833 citations · 1.7k across the 18 of their papers we have counts for
Showing 2018Show all
2 papers · 1 filter
cs.LG2018
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Christopher Morris, Martin Ritzert, Matthias Fey +4
In recent years, graph neural networks (GNNs) have emerged as a powerful neural architecture to learn vector representations of nodes and graphs in a supervised, end-to-end fashion…
cs.LG2018★ 833 cited
Hierarchical Graph Representation Learning with Differentiable Pooling
Rex Ying, Jiaxuan You, Christopher Morris +3
Recently, graph neural networks (GNNs) have revolutionized the field of graph representation learning through effectively learned node embeddings, and achieved state-of-the-art res…