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Transcending Adversarial Perturbations: Manifold-Aided Adversarial
  Examples with Legitimate Semantics

Transcending Adversarial Perturbations: Manifold-Aided Adversarial Examples with Legitimate Semantics

5 February 2024
Shuai Li
Xiaoyu Jiang
Xiaoguang Ma
    AAML
ArXivPDFHTML

Papers citing "Transcending Adversarial Perturbations: Manifold-Aided Adversarial Examples with Legitimate Semantics"

4 / 4 papers shown
Title
Diffusion Models for Adversarial Purification
Diffusion Models for Adversarial Purification
Weili Nie
Brandon Guo
Yujia Huang
Chaowei Xiao
Arash Vahdat
Anima Anandkumar
WIGM
200
418
0
16 May 2022
Robust Feature-Level Adversaries are Interpretability Tools
Robust Feature-Level Adversaries are Interpretability Tools
Stephen Casper
Max Nadeau
Dylan Hadfield-Menell
Gabriel Kreiman
AAML
42
27
0
07 Oct 2021
Constructing Unrestricted Adversarial Examples with Generative Models
Constructing Unrestricted Adversarial Examples with Generative Models
Yang Song
Rui Shu
Nate Kushman
Stefano Ermon
GAN
AAML
185
302
0
21 May 2018
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
261
3,109
0
04 Nov 2016
1