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2107.04086
Cited By
Robust Counterfactual Explanations on Graph Neural Networks
8 July 2021
Mohit Bajaj
Lingyang Chu
Zihui Xue
J. Pei
Lanjun Wang
P. C. Lam
Yong Zhang
OOD
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Papers citing
"Robust Counterfactual Explanations on Graph Neural Networks"
20 / 20 papers shown
Title
COMRECGC: Global Graph Counterfactual Explainer through Common Recourse
Gregoire Fournier
Sourav Medya
BDL
44
0
0
11 May 2025
Interpretability of Graph Neural Networks to Assess Effects of Global Change Drivers on Ecological Networks
Emré Anakok
Pierre Barbillon
Colin Fontaine
Elisa Thébault
47
0
0
19 Mar 2025
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
73
2
0
14 Feb 2025
F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI
Xu Zheng
Farhad Shirani
Zhuomin Chen
Chaohao Lin
Wei Cheng
Wenbo Guo
Dongsheng Luo
AAML
28
0
0
03 Oct 2024
Explainable Graph Neural Networks Under Fire
Zhong Li
Simon Geisler
Yuhang Wang
Stephan Günnemann
M. Leeuwen
AAML
43
0
0
10 Jun 2024
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges
Wei Ju
Siyu Yi
Yifan Wang
Zhiping Xiao
Zhengyan Mao
...
Senzhang Wang
Xinwang Liu
Xiao Luo
Philip S. Yu
Ming Zhang
AI4CE
36
35
0
07 Mar 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
Wenzhao Jiang
Hao Liu
Hui Xiong
CML
AI4CE
44
2
0
19 Dec 2023
Robust Stochastic Graph Generator for Counterfactual Explanations
Mario Alfonso Prado-Romero
Bardh Prenkaj
Giovanni Stilo
CML
8
3
0
18 Dec 2023
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion
Jialin Chen
Shirley Wu
Abhijit Gupta
Rex Ying
DiffM
39
4
0
30 Oct 2023
Robust Ante-hoc Graph Explainer using Bilevel Optimization
Kha-Dinh Luong
Mert Kosan
A. Silva
Ambuj K. Singh
34
6
0
25 May 2023
GANExplainer: GAN-based Graph Neural Networks Explainer
Yiqiao Li
Jianlong Zhou
Boyuan Zheng
Fang Chen
LLMAG
32
4
0
30 Dec 2022
Global Counterfactual Explainer for Graph Neural Networks
Mert Kosan
Zexi Huang
Sourav Medya
Sayan Ranu
Ambuj K. Singh
26
47
0
21 Oct 2022
CLEAR: Generative Counterfactual Explanations on Graphs
Jing Ma
Ruocheng Guo
Saumitra Mishra
Aidong Zhang
Jundong Li
CML
OOD
30
53
0
16 Oct 2022
A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics
Yiqiao Li
Jianlong Zhou
Sunny Verma
Fang Chen
XAI
31
39
0
26 Jul 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Bingzhe Wu
Jintang Li
Junchi Yu
Yatao Bian
Hengtong Zhang
...
Guangyu Sun
Peng Cui
Zibin Zheng
Zhe Liu
P. Zhao
OOD
30
25
0
20 May 2022
Cardinality-Minimal Explanations for Monotonic Neural Networks
Ouns El Harzli
Bernardo Cuenca Grau
Ian Horrocks
FAtt
35
5
0
19 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
He Zhang
Bang Wu
Xingliang Yuan
Shirui Pan
Hanghang Tong
Jian Pei
45
104
0
16 May 2022
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data
Raphael Mazzine
David Martens
16
33
0
09 Jul 2021
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks
Thorben Funke
Megha Khosla
Mandeep Rathee
Avishek Anand
FAtt
23
38
0
18 May 2021
NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised Classification
Rui Yang
Wenrui Dai
Chenglin Li
Junni Zou
H. Xiong
25
20
0
07 Dec 2020
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