36 citations · 206 across the 41 of their papers we have counts for
15 papers · 1 filter
Stable and Transferable Wireless Resource Allocation Policies via Manifold Neural Networks
Zhiyang Wang, Luana Ruiz, Mark Eisen +1
We consider the problem of resource allocation in large scale wireless networks. When contextualizing wireless network structures as graphs, we can model the limits of very large w…
Stability of Neural Networks on Manifolds to Relative Perturbations
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Graph Neural Networks (GNNs) show impressive performance in many practical scenarios, which can be largely attributed to their stability properties. Empirically, GNNs can scale wel…
Quiver Signal Processing (QSP)
Alejandro Parada-Mayorga, Hans Riess, Alejandro Ribeiro +1
In this paper we state the basics for a signal processing framework on quiver representations. A quiver is a directed graph and a quiver representation is an assignment of vector s…
Discriminability of Single-Layer Graph Neural Networks
Samuel Pfrommer, Fernando Gama, Alejandro Ribeiro
Network data can be conveniently modeled as a graph signal, where data values are assigned to the nodes of a graph describing the underlying network topology. Successful learning f…
Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks
Luana Ruiz, Fernando Gama, Alejandro Ribeiro +1
Graph convolutional neural networks (GCNNs) learn compositional representations from network data by nesting linear graph convolutions into nonlinearities. In this work, we approac…
Graph-Adaptive Activation Functions for Graph Neural Networks
Bianca Iancu, Luana Ruiz, Alejandro Ribeiro +1
Activation functions are crucial in graph neural networks (GNNs) as they allow defining a nonlinear family of functions to capture the relationship between the input graph data and…