8 citations · 15 across the 7 of their papers we have counts for
3 papers · 1 filter
Ordered Subgraph Aggregation Networks
Chendi Qian, Gaurav Rattan, Floris Geerts +2
Numerous subgraph-enhanced graph neural networks (GNNs) have emerged recently, provably boosting the expressive power of standard (message-passing) GNNs. However, there is a limite…
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks
Christopher Morris, Gaurav Rattan, Sandra Kiefer +1
While (message-passing) graph neural networks have clear limitations in approximating permutation-equivariant functions over graphs or general relational data, more expressive, hig…
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…