Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing

5 June 2020

Papers citing "Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing"

7 / 7 papers shown

Title
Explicit Lipschitz Value Estimation Enhances Policy Robustness Against Perturbation Xulin Chen Ruipeng Liu Garret E. Katz 46 0 0 22 Apr 2024
Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering Rui Zhu Di Tang Siyuan Tang Guanhong Tao Shiqing Ma Xiaofeng Wang Haixu Tang DD 23 3 0 29 Jan 2023
A Quantitative Geometric Approach to Neural-Network Smoothness Zehao Wang Gautam Prakriya S. Jha 43 13 0 02 Mar 2022
Robust Adversarial Classification via Abstaining Abed AlRahman Al Makdah Vaibhav Katewa Fabio Pasqualetti 21 0 0 06 Apr 2021
CLIP: Cheap Lipschitz Training of Neural Networks Leon Bungert René Raab Tim Roith Leo Schwinn Daniel Tenbrinck 32 32 0 23 Mar 2021
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 194 275 0 03 Dec 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 317 5,847 0 08 Jul 2016