| Discovering and explaining the representation bottleneck of dnns H Deng, Q Ren, H Zhang, Q Zhang arXiv preprint arXiv:2111.06236, 2021 | 52 | 2021 |
| Interpreting representation quality of DNNs for 3D point cloud processing W Shen, Q Ren, D Liu, Q Zhang Advances in Neural Information Processing Systems 34, 8857-8870, 2021 | 16 | 2021 |
| Where We Have Arrived in Proving the Emergence of Sparse Symbolic Concepts in AI Models Q Ren, J Gao, W Shen, Q Zhang arXiv preprint arXiv:2305.01939, 2023 | 7 | 2023 |
| Bayesian neural networks tend to ignore complex and sensitive concepts Q Ren, H Deng, Y Chen, S Lou, Q Zhang arXiv preprint arXiv:2302.13095, 2023 | 5 | 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 Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 3 | 2023 |
| Rotation-Equivariant Neural Networks for Privacy Protection H Zhang, Y Chen, H Ma, X Cheng, Q Ren, L Xiang, J Shi, Q Zhang arXiv preprint arXiv:2006.13016, 2020 | 3 | 2020 |
| Rotation-Equivariant Quaternion Neural Networks for 3D Point Cloud Processing W Shen, Z Wei, Q Ren, B Zhang, S Huang, J Fan, Q Zhang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 1 | 2024 |
| 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 | 1 | 2023 |
Quanshi ZhangShanghai Jiao Tong University在 sjtu.edu.cn 的电子邮件经过验证
