Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank-Reference-Cited by-同舟云学术

Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank

Published:2023-10-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
language:
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Author:

Liu Zhanyu¹^ORCID,Zheng Guanjie¹^ORCID,Yu Yanwei²^ORCID

Affiliation:

1. Shanghai Jiao Tong University, Shanghai, China

2. Ocean University of China, Qingdao, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Provincial Key Research and Development Program of Zhejiang

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583780.3614829

Reference51 articles.

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2. Lei Bai , Lina Yao , Can Li , Xianzhi Wang , and Can Wang . 2020. Adaptive graph convolutional recurrent network for traffic forecasting. arXiv preprint arXiv:2007.02842 ( 2020 ). Lei Bai, Lina Yao, Can Li, Xianzhi Wang, and Can Wang. 2020. Adaptive graph convolutional recurrent network for traffic forecasting. arXiv preprint arXiv:2007.02842 (2020).

3. Defu Cao Yujing Wang Juanyong Duan Ce Zhang Xia Zhu Congrui Huang Yunhai Tong Bixiong Xu Jing Bai Jie Tong etal 2020. Spectral temporal graph neural network for multivariate time-series forecasting. Advances in neural information processing systems 33 (2020) 17766--17778. Defu Cao Yujing Wang Juanyong Duan Ce Zhang Xia Zhu Congrui Huang Yunhai Tong Bixiong Xu Jing Bai Jie Tong et al. 2020. Spectral temporal graph neural network for multivariate time-series forecasting. Advances in neural information processing systems 33 (2020) 17766--17778.

4. Graph Neural Controlled Differential Equations for Traffic Forecasting

5. Towards Spatio- Temporal Aware Traffic Time Series Forecasting

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