Do Wider Neural Networks Really Help Adversarial Robustness?

3 October 2020

Quanquan Gu

Papers citing "Do Wider Neural Networks Really Help Adversarial Robustness?"

26 / 26 papers shown

Title
TAROT: Towards Essentially Domain-Invariant Robustness with Theoretical Justification Dongyoon Yang Jihu Lee Yongdai Kim 29 0 0 10 May 2025
Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models Yoojin Jung Byung Cheol Song AAML VLM MQ 38 0 0 07 Apr 2025
The Curious Case of Arbitrariness in Machine Learning Prakhar Ganesh Afaf Taik G. Farnadi 59 2 0 28 Jan 2025
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods A. Ma Yangchen Pan Amir-massoud Farahmand AAML 25 5 0 13 Aug 2023
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks Sihui Dai Saeed Mahloujifar Chong Xiang Vikash Sehwag Pin-Yu Chen Prateek Mittal AAML OOD 29 7 0 21 Feb 2023
MedViT: A Robust Vision Transformer for Generalized Medical Image Classification Omid Nejati Manzari Hamid Ahmadabadi Hossein Kashiani S. B. Shokouhi Ahmad Ayatollahi ViT MedIm 34 177 0 19 Feb 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels Simone Bombari Shayan Kiyani Marco Mondelli AAML 36 10 0 03 Feb 2023
An Adversarial Robustness Perspective on the Topology of Neural Networks Morgane Goibert Thomas Ricatte Elvis Dohmatob AAML 11 2 0 04 Nov 2022
A Light Recipe to Train Robust Vision Transformers Edoardo Debenedetti Vikash Sehwag Prateek Mittal ViT 32 68 0 15 Sep 2022
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization) Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos V. Cevher 39 19 0 15 Sep 2022
Bag of Tricks for FGSM Adversarial Training Zichao Li Li Liu Zeyu Wang Yuyin Zhou Cihang Xie AAML 33 6 0 06 Sep 2022
ADBench: Anomaly Detection Benchmark Songqiao Han Xiyang Hu Hailiang Huang Mingqi Jiang Yue Zhao OOD 41 296 0 19 Jun 2022
Wavelet Regularization Benefits Adversarial Training Jun Yan Huilin Yin Xiaoyang Deng Zi-qin Zhao Wancheng Ge Hao Zhang Gerhard Rigoll AAML 19 2 0 08 Jun 2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling Lei Cheng Feng Yin Sergios Theodoridis S. Chatzis Tsung-Hui Chang 68 75 0 28 May 2022
Squeeze Training for Adversarial Robustness Qizhang Li Yiwen Guo W. Zuo Hao Chen OOD 39 9 0 23 May 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes Elvis Dohmatob A. Bietti AAML 32 13 0 22 Mar 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
Benign Overfitting in Adversarially Robust Linear Classification Jinghui Chen Yuan Cao Quanquan Gu AAML SILM 34 10 0 31 Dec 2021
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 194 345 0 15 Dec 2021
Stochastic Local Winner-Takes-All Networks Enable Profound Adversarial Robustness Konstantinos P. Panousis S. Chatzis Sergios Theodoridis BDL AAML 60 11 0 05 Dec 2021
Improving Robustness using Generated Data Sven Gowal Sylvestre-Alvise Rebuffi Olivia Wiles Florian Stimberg D. A. Calian Timothy A. Mann 36 293 0 18 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 46 100 0 07 Oct 2021
Interpolation can hurt robust generalization even when there is no noise Konstantin Donhauser Alexandru cTifrea Michael Aerni Reinhard Heckel Fanny Yang 34 14 0 05 Aug 2021
Learning distinct features helps, provably Firas Laakom Jenni Raitoharju Alexandros Iosifidis Moncef Gabbouj MLT 36 6 0 10 Jun 2021
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 65 230 0 25 May 2018
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 273 3,110 0 04 Nov 2016