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Found 3 papers, 1 papers with code
A Correlation Information-based Spatiotemporal Network for Traffic Flow Forecasting
Using SCorr, we propose a novel correlation information-based spatiotemporal network (CorrSTN), including a dynamic graph neural network component incorporating correlation information into the spatial structure effectively and a multi-head attention component utilizing spatial correlation information to extract dynamic temporal dependencies accurately.
An Effective Dynamic Spatio-temporal Framework with Multi-Source Information for Traffic Prediction
Traffic prediction is necessary not only for management departments to dispatch vehicles but also for drivers to avoid congested roads.
SQLFlow: A Bridge between SQL and Machine Learning
Previous database systems extended their SQL dialect to support ML.
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