Abstract Catastrophic forgetting in neural networks is a common problem. in which neural networks lose information from previous tasks after training on new tasks. Although adopting a regularization method that preferentially retains the parameters important to the previous task to avoid catastrophic forgetting has a positive effect; existing regularization methods cause the gradient ... https://steedaes.shop/product-category/steam-kit/