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Graph theory isn’t enough. The mathematical language for talking ... These are, effectively, hypergraphs viewed through the framework of topology. Neural networks, which fall into the general category ...

Expect to hear increasing buzz around graph neural network use cases among hyperscalers in the coming year. Behind the scenes, these are already replacing existing recommendation systems and traveling ...

To make sense of this, graph neural networks (GNNs) are often applied ... flouting the “Dunbar’s number” sociological theory that any one person can only have a certain number of friends ...

But as mobile hardware advances, Machine Learning (ML) techniques, particularly Graph Neural Networks (GNNs), are emerging as a powerful, efficient alternative to emulate physics on mobile. GNNs are ...

It’s often assumed that Dijkstra’s algorithm, or the A* graph traversal algorithm is used, but the reality is that although these pure graph theory algorithms ... of a network clear, but ...

Besides computer science, this type of optimization problem has implications for modeling the precise networks of chemical ... Borgs's prior university labors on graph theory and phase transitions ...

But in theory ... "The graph isomorphism problem does not seem hard, but we somehow can't yet prove that it's easy." Graphs ...