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With the installation of smart meters, high resolution building-level energy consumption data become increasingly accessible, which not only provides more accurate data for energy forecasting at the aggregated level but also enables datadriven energy forecasting for individual buildings. On the one hand, individual buildings exhibit high randomness, making the forecasting problem at the building-level more challenging. On the other hand, buildings usually have their own characteristics,doi:10.1109/ijcnn48605.2020.9207402 dblp:conf/ijcnn/DaiM20 fatcat:wjzs7vmj3rc4pgjfkicrhaao44