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Phase transition in the detection of modules in sparse networks

Phase transition in the detection of modules in sparse networks

Physical Review Letters (PRL), 2011
6 February 2011
A. Decelle
Florent Krzakala
Cristopher Moore
Lenka Zdeborová
ArXiv (abs)PDFHTML

Papers citing "Phase transition in the detection of modules in sparse networks"

30 / 30 papers shown
Learning from higher-order statistics, efficiently: hypothesis tests,
  random features, and neural networks
Learning from higher-order statistics, efficiently: hypothesis tests, random features, and neural networks
Eszter Székely
Lorenzo Bardone
Federica Gerace
Sebastian Goldt
436
3
0
22 Dec 2023
NISQ-ready community detection based on separation-node identification
NISQ-ready community detection based on separation-node identification
Jonas Stein
Dominik Ott
Jonas Nüßlein
David Bucher
Mirco Schoenfeld
Sebastian Feld
256
5
0
30 Dec 2022
Dense Hebbian neural networks: a replica symmetric picture of supervised
  learning
Dense Hebbian neural networks: a replica symmetric picture of supervised learningSocial Science Research Network (SSRN), 2022
E. Agliari
L. Albanese
Francesco Alemanno
Andrea Alessandrelli
Adriano Barra
F. Giannotti
Daniele Lotito
D. Pedreschi
306
23
0
25 Nov 2022
Descriptive vs. inferential community detection in networks: pitfalls,
  myths, and half-truths
Descriptive vs. inferential community detection in networks: pitfalls, myths, and half-truths
Tiago P. Peixoto
643
57
0
30 Nov 2021
Gaussian-Spherical Restricted Boltzmann Machines
Gaussian-Spherical Restricted Boltzmann Machines
A. Decelle
Cyril Furtlehner
190
8
0
31 Oct 2019
Subexponential-Time Algorithms for Sparse PCA
Subexponential-Time Algorithms for Sparse PCAFoundations of Computational Mathematics (FoCM), 2019
Yunzi Ding
Dmitriy Kunisky
Alexander S. Wein
Afonso S. Bandeira
627
75
0
26 Jul 2019
How to iron out rough landscapes and get optimal performances: Averaged
  Gradient Descent and its application to tensor PCA
How to iron out rough landscapes and get optimal performances: Averaged Gradient Descent and its application to tensor PCA
Giulio Biroli
C. Cammarota
F. Ricci-Tersenghi
354
33
0
29 May 2019
Unsupervised Community Detection with Modularity-Based Attention Model
Unsupervised Community Detection with Modularity-Based Attention Model
Ivan Lobov
Sergey Ivanov
167
11
0
20 May 2019
The Kikuchi Hierarchy and Tensor PCA
The Kikuchi Hierarchy and Tensor PCA
Alexander S. Wein
A. Alaoui
Cristopher Moore
428
76
0
08 Apr 2019
A Map Equation with Metadata: Varying the Role of Attributes in
  Community Detection
A Map Equation with Metadata: Varying the Role of Attributes in Community Detection
Scott Emmons
P. Mucha
293
23
0
24 Oct 2018
Asymptotic uncertainty quantification for communities in sparse planted
  bi-section models
Asymptotic uncertainty quantification for communities in sparse planted bi-section models
B. Kleijn
J. van Waaij
404
0
0
22 Oct 2018
Community detection in networks without observing edges
Community detection in networks without observing edges
Till Hoffmann
Leto Peel
R. Lambiotte
N. Jones
205
55
0
18 Aug 2018
Universality of the stochastic block model
Universality of the stochastic block model
Jean-Gabriel Young
G. St‐Onge
P. Desrosiers
Louis J. Dubé
284
32
0
11 Jun 2018
Reconstructing networks with unknown and heterogeneous errors
Reconstructing networks with unknown and heterogeneous errors
Tiago P. Peixoto
341
94
0
09 Jun 2018
Structured networks and coarse-grained descriptions: a dynamical
  perspective
Structured networks and coarse-grained descriptions: a dynamical perspective
Michael T. Schaub
Jean-Charles Delvenne
R. Lambiotte
Mauricio Barahona
186
6
0
17 Apr 2018
Stochastic Block Models with Multiple Continuous Attributes
Stochastic Block Models with Multiple Continuous Attributes
Natalie Stanley
T. Bonacci
Roland Kwitt
Marc Niethammer
P. Mucha
236
71
0
07 Mar 2018
Algorithmic detectability threshold of the stochastic block model
Algorithmic detectability threshold of the stochastic block modelPhysical Review E (PRE), 2017
T. Kawamoto
248
17
0
24 Oct 2017
The Stochastic Replica Approach to Machine Learning: Stability and
  Parameter Optimization
The Stochastic Replica Approach to Machine Learning: Stability and Parameter Optimization
Patrick Chao
T. Mazaheri
Bo Sun
N. B. Weingartner
Z. Nussinov
341
5
0
18 Aug 2017
A network approach to topic models
A network approach to topic models
Martin Gerlach
Tiago P. Peixoto
E. Altmann
BDL
344
227
0
04 Aug 2017
Bayesian stochastic blockmodeling
Bayesian stochastic blockmodeling
Tiago P. Peixoto
888
231
0
29 May 2017
Statistical test for detecting community structure in real-valued
  edge-weighted graphs
Statistical test for detecting community structure in real-valued edge-weighted graphsPLoS ONE (PLOS ONE), 2016
Tomoki Tokuda
258
10
0
13 Oct 2016
Community Detection Algorithm Combining Stochastic Block Model and
  Attribute Data Clustering
Community Detection Algorithm Combining Stochastic Block Model and Attribute Data Clustering
Shuníchi Kataoka
Takuto Kobayashi
Muneki Yasuda
Kazuyuki Tanaka
238
3
0
21 Jul 2016
Inference of hidden structures in complex physical systems by
  multi-scale clustering
Inference of hidden structures in complex physical systems by multi-scale clustering
Z. Nussinov
P. Ronhovde
Dandan Hu
S. Chakrabarty
M. Sahu
Bo Sun
Nicholas A. Mauro
K. Sahu
AI4CE
296
14
0
05 Mar 2015
Detecting change points in the large-scale structure of evolving
  networks
Detecting change points in the large-scale structure of evolving networksAAAI Conference on Artificial Intelligence (AAAI), 2014
Leto Peel
A. Clauset
342
250
0
05 Mar 2014
Phase Transitions in Community Detection: A Solvable Toy Model
Phase Transitions in Community Detection: A Solvable Toy Model
Greg Ver Steeg
Cristopher Moore
Aram Galstyan
A. Allahverdyan
198
9
0
02 Dec 2013
Joint modeling of multiple time series via the beta process with
  application to motion capture segmentation
Joint modeling of multiple time series via the beta process with application to motion capture segmentation
E. Fox
M. C. Hughes
Erik B. Sudderth
Sai Li
389
100
0
22 Aug 2013
Spectral redemption: clustering sparse networks
Spectral redemption: clustering sparse networksProceedings of the National Academy of Sciences of the United States of America (PNAS), 2013
Florent Krzakala
Cristopher Moore
Elchanan Mossel
Joe Neeman
Allan Sly
Lenka Zdeborová
Pan Zhang
618
653
0
24 Jun 2013
Adapting the Stochastic Block Model to Edge-Weighted Networks
Adapting the Stochastic Block Model to Edge-Weighted Networks
Christopher Aicher
David Bau
A. Clauset
303
78
0
24 May 2013
Parsimonious module inference in large networks
Parsimonious module inference in large networks
Tiago P. Peixoto
MoE
613
213
0
19 Dec 2012
A Replica Inference Approach to Unsupervised Multi-Scale Image
  Segmentation
A Replica Inference Approach to Unsupervised Multi-Scale Image Segmentation
Dandan Hu
P. Ronhovde
Z. Nussinov
155
35
0
28 Jun 2011
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