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Standard artificial neural networks suffer from the well-known issue of catastrophic forgetting, making continual or lifelong learning difficult for machine learning.
Metric learning for large scale image classification: Generalizing to new classes at near-zero cost
Thomas Mensink, Jakob Verbeek, Florent Perronnin, and Gabriela Csurka · 2012
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An empirical investigation of catastrophic forgetting in gradient-based neural networks
Ian J Goodfellow, Mehdi Mirza, Da Xiao, Aaron Courville, and Yoshua Bengio · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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New insights and perspectives on the natural gradient method
James Martens · 2014
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Variational inference with normalizing flows
Danilo Jimenez Rezende and Shakir Mohamed · 2015
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What learning systems do intelligent agents need? complementary learning systems theory updated
Dharshan Kumaran, Demis Hassabis, and James L McClelland · 2016
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Pixel recurrent neural networks
Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
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Tutorial on variational autoencoders
Carl Doersch · 2016
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
Cited alongside, same era.
Variational continual learning
Cuong V Nguyen, Yingzhen Li, Thang D Bui, and Richard E Turner · 2017
Cited alongside, same era.
Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
Cited alongside, same era.
Measuring catastrophic forgetting in neural networks
Ronald Kemker, Angelina Abitino, Marc McClure, and Christopher Kanan · 2017
Cited alongside, same era.
Deep generative dual memory network for continual learning
Nitin Kamra, Umang Gupta, and Yan Liu · 2017
Cited alongside, same era.
Incremental classifier learning with generative adversarial networks
Yue Wu, Yinpeng Chen, Lijuan Wang, Yuancheng Ye, Zicheng Liu, Yandong Guo, Zhengyou Zhang, and Yun Fu · 2018
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Generative replay with feedback connections as a general strategy for continual learning
Gido M van de Ven and Andreas S Tolias · 2018
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Re-evaluating continual learning scenarios: A categorization and case for strong baselines
Yen-Chang Hsu, Yen-Cheng Liu, and Zsolt Kira · 2018
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Towards robust evaluations of continual learning
Sebastian Farquhar and Yarin Gal · 2018
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Riemannian walk for incremental learning: Understanding forgetting and intransigence
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Pathnet: Evolution channels gradient descent in super neural networks
Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A Rusu, Alexander Pritzel, and Daan Wierstra · 2017
Cited alongside, same era.
Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
Cited alongside, same era.
Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
Cited alongside, same era.
A strategy for an uncompromising incremental learner
Ragav Venkatesan, Hemanth Venkateswara, Sethuraman Panchanathan, and Baoxin Li · 2017
Cited alongside, same era.
Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization
Nicolas Y Masse, Gregory D Grant, and David J Freedman · 2018
Cited alongside, same era.
Fearnet: Brain-inspired model for incremental learning
Ronald Kemker and Christopher Kanan · 2018
Cited alongside, same era.
Arslan Chaudhry, Puneet K Dokania, Thalaiyasingam Ajanthan, and Philip HS Torr · 2018
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Overcoming catastrophic forgetting with hard attention to the task
Joan Serrà, Dídac Surís, Marius Miron, and Alexandros Karatzoglou · 2018
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Progress & compress: A scalable framework for continual learning
Jonathan Schwarz, Jelena Luketina, Wojciech M Czarnecki, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell · 2018
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Continual lifelong learning with neural networks: A review
German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan, and Stefan Wermter · 2018
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Note on the quadratic penalties in elastic weight consolidation
Ferenc Huszár · 2018
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Task agnostic continual learning using online variational bayes
Chen Zeno, Itay Golan, Elad Hoffer, and Daniel Soudry · 2019
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Incremental learning with unlabeled data in the wild
Kibok Lee, Kimin Lee, Jinwoo Shin, and Honglak Lee · 2019
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