Graph-Based Deep Modeling and Real Time Forecasting of Sparse Spatio-Temporal Data
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Abstract (arXiv)
We present a generic framework for spatio-temporal (ST) data modeling, analysis, and forecasting, with a special focus on data that is sparse in both space and time. Our multi-scaled framework is a seamless coupling of two major components: a self-exciting point process that models the macroscale statistical behaviors of the ST data and a graph structured recurrent neural network (GSRNN) to discover the microscale patterns of the ST data on the inferred graph. This novel deep neural network (DNN) incorporates the real time interactions of the graph nodes to enable more accurate real time forecasting. The effectiveness of our method is demonstrated on both crime and traffic forecasting.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Apr 2018.
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Citing papers per year: 2021: 5; 2022: 0; 2023: 2; 2024: 3.
10 papers.
- 2021Graph Neural Network for Traffic Forecasting: A Surveycited by 261
- 2023Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Surveycited by 140
- 2021Graph Neural Networks for Traffic Forecastingcited by 7
- 2021A Study of Joint Graph Inference and Forecastingcited by 5
- 2021Crime Prediction with Graph Neural Networks and Multivariate Normal Distributionscited by 3
- 2024FusionTransNet for Smart Urban Mobility: Spatiotemporal Traffic Forecasting Through Multimodal Network Integrationcited by 1
- 2021A Survey on Societal Event Forecasting with Deep Learningcited by 0
- 2023Deep Learning-Based Spatiotemporal Multi-Event Reconstruction for Delay Line Detectorscited by 0
- 2024WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecastingcited by 0
- 2024Graph Based Traffic Analysis and Delay Predictioncited by 0
- 2024Graph Based Traffic Analysis and Delay Prediction28 Oct 2024
- 2024FusionTransNet for Smart Urban Mobility: Spatiotemporal Traffic Forecasting Through Multimodal Network Integration9 May 2024
- 2024WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecasting1 May 2024
- 2023Deep Learning-Based Spatiotemporal Multi-Event Reconstruction for Delay Line Detectors13 Jun 2023
- 2023Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey25 Mar 2023
- 2021A Survey on Societal Event Forecasting with Deep Learning12 Dec 2021
- 2021Crime Prediction with Graph Neural Networks and Multivariate Normal Distributions29 Nov 2021
- 2021A Study of Joint Graph Inference and Forecasting10 Sep 2021
- 2021Graph Neural Networks for Traffic Forecasting27 Apr 2021
- 2021Graph Neural Network for Traffic Forecasting: A Survey27 Jan 2021