What is diffusion model?

Diffusion models are a class of generative models inspired by thermodynamics. They work by progressively adding Gaussian noise to data, destroying its structure. Then, a neural network is trained to reverse this diffusion process, iteratively denoising the data to generate new samples similar to the training data. They are commonly used for image generation, audio synthesis, and other tasks where high-quality, diverse samples are desired.