6 citations · 6 across the 8 of their papers we have counts for
8 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…
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…
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…
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…
NuwaTS: a Foundation Model Mending Every Incomplete Time Series
Jinguo Cheng, Chunwei Yang, Wanlin Cai +3
Time series imputation is critical for many real-world applications and has been widely studied. However, existing models often require specialized designs tailored to specific mis…
MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting
Wanlin Cai, Yuxuan Liang, Xianggen Liu +2
Multivariate time series forecasting poses an ongoing challenge across various disciplines. Time series data often exhibit diverse intra-series and inter-series correlations, contr…
Rethinking Urban Mobility Prediction: A Super-Multivariate Time Series Forecasting Approach
Jinguo Cheng, Ke Li, Yuxuan Liang +3
Long-term urban mobility predictions play a crucial role in the effective management of urban facilities and services. Conventionally, urban mobility data has been structured as sp…