Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization Q Wei, H Sun, X Lu, Y Yin ECCV 2022, 2022 | 45 | 2022 |
Learning to rectify for robust learning with noisy labels H Sun, C Guo, Q Wei, Z Han, Y Yin Pattern Recognition 124, 108467, 2022 | 33 | 2022 |
Fine-grained classification with noisy labels Q Wei, L Feng, H Sun, R Wang, C Guo, Y Yin CVPR 2023, 2023 | 24 | 2023 |
Converting Artificial Neural Networks to Ultra-Low-Latency Spiking Neural Networks for Action Recognition H You, X Zhong, W Liu, Q Wei, W Huang, Z Yu, T Huang IEEE Transactions on Cognitive and Developmental Systems 16 (4), 1533-1545, 2024 | 4 | 2024 |
Learning sample-aware threshold for semi-supervised learning Q Wei, L Feng, H Sun, R Wang, R He, Y Yin Machine Learning 113, 5423–5445, 2024 | 1 | 2024 |
Improving Generalization in Meta-Learning via Meta-Gradient Augmentation R Wang, H Sun, Q Wei, X Nie, Y Ma, Y Yin arXiv preprint arXiv:2306.08460, 2023 | 1 | 2023 |
Variational Rectification Inference for Learning with Noisy Labels H Sun, Q Wei, L Feng, Y Hu, F Liu, H Fan, Y Yin International Journal of Computer Vision, 1-20, 2024 | | 2024 |
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data J Zhang, Q Wei, F Liu, L Feng ICML 2024, 2024 | | 2024 |
BDetCLIP: Multimodal Prompting Contrastive Test-Time Backdoor Detection Y Niu, S He, Q Wei, F Liu, L Feng arXiv preprint arXiv:2405.15269, 2024 | | 2024 |
Debiased Sample Selection for Combating Noisy Labels Q Wei, L Feng, H Wang, B An arXiv preprint arXiv:2401.13360, 2024 | | 2024 |