MCST-Mamba combines STAEformer-style adaptive embeddings with two Mamba blocks to jointly predict speed, flow, and occupancy, but its claimed state-of-the-art results rest on comparing aggregated multi-channel errors to single-channel baseline errors.
A task-oriented spatial graph structure learning method for traffic forecasting,
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MCST-Mamba: Multivariate Mamba-Based Model for Traffic Prediction
MCST-Mamba combines STAEformer-style adaptive embeddings with two Mamba blocks to jointly predict speed, flow, and occupancy, but its claimed state-of-the-art results rest on comparing aggregated multi-channel errors to single-channel baseline errors.