Efficiently and quickly chewing through one trillion edges of a complex graph is no longer in itself a standalone achievement, but doing so on a single node, albeit with some acceleration and ...

Graphs are a ubiquitous data structure and a universal language for representing objects and complex interactions. They can model a wide range of real-world systems, such as social networks, chemical ...

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Networks pervade our lives. Every day we use intricate networks of roads, railways, maritime routes and skyways traversed by commercial flights. They exist even beyond our immediate experience. Think ...

Graphs are widely used to represent complex relationships in everyday applications such as social networks, bioinformatics, and recommendation ...