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Continual acquisition of novel experience without interfering previously learned knowledge, i.e.
The organization of behavior: a neuropsychological theory
Donald Olding Hebb · 1962
Earlier work this paper cites.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
Earlier work this paper cites.
Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory
James L McClelland, Bruce L McNaughton, and Randall C O’Reilly · 1995
Earlier work this paper cites.
The mnist database of handwritten digits
Yann LeCun · 1998
Earlier work this paper cites.
The organization of recent and remote memories
Paul W Frankland and Bruno Bontempi · 2005
Earlier work this paper cites.
A functional hypothesis for adult hippocampal neurogenesis: avoidance of catastrophic interference in the dentate gyrus
Laurenz Wiskott, Malte J Rasch, and Gerd Kempermann · 2006
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
New neurons and new memories: how does adult hippocampal neurogenesis affect learning and memory?
Wei Deng, James B Aimone, and Fred H Gage · 2010
Earlier work this paper cites.
Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y Ng · 2011
Earlier work this paper cites.
The mechanisms for pattern completion and pattern separation in the hippocampus
Edmund Rolls · 2013
Earlier work this paper cites.
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Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
Earlier work this paper cites.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Cited alongside, same era.
Adult neurogenesis in the hippocampus: from stem cells to behavior
J Tiago Gonçalves, Simon T Schafer, and Fred H Gage · 2016
Cited alongside, same era.
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Cited alongside, same era.
Critical learning periods in deep neural networks
Alessandro Achille, Matteo Rovere, and Stefano Soatto · 2017
Cited alongside, same era.
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Cited alongside, same era.
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End-to-end incremental learning
Francisco M Castro, Manuel J Marín-Jiménez, Nicolás Guil, Cordelia Schmid, and Karteek Alahari · 2018
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Riemannian walk for incremental learning: Understanding forgetting and intransigence
Arslan Chaudhry, Puneet K Dokania, Thalaiyasingam Ajanthan, and Philip HS Torr · 2018
Later among the works it cites.
Measuring catastrophic forgetting in neural networks
Ronald Kemker, Marc McClure, Angelina Abitino, Tyler L Hayes, and Christopher Kanan · 2018
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Cited alongside, same era.
Triple generative adversarial nets
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icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
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Cited alongside, same era.
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Memory replay gans: Learning to generate new categories without forgetting
Chenshen Wu, Luis Herranz, Xialei Liu, Joost van de Weijer, Bogdan Raducanu, et al · 2018
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Continual lifelong learning with neural networks: A review
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Three scenarios for continual learning
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