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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.

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Cite this as

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

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Additional Info

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