What is recorded here?
Estimated gradients of noise-perturbed data densities at multiple scales and generated samples with annealed Langevin dynamics.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Score matching and Langevin dynamics predate this work. Estimated scores and finite dynamics do not guarantee exact sampling of an arbitrary original data distribution.
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People and systems
Yang Song; Stefano Ermon
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
Song and Ermon: noise-conditioned score generation
Estimated gradients of noise-perturbed data densities at multiple scales and generated samples with annealed Langevin dynamics.
Scientific scope
Score matching and Langevin dynamics predate this work. Estimated scores and finite dynamics do not guarantee exact sampling of an arbitrary original data distribution.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Yang Song; Stefano Ermon
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.