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researcher

A. Marques

23 papers hereh-index 344.5k citations159 works total

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

author position
  • sole author1
  • first author2
  • middle author14
  • last author6

Across the 23 of 23 papers where every author was matched, so the position is known.

fields
  • eess.SP11
  • cs.LG4
  • cs.IT3
  • cs.AI1
  • cs.NI1
  • cs.SI1
same name
  • A. Marques — 2 papers
  • A. Marques — 2 papers, h 11
  • A. Marques — 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
20092022
most citedGraph-signal Reconstruction and Blind Deconvolution for Structured Inputs

21 citations · 29 across the 9 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2020

Tensor Graph Convolutional Networks for Multi-relational and Robust Learning

Vassilis N. Ioannidis, Antonio G. Marques, Georgios B. Giannakis

The era of "data deluge" has sparked renewed interest in graph-based learning methods and their widespread applications ranging from sociology and biology to transportation and com…

cs.LG2018

A Recurrent Graph Neural Network for Multi-Relational Data

Vassilis N. Ioannidis, Antonio G. Marques, Georgios B. Giannakis

The era of data deluge has sparked the interest in graph-based learning methods in a number of disciplines such as sociology, biology, neuroscience, or engineering. In this paper,…

cs.LG2018

Median activation functions for graph neural networks

Luana Ruiz, Fernando Gama, Antonio G. Marques +1

Graph neural networks (GNNs) have been shown to replicate convolutional neural networks' (CNNs) superior performance in many problems involving graphs. By replacing regular convolu…

cs.LG2018

MIMO Graph Filters for Convolutional Neural Networks

Fernando Gama, Antonio G. Marques, Alejandro Ribeiro +1

Superior performance and ease of implementation have fostered the adoption of Convolutional Neural Networks (CNNs) for a wide array of inference and reconstruction tasks. CNNs impl…

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