Enhancing Hyperspectral Unmixing With Two-Stage Multiplicative Update Nonnegative Matrix Factorization. - Li Sun; Kang Zhao 001; Congying Han; Ziwen Liu 001 (IEEE Access, 2019)

Blocked and Hierarchical Disentangled Representation From Information Theory Perspective. - Ziwen Liu 001; Mingqiang Li; Congying Han (CoRR, 2021)

Graph Representation Learning by Ensemble Aggregating Subgraphs via Mutual Information Maximization. - Chenguang Wang 011; Ziwen Liu 001 (CoRR, 2021)

Masked Reconstruction Contrastive Learning with Information Bottleneck Principle. - Ziwen Liu 001; Bonan Li; Congying Han; Tiande Guo; Xuecheng Nie (CoRR, 2022)

Learning graph representation by aggregating subgraphs via mutual information maximization. - Ziwen Liu 001; Chenguang Wang 011; Congying Han; Tiande Guo (Neurocomputing, 2023)

XNet v2: Fewer Limitations, Better Results and Greater Universality. - Yanfeng Zhou; Lingrui Li; Zichen Wang; Guole Liu; Ziwen Liu 001; Ge Yang 002 (BIBM, 2024)

Learning Dynamic Tetrahedra for High-Quality Talking Head Synthesis. - Zicheng Zhang; Ruobing Zheng; Bonan Li; Congying Han; Tianqi Li; Meng Wang; Tiande Guo; Jingdong Chen; Ziwen Liu 001; Ming Yang 007 (CVPR, 2024)

Blaze3DM: Marry Triplane Representation with Diffusion for 3D Medical Inverse Problem Solving. - Jia He; Bonan Li; Ge Yang 002; Ziwen Liu 001 (CoRR, 2024)

STDNet: Rethinking Disentanglement Learning With Information Theory. - Ziwen Liu 001; Mingqiang Li; Congying Han; Siqi Tang; Tiande Guo (IEEE Trans. Neural Networks Learn. Syst., 2024)

IYNet: Asymmetric Multi-Input Network with Wavelet-Driven LF/HF Perturbation for Semi-Supervised Biomedical Image Segmentation. - Shangwu Feng; Ziwen Liu 001; Ge Yang 002 (BIBM, 2025)

Blaze3DM: Integrating Triplane Representation with Diffusion for Solving 3D Inverse Problems in Medical Imaging. - Jia He; Bonan Li; Ge Yang 002; Ziwen Liu 001 (MICCAI (2), 2025)

Confidence-aware dual-consistency and pixel-sampled dual-contrastive learning for semi-supervised biomedical image segmentation. - Shangwu Feng; Ziwen Liu 001; Ge Yang 002 (Neurocomputing, 2026)