91 citations · 349 across the 17 of their papers we have counts for
4 papers · 2 filters
Elastic Graph Neural Networks
Xiaorui Liu, Wei Jin, Yao Ma +5
While many existing graph neural networks (GNNs) have been proven to perform -based graph smoothing that enforces smoothness globally, in this work we aim to further enhanc…
Is Homophily a Necessity for Graph Neural Networks?
Yao Ma, Xiaorui Liu, Neil Shah +1
Graph neural networks (GNNs) have shown great prowess in learning representations suitable for numerous graph-based machine learning tasks. When applied to semi-supervised node cla…
Automated Self-Supervised Learning for Graphs
Wei Jin, Xiaorui Liu, Xiangyu Zhao +3
Graph self-supervised learning has gained increasing attention due to its capacity to learn expressive node representations. Many pretext tasks, or loss functions have been designe…
Graph Feature Gating Networks
Wei Jin, Xiaorui Liu, Yao Ma +3
Graph neural networks (GNNs) have received tremendous attention due to their power in learning effective representations for graphs. Most GNNs follow a message-passing scheme where…