[Deep Dive] GLANCE: Graph-based Learnable Digital Twin for Wireless Networks

In this episode, we dive into the applications of graph neural networks as a learnable digital twin of network simulators, which can accelerate network optimization by its fast and differentiable prediction of networking key performance indicators (KPIs). This episode is based on a preprient authored by Boning Li, et al.

Generated using NotebookLM from Google, this podcast highlights the key findings and implications of this research.

🎧 Read the paper here: [arXiv]

📷 Cover Image Source: imagine.art, Microsoft Designer

🎵 BGM: Artlist.io

🛠️ Credits: NotebookLM by Google