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Found 2 papers, 1 papers with code
Privacy-Preserving Collaborative Split Learning Framework for Smart Grid Load Forecasting
Under this framework, each GS is responsible for training a personalized model split for their respective neighbourhoods, whereas the SP can train a single global or personalized model for each GS.
A Novel DDPM-based Ensemble Approach for Energy Theft Detection in Smart Grids
To address these challenges, several unsupervised ETD methods have been proposed, focusing on learning the normal patterns from honest users, specifically the reconstruction of input.
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