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On the Bottleneck of Graph Neural Networks and its Practical
  Implications
v1v2v3v4 (latest)

On the Bottleneck of Graph Neural Networks and its Practical Implications

9 June 2020
Uri Alon
Eran Yahav
    GNN
ArXiv (abs)PDFHTMLGithub (94★)

Papers citing "On the Bottleneck of Graph Neural Networks and its Practical Implications"

50 / 416 papers shown
Title
The Self-Loop Paradox: Investigating the Impact of Self-Loops on Graph
  Neural Networks
The Self-Loop Paradox: Investigating the Impact of Self-Loops on Graph Neural Networks
Moritz Lampert
Ingo Scholtes
GNNSSL
56
3
0
04 Dec 2023
Recurrent Distance Filtering for Graph Representation Learning
Recurrent Distance Filtering for Graph Representation Learning
Yuhui Ding
Antonio Orvieto
Bobby He
Thomas Hofmann
GNN
136
8
0
03 Dec 2023
Improving embedding of graphs with missing data by soft manifolds
Improving embedding of graphs with missing data by soft manifolds
Andrea Marinoni
Pietro Lio
Alessandro Barp
Christian Jutten
Mark Girolami
70
0
0
29 Nov 2023
Over-Squashing in Riemannian Graph Neural Networks
Over-Squashing in Riemannian Graph Neural Networks
Julia Balla
72
1
0
27 Nov 2023
Effective Structural Encodings via Local Curvature Profiles
Effective Structural Encodings via Local Curvature Profiles
Lukas Fesser
Melanie Weber
85
3
0
24 Nov 2023
Learning to Optimise Wind Farms with Graph Transformers
Learning to Optimise Wind Farms with Graph Transformers
Siyi Li
Arnaud Robert
A. A. Faisal
M. Piggott
45
5
0
21 Nov 2023
Content Augmented Graph Neural Networks
Content Augmented Graph Neural Networks
Fatemeh Gholamzadeh Nasrabadi
AmirHossein Kashani
Pegah Zahedi
M. H. Chehreghani
68
3
0
21 Nov 2023
AMES: A Differentiable Embedding Space Selection Framework for Latent
  Graph Inference
AMES: A Differentiable Embedding Space Selection Framework for Latent Graph Inference
Yuan Lu
Haitz Sáez de Ocáriz Borde
Pietro Lio
80
2
0
20 Nov 2023
Higher-Order Expander Graph Propagation
Higher-Order Expander Graph Propagation
Thomas Christie
Yu He
76
4
0
14 Nov 2023
Exposition on over-squashing problem on GNNs: Current Methods,
  Benchmarks and Challenges
Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges
Dai Shi
Andi Han
Lequan Lin
Yi Guo
Junbin Gao
123
14
0
13 Nov 2023
Multiscale Neural Operators for Solving Time-Independent PDEs
Multiscale Neural Operators for Solving Time-Independent PDEs
Winfried Ripken
Lisa Coiffard
Felix Pieper
Sebastian Dziadzio
AI4CE
57
2
0
10 Nov 2023
Mixture of Weak & Strong Experts on Graphs
Mixture of Weak & Strong Experts on Graphs
Hanqing Zeng
Hanjia Lyu
Diyi Hu
Yinglong Xia
Jiebo Luo
95
4
0
09 Nov 2023
Hybrid Focal and Full-Range Attention Based Graph Transformers
Hybrid Focal and Full-Range Attention Based Graph Transformers
Minhong Zhu
Zhenhao Zhao
Weiran Cai
72
0
0
08 Nov 2023
Sparse Training of Discrete Diffusion Models for Graph Generation
Sparse Training of Discrete Diffusion Models for Graph Generation
Yiming Qin
Clément Vignac
Pascal Frossard
76
14
0
03 Nov 2023
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method
Yuyan Ni
Shikun Feng
Wei-Ying Ma
Zhiming Ma
Yanyan Lan
DiffMAI4CE
82
11
0
03 Nov 2023
A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction
A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction
Nicholas Walker
Stefan Ultes
Pierre Lison
LM&Ro
159
1
0
03 Nov 2023
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs
  through Efficient Communication Channel
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel
Xuan Li
Zhanke Zhou
Jiangchao Yao
Yu Rong
Lu Zhang
Bo Han
118
5
0
02 Nov 2023
Diversified Node Sampling based Hierarchical Transformer Pooling for
  Graph Representation Learning
Diversified Node Sampling based Hierarchical Transformer Pooling for Graph Representation Learning
Gaichao Li
Jinsong Chen
John E. Hopcroft
Kun He
46
0
0
31 Oct 2023
Transformers as Graph-to-Graph Models
Transformers as Graph-to-Graph Models
James Henderson
Alireza Mohammadshahi
Andrei Catalin Coman
Lesly Miculicich
GNN
69
6
0
27 Oct 2023
Multi-omics Sampling-based Graph Transformer for Synthetic Lethality
  Prediction
Multi-omics Sampling-based Graph Transformer for Synthetic Lethality Prediction
Xusheng Zhao
Hao Liu
Qiong Dai
Hao Peng
Xu Bai
Huailiang Peng
46
2
0
17 Oct 2023
SignGT: Signed Attention-based Graph Transformer for Graph
  Representation Learning
SignGT: Signed Attention-based Graph Transformer for Graph Representation Learning
Jinsong Chen
Gaichao Li
John E. Hopcroft
Kun He
SLR
88
5
0
17 Oct 2023
From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and
  Beyond
From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond
Andi Han
Dai Shi
Lequan Lin
Junbin Gao
AI4CEGNN
105
24
0
16 Oct 2023
Non-backtracking Graph Neural Networks
Non-backtracking Graph Neural Networks
Seonghyun Park
Narae Ryu
Ga-Rin Kim
Dongyeop Woo
Se-Young Yun
SungSoo Ahn
84
4
0
11 Oct 2023
Are GATs Out of Balance?
Are GATs Out of Balance?
Nimrah Mustafa
Aleksandar Bojchevski
R. Burkholz
130
5
0
11 Oct 2023
Flood and Echo Net: Algorithmically Aligned GNNs that Generalize
Flood and Echo Net: Algorithmically Aligned GNNs that Generalize
Joël Mathys
Florian Grötschla
K. Nadimpalli
Roger Wattenhofer
FedML
84
0
0
10 Oct 2023
Tailoring Self-Attention for Graph via Rooted Subtrees
Tailoring Self-Attention for Graph via Rooted Subtrees
Siyuan Huang
Yunchong Song
Jiayue Zhou
Zhouhan Lin
81
8
0
08 Oct 2023
Latent Graph Inference with Limited Supervision
Latent Graph Inference with Limited Supervision
Jianglin Lu
Yi Tian Xu
Huan Wang
Yue Bai
Yun Fu
71
4
0
06 Oct 2023
On the Two Sides of Redundancy in Graph Neural Networks
On the Two Sides of Redundancy in Graph Neural Networks
Vidya Sagar Sharma
Samir Moustafa
Johannes Langguth
Wilfried N. Gansterer
Nils M. Kriege
84
2
0
06 Oct 2023
Fishnets: Information-Optimal, Scalable Aggregation for Sets and Graphs
Fishnets: Information-Optimal, Scalable Aggregation for Sets and Graphs
T. Lucas Makinen
Justin Alsing
Benjamin Dan Wandelt
GNNFedML
65
3
0
05 Oct 2023
Probabilistically Rewired Message-Passing Neural Networks
Probabilistically Rewired Message-Passing Neural Networks
Chendi Qian
Andrei Manolache
Kareem Ahmed
Zhe Zeng
Guy Van den Broeck
Mathias Niepert
Christopher Morris
150
15
0
03 Oct 2023
Transformers are efficient hierarchical chemical graph learners
Transformers are efficient hierarchical chemical graph learners
Zihan Pengmei
Zimu Li
Chih-chan Tien
Risi Kondor
Aaron R Dinner
GNN
48
2
0
02 Oct 2023
Locality-Aware Graph-Rewiring in GNNs
Locality-Aware Graph-Rewiring in GNNs
Federico Barbero
A. Velingker
Amin Saberi
Michael M. Bronstein
Francesco Di Giovanni
108
33
0
02 Oct 2023
Cooperative Graph Neural Networks
Cooperative Graph Neural Networks
Ben Finkelshtein
Xingyue Huang
Michael M. Bronstein
.Ismail .Ilkan Ceylan
GNN
110
26
0
02 Oct 2023
ResolvNet: A Graph Convolutional Network with multi-scale Consistency
ResolvNet: A Graph Convolutional Network with multi-scale Consistency
Christian Koke
Abhishek Saroha
Yuesong Shen
Marvin Eisenberger
Daniel Cremers
GNN
54
1
0
30 Sep 2023
Deep Prompt Tuning for Graph Transformers
Deep Prompt Tuning for Graph Transformers
Reza Shirkavand
Heng-Chiao Huang
57
7
0
18 Sep 2023
Mitigating Over-Smoothing and Over-Squashing using Augmentations of
  Forman-Ricci Curvature
Mitigating Over-Smoothing and Over-Squashing using Augmentations of Forman-Ricci Curvature
Lukas Fesser
Melanie Weber
100
25
0
17 Sep 2023
Motif-aware Attribute Masking for Molecular Graph Pre-training
Motif-aware Attribute Masking for Molecular Graph Pre-training
Eric Inae
Gang Liu
Meng Jiang
AI4CE
122
14
0
08 Sep 2023
Graph Neural Networks Use Graphs When They Shouldn't
Graph Neural Networks Use Graphs When They Shouldn't
Maya Bechler-Speicher
Ido Amos
Ran Gilad-Bachrach
Amir Globerson
GNNAI4CE
45
15
0
08 Sep 2023
Curve Your Attention: Mixed-Curvature Transformers for Graph
  Representation Learning
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning
Sungjun Cho
Seunghyuk Cho
Sungwoo Park
Hankook Lee
Ho Hin Lee
Moontae Lee
111
7
0
08 Sep 2023
Unifying over-smoothing and over-squashing in graph neural networks: A
  physics informed approach and beyond
Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond
Zhiqi Shao
Dai Shi
Andi Han
Yi Guo
Qianchuan Zhao
Junbin Gao
79
12
0
06 Sep 2023
Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular
  Property Prediction
Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction
Minghao Guo
Veronika Thost
Samuel W Song
A. Balachandran
Payel Das
Jie Chen
Wojciech Matusik
AI4CE
71
0
0
04 Sep 2023
Curvature-based Pooling within Graph Neural Networks
Curvature-based Pooling within Graph Neural Networks
Cedric Sanders
Andreas Roth
Thomas Liebig
80
5
0
31 Aug 2023
TransGNN: Harnessing the Collaborative Power of Transformers and Graph
  Neural Networks for Recommender Systems
TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems
Peiyan Zhang
Yuchen Yan
Xi Zhang
Chaozhuo Li
Senzhang Wang
Feiran Huang
Sunghun Kim
79
22
0
28 Aug 2023
Enhancing Graph Transformers with Hierarchical Distance Structural
  Encoding
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding
Yuan Luo
Hongkang Li
Lei Shi
Xiao-Ming Wu
78
8
0
22 Aug 2023
Investigating the Interplay between Features and Structures in Graph
  Learning
Investigating the Interplay between Features and Structures in Graph Learning
Daniele Castellana
Federico Errica
101
4
0
18 Aug 2023
Half-Hop: A graph upsampling approach for slowing down message passing
Half-Hop: A graph upsampling approach for slowing down message passing
Mehdi Azabou
Venkataraman Ganesh
S. Thakoor
Chi-Heng Lin
Lakshmi Sathidevi
Ran Liu
Michal Valko
Petar Velickovic
Eva L. Dyer
97
23
0
17 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
231
26
0
16 Aug 2023
Label Inference Attacks against Node-level Vertical Federated GNNs
Label Inference Attacks against Node-level Vertical Federated GNNs
Marco Arazzi
Mauro Conti
Stefanos Koffas
Marina Krček
Antonino Nocera
S. Picek
Jing Xu
FedMLAAML
55
1
0
04 Aug 2023
Graph Neural Networks for Forecasting Multivariate Realized Volatility
  with Spillover Effects
Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects
Chao Zhang
Xingyue Pu
Ning Zhang
Xiaowen Dong
24
4
0
01 Aug 2023
Feature Transportation Improves Graph Neural Networks
Feature Transportation Improves Graph Neural Networks
Moshe Eliasof
E. Haber
Eran Treister
GNN
109
12
0
29 Jul 2023
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