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Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning

ICLR 2023 · Image generation › Fast diffusion sampling · approach: Discrete diffusion solvers · 80 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add Self-Conditioning at sampling and training (ablation)Bit Diffusion / DDPM, DPM-Solver 20 NFE (x0 prediction) · ImageNet 64x64 continuousFID: 12.13 -> 6.94Helped
add Self-Conditioning (eps prediction) (ablation)continuous diffusion · ImageNet 64x64 continuous, DPM-Solver 20 NFEFID: 6.10 -> 4.24Helped
add Self-Conditioning on binary encodings (ablation)Bit Diffusion · CIFAR-10FIDHelped
add asymmetric time intervals (time difference 0 -> 7/8) at sampling (ablation)Bit Diffusion captioning, 10 steps · MS-COCO captioningBLEU-4: 17.6 -> 34.6Helped
add asymmetric time intervals (ablation)Bit Diffusion captioning, 5 steps · MS-COCO captioningBLEU-4: 17.1 -> 31.6Helped
add non-zero time difference at 400 steps (ablation)Bit Diffusion · ImageNet 64x64FIDNo clear effect
add non-zero time difference at 100 steps (ablation)Bit Diffusion · ImageNet 64x64FIDHelped
use uint8 (rand) categorical encoding instead of uint8 (ablation)Bit Diffusion · ImageNet 64x64 class-conditionalFID: 4.84 -> 8.76Hurt
replace base-2 uint8 with one-hot encoding (ablation)Bit Diffusion l2 loss · CIFAR-10 unconditionalFID: 3.48 -> 46.32Hurt
replace l2 loss with logistic loss (ablation)Bit Diffusion uint8 (rand) · CIFAR-10 unconditionalFID: 6.93 -> 49.29Hurt
replace l2 loss with logistic loss (ablation)Bit Diffusion uint8 / gray code · CIFAR-10 unconditionalFID: 3.48 -> 3.53; 3.86 -> 3.71No clear effect
use self-guidance sampling instead of default Self-Conditioning sampling (ablation)Bit Diffusion · ImageNet 64x64 class-conditionalFID: uint8 (rand) 8.76 -> 7.87; uint8 4.84 -> 5.15Mixed

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