Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning

17 February 2022

Juntao Tan

Papers citing "Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning"

20 / 20 papers shown

Title
Generating Skyline Explanations for Graph Neural Networks Dazhuo Qiu Haolai Che Arijit Khan Yinghui Wu 38 0 0 12 May 2025
COMRECGC: Global Graph Counterfactual Explainer through Common Recourse Gregoire Fournier Sourav Medya BDL 44 0 0 11 May 2025
Interpretability of Graph Neural Networks to Assess Effects of Global Change Drivers on Ecological Networks Emré Anakok Pierre Barbillon Colin Fontaine Elisa Thébault 47 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 68 2 0 14 Feb 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 Z. Hao 48 7 0 31 Dec 2024
Unifying Invariant and Variant Features for Graph Out-of-Distribution via Probability of Necessity and Sufficiency Xuexin Chen Ruichu Cai Kaitao Zheng Zhifan Jiang Zhengting Huang Zhifeng Hao Zijian Li 54 0 0 21 Jul 2024
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation Xuexin Chen Ruichu Cai Zhengting Huang Yuxuan Zhu Julien Horwood Zhifeng Hao Zijian Li Jose Miguel Hernandez-Lobato AAML 36 2 0 13 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 27 12 0 26 Jan 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 41 2 0 19 Dec 2023
Robust Stochastic Graph Generator for Counterfactual Explanations Mario Alfonso Prado-Romero Bardh Prenkaj Giovanni Stilo CML 8 3 0 18 Dec 2023
Robust Ante-hoc Graph Explainer using Bilevel Optimization Kha-Dinh Luong Mert Kosan A. Silva Ambuj K. Singh 34 6 0 25 May 2023
ExplainableFold: Understanding AlphaFold Prediction with Explainable AI Juntao Tan Yongfeng Zhang 17 6 0 27 Jan 2023
MEGAN: Multi-Explanation Graph Attention Network Jonas Teufel Luca Torresi Patrick Reiser Pascal Friederich 16 8 0 23 Nov 2022
Global Counterfactual Explainer for Graph Neural Networks Mert Kosan Zexi Huang Sourav Medya Sayan Ranu Ambuj K. Singh 26 47 0 21 Oct 2022
L2XGNN: Learning to Explain Graph Neural Networks G. Serra Mathias Niepert 31 7 0 28 Sep 2022
Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS) H. Chen Yunqi Li He Zhu Yongfeng Zhang 31 5 0 23 Aug 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
Deconfounded Causal Collaborative Filtering Shuyuan Xu Juntao Tan Shelby Heinecke Jia Li Yongfeng Zhang CML 27 40 0 14 Oct 2021
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