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GRAN is superior to GraphRNN: node orderings, kernel- and graph
  embeddings-based metrics for graph generators

GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generators

International Conference on Machine Learning, Optimization, and Data Science (MOD), 2023
13 July 2023
Ousmane Touat
Julian Stier
Pierre-Edouard Portier
Michael Granitzer
ArXiv (abs)PDFHTML

Papers citing "GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generators"

2 / 2 papers shown
Data Augmentation in Graph Neural Networks: The Role of Generated
  Synthetic Graphs
Data Augmentation in Graph Neural Networks: The Role of Generated Synthetic Graphs
Sumeyye Bas
Kıymet Kaya
Resul Tugay
Ş. Öğüdücü
124
0
0
20 Jul 2024
GraphRNN Revisited: An Ablation Study and Extensions for Directed
  Acyclic Graphs
GraphRNN Revisited: An Ablation Study and Extensions for Directed Acyclic Graphs
Taniya Das
Mark Koch
Maya Ravichandran
Nikhil Khatri
GNN
135
0
0
26 Jul 2023
1