PhysDGM, a diffusion model with physics penalties applied at every reverse denoising step, generates synthetic industrial time-series that improve downstream predictive maintenance and fault-diagnosis performance beyond real-data-only training.
A.et al.Active learning framework to optimize process parameters for additive- manufactured ti-6al-4v with high strength and ductility.Nature Communications16, 931 (2025)
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Physics-informed Diffusion Generative Model for Time-Series Data Synthesis in Dynamic Systems
PhysDGM, a diffusion model with physics penalties applied at every reverse denoising step, generates synthetic industrial time-series that improve downstream predictive maintenance and fault-diagnosis performance beyond real-data-only training.