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Feature Distribution on Graph Topology Mediates the Effect of Graph
  Convolution: Homophily Perspective

Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective

7 February 2024
Soo Yong Lee
Sunwoo Kim
Fanchen Bu
Jaemin Yoo
Jiliang Tang
Kijung Shin
ArXivPDFHTML

Papers citing "Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective"

12 / 12 papers shown
Title
Rewiring Techniques to Mitigate Oversquashing and Oversmoothing in GNNs:
  A Survey
Rewiring Techniques to Mitigate Oversquashing and Oversmoothing in GNNs: A Survey
Hugo Attali
Davide Buscaldi
Nathalie Pernelle
AI4CE
59
1
0
26 Nov 2024
Rethinking Reconstruction-based Graph-Level Anomaly Detection:
  Limitations and a Simple Remedy
Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy
Sunwoo Kim
Soo Yong Lee
Fanchen Bu
Shinhwan Kang
Kyungho Kim
Jaemin Yoo
Kijung Shin
14
0
0
27 Oct 2024
What Is Missing In Homophily? Disentangling Graph Homophily For Graph
  Neural Networks
What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
Yilun Zheng
Sitao Luan
Lihui Chen
35
5
0
27 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
29
3
0
31 May 2024
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step
  Guide
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide
Sunwoo Kim
Soo Yong Lee
Yue Gao
Alessia Antelmi
Mirko Polato
Kijung Shin
GNN
AI4TS
26
17
0
01 Apr 2024
Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
Chenhui Deng
Zichao Yue
Zhiru Zhang
81
23
0
02 Mar 2024
When Do Graph Neural Networks Help with Node Classification?
  Investigating the Impact of Homophily Principle on Node Distinguishability
When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability
Sitao Luan
Chenqing Hua
Minkai Xu
Qincheng Lu
Jiaqi Zhu
Xiaoming Chang
Jie Fu
J. Leskovec
Doina Precup
31
3
0
25 Apr 2023
Characterizing Graph Datasets for Node Classification:
  Homophily-Heterophily Dichotomy and Beyond
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond
Oleg Platonov
Denis Kuznedelev
Artem Babenko
Liudmila Prokhorenkova
39
19
0
13 Sep 2022
How Powerful are Spectral Graph Neural Networks
How Powerful are Spectral Graph Neural Networks
Xiyuan Wang
Muhan Zhang
70
175
0
23 May 2022
GraphWorld: Fake Graphs Bring Real Insights for GNNs
GraphWorld: Fake Graphs Bring Real Insights for GNNs
John Palowitch
Anton Tsitsulin
Brandon Mayer
Bryan Perozzi
GNN
177
68
0
28 Feb 2022
Geom-GCN: Geometric Graph Convolutional Networks
Geom-GCN: Geometric Graph Convolutional Networks
Hongbin Pei
Bingzhen Wei
Kevin Chen-Chuan Chang
Yu Lei
Bo Yang
GNN
167
1,058
0
13 Feb 2020
Contextual Stochastic Block Models
Contextual Stochastic Block Models
Y. Deshpande
Andrea Montanari
Elchanan Mossel
S. Sen
98
131
0
23 Jul 2018
1