Towards Self-Explainable Graph Neural Network-Reference-Cited by-同舟云学术

Towards Self-Explainable Graph Neural Network

Published:2021-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 30th ACM International Conference on Information & Knowledge Management
language:
Short-container-title:

Author:

Dai Enyan¹,Wang Suhang¹

Affiliation:

1. The Pennsylvania State University, State College, PA, USA

Funder

National Science Foundation

Army Research Office

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3459637.3482306

Reference54 articles.

1. Molecular generative Graph Neural Networks for Drug Discovery

2. Ming Chen Zhewei Wei Zengfeng Huang Bolin Ding and Yaliang Li. 2020. Simple and deep graph convolutional networks. In ICML. PMLR 1725--1735. Ming Chen Zhewei Wei Zengfeng Huang Bolin Ding and Yaliang Li. 2020. Simple and deep graph convolutional networks. In ICML. PMLR 1725--1735.

Cited by 35 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. Enhancing graph neural networks for self-explainable modeling: A causal perspective with multi-granularity receptive fields;Information Processing & Management;2024-09

3. A Review of Graph Neural Networks in Epidemic Modeling;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

4. Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

5. Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24