Diffusion Models
What are Diffusion Models
Diffusion models are generative machine learning models that create data, typically images, by gradually reversing a noise-adding process. During training, the model learns to remove random noise added to data step by step. This reverse process is then used to generate new samples from pure noise. They are widely applied in image, audio, and video synthesis, offering high output quality and diversity.
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