GraphSVX: Shapley Value Explanations for Graph Neural Networks

18 April 2021

Papers citing "GraphSVX: Shapley Value Explanations for Graph Neural Networks"

48 / 48 papers shown

Title
Discovering the Precursors of Traffic Breakdowns Using Spatiotemporal Graph Attribution Networks Zhaobin Mo Xiangyi Liao Dominik A. Karbowski Yanbing Wang 14 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 52 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 76 2 0 14 Feb 2025
Interpretable Load Forecasting via Representation Learning of Geo-distributed Meteorological Factors Yangze Zhou Guoxin Lin Gonghao Zhang Yi Wang AI4TS 33 0 0 04 Jan 2025
A Comprehensive Study of Shapley Value in Data Analytics Hong Lin Shixin Wan Zhongle Xie Ke Chen Meihui Zhang Lidan Shou Gang Chen 95 0 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 33 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 31 0 0 16 Oct 2024
Improving the Weighting Strategy in KernelSHAP Lars Henry Berge Olsen Martin Jullum TDI FAtt 77 2 0 07 Oct 2024
PAGE: Parametric Generative Explainer for Graph Neural Network Yang Qiu Wei Liu Jun Wang Ruixuan Li BDL 28 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 24 2 0 14 Aug 2024
Graph Neural Network Causal Explanation via Neural Causal Models Arman Behnam Binghui Wang CML 42 3 0 12 Jul 2024
Kolmogorov-Arnold Graph Neural Networks Gianluca De Carlo Andrea Mastropietro Aris Anagnostopoulos 25 26 0 26 Jun 2024
Generating Human Understandable Explanations for Node Embeddings Zohair Shafi Ayan Chatterjee Tina Eliassi-Rad 37 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 37 0 0 02 Jun 2024
Explaining Graph Neural Networks via Structure-aware Interaction Index Ngoc H. Bui Hieu Trung Nguyen Viet Anh Nguyen Rex Ying FAtt 43 4 0 23 May 2024
Comprehensible Artificial Intelligence on Knowledge Graphs: A survey Simon Schramm C. Wehner Ute Schmid 33 25 0 04 Apr 2024
Game-theoretic Counterfactual Explanation for Graph Neural Networks Chirag Chhablani Sarthak Jain Akshay Channesh Ian A. Kash Sourav Medya 41 6 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 24 0 0 07 Feb 2024
GNNShap: Scalable and Accurate GNN Explanation using Shapley Values Selahattin Akkas Ariful Azad FAtt 40 3 0 09 Jan 2024
Graph AI in Medicine Ruth Johnson Michelle M. Li Ayush Noori Owen Queen Marinka Zitnik 34 3 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 32 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 39 19 0 20 Sep 2023
Counterfactual Graph Transformer for Traffic Flow Prediction Yingbin Yang Kai Du Xingyuan Dai Jianwu Fang AI4TS 35 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 30 0 0 15 Jun 2023
Efficient GNN Explanation via Learning Removal-based Attribution Yao Rong Guanchu Wang Qizhang Feng Ninghao Liu Zirui Liu Enkelejda Kasneci Xia Hu 28 9 0 09 Jun 2023
A Survey on Explainability of Graph Neural Networks Jaykumar Kakkad Jaspal Jannu Kartik Sharma Charu C. Aggarwal Sourav Medya 30 24 0 02 Jun 2023
A Comparative Study of Methods for Estimating Conditional Shapley Values and When to Use Them Lars Henry Berge Olsen I. Glad Martin Jullum K. Aas FAtt 54 12 0 16 May 2023
Explanations of Black-Box Models based on Directional Feature Interactions A. Masoomi Davin Hill Zhonghui Xu C. Hersh E. Silverman P. Castaldi Stratis Ioannidis Jennifer Dy FAtt 37 18 0 16 Apr 2023
DAG Matters! GFlowNets Enhanced Explainer For Graph Neural Networks Wenqian Li Yinchuan Li Zhigang Li Jianye Hao Yan Pang 96 29 0 04 Mar 2023
Structural Explanations for Graph Neural Networks using HSIC Ayato Toyokuni Makoto Yamada 27 1 0 04 Feb 2023
On the Limit of Explaining Black-box Temporal Graph Neural Networks Minh Nhat Vu My T. Thai 24 4 0 02 Dec 2022
L2XGNN: Learning to Explain Graph Neural Networks G. Serra Mathias Niepert 35 7 0 28 Sep 2022
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks Xiaoqi Wang Hang Shen 34 41 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 16 1 0 05 Aug 2022
GREASE: Generate Factual and Counterfactual Explanations for GNN-based Recommendations Ziheng Chen Fabrizio Silvestri Jia Wang Yongfeng Zhang Zhenhua Huang H. Ahn Gabriele Tolomei CML 30 27 0 04 Aug 2022
ScoreCAM GNN: une explication optimale des réseaux profonds sur graphes Adrien Raison Pascal Bourdon David Helbert FAtt GNN 27 0 0 26 Jul 2022
FlowX: Towards Explainable Graph Neural Networks via Message Flows Shurui Gui Hao Yuan Jie Wang Qicheng Lao Kang Li Shuiwang Ji 38 11 0 26 Jun 2022
EiX-GNN : Concept-level eigencentrality explainer for graph neural networks Adrien Raison Pascal Bourdon David Helbert 17 1 0 07 Jun 2022
Explaining Preferences with Shapley Values Robert Hu Siu Lun Chau Jaime Ferrando Huertas Dino Sejdinovic TDI FAtt 18 6 0 26 May 2022
DT+GNN: A Fully Explainable Graph Neural Network using Decision Trees Peter Müller Lukas Faber Karolis Martinkus Roger Wattenhofer 43 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 Zhe Liu P. Zhao OOD 45 25 0 20 May 2022
The Shapley Value in Machine Learning Benedek Rozemberczki Lauren Watson Péter Bayer Hao-Tsung Yang Oliver Kiss Sebastian Nilsson Rik Sarkar TDI FAtt 21 204 0 11 Feb 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
Reliable Graph Neural Network Explanations Through Adversarial Training Donald Loveland Shusen Liu B. Kailkhura A. Hiszpanski Yong Han AAML 17 4 0 25 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
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 120 143 0 05 Feb 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 167 595 0 31 Dec 2020
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks Q. Huang M. Yamada Yuan Tian Dinesh Singh Dawei Yin Yi-Ju Chang FAtt 37 345 0 17 Jan 2020