GG-PA composes diffusion priors with physical context via a derived Gibbs sampler that is asymptotically exact as diffusion time approaches zero and exact at finite times for quadratic interactions.
Statistically optimal analysis of samples from multiple equilibrium states
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Composing diffusion priors with explicit physical context via generative Gibbs sampling
GG-PA composes diffusion priors with physical context via a derived Gibbs sampler that is asymptotically exact as diffusion time approaches zero and exact at finite times for quadratic interactions.