363 citations · 2.1k across the 64 of their papers we have counts for
3 papers · 1 filter
Detecting Contextual Network Anomalies with Graph Neural Networks
Hamid Latif-Martínez, José Suárez-Varela, Albert Cabellos-Aparicio +1
Detecting anomalies on network traffic is a complex task due to the massive amount of traffic flows in today's networks, as well as the highly-dynamic nature of traffic over time.…
Topological Graph Signal Compression
Guillermo Bernárdez, Lev Telyatnikov, Eduard Alarcón +3
Recently emerged Topological Deep Learning (TDL) methods aim to extend current Graph Neural Networks (GNN) by naturally processing higher-order interactions, going beyond the pairw…
IGNNITION: Bridging the Gap Between Graph Neural Networks and Networking Systems
David Pujol-Perich, José Suárez-Varela, Miquel Ferriol +4
Recent years have seen the vast potential of Graph Neural Networks (GNN) in many fields where data is structured as graphs (e.g., chemistry, recommender systems). In particular, GN…