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cs.LG2026
Incident-Guided Spatiotemporal Traffic Forecasting
Lixiang Fan, Bohao Li, Tao Zou +2
Recent years have witnessed the rapid development of deep-learning-based, graph-neural-network-based forecasting methods for modern intelligent transportation systems. However, mos…
cs.LG2025
Global-Lens Transformers: Adaptive Token Mixing for Dynamic Link Prediction
Tao Zou, Chengfeng Wu, Tianxi Liao +2
Dynamic graph learning plays a pivotal role in modeling evolving relationships over time, especially for temporal link prediction tasks in domains such as traffic systems, social n…
cs.LG2024
Repeat-Aware Neighbor Sampling for Dynamic Graph Learning
Tao Zou, Yuhao Mao, Junchen Ye +1
Dynamic graph learning equips the edges with time attributes and allows multiple links between two nodes, which is a crucial technology for understanding evolving data scenarios li…