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An Information-Theoretic Perspective on Variance-Invariance-Covariance
  Regularization
v1v2v3v4 (latest)

An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization

1 March 2023
Ravid Shwartz-Ziv
Randall Balestriero
Kenji Kawaguchi
Tim G. J. Rudner
Yann LeCun
ArXiv (abs)PDFHTML

Papers citing "An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization"

17 / 17 papers shown
Title
The Alignment Bottleneck
The Alignment Bottleneck
Wenjun Cao
196
0
0
19 Sep 2025
Video Representation Learning with Joint-Embedding Predictive
  Architectures
Video Representation Learning with Joint-Embedding Predictive Architectures
Katrina Drozdov
Ravid Shwartz-Ziv
Yann LeCun
AI4TS
301
6
0
14 Dec 2024
Explicit Mutual Information Maximization for Self-Supervised Learning
Explicit Mutual Information Maximization for Self-Supervised LearningIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024
Lele Chang
Peilin Liu
Qinghai Guo
Fei Wen
SSL
227
0
0
07 Sep 2024
Unsqueeze [CLS] Bottleneck to Learn Rich Representations
Unsqueeze [CLS] Bottleneck to Learn Rich Representations
Qing Su
Shihao Ji
236
0
0
24 Jul 2024
Missing Modality Prediction for Unpaired Multimodal Learning via Joint
  Embedding of Unimodal Models
Missing Modality Prediction for Unpaired Multimodal Learning via Joint Embedding of Unimodal Models
Donggeun Kim
Taesup Kim
200
12
0
17 Jul 2024
Towards an Improved Understanding and Utilization of Maximum Manifold
  Capacity Representations
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations
Rylan Schaeffer
Victor Lecomte
Dhruv Pai
Andres Carranza
Berivan Isik
...
Yann LeCun
SueYeon Chung
Andrey Gromov
Ravid Shwartz-Ziv
Sanmi Koyejo
257
9
0
13 Jun 2024
Poly-View Contrastive Learning
Poly-View Contrastive LearningInternational Conference on Learning Representations (ICLR), 2024
Amitis Shidani
Devon Hjelm
Jason Ramapuram
Russ Webb
Eeshan Gunesh Dhekane
Dan Busbridge
VLMSSL
193
9
0
08 Mar 2024
A Probabilistic Model behind Self-Supervised Learning
A Probabilistic Model behind Self-Supervised Learning
Alice Bizeul
Bernhard Schölkopf
Carl Allen
SSL
213
2
0
02 Feb 2024
Improving Intrusion Detection with Domain-Invariant Representation Learning in Latent Space
Improving Intrusion Detection with Domain-Invariant Representation Learning in Latent Space
Padmaksha Roy
Tyler Cody
Himanshu Singhal
Kevin Choi
Ming Jin
OOD
336
1
0
28 Dec 2023
Self-Supervised Learning of Representations for Space Generates
  Multi-Modular Grid Cells
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid CellsNeural Information Processing Systems (NeurIPS), 2023
Rylan Schaeffer
Mikail Khona
Tzuhsuan Ma
Cristobal Eyzaguirre
Sanmi Koyejo
Ila Rani Fiete
SSL
158
31
0
04 Nov 2023
Unveiling the Potential of Probabilistic Embeddings in Self-Supervised
  Learning
Unveiling the Potential of Probabilistic Embeddings in Self-Supervised Learning
Denis Janiak
Jakub Binkowski
Piotr Bielak
Tomasz Kajdanowicz
SSLUQCV
206
0
0
27 Oct 2023
Information Flow in Self-Supervised Learning
Information Flow in Self-Supervised LearningInternational Conference on Machine Learning (ICML), 2023
Zhiyuan Tan
Jingqin Yang
Weiran Huang
Yang Yuan
Yifan Zhang
SSL
371
17
0
29 Sep 2023
Variance-Covariance Regularization Improves Representation Learning
Variance-Covariance Regularization Improves Representation Learning
Jiachen Zhu
Katrina Evtimova
Yubei Chen
Ravid Shwartz-Ziv
Yann LeCun
SSL
218
8
0
23 Jun 2023
Feature Learning in Image Hierarchies using Functional Maximal
  Correlation
Feature Learning in Image Hierarchies using Functional Maximal Correlation
Bo Hu
Yuheng Bu
José C. Príncipe
143
1
0
31 May 2023
Reverse Engineering Self-Supervised Learning
Reverse Engineering Self-Supervised LearningNeural Information Processing Systems (NeurIPS), 2023
Ido Ben-Shaul
Ravid Shwartz-Ziv
Tomer Galanti
S. Dekel
Yann LeCun
SSL
207
43
0
24 May 2023
To Compress or Not to Compress- Self-Supervised Learning and Information
  Theory: A Review
To Compress or Not to Compress- Self-Supervised Learning and Information Theory: A ReviewEntropy (Entropy), 2023
Ravid Shwartz-Ziv
Yann LeCun
SSL
515
98
0
19 Apr 2023
Unsupervised Learning of Visual Features by Contrasting Cluster
  Assignments
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCLSSL
1.2K
4,620
0
17 Jun 2020
1