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CORD: Learning Reusable Degradation Representations Across Heterogeneous Physical Systems

Li, Haibo et al.
arXiv (All) · Papers
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machine-learning
Can heterogeneous physical degradation systems benefit from joint pretraining and move beyond system-specific prognostics toward reusable cross-system representation learning? CORD combines type-specific observation interfaces with a shared degradation backbone. Its two self-supervised objectives le
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