Theoretical Computer Science Spring School: Machine Learning / Ecole de Printemps d'Informatique Théorique : Apprentissage Automatique

Collection Theoretical Computer Science Spring School: Machine Learning / Ecole de Printemps d'Informatique Théorique : Apprentissage Automatique

Organizer(s) Cappé, Olivier ; Garivier, Aurélien ; Gribonval, Rémi ; Kaufmann, Emilie ; Vernade, Claire
Date(s) 23/05/2022 - 27/05/2022
linked URL https://conferences.cirm-math.fr/2542.html
00:00:00 / 00:00:00
3 5

There are a plethora of interesting applications that can leverage graph structured data, from drug discovery to route planning, and it is only natural that graph Machine Learning has attracted a lot of attention lately. We will review approaches in graph representation learning, leveraging intuition from graph signal processing to design and study graph neural networks and some of their recent extensions.

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Citation data

  • DOI 10.24350/CIRM.V.19921603
  • Cite this video Vandergheynst, Pierre (23/05/2022). Machine learning on graphs. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19921603
  • URL https://dx.doi.org/10.24350/CIRM.V.19921603

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