vault backup: 2024-10-28 10:40:19
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@ -38,4 +38,6 @@ Something to justify, why diffusion model as opposed to other generative AI
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15. But if we destroy the input how can we do this?
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15. But if we destroy the input how can we do this?
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16. Well we train a neural network as a denoiser.
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16. Well we train a neural network as a denoiser.
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17. Because the diffusion model forward steps are small and gaussian, we can know the reverse step is also a gaussian distribution.
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17. Because the diffusion model forward steps are small and gaussian, we can know the reverse step is also a gaussian distribution.
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18. So for our neural network, what we're trying to learn is the mean and standard deviation of the reverse steps for a given timestep.
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18. So for our neural network, what we're trying to learn is the mean and standard deviation of the reverse steps for a given timestep.
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## Writin some stuff
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