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Equivariant and Stable Positional Encoding for More Powerful Graph
  Neural Networks

Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks

1 March 2022
Hongya Wang
Haoteng Yin
Muhan Zhang
Pan Li
ArXivPDFHTML

Papers citing "Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks"

50 / 80 papers shown
Title
HOPSE: Scalable Higher-Order Positional and Structural Encoder for Combinatorial Representations
HOPSE: Scalable Higher-Order Positional and Structural Encoder for Combinatorial Representations
Martin Carrasco
Guillermo Bernardez
Marco Montagna
Nina Miolane
Lev Telyatnikov
AI4CE
20
0
0
21 May 2025
Learning Laplacian Positional Encodings for Heterophilous Graphs
Learning Laplacian Positional Encodings for Heterophilous Graphs
Michael Ito
Jiong Zhu
Dexiong Chen
Danai Koutra
Jenna Wiens
196
1
0
29 Apr 2025
MedGNN: Capturing the Links Between Urban Characteristics and Medical Prescriptions
MedGNN: Capturing the Links Between Urban Characteristics and Medical Prescriptions
Minwei Zhao
S. Šćepanović
Stephen Law
Daniele Quercia
Ivica Obadic
38
0
0
07 Apr 2025
Using Random Noise Equivariantly to Boost Graph Neural Networks Universally
Using Random Noise Equivariantly to Boost Graph Neural Networks Universally
Xuben Wang
Muhan Zhang
107
0
0
04 Feb 2025
Learning Efficient Positional Encodings with Graph Neural Networks
Learning Efficient Positional Encodings with Graph Neural Networks
Charilaos I. Kanatsoulis
Evelyn Choi
Stephanie Jegelka
Jure Leskovec
Alejandro Ribeiro
70
2
0
03 Feb 2025
GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture
GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture
Md Atik Ahamed
Andrew Cheng
Qiang Ye
Q. Cheng
GNN
60
0
0
01 Feb 2025
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality
Joshua Southern
Yam Eitan
Guy Bar-Shalom
Michael M. Bronstein
Haggai Maron
Fabrizio Frasca
35
1
0
06 Jan 2025
Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding
Jiajun Zhu
Peihao Wang
Ruisi Cai
Jason D. Lee
Pan Li
Zihan Wang
KELM
53
1
0
03 Jan 2025
Mixture of Link Predictors on Graphs
Mixture of Link Predictors on Graphs
Li Ma
Haoyu Han
Juanhui Li
Harry Shomer
Hui Liu
Xiaofeng Gao
Jiliang Tang
73
6
0
03 Jan 2025
LASE: Learned Adjacency Spectral Embeddings
LASE: Learned Adjacency Spectral Embeddings
Sofía Pérez Casulo
Marcelo Fiori
Federico Larroca
Gonzalo Mateos
AI4TS
GNN
43
0
0
23 Dec 2024
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
93
0
0
10 Dec 2024
Best of Both Worlds: Advantages of Hybrid Graph Sequence Models
Best of Both Worlds: Advantages of Hybrid Graph Sequence Models
Ali Behrouz
Ali Parviz
Mahdi Karami
Clayton Sanford
Bryan Perozzi
Vahab Mirrokni
84
2
0
23 Nov 2024
Homomorphism Counts as Structural Encodings for Graph Learning
Homomorphism Counts as Structural Encodings for Graph Learning
Linus Bao
Emily Jin
Michael M. Bronstein
.Ismail .Ilkan Ceylan
Matthias Lanzinger
30
1
0
24 Oct 2024
Towards Stable, Globally Expressive Graph Representations with Laplacian
  Eigenvectors
Towards Stable, Globally Expressive Graph Representations with Laplacian Eigenvectors
Junru Zhou
Cai Zhou
Xiyuan Wang
Pan Li
Muhan Zhang
45
0
0
13 Oct 2024
A Benchmark on Directed Graph Representation Learning in Hardware
  Designs
A Benchmark on Directed Graph Representation Learning in Hardware Designs
Haoyu Wang
Yinan Huang
Nan Wu
Pan Li
OOD
50
1
0
09 Oct 2024
Multi-Atlas Brain Network Classification through Consistency
  Distillation and Complementary Information Fusion
Multi-Atlas Brain Network Classification through Consistency Distillation and Complementary Information Fusion
Jiaxing Xu
Mengcheng Lan
Xia Dong
Kai He
Wei Zhang
Qingtian Bian
Yiping Ke
33
3
0
28 Sep 2024
Range-aware Positional Encoding via High-order Pretraining: Theory and
  Practice
Range-aware Positional Encoding via High-order Pretraining: Theory and Practice
Viet Anh Nguyen
Nhat-Khang Ngô
Truong-Son Hy
AI4CE
27
0
0
27 Sep 2024
Promoting Fairness in Link Prediction with Graph Enhancement
Promoting Fairness in Link Prediction with Graph Enhancement
Yezi Liu
Hanning Chen
Mohsen Imani
38
1
0
13 Sep 2024
Sub-graph Based Diffusion Model for Link Prediction
Sub-graph Based Diffusion Model for Link Prediction
Hang Li
Wei Jin
Geri Skenderi
Harry Shomer
Wenzhuo Tang
Wenqi Fan
Jiliang Tang
DiffM
33
0
0
13 Sep 2024
What Are Good Positional Encodings for Directed Graphs?
What Are Good Positional Encodings for Directed Graphs?
Yinan Huang
Haoyu Wang
Pan Li
38
3
0
30 Jul 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
49
7
0
09 Jun 2024
On the Expressive Power of Spectral Invariant Graph Neural Networks
On the Expressive Power of Spectral Invariant Graph Neural Networks
Bohang Zhang
Lingxiao Zhao
Haggai Maron
61
7
0
06 Jun 2024
Spatio-Spectral Graph Neural Networks
Spatio-Spectral Graph Neural Networks
Simon Geisler
Arthur Kosmala
Daniel Herbst
Stephan Günnemann
58
8
0
29 May 2024
Graph as Point Set
Graph as Point Set
Xiyuan Wang
Pan Li
Muhan Zhang
GNN
3DPC
PINN
49
4
0
05 May 2024
CKGConv: General Graph Convolution with Continuous Kernels
CKGConv: General Graph Convolution with Continuous Kernels
Liheng Ma
Soumyasundar Pal
Yitian Zhang
Jiaming Zhou
Yingxue Zhang
Mark J. Coates
37
2
0
21 Apr 2024
CSA-Trans: Code Structure Aware Transformer for AST
CSA-Trans: Code Structure Aware Transformer for AST
Saeyoon Oh
Shin Yoo
44
1
0
07 Apr 2024
Subequivariant Reinforcement Learning Framework for Coordinated Motion
  Control
Subequivariant Reinforcement Learning Framework for Coordinated Motion Control
Haoyu Wang
Xiaoyu Tan
Xihe Qiu
Chao Qu
48
2
0
22 Mar 2024
In-n-Out: Calibrating Graph Neural Networks for Link Prediction
In-n-Out: Calibrating Graph Neural Networks for Link Prediction
E. Nascimento
Diego Mesquita
Samuel Kaski
Amauri Souza
UQCV
21
1
0
07 Mar 2024
Teaching MLP More Graph Information: A Three-stage Multitask Knowledge
  Distillation Framework
Teaching MLP More Graph Information: A Three-stage Multitask Knowledge Distillation Framework
Junxian Li
Bin Shi
Erfei Cui
Hua Wei
Qinghua Zheng
51
0
0
02 Mar 2024
Expressive Higher-Order Link Prediction through Hypergraph Symmetry
  Breaking
Expressive Higher-Order Link Prediction through Hypergraph Symmetry Breaking
Simon Zhang
Cheng Xin
Tamal K. Dey
43
1
0
17 Feb 2024
Position: Topological Deep Learning is the New Frontier for Relational
  Learning
Position: Topological Deep Learning is the New Frontier for Relational Learning
Theodore Papamarkou
Tolga Birdal
Michael M. Bronstein
Gunnar Carlsson
Justin Curry
...
Petar Velickovic
Bei Wang
Yusu Wang
Guo-Wei Wei
Ghada Zamzmi
AI4CE
62
26
0
14 Feb 2024
Graph Mamba: Towards Learning on Graphs with State Space Models
Graph Mamba: Towards Learning on Graphs with State Space Models
Ali Behrouz
Farnoosh Hashemi
AI4CE
112
61
0
13 Feb 2024
Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph
  Products
Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products
Guy Bar-Shalom
Beatrice Bevilacqua
Haggai Maron
AI4CE
35
6
0
13 Feb 2024
CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with
  GNNs
CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs
Florian Grötschla
Joël Mathys
Robert Veres
Roger Wattenhofer
24
3
0
09 Feb 2024
Let Your Graph Do the Talking: Encoding Structured Data for LLMs
Let Your Graph Do the Talking: Encoding Structured Data for LLMs
Bryan Perozzi
Bahare Fatemi
Dustin Zelle
Anton Tsitsulin
Mehran Kazemi
Rami Al-Rfou
Jonathan J. Halcrow
GNN
42
57
0
08 Feb 2024
Position: Graph Foundation Models are Already Here
Position: Graph Foundation Models are Already Here
Haitao Mao
Zhikai Chen
Wenzhuo Tang
Jianan Zhao
Yao Ma
Tong Zhao
Neil Shah
Mikhail Galkin
Jiliang Tang
AI4CE
66
28
0
03 Feb 2024
Rethinking Spectral Graph Neural Networks with Spatially Adaptive
  Filtering
Rethinking Spectral Graph Neural Networks with Spatially Adaptive Filtering
Jingwei Guo
Kaizhu Huang
Xinping Yi
Zixian Su
Rui Zhang
24
3
0
17 Jan 2024
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph
  Neural Networks
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
Puja Trivedi
Mark Heimann
Rushil Anirudh
Danai Koutra
Jayaraman J. Thiagarajan
UQCV
31
4
0
07 Jan 2024
Learning Domain-Independent Heuristics for Grounded and Lifted Planning
Learning Domain-Independent Heuristics for Grounded and Lifted Planning
Dillon Z. Chen
Sylvie Thiébaux
Felipe W. Trevizan
AI4CE
34
16
0
18 Dec 2023
Graph Neural Networks with Diverse Spectral Filtering
Graph Neural Networks with Diverse Spectral Filtering
Jingwei Guo
Kaizhu Huang
Xinping Yi
Rui Zhang
72
12
0
14 Dec 2023
Expressive Sign Equivariant Networks for Spectral Geometric Learning
Expressive Sign Equivariant Networks for Spectral Geometric Learning
Derek Lim
Joshua Robinson
Stefanie Jegelka
Haggai Maron
84
16
0
04 Dec 2023
Leveraging Graph Diffusion Models for Network Refinement Tasks
Leveraging Graph Diffusion Models for Network Refinement Tasks
Puja Trivedi
Ryan A. Rossi
David Arbour
Tong Yu
Franck Dernoncourt
Sungchul Kim
Nedim Lipka
Namyong Park
Nesreen K. Ahmed
Danai Koutra
DiffM
34
0
0
29 Nov 2023
Cycle Invariant Positional Encoding for Graph Representation Learning
Cycle Invariant Positional Encoding for Graph Representation Learning
Zuoyu Yan
Teng Ma
Liangcai Gao
Zhi Tang
Chao Chen
Yusu Wang
44
5
0
24 Nov 2023
Laplacian Canonization: A Minimalist Approach to Sign and Basis
  Invariant Spectral Embedding
Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding
Jiangyan Ma
Yifei Wang
Yisen Wang
41
13
0
28 Oct 2023
Data-centric Graph Learning: A Survey
Data-centric Graph Learning: A Survey
Jixi Liu
Deyu Bo
Cheng Yang
Haoran Dai
Qi Zhang
Yixin Xiao
Yufei Peng
Chuan Shi
GNN
35
19
0
08 Oct 2023
On the Stability of Expressive Positional Encodings for Graphs
On the Stability of Expressive Positional Encodings for Graphs
Yinan Huang
William Lu
Joshua Robinson
Yu Yang
Muhan Zhang
Stefanie Jegelka
Pan Li
40
8
0
04 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
23
1
0
02 Oct 2023
Revisiting Link Prediction: A Data Perspective
Revisiting Link Prediction: A Data Perspective
Haitao Mao
Juanhui Li
Harry Shomer
Bingheng Li
Wenqi Fan
Yao Ma
Tong Zhao
Neil Shah
Jiliang Tang
52
24
0
01 Oct 2023
Rethinking the Power of Graph Canonization in Graph Representation
  Learning with Stability
Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability
Zehao Dong
Muhan Zhang
Philip R. O. Payne
Michael Province
C. Cruchaga
Tianyu Zhao
Fuhai Li
Yixin Chen
43
1
0
01 Sep 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
20
0
16 Aug 2023
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