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Recent advances in self-supervised learning with instance-level contrastive objectives facilitate unsupervised clustering.
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Deep variational information bottleneck
Clustergan: Latent space clustering in generative adversarial networks
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Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
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On the limitations of representing functions on sets
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Jianlong Wu, Keyu Long, Fei Wang, Chen Qian, Cheng Li, Zhouchen Lin, and Hongbin Zha · 2019
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Deep clustering by gaussian mixture variational autoencoders with graph embedding
Linxiao Yang, Ngai-Man Cheung, Jiaying Li, and Jun Fang · 2019
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Alexander A Alemi, Ian Fischer, Joshua V Dillon, and Kevin Murphy · 2017
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Deep adaptive image clustering
Jianlong Chang, Lingfeng Wang, Gaofeng Meng, Shiming Xiang, and Chunhong Pan · 2017
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Towards a neural statistician
Harrison Edwards and Amos Storkey · 2017
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Deep miml network
Ji Feng and Zhi-Hua Zhou · 2017
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Learning discrete representations via information maximizing self-augmented training
Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, and Masashi Sugiyama · 2017
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2017
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Variational deep embedding: An unsupervised and generative approach to clustering
Zhuxi Jiang, Yin Zheng, Huachun Tan, Bangsheng Tang, and Hanning Zhou · 2017
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Chengxu Zhuang, Alex Lin Zhai, and Daniel Yamins · 2019
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Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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A simple framework for contrastive learning of visual representations
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Improved baselines with momentum contrastive learning
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Dhog: Deep hierarchical object grouping
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Momentum contrast for unsupervised visual representation learning
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Deep semantic clustering by partition confidence maximisation
Jiabo Huang, Shaogang Gong, and Xiatian Zhu · 2020
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Prototypical contrastive learning of unsupervised representations
Junnan Li, Pan Zhou, Caiming Xiong, Richard Socher, and Steven CH Hoi · 2020
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Yunfan Li, Peng Hu, Zitao Liu, Dezhong Peng, Joey Tianyi Zhou, and Xi Peng · 2020
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Unsupervised clustering through gaussian mixture variational autoencoder with non-reparameterized variational inference and std annealing
Zhihan Li, Youjian Zhao, Haowen Xu, Wenxiao Chen, Shangqing Xu, Yilin Li, and Dan Pei · 2020
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Gatcluster: Self-supervised gaussian-attention network for image clustering
Chuang Niu, Jun Zhang, Ge Wang, and Jimin Liang · 2020
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Neural clustering processes
Ari Pakman, Yueqi Wang, Catalin Mitelut, JinHyung Lee, and Liam Paninski · 2020
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Improving unsupervised image clustering with robust learning
Sungwon Park, Sungwon Han, Sundong Kim, Danu Kim, Sungkyu Park, Seunghoon Hong, and Meeyoung Cha · 2020
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Scan: Learning to classify images without labels
Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Marc Proesmans, and Luc Van Gool · 2020
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Loco: Local contrastive representation learning
Yuwen Xiong, Mengye Ren, and Raquel Urtasun · 2020
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Robust attentional aggregation of deep feature sets for multi-view 3d reconstruction
Bo Yang, Sen Wang, Andrew Markham, and Niki Trigoni · 2020
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Deep image clustering with category-style representation
Junjie Zhao, Donghuan Lu, Kai Ma, Yu Zhang, and Yefeng Zheng · 2020
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Deep clustering by semantic contrastive learning
Jiabo Huang and Shaogang Gong · 2021
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Scaling up visual and vision-language representation learning with noisy text supervision
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