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In the continual learning setting, tasks are encountered sequentially.
Continual learning via neural pruning
S. Golkar, M. Kagan, and K. Cho · 1903
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Catastrophic interference in connectionist networks: The sequential learning problem
M. Mccloskey and N. J. Cohen · 1989
Earlier work this paper cites.
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
I. J. Goodfellow, M. Mirza, D. Xiao, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
Earlier work this paper cites.
Weight uncertainty in neural network
C. Blundell, J. Cornebise, K. Kavukcuoglu, and D. Wierstra · 2015
Earlier work this paper cites.
Variational Dropout and the Local Reparameterization Trick
D. P. Kingma, T. Salimans, and M. Welling · 2015
Earlier work this paper cites.
Deep gaussian processes for regression using approximate expectation propagation
T. Bui, D. Hernandez-Lobato, J. Hernandez-Lobato, Y. Li, and R. Turner · 2016
Earlier work this paper cites.
A. A. Rusu, N. C. Rabinowitz, G. Desjardins, H. Soyer, J. Kirkpatrick, K. Kavukcuoglu, R. Pascanu, and R. Hadsell · 2016
Earlier work this paper cites.
Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick, R. Pascanu, N. 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 · 2017
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Gradient episodic memory for continual learning
D. Lopez-Paz and M. A. Ranzato · 2017
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Bayesian compression for deep learning
C. Louizos, K. Ullrich, and M. Welling · 2017
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icarl: Incremental classifier and representation learning
S. Rebuffi, A. Kolesnikov, G. Sperl, and C. H. Lampert · 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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Continual learning through synaptic intelligence
F. Zenke, B. Poole, and S. Ganguli · 2017
Variational continual learning
C. V. Nguyen, Y. Li, T. D. Bui, and R. E. Turner · 2018
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Online structured laplace approximations for overcoming catastrophic forgetting
H. Ritter, A. Botev, and D. Barber · 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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Overpruning in Variational Bayesian Neural Networks
B. Trippe and R. Turner · 2018
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Generative replay with feedback connections as a general strategy for continual learning
G. M. van der Ven and A. S. Tolias · 2018
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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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Efficient lifelong learning with a-GEM
A. Chaudhry, M. Ranzato, M. Rohrbach, and M. Elhoseiny · 2019
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Uncertainty-guided lifelong learning in bayesian networks, 2019
S. Ebrahimi, M. Elhoseiny, T. Darrell, and M. Rohrbach · 2019
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