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ml-recall

#linear-schedule

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hardAI-checkedDiffusion Models

DDPM uses T=1000T = 1000 steps with βt\beta_t increasing linearly from β1=10−4\beta_1 = 10^{-4} to βT=0.02\beta_T = 0.02. In xT=αˉT x0+1−αˉT ϵx_T = \sqrt{\bar\alpha_T}\,x_0 + \sqrt{1-\bar\alpha_T}\,\epsilon, roughly how large is the signal coefficient αˉT\sqrt{\bar\alpha_T}? Hint: ln⁡αˉT=∑tln⁡(1−βt)≈−∑tβt\ln \bar\alpha_T = \sum_t \ln(1-\beta_t) \approx -\sum_t \beta_t.

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