5 papers
Domain-Decomposed Randomized Neural Networks for Partial Differential Equations in Unbounded Domains
Haixin Wang, Haoning Dang, Fei Wang +1
Partial differential equations on unbounded domains are challenging because the exterior region must be represented without excessive truncation error. Truncation-based methods oft…
HGAurban: Heterogeneous Graph Autoencoding for Urban Spatial-Temporal Learning
Qianru Zhang, Xinyi Gao, Haixin Wang +3
Spatial-temporal graph representations play a crucial role in urban sensing applications, including traffic analysis, human mobility behavior modeling, and citywide crime predictio…
FLDmamba: Integrating Fourier and Laplace Transform Decomposition with Mamba for Enhanced Time Series Prediction
Qianru Zhang, Chenglei Yu, Haixin Wang +5
Time series prediction, a crucial task across various domains, faces significant challenges due to the inherent complexities of time series data, including non-stationarity, multi-…
Efficient Traffic Prediction Through Spatio-Temporal Distillation
Qianru Zhang, Xinyi Gao, Haixin Wang +2
Graph neural networks (GNNs) have gained considerable attention in recent years for traffic flow prediction due to their ability to learn spatio-temporal pattern representations th…
A Survey on Point-of-Interest Recommendation: Models, Architectures, and Security
Qianru Zhang, Peng Yang, Junliang Yu +4
The widespread adoption of smartphones and Location-Based Social Networks has led to a massive influx of spatio-temporal data, creating unparalleled opportunities for enhancing Poi…