AI RESEARCH
Distribution estimation via Flow Matching with Lipschitz guarantees
arXiv CS.LG
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ArXi:2509.02337v2 Announce Type: replace-cross Flow Matching, a promising approach in generative modeling, has recently gained popularity. Relying on ordinary differential equations, it offers a simple and flexible alternative to diffusion models, which are currently the state-of-the-art. Despite its empirical success, the mathematical understanding of its statistical power so far is very limited. This is largely due to the sensitivity of theoretical bounds to the Lipschitz constant of the vector field which drives the.