| 2025 | KDD | IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting. | Wei Fan, Shun Zheng, Pengyang Wang, Rui Xie, Kun Yi, Qi Zhang, Jiang Bian, Yanjie Fu |
| 2024 | ICLR | PTaRL: Prototype-based Tabular Representation Learning via Space Calibration. | Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang |
| 2024 | ICLR | BatteryML: An Open-source Platform for Machine Learning on Battery Degradation. | Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian |
| 2024 | KDD | From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models. | Xumeng Wen, Han Zhang, Shun Zheng, Wei Xu, Jiang Bian |
| 2023 | ADMA | Efficient Graph Collaborative Filtering with Multi-layer Output-Enhanced Contrastive Learning. | Keke Li, Shaoqing Wang, Shun Zheng, Xia Wu, Yao Zhang, Fuzhen Sun |
| 2023 | APWEB | Multi-pair Contrastive Learning Based on Same-Timestamp Data Augmentation for Sequential Recommendation. | Shun Zheng, Shaoqing Wang, Lijie Zhang, Yao Zhang, Fuzhen Sun |
| 2023 | ICDE | UADB: Unsupervised Anomaly Detection Booster. | Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, Jiang Bian |
| 2023 | KDD | Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series. | Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian, Jia Li |
| 2022 | CIKM | A Graph-based Spatiotemporal Model for Energy Markets. | Swati Sharma, Srinivasan Iyengar, Shun Zheng, Kshitij Kapoor, Wei Cao, Jiang Bian, Shivkumar Kalyanaraman, John Lemmon |
| 2022 | ICLR | DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. | Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu |
| 2022 | KDD | Learning Differential Operators for Interpretable Time Series Modeling. | Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian |
| 2021 | ACL | Revisiting the Evaluation of End-to-end Event Extraction. | Shun Zheng, Wei Cao, Wei Xu, Jiang Bian |
| 2021 | CIKM | HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting. | Shun Zheng, Zhifeng Gao, Wei Cao, Jiang Bian, Tie-Yan Liu |
| 2020 | ACL | SEEK: Segmented Embedding of Knowledge Graphs. | Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu |
| 2019 | ACL | DIAG-NRE: A Neural Pattern Diagnosis Framework for Distantly Supervised Neural Relation Extraction. | Shun Zheng, Xu Han, Yankai Lin, Peilin Yu, Lu Chen, Ling Huang, Zhiyuan Liu, Wei Xu |
| 2019 | EMNLP | Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction. | Shun Zheng, Wei Cao, Wei Xu, Jiang Bian |