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Structure-Preserving Sparsification Methods for Social Networks

Structure-Preserving Sparsification Methods for Social Networks

3 January 2016
M. Hamann
Gerd Lindner
Henning Meyerhenke
Christian Staudt
D. Wagner
ArXiv (abs)PDFHTML

Papers citing "Structure-Preserving Sparsification Methods for Social Networks"

6 / 6 papers shown
Title
On the Ability of Graph Neural Networks to Model Interactions Between
  Vertices
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Noam Razin
Tom Verbin
Nadav Cohen
149
11
0
29 Nov 2022
A Generic Graph Sparsification Framework using Deep Reinforcement
  Learning
A Generic Graph Sparsification Framework using Deep Reinforcement Learning
Ryan Wickman
Xiaofei Zhang
Weizi Li
OffRL
72
13
0
02 Dec 2021
Sparsistent filtering of comovement networks from high-dimensional data
Sparsistent filtering of comovement networks from high-dimensional data
A. Chakrabarti
A. Chakrabarti
26
0
0
22 Jan 2021
Single- and Multi-level Network Sparsification by Algebraic Distance
Single- and Multi-level Network Sparsification by Algebraic Distance
E. John
Ilya Safro
41
22
0
21 Jan 2016
Engineering Parallel Algorithms for Community Detection in Massive
  Networks
Engineering Parallel Algorithms for Community Detection in Massive Networks
Christian Staudt
Henning Meyerhenke
GNN
122
146
0
16 Apr 2013
Network Sampling: From Static to Streaming Graphs
Network Sampling: From Static to Streaming Graphs
Nesreen Ahmed
Jennifer Neville
Ramana Rao Kompella
94
271
0
14 Nov 2012
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