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Not too little, not too much: a theoretical analysis of graph
  (over)smoothing

Not too little, not too much: a theoretical analysis of graph (over)smoothing

24 May 2022
Nicolas Keriven
ArXivPDFHTML

Papers citing "Not too little, not too much: a theoretical analysis of graph (over)smoothing"

50 / 55 papers shown
Title
Real-Time Manipulation Action Recognition with a Factorized Graph Sequence Encoder
Real-Time Manipulation Action Recognition with a Factorized Graph Sequence Encoder
Enes Erdogan
E. Aksoy
Sanem Sariel
41
0
0
15 Mar 2025
Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model
O. Duranthon
L. Zdeborová
41
0
0
03 Mar 2025
Training Large Recommendation Models via Graph-Language Token Alignment
Training Large Recommendation Models via Graph-Language Token Alignment
Mingdai Yang
Z. Liu
Liangwei Yang
X. Liu
Chen Wang
Hao Peng
Philip S. Yu
AI4TS
71
0
0
26 Feb 2025
What makes a good feedforward computational graph?
What makes a good feedforward computational graph?
Alex Vitvitskyi
J. G. Araújo
Marc Lackenby
Petar Velickovic
78
1
0
10 Feb 2025
Optimality of Message-Passing Architectures for Sparse Graphs
Optimality of Message-Passing Architectures for Sparse Graphs
Aseem Baranwal
K. Fountoulakis
Aukosh Jagannath
68
11
0
10 Jan 2025
A Dynamical Systems-Inspired Pruning Strategy for Addressing
  Oversmoothing in Graph Neural Networks
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks
Biswadeep Chakraborty
H. Kumar
Saibal Mukhopadhyay
75
1
0
10 Dec 2024
Unitary convolutions for learning on graphs and groups
Unitary convolutions for learning on graphs and groups
B. Kiani
Lukas Fesser
Melanie Weber
GNN
30
1
0
07 Oct 2024
Question-guided Knowledge Graph Re-scoring and Injection for Knowledge
  Graph Question Answering
Question-guided Knowledge Graph Re-scoring and Injection for Knowledge Graph Question Answering
Yu Zhang
Kehai Chen
Xuefeng Bai
zhao kang
Quanjiang Guo
Min Zhang
15
5
0
02 Oct 2024
Learning Ordering in Crystalline Materials with Symmetry-Aware Graph
  Neural Networks
Learning Ordering in Crystalline Materials with Symmetry-Aware Graph Neural Networks
Jiayu Peng
James K. Damewood
Jessica Karaguesian
Jaclyn R. Lunger
Rafael Gómez-Bombarelli
AI4CE
37
2
0
20 Sep 2024
Contrasformer: A Brain Network Contrastive Transformer for
  Neurodegenerative Condition Identification
Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification
Jiaxing Xu
Kai He
Mengcheng Lan
Qingtian Bian
Wei Li
Tieying Li
Yiping Ke
Miao Qiao
MedIm
13
0
0
17 Sep 2024
GSTAM: Efficient Graph Distillation with Structural Attention-Matching
GSTAM: Efficient Graph Distillation with Structural Attention-Matching
Arash Rasti-Meymandi
A. Sajedi
Zhaopan Xu
Konstantinos N. Plataniotis
18
0
0
29 Aug 2024
UniGAP: A Universal and Adaptive Graph Upsampling Approach to Mitigate
  Over-Smoothing in Node Classification Tasks
UniGAP: A Universal and Adaptive Graph Upsampling Approach to Mitigate Over-Smoothing in Node Classification Tasks
Xiaotang Wang
Yun Zhu
Haizhou Shi
Yongchao Liu
Chuntao Hong
32
2
0
28 Jul 2024
Graph Neural Networks: A suitable Alternative to MLPs in Latent 3D
  Medical Image Classification?
Graph Neural Networks: A suitable Alternative to MLPs in Latent 3D Medical Image Classification?
Johannes Kiechle
Daniel M. Lang
Stefan M. Fischer
Lina Felsner
J. Peeken
Julia A. Schnabel
MedIm
14
0
0
24 Jul 2024
Bridging Smoothness and Approximation: Theoretical Insights into
  Over-Smoothing in Graph Neural Networks
Bridging Smoothness and Approximation: Theoretical Insights into Over-Smoothing in Graph Neural Networks
Guangrui Yang
Jianfei Li
Ming Li
Han Feng
Ding-Xuan Zhou
28
0
0
01 Jul 2024
Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph
  Modeling
Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph Modeling
Siwei Zhang
Xi Chen
Yun Xiong
Xixi Wu
Yao Zhang
Yongrui Fu
Yinglong Zhao
Jiawei Zhang
21
2
0
14 Jun 2024
What Can We Learn from State Space Models for Machine Learning on
  Graphs?
What Can We Learn from State Space Models for Machine Learning on Graphs?
Yinan Huang
Siqi Miao
Pan Li
39
7
0
09 Jun 2024
Residual Connections and Normalization Can Provably Prevent
  Oversmoothing in GNNs
Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs
Michael Scholkemper
Xinyi Wu
Ali Jadbabaie
Michael T. Schaub
23
6
0
05 Jun 2024
Graph Neural Networks Do Not Always Oversmooth
Graph Neural Networks Do Not Always Oversmooth
Bastian Epping
Alexandre René
M. Helias
Michael T. Schaub
25
3
0
04 Jun 2024
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning
  on Heterophilic Graphs
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
Langzhang Liang
Sunwoo Kim
Kijung Shin
Zenglin Xu
Shirui Pan
Yuan Qi
34
3
0
31 May 2024
Graph Coarsening with Message-Passing Guarantees
Graph Coarsening with Message-Passing Guarantees
Antonin Joly
Nicolas Keriven
25
0
0
28 May 2024
Analysis of Corrected Graph Convolutions
Analysis of Corrected Graph Convolutions
Robert Wang
Aseem Baranwal
K. Fountoulakis
29
0
0
22 May 2024
IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors
IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors
Shenghe Zheng
Hongzhi Wang
Xianglong Liu
34
3
0
02 May 2024
Spectral Graph Pruning Against Over-Squashing and Over-Smoothing
Spectral Graph Pruning Against Over-Squashing and Over-Smoothing
Adarsh Jamadandi
Celia Rubio-Madrigal
R. Burkholz
30
1
0
06 Apr 2024
Generalization Bounds for Message Passing Networks on Mixture of
  Graphons
Generalization Bounds for Message Passing Networks on Mixture of Graphons
Sohir Maskey
Gitta Kutyniok
Ron Levie
48
5
0
04 Apr 2024
SSHPool: The Separated Subgraph-based Hierarchical Pooling
SSHPool: The Separated Subgraph-based Hierarchical Pooling
Zhuo Xu
Lixin Cui
Yue Wang
Hangyuan Du
Lu Bai
Edwin R. Hancock
22
1
0
24 Mar 2024
Subgraph Pooling: Tackling Negative Transfer on Graphs
Subgraph Pooling: Tackling Negative Transfer on Graphs
Zehong Wang
Zheyuan Zhang
Chuxu Zhang
Yanfang Ye
28
6
0
14 Feb 2024
Message Detouring: A Simple Yet Effective Cycle Representation for
  Expressive Graph Learning
Message Detouring: A Simple Yet Effective Cycle Representation for Expressive Graph Learning
Ziquan Wei
Tingting Dan
Guorong Wu
19
0
0
12 Feb 2024
Key-Graph Transformer for Image Restoration
Key-Graph Transformer for Image Restoration
Bin Ren
Yawei Li
Jingyun Liang
Rakesh Ranjan
Mengyuan Liu
Rita Cucchiara
Luc Van Gool
N. Sebe
29
1
0
04 Feb 2024
Graph Convolutions Enrich the Self-Attention in Transformers!
Graph Convolutions Enrich the Self-Attention in Transformers!
Jeongwhan Choi
Hyowon Wi
Jayoung Kim
Yehjin Shin
Kookjin Lee
Nathaniel Trask
Noseong Park
22
3
0
07 Dec 2023
Generalized Graph Prompt: Toward a Unification of Pre-Training and
  Downstream Tasks on Graphs
Generalized Graph Prompt: Toward a Unification of Pre-Training and Downstream Tasks on Graphs
Xingtong Yu
Zhenghao Liu
Yuan Fang
Zemin Liu
Sihong Chen
Xinming Zhang
33
14
0
26 Nov 2023
Networked Inequality: Preferential Attachment Bias in Graph Neural
  Network Link Prediction
Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction
Zhengyuan Yang
Levent Sagun
Yizhou Sun
14
2
0
29 Sep 2023
A Model-Agnostic Graph Neural Network for Integrating Local and Global
  Information
A Model-Agnostic Graph Neural Network for Integrating Local and Global Information
Wenzhuo Zhou
Annie Qu
Keiland W Cooper
Norbert Fortin
B. Shahbaba
17
1
0
23 Sep 2023
Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural
  Networks
Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural Networks
Andreas Roth
Thomas Liebig
25
11
0
31 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
11
19
0
17 Aug 2023
Long-range Meta-path Search on Large-scale Heterogeneous Graphs
Long-range Meta-path Search on Large-scale Heterogeneous Graphs
Chao Li
Zijie Guo
Qiuting He
Hao Xu
Kun He
16
2
0
17 Jul 2023
A Neural Collapse Perspective on Feature Evolution in Graph Neural
  Networks
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks
Vignesh Kothapalli
Tom Tirer
Joan Bruna
22
10
0
04 Jul 2023
Principles for Initialization and Architecture Selection in Graph Neural
  Networks with ReLU Activations
Principles for Initialization and Architecture Selection in Graph Neural Networks with ReLU Activations
G. Dezoort
Boris Hanin
AI4CE
15
3
0
20 Jun 2023
Centered Self-Attention Layers
Centered Self-Attention Layers
Ameen Ali
Tomer Galanti
Lior Wolf
20
6
0
02 Jun 2023
Demystifying Oversmoothing in Attention-Based Graph Neural Networks
Demystifying Oversmoothing in Attention-Based Graph Neural Networks
Xinyi Wu
A. Ajorlou
Zihui Wu
Ali Jadbabaie
11
33
0
25 May 2023
What functions can Graph Neural Networks compute on random graphs? The
  role of Positional Encoding
What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding
Nicolas Keriven
Samuel Vaiter
29
11
0
24 May 2023
A Fractional Graph Laplacian Approach to Oversmoothing
A Fractional Graph Laplacian Approach to Oversmoothing
Sohir Maskey
Raffaele Paolino
Aras Bacho
Gitta Kutyniok
20
27
0
22 May 2023
Addressing Heterophily in Node Classification with Graph Echo State
  Networks
Addressing Heterophily in Node Classification with Graph Echo State Networks
A. Micheli
Domenico Tortorella
11
8
0
14 May 2023
Understanding Noise-Augmented Training for Randomized Smoothing
Understanding Noise-Augmented Training for Randomized Smoothing
Ambar Pal
Jeremias Sulam
AAML
10
7
0
08 May 2023
Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs
Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs
Matthieu Cordonnier
Nicolas Keriven
Nicolas M Tremblay
Samuel Vaiter
GNN
45
7
0
21 Apr 2023
Gradient scarcity with Bilevel Optimization for Graph Learning
Gradient scarcity with Bilevel Optimization for Graph Learning
Hashem Ghanem
Samuel Vaiter
Nicolas Keriven
22
0
0
24 Mar 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
14
184
0
20 Mar 2023
Homophily modulates double descent generalization in graph convolution
  networks
Homophily modulates double descent generalization in graph convolution networks
Chengzhi Shi
Liming Pan
Hong Hu
Ivan Dokmanić
28
9
0
26 Dec 2022
A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks
A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks
X. Wu
Zhengdao Chen
W. Wang
Ali Jadbabaie
15
38
0
21 Dec 2022
Graph Learning and Its Advancements on Large Language Models: A Holistic
  Survey
Graph Learning and Its Advancements on Large Language Models: A Holistic Survey
Shaopeng Wei
Yu Zhao
Xingyan Chen
Qing Li
Fuzhen Zhuang
Ji Liu
Fuji Ren
Gang Kou
AI4CE
19
4
0
17 Dec 2022
Analysis of Convolutions, Non-linearity and Depth in Graph Neural
  Networks using Neural Tangent Kernel
Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel
Mahalakshmi Sabanayagam
P. Esser
D. Ghoshdastidar
13
2
0
18 Oct 2022
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