3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Adaptive Modeling of Uncertainties for Traffic Forecasting
Ying Wu, Yongchao Ye, Adnan Zeb +2
Deep neural networks (DNNs) have emerged as a dominant approach for developing traffic forecasting models. These models are typically trained to minimize error on averaged test cas…
cs.LG2020★ 1 cited
Road Network Metric Learning for Estimated Time of Arrival
Yiwen Sun, Kun Fu, Zheng Wang +2
Recently, deep learning have achieved promising results in Estimated Time of Arrival (ETA), which is considered as predicting the travel time from the origin to the destination alo…
cs.LG2020★ 3 cited
Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting
Yiwen Sun, Yulu Wang, Kun Fu +3
Traffic forecasting influences various intelligent transportation system (ITS) services and is of great significance for user experience as well as urban traffic control. It is cha…