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Global Counterfactual Explainer for Graph Neural Networks

Global Counterfactual Explainer for Graph Neural Networks

21 October 2022
Mert Kosan
Zexi Huang
Sourav Medya
Sayan Ranu
Ambuj K. Singh
ArXivPDFHTML

Papers citing "Global Counterfactual Explainer for Graph Neural Networks"

25 / 25 papers shown
Title
COMRECGC: Global Graph Counterfactual Explainer through Common Recourse
COMRECGC: Global Graph Counterfactual Explainer through Common Recourse
Gregoire Fournier
Sourav Medya
BDL
29
0
0
11 May 2025
Interpretability of Graph Neural Networks to Assess Effects of Global Change Drivers on Ecological Networks
Interpretability of Graph Neural Networks to Assess Effects of Global Change Drivers on Ecological Networks
Emré Anakok
Pierre Barbillon
Colin Fontaine
Elisa Thébault
45
0
0
19 Mar 2025
TreeX: Generating Global Graphical GNN Explanations via Critical Subtree Extraction
Shengyao Lu
Jiuding Yang
Baochun Li
Di Niu
45
0
0
12 Mar 2025
Recent Advances in Malware Detection: Graph Learning and Explainability
Recent Advances in Malware Detection: Graph Learning and Explainability
Hossein Shokouhinejad
Roozbeh Razavi-Far
Hesamodin Mohammadian
Mahdi Rabbani
Samuel Ansong
Griffin Higgins
Ali Ghorbani
AAML
57
2
0
14 Feb 2025
Graph Counterfactual Explainable AI via Latent Space Traversal
Graph Counterfactual Explainable AI via Latent Space Traversal
Andreas Abildtrup Hansen
Paraskevas Pegios
Anna Calissano
Aasa Feragen
OOD
BDL
AAML
76
0
0
15 Jan 2025
Attribute-Enhanced Similarity Ranking for Sparse Link Prediction
João Mattos
Zexi Huang
Mert Kosan
Ambuj Singh
A. Silva
69
1
0
29 Nov 2024
Global Graph Counterfactual Explanation: A Subgraph Mapping Approach
Global Graph Counterfactual Explanation: A Subgraph Mapping Approach
Yinhan He
Wendy Zheng
Yaochen Zhu
Jing Ma
Saumitra Mishra
Natraj Raman
Ninghao Liu
Jundong Li
16
0
0
25 Oct 2024
GLANCE: Global Actions in a Nutshell for Counterfactual Explainability
GLANCE: Global Actions in a Nutshell for Counterfactual Explainability
Ioannis Emiris
Dimitris Fotakis
G. Giannopoulos
Dimitrios Gunopulos
Loukas Kavouras
...
D. Rontogiannis
Dimitris Sacharidis
Nikolaos Theologitis
Dimitrios Tomaras
Konstantinos Tsopelas
CML
FAtt
16
1
0
29 May 2024
Generating Robust Counterfactual Witnesses for Graph Neural Networks
Generating Robust Counterfactual Witnesses for Graph Neural Networks
Dazhuo Qiu
Mengying Wang
Arijit Khan
Yinghui Wu
19
2
0
30 Apr 2024
Graph Neural Networks for Vulnerability Detection: A Counterfactual
  Explanation
Graph Neural Networks for Vulnerability Detection: A Counterfactual Explanation
Zhaoyang Chu
Yao Wan
Qian Li
Yang Wu
Hongyu Zhang
Yulei Sui
Guandong Xu
Hai Jin
AAML
31
1
0
24 Apr 2024
Fast Inference of Removal-Based Node Influence
Fast Inference of Removal-Based Node Influence
Weikai Li
Zhiping Xiao
Xiao Luo
Yizhou Sun
AAML
23
1
0
13 Mar 2024
Game-theoretic Counterfactual Explanation for Graph Neural Networks
Game-theoretic Counterfactual Explanation for Graph Neural Networks
Chirag Chhablani
Sarthak Jain
Akshay Channesh
Ian A. Kash
Sourav Medya
20
5
0
08 Feb 2024
View-based Explanations for Graph Neural Networks
View-based Explanations for Graph Neural Networks
Tingyang Chen
Dazhuo Qiu
Yinghui Wu
Arijit Khan
Xiangyu Ke
Yunjun Gao
25
9
0
04 Jan 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies
  and An Outlook
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
Wenzhao Jiang
Hao Liu
Hui Xiong
CML
AI4CE
24
2
0
19 Dec 2023
Generating Explanations to Understand and Repair Embedding-based Entity
  Alignment
Generating Explanations to Understand and Repair Embedding-based Entity Alignment
Xiaobin Tian
Zequn Sun
Wei Hu
11
5
0
08 Dec 2023
A Cross Attention Approach to Diagnostic Explainability using Clinical
  Practice Guidelines for Depression
A Cross Attention Approach to Diagnostic Explainability using Clinical Practice Guidelines for Depression
Sumit Dalal
Deepa Tilwani
Kaushik Roy
Manas Gaur
Sarika Jain
V. Shalin
Amit P. Sheth
11
6
0
23 Nov 2023
GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers
  through In-depth Benchmarking
GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking
Mert Kosan
S. Verma
Burouj Armgaan
Khushbu Pahwa
Ambuj K. Singh
Sourav Medya
Sayan Ranu
16
13
0
03 Oct 2023
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data
  Landscapes
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes
Bardh Prenkaj
Mario Villaizán-Vallelado
Tobias Leemann
Gjergji Kasneci
18
2
0
04 Aug 2023
Counterfactual Graph Transformer for Traffic Flow Prediction
Counterfactual Graph Transformer for Traffic Flow Prediction
Yingbin Yang
Kai Du
Xingyuan Dai
Jianwu Fang
AI4TS
22
1
0
01 Aug 2023
A Survey on Explainability of Graph Neural Networks
A Survey on Explainability of Graph Neural Networks
Jaykumar Kakkad
Jaspal Jannu
Kartik Sharma
Charu C. Aggarwal
Sourav Medya
28
23
0
02 Jun 2023
Counterfactual Learning on Graphs: A Survey
Counterfactual Learning on Graphs: A Survey
Zhimeng Guo
Teng Xiao
Zongyu Wu
Charu C. Aggarwal
Hui Liu
Suhang Wang
CML
AI4CE
38
18
0
03 Apr 2023
A Survey on Graph Counterfactual Explanations: Definitions, Methods,
  Evaluation, and Research Challenges
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges
Mario Alfonso Prado-Romero
Bardh Prenkaj
Giovanni Stilo
F. Giannotti
CML
27
30
0
21 Oct 2022
Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural
  Network
Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network
Ravinder Bhattoo
Sayan Ranu
N. M. A. Krishnan
AI4CE
11
17
0
23 Sep 2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy,
  Robustness, Fairness, and Explainability
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Enyan Dai
Tianxiang Zhao
Huaisheng Zhu
Jun Xu
Zhimeng Guo
Hui Liu
Jiliang Tang
Suhang Wang
14
123
0
18 Apr 2022
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
Ana Lucic
Maartje ter Hoeve
Gabriele Tolomei
Maarten de Rijke
Fabrizio Silvestri
107
87
0
05 Feb 2021
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