Graph neural network: Difference between revisions

Revision as of 04:43, 27 September 2021

Revision as of 14:47, 25 October 2021

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{{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}}

A '''graph neural network (GNN)''' is a class of [[neural network]]s for processing data represented by [[Graph (abstract data type)|graph data structures]].<ref>{{Cite journal|last1=Scarselli|first1=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/document/4700287|journal=IEEE Transactions on Neural Networks|volume=20|issue=1|pages=61–80|doi=10.1109/TNN.2008.2005605|pmid=19068426|s2cid=206756462|issn=1941-0093}}</ref><ref>{{Cite journal|last=Sanchez-Lengeling|first=Benjamin|last2=Reif|first2=Emily|last3=Pearce|first3=Adam|last4=Wiltschko|first4=Alex|date=2021-09-02|title=A Gentle Introduction to Graph Neural Networks|url=https://distill.pub/2021/gnn-intro|journal=Distill|language=en|volume=6|issue=9|pages=e33|doi=10.23915/distill.00033|issn=2476-0757|doi-access=free}}</ref> They were popularized by their use in [[supervised learning]] on properties of various molecules.<ref>{{Cite journal|last1=Gilmer|first1=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|arxiv=1704.01212}}</ref>