WKRR combines weak-form filtering with kernel ridge regression to learn dynamical systems from noisy data and outperforms baselines on chaotic systems up to 64D and 15kD fluid data.
arXiv preprint arXiv:2409.06751 , year=
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Fourier Weak SINDy learns ODE coefficients from noisy time series by regressing Fourier coefficients that are selected via multitaper spectral density estimation, beating SINDy baselines on chaotic benchmarks.
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Learning dynamical systems from noisy data with Weak-form Kernel Ridge Regression
WKRR combines weak-form filtering with kernel ridge regression to learn dynamical systems from noisy data and outperforms baselines on chaotic systems up to 64D and 15kD fluid data.
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Fourier Weak SINDy: Spectral Test Function Selection for Robust Model Identification
Fourier Weak SINDy learns ODE coefficients from noisy time series by regressing Fourier coefficients that are selected via multitaper spectral density estimation, beating SINDy baselines on chaotic benchmarks.