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Disentangling Interpretable Generative Parameters of Random and
  Real-World Graphs
v1v2 (latest)

Disentangling Interpretable Generative Parameters of Random and Real-World Graphs

12 October 2019
Niklas Stoehr
Emine Yilmaz
Marc Brockschmidt
Jan Stuehmer
    BDLCMLDRL
ArXiv (abs)PDFHTML

Papers citing "Disentangling Interpretable Generative Parameters of Random and Real-World Graphs"

4 / 4 papers shown
Title
Recovering Barabási-Albert Parameters of Graphs through
  Disentanglement
Recovering Barabási-Albert Parameters of Graphs through Disentanglement
Cristina Guzman
Daphna Keidar
Tristan Meynier
Andreas Opedal
Niklas Stoehr
54
0
0
03 May 2021
Deep Graph Generators: A Survey
Deep Graph Generators: A Survey
Faezeh Faez
Yassaman Ommi
M. Baghshah
Hamid R. Rabiee
GNNAI4CE
120
58
0
31 Dec 2020
A Systematic Survey on Deep Generative Models for Graph Generation
A Systematic Survey on Deep Generative Models for Graph Generation
Xiaojie Guo
Liang Zhao
MedIm
159
150
0
13 Jul 2020
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement
Xiaojie Guo
Liang Zhao
Zhao Qin
Lingfei Wu
Amarda Shehu
Yanfang Ye
CoGeDRL
123
46
0
09 Jun 2020
1