9 citations · 14 across the 4 of their papers we have counts for
7 papers
Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning -- Extended Version
Sean Bin Yang, Chenjuan Guo, Jilin Hu +3
In step with the digitalization of transportation, we are witnessing a growing range of path-based smart-city applications, e.g., travel-time estimation and travel path ranking. A…
Evolutionary Clustering of Streaming Trajectories
Tianyi Li, Lu Chen, Christian S. Jensen +2
The widespread deployment of smartphones and location-enabled, networked in-vehicle devices renders it increasingly feasible to collect streaming trajectory data of moving objects.…
Unsupervised Path Representation Learning with Curriculum Negative Sampling
Sean Bin Yang, Chenjuan Guo, Jilin Hu +2
Path representations are critical in a variety of transportation applications, such as estimating path ranking in path recommendation systems and estimating path travel time in nav…
SOUP: Spatial-Temporal Demand Forecasting and Competitive Supply
Bolong Zheng, Qi Hu, Lingfeng Ming +4
We consider a setting with an evolving set of requests for transportation from an origin to a destination before a deadline and a set of agents capable of servicing the requests. I…
Infinitely Wide Graph Convolutional Networks: Semi-supervised Learning via Gaussian Processes
Jilin Hu, Jianbing Shen, Bin Yang +1
Graph convolutional neural networks~(GCNs) have recently demonstrated promising results on graph-based semi-supervised classification, but little work has been done to explore thei…
Recurrent Multi-Graph Neural Networks for Travel Cost Prediction
Jilin Hu, Chenjuan Guo, Bin Yang +2
Origin-destination (OD) matrices are often used in urban planning, where a city is partitioned into regions and an element (i, j) in an OD matrix records the cost (e.g., travel tim…