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 ...

A mathematical function is a formula that takes an input, x, applies a set of calculations to it, and produces an output called y. By calculating a function at a large number of set intervals, it is ...

We develop parametric classes of covariance functions on linear networks and their extension to graphs with Euclidean edges, that is, graphs with edges viewed as line segments or more general sets ...