most citedSpectral Zooming and Resolution Limits of Spatial Spectral Compressive Spectral Imagers

11 citations · 11 across the 1 of their papers we have counts for

collaborators

5 papers

cs.LG2020

Stability of Algebraic Neural Networks to Small Perturbations

Alejandro Parada-Mayorga, Alejandro Ribeiro

Algebraic neural networks (AlgNNs) are composed of a cascade of layers each one associated to and algebraic signal model, and information is mapped between layers by means of a non…

eess.SP2020

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…

cs.LG2020

Graphon Pooling in Graph Neural Networks

Alejandro Parada-Mayorga, Luana Ruiz, Alejandro Ribeiro

Graph neural networks (GNNs) have been used effectively in different applications involving the processing of signals on irregular structures modeled by graphs. Relying on the use…

eess.IV201811 cited

Spectral Zooming and Resolution Limits of Spatial Spectral Compressive Spectral Imagers

Edgar Salazar, Alejandro Parada-Mayorga, Gonzalo R. Arce

The recently introduced Spatial Spectral Compressive Spectral Imager (SSCSI) has been proposed as an alternative to carry out spatial and spectral coding using a binary on-off code…

eess.SP2018

Blue-Noise Sampling on Graphs

Alejandro Parada-Mayorga, Daniel L. Lau, Jhony H. Giraldo +1

In the area of graph signal processing, a graph is a set of nodes arbitrarily connected by weighted links; a graph signal is a set of scalar values associated with each node; and s…