Yunhe Zhang

23 papers A* 8A 1Journal 12Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
MoEGAD: A Mixture-of-Experts Framework With Pseudo-Anomaly Generation for Graph-Level Anomaly Detection.
IEEE Trans. Pattern Anal. Mach. Intell.
Jinyu Cai, Yunhe Zhang, Pengyang Wang, See-Kiong Ng
2026 J jnl
discDC: Unsupervised discriminative deep image clustering via confidence-driven self-labeling.
Pattern Recognit.
Jinyu Cai, Wenzhong Guo, Yunhe Zhang, Jicong Fan
2025 — conf
Generative Imputation with Multi-level Causal Consistency for Variable Subset Forecasting.
KDD (2)
Qi Hao, Yue Gao, Runchang Liang, Yunhe Zhang, Pengyang Wang
2025 A* conf
Leveraging Diffusion Model as Pseudo-Anomalous Graph Generator for Graph-Level Anomaly Detection.
ICML
Jinyu Cai, Yunhe Zhang, Fusheng Liu, See-Kiong Ng
2025 A* conf
Mixture of Experts as Representation Learner for Deep Multi-View Clustering.
AAAI
Yunhe Zhang, Jinyu Cai, Zhihao Wu, Pengyang Wang, See-Kiong Ng
2025 A* conf
Self-Discriminative Modeling for Anomalous Graph Detection.
ICML
Jinyu Cai, Yunhe Zhang, Jicong Fan
2025 J jnl
Towards Adaptive Masked Structural Learning for Graph-Level Clustering.
IEEE Trans. Netw. Sci. Eng.
Jinbin Yang, Jinyu Cai, Yunhe Zhang, Sujia Huang, Shiping Wang
2024 A* conf
Deep Orthogonal Hypersphere Compression for Anomaly Detection.
ICLR
Yunhe Zhang, Yan Sun, Jinyu Cai, Jicong Fan
2024 A* conf
Dual Contrastive Graph-Level Clustering with Multiple Cluster Perspectives Alignment.
IJCAI
Jinyu Cai, Yunhe Zhang, Jicong Fan, Yali Du, Wenzhong Guo
2024 J jnl
FGAD: Self-boosted Knowledge Distillation for An Effective Federated Graph Anomaly Detection Framework.
CoRR
Jinyu Cai, Yunhe Zhang, Zhoumin Lu, Wenzhong Guo, See-Kiong Ng
2024 A* conf
LG-FGAD: An Effective Federated Graph Anomaly Detection Framework.
IJCAI
Jinyu Cai, Yunhe Zhang, Jicong Fan, See-Kiong Ng
2024 A* conf
Towards Effective Federated Graph Anomaly Detection via Self-boosted Knowledge Distillation.
ACM Multimedia
Jinyu Cai, Yunhe Zhang, Zhoumin Lu, Wenzhong Guo, See-Kiong Ng
2024 J jnl
Wasserstein Embedding Learning for Deep Clustering: A Generative Approach.
IEEE Trans. Multim.
Jinyu Cai, Yunhe Zhang, Shiping Wang, Jicong Fan, Wenzhong Guo
2023 J jnl
Deep Graph-Level Orthogonal Hypersphere Compression for Anomaly Detection.
CoRR
Yunhe Zhang, Yan Sun, Jinyu Cai, Jicong Fan
2023 J jnl
Dual Fusion-Propagation Graph Neural Network for Multi-View Clustering.
IEEE Trans. Multim.
Shunxin Xiao, Shide Du, Zhaoliang Chen, Yunhe Zhang, Shiping Wang
2023 J jnl
Learnable Multi-View Matrix Factorization With Graph Embedding and Flexible Loss.
IEEE Trans. Multim.
Sheng Huang, Yunhe Zhang, Lele Fu, Shiping Wang
2023 J jnl
Learning matrix factorization with scalable distance metric and regularizer.
Neural Networks
Shiping Wang, Yunhe Zhang, Xincan Lin, Lichao Su, Guobao Xiao, William Zhu, Yiqing Shi
2023 J jnl
Multiview Deep Matrix Factorization for Shared Compact Representation.
IEEE Trans. Comput. Soc. Syst.
Zexi Chen, Yunhe Zhang, Sheng Huang, Yanfang Liu, William Zhu, Shiping Wang
2023 J jnl
Self-Discriminative Modeling for Anomalous Graph Detection.
CoRR
Jinyu Cai, Yunhe Zhang, Jicong Fan
2022 A* conf
Efficient Deep Embedded Subspace Clustering.
CVPR
Jinyu Cai, Jicong Fan, Wenzhong Guo, Shiping Wang, Yunhe Zhang, Zhao Zhang
2022 A conf
Multi-View Deep Matrix Factorization with Consensual Solution from Multiple Paths.
ICME
Sheng Huang, Lele Fu, Yunhe Zhang, Haiping Xu, Shiping Wang
2021 — conf
Enhanced Multi-view Matrix Factorization with Shared Representation.
PRCV (4)
Sheng Huang, Yunhe Zhang, Lele Fu, Shiping Wang
2021 J jnl
Unsupervised feature selection via transformed auto-encoder.
Knowl. Based Syst.
Yunhe Zhang, Zhoumin Lu, Shiping Wang