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DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

Cheng Lu, Chongxuan Li, Fan Bao, Jianfei Chen, Jun Zhu, Yuhao Zhou

DPM-Solver++ generates high-quality guided samples from diffusion models in 15 to 20 steps

arxiv:2211.01095 v3 · 2022-11-02 · cs.LG · cs.CV

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Claims

C1strongest claim

Experiments show that DPM-Solver++ can generate high-quality samples within only 15 to 20 steps for guided sampling by pixel-space and latent-space DPMs.

C2weakest assumption

That the combination of data-prediction formulation and thresholding, plus the multistep variant, reliably eliminates the instability observed in prior high-order solvers when guidance scale is large.

C3one line summary

DPM-Solver++ enables high-quality guided sampling of diffusion models in 15-20 steps via data-prediction ODE solving and multistep stabilization.

References

30 extracted · 30 resolved · 4 Pith anchors

[1] Estimating the optimal covariance with imperfect mean in diffusion probabilistic models
[2] Classifier-free diffusion guidance 2021
[3] Gotta go fast when generating data with score-based models
[4] On fast sampling of diffusion probabilistic models
[5] Bilateral denoising diffusion models

Formal links

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Cited by

40 papers in Pith

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First computed 2026-05-17T23:38:48.596639Z
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414a552884b3bbade1bff468bf60817f3272773873f6e20d4c138d9d99a1c31f

Aliases

arxiv: 2211.01095 · arxiv_version: 2211.01095v3 · doi: 10.48550/arxiv.2211.01095 · pith_short_12: IFFFKKEEWO52 · pith_short_16: IFFFKKEEWO523YN7 · pith_short_8: IFFFKKEE
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/IFFFKKEEWO523YN76RUL6YEBP4 \
  | jq -c '.canonical_record' \
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Canonical record JSON
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