May 15, 2024, 4:43 a.m. | Jonas Weigand, Gerben I. Beintema, Jonas Ulmen, Daniel G\"orges, Roland T\'oth, Maarten Schoukens, Martin Ruskowski

cs.LG updates on arXiv.org arxiv.org

arXiv:2401.02902v2 Announce Type: replace-cross
Abstract: The importance of proper data normalization for deep neural networks is well known. However, in continuous-time state-space model estimation, it has been observed that improper normalization of either the hidden state or hidden state derivative of the model estimate, or even of the time interval can lead to numerical and optimization challenges with deep learning based methods. This results in a reduced model quality. In this contribution, we show that these three normalization tasks are …

abstract arxiv continuous cs.lg cs.sy data data normalization eess.sy hidden however importance interval networks neural networks normalization replace space state type

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