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Yinpeng Dong
Yinpeng Dong
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Title
Cited by
Cited by
Year
Boosting adversarial attacks with momentum
Y Dong, F Liao, T Pang, H Su, J Zhu, X Hu, J Li
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
12962018
Defense against adversarial attacks using high-level representation guided denoiser
F Liao, M Liang, Y Dong, T Pang, X Hu, J Zhu
Proceedings of the IEEE conference on computer vision and pattern …, 2018
5362018
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
2732019
Technical report on the cleverhans v2. 1.0 adversarial examples library
N Papernot, F Faghri, N Carlini, I Goodfellow, R Feinman, A Kurakin, ...
arXiv preprint arXiv:1610.00768, 2016
2232016
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
2102018
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
1972019
Towards robust detection of adversarial examples
T Pang, C Du, Y Dong, J Zhu
NeurIPS 2018, 2017
148*2017
Improving black-box adversarial attacks with a transfer-based prior
S Cheng, Y Dong, T Pang, H Su, J Zhu
NeurIPS 2019, 2019
1242019
Benchmarking adversarial robustness on image classification
Y Dong, QA Fu, X Yang, T Pang, H Su, Z Xiao, J Zhu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
1122020
Improving interpretability of deep neural networks with semantic information
Y Dong, H Su, J Zhu, B Zhang
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
972017
Towards interpretable deep neural networks by leveraging adversarial examples
Y Dong, H Su, J Zhu, F Bao
AAAI 2019 Workshop on Network Interpretability for Deep Learning, 2017
912017
Bag of tricks for adversarial training
T Pang, X Yang, Y Dong, H Su, J Zhu
ICLR 2021, 2020
842020
Rethinking softmax cross-entropy loss for adversarial robustness
T Pang, K Xu, Y Dong, C Du, N Chen, J Zhu
ICLR 2020, 2019
822019
Forecast the Plausible Paths in Crowd Scenes.
H Su, J Zhu, Y Dong, B Zhang
IJCAI 1, 2, 2017
642017
Learning visual knowledge memory networks for visual question answering
Z Su, C Zhu, Y Dong, D Cai, Y Chen, J Li
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
562018
Batch virtual adversarial training for graph convolutional networks
Z Deng, Y Dong, J Zhu
ICML 2019 Workshop on Learning and Reasoning with Graph-Structured …, 2019
522019
Crowd Scene Understanding with Coherent Recurrent Neural Networks.
H Su, Y Dong, J Zhu, H Ling, B Zhang
IJCAI 1, 2, 2016
502016
Boosting adversarial training with hypersphere embedding
T Pang, X Yang, Y Dong, K Xu, J Zhu, H Su
NeurIPS 2020, 2020
492020
Learning accurate low-bit deep neural networks with stochastic quantization
Y Dong, R Ni, J Li, Y Chen, J Zhu, H Su
British Machine Vision Conference, 2017
412017
Adversarial Distributional Training for Robust Deep Learning
Y Dong, Z Deng, T Pang, H Su, J Zhu
Advances in Neural Information Processing Systems, 2020
382020
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Articles 1–20