Obserwuj
Jun Zhu
Tytuł
Cytowane przez
Cytowane przez
Rok
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
24652018
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
8532018
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
7612018
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
6982018
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
6772019
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
5442009
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
5372016
Stochastic Training of Graph Convolutional Networks
J Chen, J Zhu
ICML (arXiv preprint arXiv:1710.10568), 2018
519*2018
Triple Generative Adversarial Nets
C Li, K Xu, J Zhu, B Zhang
NIPS (arXiv preprint arXiv:1703.02291), 2017
5082017
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
5002019
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
4502022
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
4232019
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
4222021
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
3962017
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
3962009
Improving adversarial robustness via promoting ensemble diversity
T Pang, K Xu, C Du, N Chen, J Zhu
ICML (arXiv preprint arXiv:1901.08846), 2019
3932019
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
3692019
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
3532022
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
3182018
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
3142022
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