ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2110.15255
  4. Cited By
Self-Supervised Learning Disentangled Group Representation as Feature
v1v2 (latest)

Self-Supervised Learning Disentangled Group Representation as Feature

28 October 2021
Tan Wang
Zhongqi Yue
Jianqiang Huang
Qianru Sun
Hanwang Zhang
    OOD
ArXiv (abs)PDFHTMLGithub (121★)

Papers citing "Self-Supervised Learning Disentangled Group Representation as Feature"

50 / 67 papers shown
Title
ScaleNet: An Unsupervised Representation Learning Method for Limited
  Information
ScaleNet: An Unsupervised Representation Learning Method for Limited Information
Huili Huang
M. M. Roozbahani
SSL
98
804
0
03 Oct 2023
Causal Attention for Unbiased Visual Recognition
Causal Attention for Unbiased Visual Recognition
Tan Wang
Chan Zhou
Qianru Sun
Hanwang Zhang
OODCML
97
113
0
19 Aug 2021
Counterfactual Zero-Shot and Open-Set Visual Recognition
Counterfactual Zero-Shot and Open-Set Visual Recognition
Zhongqi Yue
Tan Wang
Hanwang Zhang
Qianru Sun
Xiansheng Hua
BDL
214
197
0
01 Mar 2021
Understanding self-supervised Learning Dynamics without Contrastive
  Pairs
Understanding self-supervised Learning Dynamics without Contrastive Pairs
Yuandong Tian
Xinlei Chen
Surya Ganguli
SSL
213
286
0
12 Feb 2021
Learning Disentangled Semantic Representation for Domain Adaptation
Learning Disentangled Semantic Representation for Domain Adaptation
Ruichu Cai
Zijian Li
Pengfei Wei
Jie Qiao
Kun Zhang
Zijian Li
OODDRL
73
131
0
22 Dec 2020
Measuring Disentanglement: A Review of Metrics
Measuring Disentanglement: A Review of Metrics
M. Carbonneau
Julian Zaïdi
Jonathan Boilard
G. Gagnon
CoGeDRL
63
84
0
16 Dec 2020
How Well Do Self-Supervised Models Transfer?
How Well Do Self-Supervised Models Transfer?
Linus Ericsson
Henry Gouk
Timothy M. Hospedales
SSL
114
278
0
26 Nov 2020
Exploring Simple Siamese Representation Learning
Exploring Simple Siamese Representation Learning
Xinlei Chen
Kaiming He
SSL
258
4,072
0
20 Nov 2020
AdCo: Adversarial Contrast for Efficient Learning of Unsupervised
  Representations from Self-Trained Negative Adversaries
AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries
Q. Hu
Tianlin Li
Wei Hu
Guo-Jun Qi
SSL
54
153
0
17 Nov 2020
Contrastive Learning with Hard Negative Samples
Contrastive Learning with Hard Negative Samples
Joshua Robinson
Ching-Yao Chuang
S. Sra
Stefanie Jegelka
SSL
150
787
0
09 Oct 2020
Hard Negative Mixing for Contrastive Learning
Hard Negative Mixing for Contrastive Learning
Yannis Kalantidis
Mert Bulent Sariyildiz
Noé Pion
Philippe Weinzaepfel
Diane Larlus
SSL
134
645
0
02 Oct 2020
Interventional Few-Shot Learning
Interventional Few-Shot Learning
Zhongqi Yue
Hanwang Zhang
Qianru Sun
Xiansheng Hua
93
233
0
28 Sep 2020
What Should Not Be Contrastive in Contrastive Learning
What Should Not Be Contrastive in Contrastive Learning
Tete Xiao
Xiaolong Wang
Alexei A. Efros
Trevor Darrell
SSLDRL
82
303
0
13 Aug 2020
Debiased Contrastive Learning
Debiased Contrastive Learning
Ching-Yao Chuang
Joshua Robinson
Yen-Chen Lin
Antonio Torralba
Stefanie Jegelka
SSL
79
566
0
01 Jul 2020
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
252
4,097
0
17 Jun 2020
Bootstrap your own latent: A new approach to self-supervised Learning
Bootstrap your own latent: A new approach to self-supervised Learning
Jean-Bastien Grill
Florian Strub
Florent Altché
Corentin Tallec
Pierre Harvey Richemond
...
M. G. Azar
Bilal Piot
Koray Kavukcuoglu
Rémi Munos
Michal Valko
SSL
389
6,837
0
13 Jun 2020
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
859
42,379
0
28 May 2020
S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement
  and Data Generation
S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement and Data Generation
Yizhe Zhu
Martin Renqiang Min
Asim Kadav
H. Graf
CoGeDRL
58
96
0
23 May 2020
What Makes for Good Views for Contrastive Learning?
What Makes for Good Views for Contrastive Learning?
Yonglong Tian
Chen Sun
Ben Poole
Dilip Krishnan
Cordelia Schmid
Phillip Isola
SSL
114
1,335
0
20 May 2020
Prototypical Contrastive Learning of Unsupervised Representations
Prototypical Contrastive Learning of Unsupervised Representations
Junnan Li
Pan Zhou
Caiming Xiong
Guosheng Lin
SSLDRL
139
975
0
11 May 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
489
3,443
0
09 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
375
18,859
0
13 Feb 2020
Self-Supervised Learning of Pretext-Invariant Representations
Self-Supervised Learning of Pretext-Invariant Representations
Ishan Misra
Laurens van der Maaten
SSLVLM
108
1,458
0
04 Dec 2019
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
210
12,121
0
13 Nov 2019
Scale-Equivariant Steerable Networks
Scale-Equivariant Steerable Networks
Li Xiao
Michal Szmaja
A. Smeulders
125
149
0
14 Oct 2019
Theory and Evaluation Metrics for Learning Disentangled Representations
Theory and Evaluation Metrics for Learning Disentangled Representations
Kien Do
T. Tran
CoGeDRL
74
96
0
26 Aug 2019
Invariant Risk Minimization
Invariant Risk Minimization
Martín Arjovsky
Léon Bottou
Ishaan Gulrajani
David Lopez-Paz
OOD
195
2,242
0
05 Jul 2019
Contrastive Multiview Coding
Contrastive Multiview Coding
Yonglong Tian
Dilip Krishnan
Phillip Isola
SSL
174
2,409
0
13 Jun 2019
Learning Representations by Maximizing Mutual Information Across Views
Learning Representations by Maximizing Mutual Information Across Views
Philip Bachman
R. Devon Hjelm
William Buchwalter
SSL
195
1,477
0
03 Jun 2019
Are Disentangled Representations Helpful for Abstract Visual Reasoning?
Are Disentangled Representations Helpful for Abstract Visual Reasoning?
Sjoerd van Steenkiste
Francesco Locatello
Jürgen Schmidhuber
Olivier Bachem
82
210
0
29 May 2019
Deep Scale-spaces: Equivariance Over Scale
Deep Scale-spaces: Equivariance Over Scale
Daniel E. Worrall
Max Welling
BDL
70
167
0
28 May 2019
Data-Efficient Image Recognition with Contrastive Predictive Coding
Data-Efficient Image Recognition with Contrastive Predictive Coding
Olivier J. Hénaff
A. Srinivas
J. Fauw
Ali Razavi
Carl Doersch
S. M. Ali Eslami
Aaron van den Oord
SSL
138
1,432
0
22 May 2019
Adversarial Examples Are Not Bugs, They Are Features
Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas
Shibani Santurkar
Dimitris Tsipras
Logan Engstrom
Brandon Tran
Aleksander Madry
SILM
93
1,844
0
06 May 2019
Disentangling Factors of Variation Using Few Labels
Disentangling Factors of Variation Using Few Labels
Francesco Locatello
Michael Tschannen
Stefan Bauer
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
DRLCMLCoGe
94
124
0
03 May 2019
Unsupervised Embedding Learning via Invariant and Spreading Instance
  Feature
Unsupervised Embedding Learning via Invariant and Spreading Instance Feature
Mang Ye
Xu-Yao Zhang
PongChi Yuen
Shih-Fu Chang
SSL
99
581
0
06 Apr 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
108
480
0
05 Dec 2018
Challenging Common Assumptions in the Unsupervised Learning of
  Disentangled Representations
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
Francesco Locatello
Stefan Bauer
Mario Lucic
Gunnar Rätsch
Sylvain Gelly
Bernhard Schölkopf
Olivier Bachem
OOD
124
1,471
0
29 Nov 2018
Robustly Disentangled Causal Mechanisms: Validating Deep Representations
  for Interventional Robustness
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness
Raphael Suter
Ðorðe Miladinovic
Bernhard Schölkopf
Stefan Bauer
CMLOODDRL
133
162
0
31 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLMSSLSSeg
1.8K
95,175
0
11 Oct 2018
Learning deep representations by mutual information estimation and
  maximization
Learning deep representations by mutual information estimation and maximization
R. Devon Hjelm
A. Fedorov
Samuel Lavoie-Marchildon
Karan Grewal
Phil Bachman
Adam Trischler
Yoshua Bengio
SSLDRL
335
2,672
0
20 Aug 2018
Representation Learning with Contrastive Predictive Coding
Representation Learning with Contrastive Predictive Coding
Aaron van den Oord
Yazhe Li
Oriol Vinyals
DRLSSL
351
10,356
0
10 Jul 2018
Learning to Decompose and Disentangle Representations for Video
  Prediction
Learning to Decompose and Disentangle Representations for Video Prediction
Jun-Ting Hsieh
Bingbin Liu
De-An Huang
Li Fei-Fei
Juan Carlos Niebles
DRL
180
306
0
11 Jun 2018
Do Better ImageNet Models Transfer Better?
Do Better ImageNet Models Transfer Better?
Simon Kornblith
Jonathon Shlens
Quoc V. Le
OODMLT
170
1,329
0
23 May 2018
Unsupervised Feature Learning via Non-Parametric Instance-level
  Discrimination
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
Zhirong Wu
Yuanjun Xiong
Stella X. Yu
Dahua Lin
SSL
179
3,466
0
05 May 2018
Understanding disentangling in $β$-VAE
Understanding disentangling in βββ-VAE
Christopher P. Burgess
I. Higgins
Arka Pal
Loic Matthey
Nicholas Watters
Guillaume Desjardins
Alexander Lerchner
CoGeDRL
68
831
0
10 Apr 2018
Unsupervised Representation Learning by Predicting Image Rotations
Unsupervised Representation Learning by Predicting Image Rotations
Spyros Gidaris
Praveer Singh
N. Komodakis
OODSSLDRL
263
3,298
0
21 Mar 2018
Disentangling by Factorising
Disentangling by Factorising
Hyunjik Kim
A. Mnih
CoGeOOD
64
1,356
0
16 Feb 2018
Learning Deep Disentangled Embeddings with the F-Statistic Loss
Learning Deep Disentangled Embeddings with the F-Statistic Loss
Karl Ridgeway
Michael C. Mozer
FedMLDRLCoGe
72
218
0
14 Feb 2018
Isolating Sources of Disentanglement in Variational Autoencoders
Isolating Sources of Disentanglement in Variational Autoencoders
T. Chen
Xuechen Li
Roger C. Grosse
David Duvenaud
DRL
61
447
0
14 Feb 2018
Spherical CNNs
Spherical CNNs
Taco S. Cohen
Mario Geiger
Jonas Köhler
Max Welling
162
907
0
30 Jan 2018
12
Next