AI/ML Challenge Finale: Graph Neural Networking Challenge and Network failure using digital twins

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AI/ML Challenge Finale: Graph Neural Networking Challenge and Network failure using digital twins

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  • The ITU AI/ML in 5G Challenge in 2023 (Fourth edition) offers a platform for collaboratively addressing the problems in applying AI/ML in communication networks including 5G & 6G. The Challenge connects participants (students and professionals) from more than 100 countries, with industry and academia solving real-world problems using AI/ML in communication networks. The challenge is offering 12 problem statement in 2023. Some of these problem statements includes;   

    • Graph Neural Networking Challenge 2023 – Creating a Network Digital Twin with Real Network Data  
    • Network failure using digital twins    

    The 2023 Graph Neural Networking Challenge entitled “Building a Network Digital Twin using data from real networks challenged participants to develop, for the first time ever, a GNN-based Network Digital Twin using a dataset from a real-network. 

    The Network Failure Classification Challenge utilizes advanced Network Digital Twin (NDT) technology. NDT serves as a virtual replica of real-world networks, allowing practical simulations of network behaviors and operations. The primary goal of this challenge is to create a network failure classification model, specifically a Root Cause Analysis (RCA) model, to facilitate operational tasks such as failure analysis and mitigation within the context of Beyond 5G.   

    This webinar will cover presentation from best teams of this competition and winners will be announced at the end of the session to recognize their outstanding performance.    

    Problem Statement: Graph Neural Networking Challenge 2023 – Creating a Network Digital Twin with Real Network Data

    1. m0b1us – Winner (1st place) Prize: 2500 EUR – Cláudio Matheus Modesto, Andrey Silva, Silvia Lins,Rebecca Aben-Athar
    2. BUPT_CMCC – Runner-up (2nd place) Prize: 800 EUR – Zicheng Wang, Yuanjie Duan, Danyang Chen, Lingqi Guo
    3. LKN – Third place (3rd place) Prize: 200 EUR – Kaan Aykurt, Johannes Zerwas, Serkut Ayvasik, Maximilian Stephan

    Problem Statement:Network failure classification model using network digital twin

    1. dku_ml – Winner (1st place) Prize: 500 CHF – Kyu-haeng Lee
    2. MLAB_2023 – Runner-up (2nd place) Prize: 300 CHF – Tianhao Zhu
    3. Hyperion – Third place (3rd place) Prize: 200 CHF – Ndabuye Sengayo
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    • Start date
      14 December 2023 at 14:00 CET Geneva | 08:00-09:30 EST, New York | 21:00-22:30 CST, Beijing
    • End date
      14 December 2023 at 15:30 CET Geneva | 08:00-09:30 EST, New York | 21:00-22:30 CST, Beijing
    • Duration
      90 minutes
    • Programme stream
    • Topics
    • UN SDGs

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