31 citations · 35 across the 3 of their papers we have counts for
3 papers
Can strong structural encoding reduce the importance of Message Passing?
Floor Eijkelboom, Erik Bekkers, Michael Bronstein +1
The most prevalent class of neural networks operating on graphs are message passing neural networks (MPNNs), in which the representation of a node is updated iteratively by aggrega…
DRew: Dynamically Rewired Message Passing with Delay
Benjamin Gutteridge, Xiaowen Dong, Michael Bronstein +1
Message passing neural networks (MPNNs) have been shown to suffer from the phenomenon of over-squashing that causes poor performance for tasks relying on long-range interactions. T…
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero +3
Message Passing Neural Networks (MPNNs) are instances of Graph Neural Networks that leverage the graph to send messages over the edges. This inductive bias leads to a phenomenon kn…