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From Local to Global: Spectral-Inspired Graph Neural Networks

From Local to Global: Spectral-Inspired Graph Neural Networks

24 September 2022
Ningyuan Huang
Soledad Villar
Carey E. Priebe
Da Zheng
Cheng-Fu Huang
Lin F. Yang
Vladimir Braverman
ArXivPDFHTML

Papers citing "From Local to Global: Spectral-Inspired Graph Neural Networks"

17 / 17 papers shown
Title
LASE: Learned Adjacency Spectral Embeddings
LASE: Learned Adjacency Spectral Embeddings
Sofía Pérez Casulo
Marcelo Fiori
Federico Larroca
Gonzalo Mateos
AI4TS
GNN
33
0
0
23 Dec 2024
Attack by Yourself: Effective and Unnoticeable Multi-Category Graph
  Backdoor Attacks with Subgraph Triggers Pool
Attack by Yourself: Effective and Unnoticeable Multi-Category Graph Backdoor Attacks with Subgraph Triggers Pool
Jiangtong Li
Dungy Liu
Dawei Cheng
Changchun Jiang
AAML
36
0
0
23 Dec 2024
Graph neural networks and non-commuting operators
Graph neural networks and non-commuting operators
Mauricio Velasco
Kaiying O'Hare
Bernardo Rychtenberg
Soledad Villar
GNN
112
1
0
06 Nov 2024
Global-Local Graph Neural Networks for Node-Classification
Global-Local Graph Neural Networks for Node-Classification
Moshe Eliasof
Eran Treister
41
3
0
16 Jun 2024
Spatio-Spectral Graph Neural Networks
Spatio-Spectral Graph Neural Networks
Simon Geisler
Arthur Kosmala
Daniel Herbst
Stephan Günnemann
45
8
0
29 May 2024
Conditional Shift-Robust Conformal Prediction for Graph Neural Network
Conditional Shift-Robust Conformal Prediction for Graph Neural Network
Akansha Agrawal
UQCV
50
1
0
20 May 2024
Simplified PCNet with Robustness
Simplified PCNet with Robustness
Bingheng Li
Xuanting Xie
Haoxiang Lei
Ruiyi Fang
Zhao Kang
37
5
0
06 Mar 2024
Graph Learning with Distributional Edge Layouts
Graph Learning with Distributional Edge Layouts
Xinjian Zhao
Chaolong Ying
Tianshu Yu
23
0
0
26 Feb 2024
Graph Positional Encoding via Random Feature Propagation
Graph Positional Encoding via Random Feature Propagation
Moshe Eliasof
Fabrizio Frasca
Beatrice Bevilacqua
Eran Treister
Gal Chechik
Haggai Maron
22
18
0
06 Mar 2023
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
Nicolas Keriven
30
88
0
24 May 2022
Graph Neural Networks for Graphs with Heterophily: A Survey
Graph Neural Networks for Graphs with Heterophily: A Survey
Xin-Yang Zheng
Yi Wang
Yixin Liu
Ming Li
Miao Zhang
Di Jin
Philip S. Yu
Shirui Pan
19
214
0
14 Feb 2022
Graph Neural Networks with Learnable Structural and Positional
  Representations
Graph Neural Networks with Learnable Structural and Positional Representations
Vijay Prakash Dwivedi
A. Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
GNN
192
308
0
15 Oct 2021
Reconstruction for Powerful Graph Representations
Reconstruction for Powerful Graph Representations
Leonardo Cotta
Christopher Morris
Bruno Ribeiro
AI4CE
122
78
0
01 Oct 2021
A Survey on The Expressive Power of Graph Neural Networks
A Survey on The Expressive Power of Graph Neural Networks
Ryoma Sato
184
171
0
09 Mar 2020
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
169
1,078
0
13 Feb 2020
Multi-scale Attributed Node Embedding
Multi-scale Attributed Node Embedding
Benedek Rozemberczki
Carl Allen
Rik Sarkar
GNN
148
836
0
28 Sep 2019
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
264
1,944
0
09 Jun 2018
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