[28] Timothee Lesort, Andrei Stoian, and David Filliat. "Regularization shortcomings for continual learning". In: arXiv preprint arXiv:1912.03049 (2019).
[29] Penelope A Lewis and Simon J Durrant. "The role of active forgetting in learning and memory". In: Frontiers in psychology 9 (2018), p. 1314.
[30] Zhizhong Li and Derek Hoiem. "Learning without forgetting". In: IEEE transactions on pattern analysis and machine intelligence 40.12 (2017), pp. 2935-2947.
[31] He Liu et al. "Forgetting generates a novel state that is reactivatable". In: Science advances 8.6 (2022), eabi9071.
[32] Arun Mallya and Svetlana Lazebnik. "Packet: Adding multiple tasks to a single network by iterative pruning". In: Proceedings of the IEEE conference on Computer Vision and Pattern Recognition. 2018, pp. 7765-7773.
[33] Eve Marder and Vatsala Thirumalai. "Cellular, synaptic and network effects of neuromodulation". In: Neural Networks 15.4-6 (2002), pp. 479-493.
[34] Nicolas Y Masse, Gregory D Grant, and David J Freedman. "Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization". In: Proceedings of the National Academy of Sciences 115.44 (2018), E10467-E10475.
[35] Michael McCloskey and Neal J Cohen. "Catastrophic interference in connectionist networks: The sequential learning problem". In: Psychology of learning and motivation. Vol. 24. Elsevier, 1989, pp. 109-165.
[36] Martial Mermillod, Aurélia Bugaiska, and Patrick Bonin. The stability-plasticity dilemma: Investigating the continuum from catastrophic forgetting to age-limited learning effects. 2013.
[37] Vernon B Mountcastle. “The columnar organization of the neocortex”. In: Brain 80.2 (1957), pp. 214–241.
[38] German I Parisi et al. “Continual lifelong learning with neural networks: A review”. In: Neural Networks 113 (2019), pp. 54–71.
[39] Gyeong-Moon Park, Sahng-Min Yoo, and Jong-Hwan Kim. "Convolutional neural network with developmental memory for continual learning". In: IEEE Transactions on Neural Networks and Learning Systems 32.6 (2020), pp. 2691-2705.
[40] Björn Rasch and Jan Born. “Maintaining memories by reactivation”. In: Current Opinion in Neurobiology 17.6 (2007). Motor systems / Neurobiology of behaviour, pp. 698–703. ISSN: 0959-4388.
[41] Roger Ratcliff. "Connectionist models of recognition memory: constraints imposed by learning and forgetting functions." In: Psychological review 97.2 (1990), p. 285.
[42] Anthony Robins. "Catastrophic forgetting, rehearsal and pseudorehearsal". In: Connection Science 7.2 (1995), pp. 123-146.
[43] Andrei A. Rusu et al. Progressive Neural Networks. 2016.
[44] Fahad Sarfraz, Elahe Arani, and Bahram Zonooz. "Synergy between synaptic consolidation and experience replay for general continual learning". In: Conference on Lifelong Learning Agents. PMLR. 2022, pp. 920-936.
[45] Jonathan Schwarz et al. "Progress & compress: A scalable framework for continual learning". In: International Conference on Machine Learning. PMLR. 2018, pp. 4528-4537.
[46] Tracey J Shors et al. "Use it or lose it: how neurogenesis keeps the brain fit for learning". In: Behavioural brain research 227.2 (2012), pp. 450-458.
[47] Norman E Spear. “Retrieval of memory in animals.” In: Psychological Review 80.3 (1973), p. 163.
[48] Benjamin C Storm and Elizabeth L Bjork. "Active forgetting of episodic memories: Is it time to rethink the 'retrieval failure' theory of forgetting?" In: British Journal of Psychology 110.3 (2019), pp. 549-571.
[49] Rishabh Tiwari et al. "GCR: Gradient Coreset Based Replay Buffer Selection For Continual Learning". In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022, pp. 99-108.
[50] Jane X Wang et al. “Neural modularity helps organisms evolve to learn new skills without forgetting old skills”. In: PLoS computational biology 13.2 (2017), e1005354.
[51] Fu-Yun Wang et al. "Foster: Feature boosting and compression for class-incremental learning". In: European conference on computer vision. Springer. 2022, pp. 398-414.