87 citations · 90 across the 5 of their papers we have counts for
4 papers · 1 filter
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality
Joshua Southern, Yam Eitan, Guy Bar-Shalom +3
Subgraph GNNs have emerged as promising architectures that overcome the expressiveness limitations of Graph Neural Networks (GNNs) by processing bags of subgraphs. Despite their co…
Understanding Virtual Nodes: Oversquashing and Node Heterogeneity
Joshua Southern, Francesco Di Giovanni, Michael Bronstein +1
While message passing neural networks (MPNNs) have convincing success in a range of applications, they exhibit limitations such as the oversquashing problem and their inability to…
Curvature Filtrations for Graph Generative Model Evaluation
Joshua Southern, Jeremy Wayland, Michael Bronstein +1
Graph generative model evaluation necessitates understanding differences between graphs on the distributional level. This entails being able to harness salient attributes of graphs…
A Bayesian Deep Learning Framework for End-To-End Prediction of Emotion from Heartbeat
Ross Harper, Joshua Southern
Automatic prediction of emotion promises to revolutionise human-computer interaction. Recent trends involve fusion of multiple data modalities - audio, visual, and physiological -…