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Found 2 papers, 1 papers with code
Model-assisted deep learning of rare extreme events from partial observations
To predict rare extreme events using deep neural networks, one encounters the so-called small data problem because even long-term observations often contain few extreme events.
Data-driven prediction of multistable systems from sparse measurements
Our method predicts the asymptotic behavior of an observed state by quantifying its proximity to the states in a precomputed library of data.
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