Improving Model Robustness with Latent Distribution Locally and Globally

8 July 2021

Papers citing "Improving Model Robustness with Latent Distribution Locally and Globally"

10 / 10 papers shown

Title
AutoAdvExBench: Benchmarking autonomous exploitation of adversarial example defenses Nicholas Carlini Javier Rando Edoardo Debenedetti Milad Nasr F. Tramèr AAML ELM 39 1 0 03 Mar 2025
Topology-Preserving Adversarial Training Xiaoyue Mi Fan Tang Yepeng Weng Danding Wang Juan Cao Sheng Tang Peng Li Yang Liu 49 1 0 29 Nov 2023
Cross-Entropy Loss Functions: Theoretical Analysis and Applications Anqi Mao M. Mohri Yutao Zhong AAML 21 273 0 14 Apr 2023
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 47 71 0 26 Mar 2022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses Francesco Croce Sven Gowal T. Brunner Evan Shelhamer Matthias Hein A. Cemgil TTA AAML 173 67 0 28 Feb 2022
Push Stricter to Decide Better: A Class-Conditional Feature Adaptive Framework for Improving Adversarial Robustness Jia-Li Yin Lehui Xie Wanqing Zhu Ximeng Liu Bo-Hao Chen TTA AAML 13 3 0 01 Dec 2021
Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications Wenjie Ruan Xinping Yi Xiaowei Huang AAML OOD 18 17 0 24 Aug 2021
Domain Invariant Adversarial Learning Matan Levi Idan Attias A. Kontorovich AAML OOD 30 11 0 01 Apr 2021
Robust Generative Adversarial Network Shufei Zhang Zhuang Qian Kaizhu Huang Jimin Xiao Yuan He 14 8 0 28 Apr 2020
Conditional Image Synthesis With Auxiliary Classifier GANs Augustus Odena C. Olah Jonathon Shlens GAN 224 3,190 0 30 Oct 2016