Introduces a path-space stochastic control formulation for diffusion posterior sampling with time reparameterization and trust-region optimization to achieve more accurate sampling and importance-weighted corrections.
A statistical bench- mark for diffusion posterior sampling algorithms.arXiv preprint arXiv:2509.12821
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EmbedOpt optimizes the conditional embedding of protein diffusion models at inference time to shift the structural prior toward experimental constraints, outperforming coordinate-based posterior sampling on cryo-EM fitting while remaining robust across hyperparameter ranges.
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A Stabilized Path-Space Approach to Diffusion-Based Posterior Sampling
Introduces a path-space stochastic control formulation for diffusion posterior sampling with time reparameterization and trust-region optimization to achieve more accurate sampling and importance-weighted corrections.
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Robust Inference-Time Steering of Protein Diffusion Models via Embedding Optimization
EmbedOpt optimizes the conditional embedding of protein diffusion models at inference time to shift the structural prior toward experimental constraints, outperforming coordinate-based posterior sampling on cryo-EM fitting while remaining robust across hyperparameter ranges.