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S1E10 [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…
S1E9 [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…
S1E8 [Deep Dive] Opportunities and Challenges of Graph Neural Networks in Electrical Engineering
In this episode, we dive into a survey paper of the applications of graph neural networks in electrical engineering. This episode is based on our recent publication in Nature Review Electrical…
S1E7 [Deep Dive] Fully Distributed Online Training of GNNs in Networked Systems
In this episode, we dive into fully distributed online training of graph neural networks deployed in networked systems. This episode is based on our recent preprint by Rostyslav Olshevskyi from Rice…
S1E6 [Deep Dive] Learning Decentralized Wireless Resource Allocations with Graph Neural Networks
In this episode, we dive into the combination of graph neural networks and unsupervised primal-dual learning, a model-free approach to scalable, intelligent wireless resource allocations. This…
S1E5 [Deep Dive] Annealed Langevin Dynamics for Linear Inverse Problems
In this episode, we dive into annealed Langevin dynamics, a new approach to linear inverse problems, such as massive MIMO detection, image deblurring, and network topology inference. This episode is…
S1E4 [Deep Dive] Neural OFDM Receivers for Wireless Communications
In this episode, we dive into neural OFDM receivers, a series of four papers published in IEEE Journal on Selected Areas in Communications (JSAC) and IEEE Transactions on Wireless Communications…
S1E3 [Tutorial] Graph Neural Networks for Wireless Communications
In this episode, we dive into our own tutorial (IEEE ICMLCN, MILCOM 2024) on how could graph neural networks be used to enhance wireless communications. Generated using NotebookLM from Google, this…
S1E2 [Deep Dive] Distributional Reinforcement Learning
In this episode, we dive into distributional reinforcement learning, including three papers from Google DeepMind and another Cell paper from Harvard. Generated using NotebookLM from Google, this…
S1E1 [ICLR 2023] Graph-Based Deterministic Policy Gradient for Repetitive Combinatorial Optimization
Description: In this episode, we dive into our own paper published in ICLR 2023, a study on scalable reinforcement learning for networked systems. Generated using NotebookLM from Google, this podcast…
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Deep Dive into Networked AI has published 10 episodes since December 2024, covering topics in Technology.
Deep Dive into Networked AI is currently dormant with new episodes weekly. Average episode length is 20m.
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