8 citations · 10 across the 4 of their papers we have counts for
4 papers
Some Might Say All You Need Is Sum
Eran Rosenbluth, Jan Toenshoff, Martin Grohe
The expressivity of Graph Neural Networks (GNNs) is dependent on the aggregation functions they employ. Theoretical works have pointed towards Sum aggregation GNNs subsuming every…
Stable Tuple Embeddings for Dynamic Databases
Jan Toenshoff, Neta Friedman, Martin Grohe +1
We study the problem of computing an embedding of the tuples of a relational database in a manner that is extensible to dynamic changes of the database. In this problem, the embedd…
Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing
Jan Tönshoff, Martin Ritzert, Hinrikus Wolf +1
We propose CRaWl, a novel neural network architecture for graph learning. Like graph neural networks, CRaWl layers update node features on a graph and thus can freely be combined o…
Graph Neural Networks for Maximum Constraint Satisfaction
Jan Toenshoff, Martin Ritzert, Hinrikus Wolf +1
Many combinatorial optimization problems can be phrased in the language of constraint satisfaction problems. We introduce a graph neural network architecture for solving such optim…