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wassname/denoising-diffusion-pytorch
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mirror of https://github.com/wassname/denoising-diffusion-pytorch.git synced 2026-10-03 12:20:18 +08:00
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88 Commits 2 Branches 127 Tags
c44d3ea01deda4925c32cd63d85269e7c15b1e3f
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8 Commits
Author SHA1 Message Date
Phil Wang c44d3ea01d learned noise schedule seems to be working, allow for one to make the monotonic net learn a bit more slowly than the unet 2022-06-08 12:34:07 -07:00
Phil Wang c4991f576f allow for configuring the hidden dimension of the monotonic mlp parameterizing the noise schedule 2022-06-08 11:18:54 -07:00
Phil Wang a19331aa59 fix learned noise schedule 2022-06-08 10:19:02 -07:00
Phil Wang 94eabaca1a complete learned noise schedule for variational ddpm paper, still need to finish cosine alpha schedule in log(snr) form 2022-06-08 09:47:09 -07:00
Phil Wang eaf9d9fdc4 unet needs to be conditioned on log(snr) in p_mean_variance for continuous time gaussian diffusion 2022-06-08 00:41:41 -07:00
Phil Wang 3bf5e768c2 use a non-sinusoidal embedded condition for continuous time gaussian diffusion conditioned on log(snr) 2022-06-07 21:15:27 -07:00
Phil Wang 532178a6a3 assume when sampling all batch samples are at the same time, and do not noise for the last time step 2022-06-07 16:12:44 -07:00
Phil Wang 3bbb6ebf16 get working version of gaussian diffusion with continuous time (only beta linear schedule for now, but will eventually contain alpha cosine schedule as well as parameterized, learned monotonic MLP) 2022-06-07 15:59:29 -07:00
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