Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2104.06643
Cited By
Generative Causal Explanations for Graph Neural Networks
14 April 2021
Wanyu Lin
Hao Lan
Baochun Li
CML
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Generative Causal Explanations for Graph Neural Networks"
42 / 42 papers shown
Title
Causal invariant geographic network representations with feature and structural distribution shifts
Yuhan Wang
Silu He
Qinyao Luo
Hongyuan Yuan
Ling Zhao
Jiawei Zhu
Haifeng Li
OOD
64
0
0
25 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
76
2
0
14 Feb 2025
Graph Neural Backdoor: Fundamentals, Methodologies, Applications, and Future Directions
Xiao Yang
Gaolei Li
Jianhua Li
AAML
AI4CE
51
1
0
08 Jan 2025
On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approach
Ruichu Cai
Yuxuan Zhu
Xuexin Chen
Yuan Fang
Min-man Wu
Jie Qiao
Zhifeng Hao
54
7
0
31 Dec 2024
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs
Bowen Liu
Haoyang Li
Shuning Wang
Shuo Nie
Shanghang Zhang
OODD
CML
76
0
0
29 Oct 2024
Causality-inspired Latent Feature Augmentation for Single Domain Generalization
Jian Xu
Chaojie Ji
Yankai Cao
Ye Li
Ruxin Wang
OOD
29
0
0
10 Jun 2024
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation
Zhaoning Yu
Hongyang Gao
47
3
0
21 May 2024
Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks
Jiahua Rao
Jiancong Xie
Hanjing Lin
Shuangjia Zheng
Zhen Wang
Yuedong Yang
23
0
0
07 Feb 2024
Coca: Improving and Explaining Graph Neural Network-Based Vulnerability Detection Systems
Sicong Cao
Xiaobing Sun
Xiaoxue Wu
David Lo
Lili Bo
Bin Li
Wei Liu
AAML
32
12
0
26 Jan 2024
Refining Latent Homophilic Structures over Heterophilic Graphs for Robust Graph Convolution Networks
Chenyang Qiu
Gu Nan
Tianyu Xiong
Wendi Deng
Di Wang
Zhiyang Teng
Lijuan Sun
Qimei Cui
Xiaofeng Tao
22
5
0
27 Dec 2023
Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network
Tong Li
Jiale Deng
Yanyan Shen
Luyu Qiu
Hu Yongxiang
Caleb Chen Cao
25
5
0
23 Dec 2023
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
Wenzhao Jiang
Hao Liu
Hui Xiong
CML
AI4CE
49
2
0
19 Dec 2023
Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies
Jonas Teufel
Luca Torresi
Pascal Friederich
FAtt
34
1
0
25 May 2023
Robust Ante-hoc Graph Explainer using Bilevel Optimization
Kha-Dinh Luong
Mert Kosan
A. Silva
Ambuj K. Singh
36
6
0
25 May 2023
Unstructured and structured data: Can we have the best of both worlds with large language models?
W. Tan
21
1
0
25 Apr 2023
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability
Indro Spinelli
Michele Guerra
F. Bianchi
Simone Scardapane
36
0
0
14 Apr 2023
Decision Support System for Chronic Diseases Based on Drug-Drug Interactions
Tian Bian
Yuli Jiang
Jia Li
Tingyang Xu
Yu Rong
Yi Su
Timothy S. H. Kwok
Helen Meng
Hongtao Cheng
27
3
0
04 Mar 2023
ExplainableFold: Understanding AlphaFold Prediction with Explainable AI
Juntao Tan
Yongfeng Zhang
28
6
0
27 Jan 2023
CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis
Kaizhong Zheng
Shujian Yu
Badong Chen
CML
42
32
0
04 Jan 2023
GANExplainer: GAN-based Graph Neural Networks Explainer
Yiqiao Li
Jianlong Zhou
Boyuan Zheng
Fang Chen
LLMAG
40
4
0
30 Dec 2022
L2XGNN: Learning to Explain Graph Neural Networks
G. Serra
Mathias Niepert
33
7
0
28 Sep 2022
OCTAL: Graph Representation Learning for LTL Model Checking
Prasita Mukherjee
Haoteng Yin
Susheel Suresh
Tiark Rompf
27
4
0
24 Jul 2022
BusyBot: Learning to Interact, Reason, and Plan in a BusyBoard Environment
Zeyi Liu
Zhenjia Xu
Shuran Song
35
2
0
17 Jul 2022
Features Based Adaptive Augmentation for Graph Contrastive Learning
Adnan Ali
Jinlong Li
OOD
24
7
0
05 Jul 2022
Towards Faithful and Consistent Explanations for Graph Neural Networks
Tianxiang Zhao
Dongsheng Luo
Xiang Zhang
Suhang Wang
FAtt
65
18
0
27 May 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
45
25
0
20 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
Causal Transportability for Visual Recognition
Chengzhi Mao
K. Xia
James Wang
Hongya Wang
Junfeng Yang
Elias Bareinboim
Carl Vondrick
CML
OOD
BDL
30
35
0
26 Apr 2022
OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks
Wanyu Lin
Hao Lan
Hao Wang
Baochun Li
BDL
CML
38
50
0
29 Mar 2022
Task-Agnostic Graph Explanations
Yaochen Xie
S. Katariya
Xianfeng Tang
E-Wen Huang
Nikhil S. Rao
Karthik Subbian
Shuiwang Ji
46
25
0
16 Feb 2022
MotifExplainer: a Motif-based Graph Neural Network Explainer
Zhaoning Yu
Hongyang Gao
39
15
0
01 Feb 2022
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism
Siqi Miao
Miaoyuan Liu
Pan Li
18
197
0
31 Jan 2022
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games
Shichang Zhang
Yozen Liu
Neil Shah
Yizhou Sun
FAtt
33
45
0
28 Jan 2022
Debiased Graph Neural Networks with Agnostic Label Selection Bias
Shaohua Fan
Xiao Wang
Chuan Shi
Kun Kuang
Nian Liu
Bai Wang
AI4CE
44
38
0
19 Jan 2022
Causal Attention for Interpretable and Generalizable Graph Classification
Yongduo Sui
Xiang Wang
Jiancan Wu
Min Lin
Xiangnan He
Tat-Seng Chua
CML
OOD
17
153
0
30 Dec 2021
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
Shaohua Fan
Xiao Wang
Chuan Shi
Peng Cui
Bai Wang
CML
OOD
OODD
AI4CE
59
81
0
20 Nov 2021
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
Zhiqian Chen
Fanglan Chen
Lei Zhang
Taoran Ji
Kaiqun Fu
Liang Zhao
Feng Chen
Lingfei Wu
Charu C. Aggarwal
Chang-Tien Lu
46
18
0
21 Jul 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods
Chirag Agarwal
Marinka Zitnik
Himabindu Lakkaraju
27
51
0
16 Jun 2021
Learning from Counterfactual Links for Link Prediction
Tong Zhao
Gang Liu
Daheng Wang
Wenhao Yu
Meng Jiang
CML
OOD
28
93
0
03 Jun 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
28
20
0
07 Dec 2020
Higher-Order Explanations of Graph Neural Networks via Relevant Walks
Thomas Schnake
Oliver Eberle
Jonas Lederer
Shinichi Nakajima
Kristof T. Schütt
Klaus-Robert Muller
G. Montavon
34
215
0
05 Jun 2020
1