Graph neural network: Difference between revisions

Revision as of 05:33, 7 July 2021

Revision as of 05:34, 7 July 2021

Line 1:

{{Merge from|Draft:Graph neural network|discuss=Talk:Graph neural network#Proposed merge of Draft:Graph neural network into Graph neural network|date=July 2021}}

{{Merge from|Draft:Graph neutral network|discuss=Talk:Graph neural network#Proposed merge of Draft:Graph neutral network into Graph neural network|date=July 2021}}

A '''graph neural network (GNN)''' is a class of [[Neural network|neural networks]] for processing data represented by [[Graph (abstract data type)|graph data structures]]<ref>{{Cite journal|last=Scarselli|first=Franco|last2=Gori|first2=Marco|last3=Tsoi|first3=Ah Chung|last4=Hagenbuchner|first4=Markus|last5=Monfardini|first5=Gabriele|date=2009|title=The Graph Neural Network Model|url=https://ieeexplore.ieee.org/abstract/document/4700287|journal=IEEE Transactions on Neural Networks|volume=20|issue=1|pages=61–80|doi=10.1109/TNN.2008.2005605|issn=1941-0093}}</ref>. They were popularized by their use in [[supervised learning]] on properties of various molecules<ref>{{Cite journal|last=Gilmer|first=Justin|last2=Schoenholz|first2=Samuel S.|last3=Riley|first3=Patrick F.|last4=Vinyals|first4=Oriol|last5=Dahl|first5=George E.|date=2017-07-17|title=Neural Message Passing for Quantum Chemistry|url=http://proceedings.mlr.press/v70/gilmer17a.html|journal=International Conference on Machine Learning|language=en|publisher=PMLR|pages=1263–1272}}</ref>.