Learning in deep neural networks and brains with similarity-weighted interleaved learning
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DOI: 10.1073/pnas.2115229119
Abstract: Significance Unlike humans, artificial neural networks rapidly forget previously learned information when learning something new and must be retrained by interleaving the new and old items; however, interleaving all old items is time-consuming and might… read more here.
Keywords: neural networks; similarity; old items; similarity weighted ... See more keywords