arXiv:2610.37936v1 Announce Type: new Abstract: Generative flows can admit different velocity fields that induce the same continuous marginal evolution but behave differently after numerical discretization. We study this finite-step non-equivalence while keeping the marginal path and numerical method fixed. Projected modified equations characterize the component of local integration error that changes the marginal law and give sufficient conditions for higher marginal convergence order. For affine fixed-shape distributions, we characterize exact finite-step reachability and derive spectral obstructions and sharp nearest-reachable Wasserstein errors.
Machine Learning · 2026-10-30
Finite-Step Geometry of Marginal-Preserving Velocity Fields in Generative Flows
arXiv:2610.37936v1 Announce Type: new Abstract: Generative flows can admit different velocity fields that induce the same continuous marginal evolution but behave differently after numerical discretization. We study this finite-step non-equivalence while keeping the marginal path and numerical method fixed.
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