363 citations · 1.6k across the 44 of their papers we have counts for
5 papers · 1 filter
AutoGraphAD: Unsupervised network anomaly detection using Variational Graph Autoencoders
Georgios Anyfantis, Pere Barlet-Ros
Network Intrusion Detection Systems (NIDS) are essential tools for detecting network attacks and intrusions. While extensive research has explored the use of supervised Machine Lea…
Bridging the Gap Between Simulated and Real Network Data Using Transfer Learning
Carlos Güemes-Palau, Miquel Ferriol-Galmés, Jordi Paillisse-Vilanova +3
Machine Learning (ML)-based network models provide fast and accurate predictions for complex network behaviors but require substantial training data. Collecting such data from real…
GraphUniverse: Synthetic Graph Generation for Evaluating Inductive Generalization
Louis Van Langendonck, Guillermo Bernárdez, Nina Miolane +1
A fundamental challenge in graph learning is understanding how models generalize to new, unseen graphs. While synthetic benchmarks offer controlled settings for analysis, existing…
Ordered Topological Deep Learning: a Network Modeling Case Study
Guillermo Bernárdez, Miquel Ferriol-Galmés, Carlos Güemes-Palau +4
Computer networks are the foundation of modern digital infrastructure, facilitating global communication and data exchange. As demand for reliable high-bandwidth connectivity grows…
RouteNet-Gauss: Hardware-Enhanced Network Modeling with Machine Learning
Carlos Güemes-Palau, Miquel Ferriol-Galmés, Jordi Paillisse-Vilanova +3
Network simulation is pivotal in network modeling, assisting with tasks ranging from capacity planning to performance estimation. Traditional approaches such as Discrete Event Simu…