Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...

Machine learning couldn’t be hotter, with several heavy hitters offering platforms aimed at seasoned data scientists and newcomers interested in working with neural networks. Among the more popular ...

Giulia Livieri sets out remarkable new research with results that clarify how learning works on complex graphs and how quickly any method (including Graph Convolutional Networks) can learn from them, ...