AIBullisharXiv – CS AI · 14h ago6/10
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Uncertainty-Aware Transfer Learning for Cross-Building Energy Forecasting: Toward Robust and Scalable District-Level Energy Management
Researchers developed an uncertainty-aware transfer learning framework using Temporal Fusion Transformers to enable energy forecasting models trained on one building to work effectively on different buildings with minimal retraining. The approach achieved 93.2% prediction interval coverage and demonstrated that freezing most model parameters while fine-tuning only output layers produces superior cross-building generalization compared to full model retraining.