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Solving graph compression via optimal transport

Solving graph compression via optimal transport

29 May 2019
Vikas Garg
Tommi Jaakkola
    OT
ArXiv (abs)PDFHTML

Papers citing "Solving graph compression via optimal transport"

21 / 21 papers shown
Title
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
261
7,710
0
01 Oct 2018
Optimal Transport for Multi-source Domain Adaptation under Target Shift
Optimal Transport for Multi-source Domain Adaptation under Target Shift
I. Redko
Nicolas Courty
Rémi Flamary
D. Tuia
OOD
38
142
0
13 Mar 2018
Learning SMaLL Predictors
Learning SMaLL Predictors
Vikas Garg
O. Dekel
Lin Xiao
76
3
0
06 Mar 2018
Spectrally approximating large graphs with smaller graphs
Spectrally approximating large graphs with smaller graphs
Andreas Loukas
P. Vandergheynst
68
106
0
21 Feb 2018
Structured Optimal Transport
Structured Optimal Transport
David Alvarez-Melis
Tommi Jaakkola
Stefanie Jegelka
OT
59
71
0
17 Dec 2017
Large-Scale Optimal Transport and Mapping Estimation
Large-Scale Optimal Transport and Mapping Estimation
Vivien Seguy
B. Damodaran
Rémi Flamary
Nicolas Courty
Antoine Rolet
Mathieu Blondel
OT
77
249
0
07 Nov 2017
Joint Distribution Optimal Transportation for Domain Adaptation
Joint Distribution Optimal Transportation for Domain Adaptation
Nicolas Courty
Rémi Flamary
Amaury Habrard
A. Rakotomamonjy
OTOOD
88
569
0
24 May 2017
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on
  Graphs
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
M. Simonovsky
N. Komodakis
GNN
219
1,232
0
10 Apr 2017
Convolutional Neural Networks on Graphs with Fast Localized Spectral
  Filtering
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
M. Defferrard
Xavier Bresson
P. Vandergheynst
GNN
371
7,680
0
30 Jun 2016
Stochastic Optimization for Large-scale Optimal Transport
Stochastic Optimization for Large-scale Optimal Transport
Aude Genevay
Marco Cuturi
Gabriel Peyré
Francis R. Bach
OT
85
469
0
27 May 2016
The Multiscale Laplacian Graph Kernel
The Multiscale Laplacian Graph Kernel
Risi Kondor
Horace Pan
85
176
0
20 Mar 2016
Learning with a Wasserstein Loss
Learning with a Wasserstein Loss
Charlie Frogner
Chiyuan Zhang
H. Mobahi
Mauricio Araya-Polo
T. Poggio
79
602
0
17 Jun 2015
Propagation Kernels
Propagation Kernels
Marion Neumann
Roman Garnett
Christian Bauckhage
Kristian Kersting
75
263
0
13 Oct 2014
Spectral Networks and Locally Connected Networks on Graphs
Spectral Networks and Locally Connected Networks on Graphs
Joan Bruna
Wojciech Zaremba
Arthur Szlam
Yann LeCun
GNN
238
4,884
0
21 Dec 2013
Projection onto the probability simplex: An efficient algorithm with a
  simple proof, and an application
Projection onto the probability simplex: An efficient algorithm with a simple proof, and an application
Weiran Wang
M. A. Carreira-Perpiñán
91
287
0
06 Sep 2013
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation
  Distances
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
Marco Cuturi
OT
222
4,294
0
04 Jun 2013
Towards Ultrahigh Dimensional Feature Selection for Big Data
Towards Ultrahigh Dimensional Feature Selection for Big Data
Mingkui Tan
Ivor W. Tsang
Li Wang
153
154
0
24 Sep 2012
Subgraph Matching Kernels for Attributed Graphs
Subgraph Matching Kernels for Attributed Graphs
Nils Kriege
Petra Mutzel
73
279
0
27 Jun 2012
Statistical significance in high-dimensional linear models
Statistical significance in high-dimensional linear models
Peter Buhlmann
220
229
0
07 Feb 2012
Information-theoretic limits of selecting binary graphical models in
  high dimensions
Information-theoretic limits of selecting binary graphical models in high dimensions
N. Santhanam
Martin J. Wainwright
149
204
0
16 May 2009
Graph Kernels
Graph Kernels
S.V.N. Vishwanathan
Karsten Borgwardt
I. Kondor
N. Schraudolph
154
1,206
0
01 Jul 2008
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