Abstract: We delve into the issue of node classification within graphs, specifically reevaluating the concept of neighborhood aggregation, which is a fundamental component in graph neural networks ...
Abstract: Self-supervised graph embedding has emerged as a powerful paradigm for learning expressive node and graph representations without relying on real labels. Several recent self-supervised ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results