| KDnet-RUL: A knowledge distillation framework to compress deep neural networks for machine remaining useful life prediction Q Xu, Z Chen, K Wu, C Wang, M Wu, X Li IEEE Transactions on Industrial Electronics 69 (2), 2022-2032, 2021 | 59 | 2021 |
| Contrastive adversarial knowledge distillation for deep model compression in time-series regression tasks Q Xu, Z Chen, M Ragab, C Wang, M Wu, X Li Neurocomputing 485, 242-251, 2022 | 26 | 2022 |
| A hybrid ensemble deep learning approach for early prediction of battery remaining useful life Q Xu, M Wu, E Khoo, Z Chen, X Li IEEE/CAA Journal of Automatica Sinica 10 (1), 177-187, 2023 | 15 | 2023 |
| Automatic detection of retinopathy with optical coherence tomography images via a semi-supervised deep learning method Y Luo, Q Xu, R Jin, M Wu, L Liu Biomedical Optics Express 12 (5), 2684-2702, 2021 | 11 | 2021 |
| Cross‐domain retinopathy classification with optical coherence tomography images via a novel deep domain adaptation method Y Luo, Q Xu, Y Hou, L Liu, M Wu Journal of Biophotonics 14 (8), e202100096, 2021 | 3 | 2021 |
| Reinforced Knowledge Distillation for Time Series Regression Q Xu, K Wu, M Wu, K Mao, X Li, Z Chen IEEE Transactions on Artificial Intelligence, 2023 | 1 | 2023 |
| Contrastive Distillation with Regularized Knowledge for Deep Model Compression on Sensor-based Human Activity Recognition Q Xu, M Wu, X Li, K Mao, Z Chen IEEE Transactions on Industrial Cyber-Physical Systems, 2023 | 1 | 2023 |
| Distilling Universal and Joint Knowledge for Cross-Domain Model Compression on Time Series Data Q Xu, M Wu, X Li, K Mao, Z Chen arXiv preprint arXiv:2307.03347, 2023 | 1 | 2023 |
| Improve Knowledge Distillation via Label Revision and Data Selection W Lan, Y Cheung, Q Xu, B Liu, Z Hu, M Li, Z Chen arXiv preprint arXiv:2404.03693, 2024 | | 2024 |
