HardFlow turns hard constraint enforcement during flow-matching sampling into a tractable terminal-time trajectory optimization problem using optimal control.
Theoretical guarantees for sampling and inference in generative models with latent diffusions
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Diffusion sampler framework produces intrinsically calibrated predictive uncertainty for industrial soft sensors and process models via faithful posterior sampling.
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HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization
HardFlow turns hard constraint enforcement during flow-matching sampling into a tractable terminal-time trajectory optimization problem using optimal control.
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Towards Intrinsically Calibrated Uncertainty Quantification in Industrial Data-Driven Models via Diffusion Sampler
Diffusion sampler framework produces intrinsically calibrated predictive uncertainty for industrial soft sensors and process models via faithful posterior sampling.