59 citations · 103 across the 4 of their papers we have counts for
5 papers
RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation
Miquel Ferriol-Galmés, Krzysztof Rusek, José Suárez-Varela +4
Network modeling is a fundamental tool in network research, design, and operation. Arguably the most popular method for modeling is Queuing Theory (QT). Its main limitation is that…
Digital Twin Network: Opportunities and Challenges
Paul Almasan, Miquel Ferriol-Galmés, Jordi Paillisse +13
The proliferation of emergent network applications (e.g., AR/VR, telesurgery, real-time communications) is increasing the difficulty of managing modern communication networks. Thes…
Scaling Graph-based Deep Learning models to larger networks
Miquel Ferriol-Galmés, José Suárez-Varela, Krzysztof Rusek +2
Graph Neural Networks (GNN) have shown a strong potential to be integrated into commercial products for network control and management. Early works using GNN have demonstrated an u…
The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks
José Suárez-Varela, Miquel Ferriol-Galmés, Albert López +21
During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of contro…
Applying Graph-based Deep Learning To Realistic Network Scenarios
Miquel Ferriol-Galmés, José Suárez-Varela, Pere Barlet-Ros +1
Recent advances in Machine Learning (ML) have shown a great potential to build data-driven solutions for a plethora of network-related problems. In this context, building fast and…