5 papers
AdaKernel: Learning Adaptive Kernel Parameters for Spatiotemporal Graph Neural Networks
Zhongyue Zhang, Guangyin Jin, Yuxuan Liang +2
Modeling spatial dependencies is central to spatiotemporal data analysis using Graph Neural Networks (GNNs). Traditional methods rely on distance-based kernels with predefined para…
UrbanFM: Scaling Urban Spatio-Temporal Foundation Models
Wei Chen, Yuqian Wu, Junle Chen +2
Urban systems, as dynamic complex systems, continuously generate spatio-temporal data streams that encode the fundamental laws of human mobility and city evolution. While AI for Sc…
Revitalizing Canonical Pre-Alignment for Irregular Multivariate Time Series Forecasting
Ziyu Zhou, Yiming Huang, Yanyun Wang +3
Irregular multivariate time series (IMTS), characterized by uneven sampling and inter-variate asynchrony, fuel many forecasting applications yet remain challenging to model efficie…
Aeolus: A Multi-structural Flight Delay Dataset
Lin Xu, Xinyun Yuan, Yuxuan Liang +2
We introduce Aeolus, a large-scale Multi-modal Flight Delay Dataset designed to advance research on flight delay prediction and support the development of foundation models for tab…
Reinforcement Learning for Hybrid Charging Stations Planning and Operation Considering Fixed and Mobile Chargers
Yanchen Zhu, Honghui Zou, Chufan Liu +3
The success of vehicle electrification relies on efficient and adaptable charging infrastructure. Fixed-location charging stations often suffer from underutilization or congestion…