Unsupervised Domain Adaptation with Sphere Retracting Transformation. - Zhen Fang 001; Jie Lu 001; Feng Liu 003; Guangquan Zhang 001 (IJCNN, 2019)

Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation. - Yiyang Zhang; Feng Liu 003; Zhen Fang 001; Bo Yuan 003; Guangquan Zhang 001; Jie Lu 001 (IJCAI, 2020)

How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches? - Zhong Li 001; Zhen Fang 001; Feng Liu 003; Jie Lu 001; Bo Yuan 003; Guangquan Zhang 001 (AAAI, 2021)

Learning Bounds for Open-Set Learning. - Zhen Fang 001; Jie Lu 001; Anjin Liu; Feng Liu 003; Guangquan Zhang 001 (ICML, 2021)

Confident Anchor-Induced Multi-Source Free Domain Adaptation. - Jiahua Dong 001; Zhen Fang 001; Anjin Liu; Gan Sun; Tongliang Liu (NeurIPS, 2021)

Open Set Domain Adaptation: Theoretical Bound and Algorithm. - Zhen Fang 001; Jie Lu 001; Feng Liu 003; Junyu Xuan; Guangquan Zhang 001 (IEEE Trans. Neural Networks Learn. Syst., 2021)

Bridging Theory and Algorithms for Open-Set and Heterogeneous Domain Adaptations - Zhen Fang 001 (2021)

Federated Class-Incremental Learning. - Jiahua Dong 001; Lixu Wang; Zhen Fang 001; Gan Sun; Shichao Xu; Xiao Wang 012; Qi Zhu 002 (CVPR, 2022)

Is Out-of-Distribution Detection Learnable? - Zhen Fang 001; Yixuan Li 001; Jie Lu 001; Jiahua Dong 001; Bo Han 003; Feng Liu 003 (NeurIPS, 2022)

Multi-class Classification with Fuzzy-feature Observations: Theory and Algorithms. - Guangzhi Ma; Jie Lu 001; Feng Liu 003; Zhen Fang 001; Guangquan Zhang 001 (CoRR, 2022)

Learning From a Complementary-Label Source Domain: Theory and Algorithms. - Yiyang Zhang; Feng Liu 003; Zhen Fang 001; Bo Yuan 003; Guangquan Zhang 001; Jie Lu 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Multiple Teacher Model for Continual Test-Time Domain Adaptation. - Ran Wang 016; Hua Zuo; Zhen Fang 001; Jie Lu 001 (AI (1), 2023)

Continual Named Entity Recognition without Catastrophic Forgetting. - Duzhen Zhang; Wei Cong; Jiahua Dong 001; Yahan Yu; Xiuyi Chen; Yonggang Zhang 003; Zhen Fang 001 (EMNLP, 2023)

Multi-model Transfer Learning and Genotypic Analysis for Seizure Type Classification. - Yue Yang; Kairui Guo; Zhen Fang 001; Hua Lin; Mark Grosser; Jie Lu 001 (HIS, 2023)

Kecor: Kernel Coding Rate Maximization for Active 3D Object Detection. - Yadan Luo; Zhuoxiao Chen; Zhen Fang 001; Zheng Zhang 006; Mahsa Baktashmotlagh; Zi Huang (ICCV, 2023)

Meta OOD Learning For Continuously Adaptive OOD Detection. - Xinheng Wu; Jie Lu 001; Zhen Fang 001; Guangquan Zhang 001 (ICCV, 2023)

Moderately Distributional Exploration for Domain Generalization. - Rui Dai; Yonggang Zhang 003; Zhen Fang 001; Bo Han 003; Xinmei Tian 001 (ICML, 2023)

Detecting Out-of-distribution Data through In-distribution Class Prior. - Xue Jiang; Feng Liu 003; Zhen Fang 001; Hong Chen 004; Tongliang Liu; Feng Zheng; Bo Han 003 (ICML, 2023)

One-step Domain Adaptation Approach with Partial Label. - Guohang Zeng; Zhen Fang 001; Guangquan Zhang 001; Jie Lu 001 (IJCNN, 2023)

Learning to Augment Distributions for Out-of-distribution Detection. - Qizhou Wang; Zhen Fang 001; Yonggang Zhang 003; Feng Liu 003; Yixuan Li 001; Bo Han 003 (NeurIPS, 2023)

SODA: Robust Training of Test-Time Data Adaptors. - Zige Wang; Yonggang Zhang 003; Zhen Fang 001; Long Lan; Wenjing Yang 002; Bo Han 003 (NeurIPS, 2023)

Invariant Learning via Probability of Sufficient and Necessary Causes. - Mengyue Yang; Yonggang Zhang 003; Zhen Fang 001; Yali Du 001; Furui Liu; Jean-Francois Ton; Jianhong Wang; Jun Wang 012 (NeurIPS, 2023)

Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources. - Haotian Zheng; Qizhou Wang; Zhen Fang 001; Xiaobo Xia; Feng Liu 003; Tongliang Liu; Bo Han 003 (NeurIPS, 2023)

Invariant Learning via Probability of Sufficient and Necessary Causes. - Mengyue Yang; Zhen Fang 001; Yonggang Zhang 003; Yali Du 001; Furui Liu; Jean-Francois Ton; Jun Wang 012 (CoRR, 2023)

Semi-Supervised Heterogeneous Domain Adaptation: Theory and Algorithms. - Zhen Fang 001; Jie Lu 001; Feng Liu 003; Guangquan Zhang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation. - Zhong Li 001; Zhen Fang 001; Feng Liu 003; Bo Yuan 003; Guangquan Zhang 001; Jie Lu 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Enhancing Vision-Language Models Incorporating TSK Fuzzy System for Domain Adaptation. - Kuo Shi; Jie Lu 001; Zhen Fang 001; Guangquan Zhang 001 (FUZZ, 2024)

How Does Unlabeled Data Provably Help Out-of-Distribution Detection? - Xuefeng Du; Zhen Fang 001; Ilias Diakonikolas; Yixuan Li 001 (ICLR, 2024)

Negative Label Guided OOD Detection with Pretrained Vision-Language Models. - Xue Jiang; Feng Liu 003; Zhen Fang 001; Hong Chen 004; Tongliang Liu; Feng Zheng; Bo Han 003 (ICLR, 2024)

Out-of-Distribution Detection with Negative Prompts. - Jun Nie; Yonggang Zhang 003; Zhen Fang 001; Tongliang Liu; Bo Han 003; Xinmei Tian 001 (ICLR, 2024)

ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection. - Bo Peng; Yadan Luo; Yonggang Zhang 003; Yixuan Li 001; Zhen Fang 001 (ICLR, 2024)

NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation. - Pengfei Zheng; Yonggang Zhang 003; Zhen Fang 001; Tongliang Liu; Defu Lian; Bo Han 003 (ICLR, 2024)

Knowledge Distillation with Auxiliary Variable. - Bo Peng; Zhen Fang 001; Guangquan Zhang 001; Jie Lu 001 (ICML, 2024)

CLIP-Enhanced Unsupervised Domain Adaptation with Consistency Regularization. - Kuo Shi; Jie Lu 001; Zhen Fang 001; Guangquan Zhang 001 (IJCNN, 2024)

Prompt-Based Memory Bank for Continual Test-Time Domain Adaptation in Vision-Language Models. - Ran Wang 016; Hua Zuo; Zhen Fang 001; Jie Lu 001 (IJCNN, 2024)

Towards Robustness Prompt Tuning with Fully Test-Time Adaptation for CLIP's Zero-Shot Generalization. - Ran Wang 016; Hua Zuo; Zhen Fang 001; Jie Lu 001 (ACM Multimedia, 2024)

Spatio-temporal Heterogeneous Federated Learning for Time Series Classification with Multi-view Orthogonal Training. - Chenrui Wu 002; Haishuai Wang; Xiang Zhang 012; Zhen Fang 001; Jiajun Bu (ACM Multimedia, 2024)

Learning to Shape In-distribution Feature Space for Out-of-distribution Detection. - Yonggang Zhang 003; Jie Lu 001; Bo Peng; Zhen Fang 001; Yiu-ming Cheung (NeurIPS, 2024)

A Neighbor-Searching Discrepancy-based Drift Detection Scheme for Learning Evolving Data. - Feng Gu; Jie Lu 001; Zhen Fang 001; Kun Wang 050; Guangquan Zhang 001 (CoRR, 2024)

Exclusive Style Removal for Cross Domain Novel Class Discovery. - Yicheng Wang; Feng Liu 003; Junmin Liu; Zhen Fang 001; Kai Sun 007 (CoRR, 2024)

On the Learnability of Out-of-distribution Detection. - Zhen Fang 001; Yixuan Li 001; Feng Liu 003; Bo Han 003; Jie Lu 001 (J. Mach. Learn. Res., 2024)

Source-Free Unsupervised Domain Adaptation: Current research and future directions. - Ningyuan Zhang; Jie Lu 001; Keqiuyin Li; Zhen Fang 001; Guangquan Zhang 001 (Neurocomputing, 2024)

Multiclass Classification With Fuzzy-Feature Observations: Theory and Algorithms. - Guangzhi Ma; Jie Lu 001; Feng Liu 003; Zhen Fang 001; Guangquan Zhang 001 (IEEE Trans. Cybern., 2024)

Where and How to Transfer: Knowledge Aggregation-Induced Transferability Perception for Unsupervised Domain Adaptation. - Jiahua Dong 001; Yang Cong; Gan Sun; Zhen Fang 001; Zhengming Ding (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

An Extremely Simple Algorithm for Source Domain Reconstruction. - Zhen Fang 001; Jie Lu 001; Guangquan Zhang 001 (IEEE Trans. Cybern., 2024)

Domain Adaptation With Interval-Valued Observations: Theory and Algorithms. - Guangzhi Ma; Jie Lu 001; Feng Liu 003; Zhen Fang 001; Guangquan Zhang 001 (IEEE Trans. Fuzzy Syst., 2024)

Unsupervised Domain Adaptation Enhanced by Fuzzy Prompt Learning. - Kuo Shi; Jie Lu 001; Zhen Fang 001; Guangquan Zhang 001 (IEEE Trans. Fuzzy Syst., 2024)

Characterizing Submanifold Region for Out-of-Distribution Detection: (Extended Abstract). - Xuhui Li; Zhen Fang 001; Yonggang Zhang 003; Ning Ma; Jiajun Bu; Bo Han 003; Haishuai Wang (ICDE, 2025)

Deep Kernel Relative Test for Machine-generated Text Detection. - Yiliao Song; Zhenqiao Yuan; Shuhai Zhang; Zhen Fang 001; Jun Yu; Feng Liu 003 (ICLR, 2025)

Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer. - Ningyuan Zhang; Jie Lu 001; Keqiuyin Li; Zhen Fang 001; Guangquan Zhang 001 (ICLR, 2025)

Distributional Prototype Learning for Out-of-distribution Detection. - Bo Peng; Jie Lu 001; Yonggang Zhang 003; Guangquan Zhang 001; Zhen Fang 001 (KDD (1), 2025)

MetaGeno: a chromosome-wise multi-task genomic framework for ischaemic stroke risk prediction. - Yue Yang; Kairui Guo; Yonggang Zhang 003; Zhen Fang 001; Hua Lin; Mark Grosser; Deon Venter; Weihai Lu; Mengjia Wu; Dennis Cordato; Guangquan Zhang 001; Jie Lu 001 (Briefings Bioinform., 2025)

Out-of-distribution detection with non-semantic exploration. - Zhen Fang 001; Jie Lu 001; Guangquan Zhang 001 (Inf. Sci., 2025)

SENA: Leveraging set-level consistency adversarial learning for robust pre-trained language model adaptation. - Jianqi Gao 001; Jian Cao 001; Hang Yu 006; Yonggang Zhang 003; Zhen Fang 001 (Knowl. Based Syst., 2025)

Characterizing Submanifold Region for Out-of-Distribution Detection. - Xuhui Li; Zhen Fang 001; Yonggang Zhang 003; Ning Ma; Jiajun Bu; Bo Han 003; Haishuai Wang (IEEE Trans. Knowl. Data Eng., 2025)

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach. - Changdae Oh; Zhen Fang 001; Shawn Im; Xuefeng Du; Yixuan Li 001 (CoRR, 2025)

Provable Ordering and Continuity in Vision-Language Pretraining for Generalizable Embodied Agents. - Zhizhen Zhang; Lei Zhu 002; Zhen Fang 001; Zi Huang; Yadan Luo (CoRR, 2025)

Out-of-Distribution Detection with Virtual Outlier Smoothing. - Jun Nie; Yadan Luo; Shanshan Ye; Yonggang Zhang 003; Xinmei Tian 001; Zhen Fang 001 (Int. J. Comput. Vis., 2025)

Integrated Image-Text Augmentation for Few-Shot Learning in Vision-Language Models. - Ran Wang 016; Hua Zuo; Zhen Fang 001; Jie Lu 001 (ACM Trans. Intell. Syst. Technol., 2025)

Learning Robust Spectral Dynamics for Temporal Domain Generalization. - En Yu; Jie Lu 001; Xiaoyu Yang; Guangquan Zhang 001; Zhen Fang 001 (CoRR, 2025)

Multiview Classification Through Learning From Interval-Valued Data. - Guangzhi Ma; Jie Lu 001; Zhen Fang 001; Feng Liu 003; Guangquan Zhang 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

MiraGe: Multimodal Discriminative Representation Learning for Generalizable AI-Generated Image Detection. - Kuo Shi; Jie Lu 001; Shanshan Ye; Guangquan Zhang 001; Zhen Fang 001 (CoRR, 2025)