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From Stars to Subgraphs: Uplifting Any GNN with Local Structure
  Awareness

From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness

7 October 2021
Lingxiao Zhao
Wei Jin
L. Akoglu
Neil Shah
    GNN
ArXivPDFHTML

Papers citing "From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness"

25 / 25 papers shown
Title
Revisiting Graph Neural Networks on Graph-level Tasks: Comprehensive Experiments, Analysis, and Improvements
Haoyang Li
Y. Xu
C. Zhang
Alexander Zhou
Lei Chen
Qing Li
AI4CE
91
0
0
03 Jan 2025
Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings
Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings
Billy Joe Franks
Moshe Eliasof
Semih Cantürk
Guy Wolf
Carola-Bibiane Schönlieb
Sophie Fellenz
Marius Kloft
AI4CE
71
0
0
10 Dec 2024
Revisiting Random Walks for Learning on Graphs
Revisiting Random Walks for Learning on Graphs
Jinwoo Kim
Olga Zaghen
Ayhan Suleymanzade
Youngmin Ryou
Seunghoon Hong
54
0
0
01 Jul 2024
CiliaGraph: Enabling Expression-enhanced Hyper-Dimensional Computation
  in Ultra-Lightweight and One-Shot Graph Classification on Edge
CiliaGraph: Enabling Expression-enhanced Hyper-Dimensional Computation in Ultra-Lightweight and One-Shot Graph Classification on Edge
Yuxi Han
Jihe Wang
Danghui Wang
44
1
0
29 May 2024
Graph as Point Set
Graph as Point Set
Xiyuan Wang
Pan Li
Muhan Zhang
GNN
3DPC
PINN
35
4
0
05 May 2024
On the Theoretical Expressive Power and the Design Space of Higher-Order
  Graph Transformers
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers
Cai Zhou
Rose Yu
Yusu Wang
32
7
0
04 Apr 2024
Descriptive Kernel Convolution Network with Improved Random Walk Kernel
Descriptive Kernel Convolution Network with Improved Random Walk Kernel
Meng-Chieh Lee
Lingxiao Zhao
L. Akoglu
16
3
0
08 Feb 2024
On the Completeness of Invariant Geometric Deep Learning Models
On the Completeness of Invariant Geometric Deep Learning Models
Zian Li
Xiyuan Wang
Shijia Kang
Muhan Zhang
31
2
0
07 Feb 2024
Mixture of Weak & Strong Experts on Graphs
Mixture of Weak & Strong Experts on Graphs
Hanqing Zeng
Hanjia Lyu
Diyi Hu
Yinglong Xia
Jiebo Luo
23
3
0
09 Nov 2023
SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection
SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection
Zhihao Ding
Jieming Shi
Shiqi Shen
Xuequn Shang
Jiannong Cao
Zhipeng Wang
Zhi Gong
OODD
OOD
27
4
0
16 Oct 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
40
19
0
16 Aug 2023
Graph Inductive Biases in Transformers without Message Passing
Graph Inductive Biases in Transformers without Message Passing
Liheng Ma
Chen Lin
Derek Lim
Adriana Romero Soriano
P. Dokania
Mark J. Coates
Philip H. S. Torr
Ser-Nam Lim
AI4CE
12
86
0
27 May 2023
From Relational Pooling to Subgraph GNNs: A Universal Framework for More
  Expressive Graph Neural Networks
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks
Cai Zhou
Xiyuan Wang
Muhan Zhang
26
14
0
08 May 2023
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
14
16
0
06 Mar 2023
Technical report: Graph Neural Networks go Grammatical
Technical report: Graph Neural Networks go Grammatical
Jason Piquenot
Aldo Moscatelli
Maxime Bérar
Pierre Héroux
R. Raveaux
Jean-Yves Ramel
Sébastien Adam
20
0
0
02 Mar 2023
Diffusing Graph Attention
Diffusing Graph Attention
Daniel Glickman
Eran Yahav
GNN
28
3
0
01 Mar 2023
A Generalization of ViT/MLP-Mixer to Graphs
A Generalization of ViT/MLP-Mixer to Graphs
Xiaoxin He
Bryan Hooi
T. Laurent
Adam Perold
Yann LeCun
Xavier Bresson
22
88
0
27 Dec 2022
Beyond 1-WL with Local Ego-Network Encodings
Beyond 1-WL with Local Ego-Network Encodings
Nurudin Alvarez-Gonzalez
Andreas Kaltenbrunner
Vicencc Gómez
23
5
0
27 Nov 2022
Boosting the Cycle Counting Power of Graph Neural Networks with
  I$^2$-GNNs
Boosting the Cycle Counting Power of Graph Neural Networks with I2^22-GNNs
Yinan Huang
Xingang Peng
Jianzhu Ma
Muhan Zhang
76
46
0
22 Oct 2022
Recipe for a General, Powerful, Scalable Graph Transformer
Recipe for a General, Powerful, Scalable Graph Transformer
Ladislav Rampášek
Mikhail Galkin
Vijay Prakash Dwivedi
A. Luu
Guy Wolf
Dominique Beaini
43
507
0
25 May 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks
Christopher Morris
Gaurav Rattan
Sandra Kiefer
Siamak Ravanbakhsh
33
39
0
25 Mar 2022
Sign and Basis Invariant Networks for Spectral Graph Representation
  Learning
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
Derek Lim
Joshua Robinson
Lingxiao Zhao
Tess E. Smidt
S. Sra
Haggai Maron
Stefanie Jegelka
20
138
0
25 Feb 2022
Reconstruction for Powerful Graph Representations
Reconstruction for Powerful Graph Representations
Leonardo Cotta
Christopher Morris
Bruno Ribeiro
AI4CE
122
78
0
01 Oct 2021
Benchmarking Graph Neural Networks
Benchmarking Graph Neural Networks
Vijay Prakash Dwivedi
Chaitanya K. Joshi
Anh Tuan Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
186
913
0
02 Mar 2020
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
234
1,809
0
25 Nov 2016
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