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Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement

12 March 2025
Huidong Liang
Haitz Sáez de Ocáriz Borde
Baskaran Sripathmanathan
Michael M. Bronstein
Xiaowen Dong
    GNN
ArXiv (abs)PDFHTML

Papers citing "Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement"

15 / 15 papers shown
Title
Improving the Effective Receptive Field of Message-Passing Neural Networks
Improving the Effective Receptive Field of Message-Passing Neural Networks
Shahaf E. Finder
Ron Shapira Weber
Moshe Eliasof
Oren Freifeld
Eran Treister
46
0
0
29 May 2025
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark
Jan Tönshoff
Martin Ritzert
Eran Rosenbluth
Martin Grohe
81
54
0
01 Sep 2023
A Survey on Oversmoothing in Graph Neural Networks
A Survey on Oversmoothing in Graph Neural Networks
T. Konstantin Rusch
Michael M. Bronstein
Siddhartha Mishra
91
213
0
20 Mar 2023
Influence-Based Mini-Batching for Graph Neural Networks
Influence-Based Mini-Batching for Graph Neural Networks
Johannes Gasteiger
Chao Qian
Stephan Günnemann
GNN
71
15
0
18 Dec 2022
Understanding over-squashing and bottlenecks on graphs via curvature
Understanding over-squashing and bottlenecks on graphs via curvature
Jake Topping
Francesco Di Giovanni
B. Chamberlain
Xiaowen Dong
M. Bronstein
108
448
0
29 Nov 2021
On the Bottleneck of Graph Neural Networks and its Practical
  Implications
On the Bottleneck of Graph Neural Networks and its Practical Implications
Uri Alon
Eran Yahav
GNN
93
694
0
09 Jun 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
309
2,746
0
02 May 2020
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
Hoang NT
Takanori Maehara
GNN
130
434
0
23 May 2019
Fast Graph Representation Learning with PyTorch Geometric
Fast Graph Representation Learning with PyTorch Geometric
Matthias Fey
J. E. Lenssen
3DHGNN3DPC
237
4,364
0
06 Mar 2019
Simplifying Graph Convolutional Networks
Simplifying Graph Convolutional Networks
Felix Wu
Tianyi Zhang
Amauri Souza
Christopher Fifty
Tao Yu
Kilian Q. Weinberger
GNN
246
3,182
0
19 Feb 2019
Representation Learning on Graphs with Jumping Knowledge Networks
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu
Chengtao Li
Yonglong Tian
Tomohiro Sonobe
Ken-ichi Kawarabayashi
Stefanie Jegelka
GNN
518
1,990
0
09 Jun 2018
Deeper Insights into Graph Convolutional Networks for Semi-Supervised
  Learning
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning
Qimai Li
Zhichao Han
Xiao-Ming Wu
GNNSSL
194
2,830
0
22 Jan 2018
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
514
15,319
0
07 Jun 2017
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
662
29,156
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
358
7,671
0
30 Jun 2016
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