data-driven-dynamics

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.