Bibliography Classified by Keywords

Outline

Rehearsal

PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning, (2020) [paper] [bib] by Douillard, Arthur, Cord, Matthieu, Ollion, Charles, Robert, Thomas and Valle, Eduardo
Efficient Lifelong Learning with A-GEM, (2019) [paper] [bib] by Chaudhry, Arslan, Ranzato, Marc’Aurelio, Rohrbach, Marcus and Elhoseiny, Mohamed
Orthogonal Gradient Descent for Continual Learning, (2019) [paper] [bib] by Mehrdad Farajtabar, Navid Azizan, Alex Mott and Ang Li
Gradient based sample selection for online continual learning, (2019) [paper] [bib] by Aljundi, Rahaf, Lin, Min, Goujaud, Baptiste and Bengio, Yoshua
Online Continual Learning with Maximal Interfered Retrieval, (2019) [paper] [bib] by Aljundi, Rahaf, Caccia, Lucas, Belilovsky, Eugene, Caccia, Massimo, Lin, Min, Charlin, Laurent and Tuytelaars, Tinne
Online Learned Continual Compression with Adaptative Quantization Module, (2019) [paper] [bib] by Caccia, Lucas, Belilovsky, Eugene, Caccia, Massimo and Pineau, Joelle
Experience replay for continual learning, (2019) [paper] [bib] by Rolnick, David, Ahuja, Arun, Schwarz, Jonathan, Lillicrap, Timothy and Wayne, Gregory
Gradient Episodic Memory for Continual Learning, (2017) [paper] [bib] by Lopez-Paz, David and Ranzato, Marc-Aurelio
icarl: Incremental classifier and representation learning, (2017) [paper] [bib] by Rebuffi, Sylvestre-Alvise, Kolesnikov, Alexander, Sperl, Georg and Lampert, Christoph H

Generative Replay

Brain-Like Replay For Continual Learning With Artificial Neural Networks, (2020) [paper] [bib] by van de Ven, Gido M, Siegelmann, Hava T and Tolias, Andreas S
Learning to remember: A synaptic plasticity driven framework for continual learning, (2019) [paper] [bib] by Ostapenko, Oleksiy, Puscas, Mihai, Klein, Tassilo, Jahnichen, Patrick and Nabi, Moin
Generative Models from the perspective of Continual Learning, (2019) [paper] [bib] by Lesort, Timoth{'e}e, Caselles-Dupr{'e}, Hugo, Garcia-Ortiz, Michael, Goudou, Jean-Fran{\c c}ois and Filliat, David
Marginal replay vs conditional replay for continual learning, (2019) [paper] [bib] by Lesort, Timoth{'e}e, Gepperth, Alexander, Stoian, Andrei and Filliat, David
Generative replay with feedback connections as a general strategy for continual learning, (2018) [paper] [bib] by Michiel van der Ven and Andreas S. Tolias
Continual learning with deep generative replay, (2017) [paper] [bib] by Shin, Hanul, Lee, Jung Kwon, Kim, Jaehong and Kim, Jiwon

Dynamic Architecture

ORACLE: Order Robust Adaptive Continual Learning, (2019) [paper] [bib] by Jaehong Yoon and Saehoon Kim and Eunho Yang and Sung Ju Hwang
Random Path Selection for Incremental Learning, (2019) [paper] [bib] by Jathushan Rajasegaran and Munawar Hayat and Salman H. Khan and Fahad Shahbaz Khan and Ling Shao
Incremental Learning through Deep Adaptation, (2018) [paper] [bib] by Amir Rosenfeld and John K. Tsotsos
Continual Learning in Practice, (2018) [paper] [bib] by Diethe, Tom, Borchert, Tom, Thereska, Eno, Pigem, Borja de Balle and Lawrence, Neil
Progressive Neural Networks, (2016) [paper] [bib] by {Rusu}, A.~A., {Rabinowitz}, N.~C., {Desjardins}, G., {Soyer}, H., {Kirkpatrick}, J., {Kavukcuoglu}, K., {Pascanu}, R. and {Hadsell}, R.

Regularization

Continual Learning with Bayesian Neural Networks for Non-Stationary Data, (2020) [paper] [bib] by Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt and Stephan Günnemann
Improving and Understanding Variational Continual Learning, (2019) [paper] [bib] by Siddharth Swaroop, Cuong V. Nguyen, Thang D. Bui and Richard E. Turner
Uncertainty-based Continual Learning with Adaptive Regularization, (2019) [paper] [bib] by Ahn, Hongjoon, Cha, Sungmin, Lee, Donggyu and Moon, Taesup
Functional Regularisation for Continual Learning with Gaussian Processes, (2019) [paper] [bib] by Titsias, Michalis K, Schwarz, Jonathan, Matthews, Alexander G de G, Pascanu, Razvan and Teh, Yee Whye
Task Agnostic Continual Learning Using Online Variational Bayes, (2018) [paper] [bib] by Chen Zeno, Itay Golan, Elad Hoffer and Daniel Soudry
Overcoming Catastrophic Interference using Conceptor-Aided Backpropagation, (2018) [paper] [bib] by Xu He and Herbert Jaeger
Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence, (2018) [paper] [bib] by Chaudhry, Arslan, Dokania, Puneet K, Ajanthan, Thalaiyasingam and Torr, Philip HS
Variational Continual Learning, (2018) [paper] [bib] by Cuong V. Nguyen, Yingzhen Li, Thang D. Bui and Richard E. Turner
Progress \& compress: A scalable framework for continual learning, (2018) [paper] [bib] by Schwarz, Jonathan, Luketina, Jelena, Czarnecki, Wojciech M, Grabska-Barwinska, Agnieszka, Teh, Yee Whye, Pascanu, Razvan and Hadsell, Raia
Facilitating Bayesian Continual Learning by Natural Gradients and Stein Gradients, (2018) [paper] [bib] by Chen, Yu, Diethe, Tom and Lawrence, Neil
Overcoming catastrophic forgetting in neural networks, (2017) [paper] [bib] by Kirkpatrick, James, Pascanu, Razvan, Rabinowitz, Neil, Veness, Joel, Desjardins, Guillaume, Rusu, Andrei A, Milan, Kieran, Quan, John, Ramalho, Tiago, Grabska-Barwinska, Agnieszka and others
Memory Aware Synapses: Learning what (not) to forget, (2017) [paper] [bib] by Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach and Tinne Tuytelaars
Continual Learning Through Synaptic Intelligence, (2017) [paper] [bib] by *Zenke, Friedeman, Poole, Ben and Ganguli, Surya *

Meta-Learning

La-MAML: Look-ahead Meta Learning for Continual Learning, (2020) [paper] [bib] by Gunshi Gupta, Karmesh Yadav and Liam Paull
Learning to Continually Learn, (2020) [paper] [bib] by Beaulieu, Shawn, Frati, Lapo, Miconi, Thomas, Lehman, Joel, Stanley, Kenneth O, Clune, Jeff and Cheney, Nick
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning, (2020) [paper] [bib] by Caccia, Massimo, Rodriguez, Pau, Ostapenko, Oleksiy, Normandin, Fabrice, Lin, Min, Caccia, Lucas, Laradji, Issam, Rish, Irina, Lacoste, Alexandre, Vazquez, David and others
Meta-Learning Representations for Continual Learning, (2019) [paper] [bib] by Javed, Khurram and White, Martha
Learning from the Past: Continual Meta-Learning via Bayesian Graph Modeling, (2019) [paper] [bib] by Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Mahsa Baktashmotlagh and Yang Yang
Online Meta-Learning, (2019) [paper] [bib] by Finn, Chelsea, Rajeswaran, Aravind, Kakade, Sham and Levine, Sergey
Reconciling meta-learning and continual learning with online mixtures of tasks, (2019) [paper] [bib] by Jerfel, Ghassen, Grant, Erin, Griffiths, Tom and Heller, Katherine A
Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL, (2019) [paper] [bib] by Anusha Nagabandi, Chelsea Finn and Sergey Levine
Task Agnostic Continual Learning via Meta Learning, (2019) [paper] [bib] by Xu He, Jakub Sygnowski, Alexandre Galashov, Andrei A. Rusu, Yee Whye Teh and Razvan Pascanu
Meta-learnt priors slow down catastrophic forgetting in neural networks, (2019) [paper] [bib] by Spigler, Giacomo
Learning to learn without forgetting by maximizing transfer and minimizing interference, (2018) [paper] [bib] by Riemer, Matthew, Cases, Ignacio, Ajemian, Robert, Liu, Miao, Rish, Irina, Tu, Yuhai and Tesauro, Gerald

Replay

Brain-Like Replay For Continual Learning With Artificial Neural Networks, (2020) [paper] [bib] by van de Ven, Gido M, Siegelmann, Hava T and Tolias, Andreas S
Learning to remember: A synaptic plasticity driven framework for continual learning, (2019) [paper] [bib] by Ostapenko, Oleksiy, Puscas, Mihai, Klein, Tassilo, Jahnichen, Patrick and Nabi, Moin
Generative Models from the perspective of Continual Learning, (2019) [paper] [bib] by Lesort, Timoth{'e}e, Caselles-Dupr{'e}, Hugo, Garcia-Ortiz, Michael, Goudou, Jean-Fran{\c c}ois and Filliat, David
Marginal replay vs conditional replay for continual learning, (2019) [paper] [bib] by Lesort, Timoth{'e}e, Gepperth, Alexander, Stoian, Andrei and Filliat, David
Generative replay with feedback connections as a general strategy for continual learning, (2018) [paper] [bib] by Michiel van der Ven and Andreas S. Tolias
Continual learning with deep generative replay, (2017) [paper] [bib] by Shin, Hanul, Lee, Jung Kwon, Kim, Jaehong and Kim, Jiwon