Bridging Adversarial Robustness and Gradient Interpretability

Bridging Adversarial Robustness and Gradient Interpretability

27 March 2019

Junghoon Seo

Papers citing "Bridging Adversarial Robustness and Gradient Interpretability"

12 / 12 papers shown

Title
Stability of Explainable Recommendation Sairamvinay Vijayaraghavan Prasant Mohapatra AAML 38 1 0 03 May 2024
Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training Shizhan Gong Qi Dou Farzan Farnia FAtt 42 2 0 06 Apr 2024
Exploring the Connection between Robust and Generative Models Senad Beadini I. Masi AAML 29 1 0 08 Apr 2023
MAGIC: Mask-Guided Image Synthesis by Inverting a Quasi-Robust Classifier Mozhdeh Rouhsedaghat Masoud Monajatipoor C.-C. Jay Kuo I. Masi 34 6 0 23 Sep 2022
B-cos Networks: Alignment is All We Need for Interpretability Moritz D Boehle Mario Fritz Bernt Schiele 42 85 0 20 May 2022
Improving the trustworthiness of image classification models by utilizing bounding-box annotations K. Dharma Chicheng Zhang 32 5 0 15 Aug 2021
Adversarial Training is Not Ready for Robot Learning Mathias Lechner Ramin Hasani Radu Grosu Daniela Rus T. Henzinger AAML 38 34 0 15 Mar 2021
Do Input Gradients Highlight Discriminative Features? Harshay Shah Prateek Jain Praneeth Netrapalli AAML FAtt 21 57 0 25 Feb 2021
ROBY: Evaluating the Robustness of a Deep Model by its Decision Boundaries Jinyin Chen Zhen Wang Haibin Zheng Jun Xiao Zhaoyan Ming AAML 13 5 0 18 Dec 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor A. Madry 37 416 0 16 Jul 2020
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 191 273 0 03 Dec 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016