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20212024
most citedRevisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendation

26 citations · 50 across the 6 of their papers we have counts for

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cs.LG202326 cited

Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendation

Xiaohang Xu, Toyotaro Suzumura, Jiawei Yong +5

Next Point-of-Interest (POI) recommendation plays a crucial role in urban mobility applications. Recently, POI recommendation models based on Graph Neural Networks (GNN) have been…

cs.LG202310 cited

MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation

Zekun Cai, Renhe Jiang, Xinyu Yang +5

Urban time series data forecasting featuring significant contributions to sustainable development is widely studied as an essential task of the smart city. However, with the dramat…

cs.LG202311 cited

STAEformer: Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting

Hangchen Liu, Zheng Dong, Renhe Jiang +4

With the rapid development of the Intelligent Transportation System (ITS), accurate traffic forecasting has emerged as a critical challenge. The key bottleneck lies in capturing th…

cs.LG2023

Learning Gaussian Mixture Representations for Tensor Time Series Forecasting

Jiewen Deng, Jinliang Deng, Renhe Jiang +1

Tensor time series (TTS) data, a generalization of one-dimensional time series on a high-dimensional space, is ubiquitous in real-world scenarios, especially in monitoring systems…

cs.LG20211 cited

Event-Aware Multimodal Mobility Nowcasting

Zhaonan Wang, Renhe Jiang, Hao Xue +3

As a decisive part in the success of Mobility-as-a-Service (MaaS), spatio-temporal predictive modeling for crowd movements is a challenging task particularly considering scenarios…