| Explicit inductive bias for transfer learning with convolutional networks LI Xuhong, Y Grandvalet, F Davoine International Conference on Machine Learning, 2825-2834, 2018 | 318 | 2018 |
| Interpretable deep learning: Interpretation, interpretability, trustworthiness, and beyond X Li, H Xiong, X Li, X Wu, X Zhang, J Liu, J Bian, D Dou Knowledge and Information Systems 64 (12), 3197-3234, 2022 | 220 | 2022 |
| From distributed machine learning to federated learning: A survey J Liu, J Huang, Y Zhou, X Li, S Ji, H Xiong, D Dou Knowledge and Information Systems 64 (4), 885-917, 2022 | 177 | 2022 |
| Transfer learning in computer vision tasks: Remember where you come from X Li, Y Grandvalet, F Davoine, J Cheng, Y Cui, H Zhang, S Belongie, ... Image and Vision Computing 93, 103853, 2020 | 88 | 2020 |
| A baseline regularization scheme for transfer learning with convolutional neural networks X Li, Y Grandvalet, F Davoine Pattern Recognition 98, 107049, 2020 | 56 | 2020 |
| Cross-task transfer for geotagged audiovisual aerial scene recognition D Hu, X Li, L Mou, P Jin, D Chen, L Jing, X Zhu, D Dou Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 28* | 2020 |
| G-LIME: Statistical learning for local interpretations of deep neural networks using global priors X Li, H Xiong, X Li, X Zhang, J Liu, H Jiang, Z Chen, D Dou Artificial Intelligence 314, 103823, 2023 | 20 | 2023 |
| Explaining information flow inside vision transformers using markov chain T Yuan, X Li, H Xiong, H Cao, D Dou eXplainable AI approaches for debugging and diagnosis., 2021 | 20 | 2021 |
| Muscle: Multi-task self-supervised continual learning to pre-train deep models for x-ray images of multiple body parts W Liao, H Xiong, Q Wang, Y Mo, X Li, Y Liu, Z Chen, S Huang, D Dou International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 16 | 2022 |
| InterpretDL: Explaining Deep Models in PaddlePaddle X Li, H Xiong, X Li, X Wu, Z Chen, D Dou Journal of Machine Learning Research 23 (197), 1-6, 2022 | 10 | 2022 |
| Beyond Intuition: Rethinking Token Attributions inside Transformers J Chen, X Li, L Yu, D Dou, H Xiong Transactions on Machine Learning Research, 2023 | 7 | 2023 |
| Representation transfer by optimal transport X Li, Y Grandvalet, R Flamary, N Courty, D Dou arXiv preprint arXiv:2007.06737, 2020 | 7 | 2020 |
| Cross-model consensus of explanations and beyond for image classification models: An empirical study X Li, H Xiong, S Huang, S Ji, D Dou Machine Learning 112 (5), 1627-1662, 2023 | 6 | 2023 |
| Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models X Li, H Xiong, Y Liu, D Zhou, Z Chen, Y Wang, D Dou Machine Learning 112 (6), 2193-2209, 2023 | 5 | 2023 |
| Practical assessment of generalization performance robustness for deep networks via contrastive examples X Wu, X Li, H Xiong, X Zhang, S Huang, D Dou arXiv preprint arXiv:2106.10653, 2021 | 3 | 2021 |
| Learning from training dynamics: Identifying mislabeled data beyond manually designed features Q Jia, X Li, L Yu, J Bian, P Zhao, S Li, H Xiong, D Dou Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8041-8049, 2023 | 2 | 2023 |
| Feynman: Federated Learning-based Advertising for Ecosystems-Oriented Mobile Apps Recommendation J Bian, J Huang, S Ji, Y Liao, X Li, Q Wang, J Zhou, D Dou, Y Wang, ... IEEE Transactions on Services Computing, 2023 | 2 | 2023 |
| Can we use gradient norm as a measure of generalization error for model selection in practice? H An, H Xiong, X Li, X Li, D Dou, Z Zhu | 2 | 2020 |
| CUPre: Cross-domain Unsupervised Pre-training for Few-Shot Cell Segmentation W Liao, X Li, Q Wang, Y Xu, Z Yin, H Xiong arXiv preprint arXiv:2310.03981, 2023 | 1 | 2023 |
| Rare Codes Count: Mining Inter-code Relations for Long-tail Clinical Text Classification J Chen, X Li, J Xi, L Yu, H Xiong Proceedings of the 5th Clinical Natural Language Processing Workshop, 403-413, 2023 | 1 | 2023 |
Dejing DouBCG X, Baidu Research, University of Oregon, YaleVerified email at cs.uoregon.edu
