| Explainability for large language models: A survey H Zhao, H Chen, F Yang, N Liu, H Deng, H Cai, S Wang, D Yin, M Du ACM Transactions on Intelligent Systems and Technology 15 (2), 1-38, 2024 | 418 | 2024 |
| Discovering and explaining the representation bottleneck of dnns H Deng, Q Ren, H Zhang, Q Zhang Proceedings of International Conference on Learning Representations (ICLR), 2022, 2021 | 72 | 2021 |
| Machine learning model to predict recurrent ulcer bleeding in patients with history of idiopathic gastroduodenal ulcer bleeding GLH Wong, AJ Ma, H Deng, JYL Ching, VWS Wong, YK Tse, TCF Yip, ... Alimentary Pharmacology & Therapeutics 49 (7), 912-918, 2019 | 56 | 2019 |
| Unifying fourteen post-hoc attribution methods with taylor interactions H Deng, N Zou, M Du, W Chen, G Feng, Z Yang, Z Li, Q Zhang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 37* | 2024 |
| Invariant subspace learning for time series data based on dynamic time warping distance H Deng, W Chen, Q Shen, AJ Ma, PC Yuen, G Feng Pattern Recognition 102, 107210, 2020 | 30 | 2020 |
| Defining and quantifying the emergence of sparse concepts in dnns J Ren, M Li, Q Chen, H Deng, Q Zhang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 27 | 2023 |
| UA-CRNN: Uncertainty-aware convolutional recurrent neural network for mortality risk prediction Q Tan, AJ Ma, M Ye, B Yang, H Deng, VWS Wong, YK Tse, TCF Yip, ... Proceedings of the 28th ACM international conference on information and …, 2019 | 27 | 2019 |
| A unified Taylor framework for revisiting attribution methods H Deng, N Zou, M Du, W Chen, G Feng, X Hu Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11462 …, 2021 | 18 | 2021 |
| A hybrid residual network and long short-term memory method for peptic ulcer bleeding mortality prediction Q Tan, AJ Ma, H Deng, VWS Wong, YK Tse, TCF Yip, GLH Wong, ... AMIA Annual Symposium Proceedings 2018, 998, 2018 | 16 | 2018 |
| Bayesian neural networks avoid encoding complex and perturbation-sensitive concepts Q Ren, H Deng, Y Chen, S Lou, Q Zhang International Conference on Machine Learning, 28889-28913, 2023 | 14 | 2023 |
| Towards the difficulty for a deep neural network to learn concepts of different complexities D Liu, H Deng, X Cheng, Q Ren, K Wang, Q Zhang Advances in Neural Information Processing Systems 36, 41283-41304, 2023 | 13 | 2023 |
| Explaining generalization power of a dnn using interactive concepts H Zhou, H Zhang, H Deng, D Liu, W Shen, SH Chan, Q Zhang Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 17105 …, 2024 | 12 | 2024 |
| Concept-level explanation for the generalization of a dnn H Zhou, H Zhang, H Deng, D Liu, W Shen, SH Chan, Q Zhang arXiv preprint arXiv:2302.13091, 2023 | 12 | 2023 |
| Towards axiomatic, hierarchical, and symbolic explanation for deep models J Ren, M Li, Q Chen, H Deng, Q Zhang | 11 | 2021 |
| Trap of feature diversity in the learning of mlps D Liu, S Wang, J Ren, K Wang, S Yin, H Deng, Q Zhang arXiv preprint arXiv:2112.00980, 2021 | 7 | 2021 |
| Memory disagreement: A pseudo-labeling measure from training dynamics for semi-supervised graph learning H Pei, Y Xiong, P Wang, J Tao, J Liu, H Deng, J Ma, X Guan Proceedings of the ACM on Web Conference 2024, 434-445, 2024 | 6 | 2024 |
| Hago-net: Hierarchical geometric massage passing for molecular representation learning H Pei, T Chen, A Chen, H Deng, J Tao, P Wang, X Guan Proceedings of the AAAI Conference on Artificial Intelligence 38 (13), 14572 …, 2024 | 6 | 2024 |
| Mutual information preserving back-propagation: Learn to invert for faithful attribution H Deng, N Zou, W Chen, G Feng, M Du, X Hu Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 5 | 2021 |
| Robust shapelets learning: Transform-invariant prototypes H Deng, W Chen, AJ Ma, Q Shen, PC Yuen, G Feng Pattern Recognition and Computer Vision: First Chinese Conference, PRCV 2018 …, 2018 | 5 | 2018 |
| Multi-Track Message Passing: Tackling Oversmoothing and Oversquashing in Graph Learning via Preventing Heterophily Mixing H Pei, Y Li, H Deng, J Hai, P Wang, J Ma, J Tao, Y Xiong, X Guan Forty-first International Conference on Machine Learning, 0 | 5 | |
Quanshi ZhangShanghai Jiao Tong UniversityAdresse e-mail validée de sjtu.edu.cn