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Found 3 papers, 2 papers with code
Learning to Continually Learn with the Bayesian Principle
On the other hand, in the more classical literature of statistical machine learning, many models have sequential Bayesian update rules that yield the same learning outcome as the batch training, i. e., they are completely immune to catastrophic forgetting.
When Meta-Learning Meets Online and Continual Learning: A Survey
Over the past decade, deep neural networks have demonstrated significant success using the training scheme that involves mini-batch stochastic gradient descent on extensive datasets.
Recasting Continual Learning as Sequence Modeling
That is, we propose to formulate continual learning as a sequence modeling problem, allowing advanced sequence models to be utilized for continual learning.
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