Difference between revisions of "Publications/veyrin-forrer.22.egc"

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| authors = Luca Veyrin-Forrer, Ataollah Kamal, Stefan Duffner, Marc Plantevit, Céline Robardet
 
| authors = Luca Veyrin-Forrer, Ataollah Kamal, Stefan Duffner, Marc Plantevit, Céline Robardet
 
| title = Qu'est-ce que mon GNN capture vraiment ? Exploration des représentations internes d'un GNN
 
| title = Qu'est-ce que mon GNN capture vraiment ? Exploration des représentations internes d'un GNN
| booktitle = Extraction et Gestion des Connaissances, EGC 2022, Blois, France24 au 28 janvier 2022
+
| booktitle = Extraction et Gestion des Connaissances, EGC 2022Blois, France, 24 au 28 janvier 2022
 
| pages = 159 to 170
 
| pages = 159 to 170
| None = http://editions-rnti.fr/?inprocid=1002725
+
| opturl = http://editions-rnti.fr/?inprocid=1002725
  +
| note = In French, Best paper award
| timestamp = Wed, 09 Mar 2022 16:39:53 +0100
 
| note = In French, Best paper award category = national
+
| category = national
| lrdeprojects =
 
 
| lrdekeywords = IA
 
| lrdekeywords = IA
 
| lrdenewsdate = 2022-03-24
 
| lrdenewsdate = 2022-03-24
| abstract = While existing GNN's explanation methods explain the decision by studying the output layer, we propose a method that analyzes the hidden layers to identify the neurons that are co-activated for a class. We associate to them a graph.
+
| abstract = While existing GNN's explanation methods explain the decision by studying the output layer, we propose a method that analyzes the hidden layers to identify the neurons that are co-activated for a class. We associate to them a graph.
 
| type = inproceedings
 
| type = inproceedings
 
| id = veyrin-forrer.22.egc
 
| id = veyrin-forrer.22.egc
 
| bibtex =
 
| bibtex =
 
@InProceedings<nowiki>{</nowiki> veyrin-forrer.22.egc,
 
@InProceedings<nowiki>{</nowiki> veyrin-forrer.22.egc,
author = <nowiki>{</nowiki>Luca Veyrin<nowiki>{</nowiki>-<nowiki>}</nowiki>Forrer and Ataollah Kamal and Stefan Duffner
+
author = <nowiki>{</nowiki>Luca <nowiki>{</nowiki>Veyrin-Forrer<nowiki>}</nowiki> and Ataollah Kamal and Stefan Duffner
and Marc Plantevit and C<nowiki>{</nowiki>\'<nowiki>{</nowiki>e<nowiki>}</nowiki><nowiki>}</nowiki>line Robardet<nowiki>}</nowiki>,
+
and Marc Plantevit and C\'eline Robardet<nowiki>}</nowiki>,
title = <nowiki>{</nowiki>Qu'est-ce que mon <nowiki>{</nowiki>GNN<nowiki>}</nowiki> capture vraiment ? Exploration des
+
title = <nowiki>{</nowiki>Qu'est-ce que mon <nowiki>{</nowiki>GNN<nowiki>}</nowiki> capture vraiment ? <nowiki>{</nowiki>E<nowiki>}</nowiki>xploration
repr<nowiki>{</nowiki>\'<nowiki>{</nowiki>e<nowiki>}</nowiki><nowiki>}</nowiki>sentations internes d'un <nowiki>{</nowiki>GNN<nowiki>}</nowiki><nowiki>}</nowiki>,
+
des repr\'esentations internes d'un <nowiki>{</nowiki>GNN<nowiki>}</nowiki><nowiki>}</nowiki>,
 
booktitle = <nowiki>{</nowiki>Extraction et Gestion des Connaissances, <nowiki>{</nowiki>EGC<nowiki>}</nowiki> 2022,
 
booktitle = <nowiki>{</nowiki>Extraction et Gestion des Connaissances, <nowiki>{</nowiki>EGC<nowiki>}</nowiki> 2022,
 
Blois, France, 24 au 28 janvier 2022<nowiki>}</nowiki>,
 
Blois, France, 24 au 28 janvier 2022<nowiki>}</nowiki>,
 
pages = <nowiki>{</nowiki>159--170<nowiki>}</nowiki>,
 
pages = <nowiki>{</nowiki>159--170<nowiki>}</nowiki>,
 
year = <nowiki>{</nowiki>2022<nowiki>}</nowiki>,
 
year = <nowiki>{</nowiki>2022<nowiki>}</nowiki>,
url = <nowiki>{</nowiki>http://editions-rnti.fr/?inprocid=1002725<nowiki>}</nowiki>,
+
opturl = <nowiki>{</nowiki>http://editions-rnti.fr/?inprocid=1002725<nowiki>}</nowiki>,
timestamp = <nowiki>{</nowiki>Wed, 09 Mar 2022 16:39:53 +0100<nowiki>}</nowiki>,
 
 
note = <nowiki>{</nowiki>In French, Best paper award<nowiki>}</nowiki>,
 
note = <nowiki>{</nowiki>In French, Best paper award<nowiki>}</nowiki>,
 
category = <nowiki>{</nowiki>national<nowiki>}</nowiki>,
 
category = <nowiki>{</nowiki>national<nowiki>}</nowiki>,

Revision as of 14:44, 5 April 2022

Abstract

While existing GNN's explanation methods explain the decision by studying the output layer, we propose a method that analyzes the hidden layers to identify the neurons that are co-activated for a class. We associate to them a graph.


Bibtex (lrde.bib)

@InProceedings{	  veyrin-forrer.22.egc,
  author	= {Luca {Veyrin-Forrer} and Ataollah Kamal and Stefan Duffner
		  and Marc Plantevit and C\'eline Robardet},
  title		= {Qu'est-ce que mon {GNN} capture vraiment ? {E}xploration
		  des repr\'esentations internes d'un {GNN}},
  booktitle	= {Extraction et Gestion des Connaissances, {EGC} 2022,
		  Blois, France, 24 au 28 janvier 2022},
  pages		= {159--170},
  year		= {2022},
  opturl	= {http://editions-rnti.fr/?inprocid=1002725},
  note		= {In French, Best paper award},
  category	= {national},
  abstract	= {While existing GNN's explanation methods explain the
		  decision by studying the output layer, we propose a method
		  that analyzes the hidden layers to identify the neurons
		  that are co-activated for a class. We associate to them a
		  graph.}
}