Yuxuan Liang

Selected publications [See more]

* denotes corresponding author and + indicates equal contribution.

1. WWW’24

   UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Web

   Yibo Yan, Haomin Wen, Siru Zhong, Wei Chen, Haodong Chen, Qingsong Wen, Roger Zimmermann, and Yuxuan Liang*

   In The Web Conference, 2024

   Bib PDF Cited by 69

   @inproceedings{yan2024urbanclip,
     title = {UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Web},
     author = {Yan, Yibo and Wen, Haomin and Zhong, Siru and Chen, Wei and Chen, Haodong and Wen, Qingsong and Zimmermann, Roger and Liang*, Yuxuan},
     booktitle = {The Web Conference},
     year = {2024}
   }

2. WWW’24

   UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting

   Xu Liu, Junfeng Hu, Yuan Li, Shizhe Diao, Yuxuan Liang*, Bryan Hooi, and Roger Zimmermann

   In The Web Conference, 2024

   Bib PDF Cited by 95

   @inproceedings{liu2014unitime,
     title = {UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting},
     author = {Liu, Xu and Hu, Junfeng and Li, Yuan and Diao, Shizhe and Liang*, Yuxuan and Hooi, Bryan and Zimmermann, Roger},
     booktitle = {The Web Conference},
     year = {2024}
   }

3. KDD’24

   Foundation models for time series analysis: A tutorial and survey

   Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, and Qingsong Wen*

   In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Tutorial Track Paper), 2024

   Bib PDF Cited by 130

   @inproceedings{liang2024foundation,
     title = {Foundation models for time series analysis: A tutorial and survey},
     author = {Liang, Yuxuan and Wen, Haomin and Nie, Yuqi and Jiang, Yushan and Jin, Ming and Song, Dongjin and Pan, Shirui and Wen*, Qingsong},
     booktitle = {Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Tutorial Track Paper)},
     year = {2024}
   }

4. AAAI’23

   AirFormer: Predicting Nationwide Air Quality in China with Transformers

   Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang, Qingsong Wen, Junbo Zhang, Yu Zheng, and Roger Zimmermann

   In Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

   Bib PDF Code Cited by 125

   @inproceedings{liang2023airformer,
     title = {AirFormer: Predicting Nationwide Air Quality in China with Transformers},
     author = {Liang, Yuxuan and Xia, Yutong and Ke, Songyu and Wang, Yiwei and Wen, Qingsong and Zhang, Junbo and Zheng, Yu and Zimmermann, Roger},
     booktitle = {Thirty-Seventh AAAI Conference on Artificial Intelligence},
     year = {2023}
   }

5. WWW’21

   Fine-grained Urban Flow Prediction

   Yuxuan Liang, Kun Ouyang, Junkai Sun, Yiwei Wang, Junbo Zhang, Yu Zheng, David Rosenblum, and Roger Zimmermann

   In Proceedings of the Web Conference, 2021

   Bib PDF Cited by 86

   @inproceedings{liang2021fine,
     title = {Fine-grained Urban Flow Prediction},
     author = {Liang, Yuxuan and Ouyang, Kun and Sun, Junkai and Wang, Yiwei and Zhang, Junbo and Zheng, Yu and Rosenblum, David and Zimmermann, Roger},
     booktitle = {Proceedings of the Web Conference},
     pages = {1833--1845},
     year = {2021}
   }

6. KDD’19

   Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning

   Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, and Junbo Zhang

   In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining, 2019

   Bib PDF Code Cited by 614

   @inproceedings{pan2019urban,
     title = {Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning},
     author = {Pan, Zheyi and Liang, Yuxuan and Wang, Weifeng and Yu, Yong and Zheng, Yu and Zhang, Junbo},
     booktitle = {Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery \& data mining},
     pages = {1720--1730},
     year = {2019}
   }

7. KDD’19

   Urbanfm: Inferring Fine-Grained Urban Flows

   Yuxuan Liang+, Kun Ouyang+, Lin Jing, Sijie Ruan, Ye Liu, Junbo Zhang, David S Rosenblum, and Yu Zheng

   In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining, 2019

   Bib PDF Code Cited by 150

   @inproceedings{liang2019urbanfm,
     title = {Urbanfm: Inferring Fine-Grained Urban Flows},
     author = {Liang+, Yuxuan and Ouyang+, Kun and Jing, Lin and Ruan, Sijie and Liu, Ye and Zhang, Junbo and Rosenblum, David S and Zheng, Yu},
     booktitle = {Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery \& data mining},
     pages = {3132--3142},
     year = {2019}
   }

8. IJCAI’18

   GeoMAN: Multi-Level Attention Networks for Geo-sensory Time Series Prediction

   Yuxuan Liang, Songyu Ke, Junbo Zhang, Xiuwen Yi, and Yu Zheng

   In International Joint Conference on Artificial Intelligence, 2018

   Bib PDF Code Cited by 594

   @inproceedings{liang2018geoman,
     title = {GeoMAN: Multi-Level Attention Networks for Geo-sensory Time Series Prediction},
     author = {Liang, Yuxuan and Ke, Songyu and Zhang, Junbo and Yi, Xiuwen and Zheng, Yu},
     booktitle = {International Joint Conference on Artificial Intelligence},
     volume = {2018},
     pages = {3428--3434},
     year = {2018}
   }