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Graph Classification via Reference Distribution Learning: Theory and
  Practice

Graph Classification via Reference Distribution Learning: Theory and Practice

21 August 2024
Zixiao Wang
Jicong Fan
ArXivPDFHTML

Papers citing "Graph Classification via Reference Distribution Learning: Theory and Practice"

24 / 24 papers shown
Title
Structural Entropy Guided Graph Hierarchical Pooling
Structural Entropy Guided Graph Hierarchical Pooling
Junran Wu
Xueyuan Chen
Ke Xu
Shangzhe Li
55
76
0
26 Jun 2022
Weisfeiler-Lehman meets Gromov-Wasserstein
Weisfeiler-Lehman meets Gromov-Wasserstein
Samantha Chen
Sunhyuk Lim
Facundo Mémoli
Qingsong Wang
Yusu Wang
CoGe
52
18
0
05 Feb 2022
Graph Contrastive Learning Automated
Graph Contrastive Learning Automated
Yuning You
Tianlong Chen
Yang Shen
Zhangyang Wang
76
476
0
10 Jun 2021
Graph Self-Supervised Learning: A Survey
Graph Self-Supervised Learning: A Survey
Yixin Liu
Ming Jin
Shirui Pan
Chuan Zhou
Yu Zheng
Xiwei Xu
Philip S. Yu
SSL
103
566
0
27 Feb 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
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural
  Networks
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks
Renjie Liao
R. Urtasun
R. Zemel
55
90
0
14 Dec 2020
TUDataset: A collection of benchmark datasets for learning with graphs
TUDataset: A collection of benchmark datasets for learning with graphs
Christopher Morris
Nils M. Kriege
Franka Bause
Kristian Kersting
Petra Mutzel
Marion Neumann
233
820
0
16 Jul 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Weihua Hu
Matthias Fey
Marinka Zitnik
Yuxiao Dong
Hongyu Ren
Bowen Liu
Michele Catasta
J. Leskovec
303
2,730
0
02 May 2020
Generalization and Representational Limits of Graph Neural Networks
Generalization and Representational Limits of Graph Neural Networks
Vikas Garg
Stefanie Jegelka
Tommi Jaakkola
GNN
94
313
0
14 Feb 2020
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph
  Representations
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Ekagra Ranjan
Soumya Sanyal
Partha P. Talukdar
GNN
165
333
0
18 Nov 2019
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation
  Learning via Mutual Information Maximization
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
Fan-Yun Sun
Jordan Hoffmann
Vikas Verma
Jian Tang
SSL
143
862
0
31 Jul 2019
Provably Powerful Graph Networks
Provably Powerful Graph Networks
Haggai Maron
Heli Ben-Hamu
Hadar Serviansky
Y. Lipman
118
579
0
27 May 2019
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
238
7,642
0
01 Oct 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
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
479
20,138
0
30 Oct 2017
Spectrally-normalized margin bounds for neural networks
Spectrally-normalized margin bounds for neural networks
Peter L. Bartlett
Dylan J. Foster
Matus Telgarsky
ODL
202
1,217
0
26 Jun 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
503
15,232
0
07 Jun 2017
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
593
7,443
0
04 Apr 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
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
617
29,051
0
09 Sep 2016
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
342
7,650
0
30 Jun 2016
Learning Convolutional Neural Networks for Graphs
Learning Convolutional Neural Networks for Graphs
Mathias Niepert
Mohamed Ahmed
Konstantin Kutzkov
GNN
SSL
135
2,154
0
17 May 2016
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
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