HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations

no code implementations • 7 Oct 2023 • Mozes Jacobs, Bingni W. Brunton, Steven L. Brunton, J. Nathan Kutz, Ryan V. Raut

Taken together, HyperSINDy offers a promising framework for model discovery and uncertainty quantification in real-world systems, integrating sparse equation discovery methods with advances in statistical machine learning and deep generative modeling.

Model Discovery Uncertainty Quantification

Beyond expectations: Residual Dynamic Mode Decomposition and Variance for Stochastic Dynamical Systems

1 code implementation • 21 Aug 2023 • Matthew J. Colbrook, Qin Li, Ryan V. Raut, Alex Townsend

Finally, we present a suite of convergence results for the spectral information of stochastic Koopman operators.