SFBD Flow converts the iterative SFBD approach into a continuous optimization framework for diffusion models on noisy samples, with its Online SFBD instantiation outperforming baselines.
Additionally, inf κ∈[0,K] Φpdata(u) − Φpκ 0 (u) ≤ exp τ 2 ∥u∥2 2DKL(pdata ∥ pEclean ) K 1/2 for K > 0 and u ∈ Rd
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SFBD Flow: A Continuous-Optimization Framework for Training Diffusion Models with Noisy Samples
SFBD Flow converts the iterative SFBD approach into a continuous optimization framework for diffusion models on noisy samples, with its Online SFBD instantiation outperforming baselines.