AINeutralarXiv – CS AI · 6h ago6/10
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PatchSTG: Scalable Spatiotemporal Graph Transformers for Traffic Forecasting on Irregular Sensor Networks
Researchers introduce PatchSTG, a new graph Transformer architecture that addresses scalability challenges in traffic forecasting by partitioning unevenly distributed sensors into geographic patches. The model reduces computational complexity from quadratic to near-linear while maintaining competitive forecasting accuracy across multiple prediction horizons.