131 citations · 245 across the 24 of their papers we have counts for
6 papers · 1 filter
BiTSA: Leveraging Time Series Foundation Model for Building Energy Analytics
Xiachong Lin, Arian Prabowo, Imran Razzak +4
Incorporating AI technologies into digital infrastructure offers transformative potential for energy management, particularly in enhancing energy efficiency and supporting net-zero…
Exploring Capabilities of Time Series Foundation Models in Building Analytics
Xiachong Lin, Arian Prabowo, Imran Razzak +4
The growing integration of digitized infrastructure with Internet of Things (IoT) networks has transformed the management and optimization of building energy consumption. By levera…
BTS: Building Timeseries Dataset: Empowering Large-Scale Building Analytics
Arian Prabowo, Xiachong Lin, Imran Razzak +4
Buildings play a crucial role in human well-being, influencing occupant comfort, health, and safety. Additionally, they contribute significantly to global energy consumption, accou…
Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned
Du Yin, Jinliang Deng, Shuang Ao +6
Training models on spatio-temporal (ST) data poses an open problem due to the complicated and diverse nature of the data itself, and it is challenging to ensure the model's perform…
XXLTraffic: Expanding and Extremely Long Traffic forecasting beyond test adaptation
Du Yin, Hao Xue, Arian Prabowo +2
Traffic forecasting is crucial for smart cities and intelligent transportation initiatives, where deep learning has made significant progress in modeling complex spatio-temporal pa…
A Gap in Time: The Challenge of Processing Heterogeneous IoT Data in Digitalized Buildings
Xiachong Lin, Arian Prabowo, Imran Razzak +4
The increasing demand for sustainable energy solutions has driven the integration of digitalized buildings into the power grid, leveraging Internet-of-Things (IoT) technologies to…