Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2408.11370
Cited By
Graph Classification via Reference Distribution Learning: Theory and Practice
21 August 2024
Zixiao Wang
Jicong Fan
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Graph Classification via Reference Distribution Learning: Theory and Practice"
24 / 24 papers shown
Title
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
Samantha Chen
Sunhyuk Lim
Facundo Mémoli
Qingsong Wang
Yusu Wang
CoGe
52
18
0
05 Feb 2022
Graph Contrastive Learning Automated
Yuning You
Tianlong Chen
Yang Shen
Zhangyang Wang
76
476
0
10 Jun 2021
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
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
Renjie Liao
R. Urtasun
R. Zemel
55
90
0
14 Dec 2020
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
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
Vikas Garg
Stefanie Jegelka
Tommi Jaakkola
GNN
94
313
0
14 Feb 2020
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
Fan-Yun Sun
Jordan Hoffmann
Vikas Verma
Jian Tang
SSL
143
862
0
31 Jul 2019
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?
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
Titouan Vayer
Laetitia Chapel
Rémi Flamary
R. Tavenard
Nicolas Courty
OT
63
273
0
23 May 2018
Computational Optimal Transport
Gabriel Peyré
Marco Cuturi
OT
217
2,147
0
01 Mar 2018
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
Peter L. Bartlett
Dylan J. Foster
Matus Telgarsky
ODL
202
1,217
0
26 Jun 2017
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
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
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
Thomas Kipf
Max Welling
GNN
SSL
617
29,051
0
09 Sep 2016
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
Mathias Niepert
Mohamed Ahmed
Konstantin Kutzkov
GNN
SSL
135
2,154
0
17 May 2016
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
Marco Cuturi
OT
212
4,259
0
04 Jun 2013
1