4 papers · 1 filter
Uncertainty-Aware Crime Prediction With Spatial Temporal Multivariate Graph Neural Networks
Zepu Wang, Xiaobo Ma, Huajie Yang +3
Crime forecasting is a critical component of urban analysis and essential for stabilizing society today. Unlike other time series forecasting problems, crime incidents are sparse,…
Unlocking the Power of LSTM for Long Term Time Series Forecasting
Yaxuan Kong, Zepu Wang, Yuqi Nie +5
Traditional recurrent neural network architectures, such as long short-term memory neural networks (LSTM), have historically held a prominent role in time series forecasting (TSF)…
Large Language Models for Mobility Analysis in Transportation Systems: A Survey on Forecasting Tasks
Zijian Zhang, Yujie Sun, Zepu Wang +5
Mobility analysis is a crucial element in the research area of transportation systems. Forecasting traffic information offers a viable solution to address the conflict between incr…
ST-GIN: An Uncertainty Quantification Approach in Traffic Data Imputation with Spatio-temporal Graph Attention and Bidirectional Recurrent United Neural Networks
Zepu Wang, Dingyi Zhuang, Yankai Li +4
Traffic data serves as a fundamental component in both research and applications within intelligent transportation systems. However, real-world transportation data, collected from…