Geometry-Preserving Encoder/Decoder in Latent Generative Models

ArXi:2501.09876v3 Announce Type: replace-cross Generative modeling aims to generate new data samples that resemble a given dataset. When using diffusion models for this task, one of the main challenges is solving the problem in the input space, which tends to be very high-dimensional. To address this, recent approaches solve diffusion models in the latent space through an encoder that maps from the data space to a lower-dimensional latent space, improving