Diffusion Models

Diffusion models are a class of generative models used in machine learning for tasks such as image and data generation. They operate by modeling the data generation process as a gradual diffusion, transforming data points from a simple distribution to a complex one. These models are particularly beneficial for generating high-quality images and are used in applications like image synthesis, inpainting, and super-resolution.