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A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges

21 October 2022

Mario Alfonso Prado-Romero

Papers citing "A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges"

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Title
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 Zijian Li 102 7 0 31 Dec 2024
Counterfactual Learning on Graphs: A Survey Zhimeng Guo Teng Xiao Zongyu Wu Charu C. Aggarwal Hui Liu Suhang Wang CML AI4CE 83 19 0 03 Apr 2023
Global Counterfactual Explainer for Graph Neural Networks Mert Kosan Zexi Huang Sourav Medya Sayan Ranu Ambuj K. Singh 76 50 0 21 Oct 2022
CLEAR: Generative Counterfactual Explanations on Graphs Jing Ma Ruocheng Guo Saumitra Mishra Aidong Zhang Jundong Li CML OOD 68 54 0 16 Oct 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 64 27 0 04 Aug 2022
GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks Kenza Amara Rex Ying Zitao Zhang Zhihao Han Yinan Shan U. Brandes S. Schemm Ce Zhang 73 55 0 20 Jun 2022
GRETEL: A unified framework for Graph Counterfactual Explanation Evaluation Mario Alfonso Prado-Romero Giovanni Stilo 32 16 0 07 Jun 2022
Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning Juntao Tan Shijie Geng Zuohui Fu Yingqiang Ge Shuyuan Xu Yunqi Li Yongfeng Zhang 75 111 0 17 Feb 2022
Dimensionality Reduction Meets Message Passing for Graph Node Embeddings Krzysztof Sadowski Michal Szarmach Eddie Mattia 51 6 0 01 Feb 2022
Multi-objective Explanations of GNN Predictions Yifei Liu Chao Chen Yazheng Liu Xi Zhang Sihong Xie 50 13 0 29 Nov 2021
Space-Time-Separable Graph Convolutional Network for Pose Forecasting Theodoros Sofianos Alessio Sampieri Luca Franco Fabio Galasso 3DH 64 144 0 09 Oct 2021
Protein-RNA interaction prediction with deep learning: Structure matters Junkang Wei Siyuan Chen Licheng Zong Xin Gao Yu Li AI4CE 47 58 0 26 Jul 2021
Robust Counterfactual Explanations on Graph Neural Networks Mohit Bajaj Lingyang Chu Zihui Xue J. Pei Lanjun Wang P. C. Lam Yong Zhang OOD 157 99 0 08 Jul 2021
Counterfactual Graphs for Explainable Classification of Brain Networks Carlo Abrate Francesco Bonchi CML 73 56 0 16 Jun 2021
A Comprehensive Survey on Graph Anomaly Detection with Deep Learning Xiaoxiao Ma Hongzhi Zhang Shan Xue Jian Yang Chuan Zhou Quan Z. Sheng Hui Xiong Leman Akoglu GNN AI4TS 82 559 0 14 Jun 2021
MEG: Generating Molecular Counterfactual Explanations for Deep Graph Networks Danilo Numeroso D. Bacciu 69 40 0 16 Apr 2021
Generative Causal Explanations for Graph Neural Networks Wanyu Lin Hao Lan Baochun Li CML 59 177 0 14 Apr 2021
Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation Yi Sun Abel N. Valente Sijia Liu Dakuo Wang AAML 54 7 0 25 Mar 2021
GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks Tianxiang Zhao Xiang Zhang Suhang Wang 108 333 0 16 Mar 2021
On Explainability of Graph Neural Networks via Subgraph Explorations Hao Yuan Haiyang Yu Jie Wang Kang Li Shuiwang Ji FAtt 83 392 0 09 Feb 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 156 145 0 05 Feb 2021
Graph Neural Network for Traffic Forecasting: A Survey Weiwei Jiang Jiayun Luo GNN AI4TS AI4CE 222 877 0 27 Jan 2021
Identity-aware Graph Neural Networks Jiaxuan You Jonathan M. Gomes-Selman Rex Ying J. Leskovec 53 255 0 25 Jan 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 296 497 0 31 Dec 2020
Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks Binghui Wang Jinyuan Jia Neil Zhenqiang Gong GNN 92 18 0 24 Dec 2020
Parameterized Explainer for Graph Neural Network Dongsheng Luo Wei Cheng Dongkuan Xu Wenchao Yu Bo Zong Haifeng Chen Xiang Zhang 140 560 0 09 Nov 2020
Explaining Deep Graph Networks with Molecular Counterfactuals Danilo Numeroso D. Bacciu 46 10 0 09 Nov 2020
Contrastive Graph Neural Network Explanation Lukas Faber A. K. Moghaddam Roger Wattenhofer 77 36 0 26 Oct 2020
Co-embedding of Nodes and Edges with Graph Neural Networks Xiaodong Jiang Ronghang Zhu Pengsheng Ji Sheng Li GNN 50 76 0 25 Oct 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 87 403 0 19 Oct 2020
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks Minh Nhat Vu My T. Thai BDL 75 337 0 12 Oct 2020
Hierarchical Message-Passing Graph Neural Networks Zhiqiang Zhong Cheng-Te Li Jun Pang 82 49 0 08 Sep 2020
A Novel Ensemble Deep Learning Model for Stock Prediction Based on Stock Prices and News Yang Li Yi Pan AIFin 43 159 0 23 Jul 2020
TUDataset: A collection of benchmark datasets for learning with graphs Christopher Morris Nils M. Kriege Franka Bause Kristian Kersting Petra Mutzel Marion Neumann 236 821 0 16 Jul 2020
Counterfactual explanation of machine learning survival models M. Kovalev Lev V. Utkin CML OffRL 103 19 0 26 Jun 2020
Graph Neural Network Encoding for Community Detection in Attribute Networks Jianyong Sun Wei Zheng Qingfu Zhang Zongben Xu 50 80 0 06 Jun 2020
XGNN: Towards Model-Level Explanations of Graph Neural Networks Haonan Yuan Jiliang Tang Xia Hu Shuiwang Ji 83 399 0 03 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 306 2,732 0 02 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 103 378 0 30 Apr 2020
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program) Joelle Pineau Philippe Vincent-Lamarre Koustuv Sinha V. Larivière A. Beygelzimer Florence dÁlché-Buc E. Fox Hugo Larochelle 78 361 0 27 Mar 2020
Directional Message Passing for Molecular Graphs Johannes Klicpera Janek Groß Stephan Günnemann 124 879 0 06 Mar 2020
On the computation of counterfactual explanations -- A survey André Artelt Barbara Hammer LRM 69 51 0 15 Nov 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 121 6,269 0 22 Oct 2019
Unsupervised Boosting-based Autoencoder Ensembles for Outlier Detection Hamed Sarvari C. Domeniconi Bardh Prenkaj Giovanni Stilo UQCV 44 19 0 22 Oct 2019
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 266 863 0 28 Sep 2019
HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding Yu He Yangqiu Song Jianxin Li Cheng Ji Jian Peng Hao Peng 75 112 0 07 Sep 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 568 14 0 23 Aug 2019
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification Yu Rong Wenbing Huang Tingyang Xu Junzhou Huang 110 1,343 0 25 Jul 2019
Why Does My Model Fail? Contrastive Local Explanations for Retail Forecasting Ana Lucic H. Haned Maarten de Rijke 66 63 0 17 Jul 2019
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification Jun Wu Jingrui He Jiejun Xu GNN 159 198 0 05 Jun 2019