vault backup: 2024-10-28 08:59:10
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@ -24,4 +24,13 @@ Something to justify, why diffusion model as opposed to other generative AI
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1. Generating unstructured perturbations is pretty hard
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1. Generating unstructured perturbations is pretty hard
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2. They need to be 'random'
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2. They need to be 'random'
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3. diffusion model is good at creating novel examples (cite!)
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3. diffusion model is good at creating novel examples (cite!)
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4.
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4. we can use diffusion models to solve this problem of generating examples
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5. But how does a diffusion model work?
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6. Diffusion model uses two processes
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7. a forward process that introduces noise into an 'input'
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8. this forward process does this using several small steps of noise
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9. This noise is a gaussian noise
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10. over time this forward process degrades the input until it is unrecognizable
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11. This takes several several iterations, but is dependent on the amount of noise in each step
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12.
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13. A reverse process that tries to remove the noise
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