11 citations · 17 across the 4 of their papers we have counts for
4 papers
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…
Is Machine Learning Ready for Traffic Engineering Optimization?
Guillermo Bernárdez, José Suárez-Varela, Albert López +5
Traffic Engineering (TE) is a basic building block of the Internet. In this paper, we analyze whether modern Machine Learning (ML) methods are ready to be used for TE optimization.…
Unveiling the potential of Graph Neural Networks for robust Intrusion Detection
David Pujol-Perich, José Suárez-Varela, Albert Cabellos-Aparicio +1
The last few years have seen an increasing wave of attacks with serious economic and privacy damages, which evinces the need for accurate Network Intrusion Detection Systems (NIDS)…
Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges
Paul Almasan, José Suárez-Varela, Bo Wu +3
The digital transformation is pushing the existing network technologies towards new horizons, enabling new applications (e.g., vehicular networks). As a result, the networking comm…