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Beta Diffusion

NeurIPS 2023 · Image generation › Fast diffusion sampling · approach: Denoising diffusion probabilistic models · 0 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use beta diffusion instead of Gaussian VP-EDMCIFAR-10 image generation · CIFAR-10FID: 1.97 -> 3.06Hurt
use beta diffusion instead of VDMCIFAR-10 image generation · CIFAR-10FID: 4.00 -> 3.06Helped
swap the KLUB arguments, yielding the negative ELBO objective (ablation)Beta Diffusion · CIFAR-10, NFE = 1000, η×10⁻⁴ = 1, B = 512FID: 3.38 -> 4.41Hurt
reduce η×10⁻⁴ from 1 to 0.1 (ablation)Beta Diffusion with KLUB · CIFAR-10, NFE = 1000, B = 512FID: 3.38 -> 4.90Hurt
reduce η×10⁻⁴ from 1 to 0.3 (ablation)Beta Diffusion with KLUB · CIFAR-10, NFE = 1000, B = 512FID: 3.38 -> 3.67Hurt
reduce batch size B from 512 to 288 (ablation)Beta Diffusion with KLUB · CIFAR-10, NFE = 1000, η×10⁻⁴ = 1FID: 3.38 -> 3.08Helped
reduce η×10⁻⁴ from 1 to 0.8 (ablation)Beta Diffusion with KLUB · CIFAR-10, NFE = 1000, B = 288FID: 3.08 -> 3.21Helped
increase η×10⁻⁴ from 1 to 1.2 (ablation)Beta Diffusion with KLUB · CIFAR-10, NFE = 1000, B = 288FID: 3.08 -> 3.37Hurt
reduce batch size B from 512 to 128 (ablation)Beta Diffusion with KLUB · CIFAR-10, NFE = 1000, η×10⁻⁴ = 1FID: 3.38 -> 3.40Hurt
increase η×10⁻⁴ from 1 to 2 (ablation)Beta Diffusion with KLUB · CIFAR-10, NFE = 1000, B = 128FID: 3.40 -> 3.75Hurt
increase NFE from 10 to 1000 (ablation)Beta Diffusion with KLUB · CIFAR-10, η×10⁻⁴ = 1, B = 288FID: 37.67 -> 3.08Helped

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