Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation

Spatial-temporal graph learning has emerged as a promising solution for modeling structured spatial-temporal data and learning region representations for various urban sensing tasks such as crime forecasting and traffic flow prediction. However, most existing models are vulnerable to the quality of...

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Bibliographische Detailangaben

Hauptverfasser:	Zhang, Qianru, Huang, Chao, Xia, Lianghao, Wang, Zheng, Yiu, Siuming, Han, Ruihua
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Learning
Online-Zugang:	Volltext bestellen
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