Self-supervised Trajectory Representation Learning with Temporal Regularities and Travel Semantics

1 code implementation • 17 Nov 2022 • Jiawei Jiang, Dayan Pan, Houxing Ren, Xiaohan Jiang, Chao Li, Jingyuan Wang

TRL aims to convert complicated raw trajectories into low-dimensional representation vectors, which can be applied to various downstream tasks, such as trajectory classification, clustering, and similarity computation.

Contrastive Learning Graph Attention +2