cs.SI · 2026-09-02 · No. 103

Social and Information Networks, 2026-09-02.

1 new papers in cs.SI. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    A Network Science Perspective on Evaluating Deep Graph Generative Models

    Tianrui Mao, Abele Malan, Megha Khosla, Lydia Chen, Huijuan Wang

    cs.SI · cs.AI

    Traditional network models from network science, such as the Erdos-Renyi and configuration models, generate random networks that reproduce few selected topological properties observed in real-world networks. Deep graph generative models emerge as a data-driven approach, leveraging deep neural network architectures to learn complex structural distributions directly from real-world networks to generate more realistic synthetic networks. Because...

    arxiv.org/abs/2609.01015 · PDF

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