The growth in social media has exacerbated the threat of fake news to
in...
Out-of-distribution (OOD) generalization is an important issue for Graph...
This paper focuses on out-of-distribution generalization on graphs where...
Deep graph learning has achieved remarkable progresses in both business ...
Subgraph recognition aims at discovering a compressed substructure of a ...
As Graph Neural Networks (GNNs) are widely adopted in digital pathology,...
The emergence of Graph Convolutional Network (GCN) has greatly boosted t...
Given the input graph and its label/property, several key problems of gr...
Face verification aims at determining whether a pair of face images belo...