GraphRNN Revisited: An Ablation Study and Extensions for Directed Acyclic Graphs

GraphRNN is a deep learning-based architecture proposed by You et al. for learning generative models for graphs. We replicate the results of You et al. using a reproduced implementation of the GraphRNN architecture and evaluate this against baseline models using new metrics. Through an ablation stud...

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Veröffentlicht in:	arXiv.org 2023-07
Hauptverfasser:	Das, Taniya, Koch, Mark, Ravichandran, Maya, Khatri, Nikhil
Format:	Artikel
Sprache:	eng
Schlagworte:	Ablation Deep learning Graph theory Graphical representations Graphs
Online-Zugang:	Volltext
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