2 papers
stat.ML2026
Itô maps for any-step SDEs
Zhengkai Pan, Peter Potaptchik, Wenxi Yao +2
Recent one-step generative models accelerate sampling by learning deterministic flow maps of the underlying dynamics. These methods rely on learning from ordinary differential equa…
cs.LG2025
You Only Look One Step: Accelerating Backpropagation in Diffusion Sampling with Gradient Shortcuts
Hongkun Dou, Zeyu Li, Xingyu Jiang +4
Diffusion models (DMs) have recently demonstrated remarkable success in modeling large-scale data distributions. However, many downstream tasks require guiding the generated conten…