Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting
Summary: Decouples diffusion and inherent time signals in traffic data via a data-driven DSTF with an estimation gate and residual decomposition. D2STGNN adds dynamic graph learning to model evolving spatial-temporal relations, delivering state-of-the-art results on four real-world datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zezhi Shao
- 2. Zhao Zhang
- 3. Wei Wei
- 4. Fei Wang
- 5. Yongjun Xu
- 6. Xin Cao
- 7. Christian S. Jensen
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,234 | BigST: Linear Complexity Spatio-Temporal Graph Neural Network for Traffic Forecasting on Large-Scale Road Networks | 2024 | VLDB | 7.3355287e-05 |
| 8,510 | Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense | 2024 | VLDB | 4.4952414e-05 |
| 10,567 | BiST: A Lightweight and Efficient Bi-directional Model for Spatiotemporal Prediction | 2025 | VLDB | 4.1945683e-05 |
| 10,593 | Scalable Pre-Training of Compact Urban Spatio-Temporal Predictive Models on Large-Scale Multi-Domain Data | 2025 | VLDB | 4.1945683e-05 |
| 10,629 | TEAM: Topological Evolution-aware Framework for Traffic Forecasting | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,411 | MDTP: A Multi-source Deep Traffic Prediction Framework over Spatio-Temporal Trajectory Data | 2021 | VLDB | 7.1253055e-05 |
| 3,464 | DeepTRANS: A Deep Learning System for Public Bus Travel Time Estimation using Traffic Forecasting | 2020 | VLDB | 7.0696727e-05 |
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