| 2025 | WSDM | Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data. | Binbin Hu, Zhicheng An, Zhengwei Wu, Ke Tu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Yufei Feng, Jiawei Chen |
| 2024 | KDD | DDCDR: A Disentangle-based Distillation Framework for Cross-Domain Recommendation. | Zhicheng An, Zhexu Gu, Li Yu, Ke Tu, Zhengwei Wu, Binbin Hu, Zhiqiang Zhang, Lihong Gu, Jinjie Gu |
| 2024 | SMC | TS3IM: Unveiling Structural Similarity in Time Series through Image Similarity Assessment Insights. | Yuhan Liu, Ke Tu |
| 2023 | CIKM | Disentangled Interest importance aware Knowledge Graph Neural Network for Fund Recommendation. | Ke Tu, Wei Qu, Zhengwei Wu, Zhiqiang Zhang, Zhongyi Liu, Yiming Zhao, Le Wu, Jun Zhou, Guannan Zhang |
| 2023 | DASFAA | A Scalable Social Recommendation Framework with Decoupled Graph Neural Network. | Ke Tu, Zhengwei Wu, Binbin Hu, Zhiqiang Zhang, Peng Cui, Xiaolong Li, Jun Zhou |
| 2022 | IJCNN | Light-Weight Branch-Shared Multi-View Convolutional Neural Networks Crowd Counting. | Yonghui Wang, Yang Li, Ke Tu |
| 2021 | CIKM | Conditional Graph Attention Networks for Distilling and Refining Knowledge Graphs in Recommendation. | Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu |
| 2020 | CIKM | Graph Neural Network for Tag Ranking in Tag-enhanced Video Recommendation. | Qi Liu, Ruobing Xie, Lei Chen, Shukai Liu, Ke Tu, Peng Cui, Bo Zhang, Leyu Lin |
| 2019 | KDD | AutoNE: Hyperparameter Optimization for Massive Network Embedding. | Ke Tu, Jianxin Ma, Peng Cui, Jian Pei, Wenwu Zhu |
| 2018 | AAAI | Structural Deep Embedding for Hyper-Networks. | Ke Tu, Peng Cui, Xiao Wang, Fei Wang, Wenwu Zhu |
| 2018 | KDD | Deep Recursive Network Embedding with Regular Equivalence. | Ke Tu, Peng Cui, Xiao Wang, Philip S. Yu, Wenwu Zhu |