Graph Neural Networking Challenge: Building a Network Digital Twin using data from real networks

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Published on July 11, 2023 12:00:00 AM ● Video Link: https://www.youtube.com/watch?v=QzDTYyWzpr0

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In recent years, the networking community has produced robust Graph Neural Networks (GNN) that can accurately mimic complex network environments. Modern GNN architectures enable building lightweight and accurate Network Digital Twins that can operate in real-time. However, and as a consequence of the lack of real-world data, current ML-based models have been mainly developed and trained using simulated data. This has strongly limited our understanding on how existing models perform in a real network.

Speakers:
Albert Cabellos
Professor
Universitat Politècnica de Catalunya

Moderators:
Thomas Basikolo
Programme Officer
International Telecommunication Union (ITU)

Vishnu Ram OV
Independent Research Consultant
Consultant

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The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.