FAST uses a Temporal-Spatial-Temporal structure with attention and Mamba modules plus learnable embeddings to achieve better accuracy on traffic prediction tasks than previous models.
Bayesian critique-tune-based reinforcement learning with adaptive pressure for multi-intersection traffic signal control,
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FAST: A Synergistic Framework of Attention and State-space Models for Spatiotemporal Traffic Prediction
FAST uses a Temporal-Spatial-Temporal structure with attention and Mamba modules plus learnable embeddings to achieve better accuracy on traffic prediction tasks than previous models.