The article discusses the challenge of catastrophic forgetting in training artificial neural networks, where a network forgets how to perform the original task after learning a new one. It introduces Elastic Weight Consolidation (EWC) as a method to address this issue. EWC is a promising approach that helps neural networks retain knowledge from previous tasks while learning new ones. This technique can improve the performance and stability of neural networks in sequential learning scenarios.
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Source link: https://towardsdatascience.com/continual-learning-a-deep-dive-into-elastic-weight-consolidation-loss-7cda4a2d058c
#Exploring Elastic Weight Consolidation Loss in Continual Learning #LearningContinuously
