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An Unsupervised Algorithm For Learning Lie Group Transformations
v1v2v3v4v5 (latest)

An Unsupervised Algorithm For Learning Lie Group Transformations

7 January 2010
Jascha Narain Sohl-Dickstein
Jimmy C. Wang
Bruno A. Olshausen
ArXiv (abs)PDFHTML

Papers citing "An Unsupervised Algorithm For Learning Lie Group Transformations"

32 / 32 papers shown
Title
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
61
0
0
13 May 2025
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory
Andrea Perin
Stéphane Deny
134
2
0
16 Dec 2024
Learning Infinitesimal Generators of Continuous Symmetries from Data
Learning Infinitesimal Generators of Continuous Symmetries from Data
Gyeonghoon Ko
Hyunsu Kim
Juho Lee
73
5
0
29 Oct 2024
SymmetryLens: A new candidate paradigm for unsupervised symmetry
  learning via locality and equivariance
SymmetryLens: A new candidate paradigm for unsupervised symmetry learning via locality and equivariance
Onur Efe
Arkadas Ozakin
70
0
0
07 Oct 2024
Symmetry Discovery Beyond Affine Transformations
Symmetry Discovery Beyond Affine Transformations
Ben Shaw
Abram Magner
Kevin R. Moon
130
3
0
05 Jun 2024
Compositional Factorization of Visual Scenes with Convolutional Sparse
  Coding and Resonator Networks
Compositional Factorization of Visual Scenes with Convolutional Sparse Coding and Resonator Networks
Christopher J. Kymn
Sonia Mazelet
Annabel Ng
Denis Kleyko
Bruno A. Olshausen
66
5
0
29 Apr 2024
Harmonics of Learning: Universal Fourier Features Emerge in Invariant
  Networks
Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks
Giovanni Luca Marchetti
Christopher Hillar
Danica Kragic
Sophia Sanborn
81
14
0
13 Dec 2023
Learning Lie Group Symmetry Transformations with Neural Networks
Learning Lie Group Symmetry Transformations with Neural Networks
Alex Gabel
Victoria G Klein
Riccardo Valperga
J. Lamb
K. Webster
Rick Quax
E. Gavves
103
7
0
04 Jul 2023
Manifold Contrastive Learning with Variational Lie Group Operators
Manifold Contrastive Learning with Variational Lie Group Operators
Kion Fallah
Alec Helbling
Kyle A. Johnsen
Christopher Rozell
SSLDRL
74
1
0
23 Jun 2023
Learning Internal Representations of 3D Transformations from 2D
  Projected Inputs
Learning Internal Representations of 3D Transformations from 2D Projected Inputs
Marissa Connor
Bruno A. Olshausen
Christopher Rozell
74
1
0
31 Mar 2023
Commutativity and Disentanglement from the Manifold Perspective
Commutativity and Disentanglement from the Manifold Perspective
Frank Qiu
CoGe
47
0
0
14 Oct 2022
Unsupervised Learning of Equivariant Structure from Sequences
Unsupervised Learning of Equivariant Structure from Sequences
Takeru Miyato
Masanori Koyama
Kenji Fukumizu
86
12
0
12 Oct 2022
LieGG: Studying Learned Lie Group Generators
LieGG: Studying Learned Lie Group Generators
A. Moskalev
A. Sepliarskaia
Ivan Sosnovik
A. Smeulders
88
27
0
09 Oct 2022
Bispectral Neural Networks
Bispectral Neural Networks
Sophia Sanborn
Christian Shewmake
Bruno A. Olshausen
Christopher Hillar
74
13
0
07 Sep 2022
Disentangling Patterns and Transformations from One Sequence of Images
  with Shape-invariant Lie Group Transformer
Disentangling Patterns and Transformations from One Sequence of Images with Shape-invariant Lie Group Transformer
Takumi Takada
Wataru Shimaya
Yoshiyuki Ohmura
Yasuo Kuniyoshi
ViT
40
3
0
21 Mar 2022
Hamiltonian latent operators for content and motion disentanglement in
  image sequences
Hamiltonian latent operators for content and motion disentanglement in image sequences
Asif Khan
Amos Storkey
64
2
0
02 Dec 2021
Automatic Symmetry Discovery with Lie Algebra Convolutional Network
Automatic Symmetry Discovery with Lie Algebra Convolutional Network
Nima Dehmamy
Robin Walters
Yanchen Liu
Dashun Wang
Rose Yu
AI4CE
171
88
0
15 Sep 2021
Learning Identity-Preserving Transformations on Data Manifolds
Learning Identity-Preserving Transformations on Data Manifolds
Marissa Connor
Kion Fallah
Christopher Rozell
72
6
0
22 Jun 2021
Addressing the Topological Defects of Disentanglement via Distributed
  Operators
Addressing the Topological Defects of Disentanglement via Distributed Operators
Diane Bouchacourt
Mark Ibrahim
Stéphane Deny
38
22
0
10 Feb 2021
Disentangling images with Lie group transformations and sparse coding
Disentangling images with Lie group transformations and sparse coding
Ho Yin Chau
Frank Qiu
Yubei Chen
Bruno A. Olshausen
57
13
0
11 Dec 2020
Joint Estimation of Image Representations and their Lie Invariants
Joint Estimation of Image Representations and their Lie Invariants
Christine Allen-Blanchette
Kostas Daniilidis
18
0
0
05 Dec 2020
Deep Autoencoders: From Understanding to Generalization Guarantees
Deep Autoencoders: From Understanding to Generalization Guarantees
Romain Cosentino
Randall Balestriero
Richard Baraniuk
B. Aazhang
40
6
0
20 Sep 2020
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse
  Coding
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
David A. Klindt
Lukas Schott
Yash Sharma
Ivan Ustyuzhaninov
Wieland Brendel
Matthias Bethge
Dylan M. Paiton
CML
137
134
0
21 Jul 2020
Disentangling by Subspace Diffusion
Disentangling by Subspace Diffusion
David Pfau
I. Higgins
Aleksandar Botev
S. Racanière
DiffMDRL
79
37
0
23 Jun 2020
Invariant Feature Coding using Tensor Product Representation
Invariant Feature Coding using Tensor Product Representation
Yusuke Mukuta
Tatsuya Harada
43
0
0
05 Jun 2019
Towards a Definition of Disentangled Representations
Towards a Definition of Disentangled Representations
I. Higgins
David Amos
David Pfau
S. Racanière
Loic Matthey
Danilo Jimenez Rezende
Alexander Lerchner
OCLDRL
118
480
0
05 Dec 2018
Transformational Sparse Coding
Transformational Sparse Coding
Dimitrios C. Gklezakos
Rajesh P. N. Rao
24
2
0
08 Dec 2017
Unsupervised Transformation Learning via Convex Relaxations
Unsupervised Transformation Learning via Convex Relaxations
Tatsunori B. Hashimoto
John C. Duchi
Percy Liang
50
12
0
06 Nov 2017
A Probabilistic Theory of Deep Learning
A Probabilistic Theory of Deep Learning
Ankit B. Patel
M. T. Nguyen
Richard G. Baraniuk
BDLOODUQCV
94
89
0
02 Apr 2015
Transformation Properties of Learned Visual Representations
Transformation Properties of Learned Visual Representations
Taco S. Cohen
Max Welling
75
106
0
24 Dec 2014
Efficient Methods for Unsupervised Learning of Probabilistic Models
Efficient Methods for Unsupervised Learning of Probabilistic Models
Jascha Narain Sohl-Dickstein
TPM
55
0
0
19 May 2012
Learning image transformations without training examples
Learning image transformations without training examples
S. Pankov
3DH
47
0
0
01 Oct 2011
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