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Inspecting adversarial examples using the Fisher information

Inspecting adversarial examples using the Fisher information

12 September 2019
Jörg Martin
Clemens Elster
    AAML
ArXiv (abs)PDFHTML

Papers citing "Inspecting adversarial examples using the Fisher information"

6 / 6 papers shown
Title
Cartan moving frames and the data manifolds
Cartan moving frames and the data manifoldsInformation Geometry (IG), 2024
Eliot Tron
Rita Fioresi
Nicolas Couellan
Stéphane Puechmorel
134
1
0
18 Sep 2024
Adversarial robustness of VAEs through the lens of local geometry
Adversarial robustness of VAEs through the lens of local geometryInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Asif Khan
Amos Storkey
AAMLDRL
252
5
0
08 Aug 2022
On the Interpretability of Regularisation for Neural Networks Through
  Model Gradient Similarity
On the Interpretability of Regularisation for Neural Networks Through Model Gradient SimilarityNeural Information Processing Systems (NeurIPS), 2022
Vincent Szolnoky
Viktor Andersson
Balázs Kulcsár
Rebecka Jörnsten
133
6
0
25 May 2022
Resilient Machine Learning for Networked Cyber Physical Systems: A
  Survey for Machine Learning Security to Securing Machine Learning for CPS
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPSIEEE Communications Surveys and Tutorials (COMST), 2021
Felix O. Olowononi
D. Rawat
Chunmei Liu
234
158
0
14 Feb 2021
Attention-Guided Black-box Adversarial Attacks with Large-Scale
  Multiobjective Evolutionary Optimization
Attention-Guided Black-box Adversarial Attacks with Large-Scale Multiobjective Evolutionary OptimizationInternational Journal of Intelligent Systems (IJIS), 2021
Jie Wang
Z. Yin
Jing Jiang
Yang Du
AAML
260
10
0
19 Jan 2021
Detecting unusual input to neural networks
Detecting unusual input to neural networks
Jörg Martin
Clemens Elster
AAML
113
7
0
15 Jun 2020
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