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On Over-Squashing in Message Passing Neural Networks: The Impact of
  Width, Depth, and Topology

On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology

6 February 2023
Francesco Di Giovanni
Lorenzo Giusti
Federico Barbero
Giulia Luise
Pietro Lio
Michael M. Bronstein
ArXivPDFHTML

Papers citing "On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology"

24 / 24 papers shown
Title
Schreier-Coset Graph Propagation
Schreier-Coset Graph Propagation
Aryan Mishra
Lizhen Lin
42
0
0
15 May 2025
Multi-Scale Graph Learning for Anti-Sparse Downscaling
Multi-Scale Graph Learning for Anti-Sparse Downscaling
Yingda Fan
Runlong Yu
Janet R. Barclay
A. Appling
Yiming Sun
Yiqun Xie
Xiaowei Jia
AI4CE
54
0
0
03 May 2025
Effects of Random Edge-Dropping on Over-Squashing in Graph Neural Networks
Effects of Random Edge-Dropping on Over-Squashing in Graph Neural Networks
Jasraj Singh
Keyue Jiang
Brooks Paige
Laura Toni
75
1
0
11 Feb 2025
No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets
No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets
Corinna Coupette
Jeremy Wayland
Emily Simons
Bastian Rieck
106
1
0
04 Feb 2025
Cayley Graph Propagation
Cayley Graph Propagation
JJ Wilson
Maya Bechler-Speicher
Petar Veličković
42
6
0
04 Oct 2024
Joint Graph Rewiring and Feature Denoising via Spectral Resonance
Joint Graph Rewiring and Feature Denoising via Spectral Resonance
Jonas Linkerhagner
Cheng Shi
Ivan Dokmanić
47
0
0
13 Aug 2024
Scalable Graph Compressed Convolutions
Scalable Graph Compressed Convolutions
Junshu Sun
Chen Yang
Shuhui Wang
Qingming Huang
GNN
60
0
0
26 Jul 2024
Commute Graph Neural Networks
Commute Graph Neural Networks
Wei Zhuo
Han Yu
Guang Tan
Xiaoxiao Li
GNN
98
1
0
30 Jun 2024
UniIF: Unified Molecule Inverse Folding
UniIF: Unified Molecule Inverse Folding
Zhangyang Gao
Jue Wang
Cheng Tan
Lirong Wu
Yufei Huang
Siyuan Li
Zhirui Ye
Stan Z. Li
45
4
0
29 May 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
53
1
0
24 May 2024
E(n) Equivariant Topological Neural Networks
E(n) Equivariant Topological Neural Networks
Claudio Battiloro
Ege Karaismailoglu
Mauricio Tec
George Dasoulas
Michelle Audirac
Francesca Dominici
63
6
0
24 May 2024
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks:
  Heterophily, Over-smoothing, and Over-squashing
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing
Keke Huang
Yu Guang Wang
Ming Li
Pietro Lio
54
22
0
21 May 2024
Graph Unitary Message Passing
Graph Unitary Message Passing
Haiquan Qiu
Yatao Bian
Quanming Yao
48
2
0
17 Mar 2024
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
Federico Errica
Henrik Christiansen
Viktor Zaverkin
Takashi Maruyama
Mathias Niepert
Francesco Alesiani
65
8
0
27 Dec 2023
Graph Neural Networks for Pressure Estimation in Water Distribution
  Systems
Graph Neural Networks for Pressure Estimation in Water Distribution Systems
Huy Truong
Andres Tello
Alexander Lazovik
Victoria Degeler
56
8
0
17 Nov 2023
Cooperative Graph Neural Networks
Cooperative Graph Neural Networks
Ben Finkelshtein
Xingyue Huang
Michael M. Bronstein
.Ismail .Ilkan Ceylan
GNN
47
21
0
02 Oct 2023
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks
Haoran Liu
Bokun Wang
Jianling Wang
Xiangjue Dong
Tianbao Yang
James Caverlee
AAML
46
3
0
29 Aug 2023
Weisfeiler and Leman Go Measurement Modeling: Probing the Validity of
  the WL Test
Weisfeiler and Leman Go Measurement Modeling: Probing the Validity of the WL Test
Arjun Subramonian
Adina Williams
Maximilian Nickel
Yizhou Sun
Levent Sagun
41
0
0
11 Jul 2023
Is Rewiring Actually Helpful in Graph Neural Networks?
Is Rewiring Actually Helpful in Graph Neural Networks?
Domenico Tortorella
Alessio Micheli
AI4CE
49
2
0
31 May 2023
Dynamic Graph Representation Learning with Neural Networks: A Survey
Dynamic Graph Representation Learning with Neural Networks: A Survey
Leshanshui Yang
Sébastien Adam
Clément Chatelain
AI4TS
AI4CE
46
14
0
12 Apr 2023
Expander Graph Propagation
Expander Graph Propagation
Andreea Deac
Marc Lackenby
Petar Velivcković
96
55
0
06 Oct 2022
Affinity-Aware Graph Networks
Affinity-Aware Graph Networks
A. Velingker
A. Sinop
Ira Ktena
Petar Velickovic
Sreenivas Gollapudi
GNN
52
16
0
23 Jun 2022
Heterogeneous manifolds for curvature-aware graph embedding
Heterogeneous manifolds for curvature-aware graph embedding
Francesco Di Giovanni
Giulia Luise
M. Bronstein
82
23
0
02 Feb 2022
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
281
1,956
0
09 Jun 2018
1