ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2306.15427
  4. Cited By
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and
  New Directions

Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions

27 June 2023
Lukas Gosch
Simon Geisler
Daniel Sturm
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
    AAML
    GNN
ArXivPDFHTML

Papers citing "Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions"

22 / 22 papers shown
Title
SpecSphere: Dual-Pass Spectral-Spatial Graph Neural Networks with Certified Robustness
SpecSphere: Dual-Pass Spectral-Spatial Graph Neural Networks with Certified Robustness
Yoonhyuk Choi
Chong-Kwon Kim
39
0
0
13 May 2025
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
Gaozheng Pei
Ke Ma
Yingfei Sun
Qianqian Xu
Qingming Huang
DiffM
45
0
0
02 May 2025
Robust Conformal Prediction with a Single Binary Certificate
Soroush H. Zargarbashi
Aleksandar Bojchevski
39
0
0
07 Mar 2025
REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective
Simon Geisler
Tom Wollschlager
M. H. I. Abdalla
Vincent Cohen-Addad
Johannes Gasteiger
Stephan Günnemann
AAML
88
2
0
24 Feb 2025
Personalized Layer Selection for Graph Neural Networks
Kartik Sharma
Vineeth Rakesh Mohan
Yingtong Dou
Srijan Kumar
Mahashweta Das
45
0
0
28 Jan 2025
LLMPirate: LLMs for Black-box Hardware IP Piracy
LLMPirate: LLMs for Black-box Hardware IP Piracy
Vasudev Gohil
Matthew DeLorenzo
Veera Vishwa Achuta Sai Venkat Nallam
Joey See
Jeyavijayan Rajendran
72
3
0
25 Nov 2024
Adversarial Training: A Survey
Adversarial Training: A Survey
Mengnan Zhao
Lihe Zhang
Jingwen Ye
Huchuan Lu
Baocai Yin
Xinchao Wang
AAML
38
1
0
19 Oct 2024
Can Large Language Models Improve the Adversarial Robustness of Graph
  Neural Networks?
Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?
Zhongjian Zhang
Xiao Wang
Huichi Zhou
Yue Yu
Mengmei Zhang
Cheng Yang
Chuan Shi
AAML
48
7
0
16 Aug 2024
Relaxing Graph Transformers for Adversarial Attacks
Relaxing Graph Transformers for Adversarial Attacks
Philipp Foth
Lukas Gosch
Simon Geisler
Leo Schwinn
Stephan Günnemann
AAML
52
1
0
16 Jul 2024
Explainable Graph Neural Networks Under Fire
Explainable Graph Neural Networks Under Fire
Zhong Li
Simon Geisler
Yuhang Wang
Stephan Günnemann
M. Leeuwen
AAML
43
0
0
10 Jun 2024
Graph Adversarial Diffusion Convolution
Graph Adversarial Diffusion Convolution
Songtao Liu
Jinghui Chen
Tianfan Fu
Lu Lin
Marinka Zitnik
Dinghao Wu
DiffM
45
1
0
04 Jun 2024
Collective Certified Robustness against Graph Injection Attacks
Collective Certified Robustness against Graph Injection Attacks
Y. Lai
Bailin Pan
Kaihuang Chen
Yancheng Yuan
Kai Zhou
AAML
45
2
0
03 Mar 2024
AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement
  Learning
AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement Learning
Vasudev Gohil
Satwik Patnaik
D. Kalathil
Jeyavijayan Rajendran
AAML
40
3
0
21 Feb 2024
Attacking Large Language Models with Projected Gradient Descent
Attacking Large Language Models with Projected Gradient Descent
Simon Geisler
Tom Wollschlager
M. H. I. Abdalla
Johannes Gasteiger
Stephan Günnemann
AAML
SILM
49
50
0
14 Feb 2024
Poisoning $\times$ Evasion: Symbiotic Adversarial Robustness for Graph
  Neural Networks
Poisoning ×\times× Evasion: Symbiotic Adversarial Robustness for Graph Neural Networks
Ege Erdogan
Simon Geisler
Stephan Günnemann
AAML
32
0
0
09 Dec 2023
Node-aware Bi-smoothing: Certified Robustness against Graph Injection
  Attacks
Node-aware Bi-smoothing: Certified Robustness against Graph Injection Attacks
Y. Lai
Yulin Zhu
Bailin Pan
Kai Zhou
AAML
46
6
0
07 Dec 2023
On the Adversarial Robustness of Graph Contrastive Learning Methods
On the Adversarial Robustness of Graph Contrastive Learning Methods
Filippo Guerranti
Zinuo Yi
Anna Starovoit
Rafiq Kamel
Simon Geisler
Stephan Günnemann
AAML
41
2
0
29 Nov 2023
Hierarchical Randomized Smoothing
Hierarchical Randomized Smoothing
Yan Scholten
Jan Schuchardt
Aleksandar Bojchevski
Stephan Günnemann
AAML
44
5
0
24 Oct 2023
Expressivity of Graph Neural Networks Through the Lens of Adversarial
  Robustness
Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness
Francesco Campi
Lukas Gosch
Thomas Wollschläger
Yan Scholten
Stephan Günnemann
AAML
62
2
0
16 Aug 2023
Revisiting Robustness in Graph Machine Learning
Revisiting Robustness in Graph Machine Learning
Lukas Gosch
Daniel Sturm
Simon Geisler
Stephan Günnemann
AAML
OOD
74
22
0
01 May 2023
Learning Robust Representation through Graph Adversarial Contrastive
  Learning
Learning Robust Representation through Graph Adversarial Contrastive Learning
Jiayan Guo
Shangyang Li
Yue Zhao
Fei Huang
33
5
0
31 Jan 2022
Contextual Stochastic Block Models
Contextual Stochastic Block Models
Y. Deshpande
Andrea Montanari
Elchanan Mossel
S. Sen
103
154
0
23 Jul 2018
1