most citedFMA-ETA: Estimating Travel Time Entirely Based on FFN With Attention

4 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2022

A Machine Learning Method for Material Property Prediction: Example Polymer Compatibility

Zhilong Liang, Zhiwei Li, Shuo Zhou +3

Prediction of material property is a key problem because of its significance to material design and screening. We present a brand-new and general machine learning method for materi…

cs.LG20201 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.LG20204 cited

FMA-ETA: Estimating Travel Time Entirely Based on FFN With Attention

Yiwen Sun, Yulu Wang, Kun Fu +4

Estimated time of arrival (ETA) is one of the most important services in intelligent transportation systems and becomes a challenging spatial-temporal (ST) data mining task in rece…

cs.LG20204 cited

Fusion Recurrent Neural Network

Yiwen Sun, Yulu Wang, Kun Fu +3

Considering deep sequence learning for practical application, two representative RNNs - LSTM and GRU may come to mind first. Nevertheless, is there no chance for other RNNs? Will t…

cs.LG20203 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…