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Time-dependent data-generating distributions have proven to be difficult for gradient-based training of neural networks, as the greedy updates result in catastrophic forgetting of previously learned knowledge.
Continual learning with tiny episodic memories
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet K Dokania, Philip HS Torr, and Marc’Aurelio Ranzato · 1902
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Stephen Grossberg · 1982
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Catastrophic forgetting in connectionist networks
Robert M French · 1999
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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MNIST handwritten digit database
Yann LeCun and Corinna Cortes · 2010
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Playing atari with deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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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
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Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, and Daan Wierstra · 2016
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Synthetic speech commands: a public dataset for single-word speech recognition
Johannes Buchner · 2017
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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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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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Encoder based lifelong learning
Amal Rannen, Rahaf Aljundi, Matthew B Blaschko, and Tinne Tuytelaars · 2017
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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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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 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
Online continual learning from imbalanced data
Aristotelis Chrysakis and Marie-Francine Moens · 2020
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Online continual learning under extreme memory constraints
Enrico Fini, Stéphane Lathuiliere, Enver Sangineto, Moin Nabi, and Elisa Ricci · 2020
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Brain-inspired replay for continual learning with artificial neural networks
Gido M van de Ven, Hava T Siegelmann, and Andreas S Tolias · 2020
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Continual learning for recurrent neural networks: An empirical evaluation
Andrea Cossu, Antonio Carta, Vincenzo Lomonaco, and Davide Bacciu · 2021
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Continual prototype evolution: Learning online from non-stationary data streams
Matthias De Lange and Tinne Tuytelaars · 2021
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A continual learning survey: Defying forgetting in classification tasks
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Packnet: Adding multiple tasks to a single network by iterative pruning
Arun Mallya and Svetlana Lazebnik · 2018
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Overcoming catastrophic forgetting with hard attention to the task
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Task2vec: Task embedding for meta-learning
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Online continual learning with maximally interfered retrieval
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Continual lifelong learning with neural networks: A review
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Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Greg Slabaugh, and Tinne Tuytelaars · 2021
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Natural continual learning: success is a journey, not (just) a destination
Ta-Chu Kao, Kristopher Jensen, Gido van de Ven, Alberto Bernacchia, and Guillaume Hennequin · 2021
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Avalanche: an end-to-end library for continual learning
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido M van de Ven, et al · 2021
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Online class-incremental continual learning with adversarial shapley value
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Efficient feature transformations for discriminative and generative continual learning
Vinay Kumar Verma, Kevin J Liang, Nikhil Mehta, Piyush Rai, and Lawrence Carin · 2021
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Rehearsal revealed: The limits and merits of revisiting samples in continual learning
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Domain adaptive ensemble learning
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New insights on reducing abrupt representation change in online continual learning
Lucas Caccia, Rahaf Aljundi, Nader Asadi, Tinne Tuytelaars, Joelle Pineau, and Eugene Belilovsky · 2022
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Three types of incremental learning
Gido M van de Ven, Tinne Tuytelaars, and Andreas S Tolias · 2022
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