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pro vyhledávání: '"Anthes, Daniel"'
Unlike primates, training artificial neural networks on changing data distributions leads to a rapid decrease in performance on old tasks. This phenomenon is commonly referred to as catastrophic forgetting. In this paper, we investigate the represent
Externí odkaz:
http://arxiv.org/abs/2310.05644
Continual learning algorithms strive to acquire new knowledge while preserving prior information. Often, these algorithms emphasise stability and restrict network updates upon learning new tasks. In many cases, such restrictions come at a cost to the
Externí odkaz:
http://arxiv.org/abs/2310.04741