Transcription of Graph WaveNet for Deep Spatial-Temporal Graph Modeling - …
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Graph WaveNet for Deep Spatial-Temporal Graph ModelingZonghan Wu1,Shirui Pan2 ,Guodong Long1,Jing Jiang1,Chengqi Zhang11 Centre for Artificial Intelligence, FEIT, University of Technology Sydney, Australia2 Faculty of Information Technology, Monash University, , Graph Modeling is an importanttask to analyze the spatial relations and temporaltrends of components in a system. Existing ap-proaches mostly capture the spatial dependency ona fixed Graph structure, assuming that the under-lying relation between entities is , the explicit Graph structure (relation)does not necessarily reflect the true dependency andgenuine relation may be missing due to the incom-plete connections in the data.
to model the dynamic node-level inputs by assuming inter-dependency between connected nodes, as demonstrated by Figure 1. Spatial-temporal graph modeling has wide appli-cations in solving complex system problems such as traf-fic speed forecasting [Li et al., 2018b], taxi demand pre-diction [Yao et al., 2018], human action recognition Yan
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