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Abstract: Deep neural networks (DNNs) struggle to learn in dy-namic settings because they mainly rely on static datasets. Continual learning (CL) aims to overcome this limitation by enabling DNNs to ...

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Abstract: Class-incremental learning (CIL) aims to learn a family of classes incrementally with data available in order rather than training all data at once. One main drawback of CIL is that standard ...