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Models trained in the context of continual learning (CL) should be able to learn from a stream of data over an undefined period of time.
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Y. LeCun · 1998
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R. M. French · 1999
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Y. Netzer, T. Wang, A. Coates, A. Bissacco, B. Wu, and A. Y. Ng · 2011
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M. Mayford, S. A. Siegelbaum, and E. R. Kandel · 2012
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I. J. Goodfellow, M. Mirza, D. Xiao, A. Courville, and Y. Bengio · 2013
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The cifar-10 dataset
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Training deep neural networks with binary weights during propagations. arxiv preprint
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Unsupervised representation learning with deep convolutional generative adversarial networks
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Imagenet large scale visual recognition challenge
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Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick, R. Pascanu, N. C. Rabinowitz, J. Veness, G. Desjardins, A. A. Rusu, K. Milan, J. Quan, T. Ramalho, A. Grabska-Barwinska, D. Hassabis, C. Clopath, D. Kumaran, and R. Hadsell · 2016
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Z. Li and D. Hoiem · 2016
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Conditional image synthesis with auxiliary classifier gans
A. Odena, C. Olah, and J. Shlens · 2016
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icarl: Incremental classifier and representation learning
S. Rebuffi, A. Kolesnikov, and C. H. Lampert · 2016
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A. A. Rusu, N. C. Rabinowitz, G. Desjardins, H. Soyer, J. Kirkpatrick, K. Kavukcuoglu, R. Pascanu, and R. Hadsell · 2016
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Improved multitask learning through synaptic intelligence
F. Zenke, B. Poole, and S. Ganguli · 2017
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Riemannian walk for incremental learning: Understanding forgetting and intransigence
A. Chaudhry, P. K. Dokania, T. Ajanthan, and P. H. S. Torr · 2018
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Piggyback: Adding multiple tasks to a single, fixed network by learning to mask
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Adding new tasks to a single network with weight trasformations using binary masks
M. Mancini, E. Ricci, B. Caputo, and S. R. Bulò · 2018
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Efficient parametrization of multi-domain deep neural network
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R. Aljundi, F. Babiloni, M. Elhoseiny, M. Rohrbach, and T. Tuytelaars · 2017
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Improved training of wasserstein gans
I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, and A. C. Courville · 2017
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Deep generative dual memory network for continual learning
N. Kamra, U. Gupta, and Y. Liu · 2017
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Fearnet: Brain-inspired model for incremental learning
R. Kemker and C. Kanan · 2017
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Variational continual learning
C. V. Nguyen, Y. Li, T. D. Bui, and R. E. Turner · 2017
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Continual learning in generative adversarial nets
A. Seff, A. Beatson, D. Suo, and H. Liu · 2017
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Continual learning with deep generative replay
H. Shin, J. K. Lee, J. Kim, and J. Kim · 2017
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S.-A. Rebuffi, H. Bilen, and A. Vedaldi · 2018
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Incremental learning through deep adaptation
A. Rosenfeld and J. K. Tsotsos · 2018
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Progress & compress: A scalable framework for continual learning
J. Schwarz, J. Luketina, W. M. Czarnecki, A. Grabska-Barwinska, Y. W. Teh, R. Pascanu, and R. Hadsell · 2018
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Overcoming catastrophic forgetting with hard attention to the task
J. Serrà, D. Surís, M. Miron, and A. Karatzoglou · 2018
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Memory Replay GANs: learning to generate images from new categories without forgetting
C. Wu, L. Herranz, X. Liu, Y. Wang, J. van de Weijer, and B. Raducanu · 2018
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Incremental classifier learning with generative adversarial networks
Y. Wu, Y. Chen, L. Wang, Y. Ye, Z. Liu, Y. Guo, Z. Zhang, and Y. Fu · 2018
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Lifelong learning with dynamically expandable networks
J. Yoon, E. Yang, J. Lee, and S. J. Hwang · 2018
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