Towards Intrinsically Calibrated Uncertainty Quantification in Industrial Data-Driven Models via Diffusion Sampler
Towards Intrinsically Calibrated Uncertainty Quantification in Industrial Data-Driven Models via Diffusion Sampler explores A diffusion-based framework for intrinsically calibrated uncertainty quantification in industrial data-driven models, improving safety and decision-making.. Commercial viability score: 7/10 in Industrial AI.
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