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ibm.com
What are Diffusion Models? | IBM
Diffusion models are generative models that “diffuse” training data with random noise, then learn to reverse the diffusion process to output new images.
Aug 21, 2024
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SCIENCE | FACTS | BEYOND | HISTORY | on Instagram: "Think of diffusion models like reverse smudging. Start with noise: Begin with a random pattern of pixels — pure static. Step by step, remove noise: The model gradually refines the image, removing randomness while adding structure. Guided by patterns: It knows what features belong where based on training data. Result emerges: After multiple iterations, a clear, realistic image appears from pure noise. It’s called a “diffusion” model because it s
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