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The Loss Floor of Denoising Score Matching: Fisher Geometry from Schr\"odinger Bridges

This story is from 2026-08-26. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2608.23916v1 Announce Type: new Abstract: Denoising score matching trains diffusion models by regressing onto a conditional score, although generation ultimately requires the marginal score. The two objectives share the same population minimizer, but the conditional target remains random at f…

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  1. 2026-08-26 04:00 · arXiv cs.LG
    The Loss Floor of Denoising Score Matching: Fisher Geometry from Schr\"odinger Bridges

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