Conservation Laws for Diffusion Models

Researchers have developed conservation laws for diffusion models using generalized extrinsic information transfer functions to better analyze their training dynamics. This framework offers a mathematical approach to understanding how these models learn, providing a theoretical alternative to the denoising objectives typically used in current training methods.