AI RESEARCH
Thermal-GEMs: Generalized Models for Building Thermal Dynamics
arXiv CS.LG
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ArXi:2604.16443v1 Announce Type: cross Data-driven models for building thermal dynamics are a scalable approach for enabling energy-efficient operation through fault detection & diagnosis or advanced control. To obtain accurate models, measurement data from a target building spanning months to years are required. Transfer Learning (TL) mitigates this challenge by employing pretrained models based on single or multiple source buildings.