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Generalizing Convolutional Neural Networks for Equivariance to Lie
  Groups on Arbitrary Continuous Data

Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data

25 February 2020
Marc Finzi
Samuel Stanton
Pavel Izmailov
A. Wilson
ArXivPDFHTML

Papers citing "Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data"

50 / 70 papers shown
Title
Symmetries-enhanced Multi-Agent Reinforcement Learning
Symmetries-enhanced Multi-Agent Reinforcement Learning
N. Bousias
Stefanos Pertigkiozoglou
Kostas Daniilidis
George Pappas
AI4CE
73
0
0
02 Jan 2025
Unsupervised Representation Learning from Sparse Transformation Analysis
Unsupervised Representation Learning from Sparse Transformation Analysis
Yue Song
Thomas Anderson Keller
Yisong Yue
Pietro Perona
Max Welling
DRL
29
0
0
07 Oct 2024
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups
Zakhar Shumaylov
Peter Zaika
James Rowbottom
Ferdia Sherry
Melanie Weber
Carola-Bibiane Schönlieb
34
1
0
03 Oct 2024
Variational Partial Group Convolutions for Input-Aware Partial
  Equivariance of Rotations and Color-Shifts
Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts
Hyunsu Kim
Yegon Kim
Hongseok Yang
Juho Lee
37
0
0
05 Jul 2024
Relaxing Continuous Constraints of Equivariant Graph Neural Networks for
  Physical Dynamics Learning
Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning
Zinan Zheng
Yang Liu
Jia Li
Jianhua Yao
Yu Rong
AI4CE
51
1
0
24 Jun 2024
Molecule Graph Networks with Many-body Equivariant Interactions
Molecule Graph Networks with Many-body Equivariant Interactions
Zetian Mao
Jiawen Li
Chen Liang
Diptesh Das
Masato Sumita
Koji Tsuda
Kelin Xia
Koji Tsuda
35
1
0
19 Jun 2024
E(n) Equivariant Topological Neural Networks
E(n) Equivariant Topological Neural Networks
Claudio Battiloro
Ege Karaismailoglu
Mauricio Tec
George Dasoulas
Michelle Audirac
Francesca Dominici
47
5
0
24 May 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
Jiaqi Han
Jiacheng Cen
Liming Wu
Zongzhao Li
Xiangzhe Kong
...
Zhewei Wei
Deli Zhao
Yu Rong
Wenbing Huang
Wenbing Huang
AI4CE
34
20
0
01 Mar 2024
Bi-invariant Dissimilarity Measures for Sample Distributions in Lie
  Groups
Bi-invariant Dissimilarity Measures for Sample Distributions in Lie Groups
M. Hanik
H. Hege
C. V. Tycowicz
19
3
0
20 Feb 2024
Equivariant Symmetry Breaking Sets
Equivariant Symmetry Breaking Sets
YuQing Xie
Tess E. Smidt
25
4
0
05 Feb 2024
CFASL: Composite Factor-Aligned Symmetry Learning for Disentanglement in
  Variational AutoEncoder
CFASL: Composite Factor-Aligned Symmetry Learning for Disentanglement in Variational AutoEncoder
Heeseung Jung
Jaehyoung Jeong
Kangil Kim
CoGe
26
0
0
17 Jan 2024
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie
  Algebras
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras
Tzu-Yuan Lin
Minghan Zhu
Maani Ghaffari
40
1
0
06 Oct 2023
Learned Gridification for Efficient Point Cloud Processing
Learned Gridification for Efficient Point Cloud Processing
P. A. V. D. Linden
David W. Romero
Erik J. Bekkers
3DPC
20
2
0
22 Jul 2023
A new perspective on building efficient and expressive 3D equivariant
  graph neural networks
A new perspective on building efficient and expressive 3D equivariant graph neural networks
Weitao Du
Yuanqi Du
Limei Wang
Dieqiao Feng
Guifeng Wang
Shuiwang Ji
Carla P. Gomes
Zhixin Ma
AI4CE
27
33
0
07 Apr 2023
EqMotion: Equivariant Multi-agent Motion Prediction with Invariant
  Interaction Reasoning
EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning
Chenxin Xu
R. Tan
Yuhong Tan
Siheng Chen
Yu Wang
Xinchao Wang
Yanfeng Wang
30
96
0
20 Mar 2023
Steerable Equivariant Representation Learning
Steerable Equivariant Representation Learning
Sangnie Bhardwaj
Willie McClinton
Tongzhou Wang
Guillaume Lajoie
Chen Sun
Phillip Isola
Dilip Krishnan
OOD
LLMSV
26
5
0
22 Feb 2023
GPS++: Reviving the Art of Message Passing for Molecular Property
  Prediction
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction
Dominic Masters
Josef Dean
Kerstin Klaser
Zhiyi Li
Sam Maddrell-Mander
...
D. Beker
Andrew Fitzgibbon
Shenyang Huang
Ladislav Rampášek
Dominique Beaini
28
8
0
06 Feb 2023
Implicit Convolutional Kernels for Steerable CNNs
Implicit Convolutional Kernels for Steerable CNNs
Maksim Zhdanov
Nico Hoffmann
Gabriele Cesa
24
5
0
12 Dec 2022
PAC-Bayes Compression Bounds So Tight That They Can Explain
  Generalization
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization
Sanae Lotfi
Marc Finzi
Sanyam Kapoor
Andres Potapczynski
Micah Goldblum
A. Wilson
BDL
MLT
AI4CE
19
51
0
24 Nov 2022
Homomorphic Self-Supervised Learning
Homomorphic Self-Supervised Learning
Thomas Anderson Keller
Xavier Suau
Luca Zappella
SSL
19
2
0
15 Nov 2022
A PAC-Bayesian Generalization Bound for Equivariant Networks
A PAC-Bayesian Generalization Bound for Equivariant Networks
Arash Behboodi
Gabriele Cesa
Taco S. Cohen
48
17
0
24 Oct 2022
A tradeoff between universality of equivariant models and learnability
  of symmetries
A tradeoff between universality of equivariant models and learnability of symmetries
Vasco Portilheiro
25
2
0
17 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
27
88
0
16 Oct 2022
S4ND: Modeling Images and Videos as Multidimensional Signals Using State
  Spaces
S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces
Eric N. D. Nguyen
Karan Goel
Albert Gu
Gordon W. Downs
Preey Shah
Tri Dao
S. Baccus
Christopher Ré
VLM
22
38
0
12 Oct 2022
How Much Data Are Augmentations Worth? An Investigation into Scaling
  Laws, Invariance, and Implicit Regularization
How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization
Jonas Geiping
Micah Goldblum
Gowthami Somepalli
Ravid Shwartz-Ziv
Tom Goldstein
A. Wilson
24
35
0
12 Oct 2022
The Lie Derivative for Measuring Learned Equivariance
The Lie Derivative for Measuring Learned Equivariance
Nate Gruver
Marc Finzi
Micah Goldblum
A. Wilson
16
34
0
06 Oct 2022
Analysis of (sub-)Riemannian PDE-G-CNNs
Analysis of (sub-)Riemannian PDE-G-CNNs
Gijs Bellaard
Daan Bon
Gautam Pai
B. Smets
R. Duits
AI4CE
28
12
0
03 Oct 2022
Automatic Data Augmentation via Invariance-Constrained Learning
Automatic Data Augmentation via Invariance-Constrained Learning
Ignacio Hounie
Luiz F. O. Chamon
Alejandro Ribeiro
23
10
0
29 Sep 2022
Exact conservation laws for neural network integrators of dynamical
  systems
Exact conservation laws for neural network integrators of dynamical systems
E. Müller
PINN
41
12
0
23 Sep 2022
The Neural Process Family: Survey, Applications and Perspectives
The Neural Process Family: Survey, Applications and Perspectives
Saurav Jha
Dong Gong
Xuesong Wang
Richard E. Turner
L. Yao
BDL
73
24
0
01 Sep 2022
Deep Neural Network Approximation of Invariant Functions through
  Dynamical Systems
Deep Neural Network Approximation of Invariant Functions through Dynamical Systems
Qianxiao Li
T. Lin
Zuowei Shen
18
6
0
18 Aug 2022
Graph neural networks for materials science and chemistry
Graph neural networks for materials science and chemistry
Patrick Reiser
Marlen Neubert
André Eberhard
Luca Torresi
Chen Zhou
...
Houssam Metni
Clint van Hoesel
Henrik Schopmans
T. Sommer
Pascal Friederich
GNN
AI4CE
39
370
0
05 Aug 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
Edgar Dobriban
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
16
18
0
11 Jun 2022
Relaxing Equivariance Constraints with Non-stationary Continuous Filters
Relaxing Equivariance Constraints with Non-stationary Continuous Filters
Tycho F. A. van der Ouderaa
David W. Romero
Mark van der Wilk
24
33
0
14 Apr 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed
  Machine Learning
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning
Chuizheng Meng
Sungyong Seo
Defu Cao
Sam Griesemer
Yan Liu
PINN
AI4CE
34
55
0
31 Mar 2022
Symmetry-Based Representations for Artificial and Biological General
  Intelligence
Symmetry-Based Representations for Artificial and Biological General Intelligence
I. Higgins
S. Racanière
Danilo Jimenez Rezende
AI4CE
24
44
0
17 Mar 2022
Equivariant Graph Mechanics Networks with Constraints
Equivariant Graph Mechanics Networks with Constraints
Wen-bing Huang
J. Han
Yu Rong
Tingyang Xu
Fuchun Sun
Junzhou Huang
AI4CE
33
79
0
12 Mar 2022
Equivariant Graph Attention Networks for Molecular Property Prediction
Equivariant Graph Attention Networks for Molecular Property Prediction
Tuan Le
Frank Noé
Djork-Arné Clevert
11
21
0
20 Feb 2022
Residual Pathway Priors for Soft Equivariance Constraints
Residual Pathway Priors for Soft Equivariance Constraints
Marc Finzi
Gregory W. Benton
A. Wilson
BDL
UQCV
24
50
0
02 Dec 2021
Co-domain Symmetry for Complex-Valued Deep Learning
Co-domain Symmetry for Complex-Valued Deep Learning
Utkarsh Singhal
Yifei Xing
Stella X. Yu
23
12
0
02 Dec 2021
Deformation Robust Roto-Scale-Translation Equivariant CNNs
Deformation Robust Roto-Scale-Translation Equivariant CNNs
Liyao (Mars) Gao
Guang Lin
Wei-wei Zhu
15
8
0
22 Nov 2021
Physics-enhanced Neural Networks in the Small Data Regime
Physics-enhanced Neural Networks in the Small Data Regime
Jonas Eichelsdörfer
Sebastian Kaltenbach
P. Koutsourelakis
AI4CE
PINN
6
5
0
19 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-Neng Chen
Bin Shao
Tie-Yan Liu
48
79
0
26 Oct 2021
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel
  Sizes
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes
David W. Romero
Robert-Jan Bruintjes
Jakub M. Tomczak
Erik J. Bekkers
Mark Hoogendoorn
J. C. V. Gemert
80
81
0
15 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
13
5
0
14 Oct 2021
Relative Molecule Self-Attention Transformer
Relative Molecule Self-Attention Transformer
Lukasz Maziarka
Dawid Majchrowski
Tomasz Danel
Piotr Gaiñski
Jacek Tabor
Igor T. Podolak
Pawel M. Morkisz
Stanislaw Jastrzebski
MedIm
32
34
0
12 Oct 2021
Geometric and Physical Quantities Improve E(3) Equivariant Message
  Passing
Geometric and Physical Quantities Improve E(3) Equivariant Message Passing
Johannes Brandstetter
Rob D. Hesselink
Elise van der Pol
Erik J. Bekkers
Max Welling
17
229
0
06 Oct 2021
Automatic Symmetry Discovery with Lie Algebra Convolutional Network
Automatic Symmetry Discovery with Lie Algebra Convolutional Network
Nima Dehmamy
Robin G. Walters
Yanchen Liu
Dashun Wang
Rose Yu
AI4CE
78
81
0
15 Sep 2021
Topographic VAEs learn Equivariant Capsules
Topographic VAEs learn Equivariant Capsules
Thomas Anderson Keller
Max Welling
BDL
36
38
0
03 Sep 2021
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