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The ability of deep neural networks to continually learn and adapt to a sequence of tasks has remained challenging due to catastrophic forgetting of previously learned tasks.
Scalable and order-robust continual learning with additive parameter decomposition
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Lao, Q., Jiang, X., Havaei, M., and Bengio, Y. (2020) · 2003
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Coordinated memory replay in the visual cortex and hippocampus during sleep
Ji, D. and Wilson, M. A. (2007) · 2007
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Noise in the nervous system
Faisal, A. A., Selen, L. P., and Wolpert, D. M. (2008) · 2008
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Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L. (2009) · 2009
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Krizhevsky, A., Hinton, G., et al. (2009) · 2009
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An image is worth 16x16 words: Transformers for image recognition at scale
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al. (2020) · 2010
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Torchattacks: A pytorch repository for adversarial attacks
Kim, H. (2020) · 2010
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Class-incremental learning: survey and performance evaluation on image classification
Masana, M., Liu, X., Twardowski, B., Menta, M., Bagdanov, A. D., and van de Weijer, J. (2020) · 2010
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icarl: Incremental classifier and representation learning
Rebuffi, S.-A., Kolesnikov, A., Sperl, G., and Lampert, C. H. (2017) · 2010
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The benefits of noise in neural systems: bridging theory and experiment
McDonnell, M. D. and Ward, L. M. (2011) · 2011
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Noise as a resource for computation and learning in networks of spiking neurons
Maass, W. (2014) · 2014
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Distilling the knowledge in a neural network
Hinton, G., Vinyals, O., and Dean, J. (2015) · 2015
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Tiny imagenet visual recognition challenge
Le, Y. and Yang, X. (2015) · 2015
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What learning systems do intelligent agents need? complementary learning systems theory updated
Kumaran, D., Hassabis, D., and McClelland, J. L. (2016) · 2016
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Rusu, A. A., Rabinowitz, N. C., Desjardins, G., Soyer, H., Kirkpatrick, J., Kavukcuoglu, K., Pascanu, R., and Hadsell, R. (2016) · 2016
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Expert gate: Lifelong learning with a network of experts
Aljundi, R., Chakravarty, P., and Tuytelaars, T. (2017) · 2017
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Pathnet: Evolution channels gradient descent in super neural networks
Fernando, C., Banarse, D., Blundell, C., Zwols, Y., Ha, D., Rusu, A. A., Pritzel, A., and Wierstra, D. (2017) · 2017
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Neuroscience-inspired artificial intelligence
Hassabis, D., Kumaran, D., Summerfield, C., and Botvinick, M. (2017) · 2017
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Fearnet: Brain-inspired model for incremental learning
Kemker, R. and Kanan, C. (2017) · 2017
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Overcoming catastrophic forgetting in neural networks
Kirkpatrick, J., Pascanu, R., Rabinowitz, N., Veness, J., Desjardins, G., Rusu, A. A., Milan, K., Quan, J., Ramalho, T., Grabska-Barwinska, A., et al. (2017) · 2017
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Learning without forgetting
Li, Z. and Hoiem, D. (2017) · 2017
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Noise against noise: stochastic label noise helps combat inherent label noise
Chen, P., Chen, G., Ye, J., Heng, P.-A., et al. (2021) · 2021
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Convit: Improving vision transformers with soft convolutional inductive biases
d’Ascoli, S., Touvron, H., Leavitt, M. L., Morcos, A. S., Biroli, G., and Sagun, L. (2021) · 2021
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A continual learning survey: Defying forgetting in classification tasks
De Lange, M., Aljundi, R., Masana, M., Parisot, S., Jia, X., Leonardis, A., Slabaugh, G., and Tuytelaars, T. (2021) · 2021
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Continuum: Simple management of complex continual learning scenarios
Douillard, A. and Lesort, T. (2021) · 2021
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Dytox: Transformers for continual learning with dynamic token expansion
Douillard, A., Ramé, A., Couairon, G., and Cord, M. (2021) · 2021
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Gradient episodic memory for continual learning
Lopez-Paz, D. and Ranzato, M. (2017) · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I. (2017) · 2017
Cited alongside, same era.
Continual learning through synaptic intelligence
Zenke, F., Poole, B., and Ganguli, S. (2017) · 2017
Cited alongside, same era.
Riemannian walk for incremental learning: Understanding forgetting and intransigence
Chaudhry, A., Dokania, P. K., Ajanthan, T., and Torr, P. H. (2018) · 2018
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Towards robust evaluations of continual learning
Farquhar, S. and Gal, Y. (2018) · 2018
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Memory efficient experience replay for streaming learning
Hayes, T. L., Cahill, N. D., and Kanan, C. (2019) · 2019
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Learning a unified classifier incrementally via rebalancing
Hou, S., Pan, X., Loy, C. C., Wang, Z., and Lin, D. (2019) · 2019
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Remembering for the right reasons: Explanations reduce catastrophic forgetting
Ebrahimi, S., Petryk, S., Gokul, A., Gan, W., Gonzalez, J. E., Rohrbach, M., and Darrell, T. (2021) · 2021
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Overcoming long-term catastrophic forgetting through adversarial neural pruning and synaptic consolidation
Peng, J., Tang, B., Jiang, H., Li, Z., Lei, Y., Lin, T., and Li, H. (2021) · 2021
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Do vision transformers see like convolutional neural networks?
Raghu, M., Unterthiner, T., Kornblith, S., Zhang, C., and Dosovitskiy, A. (2021) · 2021
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Always be dreaming: A new approach for data-free class-incremental learning
Smith, J., Hsu, Y.-C., Balloch, J., Shen, Y., Jin, H., and Kira, Z. (2021) · 2021
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Training data-efficient image transformers & distillation through attention
Touvron, H., Cord, M., Douze, M., Massa, F., Sablayrolles, A., and Jégou, H. (2021) · 2021
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Improving vision transformers for incremental learning
Yu, P., Chen, Y., Jin, Y., and Liu, Z. (2021) · 2021
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Toward understanding the importance of noise in training neural networks
Zhou, M., Liu, T., Li, Y., Lin, D., Zhou, E., and Zhao, T. (2019) · 2021
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Consistency is the key to further mitigating catastrophic forgetting in continual learning
Bhat, P. S., Zonooz, B., and Arani, E. (2022) · 2022
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Continual learning with transformers for image classification
Ermis, B., Zappella, G., Wistuba, M., Rawal, A., and Archambeau, C. (2022) · 2022
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R-dfcil: Relation-guided representation learning for data-free class incremental learning
Gao, Q., Zhao, C., Ghanem, B., and Zhang, J. (2022) · 2022
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A comprehensive study of vision transformers on dense prediction tasks
Jeeveswaran., K., Kathiresan., S., Varma., A., Magdy., O., Zonooz., B., and Arani., E. (2022) · 2022
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Susceptibility of continual learning against adversarial attacks
Khan, H., Shah, P. M., Zaidi, S. F. A., et al. (2022) · 2022
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Biological underpinnings for lifelong learning machines
Kudithipudi, D., Aguilar-Simon, M., Babb, J., Bazhenov, M., Blackiston, D., Bongard, J., Brna, A. P., Chakravarthi Raja, S., Cheney, N., Clune, J., et al. (2022) · 2022
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Robust training under label noise by over-parameterization
Liu, S., Zhu, Z., Qu, Q., and You, C. (2022) · 2022
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Online continual learning in image classification: An empirical survey
Mai, Z., Li, R., Jeong, J., Quispe, D., Kim, H., and Sanner, S. (2022) · 2022
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Towards exemplar-free continual learning in vision transformers: an account of attention, functional and weight regularization
Pelosin, F., Jha, S., Torsello, A., Raducanu, B., and van de Weijer, J. (2022) · 2022
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Synergy between synaptic consolidation and experience replay for general continual learning
Sarfraz, F., Arani, E., and Zonooz, B. (2022) · 2022
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Task-aware information routing from common representation space in lifelong learning
Bhat, P. S., Zonooz, B., and Arani, E. (2023) · 2023
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