Research map / Graph learning / Knowledge and temporal graphs
Gated Residual Recurrent Graph Neural Networks for Traffic Prediction
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| MRes-RGNN vs DCRNN | traffic prediction · METR-LA | MAE: 2.49 -> 2.07 | Helped |
| MRes-RGNN vs DCRNN | traffic prediction · PEMS-BAY | MAE: 1.72 -> 1.52 | Helped |
| add residual shortcuts (ablation) | M-RGNN · METR-LA | MAE: 2.34 -> 2.19 | Helped |
| add gating to residual shortcuts (ablation) | MRes-RGNN · METR-LA | MAE: 2.19 -> 2.07 | Helped |
| add gating to residual shortcuts (ablation) | MRes-RGNN · PEMS-BAY | MAE: 1.61 -> 1.52 | Helped |
| add daily-period branch (ablation) | Res-RGNN · METR-LA | MAE: 2.32 -> 2.16 | Helped |
| add external factors (ablation) | Res-RGNN-ND · METR-LA | MAE: 2.16 -> 2.07 | Helped |
Closest papers by meaning
- Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting (NeurIPS 2020 · similarity 0.92)
- DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting (ICML 2022 · similarity 0.90)
- Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting (ICLR 2018 · similarity 0.90)
- Efficient Traffic Prediction Through Spatio-Temporal Distillation (AAAI 2025 · similarity 0.87)
- TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts (ICLR 2024 · similarity 0.86)
- Spatio-Temporal Pivotal Graph Neural Networks for Traffic Flow Forecasting (AAAI 2024 · similarity 0.86)
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