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On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approach

On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approach

31 December 2024
Ruichu Cai
Yuxuan Zhu
Xuexin Chen
Yuan Fang
Min-man Wu
Jie Qiao
Z. Hao
ArXivPDFHTML

Papers citing "On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approach"

9 / 9 papers shown
Title
Unifying Invariant and Variant Features for Graph Out-of-Distribution
  via Probability of Necessity and Sufficiency
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
Unifying Invariance and Spuriousity for Graph Out-of-Distribution via
  Probability of Necessity and Sufficiency
Unifying Invariance and Spuriousity 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
24
2
0
14 Feb 2024
Feature Attribution with Necessity and Sufficiency via Dual-stage
  Perturbation Test for Causal Explanation
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
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data
  Landscapes
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes
Bardh Prenkaj
Mario Villaizán-Vallelado
Tobias Leemann
Gjergji Kasneci
28
2
0
04 Aug 2023
Counterfactual Learning on Graphs: A Survey
Counterfactual Learning on Graphs: A Survey
Zhimeng Guo
Teng Xiao
Zongyu Wu
Charu C. Aggarwal
Hui Liu
Suhang Wang
CML
AI4CE
40
18
0
03 Apr 2023
A Survey on Graph Counterfactual Explanations: Definitions, Methods,
  Evaluation, and Research Challenges
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
A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation
  Metrics
A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics
Yiqiao Li
Jianlong Zhou
Sunny Verma
Fang Chen
XAI
31
39
0
26 Jul 2022
Explainability in Graph Neural Networks: A Taxonomic Survey
Explainability in Graph Neural Networks: A Taxonomic Survey
Hao Yuan
Haiyang Yu
Shurui Gui
Shuiwang Ji
167
591
0
31 Dec 2020
A causal framework for explaining the predictions of black-box
  sequence-to-sequence models
A causal framework for explaining the predictions of black-box sequence-to-sequence models
David Alvarez-Melis
Tommi Jaakkola
CML
227
201
0
06 Jul 2017
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