In this work, we proposed a novel and general method to construct tight
...
The nature of heterophilous graphs is significantly different with that ...
In this paper, we investigate in detail the structures of the variationa...
In this paper, we develop a general theoretical framework for constructi...
Graph representation learning has many real-world applications, from
sup...
Based on hierarchical partitions, we provide the construction of Haar-ty...
Deep Graph Neural Networks (GNNs) are instrumental in graph classificati...
Graph Neural Networks (GNNs) have become a topic of intense research rec...