Modeling the Uncertainty with Maximum Discrepant Students for Semi-supervised 2D Pose Estimation. - Jiaqi Wu 013; Junbiao Pang; Qingming Huang (CoRR, 2023)

Generating Unbiased Pseudo-labels via a Theoretically Guaranteed Chebyshev Constraint to Unify Semi-supervised Classification and Regression. - Jiaqi Wu 013; Junbiao Pang; Qingming Huang (CoRR, 2023)

Ensemble of Distinct Students for SSL 2D Pose Estimation. - Jiaqi Wu 013; Junbiao Pang; Qingming Huang (CVIPPR, 2024)

Feature-based Perturbation Makes a Better Ensemble Learning for SSL Classification. - Jiaqi Wu 013; Junbiao Pang; Qingming Huang (CVIPPR, 2024)

Push Quantization-Aware Training Toward Full Precision Performances via Consistency Regularization. - Junbiao Pang; Tianyang Cai; Baochang Zhang 001; Jiaqi Wu 013; Ye Tao (CoRR, 2024)

A Channel-ensemble Approach: Unbiased and Low-variance Pseudo-labels is Critical for Semi-supervised Classification. - Jiaqi Wu 013; Junbiao Pang; Baochang Zhang 001; Qingming Huang (CoRR, 2024)

Modeling Multi-Granularity Context Information Flow for Pavement Crack Detection. - Junbiao Pang; Baocheng Xiong; Jiaqi Wu 013 (CoRR, 2024)

Decorrelating structure via adapters makes ensemble learning practical for Semi-supervised Learning. - Jiaqi Wu 013; Junbiao Pang; Qingming Huang (Eng. Appl. Artif. Intell., 2025)

Uncertainty-aware Long-tailed Weights Model the Utility of Pseudo-labels for Semi-supervised Learning. - Jiaqi Wu 013; Junbiao Pang; Qingming Huang (CoRR, 2025)

Modeling Multi-Granularity Context Information Flow for Pavement Crack Detection. - Junbiao Pang; Baocheng Xiong; Jiaqi Wu 013; Qingming Huang (IEEE Trans. Intell. Transp. Syst., 2025)

Few Shot Semi-Supervised Learning for Abnormal Stop Detection from Sparse GPS Trajectories. - Muhammad Ayub Sabir; Junbiao Pang; Jiaqi Wu 013; Fatima Ashraf (CoRR, 2025)