Improving Adversarial Robustness of DEQs with Explicit Regulations Along
the Neural Dynamics

Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural Dynamics

2 June 2023

Peng Li

Yang Liu

Papers citing "Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural Dynamics"

5 / 5 papers shown

Title
Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing Weizhi Gao Zhichao Hou Han Xu Xiaorui Liu AAML 26 0 0 01 Nov 2024
TorchDEQ: A Library for Deep Equilibrium Models Zhengyang Geng J. Zico Kolter VLM 44 12 0 28 Oct 2023
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses Francesco Croce Sven Gowal T. Brunner Evan Shelhamer Matthias Hein A. Cemgil TTA AAML 170 67 0 28 Feb 2022
On Training Implicit Models Zhengyang Geng Xinyu Zhang Shaojie Bai Yisen Wang Zhouchen Lin 56 69 0 09 Nov 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 217 674 0 19 Oct 2020