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On the equivalence between graph isomorphism testing and function
  approximation with GNNs

On the equivalence between graph isomorphism testing and function approximation with GNNs

29 May 2019
Zhengdao Chen
Soledad Villar
Lei Chen
Joan Bruna
ArXivPDFHTML

Papers citing "On the equivalence between graph isomorphism testing and function approximation with GNNs"

40 / 40 papers shown
Title
Repetition Makes Perfect: Recurrent Sum-GNNs Match Message Passing Limit
Repetition Makes Perfect: Recurrent Sum-GNNs Match Message Passing Limit
Eran Rosenbluth
Martin Grohe
19
0
0
01 May 2025
Learning Efficiency Meets Symmetry Breaking
Learning Efficiency Meets Symmetry Breaking
Yingbin Bai
Sylvie Thiébaux
Felipe Trevizan
32
0
0
28 Apr 2025
Optimality of Message-Passing Architectures for Sparse Graphs
Optimality of Message-Passing Architectures for Sparse Graphs
Aseem Baranwal
K. Fountoulakis
Aukosh Jagannath
70
11
0
10 Jan 2025
Graph Sampling for Scalable and Expressive Graph Neural Networks on Homophilic Graphs
Graph Sampling for Scalable and Expressive Graph Neural Networks on Homophilic Graphs
Haolin Li
Luana Ruiz
Luana Ruiz
32
0
0
22 Oct 2024
Theoretical Insights into Line Graph Transformation on Graph Learning
Theoretical Insights into Line Graph Transformation on Graph Learning
Fan Yang
Xingyue Huang
22
0
0
21 Oct 2024
Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal
  Inference in Networks
Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal Inference in Networks
Xiaojing Du
Feiyu Yang
Wentao Gao
Xiongren Chen
CML
19
1
0
13 Sep 2024
Revisiting Random Walks for Learning on Graphs
Revisiting Random Walks for Learning on Graphs
Jinwoo Kim
Olga Zaghen
Ayhan Suleymanzade
Youngmin Ryou
Seunghoon Hong
54
0
0
01 Jul 2024
KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning
KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning
Roman Bresson
Giannis Nikolentzos
G. Panagopoulos
Michail Chatzianastasis
Jun Pang
Michalis Vazirgiannis
60
42
0
26 Jun 2024
Efficient Graph Similarity Computation with Alignment Regularization
Efficient Graph Similarity Computation with Alignment Regularization
Wei Zhuo
Guang Tan
19
17
0
21 Jun 2024
Bundle Neural Networks for message diffusion on graphs
Bundle Neural Networks for message diffusion on graphs
Jacob Bamberger
Federico Barbero
Xiaowen Dong
Michael M. Bronstein
37
1
0
24 May 2024
Neighbour-level Message Interaction Encoding for Improved Representation
  Learning on Graphs
Neighbour-level Message Interaction Encoding for Improved Representation Learning on Graphs
Haimin Zhang
Min Xu
GNN
20
0
0
15 Apr 2024
A Survey of Graph Neural Networks in Real world: Imbalance, Noise,
  Privacy and OOD Challenges
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges
Wei Ju
Siyu Yi
Yifan Wang
Zhiping Xiao
Zhengyan Mao
...
Senzhang Wang
Xinwang Liu
Xiao Luo
Philip S. Yu
Ming Zhang
AI4CE
34
36
0
07 Mar 2024
CktGNN: Circuit Graph Neural Network for Electronic Design Automation
CktGNN: Circuit Graph Neural Network for Electronic Design Automation
Zehao Dong
Weidong Cao
Muhan Zhang
Dacheng Tao
Yixin Chen
Xuan Zhang
GNN
19
30
0
31 Aug 2023
The Expressive Power of Graph Neural Networks: A Survey
The Expressive Power of Graph Neural Networks: A Survey
Bingxue Zhang
Changjun Fan
Shixuan Liu
Kuihua Huang
Xiang Zhao
Jin-Yu Huang
Zhong Liu
40
19
0
16 Aug 2023
A graphon-signal analysis of graph neural networks
A graphon-signal analysis of graph neural networks
Ron Levie
24
16
0
25 May 2023
A Generalization of ViT/MLP-Mixer to Graphs
A Generalization of ViT/MLP-Mixer to Graphs
Xiaoxin He
Bryan Hooi
T. Laurent
Adam Perold
Yann LeCun
Xavier Bresson
22
88
0
27 Dec 2022
On the Ability of Graph Neural Networks to Model Interactions Between
  Vertices
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Noam Razin
Tom Verbin
Nadav Cohen
14
10
0
29 Nov 2022
Exponentially Improving the Complexity of Simulating the
  Weisfeiler-Lehman Test with Graph Neural Networks
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks
Anders Aamand
Justin Y. Chen
Piotr Indyk
Shyam Narayanan
R. Rubinfeld
Nicholas Schiefer
Sandeep Silwal
Tal Wagner
30
21
0
06 Nov 2022
Boosting the Cycle Counting Power of Graph Neural Networks with
  I$^2$-GNNs
Boosting the Cycle Counting Power of Graph Neural Networks with I2^22-GNNs
Yinan Huang
Xingang Peng
Jianzhu Ma
Muhan Zhang
76
46
0
22 Oct 2022
On Representing Linear Programs by Graph Neural Networks
On Representing Linear Programs by Graph Neural Networks
Ziang Chen
Jialin Liu
Xinshang Wang
Jian Lu
W. Yin
AI4CE
42
31
0
25 Sep 2022
Recipe for a General, Powerful, Scalable Graph Transformer
Recipe for a General, Powerful, Scalable Graph Transformer
Ladislav Rampášek
Mikhail Galkin
Vijay Prakash Dwivedi
A. Luu
Guy Wolf
Dominique Beaini
43
506
0
25 May 2022
Expressiveness and Approximation Properties of Graph Neural Networks
Expressiveness and Approximation Properties of Graph Neural Networks
Floris Geerts
Juan L. Reutter
11
64
0
10 Apr 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks
Christopher Morris
Gaurav Rattan
Sandra Kiefer
Siamak Ravanbakhsh
23
39
0
25 Mar 2022
Equivariant and Stable Positional Encoding for More Powerful Graph
  Neural Networks
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks
Hongya Wang
Haoteng Yin
Muhan Zhang
Pan Li
23
106
0
01 Mar 2022
Sign and Basis Invariant Networks for Spectral Graph Representation
  Learning
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
Derek Lim
Joshua Robinson
Lingxiao Zhao
Tess E. Smidt
S. Sra
Haggai Maron
Stefanie Jegelka
20
138
0
25 Feb 2022
A Short Tutorial on The Weisfeiler-Lehman Test And Its Variants
A Short Tutorial on The Weisfeiler-Lehman Test And Its Variants
Ningyuan Huang
Soledad Villar
14
60
0
18 Jan 2022
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural
  Networks
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks
Pál András Papp
Karolis Martinkus
Lukas Faber
Roger Wattenhofer
GNN
9
138
0
11 Nov 2021
Equivariant Subgraph Aggregation Networks
Equivariant Subgraph Aggregation Networks
Beatrice Bevilacqua
Fabrizio Frasca
Derek Lim
Balasubramaniam Srinivasan
Chen Cai
G. Balamurugan
M. Bronstein
Haggai Maron
22
174
0
06 Oct 2021
Reconstruction for Powerful Graph Representations
Reconstruction for Powerful Graph Representations
Leonardo Cotta
Christopher Morris
Bruno Ribeiro
AI4CE
120
78
0
01 Oct 2021
Scalars are universal: Equivariant machine learning, structured like
  classical physics
Scalars are universal: Equivariant machine learning, structured like classical physics
Soledad Villar
D. Hogg
Kate Storey-Fisher
Weichi Yao
Ben Blum-Smith
PINN
AI4CE
19
130
0
11 Jun 2021
Combinatorial optimization and reasoning with graph neural networks
Combinatorial optimization and reasoning with graph neural networks
Quentin Cappart
Didier Chételat
Elias Boutros Khalil
Andrea Lodi
Christopher Morris
Petar Velickovic
AI4CE
28
344
0
18 Feb 2021
Topological Graph Neural Networks
Topological Graph Neural Networks
Max Horn
E. Brouwer
Michael Moor
Yves Moreau
Bastian Alexander Rieck
Karsten M. Borgwardt
AI4CE
20
87
0
15 Feb 2021
Graph Neural Networks: Architectures, Stability and Transferability
Graph Neural Networks: Architectures, Stability and Transferability
Luana Ruiz
Fernando Gama
Alejandro Ribeiro
GNN
32
121
0
04 Aug 2020
The expressive power of kth-order invariant graph networks
The expressive power of kth-order invariant graph networks
Floris Geerts
123
37
0
23 Jul 2020
Graph Structure of Neural Networks
Graph Structure of Neural Networks
Jiaxuan You
J. Leskovec
Kaiming He
Saining Xie
GNN
6
136
0
13 Jul 2020
Can Graph Neural Networks Count Substructures?
Can Graph Neural Networks Count Substructures?
Zhengdao Chen
Lei Chen
Soledad Villar
Joan Bruna
GNN
14
319
0
10 Feb 2020
Graph Random Neural Features for Distance-Preserving Graph
  Representations
Graph Random Neural Features for Distance-Preserving Graph Representations
Daniele Zambon
C. Alippi
L. Livi
11
1
0
09 Sep 2019
Graph Neural Networks: A Review of Methods and Applications
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou
Ganqu Cui
Shengding Hu
Zhengyan Zhang
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
AI4CE
GNN
26
5,365
0
20 Dec 2018
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
226
1,935
0
09 Jun 2018
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
231
3,202
0
24 Nov 2016
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