Deep learning on giant graphs

Simple scalable graph neural networks

One of the challenges that have so far precluded the wide adoption of graph neural networks in industrial applications is the difficulty to scale them to large graphs such as the Twitter follow graph. The interdependence between nodes makes the decomposition of the loss function into individual nodes’ contributions

Michael Bronstein
12 min readAug 8, 2020

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