Publication

Information cascade

• Transformer-enhanced Hawkes process with decoupling training for information cascade prediction. KBS. 2022.
• CCGL: Contrastive cascade graph learning. TKDE. 2022. code.
• CasFlow: Exploring hierarchical structures and propagation uncertainty for cascade prediction. TKDE. 2021. code.
• Decoupling representation and regressor for long-tailed information cascade prediction. SIGIR. 2021.
• A survey of information cascade analysis: models, predictions, and recent advances. ACM CSUR. 2021. arXiv
• Continual information cascade learning. GLOBECOM. 2020.
• Variational information diffusion for probabilistic sascade prediction. INFOCOM. 2020. code.

Urban computing & spatial-temporal data modeling

• Spatial-temporal contrasting for fine-grained urban flow inference. Under review. 2023. code.
• Predicting human mobility via self-supervised disentanglement learning. arXiv. 2022.
• Overcoming forgetting in fine-grained urban flow inference via adaptive knowledge replay. AAAI. 2023.
• Probabilistic fine-grained urban flow inference via normalizing flows. ICASSP. 2022. data. video.
• Contrastive trajectory learning for tour recommendation. ACM TIST. 2021.

Science of science

• Heterogeneous dynamical academic network for learning scientific impact propagation. KBS. 2022. code.
• A heterogeneous dynamical graph neural networks approach to quantify scientific impact. arXiv. 2020. code.

Graph learning

• HGENA: A hyperbolic graph embedding approach for social network alignment. GLOBECOM. 2021.
• Unsupervised user identity linkage via graph neural networks. GLOBECOM. 2020.

Recommender system

• Vector-quantized autoencoder with copula for collaborative filtering. CIKM. 2021.

Time series

• Learning latent seasonal-trend representations for time series forecasting. NeurIPS. Oral. 2022. code.
• PrEF: Probabilistic electricity forecasting via copula-augmented state space model. AAAI. 2022.

Social network analysis

• Meta-learned user preference for topic participation prediction. GLOBECOM. 2020.

---

* Corresponding author, † Equal contribution

1. Xovee Xu, Ting Zhong, Qiang Gao, Fan Zhou*, and Goce Trajcevski.
   Spatial-temporal contrasting for fine-grained urban flow inference. Under review. 2023. code.
2. Haoyang Yu†, Xovee Xu†, Ting Zhong*, and Fan Zhou*.
   Overcoming forgetting in fine-grained urban flow inference via adaptive knowledge replay. AAAI. 2023.
3. Qiang Gao, Jinyu Hong, Xovee Xu, Ping Kuang, Fan Zhou, and Goce Trajcevski.
   Predicting human mobility via self-supervised disentanglement learning. arXiv:2211.09625. 2022.
4. Zhiyuan Wang, Xovee Xu, Goce Trajcevski, Weifeng Zhang, Ting Zhong, and Fan Zhou.
   Learning latent seasonal-trend representations for time series forecasting. NeurIPS. 2022. Oral. code.
5. Liu Yu†, Xovee Xu†, Goce Trajcevski, and Fan Zhou*.
   Transformer-enhanced Hawkes process with decoupling training for information cascade prediction. KBS, 2022.
6. Ting Zhong, Haoyang Yu, Rongfan Li, Xovee Xu*, Xucheng Luo, and Fan Zhou.
   Probabilistic fine-grained urban flow inference with normalizing flows. ICASSP, 2022. data. video.
7. Zhiyuan Wang†, Xovee Xu†, Goce Trajcevski, Kunpeng Zhang, Ting Zhong, and Fan Zhou*.
   PrEF: Probabilistic electricity forecasting via copula-augmented state space model. AAAI, 2022.
8. Xovee Xu, Fan Zhou*, Kunpeng Zhang, and Siyuan Liu.
   CCGL: Contrastive cascade graph learning. TKDE, 2022. arXiv:2107.12576 code.
9. Xovee Xu, Ting Zhong, Ce Li, Goce Trajcevski, and Fan Zhou*.
   Heterogeneous dynamical academic network for learning scientific impact propagation. Knowledge-Based Systems, 2022. code.
10. Fan Zhou, Pengyu Wang, Xovee Xu*, Wenxin Tai, and Goce Trajcevski.
    Contrastive trajectory learning for tour recommendation. ACM TIST, 2021.
11. Fan Zhou, Ce Li, Xovee Xu, Leyuan Liu*, and Goce Trajcevski.
    HGENA: A hyperbolic graph embedding approach for social network alignment. GLOBECOM, 2021.
12. Xovee Xu, Fan Zhou*, Kunpeng Zhang, Siyuan Liu, and Goce Trajcevski.
    CasFlow: Exploring hierarchical structures and propagation uncertainty for cascade prediction. TKDE, 2021. code.
13. Guanyu Wang, Ting Zhong, Xovee Xu, Kunpeng Zhang, Fan Zhou*, and Yong Wang.
    Vector-quantized autoencoder with copula for collaborative filtering. CIKM, 2021.
14. Fan Zhou, Liu Yu, Xovee Xu*, and Goce Trajcevski.
    Decoupling representation and regressor for long-tailed information cascade prediction. SIGIR, 2021.
15. Xovee Xu.
    A research of information diffusion models and popularity prediction using graph neural networks (in Chinese).
    Master's Thesis, School of Information and Software Engineering, Univeristy of Electronic Science and Technology of China (UESTC), Chengdu, Sichuan, China, 2021. Advisor: Ting Zhong. Committee chair: Jingye Cai. Excellent Master Thesis of UESTC.
16. Fan Zhou, Xovee Xu*, Goce Trajcevski, and Kunpeng Zhang.
    A survey of information cascade analysis: Models, predictions, and recent advances. ACM Computing Surveys, 2021. arXiv:2005.11041.
17. Fan Zhou, Xiuxiu Qi, Xovee Xu, Jiahao Wang*, Ting Zhong, and Goce Trajcevski.
    Meta-learned user preference for topic participation prediction. GLOBECOM, 2020.
18. Fan Zhou, Zijing Wen, Ting Zhong*, Goce Trajcevski, Xovee Xu, Leyuan Liu.
    Unsupervised user identity linkage via graph neural networks. GLOBECOM, 2020.
19. Fan Zhou, Xin Jing, Xovee Xu, Ting Zhong, Goce Trajcevski, and Jin Wu*.
    Continual information cascade learning. GLOBECOM, 2020.
20. Fan Zhou, Xovee Xu, Ce Li, Goce Trajcevski, Ting Zhong, and Kunpeng Zhang.
    A heterogeneous dynamical graph neural networks approach to quantify scientific impact. arXiv:2003.12042, 2020. code.
21. Fan Zhou, Xovee Xu, Kunpeng Zhang, Goce Trajcevski, and Ting Zhong*.
    Variational information diffusion for probabilistic cascade prediction. INFOCOM, 2020. video. Student Conference Award.

---