Recently, many works studied the expressive power of graph neural networ...
Numerous subgraph-enhanced graph neural networks (GNNs) have emerged
rec...
Characterizing the separation power of graph neural networks (GNNs) prov...
We investigate the power of message-passing neural networks (MPNNs) in t...
Various recent proposals increase the distinguishing power of Graph Neur...
Linear algebra algorithms often require some sort of iteration or recurs...
The expressive power of graph neural network formalisms is commonly meas...
The expressive power of message passing neural networks (MPNNs) is known...
In this paper we cast neural networks defined on graphs as message-passi...
We investigate when two graphs, represented by their adjacency matrices,...
Most graph query languages are rooted in logic. By contrast, in this pap...
Anytime approximation algorithms for computing query probabilities over
...
We investigate the expressive power of MATLANG, a formal language
for ma...