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researcher

Alejandro Ribeiro

114 papers hereh-index 6415.8k citations335 works total

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

author position
  • middle author24
  • last author87

Across the 111 of 114 papers where every author was matched, so the position is known.

fields
  • cs.LG30
  • math.OC30
  • cs.RO13
  • cs.SI10
  • eess.SP10
  • cs.IT7
same name
  • Alejandro Ribeiro — 123 papers, h 30
  • Alejandro Ribeiro — 14 papers, h 4
  • Alejandro Ribeiro — 8 papers, h 1
  • Alejandro Ribeiro — 7 papers, h 3
  • Alejandro Ribeiro — 5 papers, h 4
  • Alejandro Ribeiro — 5 papers, h 4

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
20112023
most citedLearning Decentralized Controllers for Robot Swarms with Graph Neural Networks

410 citations · 4.5k across the 91 of their papers we have counts for

collaborators
Showing 2015 · cs.SIShow all

4 papers · 2 filters

cs.SI2015★ 102 cited

Reconstruction of Graph Signals through Percolation from Seeding Nodes

Santiago Segarra, Antonio G. Marques, Geert Leus +1

New schemes to recover signals defined in the nodes of a graph are proposed. Our focus is on reconstructing bandlimited graph signals, which are signals that admit a sparse represe…

cs.SI2015★ 1 cited

Persistent Homology Lower Bounds on High Order Network Distances

Weiyu Huang, Alejandro Ribeiro

High order networks are weighted hypergraphs col- lecting relationships between elements of tuples, not necessarily pairs. Valid metric distances between high order networks have b…

cs.SI2015★ 15 cited

Metrics in the Space of High Order Networks

Weiyu Huang, Alejandro Ribeiro

This paper presents methods to compare high order networks, defined as weighted complete hypergraphs collecting relationship functions between elements of tuples. They can be consi…

cs.SI2015★ 297 cited

Sampling of graph signals with successive local aggregations

Antonio G. Marques, Santiago Segarra, Geert Leus +1

A new scheme to sample signals defined in the nodes of a graph is proposed. The underlying assumption is that such signals admit a sparse representation in a frequency domain relat…

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