2021年1月12日 · Denoising diffusion probabilistic models (DDPMs) have achieved high quality image generation without adversarial training, yet they require simulating a Markov chain for …

2023年2月1日 · We present an interpretation of the accelerating effects of DDIM that also explains the advantages of a deterministic sampling scheme over the stochastic one for fast …

2025年1月22日 · Classifier-free guidance (CFG) is a fundamental tool in modern diffusion models for text-guided generation. Although effective, CFG has notable drawbacks. For instance, …

els (DDIM) (Song et al.,2020a) and DiffWave (Kong et al., 2020b). In detail, FastDPM offers two ways to construct the approximate diffusion process: selecting Ssteps in the original diffusion …

2023年2月1日 · ddim encoder is almost equal to optimal transport. Open Peer Review. Open Publishing. Open Access. Open Discussion.

Elucidating the Design Space of Diffusion-Based Generative Models ... d (σ)

2024年9月26日 · This paper describes an efficient algorithm for solving noisy linear inverse problems using pretrained diffusion models. Extending the paradigm of denoising diffusion …

marginals in Eq. 2. The ODE perspective of DDIM and other related works on accelerated sampling from diffusion models are discussed in Appendix A.1. 3 APPROACH We propose …

2022年12月5日 · The proposed method also improves upon the speed vs quality tradeoff exhibited in standard unconditional DDPM/DDIM models (for instance, \textbf{FID of 16.47 vs …

student DDIM step match 2 teacher DDIM steps. We calculate this target value by running 2 DDIM sampling steps using the teacher, starting from z tand ending at z 1=N, with Nbeing the …