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 ...

Google published details of a new kind of AI based on graphs called a Graph Foundation Model (GFM) that generalizes to previously unseen graphs and delivers a three to forty times boost in precision ...

Smoothness penalties are efficient regularization and dimension reduction tools for functional regressions. However, for spiky functional data observed on a dense grid, the coefficient function in a ...

What if instead of defining a mesh as a series of vertices and edges in a 3D space, you could describe it as a single function? The easiest function would return the signed distance to the closest ...

If you are looking to improve your financial modelling skills when using Microsoft Excel spreadsheets you might be interested in this quick overview guide that provides an in-depth exploration of the ...