| 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 | 3192 | 2018 |
| Dino: Detr with improved denoising anchor boxes for end-to-end object detection H Zhang, F Li, S Liu, L Zhang, H Su, J Zhu, LM Ni, HY Shum arXiv preprint arXiv:2203.03605, 2022 | 1184 | 2022 |
| Grounding dino: Marrying dino with grounded pre-training for open-set object detection S Liu, Z Zeng, T Ren, F Li, H Zhang, J Yang, C Li, J Yang, H Su, J Zhu, ... arXiv preprint arXiv:2303.05499, 2023 | 1095 | 2023 |
| Spatio-temporal backpropagation for training high-performance spiking neural networks Y Wu, L Deng, G Li, J Zhu, L Shi Frontiers in neuroscience 12, 323875, 2018 | 1065 | 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 | 1022 | 2018 |
| 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 | 941 | 2019 |
| DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps C Lu, Y Zhou, F Bao, J Chen, C Li, J Zhu NeurIPS (arXiv preprint arXiv:2206.00927), 2022 | 905 | 2022 |
| 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 | 866 | 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 | 776 | 2021 |
| 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 | 767 | 2019 |
| Dab-detr: Dynamic anchor boxes are better queries for detr S Liu, F Li, H Zhang, X Yang, X Qi, H Su, J Zhu, L Zhang arXiv preprint arXiv:2201.12329, 2022 | 712 | 2022 |
| 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 | 678 | 2019 |
| Stochastic Training of Graph Convolutional Networks J Chen, J Zhu ICML (arXiv preprint arXiv:1710.10568), 2018 | 615* | 2018 |
| 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 | 604 | 2016 |
| 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 | 564 | 2009 |
| Triple Generative Adversarial Nets C Li, K Xu, J Zhu, B Zhang NIPS (arXiv preprint arXiv:1703.02291), 2017 | 559 | 2017 |
| ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation Z Wang, C Lu, Y Wang, F Bao, C Li, H Su, J Zhu NeurIPS (arXiv preprint arXiv:2305.16213), 2023 | 520 | 2023 |
| Improving adversarial robustness via promoting ensemble diversity T Pang, K Xu, C Du, N Chen, J Zhu ICML (arXiv preprint arXiv:1901.08846), 2019 | 484 | 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 | 465 | 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 | 453 | 2017 |
Hang SuAssociated Professor, Tsinghua UniversityVerified email at mail.tsinghua.edu.cn
