CLEAR: Generative Counterfactual Explanations on Graphs

16 October 2022

Jing Ma

Aidong Zhang

Papers citing "CLEAR: Generative Counterfactual Explanations on Graphs"

39 / 39 papers shown

Title
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 68 2 0 14 Feb 2025
Graph Counterfactual Explainable AI via Latent Space Traversal Andreas Abildtrup Hansen Paraskevas Pegios Anna Calissano Aasa Feragen OOD BDL AAML 81 0 0 15 Jan 2025
Global Graph Counterfactual Explanation: A Subgraph Mapping Approach Yinhan He Wendy Zheng Yaochen Zhu Jing Ma Saumitra Mishra Natraj Raman Ninghao Liu Jundong Li 26 0 0 25 Oct 2024
Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property Prediction Yinhan He Zaiyi Zheng Patrick Soga Yaozhen Zhu Yushun Dong Jundong Li 19 1 0 19 Oct 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 24 0 0 16 Oct 2024
Causal Inference with Latent Variables: Recent Advances and Future Prospectives Yaochen Zhu Yinhan He Jing Ma Mengxuan Hu Sheng R. Li Jundong Li CML 43 3 0 20 Jun 2024
Global Human-guided Counterfactual Explanations for Molecular Properties via Reinforcement Learning Danqing Wang Antonis Antoniades Kha-Dinh Luong Edwin Zhang Mert Kosan Jiachen Li Ambuj Singh William Yang Wang Lei Li AI4CE 20 0 0 19 Jun 2024
How Interpretable Are Interpretable Graph Neural Networks? Yongqiang Chen Yatao Bian Bo Han James Cheng 44 4 0 12 Jun 2024
LLM-Generated Black-box Explanations Can Be Adversarially Helpful R. Ajwani Shashidhar Reddy Javaji Frank Rudzicz Zining Zhu AAML 32 6 0 10 May 2024
Graph Neural Networks for Vulnerability Detection: A Counterfactual Explanation Zhaoyang Chu Yao Wan Qian Li Yang Wu Hongyu Zhang Yulei Sui Guandong Xu Hai Jin AAML 36 9 0 24 Apr 2024
CASPER: Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation Baoyu Jing Dawei Zhou Kan Ren Carl Yang CML AI4TS 32 6 0 18 Mar 2024
Towards Non-Adversarial Algorithmic Recourse Tobias Leemann Martin Pawelczyk Bardh Prenkaj Gjergji Kasneci AAML 26 1 0 15 Mar 2024
Fast Inference of Removal-Based Node Influence Weikai Li Zhiping Xiao Xiao Luo Yizhou Sun AAML 28 1 0 13 Mar 2024
QUCE: The Minimisation and Quantification of Path-Based Uncertainty for Generative Counterfactual Explanations J. Duell M. Seisenberger Hsuan-Wei Fu Xiuyi Fan UQCV BDL 32 1 0 27 Feb 2024
Game-theoretic Counterfactual Explanation for Graph Neural Networks Chirag Chhablani Sarthak Jain Akshay Channesh Ian A. Kash Sourav Medya 33 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 22 0 0 07 Feb 2024
PowerGraph: A power grid benchmark dataset for graph neural networks Anna Varbella Kenza Amara B. Gjorgiev Mennatallah El-Assady G. Sansavini 18 5 0 05 Feb 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 36 2 0 19 Dec 2023
Robust Stochastic Graph Generator for Counterfactual Explanations Mario Alfonso Prado-Romero Bardh Prenkaj Giovanni Stilo CML 6 3 0 18 Dec 2023
Factorized Explainer for Graph Neural Networks Rundong Huang Farhad Shirani Dongsheng Luo 37 8 0 09 Dec 2023
Exploring Causal Learning through Graph Neural Networks: An In-depth Review Simi Job Xiaohui Tao Taotao Cai Haoran Xie Lin Li Jianming Yong Qing Li CML AI4CE 24 5 0 25 Nov 2023
Generative Explanations for Graph Neural Network: Methods and Evaluations Jialin Chen Kenza Amara Junchi Yu Rex Ying 37 3 0 09 Nov 2023
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion Jialin Chen Shirley Wu Abhijit Gupta Rex Ying DiffM 34 4 0 30 Oct 2023
Graph AI in Medicine Ruth Johnson Michelle M. Li Ayush Noori Owen Queen Marinka Zitnik 21 3 0 20 Oct 2023
Deep Backtracking Counterfactuals for Causally Compliant Explanations Klaus-Rudolf Kladny Julius von Kügelgen Bernhard Schölkopf Michael Muehlebach BDL 26 4 0 11 Oct 2023
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks Xu Zheng Farhad Shirani Tianchun Wang Wei Cheng Zhuomin Chen Haifeng Chen Hua Wei Dongsheng Luo 27 11 0 03 Oct 2023
GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking Mert Kosan S. Verma Burouj Armgaan Khushbu Pahwa Ambuj K. Singh Sourav Medya Sayan Ranu 27 13 0 03 Oct 2023
GInX-Eval: Towards In-Distribution Evaluation of Graph Neural Network Explanations Kenza Amara Mennatallah El-Assady Rex Ying 28 6 0 28 Sep 2023
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes Bardh Prenkaj Mario Villaizán-Vallelado Tobias Leemann Gjergji Kasneci 26 2 0 04 Aug 2023
A Survey on Explainability of Graph Neural Networks Jaykumar Kakkad Jaspal Jannu Kartik Sharma Charu C. Aggarwal Sourav Medya 28 23 0 02 Jun 2023
Unstructured and structured data: Can we have the best of both worlds with large language models? W. Tan 11 1 0 25 Apr 2023
Counterfactual Learning on Graphs: A Survey Zhimeng Guo Teng Xiao Zongyu Wu Charu C. Aggarwal Hui Liu Suhang Wang CML AI4CE 38 18 0 03 Apr 2023
Efficient XAI Techniques: A Taxonomic Survey Yu-Neng Chuang Guanchu Wang Fan Yang Zirui Liu Xuanting Cai Mengnan Du Xia Hu 13 31 0 07 Feb 2023
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges Mario Alfonso Prado-Romero Bardh Prenkaj Giovanni Stilo F. Giannotti CML 27 30 0 21 Oct 2022
FlowX: Towards Explainable Graph Neural Networks via Message Flows Shurui Gui Hao Yuan Jie Wang Qicheng Lao Kang Li Shuiwang Ji 28 11 0 26 Jun 2022
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 110 142 0 05 Feb 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 167 591 0 31 Dec 2020
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 221 1,337 0 12 Feb 2018
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 166 1,775 0 02 Mar 2017