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Substituting this into the result from Property 3: W1 (K n F (δz), ν F )≤L F ρnW1 (δx0 , ν).(83) To obtain the second bound, we need to relate W1(δx0 , ν) back to νF

(Convergence Bounds) Assume the base kernel satisfies W1(K n(δx), ν)≤ρ nW1(δx, ν)

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Conditional Diffusion Sampling

stat.ML · 2026-05-05 · unverdicted · novelty 7.0

CDS combines parallel tempering for initial exploration with exact diffusion transport via conditional interpolants to sample unnormalized multimodal distributions more efficiently.

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  • Conditional Diffusion Sampling stat.ML · 2026-05-05 · unverdicted · none · ref 20

    CDS combines parallel tempering for initial exploration with exact diffusion transport via conditional interpolants to sample unnormalized multimodal distributions more efficiently.