| 2023 | A Causality Inspired Framework for Model Interpretation. | Chenwang Wu, Xiting Wang, Defu Lian, Xing Xie, Enhong Chen |
| 2023 | Self-Adaptive Perturbation Radii for Adversarial Training. | Huimin Wu, Wanli Shi, Chenkang Zhang, Bin Gu |
| 2023 | DNet: Distributional Network for Distributional Individualized Treatment Effects. | Guojun Wu, Ge Song, Xiaoxiang Lv, Shikai Luo, Chengchun Shi, Hongtu Zhu |
| 2023 | Certified Edge Unlearning for Graph Neural Networks. | Kun Wu, Jie Shen, Yue Ning, Ting Wang, Wendy Hui Wang |
| 2023 | Deep Learning on Graphs: Methods and Applications (DLG-KDD2023). | Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo |
| 2023 | Deep Bayesian Active Learning for Accelerating Stochastic Simulation. | Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu |
| 2023 | Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation. | Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, Enhong Chen |
| 2023 | Towards Reliable Rare Category Analysis on Graphs via Individual Calibration. | Longfeng Wu, Bowen Lei, Dongkuan Xu, Dawei Zhou |
| 2023 | TransformerLight: A Novel Sequence Modeling Based Traffic Signaling Mechanism via Gated Transformer. | Qiang Wu, Mingyuan Li, Jun Shen, Linyuan L, Bo Du, Ke Zhang |
| 2023 | Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining. | Xidong Wu, Zhengmian Hu, Jian Pei, Heng Huang |
| 2023 | Trustworthy Transfer Learning: Transferability and Trustworthiness. | Jun Wu, Jingrui He |
| 2023 | DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection. | Jiaying Wu, Bryan Hooi |
| 2023 | Graph Neural Networks: Foundation, Frontiers and Applications. | Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Xiaojie Guo |
| 2023 | Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering. | Yan Wen, Chen Gao, Lingling Yi, Liwei Qiu, Yaqing Wang, Yong Li |
| 2023 | To Aggregate or Not? Learning with Separate Noisy Labels. | Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu |
| 2023 | Meta Graph Learning for Long-tail Recommendation. | Chunyu Wei, Jian Liang, Di Liu, Zehui Dai, Mang Li, Fei Wang |
| 2023 | RLTP: Reinforcement Learning to Pace for Delayed Impression Modeling in Preloaded Ads. | Penghui Wei, Yongqiang Chen, Shaoguo Liu, Liang Wang, Bo Zheng |
| 2023 | Granger Causal Chain Discovery for Sepsis-Associated Derangements via Continuous-Time Hawkes Processes. | Song Wei, Yao Xie, Christopher S. Josef, Rishikesan Kamaleswaran |
| 2023 | Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring. | Runzhe Wan, Yu Liu, James McQueen, Doug Hains, Rui Song |
| 2023 | Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning. | Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou |
| 2023 | An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series. | Xu Wang, Hongbo Zhang, Pengkun Wang, Yudong Zhang, Binwu Wang, Zhengyang Zhou, Yang Wang |
| 2023 | Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction. | Binwu Wang, Yudong Zhang, Xu Wang, Pengkun Wang, Zhengyang Zhou, Lei Bai, Yang Wang |
| 2023 | VRDU: A Benchmark for Visually-rich Document Understanding. | Zilong Wang, Yichao Zhou, Wei Wei, Chen-Yu Lee, Sandeep Tata |
| 2023 | Improving Conversational Recommendation Systems via Counterfactual Data Simulation. | Xiaolei Wang, Kun Zhou, Xinyu Tang, Wayne Xin Zhao, Fan Pan, Zhao Cao, Ji-Rong Wen |
| 2023 | Automated 3D Pre-Training for Molecular Property Prediction. | Xu Wang, Huan Zhao, Wei-Wei Tu, Quanming Yao |