Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2104.10482
Cited By
v1
v2 (latest)
GraphSVX: Shapley Value Explanations for Graph Neural Networks
18 April 2021
Alexandre Duval
Fragkiskos D. Malliaros
FAtt
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"GraphSVX: Shapley Value Explanations for Graph Neural Networks"
50 / 51 papers shown
QGShap: Quantum Acceleration for Faithful GNN Explanations
Haribandhu Jena
Jyotirmaya Shivottam
Subhankar Mishra
FAtt
282
0
0
01 Dec 2025
ARM-Explainer -- Explaining and improving graph neural network predictions for the maximum clique problem using node features and association rule mining
Bharat Sharman
Elkafi Hassini
161
0
0
28 Nov 2025
GnnXemplar: Exemplars to Explanations -- Natural Language Rules for Global GNN Interpretability
Burouj Armgaan
Eshan Jain
Harsh Pandey
Mahesh Chandran
Jignesh M. Patel
LLMAG
324
0
0
22 Sep 2025
Z-REx: Human-Interpretable GNN Explanations for Real Estate Recommendations
Kunal Mukherjee
Zachary Harrison
Saeid Balaneshin
272
1
0
01 Jul 2025
Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference
Shuichi Nishino
Tomohiro Shiraishi
Teruyuki Katsuoka
Ichiro Takeuchi
281
0
0
22 May 2025
Discovering the Precursors of Traffic Breakdowns Using Spatiotemporal Graph Attribution Networks
Zhaobin Mo
Xiangyi Liao
Dominik A. Karbowski
Yanbing Wang
117
0
0
23 Apr 2025
Interpretability of Graph Neural Networks to Assess Effects of Global Change Drivers on Ecological Networks
Emré Anakok
Pierre Barbillon
Colin Fontaine
Elisa Thébault
394
1
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
557
13
0
14 Feb 2025
Interpretable Load Forecasting via Representation Learning of Geo-distributed Meteorological Factors
Yangze Zhou
Guoxin Lin
Gonghao Zhang
Yi Wang
AI4TS
160
0
0
04 Jan 2025
A Comprehensive Study of Shapley Value in Data Analytics
Proceedings of the VLDB Endowment (PVLDB), 2024
Hong Lin
Shixin Wan
Zhongle Xie
Ke Chen
Meihui Zhang
Lidan Shou
Gang Chen
728
1
0
02 Dec 2024
MBExplainer: Multilevel bandit-based explanations for downstream models with augmented graph embeddings
Ashkan Golgoon
Ryan Franks
Khashayar Filom
Arjun Ravi Kannan
344
0
0
01 Nov 2024
Explanation-Preserving Augmentation for Semi-Supervised Graph Representation Learning
Zhuomin Chen
Jingchao Ni
Hojat Allah Salehi
Xu Zheng
Esteban Schafir
Farhad Shirani
Dongsheng Luo
265
1
0
16 Oct 2024
PAGE: Parametric Generative Explainer for Graph Neural Network
European Conference on Artificial Intelligence (ECAI), 2024
Yang Qiu
Wei Liu
Jun Wang
Ruixuan Li
BDL
303
0
0
26 Aug 2024
Towards Few-shot Self-explaining Graph Neural Networks
Jingyu Peng
Qi Liu
Linan Yue
Zaixi Zhang
Kai Zhang
Yunhao Sha
MILM
186
4
0
14 Aug 2024
Graph Neural Network Causal Explanation via Neural Causal Models
Arman Behnam
Binghui Wang
CML
228
10
0
12 Jul 2024
Kolmogorov-Arnold Graph Neural Networks
Gianluca De Carlo
Andrea Mastropietro
Aris Anagnostopoulos
345
39
0
26 Jun 2024
Generating Human Understandable Explanations for Node Embeddings
Zohair Shafi
Ayan Chatterjee
Tina Eliassi-Rad
211
1
0
11 Jun 2024
LinkLogic: A New Method and Benchmark for Explainable Knowledge Graph Predictions
Niraj Kumar Singh
G. Polleti
Saee Paliwal
Rachel Hodos-Nkhereanye
198
0
0
02 Jun 2024
Explaining Graph Neural Networks via Structure-aware Interaction Index
International Conference on Machine Learning (ICML), 2024
Ngoc H. Bui
Hieu Trung Nguyen
Viet Anh Nguyen
Rex Ying
FAtt
210
11
0
23 May 2024
Comprehensible Artificial Intelligence on Knowledge Graphs: A survey
Journal of Web Semantics (Web Semantics), 2023
Simon Schramm
C. Wehner
Ute Schmid
238
37
0
04 Apr 2024
Game-theoretic Counterfactual Explanation for Graph Neural Networks
Chirag Chhablani
Sarthak Jain
Akshay Channesh
Ian A. Kash
Sourav Medya
333
9
0
08 Feb 2024
PAC Learnability under Explanation-Preserving Graph Perturbations
Xu Zheng
Farhad Shirani
Tianchun Wang
Shouwei Gao
Wenqian Dong
Wei Cheng
Dongsheng Luo
200
0
0
07 Feb 2024
GNNShap: Scalable and Accurate GNN Explanation using Shapley Values
The Web Conference (WWW), 2024
Selahattin Akkas
Ariful Azad
FAtt
298
18
0
09 Jan 2024
Graph AI in Medicine
Ruth Johnson
Michelle M. Li
Ayush Noori
Owen Queen
Marinka Zitnik
352
4
0
20 Oct 2023
RekomGNN: Visualizing, Contextualizing and Evaluating Graph Neural Networks Recommendations
C. Brumar
G. Appleby
Jen Rogers
Teddy Matinde
Lara Thompson
Remco Chang
Anamaria Crisan
HAI
235
1
0
17 Oct 2023
Towards Data-centric Graph Machine Learning: Review and Outlook
Xin Zheng
Yixin Liu
Zhifeng Bao
Meng Fang
Xia Hu
Alan Wee-Chung Liew
Shirui Pan
GNN
AI4CE
250
22
0
20 Sep 2023
Counterfactual Graph Transformer for Traffic Flow Prediction
Yingbin Yang
Kai Du
Xingyuan Dai
Jianwu Fang
AI4TS
298
1
0
01 Aug 2023
On the Interplay of Subset Selection and Informed Graph Neural Networks
Niklas Breustedt
Paolo Climaco
Jochen Garcke
J. Hamaekers
Gitta Kutyniok
D. Lorenz
Rick Oerder
Chirag Varun Shukla
155
0
0
15 Jun 2023
Efficient GNN Explanation via Learning Removal-based Attribution
ACM Transactions on Knowledge Discovery from Data (TKDD), 2023
Yao Rong
Guanchu Wang
Qizhang Feng
Ninghao Liu
Zirui Liu
Enkelejda Kasneci
Helen Zhou
219
9
0
09 Jun 2023
A Survey on Explainability of Graph Neural Networks
IEEE Data Engineering Bulletin (IEEE Data Eng. Bull.), 2023
Jaykumar Kakkad
Jaspal Jannu
Kartik Sharma
Charu C. Aggarwal
Sourav Medya
213
54
0
02 Jun 2023
A Comparative Study of Methods for Estimating Conditional Shapley Values and When to Use Them
Data mining and knowledge discovery (DMKD), 2023
Lars Henry Berge Olsen
I. Glad
Martin Jullum
K. Aas
FAtt
194
25
0
16 May 2023
Explanations of Black-Box Models based on Directional Feature Interactions
International Conference on Learning Representations (ICLR), 2023
A. Masoomi
Davin Hill
Zhonghui Xu
C. Hersh
E. Silverman
P. Castaldi
Stratis Ioannidis
Jennifer Dy
FAtt
289
25
0
16 Apr 2023
DAG Matters! GFlowNets Enhanced Explainer For Graph Neural Networks
International Conference on Learning Representations (ICLR), 2023
Wenqian Li
Yinchuan Li
Zhigang Li
Jianye Hao
Yan Pang
221
34
0
04 Mar 2023
Structural Explanations for Graph Neural Networks using HSIC
Ayato Toyokuni
Makoto Yamada
190
3
0
04 Feb 2023
On the Limit of Explaining Black-box Temporal Graph Neural Networks
Minh Nhat Vu
My T. Thai
165
3
0
02 Dec 2022
L2XGNN: Learning to Explain Graph Neural Networks
Machine-mediated learning (ML), 2022
G. Serra
Mathias Niepert
226
9
0
28 Sep 2022
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
International Conference on Learning Representations (ICLR), 2022
Xiaoqi Wang
Hang Shen
253
53
0
15 Sep 2022
PGX: A Multi-level GNN Explanation Framework Based on Separate Knowledge Distillation Processes
Tien-Cuong Bui
Wen-Syan Li
S. Cha
194
2
0
05 Aug 2022
GREASE: Generate Factual and Counterfactual Explanations for GNN-based Recommendations
Ziheng Chen
Fabrizio Silvestri
Jia Wang
Zelong Li
Zhenhua Huang
H. Ahn
Gabriele Tolomei
CML
186
37
0
04 Aug 2022
ScoreCAM GNN: une explication optimale des réseaux profonds sur graphes
Adrien Raison
Pascal Bourdon
David Helbert
FAtt
GNN
120
0
0
26 Jul 2022
FlowX: Towards Explainable Graph Neural Networks via Message Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Shurui Gui
Hao Yuan
Jie Wang
Qicheng Lao
Kang Li
Shuiwang Ji
316
25
0
26 Jun 2022
EiX-GNN : Concept-level eigencentrality explainer for graph neural networks
Adrien Raison
Pascal Bourdon
David Helbert
192
2
0
07 Jun 2022
Explaining Preferences with Shapley Values
Neural Information Processing Systems (NeurIPS), 2022
Robert Hu
Siu Lun Chau
Jaime Ferrando Huertas
Dino Sejdinovic
TDI
FAtt
192
7
0
26 May 2022
DT+GNN: A Fully Explainable Graph Neural Network using Decision Trees
Peter Müller
Lukas Faber
Karolis Martinkus
Roger Wattenhofer
170
8
0
26 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
Yanfeng Guo
P. Zhao
OOD
311
29
0
20 May 2022
The Shapley Value in Machine Learning
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Benedek Rozemberczki
Lauren Watson
Péter Bayer
Hao-Tsung Yang
Oliver Kiss
Sebastian Nilsson
Rik Sarkar
TDI
FAtt
330
294
0
11 Feb 2022
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games
Neural Information Processing Systems (NeurIPS), 2022
Shichang Zhang
Yozen Liu
Neil Shah
Luke Huan
FAtt
363
64
0
28 Jan 2022
Reliable Graph Neural Network Explanations Through Adversarial Training
Donald Loveland
Shusen Liu
B. Kailkhura
A. Hiszpanski
Yong Han
AAML
120
5
0
25 Jun 2021
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021
Thorben Funke
Megha Khosla
Mandeep Rathee
Avishek Anand
FAtt
262
55
0
18 May 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Ana Lucic
Maartje ter Hoeve
Gabriele Tolomei
Maarten de Rijke
Fabrizio Silvestri
566
174
0
05 Feb 2021
1
2
Next
Page 1 of 2
