A Demonstration of Interpretability Methods for Graph Neural Networks

Ehsan B. Mobaraki; Arijit Khan

doi:10.1145/3594778.3594880

A Demonstration of Interpretability Methods for Graph Neural Networks

Ehsan B. Mobaraki
, Arijit Khan

Aalborg University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Proceedings of the 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems (GRADES) and Network Data Analytics (NDA) 2023, GRADES-NDA 2023
Editors	Olaf Hartig, Yuichi Yoshida
Publisher	Association for Computing Machinery
ISBN (Electronic)	9798400702013
DOIs	https://doi.org/10.1145/3594778.3594880
State	Published - Jun 21 2023
Externally published	Yes
Event	6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems and Network Data Analytics, GRADES-NDA 2023 - Seattle, United States Duration: Jun 18 2023 → Jun 18 2023

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems and Network Data Analytics, GRADES-NDA 2023
Country/Territory	United States
City	Seattle
Period	6/18/23 → 6/18/23

ASJC Scopus Subject Areas

Human-Computer Interaction
Computer Networks and Communications
Computer Vision and Pattern Recognition
Software

Keywords

explainable AI
Graph neural network
interpretability

Access to Document

10.1145/3594778.3594880

Cite this

Mobaraki, E. B., & Khan, A. (2023). A Demonstration of Interpretability Methods for Graph Neural Networks. In O. Hartig, & Y. Yoshida (Eds.), Proceedings of the 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems (GRADES) and Network Data Analytics (NDA) 2023, GRADES-NDA 2023 Article 9 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3594778.3594880

A Demonstration of Interpretability Methods for Graph Neural Networks. / Mobaraki, Ehsan B.; Khan, Arijit.
Proceedings of the 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems (GRADES) and Network Data Analytics (NDA) 2023, GRADES-NDA 2023. ed. / Olaf Hartig; Yuichi Yoshida. Association for Computing Machinery, 2023. 9 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mobaraki, EB & Khan, A 2023, A Demonstration of Interpretability Methods for Graph Neural Networks. in O Hartig & Y Yoshida (eds), Proceedings of the 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems (GRADES) and Network Data Analytics (NDA) 2023, GRADES-NDA 2023., 9, ACM International Conference Proceeding Series, Association for Computing Machinery, 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems and Network Data Analytics, GRADES-NDA 2023, Seattle, United States, 6/18/23. https://doi.org/10.1145/3594778.3594880

Mobaraki EB, Khan A. A Demonstration of Interpretability Methods for Graph Neural Networks. In Hartig O, Yoshida Y, editors, Proceedings of the 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems (GRADES) and Network Data Analytics (NDA) 2023, GRADES-NDA 2023. Association for Computing Machinery. 2023. 9. (ACM International Conference Proceeding Series). doi: 10.1145/3594778.3594880

Mobaraki, Ehsan B. ; Khan, Arijit. / A Demonstration of Interpretability Methods for Graph Neural Networks. Proceedings of the 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems (GRADES) and Network Data Analytics (NDA) 2023, GRADES-NDA 2023. editor / Olaf Hartig ; Yuichi Yoshida. Association for Computing Machinery, 2023. (ACM International Conference Proceeding Series).

@inproceedings{fdbbc1140c264452bd86d1ceab12bae7,

title = "A Demonstration of Interpretability Methods for Graph Neural Networks",

keywords = "explainable AI, Graph neural network, interpretability",

author = "Mobaraki, \{Ehsan B.\} and Arijit Khan",

note = "Publisher Copyright: {\textcopyright} 2023 Copyright held by the owner/author(s).; 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems and Network Data Analytics, GRADES-NDA 2023 ; Conference date: 18-06-2023 Through 18-06-2023",

year = "2023",

month = jun,

day = "21",

doi = "10.1145/3594778.3594880",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

editor = "Olaf Hartig and Yuichi Yoshida",

booktitle = "Proceedings of the 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems (GRADES) and Network Data Analytics (NDA) 2023, GRADES-NDA 2023",

}

TY - GEN

T1 - A Demonstration of Interpretability Methods for Graph Neural Networks

AU - Mobaraki, Ehsan B.

AU - Khan, Arijit

PY - 2023/6/21

Y1 - 2023/6/21

KW - explainable AI

KW - Graph neural network

KW - interpretability

UR - https://www.scopus.com/pages/publications/85163724299

UR - https://www.scopus.com/pages/publications/85163724299#tab=citedBy

U2 - 10.1145/3594778.3594880

DO - 10.1145/3594778.3594880

M3 - Conference contribution

AN - SCOPUS:85163724299

T3 - ACM International Conference Proceeding Series

BT - Proceedings of the 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems (GRADES) and Network Data Analytics (NDA) 2023, GRADES-NDA 2023

A2 - Hartig, Olaf

A2 - Yoshida, Yuichi

PB - Association for Computing Machinery

T2 - 6th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems and Network Data Analytics, GRADES-NDA 2023

Y2 - 18 June 2023 through 18 June 2023

ER -

A Demonstration of Interpretability Methods for Graph Neural Networks

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

Other files and links

Cite this