A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks

We use synthetic datasets with different levels of interdependency between feature and network characters and show (i) that shallow embeddings relying on shared information

We also proposed to use a supergraph as input layer in order to extend graph neural networks based on spectral theory to the prediction of graph properties for arbitrary

Serratosa, A general model to define the substitu- tion, insertion and deletion graph edit costs based on an embedded space, Pattern Recognition Let- ters 138 (2020) 115 –

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

Protein-protein interaction (PPI) net- works, biochemical networks, transcriptional regulation networks, signal transduction or metabolic networks are the highlighted network

59 See Milanovic, supra note 6, at 8: ‘Jurisdiction is the actual exercise of control and authority by a state, while title and sovereignty establish the state’s right in

Ensuite, nous présenterons l’impact des TIC sur les différents processus métiers de l’entreprise, à savoir : la fonction logistique, production, commerciale, gestion des

The policy-based solutions parameterize the policy function directly by a neural architecture and try to find the optimal policy using gradient ascent, while the value-based