Author

Maxime Haddouche

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Jul 2026

Tightening the Score Matching Gap for Diffusion Models

This work develops tighter bounds for three metrics: KL divergence, reverse KL divergence, and Wasserstein distance, effectively exploiting the regularity of the class of score estimators, and suggests that the quality of the score approximation has more impact on closing the score matching gap for low noise scales.

Benjamin Dupuis, Tyler Farghly, Maxime Haddouche et al. · arXiv.org · 0 citations