March 11, 2024, 4:42 a.m. | Aleksandr Dekhovich, O. Taylan Turan, Jiaxiang Yi, Miguel A. Bessa

cs.LG updates on arXiv.org arxiv.org

arXiv:2211.12971v2 Announce Type: replace-cross
Abstract: Data-driven modeling in mechanics is evolving rapidly based on recent machine learning advances, especially on artificial neural networks. As the field matures, new data and models created by different groups become available, opening possibilities for cooperative modeling. However, artificial neural networks suffer from catastrophic forgetting, i.e. they forget how to perform an old task when trained on a new one. This hinders cooperation because adapting an existing model for a new task affects the performance …

abstract advances artificial artificial neural networks arxiv become catastrophic forgetting cond-mat.mtrl-sci cs.lg cs.na data data-driven however machine machine learning math.na modeling networks neural networks type

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