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Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting

AAAI 2021 · Graph learning › Knowledge and temporal graphs · approach: Spatio-temporal graph traffic forecasting · 904 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use STFGNN instead of the strongest listed baseline, STSGCNTraffic forecasting · PEMS03MAE: 17.48 ± 0.15 -> 16.77 ± 0.09Helped
Use STFGNN instead of STSGCNTraffic forecasting · PEMS04MAE: 21.19 ± 0.10 -> 19.83± 0.06Helped
Use STFGNN instead of STSGCNTraffic forecasting · PEMS07MAE: 24.26 ± 0.14 -> 22.07± 0.11Helped
Use STFGNN instead of STSGCNTraffic forecasting · PEMS08MAE: 17.13 ± 0.09 -> 16.64± 0.09Helped
Increase fusion graph size from 3 to 4 (ablation)STFGNN without gated convolution, temporal graph sparsity about 1% · PEMS04MAE: 20.09 -> 19.92Helped
Increase fusion graph size from 3 to 4 (ablation)STFGNN without gated convolution, temporal graph sparsity about 1% · PEMS08MAE: 16.84 -> 16.70Helped
Add gated convolution (ablation)STFGNN with fusion graph size 4 and temporal graph sparsity about 1% · PEMS04MAE: 19.92 -> 19.83Helped
Add gated convolution (ablation)STFGNN with fusion graph size 4 and temporal graph sparsity about 1% · PEMS08MAE: 16.70 -> 16.64No clear effect
Replace the spatial graph with the temporal graph (ablation)STFGNN, fusion graph size 4 and sparsity about 1% · PEMS04MAE: 19.83 -> 20.02Hurt
Replace the spatial graph with the temporal graph (ablation)STFGNN, fusion graph size 4 and sparsity about 1% · PEMS08MAE: 16.64 -> 18.23Hurt
Increase temporal graph sparsity from about 1% to about 5% in temporal-only configuration (ablation)STFGNN with fusion graph size 4 and gated convolution · PEMS04MAE: 20.02 -> 19.91No clear effect
Increase temporal graph sparsity from about 1% to about 5% in temporal-only configuration (ablation)STFGNN with fusion graph size 4 and gated convolution · PEMS08MAE: 18.23 -> 16.02Helped

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