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A multifidelity approach to continual learning for physical systems

We introduce a novel continual learning method based on multifidelity deep neural networks. This method learns the correlation between the output of previously trained models and the desired output of the model on the current training dataset, limiting catastrophic forgetting. On its own the multifi...

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Váldodahkkit: Amanda Howard, Yucheng Fu, Panos Stinis
Materiálatiipa: Artigo
Giella:Inglês
Almmustuhtton: IOP Publishing 2024-01-01
Ráidu:Machine Learning: Science and Technology
Fáttát:
Liŋkkat:https://doi.org/10.1088/2632-2153/ad45b2
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