NVAR models exhibit training error scaling laws tied to feature library representation of Lie-series coefficients, with delays reducing one-step error but aiding long-horizon forecasts only under sufficient nonlinearity.
Weak SINDy: Galerkin-Based Data-Driven Model Selection
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A data-driven stochastic differential equation for tropical cyclone intensification is inferred from IBTrACS and ERA5 data, producing synthetic storms whose statistics and nonlinear dynamics match observations and a leading physics-based model.
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Flow map learning in nonlinear vector autoregressive models: influence of the feature-library structure on the training error
NVAR models exhibit training error scaling laws tied to feature library representation of Lie-series coefficients, with delays reducing one-step error but aiding long-horizon forecasts only under sufficient nonlinearity.
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Learning a Stochastic Differential Equation Model of Tropical Cyclone Intensification from Reanalysis and Observational Data
A data-driven stochastic differential equation for tropical cyclone intensification is inferred from IBTrACS and ERA5 data, producing synthetic storms whose statistics and nonlinear dynamics match observations and a leading physics-based model.