Accepted Papers
Aurora: Towards Universal Generative Multimodal Time Series Forecasting
🧑💻 Xingjian Wu, Jianxin Jin, Wanghui Qiu, Peng Chen, Yang Shu, Bin Yang, Chenjuan Guo#
🏛️ International Conference on Learning Representations (ICLR), 2026. CCF A.
🧑💻 Hanyin Cheng, Xingjian Wu, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo#
🏛️ International Conference on Learning Representations (ICLR), 2026. CCF A.
GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables
🧑💻 Zhengyu Li, Xiangfei Qiu, Yuhan Zhu, Xingjian Wu, Jilin Hu, Chenjuan Guo, Bin Yang#
🏛️ International Conference on Learning Representations (ICLR), 2026. CCF A.
🧑💻 Xvyuan Liu, Xiangfei Qiu, Hanyin Cheng, Xingjian Wu, Chenjuan Guo, Bin Yang, Jilin Hu#
🏛️ International Conference on Learning Representations (ICLR), 2026. CCF A.
Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline
🧑💻 Xvyuan Liu*, Xiangfei Qiu*, Xingjian Wu*, Zhengyu Li, Chenjuan Guo, Jilin Hu#, Bin Yang
🏛️ Association for the Advancement of Artificial Intelligence Conference on Artificial Intelligence (AAAI), 2026. CCF A.
🏆 Accepted as an Oral paper (Top 4%).
Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective
🧑💻 Xingjian Wu, Xiangfei Qiu, Hanyin Cheng, Zhengyu Li, Jilin Hu, Chenjuan Guo, Bin Yang#
🏛️ Conference on Neural Information Processing Systems (NeurIPS), 2025. CCF A.
🏆 Accepted as a Spotlight poster (Top 3.2%).
Decomposition-based Loss Function for Time Series Forecasting
🧑💻 Xiangfei Qiu, Xingjian Wu, Hanyin Cheng, Xvyuan Liu, Chenjuan Guo, Jilin Hu#, Bin Yang
🏛️ Conference on Neural Information Processing Systems (NeurIPS), 2025. CCF A.
K2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
🧑💻 Xingjian Wu*, Xiangfei Qiu*, Hongfan Gao, Jilin Hu, Bin Yang#, Chenjuan Guo
🏛️ International Conference on Machine Learning (ICML), 2025. CCF A.
🏆 Accepted as a Spotlight poster (Top 2.6%).
TAB: Unified Benchmarking of Time Series Anomaly Detection Methods
🧑💻 Xiangfei Qiu, Zhe Li, Wanghui Qiu, Shiyan Hu, Lekui Zhou, Xingjian Wu, Zhengyu Li, Chenjuan Guo, Aoying Zhou, Zhenli Sheng, Jilin Hu#, Christian S. Jensen, Bin Yang
🏛️ International Conference on Very Large Databases (PVLDB), 2025. CCF A.
CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching
🧑💻 Xingjian Wu, Xiangfei Qiu, Zhengyu Li, Yihang Wang, Jilin Hu, Chenjuan Guo, Hui Xiong, Bin Yang#
🏛️ International Conference on Learning Representations (ICLR), 2025. CCF A.
EasyTime: Time Series Forecasting Made Easy
🧑💻 Xiangfei Qiu*, Xiuwen Li*, Ruiyang Pang*, Zhicheng Pan*, Xingjian Wu*, Liu Yang*, Jilin Hu, Yang Shu, Xuesong Lu, Chengcheng Yang, Chenjuan Guo, Aoying Zhou, Christian S. Jensen and Bin Yang#.
🏛️ IEEE International Conference on Data Engineering (ICDE), 2025. CCF A.
DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting
🧑💻 Xiangfei Qiu, Xingjian Wu, Yan Lin, Chenjuan Guo, Jilin Hu#, Bin Yang
🏛️ ACM Knowledge Discovery and Data Mining (SIGKDD), 2025. CCF A.
Fully Automated Correlated Time Series Forecasting in Minutes
🧑💻 Xinle Wu, Xingjian Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Bin Yang#, Christian S. Jensen
🏛️ International Conference on Very Large Databases (PVLDB), 2025. CCF A.
🧑💻 Xinle Wu*, Xingjian Wu*, Bin Yang#, Lekui Zhou, Chenjuan Guo, Xiangfei Qiu, Jilin Hu, Zhenli Sheng, Christian S. Jensen
🏛️ VLDB Journal (VLDBJ), 2024. CCF A.
TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
🧑💻 Xiangfei Qiu, Jilin Hu#, Lekui Zhou, Xingjian Wu, Junyang Du, Buang Zhang, Chenjuan Guo, Aoying Zhou, Christian S. Jensen, Zhenli Sheng, Bin Yang
🏛️ International Conference on Very Large Databases (PVLDB), 2024. CCF A.
Preprints
ST-EVO: Towards Generative Spatio-Temporal Evolution of Multi-Agent Communication Topologies
🧑💻 Xingjian Wu, Xvyuan Liu, Junkai Lu, Siyuan Wang, Xiangfei Qiu, Yang Shu, Jilin Hu, Chenjuan Guo, Bin Yang#
arXiv preprint, 2026.
TimeART: Towards Agentic Time Series Reasoning via Tool-Agumentation
🧑💻 Xingjian Wu, Junkai Lu, Zhengyu Li, Xiangfei Qiu, Jilin Hu, Chenjuan Guo, Christian S. Jensen, Bin Yang#
arXiv preprint, 2026.
FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting
🧑💻 Xingjian Wu, Hanyin Cheng, Xiangfei Qiu, Zhengyu Li, Jilin Hu, Chenjuan Guo, Bin Yang#
arXiv preprint, 2025.
Task-Aware Mixture-of-Experts for Time Series Analysis
🧑💻 Xingjian Wu, Zhengyu Li, Hanyin Cheng, Xiangfei Qiu, Jilin Hu, Chenjuan Guo, Bin Yang#
arXiv preprint, 2025.
🧑💻 Xiangfei Qiu, Liu Yang, Hanyin Cheng, Xingjian Wu, Rongjia Wu, Zhigang Zhang, Ding Tu, Chenjuan Guo, Bin Yang, Christian S. Jensen, Jilin Hu#
arXiv preprint, 2025.
🧑💻 Xiangfei Qiu, Xvyuan Liu, Tianen Shen, Xingjian Wu, Hanyin Cheng, Bin Yang, Jilin Hu#
arXiv preprint, 2026.
🧑💻 Xiangfei Qiu, Kangjia Yan, Xvyuan Liu, Xingjian Wu, Jilin Hu#
arXiv preprint, 2026.
DAG: A Dual Causal Network for Time Series Forecasting with Exogenous Variables
🧑💻 Xiangfei Qiu, Yuhan Zhu, Zhengyu Li, Hanyin Cheng, Xingjian Wu, Chenjuan Guo, Bin Yang, Jilin Hu#
arXiv preprint, 2025.
🧑💻 Xiangfei Qiu, Hanyin Cheng, Xingjian Wu, Jilin Hu, Chenjuan Guo, Bin Yang
arXiv preprint, 2025.
Empowering Time Series Analysis with Large-Scale Multimodal Pretraining
🧑💻 Peng Chen, Siyuan Wang, Shiyan Hu, Xingjian Wu, Yang Shu, Zhongwen Rao, Meng Wang, Yijie Li, Bin Yang, Chenjuan Guo#
arXiv preprint, 2025.
*Equal Contribution, # Corresponding Author. More working drafts / preprints under review will be released later ⌛️