Jointly Contrastive Representation Learning on Road Network and Trajectory

Author:

Mao Zhenyu1,Li Ziyue2,Li Dedong1,Bai Lei3,Zhao Rui4

Affiliation:

1. SenseTime Research, Shanghai, China

2. University of Cologne & EWI gGmbH, Cologne, Germany

3. Shanghai AI Lab, Shanghai, China

4. SenseTime Research & Qing Yuan Research Institute of Shanghai Jiao Tong University, Shanghai, China

Publisher

ACM

Reference45 articles.

1. Philip Bachman , R Devon Hjelm , and William Buchwalter . 2019. Learning representations by maximizing mutual information across views. arXiv preprint arXiv:1906.00910 ( 2019 ). Philip Bachman, R Devon Hjelm, and William Buchwalter. 2019. Learning representations by maximizing mutual information across views. arXiv preprint arXiv:1906.00910 (2019).

2. Adaptive graph convolutional recurrent network for traffic forecasting;Bai Lei;Advances in Neural Information Processing Systems,2020

3. Spatial networks

4. Mohamed Ishmael Belghazi , Aristide Baratin , Sai Rajeshwar , Sherjil Ozair , Yoshua Bengio , Aaron Courville , and Devon Hjelm . 2018 . Mutual information neural estimation . In International Conference on Machine Learning. PMLR, 531--540 . Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeshwar, Sherjil Ozair, Yoshua Bengio, Aaron Courville, and Devon Hjelm. 2018. Mutual information neural estimation. In International Conference on Machine Learning. PMLR, 531--540.

5. Ting Chen , Simon Kornblith , Mohammad Norouzi , and Geoffrey Hinton . 2020 . A simple framework for contrastive learning of visual representations . In International conference on machine learning. PMLR, 1597--1607 . Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020. A simple framework for contrastive learning of visual representations. In International conference on machine learning. PMLR, 1597--1607.

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