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Bounding the Expected Robustness of Graph Neural Networks Subject to
  Node Feature Attacks

Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks

27 April 2024
Yassine Abbahaddou
Sofiane Ennadir
J. Lutzeyer
Michalis Vazirgiannis
Henrik Bostrom
    AAML
    OOD
ArXivPDFHTML

Papers citing "Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks"

5 / 5 papers shown
Title
A Simple and Yet Fairly Effective Defense for Graph Neural Networks
A Simple and Yet Fairly Effective Defense for Graph Neural Networks
Sofiane Ennadir
Yassine Abbahaddou
J. Lutzeyer
Michalis Vazirgiannis
Henrik Bostrom
AAML
24
11
0
21 Feb 2024
Revisiting Robustness in Graph Machine Learning
Revisiting Robustness in Graph Machine Learning
Lukas Gosch
Daniel Sturm
Simon Geisler
Stephan Günnemann
AAML
OOD
61
21
0
01 May 2023
Orthogonal Graph Neural Networks
Orthogonal Graph Neural Networks
Kai Guo
Kaixiong Zhou
Xia Hu
Yu Li
Yi Chang
Xin Wang
41
34
0
23 Sep 2021
Elastic Graph Neural Networks
Elastic Graph Neural Networks
Xiaorui Liu
W. Jin
Yao Ma
Yaxin Li
Hua Liu
Yiqi Wang
Ming Yan
Jiliang Tang
84
106
0
05 Jul 2021
Fast and accurate optimization on the orthogonal manifold without
  retraction
Fast and accurate optimization on the orthogonal manifold without retraction
Pierre Ablin
Gabriel Peyré
40
26
0
15 Feb 2021
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