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Universal Invariant and Equivariant Graph Neural Networks

Universal Invariant and Equivariant Graph Neural Networks

13 May 2019
Nicolas Keriven
Gabriel Peyré
ArXivPDFHTML

Papers citing "Universal Invariant and Equivariant Graph Neural Networks"

50 / 82 papers shown
Title
Quotient Complex Transformer (QCformer) for Perovskite Data Analysis
Quotient Complex Transformer (QCformer) for Perovskite Data Analysis
Xinyu You
Xiang Liu
Chuan-Shen Hu
Kelin Xia
Tze Chien Sum
24
0
0
14 May 2025
SpecSphere: Dual-Pass Spectral-Spatial Graph Neural Networks with Certified Robustness
SpecSphere: Dual-Pass Spectral-Spatial Graph Neural Networks with Certified Robustness
Yoonhyuk Choi
Chong-Kwon Kim
31
0
0
13 May 2025
Lie Group Symmetry Discovery and Enforcement Using Vector Fields
Lie Group Symmetry Discovery and Enforcement Using Vector Fields
Ben Shaw
Sasidhar Kunapuli
Abram Magner
Kevin R. Moon
32
0
0
13 May 2025
Monocular visual simultaneous localization and mapping: (r)evolution from geometry to deep learning-based pipelines
Olaya Álvarez-Tunón
Yury Brodskiy
Erdal Kayacan
73
6
0
04 Mar 2025
GOFA: A Generative One-For-All Model for Joint Graph Language Modeling
GOFA: A Generative One-For-All Model for Joint Graph Language Modeling
Lecheng Kong
Jiarui Feng
Hao Liu
Chengsong Huang
Jiaxin Huang
Yixin Chen
Muhan Zhang
AI4CE
77
6
0
12 Jul 2024
On normalization-equivariance properties of supervised and unsupervised
  denoising methods: a survey
On normalization-equivariance properties of supervised and unsupervised denoising methods: a survey
Sébastien Herbreteau
Charles Kervrann
OOD
43
0
0
23 Feb 2024
Isomorphic-Consistent Variational Graph Auto-Encoders for Multi-Level
  Graph Representation Learning
Isomorphic-Consistent Variational Graph Auto-Encoders for Multi-Level Graph Representation Learning
Hanxuan Yang
Qingchao Kong
Wenji Mao
BDL
22
0
0
09 Dec 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
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
49
7
0
21 Apr 2023
Equivariant Architectures for Learning in Deep Weight Spaces
Equivariant Architectures for Learning in Deep Weight Spaces
Aviv Navon
Aviv Shamsian
Idan Achituve
Ethan Fetaya
Gal Chechik
Haggai Maron
47
63
0
30 Jan 2023
An Analysis of Attention via the Lens of Exchangeability and Latent
  Variable Models
An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models
Yufeng Zhang
Boyi Liu
Qi Cai
Lingxiao Wang
Zhaoran Wang
53
11
0
30 Dec 2022
VC dimensions of group convolutional neural networks
VC dimensions of group convolutional neural networks
P. Petersen
A. Sepliarskaia
VLM
27
7
0
19 Dec 2022
Graph Convolutional Neural Networks as Parametric CoKleisli morphisms
Graph Convolutional Neural Networks as Parametric CoKleisli morphisms
Bruno Gavranović
M. Villani
GNN
86
0
0
01 Dec 2022
On the Ability of Graph Neural Networks to Model Interactions Between
  Vertices
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Noam Razin
Tom Verbin
Nadav Cohen
23
10
0
29 Nov 2022
KGTN-ens: Few-Shot Image Classification with Knowledge Graph Ensembles
KGTN-ens: Few-Shot Image Classification with Knowledge Graph Ensembles
Dominik Filipiak
A. Fensel
A. Filipowska
33
1
0
06 Nov 2022
Theoretical Guarantees for Permutation-Equivariant Quantum Neural
  Networks
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks
Louis Schatzki
Martín Larocca
Quynh T. Nguyen
F. Sauvage
M. Cerezo
39
84
0
18 Oct 2022
Theory for Equivariant Quantum Neural Networks
Theory for Equivariant Quantum Neural Networks
Quynh T. Nguyen
Louis Schatzki
Paolo Braccia
Michael Ragone
Patrick J. Coles
F. Sauvage
Martín Larocca
M. Cerezo
40
89
0
16 Oct 2022
On Representing Linear Programs by Graph Neural Networks
On Representing Linear Programs by Graph Neural Networks
Ziang Chen
Jialin Liu
Xinshang Wang
Jian Lu
W. Yin
AI4CE
60
31
0
25 Sep 2022
Periodic Graph Transformers for Crystal Material Property Prediction
Periodic Graph Transformers for Crystal Material Property Prediction
Keqiang Yan
Yi Liu
Yu-Ching Lin
Shuiwang Ji
AI4TS
88
84
0
23 Sep 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications
Diffusion Models: A Comprehensive Survey of Methods and Applications
Ling Yang
Zhilong Zhang
Yingxia Shao
Shenda Hong
Runsheng Xu
Yue Zhao
Wentao Zhang
Tengjiao Wang
Ming-Hsuan Yang
DiffM
MedIm
224
1,304
0
02 Sep 2022
Graph Neural Network Based Node Deployment for Throughput Enhancement
Graph Neural Network Based Node Deployment for Throughput Enhancement
Yifei Yang
Dongmian Zou
Xiaofan He
15
5
0
19 Aug 2022
Thermodynamics of learning physical phenomena
Thermodynamics of learning physical phenomena
Elías Cueto
Francisco Chinesta
AI4CE
25
22
0
26 Jul 2022
Pure Transformers are Powerful Graph Learners
Pure Transformers are Powerful Graph Learners
Jinwoo Kim
Tien Dat Nguyen
Seonwoo Min
Sungjun Cho
Moontae Lee
Honglak Lee
Seunghoon Hong
43
189
0
06 Jul 2022
State-Augmented Learnable Algorithms for Resource Management in Wireless
  Networks
State-Augmented Learnable Algorithms for Resource Management in Wireless Networks
Navid Naderializadeh
Mark Eisen
Alejandro Ribeiro
29
17
0
05 Jul 2022
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant
  Networks on Homogeneous Spaces
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces
Yinshuang Xu
Jiahui Lei
Yan Sun
Kostas Daniilidis
23
19
0
16 Jun 2022
E2PN: Efficient SE(3)-Equivariant Point Network
E2PN: Efficient SE(3)-Equivariant Point Network
Minghan Zhu
Maani Ghaffari
W. A. Clark
Huei Peng
3DPC
27
18
0
11 Jun 2022
Shortest Path Networks for Graph Property Prediction
Shortest Path Networks for Graph Property Prediction
Ralph Abboud
Radoslav Dimitrov
.Ismail .Ilkan Ceylan
GNN
27
45
0
02 Jun 2022
Low Dimensional Invariant Embeddings for Universal Geometric Learning
Low Dimensional Invariant Embeddings for Universal Geometric Learning
Nadav Dym
S. Gortler
29
39
0
05 May 2022
Theory of Graph Neural Networks: Representation and Learning
Theory of Graph Neural Networks: Representation and Learning
Stefanie Jegelka
GNN
AI4CE
33
68
0
16 Apr 2022
Permutation Invariant Representations with Applications to Graph Deep
  Learning
Permutation Invariant Representations with Applications to Graph Deep Learning
R. Balan
Naveed Haghani
M. Singh
28
25
0
14 Mar 2022
Learning Resilient Radio Resource Management Policies with Graph Neural
  Networks
Learning Resilient Radio Resource Management Policies with Graph Neural Networks
Navid Naderializadeh
Mark Eisen
Alejandro Ribeiro
24
27
0
07 Mar 2022
Thermodynamics-informed graph neural networks
Thermodynamics-informed graph neural networks
Quercus Hernandez
Alberto Badías
Francisco Chinesta
Elías Cueto
AI4CE
PINN
32
31
0
03 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
49
141
0
25 Feb 2022
Robust Hybrid Learning With Expert Augmentation
Robust Hybrid Learning With Expert Augmentation
Antoine Wehenkel
Jens Behrmann
Hsiang Hsu
Guillermo Sapiro
Gilles Louppe and
J. Jacobsen
26
8
0
08 Feb 2022
Score-based Generative Modeling of Graphs via the System of Stochastic
  Differential Equations
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations
Jaehyeong Jo
Seul Lee
Sung Ju Hwang
DiffM
22
210
0
05 Feb 2022
What Has Been Enhanced in my Knowledge-Enhanced Language Model?
What Has Been Enhanced in my Knowledge-Enhanced Language Model?
Yifan Hou
Guoji Fu
Mrinmaya Sachan
KELM
33
1
0
02 Feb 2022
Debiased Graph Neural Networks with Agnostic Label Selection Bias
Debiased Graph Neural Networks with Agnostic Label Selection Bias
Shaohua Fan
Xiao Wang
Chuan Shi
Kun Kuang
Nian Liu
Bai Wang
AI4CE
44
38
0
19 Jan 2022
How Can Graph Neural Networks Help Document Retrieval: A Case Study on
  CORD19 with Concept Map Generation
How Can Graph Neural Networks Help Document Retrieval: A Case Study on CORD19 with Concept Map Generation
Hejie Cui
Jiaying Lu
Yao Ge
Carl Yang
19
22
0
12 Jan 2022
Robust Graph Neural Networks via Probabilistic Lipschitz Constraints
Robust Graph Neural Networks via Probabilistic Lipschitz Constraints
R. Arghal
E. Lei
Shirin Saeedi Bidokhti
13
19
0
14 Dec 2021
Explicitly antisymmetrized neural network layers for variational Monte
  Carlo simulation
Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation
Jeffmin Lin
Gil Goldshlager
Lin Lin
40
22
0
07 Dec 2021
ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point
  Clouds
ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point Clouds
Georg Bökman
Fredrik Kahl
Axel Flinth
3DPC
26
19
0
30 Nov 2021
Deformation Robust Roto-Scale-Translation Equivariant CNNs
Deformation Robust Roto-Scale-Translation Equivariant CNNs
Liyao (Mars) Gao
Guang Lin
Wei-wei Zhu
22
8
0
22 Nov 2021
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
Shaohua Fan
Xiao Wang
Chuan Shi
Peng Cui
Bai Wang
CML
OOD
OODD
AI4CE
54
81
0
20 Nov 2021
Learning on Random Balls is Sufficient for Estimating (Some) Graph
  Parameters
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters
Takanori Maehara
Hoang NT
41
2
0
05 Nov 2021
SE(3) Equivariant Graph Neural Networks with Complete Local Frames
SE(3) Equivariant Graph Neural Networks with Complete Local Frames
Weitao Du
He Zhang
Yuanqi Du
Qi Meng
Wei Chen
Bin Shao
Tie-Yan Liu
56
79
0
26 Oct 2021
Capacity of Group-invariant Linear Readouts from Equivariant
  Representations: How Many Objects can be Linearly Classified Under All
  Possible Views?
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views?
M. Farrell
Blake Bordelon
Shubhendu Trivedi
C. Pehlevan
18
5
0
14 Oct 2021
Understanding Pooling in Graph Neural Networks
Understanding Pooling in Graph Neural Networks
Daniele Grattarola
Daniele Zambon
F. Bianchi
Cesare Alippi
GNN
FAtt
AI4CE
30
90
0
11 Oct 2021
From Stars to Subgraphs: Uplifting Any GNN with Local Structure
  Awareness
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness
Lingxiao Zhao
Wei Jin
L. Akoglu
Neil Shah
GNN
24
160
0
07 Oct 2021
Training Stable Graph Neural Networks Through Constrained Learning
Training Stable Graph Neural Networks Through Constrained Learning
J. Cerviño
Luana Ruiz
Alejandro Ribeiro
GNN
31
12
0
07 Oct 2021
Equivariant Subgraph Aggregation Networks
Equivariant Subgraph Aggregation Networks
Beatrice Bevilacqua
Fabrizio Frasca
Derek Lim
Balasubramaniam Srinivasan
Chen Cai
G. Balamurugan
M. Bronstein
Haggai Maron
53
175
0
06 Oct 2021
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