Learning to Generate Noise for Multi-Attack Robustness

22 June 2020

Papers citing "Learning to Generate Noise for Multi-Attack Robustness"

8 / 8 papers shown

Title
Towards Universal Certified Robustness with Multi-Norm Training Enyi Jiang Gagandeep Singh Gagandeep Singh AAML 60 1 0 03 Oct 2024
PureEBM: Universal Poison Purification via Mid-Run Dynamics of Energy-Based Models Omead Brandon Pooladzandi Jeffrey Q. Jiang Sunay Bhat Gregory Pottie AAML 31 0 0 28 May 2024
RAMP: Boosting Adversarial Robustness Against Multiple $l_p$ Perturbations Enyi Jiang Gagandeep Singh AAML 30 1 0 09 Feb 2024
Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks Tianwei Liu Yu Yang Baharan Mirzasoleiman AAML 30 27 0 14 Aug 2022
Efficient Test-Time Model Adaptation without Forgetting Shuaicheng Niu Jiaxiang Wu Yifan Zhang Yaofo Chen S. Zheng P. Zhao Mingkui Tan OOD VLM TTA 28 308 0 06 Apr 2022
Mind the box: $l_1$ -APGD for sparse adversarial attacks on image classifiers Francesco Croce Matthias Hein AAML 47 54 0 01 Mar 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 359 11,684 0 09 Mar 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016