Robust Anomaly Detection from Partially Observed Anomalies with Augmented Classes. - Rundong He; Zhongyi Han; Yu Zhang; Xueying He; Xiushan Nie; Yilong Yin (CICAI (2), 2021)

Semi-Supervised Screening of COVID-19 from Positive and Unlabeled Data with Constraint Non-Negative Risk Estimator. - Zhongyi Han; Rundong He; Tianyang Li; Benzheng Wei; Jian Wang 123; Yilong Yin (IPMI, 2021)

Normality Learning in Multispace for Video Anomaly Detection. - Yu Zhang; Xiushan Nie; Rundong He; Meng Chen 003; Yilong Yin (IEEE Trans. Circuits Syst. Video Technol., 2021)

Not All Parameters Should Be Treated Equally: Deep Safe Semi-supervised Learning under Class Distribution Mismatch. - Rundong He; Zhongyi Han; Yang Yang 074; Yilong Yin (AAAI, 2022)

SNAIL: Semi-Separated Uncertainty Adversarial Learning for Universal Domain Adaptation. - Zhongyi Han; Wan Su; Rundong He; Yilong Yin (ACML, 2022)

Safe-Student for Safe Deep Semi-Supervised Learning with Unseen-Class Unlabeled Data. - Rundong He; Zhongyi Han; Xiankai Lu; Yilong Yin (CVPR, 2022)

RONF: Reliable Outlier Synthesis under Noisy Feature Space for Out-of-Distribution Detection. - Rundong He; Zhongyi Han; Xiankai Lu; Yilong Yin (ACM Multimedia, 2022)

Topological Structure Learning for Weakly-Supervised Out-of-Distribution Detection. - Rundong He; Rongxue Li; Zhongyi Han; Yilong Yin (CoRR, 2022)

Towards safe and robust weakly-supervised anomaly detection under subpopulation shift. - Rundong He; Zhongyi Han; Yilong Yin (Knowl. Based Syst., 2022)

Discriminability and Transferability Estimation: A Bayesian Source Importance Estimation Approach for Multi-Source-Free Domain Adaptation. - Zhongyi Han; Zhiyan Zhang; Fan Wang; Rundong He; Wan Su; Xiaoming Xi; Yilong Yin (AAAI, 2023)

MHPL: Minimum Happy Points Learning for Active Source Free Domain Adaptation. - Fan Wang; Zhongyi Han; Zhiyan Zhang; Rundong He; Yilong Yin (CVPR, 2023)

Topological Structure Learning for Weakly-Supervised Out-of-Distribution Detection. - Rundong He; Rongxue Li; Zhongyi Han; Xihong Yang; Yilong Yin (ACM Multimedia, 2023)

LHAct: Rectifying Extremely Low and High Activations for Out-of-Distribution Detection. - Yue Yuan; Rundong He; Zhongyi Han; Yilong Yin (ACM Multimedia, 2023)

How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation. - Zhongyi Han; Guanglin Zhou; Rundong He; Jindong Wang 001; Tailin Wu; Yilong Yin; Salman H. Khan 001; Lina Yao 001; Tongliang Liu; Kun Zhang 001 (CoRR, 2023)

Neighborhood-based credibility anchor learning for universal domain adaptation. - Wan Su; Zhongyi Han; Rundong He; Benzheng Wei; Xueying He; Yilong Yin (Pattern Recognit., 2023)

Exploring Channel-Aware Typical Features for Out-of-Distribution Detection. - Rundong He; Yue Yuan; Zhongyi Han; Fan Wang; Wan Su; Yilong Yin; Tongliang Liu; Yongshun Gong (AAAI, 2024)

Navigating the Unknown: A Novel MGUAN Framework for Medical Image Recognition Across Dynamic Domains. - Wan Su; Fan Wang; Rundong He; Zhongyi Han; Yilong Yin (BIBM, 2024)

Discriminability-Driven Channel Selection for Out-of-Distribution Detection. - Yue Yuan; Rundong He; Yicong Dong; Zhongyi Han; Yilong Yin (CVPR, 2024)

CLIP-driven Outliers Synthesis for few-shot OOD detection. - Hao Sun; Rundong He; Zhongyi Han; Zhicong Lin; Yongshun Gong; Yilong Yin (CoRR, 2024)

SAFER-STUDENT for Safe Deep Semi-Supervised Learning With Unseen-Class Unlabeled Data. - Rundong He; Zhongyi Han; Xiankai Lu; Yilong Yin (IEEE Trans. Knowl. Data Eng., 2024)

Learning sample-aware threshold for semi-supervised learning. - Qi Wei 004; Lei Feng 006; Haoliang Sun; Ren Wang 011; Rundong He; Yilong Yin (Mach. Learn., 2024)

Correction: Learning sample-aware threshold for semi-supervised learning. - Qi Wei 004; Lei Feng 006; Haoliang Sun; Ren Wang 011; Rundong He; Yilong Yin (Mach. Learn., 2024)

Visual Out-of-Distribution Detection in Open-Set Noisy Environments. - Rundong He; Zhongyi Han; Xiushan Nie; Yilong Yin; Xiaojun Chang (Int. J. Comput. Vis., 2024)

Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model. - Rundong He; Yicong Dong; Lanzhe Guo; Yilong Yin; Tailin Wu (ICLR, 2025)

Diverse Teacher-Students for deep safe semi-supervised learning under class mismatch. - Qikai Wang; Rundong He; Yongshun Gong; Chunxiao Ren; Haoliang Sun; Xiaoshui Huang; Yilong Yin (Neural Networks, 2025)

G-OSR: A Comprehensive Benchmark for Graph Open-Set Recognition. - Yicong Dong; Rundong He; Guangyao Chen; Wentao Zhang; Zhongyi Han; Jieming Shi 001; Yilong Yin (CoRR, 2025)