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Progressive Graph Convolutional Networks for Spatial-Temporal Traffic Forecasting

The complex spatial-temporal correlations in traffic data make the traffic forecasting problem challenging. The proposed model captures the time-varying spatial correlations by progressively adapting to data used for forecasting tasks.

Data and Resources

Cite this as

Yuyol Shin, Yoonjin Yoon (2024). Dataset: Progressive Graph Convolutional Networks for Spatial-Temporal Traffic Forecasting. https://doi.org/10.57702/hz168m03

DOI retrieved: December 3, 2024

Additional Info

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Created December 3, 2024
Last update December 3, 2024
Author Yuyol Shin
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Yoonjin Yoon
Homepage https://doi.org/10.1145/1234567890