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Alejandro Parada-Mayorga

University of Pennsylvania

7 papers hereh-index 10256 citations28 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author3

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • eess.SP4
  • cs.LG2
  • eess.IV1
affiliations
  • University of Pennsylvania
Homepage
same name
  • Alejandro Parada-Mayorga — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182022
most citedSpectral Zooming and Resolution Limits of Spatial Spectral Compressive Spectral Imagers

11 citations · 11 across the 3 of their papers we have counts for

collaborators
Showing eess.SPShow all

4 papers · 1 filter

eess.SP2022

Algebraic Convolutional Filters on Lie Group Algebras

Harshat Kumar, Alejandro Parada-Mayorga, Alejandro Ribeiro

Group convolutional neural networks are a useful tool for utilizing symmetries known to be in a signal; however, they require that the signal is defined on the group itself. Existi…

eess.SP2022

Learning with Multigraph Convolutional Filters

Landon Butler, Alejandro Parada-Mayorga, Alejandro Ribeiro

In this paper, we introduce a convolutional architecture to perform learning when information is supported on multigraphs. Exploiting algebraic signal processing (ASP), we propose…

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…

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.