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1 λ Eµλ(ex|XT ) X d:exd=M −logs θ(ex)d,X d T # , ∝E X∼P ¯θk−1 er(XT ) dPref dP¯θk−1 ηk ηk+1 Eλ∼Unif(0,1)

resample{X (i) T }N i=1 by following categorical distribution: { ˜XT }N i=1 ∼Cat   ( wθk ηk(X(i)) PN i=1 wθk ηk(X(i)) )N i=1 ,{X (i) T }N i=1   · 2025

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Proximal Diffusion Neural Sampler

cs.LG · 2025-10-04 · unverdicted · novelty 6.0

PDNS decomposes diffusion neural sampler training into proximal subproblems on path measures to gradually approach multimodal targets and promote mode exploration.

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  • Proximal Diffusion Neural Sampler cs.LG · 2025-10-04 · unverdicted · none · ref 13

    PDNS decomposes diffusion neural sampler training into proximal subproblems on path measures to gradually approach multimodal targets and promote mode exploration.