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News/Uncertainty-Aware Transfer Learning for Cross-Building Energy Forecasting: Toward Robust and Scalable District-Level Energy Management
arxiv
PublishedMay 29, 2026 at 4:00 AM
—neutral

Uncertainty-Aware Transfer Learning for Cross-Building Energy Forecasting: Toward Robust and Scalable District-Level Energy Management

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arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2605.29733v1 Announce Type: new Abstract: Scaling data-driven energy forecasting to district level requires models that can be re-used across buildings with minimal target-domain data and honest uncertainty estimates. We present an uncertainty-aware transfer learning (TL) framework for cross-b

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Mentioned models
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  • 01
    Temporal Fusion Transformer (TFT)
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arxiv
Read original ↗All from arxiv →
Tags
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#energy-forecasting#transfer-learning#uncertainty-estimation#smart-buildings

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Mentioned models
01
  • 01
    Temporal Fusion Transformer (TFT)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#energy-forecasting#transfer-learning#uncertainty-estimation#smart-buildings

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