HAL (France)
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Diffusion Flow Matching: Dimension-Improved KL Bounds and Wasserstein Guarantees
Diffusion Flow Matching (DFM) has recently emerged as a versatile framework for generative modeling, yet its theoretical convergence properties remain only partially understood. In this work, we provide refined and novel convergence guarantees for Brownian motion based DFMs, focusing on the discreti
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