Delayed Message Passing

Dynamically Rewired Delayed Message Passing GNNs

Message-passing graph neural networks (MPNNs) tend to suffer from the phenomenon of over-squashing, causing performance deterioration for tasks relying on long-range interactions. This can be largely attributed to message passing only occurring locally, over a node’s immediate neighbours. Traditional static graph…

Michael Bronstein
9 min readJun 19, 2023

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DeepMind Professor of AI @Oxford. Serial startupper. ML for graphs, biochemistry, drug design, and animal communication.