| 2026 | KDD | Enhancing Node-Level Graph Domain Adaptation by Alleviating Local Dependency. | Xinwei Tai, Dongmian Zou, Hongfei Wang |
| 2025 | CIKM | Ensemble Pruning via Graph Neural Networks. | Yuanke Li, Yiyang Liu, Dongmian Zou, Hongfei Wang |
| 2025 | ECAI | Enhancing Fairness in Autoencoders for Node-Level Graph Anomaly Detection. | Shouju Wang, Yuchen Song, Sheng'en Li, Dongmian Zou |
| 2024 | ECCV | Improving Hyperbolic Representations via Gromov-Wasserstein Regularization. | Yifei Yang, Wonjun Lee, Dongmian Zou, Gilad Lerman |
| 2024 | KDD | Improving Robustness of Hyperbolic Neural Networks by Lipschitz Analysis. | Yuekang Li, Yidan Mao, Yifei Yang, Dongmian Zou |
| 2023 | AISTATS | An Unpooling Layer for Graph Generation. | Yinglong Guo, Dongmian Zou, Gilad Lerman |
| 2023 | AISTATS | Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection. | Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman |
| 2023 | KDD | Enhancing Node-Level Adversarial Defenses by Lipschitz Regularization of Graph Neural Networks. | Yaning Jia, Dongmian Zou, Hongfei Wang, Hai Jin |
| 2020 | ICLR | Robust Subspace Recovery Layer for Unsupervised Anomaly Detection. | Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman |
| 2019 | IJCNN | Encoding robust representation for graph generation. | Dongmian Zou, Gilad Lerman |