The paper develops an action-operator semantics for molecular diffusion models that supports auditable free-energy estimation from endpoint data.
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Derives Õ(d β² A² / ε⁴) oracle complexity for AIS estimating normalizing constant Z to relative error ε and introduces reverse diffusion sampler for geometric paths with large action.
CARD uses radix decomposition to enable autoregressive modeling of molecular coordinates as a zero-free-energy reference distribution, delivering classical accuracy for absolute free energy on unseen systems at ~40x speedup.
citing papers explorer
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Unsupervised Thermodynamics of Molecular Diffusion Models: Action-Operator Semantics and Auditable Free-Energy Readout
The paper develops an action-operator semantics for molecular diffusion models that supports auditable free-energy estimation from endpoint data.
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Complexity Analysis of Normalizing Constant Estimation: from Jarzynski Equality to Annealed Importance Sampling and beyond
Derives Õ(d β² A² / ε⁴) oracle complexity for AIS estimating normalizing constant Z to relative error ε and introduces reverse diffusion sampler for geometric paths with large action.
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CARD: Coarse-to-fine Autoregressive Modeling with Radix-based Decomposition for Transferable Free Energy Estimation
CARD uses radix decomposition to enable autoregressive modeling of molecular coordinates as a zero-free-energy reference distribution, delivering classical accuracy for absolute free energy on unseen systems at ~40x speedup.