Fetching the paper…
Reading the bibliography…
Unsupervised disentangled representation learning is a long-standing problem in computer vision.
Deep Discriminative Clustering Analysis
Chang, J.; Guo, Y.; Wang, L.; Meng, G.; Xiang, S.; and Pan, C. 2019 · 1905
Earlier work this paper cites.
Data-Efficient Image Recognition with Contrastive Predictive Coding
Hénaff, O. J.; Srinivas, A.; Fauw, J. D.; Razavi, A.; Doersch, C.; Eslami, S. M. A.; and van den Oord, A. 2019 · 1905
Earlier work this paper cites.
An Introduction to Variational Autoencoders
Kingma, D. P.; and Welling, M. 2019 · 1906
Earlier work this paper cites.
Tian, Y.; Krishnan, D.; and Isola, P. 2019 · 1906
Earlier work this paper cites.
Momentum Contrast for Unsupervised Visual Representation Learning
He, K.; Fan, H.; Wu, Y.; Xie, S.; and Girshick, R. B. 2019 · 1911
Earlier work this paper cites.
Some methods for classification and analysis of multivariate observations
Macqueen, J. 1967 · 1967
Earlier work this paper cites.
Gaussian parsimonious clustering models
Celeux, G.; and Govaert, G. 1995 · 1995
Earlier work this paper cites.
The challenges of clustering high-dimensional data
Steinbach, M.; Ertöz, L.; and Kumar, V. 2003 · 2003
Earlier work this paper cites.
Supervised Contrastive Learning
Khosla, P.; Teterwak, P.; Wang, C.; Sarna, A.; Tian, Y.; Isola, P.; Maschinot, A.; Liu, C.; and Krishnan, D. 2020 · 2004
Earlier work this paper cites.
CURL: Contrastive Unsupervised Representations for Reinforcement Learning
Srinivas, A.; Laskin, M.; and Abbeel, P. 2020 · 2004
Earlier work this paper cites.
Self-tuning spectral clustering
Zelnik-manor, L.; and Perona, P. 2004 · 2004
Earlier work this paper cites.
Prototypical Contrastive Learning of Unsupervised Representations
Li, J.; Zhou, P.; Xiong, C.; Socher, R.; and Hoi, S. C. H. 2020 · 2005
Earlier work this paper cites.
Greedy Layer-Wise Training of Deep Networks
Bengio, Y.; Lamblin, P.; Popovici, D.; and Larochelle, H. 2006 · 2006
Earlier work this paper cites.
Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning
Grill, J.; Strub, F.; Altché, F.; Tallec, C.; Richemond, P. H.; Buchatskaya, E.; Doersch, C.; Pires, B. Á.; Guo, Z. D.; Azar, M. G.; Piot, B.; Kavukcuoglu, K.; Munos, R.; and Valko, M. 2020a · 2006
Earlier work this paper cites.
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases
Purushwalkam, S.; and Gupta, A. 2020 · 2007
Earlier work this paper cites.
Visualizing Data using t-SNE
van der Maaten, L.; and Hinton, G. 2008 · 2008
Earlier work this paper cites.
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
Vincent, P.; Larochelle, H.; Lajoie, I.; Bengio, Y.; and Manzagol, P.-A. 2010 · 2010
Earlier work this paper cites.
Graph Contrastive Learning with Augmentations
You, Y.; Chen, T.; Sui, Y.; Chen, T.; Wang, Z.; and Shen, Y. 2020 · 2010
Earlier work this paper cites.
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks
Dosovitskiy, A.; Springenberg, J. T.; Riedmiller, M.; and Brox, T. 2014 · 2014
Cited alongside, same era.
Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2015 · 2015
Cited alongside, same era.
Adam: A Method for Stochastic Optimization
Kingma, D. P.; and Ba, J. 2015 · 2015
Cited alongside, same era.
Unsupervised Deep Embedding for Clustering Analysis
Xie, J.; Girshick, R. B.; and Farhadi, A. 2015 · 2015
Cited alongside, same era.
Variational Deep Embedding: A Generative Approach to Clustering
Jiang, Z.; Zheng, Y.; Tan, H.; Tang, B.; and Zhou, H. 2016 · 2016
Cited alongside, same era.
A Self-Training Approach for Short Text Clustering
Hadifar, A.; Sterckx, L.; Demeester, T.; and Develder, C. 2019 · 2019
Later among the works it cites.
Associative Deep Clustering: Training a Classification Network with No Labels
Haeusser, P.; Plapp, J.; Golkov, V.; Aljalbout, E.; and Cremers, D. 2019 · 2019
Later among the works it cites.
Learning deep representations by mutual information estimation and maximization
Hjelm, R. D.; Fedorov, A.; Lavoie-Marchildon, S.; Grewal, K.; Bachman, P.; Trischler, A.; and Bengio, Y. 2019 · 2019
Later among the works it cites.
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Paszke, A.; Gross, S.; Massa, F.; Lerer, A.; Bradbury, J.; Chanan, G.; Killeen, T.; Lin, Z.; Gimelshein, N.; Antiga, L.; Desmaison, A.; Kopf, A.; Yang, E.; DeVito, Z.; Raison, M.; Tejani, A.; Chilamkurthy, S.; Steiner, B.; Fang, L.; Bai, J.; and Chintala, S. 2019 · 2019
Later among the works it cites.
Deep Comprehensive Correlation Mining for Image Clustering
Wu, J.; Long, K.; Wang, F.; Qian, C.; Li, C.; Lin, Z.; and Zha, H. 2019 · 2019
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles
Noroozi, M.; and Favaro, P. 2016 · 2016
Cited alongside, same era.
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Radford, A.; Metz, L.; and Chintala, S. 2016 · 2016
Cited alongside, same era.
Joint Unsupervised Learning of Deep Representations and Image Clusters
Yang, J.; Parikh, D.; and Batra, D. 2016 · 2016
Cited alongside, same era.
Deep Adaptive Image Clustering
Chang, J.; Wang, L.; Meng, G.; Xiang, S.; and Pan, C. 2017 · 2017
Cited alongside, same era.
Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization
Dizaji, K. G.; Herandi, A.; Deng, C.; Cai, W.; and Huang, H. 2017 · 2017
Cited alongside, same era.
Deep Clustering for Unsupervised Learning of Visual Features
Caron, M.; Bojanowski, P.; Joulin, A.; and Douze, M. 2018 · 2018
Cited alongside, same era.
Unsupervised Representation Learning by Predicting Image Rotations
Gidaris, S.; Singh, P.; and Komodakis, N. 2018 · 2018
Cited alongside, same era.
Later among the works it cites.
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Caron, M.; Misra, I.; Mairal, J.; Goyal, P.; Bojanowski, P.; and Joulin, A. 2020 · 2020
Later among the works it cites.
A Simple Framework for Contrastive Learning of Visual Representations
Chen, T.; Kornblith, S.; Norouzi, M.; and Hinton, G. 2020 · 2020
Later among the works it cites.
SCAN: Learning to Classify Images Without Labels
Gansbeke, W. V.; Vandenhende, S.; Georgoulis, S.; Proesmans, M.; and Gool, L. 2020 · 2020
Later among the works it cites.
Deep Semantic Clustering by Partition Confidence Maximisation
Huang, J.; Gong, S.; and Zhu, X. 2020 · 2020
Later among the works it cites.
Exploring Simple Siamese Representation Learning
Chen, X.; and He, K. 2021 · 2021
Closest in time.
The Single-Noun Prior for Image Clustering
Cohen, N.; and Hoshen, Y. 2021 · 2021
Closest in time.
Representation Learning for Clustering via Building Consensus
Deshmukh, A. A.; Regatti, J. R.; Manavoglu, E.; and Dogan, Ü. 2021 · 2021
Closest in time.
Contrastive Clustering
Li, Y.; Hu, P.; Liu, Z.; Peng, D.; Zhou, J. T.; and Peng, X. 2021 · 2021
Closest in time.
SPICE: Semantic Pseudo-labeling for Image Clustering
Niu, C.; and Wang, G. 2021 · 2021
Closest in time.
Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation
Tao, Y.; Takagi, K.; and Nakata, K. 2021 · 2021
Closest in time.
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Zbontar, J.; Jing, L.; Misra, I.; LeCun, Y.; and Deny, S. 2021 · 2021
Closest in time.
Supporting Clustering with Contrastive Learning
Zhang, D.; Nan, F.; Wei, X.; Li, S.; Zhu, H.; McKeown, K. R.; Nallapati, R.; Arnold, A. O.; and Xiang, B. 2021 · 2021
Closest in time.