Diffusion sampler framework produces intrinsically calibrated predictive uncertainty for industrial soft sensors and process models via faithful posterior sampling.
Integrating autoencoder and heteroscedastic noise neural networks for the batch process soft-sensor design
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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.