Abstract: We propose a notion of universality for graph neural networks (GNNs) in the large random graphs limit, tailored for node-level tasks. When graphs are drawn from a latent space model, or from ...

This is a preview. Log in through your library . Abstract Many data are suitably modeled by functions consisting of straight-line segments. These functions may be called piecewise-linear. Smooth ...

This is a preview. Log in through your library . Abstract In recent times there occur situations, especially in estimation problems in certain stochastic processes, in which the limit of the suitably ...