2 papers
cs.LG2026
OgBench: A Framework for Evaluating Graph Neural Networks on Omics Data
Louisa Cornelis, Johan Mathe, Louis Van Langendonck +2
Graph Neural Networks (GNNs) have become the dominant framework for inductive graph-level learning. Yet most benchmarks focus on the regime , where the number of graphs $n…
cs.LG2024
PPT-GNN: A Practical Pre-Trained Spatio-Temporal Graph Neural Network for Network Security
Louis Van Langendonck, Ismael Castell-Uroz, Pere Barlet-Ros
Recent works have demonstrated the potential of Graph Neural Networks (GNN) for network intrusion detection. Despite their advantages, a significant gap persists between real-world…