Clustering by finding prominent peaks in density space. - Li Ni; Wenjian Luo; Wenjie Zhu 005; Wenjie Liu 008 (Eng. Appl. Artif. Intell., 2019)

Evolutionary Approach to Multiparty Multiobjective Optimization Problems with Common Pareto Optimal Solutions. - Wenjie Liu 008; Wenjian Luo; Xin Lin 004; Miqing Li; Shengxiang Yang (CEC, 2020)

A Novel Sequential Coreset Method for Gradient Descent Algorithms. - Jiawei Huang 009; Ruomin Huang; Wenjie Liu 008; Nikolaos M. Freris; Hu Ding (ICML, 2021)

Coresets for Wasserstein Distributionally Robust Optimization Problems. - Ruomin Huang; Jiawei Huang 009; Wenjie Liu 008; Hu Ding (NeurIPS, 2022)

Solving Low-Dose CT Reconstruction via GAN with Local Coherence. - Wenjie Liu 008; Hu Ding (MICCAI (10), 2023)

A Data-dependent Approach for High-dimensional (Robust) Wasserstein Alignment. - Hu Ding; Wenjie Liu 008; Mingquan Ye (ACM J. Exp. Algorithmics, 2023)

Bi-criteria Sublinear Time Algorithms for Clustering with Outliers in High Dimensions. - Jiawei Huang 009; Wenjie Liu 008; Hu Ding (COCOON (1), 2024)

A Novel Confidence Guided Training Method for Conditional GANs with Auxiliary Classifier. - Qi Chen; Wenjie Liu 008; Hu Ding (ACM Multimedia, 2024)

Efficient and Robust Neural Combinatorial Optimization via Wasserstein-Based Coresets. - Xu Wang; Fuyou Miao 001; Wenjie Liu 008; Yan Xiong 001 (ICLR, 2025)