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Semi-relaxed Gromov-Wasserstein divergence with applications on graphs

Semi-relaxed Gromov-Wasserstein divergence with applications on graphs

6 October 2021
Cédric Vincent-Cuaz
Rémi Flamary
Marco Corneli
Titouan Vayer
Nicolas Courty
    OT
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Papers citing "Semi-relaxed Gromov-Wasserstein divergence with applications on graphs"

34 / 34 papers shown
Title
Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights
Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights
Zeqin Yang
Weilin Chen
Ruichu Cai
Yuguang Yan
Zhifeng Hao
Zhipeng Yu
Zhichao Zou
Jixing Xu
Zhen Peng
Jiecheng Guo
114
3
0
27 Jun 2024
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
352
1,148
0
27 Apr 2021
Online Graph Dictionary Learning
Online Graph Dictionary Learning
Cédric Vincent-Cuaz
Titouan Vayer
Rémi Flamary
Marco Corneli
Nicolas Courty
48
46
0
12 Feb 2021
Learning Graphons via Structured Gromov-Wasserstein Barycenters
Learning Graphons via Structured Gromov-Wasserstein Barycenters
Hongteng Xu
Dixin Luo
Lawrence Carin
H. Zha
84
31
0
10 Dec 2020
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and
  Relaxation
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation
Thibault Séjourné
François-Xavier Vialard
Gabriel Peyré
OT
62
70
0
09 Sep 2020
Generalized Spectral Clustering via Gromov-Wasserstein Learning
Generalized Spectral Clustering via Gromov-Wasserstein Learning
Samir Chowdhury
Tom Needham
43
54
0
07 Jun 2020
Partial Optimal Transport with Applications on Positive-Unlabeled
  Learning
Partial Optimal Transport with Applications on Positive-Unlabeled Learning
Laetitia Chapel
Mokhtar Z. Alaya
Gilles Gasso
OT
31
8
0
19 Feb 2020
Gromov-Wasserstein Factorization Models for Graph Clustering
Gromov-Wasserstein Factorization Models for Graph Clustering
Hongteng Xu
59
49
0
19 Nov 2019
GOT: An Optimal Transport framework for Graph comparison
GOT: An Optimal Transport framework for Graph comparison
Hermina Petric Maretic
Mireille El Gheche
Giovanni Chierchia
P. Frossard
OT
129
119
0
05 Jun 2019
Wasserstein Weisfeiler-Lehman Graph Kernels
Wasserstein Weisfeiler-Lehman Graph Kernels
Matteo Togninalli
M. Ghisu
Felipe Llinares-López
Bastian Rieck
Karsten Borgwardt
61
199
0
04 Jun 2019
Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
Hongteng Xu
Dixin Luo
Lawrence Carin
57
195
0
18 May 2019
Graph U-Nets
Graph U-Nets
Hongyang Gao
Shuiwang Ji
AI4CE
SSL
SSeg
GNN
127
1,086
0
11 May 2019
A Survey on Graph Kernels
A Survey on Graph Kernels
Nils M. Kriege
Fredrik D. Johansson
Christopher Morris
133
418
0
28 Mar 2019
GAP: Generalizable Approximate Graph Partitioning Framework
GAP: Generalizable Approximate Graph Partitioning Framework
Azade Nazi
W. Hang
Anna Goldie
Sujith Ravi
Azalia Mirhoseini
63
61
0
02 Mar 2019
Gromov-Wasserstein Learning for Graph Matching and Node Embedding
Gromov-Wasserstein Learning for Graph Matching and Node Embedding
Hongteng Xu
Dixin Luo
H. Zha
Lawrence Carin
89
259
0
17 Jan 2019
A Comprehensive Survey on Graph Neural Networks
A Comprehensive Survey on Graph Neural Networks
Zonghan Wu
Shirui Pan
Fengwen Chen
Guodong Long
Chengqi Zhang
Philip S. Yu
FaML
GNN
AI4TS
AI4CE
754
8,526
0
03 Jan 2019
Fused Gromov-Wasserstein distance for structured objects: theoretical
  foundations and mathematical properties
Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties
David Tellez
G. Litjens
J. A. van der Laak
R. Tavenard
F. Ciompi
OT
75
127
0
07 Nov 2018
Mean-field theory of graph neural networks in graph partitioning
Mean-field theory of graph neural networks in graph partitioning
T. Kawamoto
Masashi Tsubaki
T. Obuchi
72
58
0
29 Oct 2018
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Christopher Morris
Martin Ritzert
Matthias Fey
William L. Hamilton
J. E. Lenssen
Gaurav Rattan
Martin Grohe
GNN
192
1,634
0
04 Oct 2018
Bayesian Semi-supervised Learning with Graph Gaussian Processes
Bayesian Semi-supervised Learning with Graph Gaussian Processes
Yin Cheng Ng
Nicolo Colombo
Ricardo M. A. Silva
BDL
65
90
0
12 Sep 2018
Hierarchical Graph Representation Learning with Differentiable Pooling
Hierarchical Graph Representation Learning with Differentiable Pooling
Rex Ying
Jiaxuan You
Christopher Morris
Xiang Ren
William L. Hamilton
J. Leskovec
GNN
292
2,146
0
22 Jun 2018
Optimal Transport for structured data with application on graphs
Optimal Transport for structured data with application on graphs
Titouan Vayer
Laetitia Chapel
Rémi Flamary
R. Tavenard
Nicolas Courty
OT
63
273
0
23 May 2018
Computational Optimal Transport
Computational Optimal Transport
Gabriel Peyré
Marco Cuturi
OT
217
2,147
0
01 Mar 2018
DS*: Tighter Lifting-Free Convex Relaxations for Quadratic Matching
  Problems
DS*: Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems
Florian Bernard
Christian Theobalt
Michael Möller
78
43
0
29 Nov 2017
Wasserstein Dictionary Learning: Optimal Transport-based unsupervised
  non-linear dictionary learning
Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning
M. Schmitz
Matthieu Heitz
Nicolas Bonneel
Fred-Maurice Ngole-Mboula
D. Coeurjolly
Marco Cuturi
Gabriel Peyré
Jean-Luc Starck
OT
57
136
0
07 Aug 2017
Distance Metric Learning using Graph Convolutional Networks: Application
  to Functional Brain Networks
Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks
S. Ktena
Sarah Parisot
Enzo Ferrante
Martin Rajchl
M. J. Lee
Ben Glocker
Daniel Rueckert
GNN
155
194
0
07 Mar 2017
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
805
3,281
0
24 Nov 2016
Optimal spectral transportation with application to music transcription
Optimal spectral transportation with application to music transcription
Rémi Flamary
Cédric Févotte
Nicolas Courty
Valentin Emiya
OT
46
34
0
30 Sep 2016
Convergence Rate of Frank-Wolfe for Non-Convex Objectives
Convergence Rate of Frank-Wolfe for Non-Convex Objectives
Simon Lacoste-Julien
71
195
0
01 Jul 2016
Adjusting for Chance Clustering Comparison Measures
Adjusting for Chance Clustering Comparison Measures
Simone Romano
X. Nguyen
James Bailey
Karin Verspoor
42
182
0
03 Dec 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,039
0
22 Dec 2014
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation
  Distances
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
Marco Cuturi
OT
212
4,259
0
04 Jun 2013
The Emerging Field of Signal Processing on Graphs: Extending
  High-Dimensional Data Analysis to Networks and Other Irregular Domains
The Emerging Field of Signal Processing on Graphs: Extending High-Dimensional Data Analysis to Networks and Other Irregular Domains
D. Shuman
S. K. Narang
P. Frossard
Antonio Ortega
P. Vandergheynst
126
3,972
0
31 Oct 2012
Improved Graph Clustering
Improved Graph Clustering
Yudong Chen
Sujay Sanghavi
Huan Xu
194
190
0
11 Oct 2012
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