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Weisfeiler-Lehman goes dynamic: An analysis of the expressive power of Graph Neural Networks for attributed and dynamic graphs.

Silvia Beddar-WiesingGiuseppe Alessio D'InvernoCaterina GrazianiVeronica LachiAlice Moallemy-OurehFranco ScarselliJosephine Maria Thomas
Published in: Neural Networks (2024)
Keyphrases
  • expressive power
  • neural network
  • dynamic graph
  • first order logic
  • query language
  • graph mining
  • database
  • data model
  • np hard
  • structured data
  • graph matching
  • data complexity
  • transitive closure
  • computational properties