3 citations · 3 across the 4 of their papers we have counts for
4 papers
LISA: Learning-Integrated Space Partitioning Framework for Traffic Accident Forecasting on Heterogeneous Spatiotemporal Data
Bang An, Xun Zhou, Amin Vahedian +3
Traffic accident forecasting is an important task for intelligent transportation management and emergency response systems. However, this problem is challenging due to the spatial…
GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models through Statistically-Guided Geo-Prototyping
Bang An, Xun Zhou, Zirui Zhou +3
The problem of forecasting spatiotemporal events such as crimes and accidents is crucial to public safety and city management. Besides accuracy, interpretability is also a key requ…
Referee-Meta-Learning for Fast Adaptation of Locational Fairness
Weiye Chen, Yiqun Xie, Xiaowei Jia +4
When dealing with data from distinct locations, machine learning algorithms tend to demonstrate an implicit preference of some locations over the others, which constitutes biases t…
SpatialRank: Urban Event Ranking with NDCG Optimization on Spatiotemporal Data
Bang An, Xun Zhou, Yongjian Zhong +1
The problem of urban event ranking aims at predicting the top-k most risky locations of future events such as traffic accidents and crimes. This problem is of fundamental importanc…