most citedLifelong Learning of Graph Neural Networks for Open-World Node Classification

25 citations · 46 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021★ 21 cited

Lifelong Learning on Evolving Graphs Under the Constraints of Imbalanced Classes and New Classes

Lukas Galke, Iacopo Vagliano, Benedikt Franke +3

Lifelong graph learning deals with the problem of continually adapting graph neural network (GNN) models to changes in evolving graphs. We address two critical challenges of lifelo…

cs.LG2020★ 25 cited

Lifelong Learning of Graph Neural Networks for Open-World Node Classification

Lukas Galke, Benedikt Franke, Tobias Zielke +1

Graph neural networks (GNNs) have emerged as the standard method for numerous tasks on graph-structured data such as node classification. However, real-world graphs are often evolv…