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ORCIDKun Fang 0004
Person information
- affiliation: Shanghai Jiao Tong University, Institute of Image Processing and Pattern Recognition, China
Other persons with the same name
- Kun Fang — disambiguation page
- Kun Fang 0001
![[0000-0002-9232-6846]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-9232-6846")
— University of Cambridge, Department of Applied Mathematics and Theoretical Physics, UK (and 2 more) - Kun Fang 0002 — Beihang University, Research Institute for Frontier Science, Beijing, China (and 1 more)
- Kun Fang 0003 — Delft University of Technnology, Faculty of Electrical Engineering, Mathematics and Computer Science, EEMCS, Netherlands (and 2 more)
- Kun Fang 0005 — Nvidia, Santa Clara, CA, USA (and 1 more)
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Journal Articles
- 2024
[j8]Kun Fang, Qinghua Tao, Xiaolin Huang, Jie Yang:
Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective. Int. J. Comput. Vis. 132(12): 6107-6126 (2024)- [j7]Jiawen Li, Kun Fang, Xiaolin Huang, Jie Yang:
Boosting certified robustness via an expectation-based similarity regularization. Image Vis. Comput. 151: 105272 (2024) - [j6]Kun Fang, Qinghua Tao, Yingwen Wu, Tao Li, Jia Cai, Feipeng Cai, Xiaolin Huang, Jie Yang:
Towards robust neural networks via orthogonal diversity. Pattern Recognit. 149: 110281 (2024) - [j5]Tao Li, Qinghua Tao, Weihao Yan, Yingwen Wu, Zehao Lei, Kun Fang, Mingzhen He, Xiaolin Huang:
Revisiting Random Weight Perturbation for Efficiently Improving Generalization. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [j4]Jiawen Li, Kun Fang, Xiaolin Huang, Jie Yang:
Improving adversarial robustness through a curriculum-guided reliable distillation. Comput. Secur. 133: 103411 (2023) - [j3]Kun Fang, Fanghui Liu, Xiaolin Huang, Jie Yang:
End-to-end kernel learning via generative random Fourier features. Pattern Recognit. 134: 109057 (2023) - [j2]Tianshu Chu, Kun Fang, Jie Yang, Xiaolin Huang:
Improving the adversarial robustness of quantized neural networks via exploiting the feature diversity. Pattern Recognit. Lett. 176: 117-122 (2023) - [j1]Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang:
Unifying Gradients to Improve Real-World Robustness for Deep Networks. ACM Trans. Intell. Syst. Technol. 14(6): 101:1-101:16 (2023)
Conference and Workshop Papers
- 2022
- [c7]Tao Li, Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang:
Subspace Adversarial Training. CVPR 2022: 13399-13408 - [c6]Yiming Sun, Zhiqiang Xie, Kun Fang, Enmei Tu, Jie Yang:
Learnable Relation with Triplet Formulation for Semi-supervised Medical Image Classification. DMBD (1) 2022: 383-393 - [c5]Jianwei Cai, Kun Fang, Weihao Yu, Jie Yang, Yu Qiao:
Local-Global Semantic Fusion Single-shot Classification Method. ICONIP (1) 2022: 128-139 - [c4]Pengjin Wei, Guohang Yan, Yikang Li, Kun Fang, Xinyu Cai, Jie Yang, Wei Liu:
CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene. IROS 2022: 12857-12863 - 2021
- [c3]Kun Fang, Jie Yang:
Robust Deep Facial Attribute Prediction against Adversarial Attacks. ICCAI 2021: 202-207 - [c2]Yizhang Huang, Kun Fang, Xiaolin Huang, Jie Yang:
ADVMIX: Data Augmentation for Accurate Scene Text Spotting. ICIP 2021: 954-958 - [c1]Qin Luo, Kun Fang, Jie Yang, Xiaolin Huang:
Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels. IJCNN 2021: 1-8
Informal and Other Publications
- 2024
- [i12]Kun Fang, Qinghua Tao, Kexin Lv, Mingzhen He, Xiaolin Huang, Jie Yang:
Kernel PCA for Out-of-Distribution Detection. CoRR abs/2402.02949 (2024) - [i11]Tao Li, Qinghua Tao, Weihao Yan, Zehao Lei, Yingwen Wu, Kun Fang, Mingzhen He, Xiaolin Huang:
Revisiting Random Weight Perturbation for Efficiently Improving Generalization. CoRR abs/2404.00357 (2024) - [i10]Kun Fang, Qinghua Tao, Zuopeng Yang, Xiaolin Huang, Jie Yang:
DDoS: Diffusion Distribution Similarity for Out-of-Distribution Detection. CoRR abs/2409.10094 (2024) - 2023
- [i9]Kun Fang, Qinghua Tao, Xiaolin Huang, Jie Yang:
Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective. CoRR abs/2310.14227 (2023) - 2022
- [i8]Pengjin Wei, Guohang Yan, Yikang Li, Kun Fang, Wei Liu, Xinyu Cai, Jie Yang:
CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene. CoRR abs/2203.03182 (2022) - [i7]Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang:
Unifying Gradients to Improve Real-world Robustness for Deep Networks. CoRR abs/2208.06228 (2022) - [i6]Kun Fang, Qinghua Tao, Yingwen Wu, Tao Li, Xiaolin Huang, Jie Yang:
On Multi-head Ensemble of Smoothed Classifiers for Certified Robustness. CoRR abs/2211.10882 (2022) - [i5]Tao Li, Weihao Yan, Zehao Lei, Yingwen Wu, Kun Fang, Ming Yang, Xiaolin Huang:
Efficient Generalization Improvement Guided by Random Weight Perturbation. CoRR abs/2211.11489 (2022) - 2021
- [i4]Qin Luo, Kun Fang, Jie Yang, Xiaolin Huang:
Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels. CoRR abs/2104.06204 (2021) - [i3]Tao Li, Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang:
Subspace Adversarial Training. CoRR abs/2111.12229 (2021) - 2020
- [i2]Kun Fang, Xiaolin Huang, Fanghui Liu, Jie Yang:
End-to-end Kernel Learning via Generative Random Fourier Features. CoRR abs/2009.04614 (2020) - [i1]Kun Fang, Yingwen Wu, Tao Li, Xiaolin Huang, Jie Yang:
Learn Robust Features via Orthogonal Multi-Path. CoRR abs/2010.12190 (2020)
Coauthor Index
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