Code for "SINDy-RL for Interpretable and Efficient Model-Based Reinforcement Learning" by Zolman et al.
AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
a collection of modern sparse (regularized) linear regression algorithms.
Physically-informed model discovery of systems with nonlinear, rational terms using the SINDy-PI method. Contains functionality for spectral filtering/differentiation.
MEDIDA: Model Error Discovery with Interpretability and Data Assimilation
Building SINDy model from scratch
Final projects for 401-4656-21L AI in Sciences and Engineering @ ETHz. Includes implementation of Fourier Neural Operator (FNO) with time dependency, data-driven symbolic regression with PDE-Find and foundation model based on FNO for phase-field dynamics
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