Fetching the paper…
Reading the bibliography…
Continual learning, the setting where a learning agent is faced with a never ending stream of data, continues to be a great challenge for modern machine learning systems.
Studies of mind and brain : neural principles of learning, perception, development, cognition, and motor control
Stephen Grossberg · 1982
Earlier work this paper cites.
Semi-distributed representations and catastrophic forgetting in connectionist networks
Robert M French · 1992
Earlier work this paper cites.
Alcove: an exemplar-based connectionist model of category learning
John K Kruschke · 1992
Earlier work this paper cites.
Reducing interference in distributed memories through episodic gating
Steven A Sloman and David E Rumelhart · 1992
Earlier work this paper cites.
Human category learning: Implications for backpropagation models
John K Kruschke · 1993
Earlier work this paper cites.
Dynamically constraining connectionist networks to produce distributed, orthogonal representations to reduce catastrophic interference
Robert M French · 1994
Earlier work this paper cites.
Catastrophic forgetting, rehearsal and pseudorehearsal
Anthony Robins · 1995
Earlier work this paper cites.
Complementary learning systems in the brain: A connectionist approach to explicit and implicit cognition and memory
JAMES L McCLELLAND · 1998
Earlier work this paper cites.
Catastrophic forgetting in connectionist networks
Robert M French · 1999
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Earlier work this paper cites.
An empirical investigation of catastrophic forgetting in gradient-based neural networks
Ian J Goodfellow, Mehdi Mirza, Da Xiao, Aaron Courville, and Yoshua Bengio · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
Earlier work this paper cites.
Expert gate: Lifelong learning with a network of experts
Rahaf Aljundi, Punarjay Chakravarty, and Tinne Tuytelaars · 2016
Earlier work this paper cites.
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 · 2016
Cited alongside, same era.
Learning without forgetting
Zhizhong Li and Derek Hoiem · 2016
Cited alongside, same era.
Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
Cited alongside, same era.
Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Daan Wierstra, et al · 2016
Cited alongside, same era.
Switching between internal and external modes: a multiscale learning principle
Christopher J Honey, Ehren L Newman, and Anna C Schapiro · 2017
Cited alongside, same era.
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.
Towards robust evaluations of continual learning
Sebastian Farquhar and Yarin Gal · 2018
Later among the works it cites.
Continual classification learning using generative models, 2018
Frantzeska Lavda, Jason Ramapuram, Magda Gregorova, and Alexandros Kalousis · 2018
Later among the works it cites.
Generative models from the perspective of continual learning
Timothée Lesort, Hugo Caselles-Dupré, Michael Garcia-Ortiz, Andrei Stoian, and David Filliat · 2018
Later among the works it cites.
Decoding the tradeoff between encoding and retrieval to predict memory for overlapping events
Kuhl BA Long NM · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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
Cited alongside, same era.
Gradient episodic memory for continual learning
David Lopez-Paz et al · 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.
Jason Ramapuram, Magda Gregorova, and Alexandros Kalousis · 2017
Cited alongside, same era.
icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 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.
Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
Cited alongside, same era.
Later among the works it cites.
Ju Xu and Zhanxing Zhu · 2018
Later among the works it cites.
Task-free continual learning
Rahaf Aljundi, Klaas Kelchtermans, and Tinne Tuytelaars · 2019
Closest in time.
Online continual learning with no task boundaries
Rahaf Aljundi, Min Lin, Baptiste Goujaud, and Yoshua Bengio · 2019
Closest in time.
Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2019
Closest in time.
Continual learning with tiny episodic memories
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet K Dokania, Philip HS Torr, and Marc’Aurelio Ranzato · 2019
Closest in time.
Marginal replay vs conditional replay for continual learning
Timothée Lesort, Alexander Gepperth, Andrei Stoian, and David Filliat · 2019
Closest in time.
Scalable recollections for continual lifelong learning
Matthew Riemer, Tim Klinger, Djallel Bouneffouf, and Michele Franceschini · 2019
Closest in time.