4 citations · 22 across the 28 of their papers we have counts for
4 papers · 1 filter
New Frontiers in Graph Autoencoders: Joint Community Detection and Link Prediction
Guillaume Salha-Galvan, Johannes F. Lutzeyer, George Dasoulas +2
Graph autoencoders (GAE) and variational graph autoencoders (VGAE) emerged as powerful methods for link prediction (LP). Their performances are less impressive on community detecti…
Improving Graph Neural Networks at Scale: Combining Approximate PageRank and CoreRank
Ariel R. Ramos Vela, Johannes F. Lutzeyer, Anastasios Giovanidis +1
Graph Neural Networks (GNNs) have achieved great successes in many learning tasks performed on graph structures. Nonetheless, to propagate information GNNs rely on a message passin…
Graph Ordering Attention Networks
Michail Chatzianastasis, Johannes F. Lutzeyer, George Dasoulas +1
Graph Neural Networks (GNNs) have been successfully used in many problems involving graph-structured data, achieving state-of-the-art performance. GNNs typically employ a message-p…
Modularity-Aware Graph Autoencoders for Joint Community Detection and Link Prediction
Guillaume Salha-Galvan, Johannes F. Lutzeyer, George Dasoulas +2
Graph autoencoders (GAE) and variational graph autoencoders (VGAE) emerged as powerful methods for link prediction. Their performances are less impressive on community detection pr…