Uncertainty Quantification of Spatiotemporal Travel Demand With Probabilistic Graph Neural Networks
Recent studies have significantly improved the prediction accuracy of travel demand using graph neural networks. However, these studies largely ignored uncertainty that inevitably exists in travel demand prediction. To fill this gap, this study proposes a framework of probabilistic graph neural netw...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers
2024
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| Online Access: | https://hdl.handle.net/1721.1/156415 |