE encodes inputs into a probability distribution over a latent space and decodes samples back into data, learning a continuous representation you can sample from to generate new examples. VAEs are a foundational generative model and a building block of systems like latent diffusion.