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The success of deep neural networks often relies on a large amount of labeled examples, which can be difficult to obtain in many real scenarios.
Autoencoders, minimum description length and helmholtz free energy
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Unsupervised visual representation learning by context prediction
C. Doersch, A. Gupta, and A. A. Efros · 2015
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Data-dependent initializations of convolutional neural networks
P. Krähenbühl, C. Doersch, J. Donahue, and T. Darrell · 2015
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Deep roto-translation scattering for object classification
E. Oyallon and S. Mallat · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2015
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X. Wang and A. Gupta · 2015
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R. Zhang, P. Isola, and A. A. Efros · 2016
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M. Arjovsky, S. Chintala, and L. Bottou · 2017
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Unsupervised learning by predicting noise
P. Bojanowski and A. Joulin · 2017
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Representation learning by learning to count
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E. Oyallon, E. Belilovsky, and S. Zagoruyko · 2017
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Loss-sensitive generative adversarial networks on lipschitz densities
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J. Donahue, P. Krähenbühl, and T. Darrell · 2016
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Adversarially learned inference
V. Dumoulin, I. Belghazi, B. Poole, O. Mastropietro, A. Lamb, M. Arjovsky, and A. Courville · 2016
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G. Larsson, M. Maire, and G. Shakhnarovich · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
M. Noroozi and P. Favaro · 2016
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Context encoders: Feature learning by inpainting
D. Pathak, P. Krahenbuhl, J. Donahue, T. Darrell, and A. A. Efros · 2016
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Split-brain autoencoders: Unsupervised learning by cross-channel prediction
R. Zhang, P. Isola, and A. A. Efros
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G.-J. Qi · 2017
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Deep clustering for unsupervised learning of visual features
M. Caron, P. Bojanowski, A. Joulin, and M. Douze · 2018
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Generalized loss-sensitive adversarial learning with manifold margins
M. Edraki and G.-J. Qi · 2018
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Unsupervised representation learning by predicting image rotations
S. Gidaris, P. Singh, and N. Komodakis · 2018
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Global versus localized generative adversarial nets
G.-J. Qi, L. Zhang, H. Hu, M. Edraki, J. Wang, and X.-S. Hua · 2018
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