arXiv (OAI Expanded)
open access
Convergence rates for generative drifting flows: fixed-scale obstructions and multihead acceleration
Drifting models offer a promising route to faster generative AI: they perform gradual transport during training, while generating new samples in a single step. This paper asks whether the underlying drifting process can converge rapidly to a target distribution under ideal conditions, before finite-
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