Jun Zhu
Cited by
Cited by
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
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
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
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
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
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
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
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
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
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
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
Stochastic Training of Graph Convolutional Networks
J Chen, J Zhu
ICML (arXiv preprint arXiv:1710.10568), 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
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
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
Triple Generative Adversarial Nets
C Li, K Xu, J Zhu, B Zhang
NIPS (arXiv preprint arXiv:1703.02291), 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
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
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
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
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