Kun Fang

According to our database, Kun Fang authored at least 20 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective.

Kun Fang, Qinghua Tao, Xiaolin Huang, Jie Yang

Int. J. Comput. Vis., December, 2024

Revisiting Random Weight Perturbation for Efficiently Improving Generalization.

Tao Li, Qinghua Tao, Weihao Yan, Yingwen Wu, Zehao Lei, Kun Fang, Mingzhen He, Xiaolin Huang

Trans. Mach. Learn. Res., 2024

Towards robust neural networks via orthogonal diversity.

Kun Fang, Qinghua Tao, Yingwen Wu, Tao Li, Jia Cai, Feipeng Cai, Xiaolin Huang, Jie Yang

Pattern Recognit., 2024

Boosting certified robustness via an expectation-based similarity regularization.

Jiawen Li, Kun Fang, Xiaolin Huang, Jie Yang

Image Vis. Comput., 2024

DDoS: Diffusion Distribution Similarity for Out-of-Distribution Detection.

Kun Fang, Qinghua Tao, Zuopeng Yang, Xiaolin Huang, Jie Yang

CoRR, 2024

Kernel PCA for Out-of-Distribution Detection.

Kun Fang, Qinghua Tao, Kexin Lv, Mingzhen He, Xiaolin Huang, Jie Yang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Unifying Gradients to Improve Real-World Robustness for Deep Networks.

Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang

ACM Trans. Intell. Syst. Technol., December, 2023

Improving the adversarial robustness of quantized neural networks via exploiting the feature diversity.

Tianshu Chu, Kun Fang, Jie Yang, Xiaolin Huang

Pattern Recognit. Lett., December, 2023

Improving adversarial robustness through a curriculum-guided reliable distillation.

Jiawen Li, Kun Fang, Xiaolin Huang, Jie Yang

Comput. Secur., October, 2023

End-to-end kernel learning via generative random Fourier features.

Kun Fang, Fanghui Liu, Xiaolin Huang, Jie Yang

Pattern Recognit., 2023

2022

Efficient Generalization Improvement Guided by Random Weight Perturbation.

Tao Li, Weihao Yan, Zehao Lei, Yingwen Wu, Kun Fang, Ming Yang, Xiaolin Huang

CoRR, 2022

On Multi-head Ensemble of Smoothed Classifiers for Certified Robustness.

Kun Fang, Qinghua Tao, Yingwen Wu, Tao Li, Xiaolin Huang, Jie Yang

CoRR, 2022

CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene.

Pengjin Wei, Guohang Yan, Yikang Li, Kun Fang, Xinyu Cai, Jie Yang, Wei Liu

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Local-Global Semantic Fusion Single-shot Classification Method.

Jianwei Cai, Kun Fang, Weihao Yu, Jie Yang, Yu Qiao

Proceedings of the Neural Information Processing - 29th International Conference, 2022

Learnable Relation with Triplet Formulation for Semi-supervised Medical Image Classification.

Yiming Sun, Zhiqiang Xie, Kun Fang, Enmei Tu, Jie Yang

Proceedings of the Data Mining and Big Data - 7th International Conference, 2022

Subspace Adversarial Training.

Tao Li, Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels.

Qin Luo, Kun Fang, Jie Yang, Xiaolin Huang

Proceedings of the International Joint Conference on Neural Networks, 2021

ADVMIX: Data Augmentation for Accurate Scene Text Spotting.

Yizhang Huang, Kun Fang, Xiaolin Huang, Jie Yang

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Robust Deep Facial Attribute Prediction against Adversarial Attacks.

Kun Fang, Jie Yang

Proceedings of the ICCAI '21: 2021 7th International Conference on Computing and Artificial Intelligence, Tianjin China, April 23, 2021

2020

Learn Robust Features via Orthogonal Multi-Path.

Kun Fang, Yingwen Wu, Tao Li, Xiaolin Huang, Jie Yang

CoRR, 2020