[Deep Dive] AirGNN: Graph Neural Networks over the air for Wireless Networks

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Deep Dive into Networked AI

NetAIStudio

10 episodes

1 day ago

Explore the cutting-edge of artificial intelligence (AI), machine learning, optimization, signal processing, wireless communications, networking, and broader networked systems. Join us as we dive deep into frontier research papers, uncover groundbreaking innovations, and discuss the possibilities shaping the future of technology and science.

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[Deep Dive] AirGNN: Graph Neural Networks over the air for Wireless Networks

Deep Dive into Networked AI

17 minutes 3 seconds

8 months ago

[Deep Dive] AirGNN: Graph Neural Networks over the air for Wireless Networks

In this episode, we explore the nuances and key considerations of implementing graph neural networks as decentralized applications in wireless networks, such as source localization, multi-robot flocking, and wireless channel management — a core theme of this podcast, especially in this season. This discussion is based on a journal paper published in IEEE Transactions on Signal Processing, authored by Zhan Gao and Deniz Gündüz.

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

🎧 Read the paper here: [IEEE TSP](https://ieeexplore.ieee.org/document/9042352)

📷 Cover Image Source: imagine.art, Microsoft Designer

🎵 BGM: Artlist.io

🛠️ Credits: NotebookLM by Google