21 citations · 30 across the 8 of their papers we have counts for
3 papers · 1 filter
Edge-Splitting MLP: Node Classification on Homophilic and Heterophilic Graphs without Message Passing
Matthias Kohn, Marcel Hoffmann, Ansgar Scherp
Message Passing Neural Networks (MPNNs) have demonstrated remarkable success in node classification on homophilic graphs. It has been shown that they do not solely rely on homophil…
Lifelong Graph Learning for Graph Summarization
Jonatan Frank, Marcel Hoffmann, Nicolas Lell +2
Summarizing web graphs is challenging due to the heterogeneity of the modeled information and its changes over time. We investigate the use of neural networks for lifelong graph su…
POWN: Prototypical Open-World Node Classification
Marcel Hoffmann, Lukas Galke, Ansgar Scherp
We consider the problem of \textit{true} open-world semi-supervised node classification, in which nodes in a graph either belong to known or new classes, with the latter not presen…