Unfolding Generative Flows with Koopman Operators: Trajectory-Preserving Linearization 事件

Unfolding Generative Flows with Koopman Operators: Trajectory-Preserving Linearization arXiv:2506.22304v3 Announce Type: replace-cross Abstract: Continuous Normalizing Flows (CNFs) enable elegant generative modeling but remain bottlenecked by their iterative nature requiring costly sampling and lacking interpretability of the intermediate states. Recent approaches accelerate sampling by straightening trajectories or distilling endpoints, yet they treat the original generative process as a black