On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
Heterophily, or the tendency of connected nodes in networks to have different class labels or
dissimilar features, has been identified as challenging for many Graph Neural Network …
dissimilar features, has been identified as challenging for many Graph Neural Network …
Advancing Graph Neural Networks for Complex Data: A Perspective Beyond Homophily
J Zhu - 2024 - deepblue.lib.umich.edu
Graph Neural Networks (GNNs) have demonstrated significant potential in extending the
empirical success of deep learning from Euclidean spaces to non-Euclidean, graph …
empirical success of deep learning from Euclidean spaces to non-Euclidean, graph …