Preprint
Aug 2026
Spatiotemporal Graph Transformer for Traffic Intelligence in Edge Computing
A spatiotemporal graph Transformer framework that jointly models spatial interactions and temporal dependencies for traffic forecasting in edge computing and leverages Transformer-based self-attention to learn long-range temporal patterns from historical traffic observations is proposed.
Laha Ale, Letian Lin, Na Cao et al.
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