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Automated data-driven modeling, the process of directly discovering the governing equations of a dynamical system from data, ... This video discusses data requirements for the Sparse Identification of Nonlinear Dynamics (SINDy) Speaker: Kadierdan Kaheman Event: Second Symposium on Machine Learning and Dynamical Systems ... Discovering Interpretable Dynamics by Sparsity Promotion on Energy and the Lagrangian, IEEE Robotics and Automation Letters, ... Video abstract on methods to extract differential equations from data and our software SEED (a Python wrapper to Mathematical Modeling at Queens College, Spring 2021. We're following the textbook Modeling and Simulation in Python by ...
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PySINDy tutorial 3: robust sparse system identification
PySINDy tutorial 4: robust sparse system identification by ensembling
PySINDy tutorial 6: the weak formulation of SINDy and SINDy-PI
PySINDy tutorial 7: identifying partial differential equations (PDEs) and choosing a regularization
PySINDy: A Python Library for Model Discovery
Sparse Nonlinear Dynamics Models with SINDy, Part 2: Training Data & Disambiguating Models
SINDy-PI: A Robust Algorithym for Parallel Implicit Sparse Identification of Nonlinear Dynamics
[ICRA2020] Discovering Interpretable Dynamics by Sparsity Promotion on Energy and the Lagrangian
DeepSense Discovery ~ Choosing the right algorithm
SEED -Software for the Extraction of Equations from Data
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Last Updated: June 7, 2026
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