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Overcoming catastrophic forgetting in neural networks

James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness et al. • Proceedings of the National Academy of Sciences (2017)

The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitabl...

OPENALEX Open Access DOI: https://doi.org/10.1073/pnas.1611835114 PMC: 5380101

CL-BPUWM: continuous learning with Bayesian parameter updating and weight memory

Yao He, Jing Yang, Shaobo Li, Jianjun Hu et al. • Complex & Intelligent Systems (2024)

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 pa...

DOAJ Open Access (DOAJ) DOI: 10.1007/s40747-024-01350-1