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Physics-Guided Recurrent State-Space Neural Networks for Multi-Step Prediction
arXiv:2606.02278v1 Announce Type: new Abstract: State-space models are traditionally based on physical knowledge, but multi-step predictions from these physical models can be poor due to model inaccuracy. Black-box deep learning has shown promise as an alternative. However, these methods rely on the availability of large datasets and potentially available physical knowledge is neglected.