Latent Manifold

The concept of a latent manifold is based on the idea that high-dimensional observations often lie on a more regular, lower-dimensional structure. One of the main goals of autoencoders and generative models is to uncover that structure. A latent space that is smooth, continuous, and semantically organized improves both representation quality and generation quality. For this reason, manifold structure is a foundational conceptual framework in deep representation learning.