Improving Robustness using Generated Data

18 October 2021

Sven Gowal

Sylvestre-Alvise Rebuffi

Papers citing "Improving Robustness using Generated Data"

50 / 200 papers shown

Title
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper M. Keuper AAML 33 24 0 12 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Ziquan Liu Antoni B. Chan AAML 27 5 0 11 Oct 2022
Revisiting adapters with adversarial training Sylvestre-Alvise Rebuffi Francesco Croce Sven Gowal AAML 36 16 0 10 Oct 2022
Learning Robust Kernel Ensembles with Kernel Average Pooling P. Bashivan Adam Ibrahim Amirozhan Dehghani Yifei Ren OOD 16 5 0 30 Sep 2022
Towards Lightweight Black-Box Attacks against Deep Neural Networks Chenghao Sun Yonggang Zhang Chaoqun Wan Qizhou Wang Ya Li Tongliang Liu Bo Han Xinmei Tian AAML MLAU 16 5 0 29 Sep 2022
Inducing Data Amplification Using Auxiliary Datasets in Adversarial Training Saehyung Lee Hyungyu Lee AAML 29 2 0 27 Sep 2022
A Light Recipe to Train Robust Vision Transformers Edoardo Debenedetti Vikash Sehwag Prateek Mittal ViT 29 68 0 15 Sep 2022
Part-Based Models Improve Adversarial Robustness Chawin Sitawarin Kornrapat Pongmala Yizheng Chen Nicholas Carlini David A. Wagner 44 11 0 15 Sep 2022
Bag of Tricks for FGSM Adversarial Training Zichao Li Li Liu Zeyu Wang Yuyin Zhou Cihang Xie AAML 25 6 0 06 Sep 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications Ling Yang Zhilong Zhang Yingxia Shao Shenda Hong Runsheng Xu Yue Zhao Wentao Zhang Bin Cui Ming-Hsuan Yang DiffM MedIm 224 1,304 0 02 Sep 2022
Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning Zhiyuan He Yijun Yang Pin-Yu Chen Qiang Xu Tsung-Yi Ho AAML 19 6 0 31 Aug 2022
Constraining Representations Yields Models That Know What They Don't Know João Monteiro Pau Rodríguez López Pierre-Andre Noel I. Laradji David Vazquez AAML 36 0 0 30 Aug 2022
An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Networks Raz Lapid Zvika Haramaty Moshe Sipper AAML MLAU 15 12 0 17 Aug 2022
Two Heads are Better than One: Robust Learning Meets Multi-branch Models Dong Huang Qi Bu Yuhao Qing Haowen Pi Sen Wang Heming Cui OOD AAML 27 0 0 17 Aug 2022
Unifying Gradients to Improve Real-world Robustness for Deep Networks Yingwen Wu Sizhe Chen Kun Fang X. Huang AAML 24 3 0 12 Aug 2022
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training Sekitoshi Kanai Shinýa Yamaguchi Masanori Yamada Hiroshi Takahashi Kentaro Ohno Yasutoshi Ida AAML 14 7 0 21 Jul 2022
Adversarially-Aware Robust Object Detector Ziyi Dong Pengxu Wei Liang Lin AAML ObjD 14 27 0 13 Jul 2022
Increasing Confidence in Adversarial Robustness Evaluations Roland S. Zimmermann Wieland Brendel Florian Tramèr Nicholas Carlini AAML 36 16 0 28 Jun 2022
Diversified Adversarial Attacks based on Conjugate Gradient Method Keiichiro Yamamura Haruki Sato Nariaki Tateiwa Nozomi Hata Toru Mitsutake Issa Oe Hiroki Ishikura Katsuki Fujisawa AAML 14 14 0 20 Jun 2022
Towards Alternative Techniques for Improving Adversarial Robustness: Analysis of Adversarial Training at a Spectrum of Perturbations Kaustubh Sridhar Souradeep Dutta Ramneet Kaur James Weimer O. Sokolsky Insup Lee AAML 29 4 0 13 Jun 2022
FACM: Intermediate Layer Still Retain Effective Features against Adversarial Examples Xiangyuan Yang Jie Lin Hanlin Zhang Xinyu Yang Peng Zhao AAML 34 0 0 02 Jun 2022
Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction Ruochen Jiao Xiangguo Liu Takami Sato Qi Alfred Chen Qi Zhu AAML 35 20 0 27 May 2022
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks Sizhe Chen Zhehao Huang Qinghua Tao Yingwen Wu Cihang Xie X. Huang AAML 110 28 0 24 May 2022
Squeeze Training for Adversarial Robustness Qizhang Li Yiwen Guo W. Zuo Hao Chen OOD 36 9 0 23 May 2022
Post-breach Recovery: Protection against White-box Adversarial Examples for Leaked DNN Models Shawn Shan Wen-Luan Ding Emily Wenger Haitao Zheng Ben Y. Zhao AAML 31 10 0 21 May 2022
Gradient Concealment: Free Lunch for Defending Adversarial Attacks Sen Pei Jiaxi Sun Xiaopeng Zhang Gaofeng Meng AAML 26 0 0 21 May 2022
Test-time Batch Normalization Tao Yang Shenglong Zhou Yuwang Wang Yan Lu Nanning Zheng OOD 54 9 0 20 May 2022
Diffusion Models for Adversarial Purification Weili Nie Brandon Guo Yujia Huang Chaowei Xiao Arash Vahdat Anima Anandkumar WIGM 212 418 0 16 May 2022
Adversarial Robustness through the Lens of Convolutional Filters Paul Gavrikov J. Keuper 35 15 0 05 Apr 2022
FrequencyLowCut Pooling -- Plug & Play against Catastrophic Overfitting Julia Grabinski Steffen Jung J. Keuper M. Keuper AAML 16 22 0 01 Apr 2022
Generating High Fidelity Data from Low-density Regions using Diffusion Models Vikash Sehwag C. Hazirbas Albert Gordo Firat Ozgenel Cristian Canton Ferrer DiffM 33 66 0 31 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 181 67 0 28 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min-Bin Lin Xiao Yang Junyi Zhu Shuicheng Yan 30 119 0 21 Feb 2022
Fast Adversarial Training with Noise Augmentation: A Unified Perspective on RandStart and GradAlign Axi Niu Kang Zhang Chaoning Zhang Chenshuang Zhang In So Kweon Chang D. Yoo Yanning Zhang AAML 51 6 0 11 Feb 2022
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests Xilie Xu Jingfeng Zhang Feng Liu Masashi Sugiyama Mohan S. Kankanhalli AAML 22 1 0 07 Feb 2022
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks A. Harrington Arturo Deza OOD AAML 27 20 0 02 Feb 2022
Adversarial Machine Learning Threat Analysis and Remediation in Open Radio Access Network (O-RAN) Edan Habler Ron Bitton D. Avraham D. Mimran Eitan Klevansky Oleg Brodt Heiko Lehmann Yuval Elovici A. Shabtai AAML 39 12 0 16 Jan 2022
Improving Robustness with Image Filtering M. Terzi Mattia Carletti Gian Antonio Susto AAML 29 0 0 21 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 20 13 0 14 Dec 2021
Generate, Annotate, and Learn: NLP with Synthetic Text Xuanli He Islam Nassar J. Kiros Gholamreza Haffari Mohammad Norouzi 36 51 0 11 Jun 2021
Provably Robust Detection of Out-of-distribution Data (almost) for free Alexander Meinke Julian Bitterwolf Matthias Hein OODD 25 22 0 08 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 23 9 0 31 May 2021
Adversarial Robustness against Multiple and Single $l_p$ -Threat Models via Quick Fine-Tuning of Robust Classifiers Francesco Croce Matthias Hein OOD AAML 20 18 0 26 May 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 33 268 0 02 Mar 2021
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training Lue Tao Lei Feng Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 28 71 0 09 Feb 2021
Towards Robust Neural Networks via Orthogonal Diversity Kun Fang Qinghua Tao Yingwen Wu Tao Li Jia Cai Feipeng Cai Xiaolin Huang Jie-jin Yang AAML 28 8 0 23 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 231 677 0 19 Oct 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo-wen Li AAML 25 128 0 09 Sep 2020
Stylized Adversarial Defense Muzammal Naseer Salman Khan Munawar Hayat F. Khan Fatih Porikli GAN AAML 20 16 0 29 Jul 2020
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016