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 ...

In this paper we develop a generalized partial linear model for longitudinal data. In the model, we allow the link and baseline functions to be unknown. We explicitly express the estimators of ...

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 ...

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 ...

Google DeepMind, launched an AI model that can create highly detailed maps of Earth to help scientists understand environmental changes. Satellites orbiting Earth to gather images and measurements of ...