Survival-Oriented Reinforcement Learning Model: An Effcient and Robust Deep Reinforcement Learning Algorithm for Autonomous Driving Problem. - Changkun Ye; Huimin Ma 001; Xiaoqin Zhang; Kai Zhang; Shaodi You (ICIG (2), 2017)

Efficient Gaussian Process Model on Class-Imbalanced Datasets for Generalized Zero-Shot Learning. - Changkun Ye; Nick Barnes; Lars Petersson; Russell Tsuchida (ICPR, 2022)

Model Calibration in Dense Classification with Adaptive Label Perturbation. - Jiawei Liu 005; Changkun Ye; Shan Wang 010; Ruikai Cui; Jing Zhang 052; Kaihao Zhang; Nick Barnes (ICCV, 2023)

Latent-based Diffusion Model for Long-tailed Recognition. - Pengxiao Han; Changkun Ye; Jieming Zhou; Jing Zhang; Jie Hong; Xuesong Li 001 (CVPR Workshops, 2024)

Self-Calibrating Vicinal Risk Minimisation for Model Calibration. - Jiawei Liu; Changkun Ye; Ruikai Cui; Nick Barnes (CVPR, 2024)

Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach. - Changkun Ye; Russell Tsuchida; Lars Petersson; Nick Barnes (WACV, 2024)

Latent-based Diffusion Model for Long-tailed Recognition. - Pengxiao Han; Changkun Ye; Jieming Zhou; Jing Zhang; Jie Hong; Xuesong Li (CoRR, 2024)

Open Set Label Shift with Test Time Out-of-Distribution Reference. - Changkun Ye; Russell Tsuchida; Lars Petersson; Nick Barnes (CVPR, 2025)

Enhancing Features in Long-tailed Data Using Large Vision Model. - Pengxiao Han; Changkun Ye; Jinguang Tong; Cuicui Jiang; Jie Hong; Li Fang; Xuesong Li (CoRR, 2025)