Generative approach to unsupervised deep local learning. - Changlu Chen; Chaoxi Niu; Xia Zhan; Kun Zhan (J. Electronic Imaging, 2019)

Graph Structure Fusion for Multiview Clustering. - Kun Zhan; Chaoxi Niu; Changlu Chen; Feiping Nie 001; Changqing Zhang; Yi Yang 001 (IEEE Trans. Knowl. Data Eng., 2019)

Mutual teaching for graph convolutional networks. - Kun Zhan; Chaoxi Niu (Future Gener. Comput. Syst., 2021)

Graph-Level Anomaly Detection via Hierarchical Memory Networks. - Chaoxi Niu; Guansong Pang; Ling Chen 006 (ECML/PKDD (1), 2023)

Graph Continual Learning with Debiased Lossless Memory Replay. - Chaoxi Niu; Guansong Pang; Ling Chen 006 (ECAI, 2024)

Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach. - Chaoxi Niu; Guansong Pang; Ling Chen 006; Bing Liu (NeurIPS, 2024)

Zero-shot Generalist Graph Anomaly Detection with Unified Neighborhood Prompts. - Chaoxi Niu; Hezhe Qiao; Changlu Chen; Ling Chen 006; Guansong Pang (CoRR, 2024)

Affinity Uncertainty-Based Hard Negative Mining in Graph Contrastive Learning. - Chaoxi Niu; Guansong Pang; Ling Chen 006 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Hierarchical Consensus Network for Multiview Feature Learning. - Chengwei Xia; Chaoxi Niu; Kun Zhan (AAAI, 2025)

AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection. - Hezhe Qiao; Chaoxi Niu; Ling Chen 006; Guansong Pang (CoRR, 2025)

Reprogramming Vision Foundation Models for Spatio-Temporal Forecasting. - Changlu Chen; Yanbin Liu; Chaoxi Niu; Ling Chen; Tianqing Zhu (CoRR, 2025)