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Understanding Dimensional Collapse in Contrastive Self-supervised
  Learning

Understanding Dimensional Collapse in Contrastive Self-supervised Learning

18 October 2021
Li Jing
Pascal Vincent
Yann LeCun
Yuandong Tian
    SSL
ArXivPDFHTML

Papers citing "Understanding Dimensional Collapse in Contrastive Self-supervised Learning"

31 / 231 papers shown
Title
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor
  Embedding
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding
Tianyang Hu
Zhili Liu
Fengwei Zhou
Wenjia Wang
Weiran Huang
SSL
36
26
0
30 May 2022
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global
  and Local Spectral Embedding Methods
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods
Randall Balestriero
Yann LeCun
SSL
18
129
0
23 May 2022
Toward a Geometrical Understanding of Self-supervised Contrastive
  Learning
Toward a Geometrical Understanding of Self-supervised Contrastive Learning
Romain Cosentino
Anirvan M. Sengupta
Salman Avestimehr
Mahdi Soltanolkotabi
Antonio Ortega
Ted Willke
Mariano Tepper
SSL
37
17
0
13 May 2022
Posterior Collapse of a Linear Latent Variable Model
Posterior Collapse of a Linear Latent Variable Model
Zihao W. Wang
Liu Ziyin
BDL
25
21
0
09 May 2022
Reducing Predictive Feature Suppression in Resource-Constrained
  Contrastive Image-Caption Retrieval
Reducing Predictive Feature Suppression in Resource-Constrained Contrastive Image-Caption Retrieval
Maurits J. R. Bleeker
Andrew Yates
Maarten de Rijke
41
4
0
28 Apr 2022
On the Representation Collapse of Sparse Mixture of Experts
On the Representation Collapse of Sparse Mixture of Experts
Zewen Chi
Li Dong
Shaohan Huang
Damai Dai
Shuming Ma
...
Payal Bajaj
Xia Song
Xian-Ling Mao
Heyan Huang
Furu Wei
MoMe
MoE
37
96
0
20 Apr 2022
Empirical Evaluation and Theoretical Analysis for Representation
  Learning: A Survey
Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey
Kento Nozawa
Issei Sato
AI4TS
19
4
0
18 Apr 2022
Perfectly Balanced: Improving Transfer and Robustness of Supervised
  Contrastive Learning
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning
Mayee F. Chen
Daniel Y. Fu
A. Narayan
Michael Zhang
Zhao-quan Song
Kayvon Fatahalian
Christopher Ré
SSL
19
46
0
15 Apr 2022
Deep Normed Embeddings for Patient Representation
Deep Normed Embeddings for Patient Representation
Thesath Nanayakkara
G. Clermont
C. Langmead
D. Swigon
AI4TS
25
1
0
12 Apr 2022
Simplicial Embeddings in Self-Supervised Learning and Downstream
  Classification
Simplicial Embeddings in Self-Supervised Learning and Downstream Classification
Samuel Lavoie
Christos Tsirigotis
Max Schwarzer
Ankit Vani
Michael Noukhovitch
Kenji Kawaguchi
Aaron C. Courville
SSL
24
17
0
01 Apr 2022
Contrasting the landscape of contrastive and non-contrastive learning
Contrasting the landscape of contrastive and non-contrastive learning
Ashwini Pokle
Jinjin Tian
Yuchen Li
Andrej Risteski
SSL
30
28
0
29 Mar 2022
Probabilistic Spherical Discriminant Analysis: An Alternative to PLDA
  for length-normalized embeddings
Probabilistic Spherical Discriminant Analysis: An Alternative to PLDA for length-normalized embeddings
Niko Brummer
Albert Swart
Ladislav Movsner
Anna Silnova
Oldvrich Plchot
Themos Stafylakis
Lukávs Burget
18
5
0
28 Mar 2022
On Understanding and Mitigating the Dimensional Collapse of Graph
  Contrastive Learning: a Non-Maximum Removal Approach
On Understanding and Mitigating the Dimensional Collapse of Graph Contrastive Learning: a Non-Maximum Removal Approach
Jiawei Sun
Ruoxin Chen
Jie Li
Chentao Wu
Yue Ding
Junchi Yan
29
0
0
24 Mar 2022
Measuring Self-Supervised Representation Quality for Downstream
  Classification using Discriminative Features
Measuring Self-Supervised Representation Quality for Downstream Classification using Discriminative Features
N. Kalibhat
Kanika Narang
Hamed Firooz
Maziar Sanjabi
S. Feizi
SSL
31
7
0
03 Mar 2022
Understanding Contrastive Learning Requires Incorporating Inductive
  Biases
Understanding Contrastive Learning Requires Incorporating Inductive Biases
Nikunj Saunshi
Jordan T. Ash
Surbhi Goel
Dipendra Kumar Misra
Cyril Zhang
Sanjeev Arora
Sham Kakade
A. Krishnamurthy
SSL
21
109
0
28 Feb 2022
A Self-Supervised Descriptor for Image Copy Detection
A Self-Supervised Descriptor for Image Copy Detection
Ed Pizzi
Sreya . Dutta Roy
Sugosh Nagavara Ravindra
Priya Goyal
Matthijs Douze
SSL
34
116
0
21 Feb 2022
When, where, and how to add new neurons to ANNs
When, where, and how to add new neurons to ANNs
Kaitlin Maile
Emmanuel Rachelson
H. Luga
Dennis G. Wilson
19
14
0
17 Feb 2022
data2vec: A General Framework for Self-supervised Learning in Speech,
  Vision and Language
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
Alexei Baevski
Wei-Ning Hsu
Qiantong Xu
Arun Babu
Jiatao Gu
Michael Auli
SSL
VLM
ViT
35
835
0
07 Feb 2022
Understanding Deep Contrastive Learning via Coordinate-wise Optimization
Understanding Deep Contrastive Learning via Coordinate-wise Optimization
Yuandong Tian
52
34
0
29 Jan 2022
Robust Contrastive Learning against Noisy Views
Robust Contrastive Learning against Noisy Views
Ching-Yao Chuang
R. Devon Hjelm
Xin Eric Wang
Vibhav Vineet
Neel Joshi
Antonio Torralba
Stefanie Jegelka
Ya-heng Song
NoLa
13
68
0
12 Jan 2022
Self-Supervised Learning based Monaural Speech Enhancement with
  Complex-Cycle-Consistent
Self-Supervised Learning based Monaural Speech Enhancement with Complex-Cycle-Consistent
Yi Li
Yang Sun
S. M. Naqvi
16
1
0
21 Dec 2021
Weakly-supervised Generative Adversarial Networks for medical image
  classification
Weakly-supervised Generative Adversarial Networks for medical image classification
Jia-min Mao
Xuesong Yin
Yuan Chang
Qi Huang
GAN
MedIm
19
1
0
29 Nov 2021
CoReS: Compatible Representations via Stationarity
CoReS: Compatible Representations via Stationarity
Niccoló Biondi
F. Pernici
Matteo Bruni
A. Bimbo
OOD
16
9
0
15 Nov 2021
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP
Andreas Fürst
Elisabeth Rumetshofer
Johannes Lehner
Viet-Hung Tran
Fei Tang
...
David P. Kreil
Michael K Kopp
G. Klambauer
Angela Bitto-Nemling
Sepp Hochreiter
VLM
CLIP
204
102
0
21 Oct 2021
The Power of Contrast for Feature Learning: A Theoretical Analysis
The Power of Contrast for Feature Learning: A Theoretical Analysis
Wenlong Ji
Zhun Deng
Ryumei Nakada
James Y. Zou
Linjun Zhang
SSL
51
48
0
06 Oct 2021
Momentum Contrastive Voxel-wise Representation Learning for
  Semi-supervised Volumetric Medical Image Segmentation
Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation
Chenyu You
Ruihan Zhao
Lawrence H. Staib
James S. Duncan
SSL
35
106
0
14 May 2021
On Feature Decorrelation in Self-Supervised Learning
On Feature Decorrelation in Self-Supervised Learning
Tianyu Hua
Wenxiao Wang
Zihui Xue
Sucheng Ren
Yue Wang
Hang Zhao
SSL
OOD
124
187
0
02 May 2021
With a Little Help from My Friends: Nearest-Neighbor Contrastive
  Learning of Visual Representations
With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations
Debidatta Dwibedi
Y. Aytar
Jonathan Tompson
P. Sermanet
Andrew Zisserman
SSL
188
452
0
29 Apr 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
314
5,775
0
29 Apr 2021
Understanding self-supervised Learning Dynamics without Contrastive
  Pairs
Understanding self-supervised Learning Dynamics without Contrastive Pairs
Yuandong Tian
Xinlei Chen
Surya Ganguli
SSL
138
279
0
12 Feb 2021
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
267
3,369
0
09 Mar 2020
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