| A unified approach to interpreting and boosting adversarial transferability X Wang, J Ren, S Lin, X Zhu, Y Wang, Q Zhang International Conference on Learning Representations, 2021 | 81 | 2021 |
| Interpretable CNNs for object classification Q Zhang, X Wang, YN Wu, H Zhou, SC Zhu IEEE transactions on pattern analysis and machine intelligence 43 (10), 3416 …, 2020 | 50 | 2020 |
| Towards a unified game-theoretic view of adversarial perturbations and robustness J Ren, D Zhang, Y Wang, L Chen, Z Zhou, Y Chen, X Cheng, X Wang, ... Advances in Neural Information Processing Systems 34, 3797-3810, 2021 | 34* | 2021 |
| Extraction of an explanatory graph to interpret a cnn Q Zhang, X Wang, R Cao, YN Wu, F Shi, SC Zhu IEEE transactions on pattern analysis and machine intelligence 43 (11), 3863 …, 2020 | 31 | 2020 |
| Interpreting attributions and interactions of adversarial attacks X Wang, S Lin, H Zhang, Y Zhu, Q Zhang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 12 | 2021 |
| Rapid detection and recognition of whole brain activity in a freely behaving Caenorhabditis elegans Y Wu, S Wu, X Wang, C Lang, Q Zhang, Q Wen, T Xu PLoS computational biology 18 (10), e1010594, 2022 | 8 | 2022 |
| Proving common mechanisms shared by twelve methods of boosting adversarial transferability Q Zhang, X Wang, J Ren, X Cheng, S Lin, Y Wang, X Zhu arXiv preprint arXiv:2207.11694, 2022 | 8 | 2022 |
| A hypothesis for the aesthetic appreciation in neural networks X Cheng, X Wang, H Xue, Z Liang, Q Zhang arXiv preprint arXiv:2108.02646, 2021 | 7 | 2021 |
Quanshi ZhangShanghai Jiao Tong University在 sjtu.edu.cn 的电子邮件经过验证
