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Triple Memory Networks: a Brain-Inspired Method for Continual Learning
[article]
2020
arXiv
pre-print
Continual acquisition of novel experience without interfering previously learned knowledge, i.e. continual learning, is critical for artificial neural networks, but limited by catastrophic forgetting. A neural network adjusts its parameters when learning a new task, but then fails to conduct the old tasks well. By contrast, the brain has a powerful ability to continually learn new experience without catastrophic interference. The underlying neural mechanisms possibly attribute to the interplay
arXiv:2003.03143v1
fatcat:eoiv3imfcrejrfvdbr3m5l4cxa