4 papers
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…
Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices II: Computation and Applications
J. F. Lutzeyer, A. T. Walden
The extended Davis-Kahan theorem makes use of polynomial matrix transformations to produce bounds at least as tight as the standard Davis-Kahan theorem. The optimization problem of…
Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory
J. F. Lutzeyer, A. T. Walden
The Davis-Kahan theorem can be used to bound the distance of the spaces spanned by the first eigenvectors of any two symmetric matrices. We extend the Davis-Kahan theorem to ap…