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.
Kolmogorov-Arnold Networks for Dynamics (KANDy) to learn governing equations from dynamical systems.
Bridging infinite-dimensional delay dynamics with fully GPU-accelerated finite-dimensional Koopman learning and provable error bounds for nonlinear delay-differential equations.
An Incremental Approach to Online Dynamic Mode Decomposition for Time-Varying Systems with Applications to EEG Data Modeling
Java Dynamic Mode Decomposition
🏎️ Model and simulate vehicle suspension dynamics using Python and Laplace Transforms for accurate analysis of second-order LTI systems.
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