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09/07/2023
Enhancing 5G Radio Planning with Graph Representations and Deep Learning
The roll out of new mobile network generations poses hard challenges due...
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08/21/2023
Topological Graph Signal Compression
Recently emerged Topological Deep Learning (TDL) methods aim to extend c...
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08/09/2023
GraphCC: A Practical Graph Learning-based Approach to Congestion Control in Datacenters
Congestion Control (CC) plays a fundamental role in optimizing traffic i...
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03/31/2023
MAGNNETO: A Graph Neural Network-based Multi-Agent system for Traffic Engineering
Current trends in networking propose the use of Machine Learning (ML) fo...
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01/26/2023
ASTrack: Automatic Detection and Removal of Web Tracking Code with Minimal Functionality Loss
Recent advances in web technologies make it more difficult than ever to ...
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01/21/2023
Leveraging Spatial and Temporal Correlations for Network Traffic Compression
The deployment of modern network applications is increasing the network ...
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12/23/2022
Proximal Policy Optimization with Graph Neural Networks for Optimal Power Flow
Optimal Power Flow (OPF) is a very traditional research area within the ...
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12/22/2022
RouteNet-Fermi: Network Modeling with Graph Neural Networks
Network models are an essential block of modern networks. For example, t...
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09/21/2022
Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing
Emerging applications such as the metaverse, telesurgery or cloud comput...
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05/27/2022
Network Digital Twin: Context, Enabling Technologies and Opportunities
The proliferation of emergent network applications (e.g., telesurgery, m...
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02/28/2022
RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation
Network modeling is a fundamental tool in network research, design, and ...
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02/01/2022
Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies
The recent growth of emergent network applications (e.g., satellite netw...
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01/04/2022
Digital Twin Network: Opportunities and Challenges
The proliferation of emergent network applications (e.g., AR/VR, telesur...
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12/29/2021
Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities
Graph neural networks (GNN) have shown outstanding applications in many ...
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10/04/2021
Scaling Graph-based Deep Learning models to larger networks
Graph Neural Networks (GNN) have shown a strong potential to be integrat...
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09/22/2021
ENERO: Efficient Real-Time Routing Optimization
Wide Area Networks (WAN) are a key infrastructure in today's society. Du...
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07/30/2021
Unveiling the potential of Graph Neural Networks for robust Intrusion Detection
The last few years have seen an increasing wave of attacks with serious ...
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10/13/2020
Applying Graph-based Deep Learning To Realistic Network Scenarios
Recent advances in Machine Learning (ML) have shown a great potential to...
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02/05/2020
Demystifying content-blockers: A large scale study of actual performance gains
With the evolution of the online advertisement and tracking ecosystem, c...
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10/16/2019
Deep Reinforcement Learning meets Graph Neural Networks: An optical network routing use case
Recent advances in Deep Reinforcement Learning (DRL) have shown a signif...
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10/03/2019
RouteNet: Leveraging Graph Neural Networks for network modeling and optimization in SDN
Network modeling is a key enabler to achieve efficient network operation...
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01/23/2019
Unveiling the potential of Graph Neural Networks for network modeling and optimization in SDN
Network modeling is a critical component for building self-driving Softw...
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03/22/2018
