| Boosting adversarial attacks with momentum Y Dong, F Liao, T Pang, H Su, J Zhu, X Hu, J Li CVPR (arXiv preprint arXiv:1710.06081, 2017), 2018 | 1898 | 2018 |
| Defense against adversarial attacks using high-level representation guided denoiser F Liao, M Liang, Y Dong, T Pang, J Zhu, X Hu CVPR (arXiv preprint arXiv:1712.02976), 2018 | 708 | 2018 |
| Adversarial Attack on Graph Structured Data H Dai, H Li, T Tian, X Huang, L Wang, J Zhu, L Song ICML (arXiv preprint arXiv:1806.02371), 2018 | 557 | 2018 |
| Spatio-temporal backpropagation for training high-performance spiking neural networks Y Wu, L Deng, G Li, J Zhu, L Shi Frontiers in neuroscience 12, 331, 2018 | 538 | 2018 |
| MedLDA: maximum margin supervised topic models for regression and classification J Zhu, A Ahmed, EP Xing Proceedings of the 26th annual international conference on machine learning …, 2009 | 531 | 2009 |
| Towards Better Analysis of Deep Convolutional Neural Networks M Liu, J Shi, Z Li, C Li, J Zhu, S Liu IEEE Transactions on Visualization & Computer Graphics, 2016 | 481 | 2016 |
| Evading defenses to transferable adversarial examples by translation-invariant attacks Y Dong, T Pang, H Su, J Zhu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 456 | 2019 |
| Triple Generative Adversarial Nets C Li, K Xu, J Zhu, B Zhang NIPS (arXiv preprint arXiv:1703.02291), 2017 | 450 | 2017 |
| Stochastic Training of Graph Convolutional Networks J Chen, J Zhu ICML (arXiv preprint arXiv:1710.10568), 2018 | 424* | 2018 |
| Statsnowball: a statistical approach to extracting entity relationships J Zhu, Z Nie, X Liu, B Zhang, JR Wen Proceedings of the 18th international conference on World wide web, 101-110, 2009 | 380 | 2009 |
| Direct training for spiking neural networks: Faster, larger, better Y Wu, L Deng, G Li, J Zhu, Y Xie, L Shi Proceedings of the AAAI conference on artificial intelligence 33 (01), 1311-1318, 2019 | 339 | 2019 |
| Towards better analysis of machine learning models: A visual analytics perspective S Liu, X Wang, M Liu, J Zhu Visual Informatics 1 (1), 48-56, 2017 | 330 | 2017 |
| Improving adversarial robustness via promoting ensemble diversity T Pang, K Xu, C Du, N Chen, J Zhu ICML (arXiv preprint arXiv:1901.08846), 2019 | 327 | 2019 |
| Efficient decision-based black-box adversarial attacks on face recognition Y Dong, H Su, B Wu, Z Li, W Liu, T Zhang, J Zhu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 284 | 2019 |
| Adversarial attacks and defences competition A Kurakin, I Goodfellow, S Bengio, Y Dong, F Liao, M Liang, T Pang, ... The NIPS'17 Competition: Building Intelligent Systems, 195-231, 2018 | 266 | 2018 |
| Explainable AI: A brief survey on history, research areas, approaches and challenges F Xu, H Uszkoreit, Y Du, W Fan, D Zhao, J Zhu Natural Language Processing and Chinese Computing: 8th CCF International …, 2019 | 246 | 2019 |
| Simultaneous record detection and attribute labeling in web data extraction J Zhu, Z Nie, JR Wen, B Zhang, WY Ma Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006 | 246 | 2006 |
| Smooth Neighbors on Teacher Graphs for Semi-supervised Learning Y Luo, J Zhu, M Li, Y Ren, B Zhang CVPR (arXiv preprint arXiv:1711.00258), 2018 | 244 | 2018 |
| Pre-trained models: Past, present and future X Han, Z Zhang, N Ding, Y Gu, X Liu, Y Huo, J Qiu, Y Yao, A Zhang, ... AI Open 2, 225-250, 2021 | 223 | 2021 |
| Improving Black-box Adversarial Attacks with a Transfer-based Prior S Cheng, Y Dong, T Pang, H Su, J Zhu NeurIPS (arXiv preprint arXiv:1906.06919), 2019 | 197 | 2019 |
Hang SuAssociated Professor, Tsinghua University在 mail.tsinghua.edu.cn 的电子邮件经过验证
