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Uncertainty Quantification of Sparse Trip Demand Prediction with Spatial-Temporal Graph Neural Networks

Author(s)
Zhuang, Dingyi; Wang, Shenhao; Koutsopoulos, Haris; Zhao, Jinhua
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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Date issued
2022-08-14
URI
https://hdl.handle.net/1721.1/146261
Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning; Massachusetts Institute of Technology. Media Laboratory; Massachusetts Institute of Technology. Human Dynamics Group; Massachusetts Institute of Technology. School of Architecture and Planning
Publisher
ACM|Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining USB
Citation
Zhuang, Dingyi, Wang, Shenhao, Koutsopoulos, Haris and Zhao, Jinhua. 2022. "Uncertainty Quantification of Sparse Trip Demand Prediction with Spatial-Temporal Graph Neural Networks."
Version: Final published version
ISBN
978-1-4503-9385-0

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