Curriculum learning for data-driven modeling of dynamical systems

no code implementations • 15 Dec 2021 • Alessandro Bucci, Onofrio Semeraro, Alexandre Allauzen, Sergio Chibbaro, Lionel Mathelin

Based on that, we consider entropy as a metric of complexity of the dataset; we show how an informed design of the training set based on the analysis of the entropy significantly improves the resulting models in terms of generalizability, and provide insights on the amount and the choice of data required for an effective data-driven modeling.

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