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On spectral embedding performance and elucidating network structure in
  stochastic block model graphs

On spectral embedding performance and elucidating network structure in stochastic block model graphs

14 August 2018
Joshua Cape
M. Tang
Carey E. Priebe
ArXiv (abs)PDFHTML

Papers citing "On spectral embedding performance and elucidating network structure in stochastic block model graphs"

12 / 12 papers shown
Title
A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs
A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs
Luana Ruiz
Ningyuan Huang
Soledad Villar
85
5
0
06 Nov 2022
Ergodic Limits, Relaxations, and Geometric Properties of Random Walk
  Node Embeddings
Ergodic Limits, Relaxations, and Geometric Properties of Random Walk Node Embeddings
Christy Lin
D. Sussman
Prakash Ishwar
51
5
0
09 Sep 2021
Spectral clustering under degree heterogeneity: a case for the random
  walk Laplacian
Spectral clustering under degree heterogeneity: a case for the random walk Laplacian
Alexander Modell
Patrick Rubin-Delanchy
47
9
0
03 May 2021
Overlapping community detection in networks via sparse spectral
  decomposition
Overlapping community detection in networks via sparse spectral decomposition
Jesús Arroyo
Elizaveta Levina
82
4
0
20 Sep 2020
The multilayer random dot product graph
The multilayer random dot product graph
Andrew Jones
Patrick Rubin-Delanchy
105
38
0
20 Jul 2020
On spectral algorithms for community detection in stochastic blockmodel
  graphs with vertex covariates
On spectral algorithms for community detection in stochastic blockmodel graphs with vertex covariates
Cong Mu
A. Mele
Lingxin Hao
Joshua Cape
A. Athreya
Carey E. Priebe
62
11
0
04 Jul 2020
On Two Distinct Sources of Nonidentifiability in Latent Position Random
  Graph Models
On Two Distinct Sources of Nonidentifiability in Latent Position Random Graph Models
Joshua Agterberg
M. Tang
Carey E. Priebe
CML
88
10
0
31 Mar 2020
Limit theorems for out-of-sample extensions of the adjacency and
  Laplacian spectral embeddings
Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings
Keith D. Levin
Fred Roosta
M. Tang
Michael W. Mahoney
Carey E. Priebe
39
6
0
29 Sep 2019
Bayesian estimation of the latent dimension and communities in
  stochastic blockmodels
Bayesian estimation of the latent dimension and communities in stochastic blockmodels
Francesco Sanna Passino
N. Heard
BDL
51
25
0
06 Apr 2019
Simultaneous Dimensionality and Complexity Model Selection for Spectral
  Graph Clustering
Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering
Congyuan Yang
Carey E. Priebe
Youngser Park
D. Marchette
47
25
0
05 Apr 2019
On a 'Two Truths' Phenomenon in Spectral Graph Clustering
On a 'Two Truths' Phenomenon in Spectral Graph Clustering
Carey E. Priebe
Youngser Park
Joshua T. Vogelstein
John M. Conroy
V. Lyzinski
M. Tang
A. Athreya
Joshua Cape
Eric W. Bridgeford
92
72
0
23 Aug 2018
Analysis of spectral clustering algorithms for community detection: the
  general bipartite setting
Analysis of spectral clustering algorithms for community detection: the general bipartite setting
Zhixin Zhou
Arash A. Amini
119
97
0
12 Mar 2018
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