Denoising Diffusion-based Generative Modeling

Diffusion-based generative models such as DALL·E 2 have achieved exceptional image generation quality. Unlike other generative models based on explicit representations of probability distributions (e.g., autoregressive) or implicit sampling procedures (e.g., GANs), diffusion models learn directly the vector field of gradients of the data distribution (scores). This framework allows flexible architectures, requires no sampling during training or the use of adversarial training methods.