2 citations · 3 across the 5 of their papers we have counts for
5 papers · 1 filter
MM-Path: Multi-modal, Multi-granularity Path Representation Learning -- Extended Version
Ronghui Xu, Hanyin Cheng, Chenjuan Guo +4
Developing effective path representations has become increasingly essential across various fields within intelligent transportation. Although pre-trained path representation learni…
LightPath: Lightweight and Scalable Path Representation Learning
Sean Bin Yang, Jilin Hu, Chenjuan Guo +2
Movement paths are used widely in intelligent transportation and smart city applications. To serve such applications, path representation learning aims to provide compact represent…
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…
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…
PathRank: A Multi-Task Learning Framework to Rank Paths in Spatial Networks
Sean Bin Yang, Bin Yang
Modern navigation services often provide multiple paths connecting the same source and destination for users to select. Hence, ranking such paths becomes increasingly important, wh…