Domain Adversarial Spatial-Temporal Network-Reference-Cited by-同舟云学术

Domain Adversarial Spatial-Temporal Network

Published:2022-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Information & Knowledge Management
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Author:

Tang Yihong¹,Qu Ao²,Chow Andy H.F.³,Lam William H.K.⁴,Wong S.C.¹,Ma Wei⁴

Affiliation:

1. University of Hong Kong, Hong Kong, Hong Kong

2. Massachusetts Institute of Technology, Boston, MA, USA

3. City University of Hong Kong, Hong Kong, Hong Kong

4. The Hong Kong Polytechnic University, Hong Kong, Hong Kong

Funder

Research Grants Council of the Hong Kong Special Administrative Region, China

Research Institute for Sustainable Urban Development (RISUD) at the Hong Kong Polytechnic University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3511808.3557294

Reference67 articles.

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

2. BusTr

3. Shai Ben-David , John Blitzer , Koby Crammer , Alex Kulesza , Fernando Pereira , and Jennifer Wortman Vaughan . 2010. A theory of learning from different domains. Machine learning , Vol. 79 , 1 ( 2010 ), 151--175. Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman Vaughan. 2010. A theory of learning from different domains. Machine learning, Vol. 79, 1 (2010), 151--175.

4. Rishi Bommasani Drew A Hudson Ehsan Adeli Russ Altman Simran Arora Sydney von Arx Michael S Bernstein Jeannette Bohg Antoine Bosselut Emma Brunskill etal 2021. On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258 (2021). Rishi Bommasani Drew A Hudson Ehsan Adeli Russ Altman Simran Arora Sydney von Arx Michael S Bernstein Jeannette Bohg Antoine Bosselut Emma Brunskill et al. 2021. On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258 (2021).

5. Traffic transformer: Capturing the continuity and periodicity of time series for traffic forecasting

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