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Continual Learning addresses the challenge of learning a number of different tasks sequentially.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J. Cohen · 1989
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Connectionist models of recognition memory: constraints imposed by learning and forgetting functions
Roger Ratcliff · 1990
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Catastrophic forgetting in connectionist networks
Robert M French · 1999
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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Practical variational inference for neural networks
Alex Graves · 2011
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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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Revisiting natural gradient for deep networks
Razvan Pascanu and Yoshua Bengio · 2013
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Compete to compute
Rupesh K Srivastava, Jonathan Masci, Sohrob Kazerounian, Faustino Gomez, and Jürgen Schmidhuber · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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New insights and perspectives on the natural gradient method
James Martens · 2014
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Tensorflow: A system for large-scale machine learning
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al · 2016
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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
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Three factors influencing minima in sgd
Stanisław Jastrzębski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, and Amos Storkey · 2017
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Fearnet: Brain-inspired model for incremental learning
Ronald Kemker and Christopher Kanan · 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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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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Variational continual learning
Cuong V Nguyen, Yingzhen Li, Thang D Bui, and Richard E Turner · 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
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods
Laurence Aitchison · 2018
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Continual learning: A comparative study on how to defy forgetting in classification tasks
Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory Slabaugh, and Tinne Tuytelaars · 2019
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Continual learning via neural pruning
Siavash Golkar, Michael Kagan, and Kyunghyun Cho · 2019
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Limitations of the empirical fisher approximation
Frederik Kunstner, Lukas Balles, and Philipp Hennig · 2019
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Lca: Loss change allocation for neural network training
Janice Lan, Rosanne Liu, Hattie Zhou, and Jason Yosinski · 2019
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Learn to grow: A continual structure learning framework for overcoming catastrophic forgetting
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Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
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
Cited alongside, same era.
Towards robust evaluations of continual learning
Sebastian Farquhar and Yarin Gal · 2018
Cited alongside, same era.
Re-evaluating continual learning scenarios: A categorization and case for strong baselines
Yen-Chang Hsu, Yen-Cheng Liu, Anita Ramasamy, and Zsolt Kira · 2018
Cited alongside, same era.
Note on the quadratic penalties in elastic weight consolidation
Ferenc Huszár · 2018
Cited alongside, same era.
On the relation between the sharpest directions of dnn loss and the sgd step length
Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, and Amos Storkey · 2018
Cited alongside, same era.
Fast and scalable bayesian deep learning by weight-perturbation in adam
Mohammad Emtiyaz Khan, Didrik Nielsen, Voot Tangkaratt, Wu Lin, Yarin Gal, and Akash Srivastava · 2018
Cited alongside, same era.
Xilai Li, Yingbo Zhou, Tianfu Wu, Richard Socher, and Caiming Xiong · 2019
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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 · 2019
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Continual learning by asymmetric loss approximation with single-side overestimation
Dongmin Park, Seokil Hong, Bohyung Han, and Kyoung Mu Lee · 2019
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Improving and understanding variational continual learning
Siddharth Swaroop, Cuong V Nguyen, Thang D Bui, and Richard E Turner · 2019
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Three scenarios for continual learning
Gido M van de Ven and Andreas S Tolias · 2019
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Continual learning with hypernetworks
Johannes von Oswald, Christian Henning, João Sacramento, and Benjamin F Grewe · 2019
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Official keras cnn example
keras · 2020
Closest in time.
Continual learning with extended kronecker-factored approximate curvature
Janghyeon Lee, Hyeong Gwon Hong, Donggyu Joo, and Junmo Kim · 2020
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Generalized variational continual learning
Noel Loo, Siddharth Swaroop, and Richard E Turner · 2020
Closest in time.
Understanding the role of training regimes in continual learning, 2020
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, and Hassan Ghasemzadeh · 2020
Closest in time.
On the interplay between noise and curvature and its effect on optimization and generalization
Valentin Thomas, Fabian Pedregosa, Bart Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, and Nicolas Le Roux · 2020
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Sola: Continual learning with second-order loss approximation, 2020
Dong Yin, Mehrdad Farajtabar, and Ang Li · 2020
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