3 papers
cs.LG2025
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…
cs.HC2019
End-To-End Prediction of Emotion From Heartbeat Data Collected by a Consumer Fitness Tracker
Ross Harper, Joshua Southern
Automatic detection of emotion has the potential to revolutionize mental health and wellbeing. Recent work has been successful in predicting affect from unimodal electrocardiogram…
cs.LG2019
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 -…