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SCGG: A deep structure-conditioned graph generative model

Deep learning-based graph generation approaches have remarkable capacities for graph data modeling, allowing them to solve a wide range of real-world problems. Making these methods able to consider different conditions during the generation procedure even increases their effectiveness by empowering...

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Detalles Bibliográficos
Autores principales: Faez, Faezeh, Hashemi Dijujin, Negin, Soleymani Baghshah, Mahdieh, Rabiee, Hamid R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678307/
https://www.ncbi.nlm.nih.gov/pubmed/36409705
http://dx.doi.org/10.1371/journal.pone.0277887

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