Global Counterfactual Explainer for Graph Neural Networks-Reference-Cited by-同舟云学术

Global Counterfactual Explainer for Graph Neural Networks

Published:2023-02-27 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining
language:
Short-container-title:

Author:

Huang Zexi¹^ORCID,Kosan Mert¹^ORCID,Medya Sourav²^ORCID,Ranu Sayan³^ORCID,Singh Ambuj¹^ORCID

Affiliation:

1. University of California, Santa Barbara, Santa Barbara, CA, USA

2. University of Illinois Chicago, Chicago, IL, USA

3. Indian Institute of Technology Delhi, Delhi, India

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3539597.3570376

Reference48 articles.

1. Carlo Abrate and Francesco Bonchi. 2021. Counterfactual graphs for explainable classification of brain networks. In SIGKDD. Carlo Abrate and Francesco Bonchi. 2021. Counterfactual graphs for explainable classification of brain networks. In SIGKDD.

2. Mohit Bajaj , Lingyang Chu , Zi Yu Xue , Jian Pei, Lanjun Wang, Peter Cho-Ho Lam, and Yong Zhang. 2021 . Robust Counterfactual Explanations on Graph Neural Networks. In NeurIPS. Mohit Bajaj, Lingyang Chu, Zi Yu Xue, Jian Pei, Lanjun Wang, Peter Cho-Ho Lam, and Yong Zhang. 2021. Robust Counterfactual Explanations on Graph Neural Networks. In NeurIPS.

3. Ravinder Bhattoo Sayan Ranu and NM Krishnan. 2022. Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network. In NeurIPS. Ravinder Bhattoo Sayan Ranu and NM Krishnan. 2022. Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network. In NeurIPS.

4. Karsten Borgwardt Nicol Schraudolph and SVN Vishwanathan. 2006. Fast computation of graph kernels. In NeurIPS. Karsten Borgwardt Nicol Schraudolph and SVN Vishwanathan. 2006. Fast computation of graph kernels. In NeurIPS.

5. Protein function prediction via graph kernels

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. GEAR: Learning graph neural network explainer via adjusting gradients;Knowledge-Based Systems;2024-10

2. Graph Neural Networks for Vulnerability Detection: A Counterfactual Explanation;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11

3. Multi-view Counterfactual Contrastive Learning for Fact-checking Fake News Detection;Proceedings of the 2024 International Conference on Multimedia Retrieval;2024-05-30

4. View-based Explanations for Graph Neural Networks (Extended Abstract);2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW);2024-05-13

5. Generating Robust Counterfactual Witnesses for Graph Neural Networks;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13