3 papers
cs.LG2024
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
Jiong Zhu, Gaotang Li, Yao-An Yang +3
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…
cs.LG2023
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks
Gaotang Li, Marlena Duda, Xiang Zhang +2
Brain graphs, which model the structural and functional relationships between brain regions, are crucial in neuroscientific and clinical applications involving graph classification…
cs.LG2023
Tackling Size Generalization of Graph Neural Networks on Biological Data from a Spectral Perspective
Gaotang Li, Danai Koutra, Yujun Yan
We address the key challenge of size-induced distribution shifts in graph neural networks (GNNs) and their impact on the generalization of GNNs to larger graphs. Existing literatur…