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Generating Semantic Adversarial Examples via Feature Manipulation
v1v2 (latest)

Generating Semantic Adversarial Examples via Feature Manipulation

6 January 2020
Shuo Wang
Surya Nepal
Carsten Rudolph
M. Grobler
Shangyu Chen
Tianle Chen
    AAML
ArXiv (abs)PDFHTML

Papers citing "Generating Semantic Adversarial Examples via Feature Manipulation"

6 / 6 papers shown
Title
Diagnostics for Deep Neural Networks with Automated Copy/Paste Attacks
Diagnostics for Deep Neural Networks with Automated Copy/Paste Attacks
Stephen Casper
K. Hariharan
Dylan Hadfield-Menell
AAML
91
11
0
18 Nov 2022
Towards Compositional Adversarial Robustness: Generalizing Adversarial
  Training to Composite Semantic Perturbations
Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations
Lei Hsiung
Yun-Yun Tsai
Pin-Yu Chen
Tsung-Yi Ho
AAML
69
30
0
09 Feb 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
154
28
0
07 Oct 2021
Exposing Previously Undetectable Faults in Deep Neural Networks
Exposing Previously Undetectable Faults in Deep Neural Networks
Isaac Dunn
Hadrien Pouget
Daniel Kroening
T. Melham
AAML
117
29
0
01 Jun 2021
Synthetic Observational Health Data with GANs: from slow adoption to a
  boom in medical research and ultimately digital twins?
Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?
Jeremy Georges-Filteau
Elisa Cirillo
SyDaAI4CE
83
17
0
27 May 2020
Generating Natural Adversarial Examples
Generating Natural Adversarial Examples
Zhengli Zhao
Dheeru Dua
Sameer Singh
GANAAML
194
601
0
31 Oct 2017
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