Papers and Talks from Our Team

[📜 Paper] Jun Wang*, Wenjie Du*, Yiyuan Yang, Linglong Qian, Wei Cao, Keli Zhang, Wenjia Wang, Yuxuan Liang, Qingsong Wen. Deep Learning for Multivariate Time Series Imputation: A Survey, IJCAI, 2025.
[DOI Link] [PDF] [Code]

[📜 Paper] Yaxuan Kong*, Yiyuan Yang*, Yoontae Hwang, Wenjie Du, Stefan Zohren, Zhangyang Wang, Ming Jin, Qingsong Wen. Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement, ACL, 2025.
[DOI Link] [PDF] [Code]

[📜 Paper] Linglong Qian, Tao Wang, Jun Wang, Hugh Logan Ellis, Robin Mitra, Richard Dobson, Zina Ibrahim. How Deep is your Guess? A Fresh Perspective on Deep Learning for Medical Time-Series Imputation, IEEE Journal of Biomedical and Health Informatics, 2025.
[DOI Link] [PDF]

[📝 Preprint] Joseph Arul Raj, Linglong Qian, Zina Ibrahim. Fine-tuning – a Transfer Learning approach, arXiv preprint, abs/2411.03941, 2024.
[DOI Link] [PDF]

[📝 Preprint] Linglong Qian, Joseph Arul Raj, Hugh Logan Ellis, Ao Zhang, Yuezhou Zhang, Tao Wang, Richard JB Dobson, Zina Ibrahim. Knowledge Enhanced Conditional Imputation for Healthcare Time-series, arXiv preprint, abs/2312.16713, 2024.
[DOI Link] [PDF] [Code]

[📝 Preprint] Tianxiang Zhan, Yuanpeng He, Yong Deng, Zhen Li, Wenjie Du, Qingsong Wen. Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting, arXiv preprint, abs/2405.06419, 2024.
[DOI Link] [PDF] [Code]

[🎙️ Talk] Wenjie Du. Learning from Partially Observed Time Series: Towards Reality-Centric AI4TS, Keynote at IJCAI'24 AI4TS (AI for Time Series Analysis) Workshop, Jeju, South Korea, August 5, 2024.
[Slides to be updated here]

[📝 Preprint] Wenjie Du*, Jun Wang*, Linglong Qian*, Yiyuan Yang*, Zina Ibrahim, Fanxing Liu, Zepu Wang, Haoxin Liu, Zhiyuan Zhao, Yingjie Zhou, Wenjia Wang, Kaize Ding, Yuxuan Liang, B. Aditya Prakash, Qingsong Wen. TSI-Bench: Benchmarking Time Series Imputation, arXiv preprint, abs/2406.12747, 2024.
[DOI Link] [PDF] [Code]

[📜 Paper] Linglong Qian, Zina Ibrahim, Wenjie Du, Yiyuan Yang, Richard JB Dobson. Unveiling the Secrets: How Masking Strategies Shape Time Series Imputation, IJCAI'24 AI4TS (AI for Time Series Analysis) Workshop, 2024.
[DOI Link] [PDF] [Code]

[📜 Paper] Wenjie Du. PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series, arXiv preprint, abs/2305.18811, 2023. (A short version appeared in the 9th SIGKDD International Workshop on Mining and Learning from Time Series (MiLeTS'23))
[DOI Link] [PDF] [Code]

[📜 Paper] Wenjie Du, David Cote, Yan Liu. SAITS: Self-Attention-based Imputation for Time Series, Expert Systems with Applications, 219:119619, 2023.
[DOI Link] [PDF] [Code] 2022 IF-8.665/JCR-Q1/CAS-Q1  

[🎙️ Talk] Wenjie Du. Efficient and Effective Time Series Imputation: from RNN to Transformer, Virtual Presentation at Ciena Corp., Montreal, Canada, July 9, 2021.

[📜 Paper] Wenjie Du, David Cote, Chris Barber, Yan Liu. Forecasting Loss of Signal in Optical Networks with Machine Learning, IEEE/OSA Journal of Optical Communications and Networking, vol. 13, no. 10, pp. E109-E121 (2021).
[DOI Link] [PDF] [Code] 2022 IF-4.508/JCR-Q1/CAS-Q1